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Articles by Bruce Fischl in JoVE

 JoVE Clinical and Translational Medicine

How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index


JoVE 3417 1/02/2012

1Department of Psychiatry, University of Geneva School of Medicine, 2Signal Processing Laboratory, École Polytechnique Fédérale de Lausanne, 3Department of Radiology, University Hospital Center and University of Lausanne, 4Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital

Measuring gyrification (cortical folding) at any age represents a window into early brain development. Hence, we previously developed an algorithm to measure local gyrification at thousands of points over the hemisphere1. In this paper, we detail the computation of this local gyrification index.

Other articles by Bruce Fischl on PubMed

The Local Structure of Space-variant Images

Local image structure is widely used in theories of both machine and biological vision. The form of the differential operators describing this structure for space-invariant images has been well documented. Although space-variant coordinates are universally used in mammalian visual systems, the form of the operators in the space-variant coordinate system has received little attention. In this report we derive the form of the most common differential operators and surface characteristics in the space-variant domain and show examples of their use. The operators include the Laplacian, the gradient and the divergence, as well as the fundamental forms of the image treated as a surface. We illustrate the use of these results by deriving the space-variant form of corner detection and image enhancement algorithms. The latter is shown to have interesting properties in the complex log domain, implicitly encoding a variable grid-size integration of the underlying PDE, allowing rapid enhancement of large scale peripheral features while preserving high spatial frequencies in the fovea. Copyright 1997 Elsevier Science Ltd.

Whole Brain Segmentation: Automated Labeling of Neuroanatomical Structures in the Human Brain

We present a technique for automatically assigning a neuroanatomical label to each voxel in an MRI volume based on probabilistic information automatically estimated from a manually labeled training set. In contrast to existing segmentation procedures that only label a small number of tissue classes, the current method assigns one of 37 labels to each voxel, including left and right caudate, putamen, pallidum, thalamus, lateral ventricles, hippocampus, and amygdala. The classification technique employs a registration procedure that is robust to anatomical variability, including the ventricular enlargement typically associated with neurological diseases and aging. The technique is shown to be comparable in accuracy to manual labeling, and of sufficient sensitivity to robustly detect changes in the volume of noncortical structures that presage the onset of probable Alzheimer's disease.

Human Cerebellum: Surface-assisted Cortical Parcellation and Volumetry with Magnetic Resonance Imaging

We describe a system of surface-assisted parcellation (SAP) of the human cerebellar cortex derived from neural systems functional and behavioral anatomy. This system is based on MRI and preserves the unique morphologic and topographic features of the individual cerebellum. All major fissures of the cerebellum were identified and traced in the flattened representation of the cerebellar cortex using the program "FreeSurfer." Parcellation of the cerebellar cortex followed using the fissure information in conjunction with landmarks using the program "Cardviews" to create 64 gyral-based cerebellar parcellation units. Computer-assisted algorithms enable the execution of the cerebellar parcellation procedure as well as volumetric measurements and topographic localization. The SAP technique makes it possible to represent multimodal structural and functional imaging data on the flattened surface of the cerebellar cortex as illustrated in one functional MRI experiment.

Focal Thinning of the Cerebral Cortex in Multiple Sclerosis

Brain atrophy as determined by quantitative MRI can be used to characterize disease progression in multiple sclerosis. Many studies have addressed white matter (WM) alterations leading to atrophy, while changes of the cerebral cortex have been studied to a lesser extent. In vivo, the cerebral cortex has been difficult to study due to its complex structure and regional variability. Measurement of cerebral cortex thickness at different disease stages may provide new insights into grey matter (GM) pathology. In the present investigation, we evaluated in vivo cortical thickness and its relationship to disability, disease duration, WM T2 hyper-intense and T1 hypo-intense lesion volumes. High-resolution MRI brain scans were obtained in 20 patients with clinically definite multiple sclerosis and 15 age-matched normal subjects. A novel method of automated surface reconstruction yielded measurements of the cortical thickness for each subject's entire brain and computed cross-subject statistics based on the cortical anatomy. Statistical thickness difference maps were generated by performing t-tests between patient and control groups and individual thickness measures were submitted to analyses of variance to investigate the relationship between cortical thickness and clinical variables. The mean overall thickness of the cortical ribbon was reduced in multiple sclerosis patients compared with controls [2.30 mm (SD 0.14) versus 2.48 mm (SD 0.11)], showing a significant main effect of group (controls versus patients). In patients, we found significant main effects for disability, disease duration, T2 and T1 lesion volumes. The visualization of statistical difference maps of the cortical GM thickness on inflated brains across the cortical surface revealed a distinct distribution of significant focal thinning of the cerebral cortex in addition to the diffuse cortical atrophy. Focal cortical thinning in frontal [2.37 mm (SD 0.17) versus 2.73 mm (SD 0.25)] and in temporal [2.65 mm (SD 0.15) versus 2.95 mm (SD 0.11)] brain regions was observed, even early in the course of the disease or in patients with mild disability. Patients with longstanding disease or severe disability, however, presented additionally with focal thinning of the motor cortex area [2.35 mm (SD 0.19) versus 2.74 mm (SD 0.15)]. We conclude that in vivo measurement of cortical thickness is feasible in patients suffering from multiple sclerosis. The data provide new insight into the cortical pathology in multiple sclerosis patients, revealing focal cortical thinning beside an overall reduction of the cortical thickness with disease progression.

Regionally Localized Thinning of the Cerebral Cortex in Schizophrenia

Schizophrenia is characterized by small reductions in cortical gray matter volume, particularly in the temporal and prefrontal cortices. The question of whether cortical thickness is reduced in schizophrenia has not been addressed using magnetic resonance imaging (MRI) techniques. Our objectives were to test the hypothesis that cortical thinning in patients with schizophrenia (relative to control subjects) is greater in temporal and prefrontal regions of interest (ROIs) than in control ROIs (superior parietal, calcarine, postcentral, central, and precentral cortices), and to obtain an unbiased estimate of the distribution of cortical thinning in patients (relative to controls) by constructing mean and statistical cortical thickness difference maps.

Permutation Tests for Classification: Towards Statistical Significance in Image-based Studies

Estimating statistical significance of detected differences between two groups of medical scans is a challenging problem due to the high dimensionality of the data and the relatively small number of training examples. In this paper, we demonstrate a non-parametric technique for estimation of statistical significance in the context of discriminative analysis (i.e., training a classifier function to label new examples into one of two groups). Our approach adopts permutation tests, first developed in classical statistics for hypothesis testing, to estimate how likely we are to obtain the observed classification performance, as measured by testing on a hold-out set or cross-validation, by chance. We demonstrate the method on examples of both structural and functional neuroimaging studies.

Sequence-independent Segmentation of Magnetic Resonance Images

We present a set of techniques for embedding the physics of the imaging process that generates a class of magnetic resonance images (MRIs) into a segmentation or registration algorithm. This results in substantial invariance to acquisition parameters, as the effect of these parameters on the contrast properties of various brain structures is explicitly modeled in the segmentation. In addition, the integration of image acquisition with tissue classification allows the derivation of sequences that are optimal for segmentation purposes. Another benefit of these procedures is the generation of probabilistic models of the intrinsic tissue parameters that cause MR contrast (e.g., T1, proton density, T2*), allowing access to these physiologically relevant parameters that may change with disease or demographic, resulting in nonmorphometric alterations in MR images that are otherwise difficult to detect. Finally, we also present a high band width multiecho FLASH pulse sequence that results in high signal-to-noise ratio with minimal image distortion due to B0 effects. This sequence has the added benefit of allowing the explicit estimation of T2* and of reducing test-retest intensity variability.

Automatically Parcellating the Human Cerebral Cortex

We present a technique for automatically assigning a neuroanatomical label to each location on a cortical surface model based on probabilistic information estimated from a manually labeled training set. This procedure incorporates both geometric information derived from the cortical model, and neuroanatomical convention, as found in the training set. The result is a complete labeling of cortical sulci and gyri. Examples are given from two different training sets generated using different neuroanatomical conventions, illustrating the flexibility of the algorithm. The technique is shown to be comparable in accuracy to manual labeling.

Thinning of the Cerebral Cortex in Aging

The thickness of the cerebral cortex was measured in 106 non-demented participants ranging in age from 18 to 93 years. For each participant, multiple acquisitions of structural T1-weighted magnetic resonance imaging (MRI) scans were averaged to yield high-resolution, high-contrast data sets. Cortical thickness was estimated as the distance between the gray/white boundary and the outer cortical surface, resulting in a continuous estimate across the cortical mantle. Global thinning was apparent by middle age. Men and women showed a similar degree of global thinning, and did not differ in mean thickness in the younger or older groups. Age-associated differences were widespread but demonstrated a patchwork of regional atrophy and sparing. Examination of subsets of the data from independent samples produced highly similar age-associated patterns of atrophy, suggesting that the specific anatomic patterns within the maps were reliable. Certain results, including prominent atrophy of prefrontal cortex and relative sparing of temporal and parahippocampal cortex, converged with previous findings. Other results were unexpected, such as the finding of prominent atrophy in frontal cortex near primary motor cortex and calcarine cortex near primary visual cortex. These findings demonstrate that cortical thinning occurs by middle age and spans widespread cortical regions that include primary as well as association cortex.

A Magnetic Resonance Imaging Study of Cortical Thickness in Animal Phobia

Despite the high prevalence of specific phobia (SP), its neural substrates remain undetermined. Although an initial series of functional neuroimaging studies have implicated paralimbic and sensory cortical regions in the pathophysiology of SP, to date contemporary morphometric neuroimaging methods have not been applied to test specific hypotheses regarding structural abnormalities.

Aids to Telemetry in the Presurgical Evaluation of Epilepsy Patients: MRI, MEG and Other Non-invasive Imaging Techniques

Effects of Age on Volumes of Cortex, White Matter and Subcortical Structures

The effect of age was investigated in and compared across 16 automatically segmented brain measures: cortical gray matter, cerebral white matter, hippocampus, amygdala, thalamus, the accumbens area, caudate, putamen, pallidum, brainstem, cerebellar cortex, cerebellar white matter, the lateral ventricle, the inferior lateral ventricle, and the 3rd and 4th ventricle. Significant age effects were found for all volumes except pallidum and the 4th ventricle. Heterogeneous age responses were seen in that age relationships for cortex, amygdala, thalamus, the accumbens area, and caudate were linear, while cerebral white matter, hippocampus, brainstem, cerebellar white, and gray matter, as well as volume of the lateral, inferior lateral, and 3rd ventricles showed curvilinear relationships with age. In general, the findings point to global and large effects of age across brain volumes.

Thickness of Ventromedial Prefrontal Cortex in Humans is Correlated with Extinction Memory

The ventromedial prefrontal cortex (vmPFC) has been implicated in fear extinction [Phelps, E. A., Delgado, M. R., Nearing, K. I. & Ledoux, J. E. (2004) Neuron 43, 897-905; Herry, C. & Garcia, R. (2003) Behav. Brain Res. 146, 89-96]. Here, we test the hypothesis that the cortical thickness of vmPFC regions is associated with how well healthy humans retain their extinction memory a day after having been conditioned and then extinguished. Fourteen participants underwent a 2-day fear conditioning and extinction protocol. The conditioned stimuli (CSs) were pictures of virtual lights, and the unconditioned stimulus (US) was an electric shock. On day 1, participants received 5 CS+US pairings (conditioning), followed by 10 CS trials with no US (extinction). On day 2, the CS was presented alone to test for extinction memory. Skin conductance response (SCR) was the behavioral index of conditioning and extinction. Participants underwent MRI scans to obtain structural images, from which cortical thickness was measured. We performed a vertex-based analysis across the entire cortical surface and a region-of-interest analysis of a priori hypothesized territories to measure cortical thickness and map correlations between this measure and SCR. We found significant, direct correlation between thickness of the vmPFC, specifically medial orbitofrontal cortex, and extinction retention. That is, thicker medial orbitofrontal cortex was associated with lower SCR to the conditioned stimulus during extinction recall (i.e., greater extinction memory). These results suggest that the size of the vmPFC might explain individual differences in the ability to modulate fear among humans.

Age Does Not Increase Rate of Forgetting over Weeks--neuroanatomical Volumes and Visual Memory Across the Adult Life-span

The aim of the study was to investigate whether age affects visual memory retention across extended time intervals. In addition, we wanted to study how memory capabilities across different time intervals are related to the volume of different neuroanatomical structures (right hippocampus, right cortex, right white matter). One test of recognition (CVMT) and one test of recall (Rey-Osterrieth Complex Figure Test) were administered, giving measures of immediate recognition/recall, 20-30 min recognition/recall, and recognition/recall at a mean of 75 days. Volumetric measures of right hemisphere hippocampus, cortex, and white matter were obtained through an automated labelling procedure of MRI recordings. Results did not demonstrate a steeper rate of forgetting for older participants when the retention intervals were increased, indicating that older people have spared ability to retain information in the long-term store. Differences in neuroanatomical volumes could explain up to 36% of the variance in memory performance, but were not significantly related to rates of forgetting. Cortical volume and hippocampal volume were in some cases independent as predictors of memory function. Generally, cortical volume was a better predictor of recognition memory than hippocampal volume, while the 2 structures did not differ in their predictive power of recall abilities. While neuroanatomical volumetric differences can explain some of the differences in memory functioning between younger and older persons, the hippocampus does not seem to be unique in this respect.

Differing Neuropsychological and Neuroanatomical Correlates of Abnormal Reading in Early-stage Semantic Dementia and Dementia of the Alzheimer Type

Individuals with semantic dementia (SD) were differentiated neuropsychologically from individuals with dementia of the Alzheimer type (DAT) at very mild-to-mild stages (clinical dementia rating 0.5 or 1). A picture naming and recognition memory experiment provided a particularly useful probe for early identification, with SD individuals showing preserved picture recognition memory and impaired naming, and DAT individuals tending to show the reverse dissociation. The identification of an early SD group provided the opportunity to inform models of reading by exploring the influence of isolated lexical semantic impairment on reading regular words. Results demonstrated prolonged latency in both SD and DAT group reading compared to a control group but exaggerated influence of frequency and length only for the SD group. The SD reading pattern was associated with focal atrophy of the left temporal pole. These cognitive-neuroanatomical findings suggest a role for the left temporal pole in lexical/semantic components of reading and demonstrate that cortical thickness differences in the left temporal pole correlate with prolonged latency associated with increased reliance on sublexical components of reading.

Cortical Volume and Speed-of-processing Are Complementary in Prediction of Performance Intelligence

The rationale for the present study was to investigate the relationship between cortical volume, the latency of the ERP component P3a (as a measure of speed-of-processing), and performance intelligence (not adjusted for age differences). Seventy-one participants aged 20-88 years underwent a visual 3-stimuli oddball ERP task, an MRI-scan, and intelligence testing. P3a latency and cortical volume shared 9% variance (p<.05) and both were significantly related to performance intelligence (R2=.26 and .40, respectively). The amount of explained variance increased significantly (to R2=.51) when both measures were used as simultaneous predictors. When a path diagram was constructed including age as an exogenous variable, P3a latency and cortical volume both significantly predicted performance intelligence, but were no longer related to one another. The main conclusion from the study is that speed and size are complementary in prediction of performance intelligence, and the theoretical implications are discussed.

Detection of Entorhinal Layer II Using 7Tesla [corrected] Magnetic Resonance Imaging

The entorhinal cortex lies in the mediotemporal lobe and has major functional, structural, and clinical significance. The entorhinal cortex has a unique cytoarchitecture with large stellate neurons in layer II that form clusters. The entorhinal cortex receives vast sensory association input, and its major output arises from the layer II and III neurons that form the perforant pathway. Clinically, the neurons in layer II are affected with neurofibrillary tangles, one of the two pathological hallmarks of Alzheimer's disease. We describe detection of the entorhinal layer II islands using magnetic resonance imaging. We scanned human autopsied temporal lobe blocks in a 7T human scanner using a solenoid coil. In 70 and 100 microm isotropic data, the entorhinal islands were clearly visible throughout the anterior-posterior extent of entorhinal cortex. Layer II islands were prominent in both the magnetic resonance imaging and corresponding histological sections, showing similar size and shape in two types of data. Area borders and island location based on cytoarchitectural features in the mediotemporal lobe were robustly detected using the magnetic resonance images. Our ex vivo results could break ground for high-resolution in vivo scanning that could ultimately benefit early diagnosis and treatment of neurodegenerative disease.

On-line Automatic Slice Positioning for Brain MR Imaging

In clinical brain MR imaging protocols, the technician collects a quick localizer and manually positions the subsequent scans using the localizer as a guide. We present a method for automatic slice positioning using a rapidly acquired 3D localizer. The localizer is automatically aligned to a statistical atlas representing 40 healthy subjects. The atlas contains the probability of a given tissue type occurring at a given location in atlas space and the conditional probability distribution of the multi-spectral MRI intensity values for a given tissue class. Accurate rigid alignment of each subject to an atlas ensures that all patients' scans are acquired in a consistent manner. A further benefit is that slices are positioned consistently over time, so that scans of patients returning for follow-up imaging can be compared side-by-side to accurately monitor the progression of illness. The procedure also helps ensure that left/right asymmetries reflect true anatomy rather than being the result of oblique slice positioning relative to the underlying anatomy. The use of an atlas-based procedure eliminates the need to refer to a database of previously scanned images of the same patient and ensures corresponding alignment across scanners and sites, without requiring fiducial markers. Since the registration method is probabilistic, the registration error tends to increase smoothly in the presence of increasing noise and unusual anatomy or pathology rather than failing catastrophically. Translations and rotations relative to the atlas can be set so that planning can be done in anatomical space, rather than scanner coordinates, and stored as part of the protocol allowing standardization of slice orientations.

Meditation Experience is Associated with Increased Cortical Thickness

Previous research indicates that long-term meditation practice is associated with altered resting electroencephalogram patterns, suggestive of long lasting changes in brain activity. We hypothesized that meditation practice might also be associated with changes in the brain's physical structure. Magnetic resonance imaging was used to assess cortical thickness in 20 participants with extensive Insight meditation experience, which involves focused attention to internal experiences. Brain regions associated with attention, interoception and sensory processing were thicker in meditation participants than matched controls, including the prefrontal cortex and right anterior insula. Between-group differences in prefrontal cortical thickness were most pronounced in older participants, suggesting that meditation might offset age-related cortical thinning. Finally, the thickness of two regions correlated with meditation experience. These data provide the first structural evidence for experience-dependent cortical plasticity associated with meditation practice.

Orbitofrontal Thickness, Retention of Fear Extinction, and Extraversion

People differ in their personality traits and in their ability to modulate fear. Does our personality determine how well we extinguish conditioned fear responses? Or is the opposite true? Herein, we examine the relationships between personality traits, memory for fear extinction, and cortical thickness as a measure of brain structure. We found that in healthy humans, extinction retention and thickness of the medial orbitofrontal cortex are positively correlated with extraversion. Path analysis indicates that extinction retention mediates the relationship between the medial orbitofrontal cortex thickness and extraversion, thereby illustrating one path through which brain structure influences personality.

A Genetic Algorithm for the Topology Correction of Cortical Surfaces

We propose a technique to accurately correct the spherical topology of cortical surfaces. We construct a mapping from the original surface onto the sphere to detect topological defects as minimal non-homeomorphic regions. A genetic algorithm corrects each defect by finding the maximum-a-posteriori retessellation in a Bayesian framework. During the genetic search, incorrect vertices are iteratively identified and eliminated, while the optimal retessellation is constructed. Applied to synthetic and real data, our method generates optimal topological corrections with only a few iterations.

Reliability in Multi-site Structural MRI Studies: Effects of Gradient Non-linearity Correction on Phantom and Human Data

Longitudinal and multi-site clinical studies create the imperative to characterize and correct technological sources of variance that limit image reproducibility in high-resolution structural MRI studies, thus facilitating precise, quantitative, platform-independent, multi-site evaluation. In this work, we investigated the effects that imaging gradient non-linearity have on reproducibility of multi-site human MRI. We applied an image distortion correction method based on spherical harmonics description of the gradients and verified the accuracy of the method using phantom data. The correction method was then applied to the brain image data from a group of subjects scanned twice at multiple sites having different 1.5 T platforms. Within-site and across-site variability of the image data was assessed by evaluating voxel-based image intensity reproducibility. The image intensity reproducibility of the human brain data was significantly improved with distortion correction, suggesting that this method may offer improved reproducibility in morphometry studies. We provide the source code for the gradient distortion algorithm together with the phantom data.

Comparison of Manual and Automatic Section Positioning of Brain MR Images

The study protocol was approved by the institutional review board and was in full compliance with HIPAA guidelines. Informed consent was obtained from all patients. The purpose of this study was to prospectively compare intra- and intersubject variability of manual versus automatic magnetic resonance (MR) imaging section prescription. In two examinations, T2-weighted series were acquired with both methods. All intrasubject and three of six intersubject section prescription variances were significantly higher for manual prescription (P < .01). Root mean square errors confirmed better coregistration of the automated approach (P < .001). Automatic section prescription leads to improved reproducibility of imaging orientations for intra- and intersubject series in clinical practice.

An Automated Labeling System for Subdividing the Human Cerebral Cortex on MRI Scans into Gyral Based Regions of Interest

In this study, we have assessed the validity and reliability of an automated labeling system that we have developed for subdividing the human cerebral cortex on magnetic resonance images into gyral based regions of interest (ROIs). Using a dataset of 40 MRI scans we manually identified 34 cortical ROIs in each of the individual hemispheres. This information was then encoded in the form of an atlas that was utilized to automatically label ROIs. To examine the validity, as well as the intra- and inter-rater reliability of the automated system, we used both intraclass correlation coefficients (ICC), and a new method known as mean distance maps, to assess the degree of mismatch between the manual and the automated sets of ROIs. When compared with the manual ROIs, the automated ROIs were highly accurate, with an average ICC of 0.835 across all of the ROIs, and a mean distance error of less than 1 mm. Intra- and inter-rater comparisons yielded little to no difference between the sets of ROIs. These findings suggest that the automated method we have developed for subdividing the human cerebral cortex into standard gyral-based neuroanatomical regions is both anatomically valid and reliable. This method may be useful for both morphometric and functional studies of the cerebral cortex as well as for clinical investigations aimed at tracking the evolution of disease-induced changes over time, including clinical trials in which MRI-based measures are used to examine response to treatment.

Regional Cortical Thickness Matters in Recall After Months More Than Minutes

The aim of this study was to determine the role of regional cortical thickness in recall of verbal material over an extended time period. MRI scans of healthy adults of varying ages were obtained. Two scans were averaged per person to achieve high spatial resolution, and a semi-automated method for continuous measurement of thickness across the entire cortical mantle was employed. Verbal memory tests assessing recall after 5 min, 30 min, and a mean interval of 83 days were administered. A general linear model (GLM) of the effects of thickness at each vertex on the different memory indices was computed, controlling for gender, age, IQ, and intracranial volume. These analyses were repeated with hippocampal volume as an additional variable to be controlled for, to assess to which extent effects of cortical thickness were independent of hippocampal size. Minute effects of cortical thickness were observed with regard to shorter time intervals (5 and 30 min). However, even when controlling for the effects of hippocampal volume, higher recall across months was associated with thicker cortex of distinct areas including parts of the gyrus rectus, the middle frontal gyrus, the parieto-occipital sulcus and the lingual gyrus of both hemispheres. In addition, hemisphere-specific associations were found in parts of the right temporal and parietal lobe as well as parts of the left precuneus. This supports a unique and critical role of the thickness of distinct cortical areas in recall after months, more than after minutes.

The Functional and Structural Significance of the Frontal Shift in the Old/new ERP Effect

There is a lack of studies mapping electrophysiological event-related potentials (ERPs) to structural neuroanatomical characteristics. The aim of the present study was to integrate electrophysiological memory-related activity with cortical and hippocampal volume, as well as psychometric memory performance, in a life-span sample. More specifically, we wanted to investigate the functional significance of the often-observed frontal shift of ERP amplitude with increasing age and whether neuroanatomical characteristics can explain this shift. Sixty six healthy participants (20-78 years) went through a neuropsychological examination, MRI scans, and a visual recognition ERP task with verbal stimuli. The results showed that ERPs elicited in the recognition memory task (the old/new effect) correlated significantly with cortical volume, but not with hippocampal volume. Large cortex predicted more differentiated ERP activity and not just larger amplitude in general, implying more distinct and efficient retrieval. Furthermore, ERP amplitude, cortical volume, and hippocampal volume all predicted scores on a composite memory scale. All these relationship were dependent upon the common influence of age. Finally, the participants with the most anterior distribution of activity showed the poorest recognition memory performance. Neither cortical nor hippocampal volume were related to this frontal shift. It is concluded that the distribution of activity along the anterior-posterior axis in a memory paradigm may have functional but not neuroanatomical volumetric correlates. The functional correlates need not be restricted to the older age groups.

Reliability of MRI-derived Measurements of Human Cerebral Cortical Thickness: the Effects of Field Strength, Scanner Upgrade and Manufacturer

In vivo MRI-derived measurements of human cerebral cortex thickness are providing novel insights into normal and abnormal neuroanatomy, but little is known about their reliability. We investigated how the reliability of cortical thickness measurements is affected by MRI instrument-related factors, including scanner field strength, manufacturer, upgrade and pulse sequence. Several data processing factors were also studied. Two test-retest data sets were analyzed: 1) 15 healthy older subjects scanned four times at 2-week intervals on three scanners; 2) 5 subjects scanned before and after a major scanner upgrade. Within-scanner variability of global cortical thickness measurements was <0.03 mm, and the point-wise standard deviation of measurement error was approximately 0.12 mm. Variability was 0.15 mm and 0.17 mm in average, respectively, for cross-scanner (Siemens/GE) and cross-field strength (1.5 T/3 T) comparisons. Scanner upgrade did not increase variability nor introduce bias. Measurements across field strength, however, were slightly biased (thicker at 3 T). The number of (single vs. multiple averaged) acquisitions had a negligible effect on reliability, but the use of a different pulse sequence had a larger impact, as did different parameters employed in data processing. Sample size estimates indicate that regional cortical thickness difference of 0.2 mm between two different groups could be identified with as few as 7 subjects per group, and a difference of 0.1 mm could be detected with 26 subjects per group. These results demonstrate that MRI-derived cortical thickness measures are highly reliable when MRI instrument and data processing factors are controlled but that it is important to consider these factors in the design of multi-site or longitudinal studies, such as clinical drug trials.

Mapping an Intrinsic MR Property of Gray Matter in Auditory Cortex of Living Humans: a Possible Marker for Primary Cortex and Hemispheric Differences

Recently, magnetic resonance properties of cerebral gray matter have been spatially mapped--in vivo--over the cortical surface. In one of the first neuroscientific applications of this approach, this study explores what can be learned about auditory cortex in living humans by mapping longitudinal relaxation rate (R1), a property related to myelin content. Gray matter R1 (and thickness) showed repeatable trends, including the following: (1) Regions of high R1 were always found overlapping posteromedial Heschl's gyrus. They also sometimes occurred in planum temporale and never in other parts of the superior temporal lobe. We hypothesize that the high R1 overlapping Heschl's gyrus (which likely indicates dense gray matter myelination) reflects auditory koniocortex (i.e., primary cortex), a heavily myelinated area that shows comparable overlap with the gyrus. High R1 overlapping Heschl's gyrus was identified in every instance suggesting that R1 may ultimately provide a marker for koniocortex in individuals. Such a marker would be significant for auditory neuroimaging, which has no standard means (anatomic or physiologic) for localizing cortical areas in individual subjects. (2) Inter-hemispheric comparisons revealed greater R1 on the left on Heschl's gyrus, planum temporale, superior temporal gyrus and superior temporal sulcus. This asymmetry suggests greater gray matter myelination in left auditory cortex, which may be a substrate for the left hemisphere's specialized processing of speech, language, and rapid acoustic changes. These results indicate that in vivo R1 mapping can provide new insights into the structure of human cortical gray matter and its relation to function.

Detailed Semiautomated MRI Based Morphometry of the Neonatal Brain: Preliminary Results

In the neonate, regional growth trajectories provide information about the coordinated development of cerebral substructures and help identify regional vulnerability by identifying times of faster growth. Segmentation of magnetic resonance images (MRI) has provided detailed information for the myelinated brain but few reports of regional neonatal brain growth exist. We report the method and preliminary results of detailed semiautomated segmentation of 12 normative neonatal brains (gestational age 31.1-42.6 weeks at time of MRI) using volumetric T1-weighted images. Accuracy was confirmed by expert review of every segmented image. In 5 brains, repeat segmentation resulted in intraclass correlation coefficients >0.9 (except for the right amygdala) and an average percent voxel overlap of 90.0%. Artifacts or image quality limited the number of regions segmented in 9/12 data sets and 1/12 was excluded from volumetric analysis due to ventriculomegaly. Brains were segmented into cerebral exterior (N = 8), cerebral lobes (N = 5), lateral ventricles (N = 8), cerebral cortex (N = 6), white matter (N = 6), corpus callosum (N = 7), deep central gray (N = 8), hippocampi (N = 8), amygdalae (N = 8), cerebellar hemispheres (N = 8), vermis (N = 8), midbrain (N = 8), pons (N = 8) and medulla (N = 8). Linear growth (P < 0.05) was identified in all regions except the cerebral white matter, medulla and ventricles. Striking differences in regional growth rates were noted. These preliminary results are consistent with the heterochronous nature of cerebral development and provide initial estimates of regional brain growth and therefore regional vulnerability in the perinatal time period.

Human Cerebral Cortex: a System for the Integration of Volume- and Surface-based Representations

We describe an MRI-based system for topological analysis followed by measurements of topographic features for the human cerebral cortex that takes as its starting point volumetric segmentation data. This permits interoperation between volume-based and surface-based topographic analysis and extends the functionality of many existing segmentation schemes. We demonstrate the utility of these operations in individual as well as to group analysis. The methodology integrates analyses of cortical segmentation data generated by manual and semi-automated volumetric morphometry routines (such as the program cardviews) with the procedures of the FreeSurfer program to generate a cortical ribbon of the cerebrum and perform cortical topographic measurements (including thickness, surface area and curvature) in individual subjects as well as in subject populations. This system allows the computation of topographical cortical measurements for segmentation data generated from manual and semi-automated volumetric sources other than FreeSurfer. These measurements can be regionally specific and integrated with systems of cortical parcellation that subdivides the neocortex into gyral-based parcellation units (PUs). This system of topographical analysis of the cerebral cortex is consistent with current views of cortical development and neural systems organization of the human and non-human primate brain.

Location and Spatial Profile of Category-specific Regions in Human Extrastriate Cortex

Subjects were scanned in a single functional MRI (fMRI) experiment that enabled us to localize cortical regions in each subject in the occipital and temporal lobes that responded significantly in a variety of contrasts: faces>objects, body parts>objects, scenes>objects, objects>scrambled objects, and moving>stationary stimuli. The resulting activation maps were co-registered across subjects using spherical surface coordinates [Fischl et al., Hum Brain Mapp 1999;8:272-284] to produce a "percentage overlap map" indicating the percentage of subjects who showed a significant response for each contrast at each point on the surface. Prominent among the overlapping activations in these contrasts were the fusiform face area (FFA), extrastriate body area (EBA), parahippocampal place area (PPA), lateral occipital complex (LOC), and MT+/V5; only a few other areas responded consistently across subjects in these contrasts. Another analysis showed that the spatial profile of the selective response drops off quite sharply outside the standard borders of the FFA and PPA (less so for the EBA and MT+/V5), indicating that these regions are not simply peaks of very broad selectivities spanning centimeters of cortex, but fairly discrete regions of cortex with distinctive functional profiles. The data also yielded a surprise that challenges our understanding of the function of area MT+: a higher response to body parts than to objects. The anatomical consistency of each of our functionally defined regions across subjects and the spatial sharpness of their activation profiles within subjects highlight the fact that these regions constitute replicable and distinctive landmarks in the functional organization of the human brain.

Quantitative Evaluation of Automated Skull-stripping Methods Applied to Contemporary and Legacy Images: Effects of Diagnosis, Bias Correction, and Slice Location

Performance of automated methods to isolate brain from nonbrain tissues in magnetic resonance (MR) structural images may be influenced by MR signal inhomogeneities, type of MR image set, regional anatomy, and age and diagnosis of subjects studied. The present study compared the performance of four methods: Brain Extraction Tool (BET; Smith [2002]: Hum Brain Mapp 17:143-155); 3dIntracranial (Ward [1999] Milwaukee: Biophysics Research Institute, Medical College of Wisconsin; in AFNI); a Hybrid Watershed algorithm (HWA, Segonne et al. [2004] Neuroimage 22:1060-1075; in FreeSurfer); and Brain Surface Extractor (BSE, Sandor and Leahy [1997] IEEE Trans Med Imag 16:41-54; Shattuck et al. [2001] Neuroimage 13:856-876) to manually stripped images. The methods were applied to uncorrected and bias-corrected datasets; Legacy and Contemporary T1-weighted image sets; and four diagnostic groups (depressed, Alzheimer's, young and elderly control). To provide a criterion for outcome assessment, two experts manually stripped six sagittal sections for each dataset in locations where brain and nonbrain tissue are difficult to distinguish. Methods were compared on Jaccard similarity coefficients, Hausdorff distances, and an Expectation-Maximization algorithm. Methods tended to perform better on contemporary datasets; bias correction did not significantly improve method performance. Mesial sections were most difficult for all methods. Although AD image sets were most difficult to strip, HWA and BSE were more robust across diagnostic groups compared with 3dIntracranial and BET. With respect to specificity, BSE tended to perform best across all groups, whereas HWA was more sensitive than other methods. The results of this study may direct users towards a method appropriate to their T1-weighted datasets and improve the efficiency of processing for large, multisite neuroimaging studies.

Selective Increase of Cortical Thickness in High-performing Elderly--structural Indices of Optimal Cognitive Aging

The aim of this study was to identify cortical areas important for optimal cognitive aging. 74 participants (20-88 years) went through neuropsychological tests and two MR sessions. The sample was split into two age groups. In each, every participant was classified as "high" or "average" on fluid ability tests and on neuropsychological tests related to executive function. The groups were compared with regard to thickness on a point-by-point basis across the entire cortical mantle. The old high fluid performers had thicker cortex than the average performers in large areas of cortex, while there was minimal difference between the groups of high vs. average executive function. Furthermore, the old group with high fluid function had thicker cortex than the young participants in the posterior cingulate and adjacent areas. Further analyses showed that the latter was a result of a complex aging pattern, differing between the two performance groups, with decades of cortical thickening and subsequent thinning.

A Technique for the Deidentification of Structural Brain MR Images

Due to the increasing need for subject privacy, the ability to deidentify structural MR images so that they do not provide full facial detail is desirable. A program was developed that uses models of nonbrain structures for removing potentially identifying facial features. When a novel image is presented, the optimal linear transform is computed for the input volume (Fischl et al. [2002]: Neuron 33:341-355; Fischl et al. [2004]: Neuroimage 23 (Suppl 1):S69-S84). A brain mask is constructed by forming the union of all voxels with nonzero probability of being brain and then morphologically dilated. All voxels outside the mask with a nonzero probability of being a facial feature are set to 0. The algorithm was applied to 342 datasets that included two different T1-weighted pulse sequences and four different diagnoses (depressed, Alzheimer's, and elderly and young control groups). Visual inspection showed none had brain tissue removed. In a detailed analysis of the impact of defacing on skull-stripping, 16 datasets were bias corrected with N3 (Sled et al. [1998]: IEEE Trans Med Imaging 17:87-97), defaced, and then skull-stripped using either a hybrid watershed algorithm (Ségonne et al. [2004]: Neuroimage 22:1060-1075, in FreeSurfer) or Brain Surface Extractor (Sandor and Leahy [1997]: IEEE Trans Med Imaging 16:41-54; Shattuck et al. [2001]: Neuroimage 13:856-876); defacing did not appreciably influence the outcome of skull-stripping. Results suggested that the automatic defacing algorithm is robust, efficiently removes nonbrain tissue, and does not unduly influence the outcome of the processing methods utilized; in some cases, skull-stripping was improved. Analyses support this algorithm as a viable method to allow data sharing with minimal data alteration within large-scale multisite projects.

Neural Activity is Modulated by Trial History: a Functional Magnetic Resonance Imaging Study of the Effects of a Previous Antisaccade

Saccadic latencies are influenced by what occurred during the previous trial. When the previous trial is an antisaccade, the latencies of both prosaccades and antisaccades are prolonged. The aim of this study was to identify neural correlates of this intertrial effect of antisaccades. Specifically, based on both monkey electrophysiology and human neuroimaging findings, we expected trials preceded by antisaccades to be associated with reduced frontal eye field (FEF) activity relative to those preceded by prosaccades. Twenty-one healthy participants performed pseudorandom sequences of prosaccade and antisaccade trials during functional magnetic resonance imaging (fMRI) with concurrent monitoring of eye position. We compared activity in trials preceded by an antisaccade with activity in trials preceded by a prosaccade. The primary result was that a previous antisaccade prolonged saccadic latency and reduced fMRI activity in the FEF and other regions. No regions showed increased activity. We interpret the reduced FEF activity and slower saccadic responses to reflect inhibitory influences on the response system as a consequence of performing an antisaccade in the previous trial. This demonstrates that neural activity is modulated by trial history, consistent with a rapid, dynamic form of learning. More generally, these results highlight the importance of trial history as a source of variability in both behavioral and neuroimaging studies.

Cortical Atrophy is Relevant in Multiple Sclerosis at Clinical Onset

Increasing evidence suggests relevant cortical gray matter pathology in patients with Multiple Sclerosis (MS), but how early this pathology begins; its impact on clinical disability and which cortical areas are primarily affected needs to be further elucidated.

Cognitive Function, P3a/P3b Brain Potentials, and Cortical Thickness in Aging

The purpose of the study was to assess the relationship between the P3a/P3b brain potentials, cortical thickness, and cognitive function in aging. Thirty-five younger and 37 older healthy participants completed a visual three-stimuli oddball ERP (event-related potential)-paradigm, a battery of neuropsychological tests, and MRI scans. Groups with short vs. long latency, and low vs. high amplitude, were compared on a point by point basis across the entire cortical mantle. In the young, thickness was only weakly related to P3. In the elderly, P3a amplitude effects were found in parietal areas, the temporoparietal junction, and parts of the posterior cingulate cortex. P3b latency was especially related to cortical thickness in large frontal regions. Path models with the whole sample pooled together were constructed, demonstrating that cortical thickness in the temporoparietal cortex predicted P3a amplitude, which in turn predicted executive function, and that thickness in orbitofrontal cortex predicted P3b latency, which in turn predicted fluid function. When age was included in the model, the relationship between P3 and cognitive function vanished, while the relationship between regional cortical thickness and P3 remained. It is concluded that thickness in specific cortical areas correlates with scalp recorded P3a/P3b in elderly, and that these relationships differentially mediate higher cognitive function.

Changes in Cerebral Cortex of Children Treated for Medulloblastoma

Children with medulloblastoma undergo surgery, radiotherapy, and chemotherapy. After treatment, these children have numerous structural abnormalities. Using high-resolution magnetic resonance imaging, we measured the thickness of the cerebral cortex in a group of medulloblastoma patients and a group of normally developing children.

Atlas Renormalization for Improved Brain MR Image Segmentation Across Scanner Platforms

Atlas-based approaches have demonstrated the ability to automatically identify detailed brain structures from 3-D magnetic resonance (MR) brain images. Unfortunately, the accuracy of this type of method often degrades when processing data acquired on a different scanner platform or pulse sequence than the data used for the atlas training. In this paper, we improve the performance of an atlas-based whole brain segmentation method by introducing an intensity renormalization procedure that automatically adjusts the prior atlas intensity model to new input data. Validation using manually labeled test datasets has shown that the new procedure improves the segmentation accuracy (as measured by the Dice coefficient) by 10% or more for several structures including hippocampus, amygdala, caudate, and pallidum. The results verify that this new procedure reduces the sensitivity of the whole brain segmentation method to changes in scanner platforms and improves its accuracy and robustness, which can thus facilitate multicenter or multisite neuroanatomical imaging studies.

Geometrically Accurate Topology-correction of Cortical Surfaces Using Nonseparating Loops

In this paper, we focus on the retrospective topology correction of surfaces. We propose a technique to accurately correct the spherical topology of cortical surfaces. Specifically, we construct a mapping from the original surface onto the sphere to detect topological defects as minimal nonhomeomorphic regions. The topology of each defect is then corrected by opening and sealing the surface along a set of nonseparating loops that are selected in a Bayesian framework. The proposed method is a wholly self-contained topology correction algorithm, which determines geometrically accurate, topologically correct solutions based on the magnetic resonance imaging (MRI) intensity profile and the expected local curvature. Applied to real data, our method provides topological corrections similar to those made by a trained operator.

Cortical Surface Shape Analysis Based on Spherical Wavelets

In vivo quantification of neuroanatomical shape variations is possible due to recent advances in medical imaging and has proven useful in the study of neuropathology and neurodevelopment. In this paper, we apply a spherical wavelet transformation to extract shape features of cortical surfaces reconstructed from magnetic resonance images (MRIs) of a set of subjects. The spherical wavelet transformation can characterize the underlying functions in a local fashion in both space and frequency, in contrast to spherical harmonics that have a global basis set. We perform principal component analysis (PCA) on these wavelet shape features to study patterns of shape variation within normal population from coarse to fine resolution. In addition, we study the development of cortical folding in newborns using the Gompertz model in the wavelet domain, which allows us to characterize the order of development of large-scale and finer folding patterns independently. Given a limited amount of training data, we use a regularization framework to estimate the parameters of the Gompertz model to improve the prediction performance on new data. We develop an efficient method to estimate this regularized Gompertz model based on the Broyden-Fletcher-Goldfarb-Shannon (BFGS) approximation. Promising results are presented using both PCA and the folding development model in the wavelet domain. The cortical folding development model provides quantitative anatomic information regarding macroscopic cortical folding development and may be of potential use as a biomarker for early diagnosis of neurologic deficits in newborns.

Abnormal Cortical Folding Patterns Within Broca's Area in Schizophrenia: Evidence from Structural MRI

We compared cortical folding patterns between patients with schizophrenia and demographically-matched healthy controls in prefrontal and temporal regions of interest. Using the Freesurfer (http://surfer.nmr.mgh.harvard.edu) cortical surface-based reconstruction methodology, we indirectly ascertained cortical displacement and convolution, together, by measuring the degree of metric distortion required to optimally register cortical folding patterns to an average template. An area within the pars triangularis of the left inferior frontal gyrus (Broca's area) showed significantly reduced metric distortion in the patient group relative to the control group (p=0.0352). We discuss these findings in relation to the neurodevelopmental hypothesis and language dysfunction in schizophrenia.

Reduced Microstructural Integrity of the White Matter Underlying Anterior Cingulate Cortex is Associated with Increased Saccadic Latency in Schizophrenia

The anterior cingulate cortex (ACC) is a key component of a network that directs both spatial attention and saccadic eye movements, which are tightly linked. Diffusion tensor imaging (DTI) has demonstrated reduced microstructural integrity of the anterior cingulum bundle as indexed by fractional anisotropy (FA) in schizophrenia, but the functional significance of these abnormalities is unclear. Using DTI, we examined the white matter underlying anterior cingulate cortex in schizophrenia to determine whether reduced FA is associated with prolonged latencies of volitional saccades. Seventeen chronic, medicated schizophrenia outpatients and nineteen healthy controls had high-resolution DTI scans. FA maps were registered to structural scans and mapped across participants using a surface-based coordinate system. Cingulate white matter was divided into rostral and dorsal anterior regions and a posterior region. Patients showed reduced FA in cingulate white matter of the right hemisphere. Reduced FA in the white matter underlying anterior cingulate cortex, frontal eye field, and posterior parietal cortex of the right hemisphere was associated with longer saccadic latencies in schizophrenia, though given the relatively small sample size, these relations warrant replication. These findings demonstrate that in schizophrenia, increased latency of volitional saccades is associated with reduced microstructural integrity of the white matter underlying key cortical components of a right-hemisphere dominant network for visuospatial attention and ocular motor control. Moreover, they suggest that anterior cingulate white matter abnormalities contribute to slower performance of volitional saccades and to inter-individual variability of saccadic latency in chronic, medicated schizophrenia.

Phase Maps Reveal Cortical Architecture

Geometry Driven Volumetric Registration

In this paper, we propose a novel method for the registration of volumetric images of the brain that attempts to maximize the overlap of cortical folds. In order to achieve this, relevant geometrical information is extracted from a surface-based morph and is diffused throughout the volume using the Navier operator of elasticity. The result is a volumetric warp that aligns the folding patterns.

A Role for the Human Dorsal Anterior Cingulate Cortex in Fear Expression

Rodent studies implicate the prelimbic (PL) region of the medial prefrontal cortex in the expression of conditioned fear. Human studies suggest that the dorsal anterior cingulate cortex (dACC) plays a role similar to PL in mediating or modulating fear responses. This study examined the role of dACC during fear conditioning in healthy humans with magnetic resonance imaging (MRI).

Feasibility of Multi-site Clinical Structural Neuroimaging Studies of Aging Using Legacy Data

The application of advances in biomedical computing to medical imaging research is enabling scientists to conduct quantitative clinical imaging studies using data collected across multiple sites to test new hypotheses on larger cohorts, increasing the power to detect subtle effects. Given that many research groups have valuable existing (legacy) data, one goal of the Morphometry Biomedical Informatics Research Network (BIRN) Testbed is to assess the feasibility of pooled analyses of legacy structural neuroimaging data in normal aging and Alzheimer's disease. The present study examined whether such data could be meaningfully reanalyzed as a larger combined data set by using rigorous data curation, image analysis, and statistical modeling methods; in this case, to test the hypothesis that hippocampal volume decreases with age and to investigate findings of hippocampal asymmetry. This report describes our work with legacy T1-weighted magnetic resonance (MR) and demographic data related to normal aging that have been shared through the BIRN by three research sites. Results suggest that, in the present application, legacy MR data from multiple sites can be pooled to investigate questions of scientific interest. In particular, statistical analyses suggested that a mixed-effects model employing site as a random effect best fits the data, accounting for site-specific effects while taking advantage of expected comparability of age-related effects. In the combined sample from three sites, significant age-related decline of hippocampal volume and right-dominant hippocampal asymmetry were detected in healthy elderly controls. These expected findings support the feasibility of combining legacy data to investigate novel scientific questions.

Effects of Registration Regularization and Atlas Sharpness on Segmentation Accuracy

In this paper, we propose a unified framework for computing atlases from manually labeled data at various degrees of "sharpness" and the joint registration-segmentation of a new brain with these atlases. In non-rigid registration, the tradeoff between warp regularization and image fidelity is typically set empirically. In segmentation, this leads to a probabilistic atlas of arbitrary "sharpness": weak regularization results in well-aligned training images and a "sharp" atlas; strong regularization yields a "blurry" atlas. We study the effects of this tradeoff in the context of cortical surface parcellation by comparing three special cases of our framework, namely: progressive registration-segmentation of a new brain to increasingly "sharp" atlases with increasingly flexible warps; secondly, progressive registration to a single atlas with increasingly flexible warps; and thirdly, registration to a single atlas with fixed constrained warps. The optimal parcellation in all three cases corresponds to a unique balance of atlas "sharpness" and warp regularization that yield statistically significant improvements over the previously demonstrated parcellation results.

Accurate Prediction of V1 Location from Cortical Folds in a Surface Coordinate System

Previous studies demonstrated substantial variability of the location of primary visual cortex (V1) in stereotaxic coordinates when linear volume-based registration is used to match volumetric image intensities [Amunts, K., Malikovic, A., Mohlberg, H., Schormann, T., and Zilles, K. (2000). Brodmann's areas 17 and 18 brought into stereotaxic space-where and how variable? Neuroimage, 11(1):66-84]. However, other qualitative reports of V1 location [Smith, G. (1904). The morphology of the occipital region of the cerebral hemisphere in man and the apes. Anatomischer Anzeiger, 24:436-451; Stensaas, S.S., Eddington, D.K., and Dobelle, W.H. (1974). The topography and variability of the primary visual cortex in man. J Neurosurg, 40(6):747-755; Rademacher, J., Caviness, V.S., Steinmetz, H., and Galaburda, A.M. (1993). Topographical variation of the human primary cortices: implications for neuroimaging, brain mapping, and neurobiology. Cereb Cortex, 3(4):313-329] suggested a consistent relationship between V1 and the surrounding cortical folds. Here, the relationship between folds and the location of V1 is quantified using surface-based analysis to generate a probabilistic atlas of human V1. High-resolution (about 200 microm) magnetic resonance imaging (MRI) at 7 T of ex vivo human cerebral hemispheres allowed identification of the full area via the stria of Gennari: a myeloarchitectonic feature specific to V1. Separate, whole-brain scans were acquired using MRI at 1.5 T to allow segmentation and mesh reconstruction of the cortical gray matter. For each individual, V1 was manually identified in the high-resolution volume and projected onto the cortical surface. Surface-based intersubject registration [Fischl, B., Sereno, M.I., Tootell, R.B., and Dale, A.M. (1999b). High-resolution intersubject averaging and a coordinate system for the cortical surface. Hum Brain Mapp, 8(4):272-84] was performed to align the primary cortical folds of individual hemispheres to those of a reference template representing the average folding pattern. An atlas of V1 location was constructed by computing the probability of V1 inclusion for each cortical location in the template space. This probabilistic atlas of V1 exhibits low prediction error compared to previous V1 probabilistic atlases built in volumetric coordinates. The increased predictability observed under surface-based registration suggests that the location of V1 is more accurately predicted by the cortical folds than by the shape of the brain embedded in the volume of the skull. In addition, the high quality of this atlas provides direct evidence that surface-based intersubject registration methods are superior to volume-based methods at superimposing functional areas of cortex and therefore are better suited to support multisubject averaging for functional imaging experiments targeting the cerebral cortex.

Cortical Folding Patterns and Predicting Cytoarchitecture

The human cerebral cortex is made up of a mosaic of structural areas, frequently referred to as Brodmann areas (BAs). Despite the widespread use of cortical folding patterns to perform ad hoc estimations of the locations of the BAs, little is understood regarding 1) how variable the position of a given BA is with respect to the folds, 2) whether the location of some BAs is more variable than others, and 3) whether the variability is related to the level of a BA in a putative cortical hierarchy. We use whole-brain histology of 10 postmortem human brains and surface-based analysis to test how well the folds predict the locations of the BAs. We show that higher order cortical areas exhibit more variability than primary and secondary areas and that the folds are much better predictors of the BAs than had been previously thought. These results further highlight the significance of cortical folding patterns and suggest a common mechanism for the development of the folds and the cytoarchitectonic fields.

Brain Morphometry with Multiecho MPRAGE

In brain morphometry studies using magnetic resonance imaging, several scans with a range of contrasts are often collected. The images may be locally distorted due to imperfect shimming in regions where magnetic susceptibility changes rapidly, and all scans may not be distorted in the same way. In multispectral studies it is critical that the edges of structures align precisely across all contrasts. The MPRAGE (MPR) sequence has excellent contrast properties for cortical segmentation, while multiecho FLASH (MEF) provides better contrast for segmentation of subcortical structures. Here, a multiecho version of the MPRAGE (MEMPR) is evaluated using SIENA and FreeSurfer. The higher bandwidth of the MEMPR results in reduced distortions that match those of the MEF while the SNR is recovered by combining the echoes. Accurate automatic identification of cortex and thickness estimation is frustrated by the presence of dura adjacent to regions such as the entorhinal cortex. In the typical MPRAGE protocol, dura and cortex are approximately isointense. However, dura has substantially smaller T2* than cortex. This information is represented in the multiple echoes of the MEMPR. An algorithm is described for correcting cortical thickness using T2*. It is shown that with MEMPR, SIENA generates more reliable percentage brain volume changes and FreeSurfer generates more reliable cortical models. The regions where cortical thickness is affected by dura are shown. MEMPR did not substantially improve subcortical segmentations. Since acquisition time is the same for MEMPR as for MPRAGE, and it has better distortion properties and additional T2* information, MEMPR is recommended for morphometry studies.

The Effect of Early Human Diet on Caudate Volumes and IQ

Early nutrition in animals affects both behavior and brain structure. In humans, randomized trials show that early nutrition affects later cognition, notably in males. We hypothesized that early nutrition also influences brain structure, measurable using magnetic resonance imaging. Prior research suggested that the caudate nucleus may be especially vulnerable to early environment and that its size relates to IQ. To test the hypothesis that the caudate nucleus could be a neural substrate for cognitive effects of early nutrition, we compared two groups of adolescents, assigned a Standard- or High-nutrient diet in the postnatal weeks after preterm birth. Groups had similar birth status and neonatal course. Scans and IQ data were obtained from 76 adolescents and volumes of several subcortical structures were calculated. The High-nutrient group had significantly larger caudate volumes and higher Verbal IQ (VIQ). Caudate volumes correlated significantly with VIQ in the Standard-nutrient group only. Caudate volume was influenced by early nutrition and related selectively to VIQ in males, but not in females. Our findings may partly explain the effects of early diet on cognition and the predominant effects in males. They are among the first to show that human brain structure can be influenced by early nutrition.

The Intrinsic Shape of Human and Macaque Primary Visual Cortex

Previous studies have reported considerable variability in primary visual cortex (V1) shape in both humans and macaques. Here, we demonstrate that much of this variability is due to the pattern of cortical folds particular to an individual and that V1 shape is similar among individual humans and macaques as well as between these 2 species. Human V1 was imaged ex vivo using high-resolution (200 microm) magnetic resonance imaging at 7 T. Macaque V1 was identified in published histological serial section data. Manual tracings of the stria of Gennari were used to construct a V1 surface, which was computationally flattened with minimal metric distortion of the cortical surface. Accurate flattening allowed investigation of intrinsic geometric features of cortex, which are largely independent of the highly variable cortical folds. The intrinsic shape of V1 was found to be similar across human subjects using both nonparametric boundary matching and a simple elliptical shape model fit to the data and is very close to that of the macaque monkey. This result agrees with predictions derived from current models of V1 topography. In addition, V1 shape similarity suggests that similar developmental mechanisms are responsible for establishing V1 shape in these 2 species.

Cerebral Cortex and the Clinical Expression of Huntington's Disease: Complexity and Heterogeneity

The clinical phenotype of Huntington's disease (HD) is far more complex and variable than depictions of it as a progressive movement disorder dominated by neostriatal pathology represent. The availability of novel neuro-imaging methods has enabled us to evaluate cerebral cortical changes in HD, which we have found to occur early and to be topographically selective. What is less clear, however, is how these changes influence the clinical expression of the disease. In this study, we used a high-resolution surface based analysis of in vivo MRI data to measure cortical thickness in 33 individuals with HD, spanning the spectrum of disease and 22 age- and sex-matched controls. We found close relationships between specific functional and cognitive measures and topologically specific cortical regions. We also found that distinct motor phenotypes were associated with discrete patterns of cortical thinning. The selective topographical associations of cortical thinning with clinical features of HD suggest that we are not simply correlating global worsening with global cortical degeneration. Our results indicate that cortical involvement contributes to important symptoms, including those that have been ascribed primarily to the striatum, and that topologically selective changes in the cortex might explain much of the clinical heterogeneity found in HD. Additionally, a significant association between regional cortical thinning and total functional capacity, currently the leading primary outcome measure used in neuroprotection trials for HD, establishes cortical MRI morphometry as a potential biomarker of disease progression.

The Relationship Between Diffusion Tensor Imaging and Volumetry As Measures of White Matter Properties

There is still limited knowledge about the relationship between different structural brain parameters, despite huge progress in analysis of neuroimaging data. The aim of the present study was to test the relationship between fractional anisotropy (FA) from diffusion tensor imaging (DTI) and regional white matter (WM) volume. As WM volume has been shown to develop until middle age, the focus was on changes in WM properties in the age range of 40 to 60 years. 100 participants were scanned with magnetic resonance imaging (MRI). Each hemisphere was parcellated into 35 WM regions, and volume, FA, axial, and radial diffusion in each region were calculated. The relationships between age and the regional measures of FA and WM volume were tested, and then FA and WM volume were correlated, corrected for intracranial volume, age, and sex. WM volume was weakly related to age, while FA correlated negatively with age in 26 of 70 regions, caused by a mix of reduced axial and increased radial diffusion with age. 23 relationships between FA and WM volume were found, with seven being positive and sixteen negative. The positive correlations were mainly caused by increased radial diffusion. It is concluded that FA is more sensitive than volume to changes in WM integrity during middle age, and that FA-age correlations probably are related to reduced amount of myelin with increasing age. Further, FA and WM volume are moderately to weakly related and to a large extent sensitive to different characteristics of WM integrity.

Model-based Segmentation of Hippocampal Subfields in Ultra-high Resolution in Vivo MRI

Recent developments in MR data acquisition technology are starting to yield images that show anatomical features of the hippocampal formation at an unprecedented level of detail, providing the basis for hippocampal subfield measurement. Because of the role of the hippocampus in human memory and its implication in a variety of disorders and conditions, the ability to reliably and efficiently quantify its subfields through in vivo neuroimaging is of great interest to both basic neuroscience and clinical research. In this paper, we propose a fully-automated method for segmenting the hippocampal subfields in ultra-high resolution MRI data. Using a Bayesian approach, we build a computational model of how images around the hippocampal area are generated, and use this model to obtain automated segmentations. We validate the proposed technique by comparing our segmentation results with corresponding manual delineations in ultra-high resolution MRI scans of five individuals.

Shape Analysis with Overcomplete Spherical Wavelets

In this paper, we explore the use of over-complete spherical wavelets in shape analysis of closed 2D surfaces. Previous work has demonstrated, theoretically and practically, the advantages of overcomplete over bi-orthogonal spherical wavelets. Here we present a detailed formulation of over-complete wavelets, as well as shape analysis experiments of cortical folding development using them. Our experiments verify in a quantitative fashion existing qualitative theories of neuroanatomical development. Furthermore, the experiments reveal novel insights into neuro-anatomical development not previously documented.

Spherical Demons: Fast Surface Registration

We present the fast Spherical Demons algorithm for registering two spherical images. By exploiting spherical vector spline interpolation theory, we show that a large class of regularizers for the modified demons objective function can be efficiently implemented on the sphere using convolution. Based on the one parameter subgroups of diffeomorphisms, the resulting registration is diffeomorphic and fast - registration of two cortical mesh models with more than 100k nodes takes less than 5 minutes, comparable to the fastest surface registration algorithms. Moreover, the accuracy of our method compares favorably to the popular FreeSurfer registration algorithm. We validate the technique in two different settings: (1) parcellation in a set of in-vivo cortical surfaces and (2) Brodmann area localization in ex-vivo cortical surfaces.

Heritability of Brain Morphology Related to Schizophrenia: a Large-scale Automated Magnetic Resonance Imaging Segmentation Study

Schizophrenia is a devastating psychiatric disorder with a strong genetic component that has been related to a number of structural brain alterations. Currently available data on the heritability of these structural changes are inconsistent.

Effects of Registration Regularization and Atlas Sharpness on Segmentation Accuracy

In non-rigid registration, the tradeoff between warp regularization and image fidelity is typically determined empirically. In atlas-based segmentation, this leads to a probabilistic atlas of arbitrary sharpness: weak regularization results in well-aligned training images and a sharp atlas; strong regularization yields a "blurry" atlas. In this paper, we employ a generative model for the joint registration and segmentation of images. The atlas construction process arises naturally as estimation of the model parameters. This framework allows the computation of unbiased atlases from manually labeled data at various degrees of "sharpness", as well as the joint registration and segmentation of a novel brain in a consistent manner. We study the effects of the tradeoff of atlas sharpness and warp smoothness in the context of cortical surface parcellation. This is an important question because of the increasingly availability of atlases in public databases, and the development of registration algorithms separate from the atlas construction process. We find that the optimal segmentation (parcellation) corresponds to a unique balance of atlas sharpness and warp regularization, yielding statistically significant improvements over the FreeSurfer parcellation algorithm. Furthermore, we conclude that one can simply use a single atlas computed at an optimal sharpness for the registration-segmentation of a new subject with a pre-determined, fixed, optimal warp constraint. The optimal atlas sharpness and warp smoothness can be determined by probing the segmentation performance on available training data. Our experiments also suggest that segmentation accuracy is tolerant up to a small mismatch between atlas sharpness and warp smoothness.

Collaborative Computational Anatomy: an MRI Morphometry Study of the Human Brain Via Diffeomorphic Metric Mapping

This article describes a large multi-institutional analysis of the shape and structure of the human hippocampus in the aging brain as measured via MRI. The study was conducted on a population of 101 subjects including nondemented control subjects (n = 57) and subjects clinically diagnosed with Alzheimer's Disease (AD, n = 38) or semantic dementia (n = 6) with imaging data collected at Washington University in St. Louis, hippocampal structure annotated at the Massachusetts General Hospital, and anatomical shapes embedded into a metric shape space using large deformation diffeomorphic metric mapping (LDDMM) at the Johns Hopkins University. A global classifier was constructed for discriminating cohorts of nondemented and demented subjects based on linear discriminant analysis of dimensions derived from metric distances between anatomical shapes, demonstrating class conditional structure differences measured via LDDMM metric shape (P < 0.01). Localized analysis of the control and AD subjects only on the coordinates of the population template demonstrates shape changes in the subiculum and the CA1 subfield in AD (P < 0.05). Such large scale collaborative analysis of anatomical shapes has the potential to enhance the understanding of neurodevelopmental and neuropsychiatric disorders.

Accurate and Robust Brain Image Alignment Using Boundary-based Registration

The fine spatial scales of the structures in the human brain represent an enormous challenge to the successful integration of information from different images for both within- and between-subject analysis. While many algorithms to register image pairs from the same subject exist, visual inspection shows that their accuracy and robustness to be suspect, particularly when there are strong intensity gradients and/or only part of the brain is imaged. This paper introduces a new algorithm called Boundary-Based Registration, or BBR. The novelty of BBR is that it treats the two images very differently. The reference image must be of sufficient resolution and quality to extract surfaces that separate tissue types. The input image is then aligned to the reference by maximizing the intensity gradient across tissue boundaries. Several lower quality images can be aligned through their alignment with the reference. Visual inspection and fMRI results show that BBR is more accurate than correlation ratio or normalized mutual information and is considerably more robust to even strong intensity inhomogeneities. BBR also excels at aligning partial-brain images to whole-brain images, a domain in which existing registration algorithms frequently fail. Even in the limit of registering a single slice, we show the BBR results to be robust and accurate.

Minute Effects of Sex on the Aging Brain: a Multisample Magnetic Resonance Imaging Study of Healthy Aging and Alzheimer's Disease

Age is associated with substantial macrostructural brain changes. While some recent magnetic resonance imaging studies have reported larger age effects in men than women, others find no sex differences. As brain morphometry is a potentially important tool in diagnosis and monitoring of age-related neurological diseases, e.g., Alzheimer's disease (AD), it is important to know whether sex influences brain aging. We analyzed cross-sectional magnetic resonance scans from 1143 healthy participants from seven subsamples provided by four independent research groups. In addition, 96 patients with mild AD were included. Estimates of cortical thickness continuously across the brain surface, as well as volume of 17 subcortical structures, were obtained by use of automated segmentation tools (FreeSurfer). In the healthy participants, no differences in aging slopes between women and men were found in any part of the cortex. Pallidum corrected for intracranial volume showed slightly higher age correlations for men. The analyses were repeated in each of the seven subsamples, and the lack of age x sex interactions was largely replicated. Analyses of the AD sample showed no interactions between sex and age for any brain region. We conclude that sex has negligible effects on the age slope of brain volumes both in healthy participants and in AD.

Task-optimal Registration Cost Functions

In this paper, we propose a framework for learning the parameters of registration cost functions--such as the tradeoff between the regularization and image similiarity term--with respect to a specific task. Assuming the existence of labeled training data, we specialize the framework for the task of localizing hidden labels via image registration. We learn the parameters of the weighted sum of squared differences (wSSD) image similarity term that are optimal for the localization of Brodmann areas (BAs) in a new subject based on cortical geometry. We demonstrate state-of-the-art localization of V1, V2, BA44 and BA45.

Supervised Nonparametric Image Parcellation

Segmentation of medical images is commonly formulated as a supervised learning problem, where manually labeled training data are summarized using a parametric atlas. Summarizing the data alleviates the computational burden at the expense of possibly losing valuable information on inter-subject variability. This paper presents a novel framework for Supervised Nonparametric Image Parcellation (SNIP). SNIP models the intensity and label images as samples of a joint distribution estimated from the training data in a non-parametric fashion. By capitalizing on recently developed fast and robust pairwise image alignment tools, SNIP employs the entire training data to segment a new image via Expectation Maximization. The use of multiple registrations increases robustness to occasional registration failures. We report experiments on 39 volumetric brain MRI scans with manual labels for the white matter, cortex and subcortical structures. SNIP yields better segmentation than state-of-the-art algorithms in multiple regions of interest.

Nonparametric Mixture Models for Supervised Image Parcellation

We present a nonparametric, probabilistic mixture model for the supervised parcellation of images. The proposed model yields segmentation algorithms conceptually similar to the recently developed label fusion methods, which register a new image with each training image separately. Segmentation is achieved via the fusion of transferred manual labels. We show that in our framework various settings of a model parameter yield algorithms that use image intensity information differently in determining the weight of a training subject during fusion. One particular setting computes a single, global weight per training subject, whereas another setting uses locally varying weights when fusing the training data. The proposed nonparametric parcellation approach capitalizes on recently developed fast and robust pairwise image alignment tools. The use of multiple registrations allows the algorithm to be robust to occasional registration failures. We report experiments on 39 volumetric brain MRI scans with expert manual labels for the white matter, cerebral cortex, ventricles and subcortical structures. The results demonstrate that the proposed nonparametric segmentation framework yields significantly better segmentation than state-of-the-art algorithms.

An MRI-based Method for Measuring Volume, Thickness and Surface Area of Entorhinal, Perirhinal, and Posterior Parahippocampal Cortex

Several quantitative MRI-based protocols have been developed for measuring the volume of entorhinal (ERC), perirhinal (PRC), and posterior parahippocampal (PPHC) cortex. However, since the volume of a cortical region is a composite measure, relating directly to both thickness and surface area, it would be ideal to be able to quantify all of these morphometric measures, particularly since disease-related processes, such as Alzheimer's disease (AD), may preferentially affect thickness. This study describes a novel protocol for measuring the thickness, surface area, and volume of these three medial temporal lobe (MTL) subregions. Participants included 29 younger normal subjects (ages 18-30), 47 older normal subjects (ages 66-90), and 29 patients with mild AD (ages 56-90). Cortical surface models were reconstructed from the gray/white and gray/cerebrospinal fluid boundaries, and a hybrid visualization approach was implemented to trace the ERC, PRC, and PPHC using both orthogonal MRI slice- and cortical surface-based visualization of landmarks. Anatomic variants of the collateral sulcus (CS) were classified in all 105 participants, and the relationship between CS variants and corresponding morphometric measures was examined. One CS variant - deep, uninterrupted CS not connected with nearby sulci - was the most common configuration and was associated with thinner cortex within the ERC and PRC regions. This novel protocol enables the reliable measurement of both the thickness and surface area of ERC, PRC, and PPHC.

Differential Effects of Aging and Alzheimer's Disease on Medial Temporal Lobe Cortical Thickness and Surface Area

The volume of parcellated cortical regions is a composite measure related to both thickness and surface area. It is not clear whether volumetric decreases in medial temporal lobe (MTL) cortical regions in aging and Alzheimer's disease (AD) are due to thinning, loss of surface area, or both, nor is it clear whether aging and AD differ in their effects on these properties. Participants included 28 Younger Normals, 47 Older Normals, and 29 patients with mild AD. T1-weighted MRI data were analyzed using a novel semi-automated protocol (presented in a companion article) to delineate the boundaries of entorhinal (ERC), perirhinal (PRC), and posterior parahippocampal (PPHC) cortical regions and calculate their mean thickness, surface area, and volume. Compared to Younger Normals, Older Normals demonstrated moderately reduced ERC and PPHC volumes, which were due primarily to reduced surface area. In contrast, the expected AD-related reduction in ERC volume was produced by a large reduction in thickness with minimal additional effect (beyond that of aging) on surface area. PRC and PPHC also showed large AD-related reductions in thickness. Of all these MTL morphometric measures, ERC and PRC thinning were the best predictors of poorer episodic memory performance in AD. Although the volumes of MTL cortical regions may decrease with both aging and AD, thickness is relatively preserved in normal aging, while even in its mild clinical stage, AD is associated with a large degree of thinning of MTL cortex. These differential morphometric effects of aging and AD may reflect distinct biologic processes and ultimately may provide insights into the anatomic substrates of change in memory-related functions of MTL cortex.

Regional White Matter Volume Differences in Nondemented Aging and Alzheimer's Disease

Accumulating evidence suggests that altered cerebral white matter (WM) influences normal aging, and further that WM degeneration may modulate the clinical expression of Alzheimer's disease (AD). Here we conducted a study of differences in WM volume across the adult age span and in AD employing a newly developed, automated method for regional parcellation of the subcortical WM that uses curvature landmarks and gray matter (GM)/WM surface boundary information. This procedure measures the volume of gyral WM, utilizing a distance constraint to limit the measurements from extending into the centrum semiovale. Regional estimates were first established to be reliable across two scan sessions in 20 young healthy individuals. Next, the method was applied to a large clinically-characterized sample of 299 individuals including 73 normal older adults and 91 age-matched participants with very mild to mild AD. The majority of measured regions showed a decline in volume with increasing age, with strong effects found in bilateral fusiform, lateral orbitofrontal, superior frontal, medial orbital frontal, inferior temporal, and middle temporal WM. The association between WM volume and age was quadratic in many regions suggesting that WM volume loss accelerates in advanced aging. A number of WM regions were further reduced in AD with parahippocampal, entorhinal, inferior parietal and rostral middle frontal WM showing the strongest AD-associated reductions. There were minimal sex effects after correction for intracranial volume, and there were associations between ventricular volume and regional WM volumes in the older adults and AD that were not apparent in the younger adults. Certain results, such as the loss of WM in the fusiform region with aging, were unexpected and provide novel insight into patterns of age associated neural and cognitive decline. Overall, these results demonstrate the utility of automated regional WM measures in revealing the distinct patterns of age and AD associated volume loss that may contribute to cognitive decline.

High Consistency of Regional Cortical Thinning in Aging Across Multiple Samples

Cross-sectional magnetic resonance imaging (MRI) studies of cortical thickness and volume have shown age effects on large areas, but there are substantial discrepancies across studies regarding the localization and magnitude of effects. These discrepancies hinder understanding of effects of aging on brain morphometry, and limit the potential usefulness of MR in research on healthy and pathological age-related brain changes. The present study was undertaken to overcome this problem by assessing the consistency of age effects on cortical thickness across 6 different samples with a total of 883 participants. A surface-based segmentation procedure (FreeSurfer) was used to calculate cortical thickness continuously across the brain surface. The results showed consistent age effects across samples in the superior, middle, and inferior frontal gyri, superior and middle temporal gyri, precuneus, inferior and superior parietal cortices, fusiform and lingual gyri, and the temporo-parietal junction. The strongest effects were seen in the superior and inferior frontal gyri, as well as superior parts of the temporal lobe. The inferior temporal lobe and anterior cingulate cortices were relatively less affected by age. The results are discussed in relation to leading theories of cognitive aging.

MRI-derived Measurements of Human Subcortical, Ventricular and Intracranial Brain Volumes: Reliability Effects of Scan Sessions, Acquisition Sequences, Data Analyses, Scanner Upgrade, Scanner Vendors and Field Strengths

Automated MRI-derived measurements of in-vivo human brain volumes provide novel insights into normal and abnormal neuroanatomy, but little is known about measurement reliability. Here we assess the impact of image acquisition variables (scan session, MRI sequence, scanner upgrade, vendor and field strengths), FreeSurfer segmentation pre-processing variables (image averaging, B1 field inhomogeneity correction) and segmentation analysis variables (probabilistic atlas) on resultant image segmentation volumes from older (n=15, mean age 69.5) and younger (both n=5, mean ages 34 and 36.5) healthy subjects. The variability between hippocampal, thalamic, caudate, putamen, lateral ventricular and total intracranial volume measures across sessions on the same scanner on different days is less than 4.3% for the older group and less than 2.3% for the younger group. Within-scanner measurements are remarkably reliable across scan sessions, being minimally affected by averaging of multiple acquisitions, B1 correction, acquisition sequence (MPRAGE vs. multi-echo-FLASH), major scanner upgrades (Sonata-Avanto, Trio-TrioTIM), and segmentation atlas (MPRAGE or multi-echo-FLASH). Volume measurements across platforms (Siemens Sonata vs. GE Signa) and field strengths (1.5 T vs. 3 T) result in a volume difference bias but with a comparable variance as that measured within-scanner, implying that multi-site studies may not necessarily require a much larger sample to detect a specific effect. These results suggest that volumes derived from automated segmentation of T1-weighted structural images are reliable measures within the same scanner platform, even after upgrades; however, combining data across platform and across field-strength introduces a bias that should be considered in the design of multi-site studies, such as clinical drug trials. The results derived from the young groups (scanner upgrade effects and B1 inhomogeneity correction effects) should be considered as preliminary and in need for further validation with a larger dataset.

Combined Volumetric and Surface Registration

In this paper, we propose a novel method for the registration of volumetric images of the brain that optimizes the alignment of both cortical and subcortical structures. In order to achieve this, relevant geometrical information is extracted from a surface-based morph and diffused into the volume using the Navier operator of elasticity, resulting in a volumetric warp that aligns cortical folding patterns. This warp field is then refined with an intensity driven optical flow procedure that registers noncortical regions, while preserving the cortical alignment. The result is a combined surface and volume morph (CVS) that accurately registers both cortical and subcortical regions, establishing a single coordinate system suitable for the entire brain.

Distinct Genetic Influences on Cortical Surface Area and Cortical Thickness

Neuroimaging studies examining the effects of aging and neuropsychiatric disorders on the cerebral cortex have largely been based on measures of cortical volume. Given that cortical volume is a product of thickness and surface area, it is plausible that measures of volume capture at least 2 distinct sets of genetic influences. The present study aims to examine the genetic relationships between measures of cortical surface area and thickness. Participants were men in the Vietnam Era Twin Study of Aging (110 monozygotic pairs and 92 dizygotic pairs). Mean age was 55.8 years (range: 51-59). Bivariate twin analyses were utilized in order to estimate the heritability of cortical surface area and thickness, as well as their degree of genetic overlap. Total cortical surface area and average cortical thickness were both highly heritable (0.89 and 0.81, respectively) but were essentially unrelated genetically (genetic correlation = 0.08). This pattern was similar at the lobar and regional levels of analysis. These results demonstrate that cortical volume measures combine at least 2 distinct sources of genetic influences. We conclude that using volume in a genetically informative study, or as an endophenotype for a disorder, may confound the underlying genetic architecture of brain structure.

Locating the Functional and Anatomical Boundaries of Human Primary Visual Cortex

The primary visual cortex (V1) can be delineated both functionally by its topographic map of the visual field and anatomically by its distinct pattern of laminar myelination. Although it is commonly assumed that the specialized anatomy V1 exhibits corresponds in location with functionally defined V1, demonstrating this in human has not been possible thus far due to the difficulty of determining the location of V1 both functionally and anatomically in the same individual. In this study we use MRI to measure the anatomical and functional V1 boundaries in the same individual and demonstrate close agreement between them. Functional V1 location was measured by parcellating occipital cortex of 10 living humans into visual cortical areas based on the topographic map of the visual field measured using functional MRI. Anatomical V1 location was estimated for these same subjects using a surface-based probabilistic atlas derived from high-resolution structural MRI of the stria of Gennari in 10 intact ex vivo human hemispheres. To ensure that the atlas prediction was correct, it was validated against V1 location measured using an observer-independent cortical parcellation based on the laminar pattern of cell density in serial brain sections from 10 separate individuals. The close agreement between the independent anatomically and functionally derived V1 boundaries indicates that the whole extent of V1 can be accurately predicted based on cortical surface reconstructions computed from structural MRI scans, eliminating the need for functional localizers of V1. In addition, that the primary cortical folds predict the location of functional V1 suggests that the mechanism giving rise to V1 location is tied to the development of the cortical folds.

Predicting the Location of Entorhinal Cortex from MRI

Entorhinal cortex (EC) is a medial temporal lobe area critical to memory formation and spatial navigation that is among the earliest parts of the brain affected by Alzheimer's disease (AD). Accurate localization of EC would thus greatly facilitate early detection and diagnosis of AD. In this study, we used ultra-high resolution ex vivo MRI to directly visualize the architectonic features that define EC rostrocaudally and mediolaterally, then applied surface-based registration techniques to quantify the variability of EC with respect to cortical geometry, and made predictions of its location on in vivo scans. The results indicate that EC can be localized quite accurately based on cortical folding patterns, within 3 mm in vivo, a significant step forward in our ability to detect the earliest effects of AD when clinical intervention is most likely to be effective.

Target-specific Contrast Agents for Magnetic Resonance Microscopy

High-resolution ex vivo magnetic resonance (MR) imaging can be used to delineate prominent architectonic features in the human brain, but increased contrast is required to visualize more subtle distinctions. To aid MR sensitivity to cell density and myelination, we have begun the development of target-specific paramagnetic contrast agents. This work details the first application of luxol fast blue (LFB), an optical stain for myelin, as a white matter-selective MR contrast agent for human ex vivo brain tissue. Formalin-fixed human visual cortex was imaged with an isotropic resolution between 80 and 150 microm at 4.7 and 14 T before and after en bloc staining with LFB. Longitudinal (R1) and transverse (R2) relaxation rates in LFB-stained tissue increased proportionally with myelination at both field strengths. Changes in R1 resulted in larger contrast-to-noise ratios (CNR), per unit time, on T1-weighted images between more myelinated cortical layers (IV-VI) and adjacent, superficial layers (I-III) at both field strengths. Specifically, CNR for LFB-treated samples increased by 229 +/- 13% at 4.7 T and 269 +/- 25% at 14 T when compared to controls. Also, additional cortical layers (IVca, IVd, and Va) were resolvable in 14 T-MR images of LFB-treated samples but not in control samples. After imaging, samples were sliced in 40-micron sections, mounted, and photographed. Both the macroscopic and microscopic distributions of LFB were found to mimic those of traditional histological preparations. Our results suggest target-specific contrast agents will enable more detailed MR images with applications in imaging pathological ex vivo samples and constructing better MR atlases from ex vivo brains.

Fully-automated, Multi-stage Hippocampus Mapping in Very Mild Alzheimer Disease

Landmark-based high-dimensional diffeomorphic maps of the hippocampus (although accurate) is highly-dependent on rater's anatomic knowledge of the hippocampus in the magnetic resonance images. It is therefore vulnerable to rater drift and errors if substantial amount of effort is not spent on quality assurance, training, and re-training. A fully-automated, FreeSurfer-initialized large-deformation diffeomorphic metric mapping procedure of small brain substructures, including the hippocampus, has been previously developed and validated in small samples. In this report, we demonstrate that this fully-automated pipeline can be used in place of the landmark-based procedure in a large-sample clinical study to produce similar statistical outcomes. Some direct comparisons of the two procedures are also presented.

Automated Segmentation of Hippocampal Subfields from Ultra-high Resolution in Vivo MRI

Recent developments in MRI data acquisition technology are starting to yield images that show anatomical features of the hippocampal formation at an unprecedented level of detail, providing the basis for hippocampal subfield measurement. However, a fundamental bottleneck in MRI studies of the hippocampus at the subfield level is that they currently depend on manual segmentation, a laborious process that severely limits the amount of data that can be analyzed. In this article, we present a computational method for segmenting the hippocampal subfields in ultra-high resolution MRI data in a fully automated fashion. Using Bayesian inference, we use a statistical model of image formation around the hippocampal area to obtain automated segmentations. We validate the proposed technique by comparing its segmentations to corresponding manual delineations in ultra-high resolution MRI scans of 10 individuals, and show that automated volume measurements of the larger subfields correlate well with manual volume estimates. Unlike manual segmentations, our automated technique is fully reproducible, and fast enough to enable routine analysis of the hippocampal subfields in large imaging studies.

Widespread Reductions of Cortical Thickness in Schizophrenia and Spectrum Disorders and Evidence of Heritability

Schizophrenia is a brain disorder with predominantly genetic risk factors, and previous research has identified heritable cortical and subcortical reductions in local brain volume. To our knowledge, cortical thickness, a measure of particular interest in schizophrenia, has not previously been evaluated in terms of its heritability in relationship to risk for schizophrenia.

Cognitive Function and Brain Structure Correlations in Healthy Elderly East Asians

We investigated the effect of age and health variables known to modulate cognitive aging on several measures of cognitive performance and brain volume in a cohort of healthy, non-demented persons of Chinese descent aged between 55 and 86 years. 248 subjects contributed combined neuropsychological, MR imaging, health and socio-demographic information. Speed of processing showed the largest age-related decline. Education and plasma homocysteine levels modulated age-related decline in cognitive performance. Total cerebral volume declined at an annual rate of 0.4%/yr. Gray and white matter volume loss was comparable in magnitude. Regionally, there was relatively greater volume loss in the lateral prefrontal cortex bilaterally, around the primary visual cortex as well as bilateral superior parietal cortices. Speed of processing showed significant positive correlation with gray matter volume in several frontal, parietal and midline occipital regions bilaterally. In spite of differences in diet, lifestyle and culture, these findings are broadly comparable to studies conducted in Caucasian populations and suggest generalizability of processes involved in age-related decline in cognition and brain volume.

Automated MRI Measures Identify Individuals with Mild Cognitive Impairment and Alzheimer's Disease

Mild cognitive impairment can represent a transitional state between normal ageing and Alzheimer's disease. Non-invasive diagnostic methods are needed to identify mild cognitive impairment individuals for early therapeutic interventions. Our objective was to determine whether automated magnetic resonance imaging-based measures could identify mild cognitive impairment individuals with a high degree of accuracy. Baseline volumetric T1-weighted magnetic resonance imaging scans of 313 individuals from two independent cohorts were examined using automated software tools to identify the volume and mean thickness of 34 neuroanatomic regions. The first cohort included 49 older controls and 48 individuals with mild cognitive impairment, while the second cohort included 94 older controls and 57 mild cognitive impairment individuals. Sixty-five patients with probable Alzheimer's disease were also included for comparison. For the discrimination of mild cognitive impairment, entorhinal cortex thickness, hippocampal volume and supramarginal gyrus thickness demonstrated an area under the curve of 0.91 (specificity 94%, sensitivity 74%, positive likelihood ratio 12.12, negative likelihood ratio 0.29) for the first cohort and an area under the curve of 0.95 (specificity 91%, sensitivity 90%, positive likelihood ratio 10.0, negative likelihood ratio 0.11) for the second cohort. For the discrimination of Alzheimer's disease, these three measures demonstrated an area under the curve of 1.0. The three magnetic resonance imaging measures demonstrated significant correlations with clinical and neuropsychological assessments as well as with cerebrospinal fluid levels of tau, hyperphosphorylated tau and abeta 42 proteins. These results demonstrate that automated magnetic resonance imaging measures can serve as an in vivo surrogate for disease severity, underlying neuropathology and as a non-invasive diagnostic method for mild cognitive impairment and Alzheimer's disease.

Increased Sensitivity to Effects of Normal Aging and Alzheimer's Disease on Cortical Thickness by Adjustment for Local Variability in Gray/white Contrast: a Multi-sample MRI Study

MRI-based estimates of cerebral morphometric properties, e.g. cortical thickness, are pivotal to studies of normal and pathological brain changes. These measures are based on automated or manual segmentation procedures, which utilize the tissue contrast between gray and white matter on T(1)-weighted MR images. Tissue contrast is unlikely to remain a constant property across groups of different age and health. An important question is therefore how the sensitivity of cortical thickness estimates is influenced by variability in WM/GM contrast. The effect of adjusting for variability in WM/GM contrast on age sensitivity of cortical thickness was tested in 1189 healthy subjects from six different samples, enabling evaluation of consistency of effects within and between sites and scanners. Further, the influence of Alzheimer's disease (AD) diagnosis on cortical thickness with and without correction for contrast was tested in an additional sample of 96 patients. In healthy controls, regional increases in the sensitivity of the cortical thickness measure to age were found after correcting for contrast. Across samples, the strongest effects were observed in frontal, lateral temporal and parietal areas. Controlling for contrast variability also increased the cortical thickness estimates' sensitivity to AD, thus replicating the finding in an independent clinical sample. The results showed increased sensitivity of cortical estimates to AD in areas earlier reported to be compromised in AD, including medial temporal, inferior and superior parietal regions. In sum, the findings indicate that adjusting for contrast can increase the sensitivity of MR morphometry to variables of interest.

The Cortical Signature of Alzheimer's Disease: Regionally Specific Cortical Thinning Relates to Symptom Severity in Very Mild to Mild AD Dementia and is Detectable in Asymptomatic Amyloid-positive Individuals

Alzheimer's disease (AD) is associated with neurodegeneration in vulnerable limbic and heteromodal regions of the cerebral cortex, detectable in vivo using magnetic resonance imaging. It is not clear whether abnormalities of cortical anatomy in AD can be reliably measured across different subject samples, how closely they track symptoms, and whether they are detectable prior to symptoms. An exploratory map of cortical thinning in mild AD was used to define regions of interest that were applied in a hypothesis-driven fashion to other subject samples. Results demonstrate a reliably quantifiable in vivo signature of abnormal cortical anatomy in AD, which parallels known regional vulnerability to AD neuropathology. Thinning in vulnerable cortical regions relates to symptom severity even in the earliest stages of clinical symptoms. Furthermore, subtle thinning is present in asymptomatic older controls with brain amyloid binding as detected with amyloid imaging. The reliability and clinical validity of AD-related cortical thinning suggests potential utility as an imaging biomarker. This "disease signature" approach to cortical morphometry, in which disease effects are mapped across the cortical mantle and then used to define ROIs for hypothesis-driven analyses, may provide a powerful methodological framework for studies of neuropsychiatric diseases.

Segmental Brain Volumes and Cognitive and Perceptual Correlates in 15-year-old Adolescents with Low Birth Weight

To determine whether preterm very low birth weight (VLBW) or term born small for gestational age (SGA) adolescents have reduced regional brain volumes. We also asked which perinatal factors are related to reduced brain volume in VLBW adolescents, which regional brain volumes are associated with cognitive and perceptual functioning, and if these differ between the groups.

Spherical Demons: Fast Diffeomorphic Landmark-free Surface Registration

We present the Spherical Demons algorithm for registering two spherical images. By exploiting spherical vector spline interpolation theory, we show that a large class of regularizors for the modified Demons objective function can be efficiently approximated on the sphere using iterative smoothing. Based on one parameter subgroups of diffeomorphisms, the resulting registration is diffeomorphic and fast. The Spherical Demons algorithm can also be modified to register a given spherical image to a probabilistic atlas. We demonstrate two variants of the algorithm corresponding to warping the atlas or warping the subject. Registration of a cortical surface mesh to an atlas mesh, both with more than 160 k nodes requires less than 5 min when warping the atlas and less than 3 min when warping the subject on a Xeon 3.2 GHz single processor machine. This is comparable to the fastest nondiffeomorphic landmark-free surface registration algorithms. Furthermore, the accuracy of our method compares favorably to the popular FreeSurfer registration algorithm. We validate the technique in two different applications that use registration to transfer segmentation labels onto a new image 1) parcellation of in vivo cortical surfaces and 2) Brodmann area localization in ex vivo cortical surfaces.

Genetic and Environmental Influences on the Size of Specific Brain Regions in Midlife: the VETSA MRI Study

The impact of genetic and environmental factors on human brain structure is of great importance for understanding normative cognitive and brain aging as well as neuropsychiatric disorders. However, most studies of genetic and environmental influences on human brain structure have either focused on global measures or have had samples that were too small for reliable estimates. Using the classical twin design, we assessed genetic, shared environmental, and individual-specific environmental influences on individual differences in the size of 96 brain regions of interest (ROIs). Participants were 474 middle-aged male twins (202 pairs; 70 unpaired) in the Vietnam Era Twin Study of Aging (VETSA). They were 51-59 years old, and were similar to U.S. men in their age range in terms of sociodemographic and health characteristics. We measured thickness of cortical ROIs and volume of other ROIs. On average, genetic influences accounted for approximately 70% of the variance in the volume of global, subcortical, and ventricular ROIs and approximately 45% of the variance in the thickness of cortical ROIs. There was greater variability in the heritability of cortical ROIs (0.00-0.75) as compared with subcortical and ventricular ROIs (0.48-0.85). The results did not indicate lateralized heritability differences or greater genetic influences on the size of regions underlying higher cognitive functions. The findings provide key information for imaging genetic studies and other studies of brain phenotypes and endophenotypes. Longitudinal analysis will be needed to determine whether the degree of genetic and environmental influences changes for different ROIs from midlife to later life.

Altered White Matter Microstructure in the Corpus Callosum in Huntington's Disease: Implications for Cortical "disconnection"

The corpus callosum (CC) is the major conduit for information transfer between the cerebral hemispheres and plays an integral role in relaying sensory, motor and cognitive information between homologous cortical regions. The majority of fibers that make up the CC arise from large pyramidal neurons in layers III and V, which project contra-laterally. These neurons degenerate in Huntington's disease (HD) in a topographically and temporally selective way. Since any focus of cortical degeneration could be expected to secondarily de-afferent homologous regions of cortex, we hypothesized that regionally selective cortical degeneration would be reflected in regionally selective degeneration of the CC. We used conventional T1-weighted, diffusion tensor imaging (DTI), and a modified corpus callosum segmentation scheme to examine the CC in healthy controls, huntingtin gene-carriers and symptomatic HD subjects. We measured mid-sagittal callosal cross-sectional thickness and several DTI parameters, including fractional anisotropy (FA), which reflects the degree of white matter organization, radial diffusivity, a suggested index of myelin integrity, and axial diffusivity, a suggested index of axonal damage of the CC. We found a topologically selective pattern of alterations in these measures in pre-manifest subjects that were more extensive in early symptomatic HD subjects and that correlated with performance on distinct cognitive measures, suggesting an important role for disrupted inter-hemispheric transfer in the clinical symptoms of HD. Our findings provide evidence for early degeneration of commissural pyramidal neurons in the neocortex, loss of cortico-cortical connectivity, and functional compromise of associative cortical processing.

Cortical Thickness is Influenced by Regionally Specific Genetic Factors

Although global brain structure is highly heritable, there is still variability in the magnitude of genetic influences on the size of specific regions. Yet, little is known about the patterning of those genetic influences, i.e., whether the same genes influence structure throughout the brain or whether there are regionally specific sets of genes.

Impact of Breast Milk on Intelligence Quotient, Brain Size, and White Matter Development

Although observational findings linking breast milk to higher scores on cognitive tests may be confounded by factors associated with mothers' choice to breastfeed, it has been suggested that one or more constituents of breast milk facilitate cognitive development, particularly in preterms. Because cognitive scores are related to head size, we hypothesized that breast milk mediates cognitive effects by affecting brain growth. We used detailed data from a randomized feeding trial to calculate percentage of expressed maternal breast milk (%EBM) in the infant diet of 50 adolescents. MRI scans were obtained (mean age=15 y 9 mo), allowing volumes of total brain (TBV) and white and gray matter (WMV, GMV) to be calculated. In the total group, %EBM correlated significantly with verbal intelligence quotient (VIQ); in boys, with all IQ scores, TBV and WMV. VIQ was, in turn, correlated with WMV and, in boys only, additionally with TBV. No significant relationships were seen in girls or with gray matter. These data support the hypothesis that breast milk promotes brain development, particularly white matter growth. The selective effect in males accords with animal and human evidence regarding gender effects of early diet. Our data have important neurobiological and public health implications and identify areas for future mechanistic study.

Evaluation of Volume-based and Surface-based Brain Image Registration Methods

Establishing correspondences across brains for the purposes of comparison and group analysis is almost universally done by registering images to one another either directly or via a template. However, there are many registration algorithms to choose from. A recent evaluation of fully automated nonlinear deformation methods applied to brain image registration was restricted to volume-based methods. The present study is the first that directly compares some of the most accurate of these volume registration methods with surface registration methods, as well as the first study to compare registrations of whole-head and brain-only (de-skulled) images. We used permutation tests to compare the overlap or Hausdorff distance performance for more than 16,000 registrations between 80 manually labeled brain images. We compared every combination of volume-based and surface-based labels, registration, and evaluation. Our primary findings are the following: 1. de-skulling aids volume registration methods; 2. custom-made optimal average templates improve registration over direct pairwise registration; and 3. resampling volume labels on surfaces or converting surface labels to volumes introduces distortions that preclude a fair comparison between the highest ranking volume and surface registration methods using present resampling methods. From the results of this study, we recommend constructing a custom template from a limited sample drawn from the same or a similar representative population, using the same algorithm used for registering brains to the template.

Atlas Generation for Subcortical and Ventricular Structures with Its Applications in Shape Analysis

Atlas-driven morphometric analysis has received great attention for studying anatomical shape variation across clinical populations in neuroimaging research as it provides a local coordinate representation for understanding the family of anatomic observations. We present a procedure for generating atlas of subcortical and ventricular structures, including amygdala, hippocampus, caudate, putamen, globus pallidus, thalamus, and lateral ventricles, using the large deformation diffeomorphic metric atlas generation algorithm. The atlas was built based on manually labeled volumes of 41 subjects randomly selected from the database of Open Access Series of Imaging Studies (OASIS, 10 young adults, 10 middle-age adults, 10 healthy elders, and 11 patients with dementia). We show that the estimated atlas is representative of the population in terms of its metric distance to each individual subject in the population. In the application of detecting shape variations, using the estimated atlas may potentially increase statistical power in identifying group shape difference when comparing with using a single subject atlas. In shape-based classification, the metric distances between subjects and each of within-class estimated atlases construct a shape feature space, which allows for performing a variety of classification algorithms to distinguish anatomies.

Improved Tractography Alignment Using Combined Volumetric and Surface Registration

Previously we introduced an automated high-dimensional non-linear registration framework, CVS, that combines volumetric and surface-based alignment to achieve robust and accurate correspondence in both cortical and sub-cortical regions (Postelnicu et al., 2009). In this paper we show that using CVS to compute cross-subject alignment from anatomical images, then applying the previously computed alignment to diffusion weighted MRI images, outperforms state-of-the-art techniques for computing cross-subject alignment directly from the DWI data itself. Specifically, we show that CVS outperforms the alignment component of TBSS in terms of degree-of-alignment of manually labeled tract models for the uncinate fasciculus, the inferior longitudinal fasciculus and the corticospinal tract. In addition, we compare linear alignment using FLIRT based on either fractional anisotropy or anatomical volumes across-subjects, and find a comparable effect. Together these results imply a clear advantage to aligning anatomy as opposed to lower resolution DWI data even when the final goal is diffusion analysis.

Salivary Cortisol and Prefrontal Cortical Thickness in Middle-aged Men: A Twin Study

Although glucocorticoid receptors are highly expressed in the prefrontal cortex, the hippocampus remains the predominant focus in the literature examining relationships between cortisol and brain. We examined phenotypic and genetic associations of cortisol levels with the thickness of prefrontal and anterior cingulate cortex regions, and with hippocampal volume in a sample of 388 middle-aged male twins who were 51-59 years old. Small but significant negative phenotypic associations were found between cortisol levels and the thickness of left dorsolateral (superior frontal gyrus, left rostral middle frontal gyrus) and ventrolateral (pars opercularis, pars triangularis, pars orbitalis) prefrontal regions, and right dorsolateral (superior frontal gyrus) and medial orbital frontal cortex. Most of the associations remained significant after adjusting for general cognitive ability, cardiovascular risk factors, and depression. Bivariate genetic analyses suggested that some of the associations were primarily accounted for by shared genetic influences; that is, some of the genes that tend to result in increased cortisol levels also tend to result in reduced prefrontal cortical thickness. Aging has been associated with reduced efficiency of hypothalamic-pituitary-adrenal function, frontal lobe shrinkage, and increases in health problems, but our present data do not allow us to determine the direction of effects. Moreover, the degree or the direction of the observed associations and the extent of their shared genetic underpinnings may well change as these individuals age. Longitudinal assessments are underway to elucidate the direction of the associations and the genetic underpinnings of longitudinal phenotypes for changes in cortisol and brain morphology.

Selective Disruption of the Cerebral Neocortex in Alzheimer's Disease

Alzheimer's disease (AD) and its transitional state mild cognitive impairment (MCI) are characterized by amyloid plaque and tau neurofibrillary tangle (NFT) deposition within the cerebral neocortex and neuronal loss within the hippocampal formation. However, the precise relationship between pathologic changes in neocortical regions and hippocampal atrophy is largely unknown.

Laminar Analysis of 7T BOLD Using an Imposed Spatial Activation Pattern in Human V1

With sufficient image encoding, high-resolution fMRI studies are limited by the biological point-spread of the hemodynamic signal. The extent of this spread is determined by the local vascular distribution and by the spatial specificity of blood flow regulation, as well as by measurement parameters that (i) alter the relative sensitivity of the acquisition to activation-induced hemodynamic changes and (ii) determine the image contrast as a function of vessel size. In particular, large draining vessels on the cortical surface are a major contributor to both the BOLD signal change and to the spatial bias of the BOLD activation away from the site of neuronal activity. In this work, we introduce a laminar surface-based analysis method and study the relationship between spatial localization and activation strength as a function of laminar depth by acquiring 1mm isotropic, single-shot EPI at 7 T and sampling the BOLD signal exclusively from the superficial, middle, or deep cortical laminae. We show that highly-accelerated EPI can limit image distortions to the point where a boundary-based registration algorithm accurately aligns the EPI data to the surface reconstruction. The spatial spread of the BOLD response tangential to the cortical surface was analyzed as a function of cortical depth using our surface-based analysis. Although sampling near the pial surface provided the highest signal strength, it also introduced the most spatial error. Thus, avoiding surface laminae improved spatial localization by about 40% at a cost of 36% in z-statistic, implying that optimal spatial resolution in functional imaging of the cortex can be achieved using anatomically-informed spatial sampling to avoid large pial vessels.

Learning Task-optimal Registration Cost Functions for Localizing Cytoarchitecture and Function in the Cerebral Cortex

Image registration is typically formulated as an optimization problem with multiple tunable, manually set parameters. We present a principled framework for learning thousands of parameters of registration cost functions, such as a spatially-varying tradeoff between the image dissimilarity and regularization terms. Our approach belongs to the classic machine learning framework of model selection by optimization of cross-validation error. This second layer of optimization of cross-validation error over and above registration selects parameters in the registration cost function that result in good registration as measured by the performance of the specific application in a training data set. Much research effort has been devoted to developing generic registration algorithms, which are then specialized to particular imaging modalities, particular imaging targets and particular postregistration analyses. Our framework allows for a systematic adaptation of generic registration cost functions to specific applications by learning the "free" parameters in the cost functions. Here, we consider the application of localizing underlying cytoarchitecture and functional regions in the cerebral cortex by alignment of cortical folding. Most previous work assumes that perfectly registering the macro-anatomy also perfectly aligns the underlying cortical function even though macro-anatomy does not completely predict brain function. In contrast, we learn 1) optimal weights on different cortical folds or 2) optimal cortical folding template in the generic weighted sum of squared differences dissimilarity measure for the localization task. We demonstrate state-of-the-art localization results in both histological and functional magnetic resonance imaging data sets.

Automatic Parcellation of Human Cortical Gyri and Sulci Using Standard Anatomical Nomenclature

Precise localization of sulco-gyral structures of the human cerebral cortex is important for the interpretation of morpho-functional data, but requires anatomical expertise and is time consuming because of the brain's geometric complexity. Software developed to automatically identify sulco-gyral structures has improved substantially as a result of techniques providing topologically correct reconstructions permitting inflated views of the human brain. Here we describe a complete parcellation of the cortical surface using standard internationally accepted nomenclature and criteria. This parcellation is available in the FreeSurfer package. First, a computer-assisted hand parcellation classified each vertex as sulcal or gyral, and these were then subparcellated into 74 labels per hemisphere. Twelve datasets were used to develop rules and algorithms (reported here) that produced labels consistent with anatomical rules as well as automated computational parcellation. The final parcellation was used to build an atlas for automatically labeling the whole cerebral cortex. This atlas was used to label an additional 12 datasets, which were found to have good concordance with manual labels. This paper presents a precisely defined method for automatically labeling the cortical surface in standard terminology.

A Generative Model for Image Segmentation Based on Label Fusion

We propose a nonparametric, probabilistic model for the automatic segmentation of medical images, given a training set of images and corresponding label maps. The resulting inference algorithms rely on pairwise registrations between the test image and individual training images. The training labels are then transferred to the test image and fused to compute the final segmentation of the test subject. Such label fusion methods have been shown to yield accurate segmentation, since the use of multiple registrations captures greater inter-subject anatomical variability and improves robustness against occasional registration failures. To the best of our knowledge, this manuscript presents the first comprehensive probabilistic framework that rigorously motivates label fusion as a segmentation approach. The proposed framework allows us to compare different label fusion algorithms theoretically and practically. In particular, recent label fusion or multiatlas segmentation algorithms are interpreted as special cases of our framework. We conduct two sets of experiments to validate the proposed methods. In the first set of experiments, we use 39 brain MRI scans-with manually segmented white matter, cerebral cortex, ventricles and subcortical structures-to compare different label fusion algorithms and the widely-used FreeSurfer whole-brain segmentation tool. Our results indicate that the proposed framework yields more accurate segmentation than FreeSurfer and previous label fusion algorithms. In a second experiment, we use brain MRI scans of 282 subjects to demonstrate that the proposed segmentation tool is sufficiently sensitive to robustly detect hippocampal volume changes in a study of aging and Alzheimer's Disease.

Automated MRI Measures Predict Progression to Alzheimer's Disease

The prediction of individuals with mild cognitive impairment (MCI) destined to develop Alzheimer's disease (AD) is of increasing clinical importance. In this study, using baseline T1-weighted MRI scans of 324 MCI individuals from two cohorts and automated software tools, we employed factor analyses and Cox proportional hazards models to identify a set of neuroanatomic measures that best predicted the time to progress from MCI to AD. For comparison, cerebrospinal fluid (CSF) assessments of cellular pathology and positron emission tomography (PET) measures of metabolic activity were additionally examined. By 3 years follow-up, 60 MCI individuals from the first cohort and 58 MCI individuals from the second cohort had progressed to a diagnosis of AD. Cox models on the first cohort demonstrated significant effects for the medial temporal factor [Hazards Ratio (HR) = 0.43{95% confidence interval (CI), 0.32-0.55}, p < 0.0001], the fronto-parietoccipital factor [HR = 0.59{95% CI, 0.48-0.80}, p < 0.001], and the lateral temporal factor [HR = 0.67 {95% CI, 0.52-0.87}, p < 0.01]. When applied to the second cohort, these Cox models showed significant effects for the medial temporal factor [HR = 0.44 {0.32-0.61}, p < 0.001] and lateral temporal factor [HR = 0.49 {0.38-0.62}, p < 0.001]. In a combined Cox model, consisting of individual CSF, PET, and MRI measures that best predicted disease progression, only the medial temporal factor [HR = 0.53 {95% CI, 0.34-0.81}, p < 0.001] demonstrated a significant effect. These findings illustrate that automated MRI measures of the medial temporal cortex accurately and reliably predict time to disease progression, outperform cellular and metabolic measures as predictors of clinical decline, and can potentially serve as a predictive marker for AD.

Anatomical Atlas-guided Diffuse Optical Tomography of Brain Activation

We describe a neuroimaging protocol that utilizes an anatomical atlas of the human head to guide diffuse optical tomography of human brain activation. The protocol is demonstrated by imaging the hemodynamic response to median-nerve stimulation in three healthy subjects, and comparing the images obtained using a head atlas with the images obtained using the subject-specific head anatomy. The results indicate that using the head atlas anatomy it is possible to reconstruct the location of the brain activation to the expected gyrus of the brain, in agreement with the results obtained with the subject-specific head anatomy. The benefits of this novel method derive from eliminating the need for subject-specific head anatomy and thus obviating the need for a subject-specific MRI to improve the anatomical interpretation of diffuse optical tomography images of brain activation.

Direct Visualization of the Perforant Pathway in the Human Brain with Ex Vivo Diffusion Tensor Imaging

Ex vivo magnetic resonance imaging yields high resolution images that reveal detailed cerebral anatomy and explicit cytoarchitecture in the cerebral cortex, subcortical structures, and white matter in the human brain. Our data illustrate neuroanatomical correlates of limbic circuitry with high resolution images at high field. In this report, we have studied ex vivo medial temporal lobe samples in high resolution structural MRI and high resolution diffusion MRI. Structural and diffusion MRIs were registered to each other and to histological sections stained for myelin for validation of the perforant pathway. We demonstrate probability maps and fiber tracking from diffusion tensor data that allows the direct visualization of the perforant pathway. Although it is not possible to validate the DTI data with invasive measures, results described here provide an additional line of evidence of the perforant pathway trajectory in the human brain and that the perforant pathway may cross the hippocampal sulcus.

Evaluating the Validity of Volume-based and Surface-based Brain Image Registration for Developmental Cognitive Neuroscience Studies in Children 4 to 11 Years of Age

Understanding the neurophysiology of human cognitive development relies on methods that enable accurate comparison of structural and functional neuroimaging data across brains from people of different ages. A fundamental question is whether the substantial brain growth and related changes in brain morphology that occur in early childhood permit valid comparisons of brain structure and function across ages. Here we investigated whether valid comparisons can be made in children from ages 4 to 11, and whether there are differences in the use of volume-based versus surface-based registration approaches for aligning structural landmarks across these ages. Regions corresponding to the calcarine sulcus, central sulcus, and Sylvian fissure in both the hemispheres were manually labeled on T1-weighted structural magnetic resonance images from 31 children ranging in age from 4.2 to 11.2years old. Quantitative measures of shape similarity and volumetric-overlap of these manually labeled regions were calculated when brains were aligned using a 12-parameter affine transform, SPM's nonlinear normalization, a diffeomorphic registration (ANTS), and FreeSurfer's surface-based registration. Registration error for normalization into a common reference framework across participants in this age range was lower than commonly used functional imaging resolutions. Surface-based registration provided significantly better alignment of cortical landmarks than volume-based registration. In addition, registering children's brains to a common space does not result in an age-associated bias between older and younger children, making it feasible to accurately compare structural properties and patterns of brain activation in children from ages 4 to 11.

Highly Accurate Inverse Consistent Registration: a Robust Approach

The registration of images is a task that is at the core of many applications in computer vision. In computational neuroimaging where the automated segmentation of brain structures is frequently used to quantify change, a highly accurate registration is necessary for motion correction of images taken in the same session, or across time in longitudinal studies where changes in the images can be expected. This paper, inspired by Nestares and Heeger (2000), presents a method based on robust statistics to register images in the presence of differences, such as jaw movement, differential MR distortions and true anatomical change. The approach we present guarantees inverse consistency (symmetry), can deal with different intensity scales and automatically estimates a sensitivity parameter to detect outlier regions in the images. The resulting registrations are highly accurate due to their ability to ignore outlier regions and show superior robustness with respect to noise, to intensity scaling and outliers when compared to state-of-the-art registration tools such as FLIRT (in FSL) or the coregistration tool in SPM.

Toward Implementing an MRI-based PET Attenuation-correction Method for Neurologic Studies on the MR-PET Brain Prototype

Several factors have to be considered for implementing an accurate attenuation-correction (AC) method in a combined MR-PET scanner. In this work, some of these challenges were investigated, and an AC method based entirely on the MRI data obtained with a single dedicated sequence was developed and used for neurologic studies performed with the MR-PET human brain scanner prototype.

Genetic Patterns of Correlation Among Subcortical Volumes in Humans: Results from a Magnetic Resonance Imaging Twin Study

Little is known about genetic influences on the volume of subcortical brain structures in adult humans, particularly whether there is regional specificity of genetic effects. Understanding patterns of genetic covariation among volumes of subcortical structures may provide insight into the development of individual differences that have consequences for cognitive and emotional behavior and neuropsychiatric disease liability. We measured the volume of 19 subcortical structures (including brain and ventricular regions) in 404 twins (110 monozygotic and 92 dizygotic pairs) from the Vietnam Era Twin Study of Aging and calculated the degree of genetic correlation among these volumes. We then examined the patterns of genetic correlation through hierarchical cluster analysis and by principal components analysis. We found that a model with four genetic factors best fit the data: a Basal Ganglia/Thalamus factor; a Ventricular factor; a Limbic factor; and a Nucleus Accumbens factor. Homologous regions from each hemisphere loaded on the same factors. The observed patterns of genetic correlation suggest the influence of multiple genetic influences. There is a genetic organization among structures which distinguishes between brain and cerebrospinal fluid spaces and between different subcortical regions. Further study is needed to understand this genetic patterning and whether it reflects influences on early development, functionally dependent patterns of growth or pruning, or regionally specific losses due to genes involved in aging, stress response, or disease.

Thickness of the Human Cerebral Cortex is Associated with Metrics of Cerebrovascular Health in a Normative Sample of Community Dwelling Older Adults

We examined how wide ranges in levels of risk factors for cerebrovascular disease are associated with thickness of the human cerebral cortex in 115 individuals ages 43-83 with no cerebrovascular or neurologic history. Cerebrovascular risk factors included blood pressure, cholesterol, body mass index, creatinine, and diabetes-related factors. Variables were submitted into a principal components analysis that confirmed four orthogonal factors (blood pressure, cholesterol, cholesterol/metabolic and glucose). T1-weighted MRI was used to create models of the cortex for calculation of regional cortical thickness. Increasing blood pressure factor scores were associated with numerous regions of reduced thickness. Increasing glucose scores were modestly associated with areas of regionally decreased thickness. Increasing cholesterol scores, in contrast, were associated with thicker cortex across the whole brain. All findings were primarily independent of age. These results provide evidence that normal and moderately abnormal levels of parameters used to assess cerebrovascular health may impact brain structure, even in the absence of cerebrovascular disease. Our data have important implications for the clinical management of vascular health, as well as for what is currently conceptualized as "normal aging" as they suggest that subclinical levels of risk may impact cortical gray matter before a disease process is evident.

Brain Structure Correlates of Individual Differences in the Acquisition and Inhibition of Conditioned Fear

Research employing aversive conditioning paradigms has elucidated the neurocircuitry involved in acquiring and diminishing fear responses. However, the factors underlying individual differences in fear acquisition and inhibition are not presently well understood. In this study, we explored whether the magnitude of individuals' acquired fear responses and the modulation of these responses via 2 fear reduction methods were correlated with structural differences in brain regions involved in affective processing. Physiological and structural magnetic resonance imaging data were obtained from experiments exploring extinction retention and intentional cognitive regulation. Our results identified 2 regions in which individual variation in brain structure correlated with subjects' fear-related arousal. Confirming previous results, increased thickness in ventromedial prefrontal cortex was correlated with the degree of extinction retention. Additionally, subjects with greater thickness in the posterior insula exhibited larger conditioned responses during acquisition. The data suggest a trend toward a negative correlation between amygdala volume and fear acquisition magnitude. There was no significant correlation between fear reduction via cognitive regulation and thickness in our prefrontal regions of interest. Acquisition and regulation measures were uncorrelated, suggesting that while certain individuals may have a propensity toward increased expression of conditioned fear, these responses can be diminished via both extinction and cognitive regulation.

Avoiding Asymmetry-induced Bias in Longitudinal Image Processing

Longitudinal image processing procedures frequently transfer or pool information across time within subject, with the dual goals of reducing the variability and increasing the accuracy of the derived measures. In this note, we discuss common difficulties in longitudinal image processing, focusing on the introduction of bias, and describe the approaches we have taken to avoid them in the FreeSurfer longitudinal processing stream.

Genetic and Environmental Contributions to Regional Cortical Surface Area in Humans: a Magnetic Resonance Imaging Twin Study

Cortical surface area measures appear to be functionally relevant and distinct in etiology, development, and behavioral correlates compared with other size characteristics, such as cortical thickness. Little is known about genetic and environmental influences on individual differences in regional surface area in humans. Using a large sample of adult twins, we determined relative contributions of genes and environment on variations in regional cortical surface area as measured by magnetic resonance imaging before and after adjustment for genetic and environmental influences shared with total cortical surface area. We found high heritability for total surface area and, before adjustment, moderate heritability for regional surface areas. Compared with other lobes, heritability was higher for frontal lobe and lower for medial temporal lobe. After adjustment for total surface area, regionally specific genetic influences were substantially reduced, although still significant in most regions. Unlike other lobes, left frontal heritability remained high after adjustment. Thus, global and regionally specific genetic factors both influence cortical surface areas. These findings are broadly consistent with results from animal studies regarding the evolution and development of cortical patterning and may guide future research into specific environmental and genetic determinants of variation among humans in the surface area of particular regions.

Connectivity-based Segmentation of Human Amygdala Nuclei Using Probabilistic Tractography

The amygdala plays an important role in emotional and social functions, and amygdala dysfunction has been associated with multiple neuropsychiatric disorders, including autism, anxiety, and depression. Although the amygdala is composed of multiple anatomically and functionally distinct nuclei, typical structural magnetic resonance imaging (MRI) sequences are unable to discern them. Thus, functional MRI (fMRI) studies typically average the BOLD response over the entire structure, which reveals some aspects of amygdala function as a whole but does not distinguish the separate roles of specific nuclei in humans. We developed a method to segment the human amygdala into its four major nuclei using only diffusion-weighted imaging and connectivity patterns derived mainly from animal studies. We refer to this new method as Tractography-based Segmentation, or TractSeg. The segmentations derived from TractSeg were topographically similar to their corresponding amygdaloid nuclei, and were validated against a high-resolution scan in which the nucleic boundaries were visible. In addition, nuclei topography was consistent across subjects. TractSeg relies on short scan acquisitions and widely accessible software packages, making it attractive for use in healthy populations to explore normal amygdala nucleus function, as well as in clinical and pediatric populations. Finally, it paves the way for implementing this method in other anatomical regions which are also composed of functional subunits that are difficult to distinguish with standard structural MRI.

Amyloid-β Associated Cortical Thinning in Clinically Normal Elderly

Both amyloid-β (Aβ) deposition and brain atrophy are associated with Alzheimer's disease (AD) and the disease process likely begins many years before symptoms appear. We sought to determine whether clinically normal (CN) older individuals with Aβ deposition revealed by positron emission tomography (PET) imaging using Pittsburgh Compound B (PiB) also have evidence of both cortical thickness and hippocampal volume reductions in a pattern similar to that seen in AD.

A Tale of Two Factors: What Determines the Rate of Progression in Huntington's Disease? A Longitudinal MRI Study

Over the past several years, increased attention has been devoted to understanding regionally selective brain changes that occur in Huntington's disease and their relationships to phenotypic variability. Clinical progression is also heterogeneous, and although CAG repeat length influences age of onset, its role, if any, in progression has been less clear. We evaluated progression in Huntington's disease using a novel longitudinal magnetic resonance imaging analysis. Our hypothesis was that the rate of brain atrophy is influenced by the age of onset of Huntington's disease. We scanned 22 patients with Huntington's disease at approximately 1-year intervals; individuals were divided into 1 of 3 groups, determined by the relative age of onset. We found significant differences in the rates of atrophy of cortex, white matter, and subcortical structures; patients who developed symptoms earlier demonstrated the most rapid rates of atrophy compared with those who developed symptoms during middle age or more advanced age. Rates of cortical atrophy were topologically variable, with the most rapid changes occurring in sensorimotor, posterior frontal, and portions of the parietal cortex. There were no significant differences in the rates of atrophy in basal ganglia structures. Although both CAG repeat length and age influenced the rate of change in some regions, there was no significant correlation in many regions. Rates of regional brain atrophy seem to be influenced by the age of onset of Huntington's disease symptoms and are only partially explained by CAG repeat length. These findings suggest that other genetic, epigenetic, and environmental factors play important roles in neurodegeneration in Huntington's disease.

The Organization of the Human Cerebral Cortex Estimated by Intrinsic Functional Connectivity

Information processing in the cerebral cortex involves interactions among distributed areas. Anatomical connectivity suggests that certain areas form local hierarchical relations such as within the visual system. Other connectivity patterns, particularly among association areas, suggest the presence of large-scale circuits without clear hierarchical relations. In this study the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI. Data from 1,000 subjects were registered using surface-based alignment. A clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex. The results revealed local networks confined to sensory and motor cortices as well as distributed networks of association regions. Within the sensory and motor cortices, functional connectivity followed topographic representations across adjacent areas. In association cortex, the connectivity patterns often showed abrupt transitions between network boundaries. Focused analyses were performed to better understand properties of network connectivity. A canonical sensory-motor pathway involving primary visual area, putative middle temporal area complex (MT+), lateral intraparietal area, and frontal eye field was analyzed to explore how interactions might arise within and between networks. Results showed that adjacent regions of the MT+ complex demonstrate differential connectivity consistent with a hierarchical pathway that spans networks. The functional connectivity of parietal and prefrontal association cortices was next explored. Distinct connectivity profiles of neighboring regions suggest they participate in distributed networks that, while showing evidence for interactions, are embedded within largely parallel, interdigitated circuits. We conclude by discussing the organization of these large-scale cerebral networks in relation to monkey anatomy and their potential evolutionary expansion in humans to support cognition.

The Dynamics of Cortical and Hippocampal Atrophy in Alzheimer Disease

To characterize rates of regional Alzheimer disease (AD)-specific brain atrophy across the presymptomatic, mild cognitive impairment, and dementia stages.

Presence of ApoE ε4 Allele Associated with Thinner Frontal Cortex in Middle Age

The presence of an ApoE ε4 allele (ε4+) increases the risk of developing Alzheimer's disease (AD). Previous studies support an adverse relationship between ε4+ status and brain structure and function in mild cognitive impairment and AD; in contrast, the presence of an ε2 allele may be protective. Whether these findings reflect disease-related effects or pre-existing endophenotypes, however, remains unclear. The present study examined the influence of ApoE allele status on brain structure solely during middle-age in a large, national sample. Participants were 482 men, ages 51-59, from the Vietnam Era Twin Study of Aging (VETSA). T1-weighted images were used in volumetric segmentation and cortical surface reconstruction methods to measure regional volume and thickness. Primary linear mixed effects models predicted structural measures with ApoE status (ε3/3, ε2/3, ε3/4) and control variables for effects of site, non-independence of twin data, age, and average cranial vault or cortical thickness. Relative to the ε3/3 group, the ε3/4 group demonstrated significantly thinner cortex in superior frontal and left rostral and right caudal midfrontal regions; there were no significant effects of ε4 status on any temporal lobe measures. The ε2/3 group demonstrated significantly thicker right parahippocampal cortex relative to the ε3/3 group. The ApoE ε4 allele may influence cortical thickness in frontal areas, which are later developing regions thought to be more susceptible to the natural aging process. Previous conflicting findings for mesial temporal regions may be driven by the inclusion of older individuals, who may evidence preclinical manifestations of disease, and by unexamined moderators of ε4-related effects. The presence of the ε2 allele was related to thicker cortex, supporting a protective role. Ongoing follow-up of the VETSA sample may shed light on the potential for age- and disease-related mediation of the influence of ApoE allele status.

Atlas-based Segmentation for Globus Pallidus Internus Targeting on Low-resolution MRI

In this paper we report a method to automatically segment the internal part of globus pallidus (GPi) on the pre-operative low-resolution magnetic resonance images (MRIs) of patients affected by Parkinson's disease. Herein we used an ultra-high resolution human brain dataset as electronic atlas of reference on which we segmented the GPi. First, we registered the ultra-high resolution dataset on the low-resolution dataset using a landmarks-based rigid registration. Then an affine and a non-rigid surface-based registration guided by the structures that surround the target was applied in order to propagate the labels of the GPi on the low-resolution un-segmented dataset and to accurately outline the target. The mapping of the atlas on the low-resolution MRI provided a highly accurate anatomical detail that can be useful for localizing the target.

Automated Probabilistic Reconstruction of White-matter Pathways in Health and Disease Using an Atlas of the Underlying Anatomy

We have developed a method for automated probabilistic reconstruction of a set of major white-matter pathways from diffusion-weighted MR images. Our method is called TRACULA (TRActs Constrained by UnderLying Anatomy) and utilizes prior information on the anatomy of the pathways from a set of training subjects. By incorporating this prior knowledge in the reconstruction procedure, our method obviates the need for manual interaction with the tract solutions at a later stage and thus facilitates the application of tractography to large studies. In this paper we illustrate the application of the method on data from a schizophrenia study and investigate whether the inclusion of both patients and healthy subjects in the training set affects our ability to reconstruct the pathways reliably. We show that, since our method does not constrain the exact spatial location or shape of the pathways but only their trajectory relative to the surrounding anatomical structures, a set a of healthy training subjects can be used to reconstruct the pathways accurately in patients as well as in controls.

Genetic Influences on Cortical Regionalization in the Human Brain

Animal data demonstrate that the development of distinct cortical areas is influenced by genes that exhibit highly regionalized expression patterns. In this paper, we show genetic patterning of cortical surface area derived from MRI data from 406 adult human twins. We mapped genetic correlations of areal expansion between selected seed regions and all other cortical locations, with the selection of seed points based on results from animal studies. "Marching seeds" and a data-driven, hypothesis-free, fuzzy-clustering approach provided convergent validation. The results reveal strong anterior-to-posterior graded, bilaterally symmetric patterns of regionalization, largely consistent with patterns previously reported in nonhuman mammalian models. Broad similarities in genetic patterning between rodents and humans might suggest a conservation of cortical patterning mechanisms, whereas dissimilarities might reflect the functionalities most essential to each species.

The Association Between a Polygenic Alzheimer Score and Cortical Thickness in Clinically Normal Subjects

Late-onset Alzheimer's disease (AD) is 50-70% heritable with complex genetic underpinnings. In addition to Apoliprotein E (APOE) ε4, the major genetic risk factor, recent genome-wide association studies (GWAS) have identified a growing list of sequence variations associated with the disease. Building on a prior large-scale AD GWAS, we used a recently developed analytic method to compute a polygenic score that involves up to 26 independent common sequence variants and is associated with AD dementia, above and beyond APOE. We then examined the associations between the polygenic score and the magnetic resonance imaging-derived thickness measurements across AD-vulnerable cortex in clinically normal (CN) human subjects (N = 104). AD-specific cortical thickness was correlated with the polygenic risk score, even after controlling for APOE genotype and cerebrospinal fluid (CSF) levels of β-amyloid (Aβ(1-42)). Furthermore, the association remained significant in CN subjects with levels of CSF Aβ(1-)(42) in the normal range and in APOE ε3 homozygotes. The observation that genetic risk variants are associated with thickness across AD-vulnerable regions of interest in CN older individuals, suggests that the combination of polygenic risk profile, neuroimaging, and CSF biomarkers may hold synergistic potential to aid in the prediction of future cognitive decline.

Volumetric Navigators for Prospective Motion Correction and Selective Reacquisition in Neuroanatomical MRI

We introduce a novel method of prospectively compensating for subject motion in neuroanatomical imaging. Short three-dimensional echo-planar imaging volumetric navigators are embedded in a long three-dimensional sequence, and the resulting image volumes are registered to provide an estimate of the subject's location in the scanner at a cost of less than 500 ms, ∼ 1% change in contrast, and ∼3% change in intensity. This time fits well into the existing gaps in sequences routinely used for neuroimaging, thus giving a motion-corrected sequence with no extra time required. We also demonstrate motion-driven selective reacquisition of k-space to further compensate for subject motion. We perform multiple validation experiments to evaluate accuracy, navigator impact on tissue intensity/contrast, and the improvement in final output. The complete system operates without adding additional hardware to the scanner and requires no external calibration, making it suitable for high-throughput environments. Magn Reson Med, 2011. © 2011 Wiley Periodicals, Inc.

Consistent Neuroanatomical Age-related Volume Differences Across Multiple Samples

Magnetic resonance imaging (MRI) is the principal method for studying structural age-related brain changes in vivo. However, previous research has yielded inconsistent results, precluding understanding of structural changes of the aging brain. This inconsistency is due to methodological differences and/or different aging patterns across samples. To overcome these problems, we tested age effects on 17 different neuroanatomical structures and total brain volume across five samples, of which one was split to further investigate consistency (883 participants). Widespread age-related volume differences were seen consistently across samples. In four of the five samples, all structures, except the brainstem, showed age-related volume differences. The strongest and most consistent effects were found for cerebral cortex, pallidum, putamen and accumbens volume. Total brain volume, cerebral white matter, caudate, hippocampus and the ventricles consistently showed non-linear age functions. Healthy aging appears associated with more widespread and consistent age-related neuroanatomical volume differences than previously believed.

Heritability of Brain Ventricle Volume: Converging Evidence from Inconsistent Results

Twin studies generally show great consistency for the heritability of brain structures. Ironically, the lateral ventricles--perhaps the most reliably measured brain regions of interest--are the most inconsistent when it comes to estimating genetic influences on their volume. Heritability estimates in twin studies have ranged from zero to almost 0.80. Here we aggregate heritability estimates from extant twin studies, and we review and reinterpret some of the findings. Based on our revised estimates, we conclude that lateral ventricular volume is indeed heritable. The weighted average heritability of the revised estimates was 0.54. Although accumulated environmental insults might seem most logical as the predominant cause of age-related ventricular expansion, the data strongly suggest that genetic influences on lateral ventricular volume are increasing with age. Genetic influences accounted for 32-35% of the variance in lateral ventricular volume in childhood, but about 75% of the variance in late middle and older age. These conclusions have implications for the basic understanding of the genetic and environmental underpinnings of normative and pathological brain aging.

FreeSurfer

FreeSurfer is a suite of tools for the analysis of neuroimaging data that provides an array of algorithms to quantify the functional, connectional and structural properties of the human brain. It has evolved from a package primarily aimed at generating surface representations of the cerebral cortex into one that automatically creates models of most macroscopically visible structures in the human brain given any reasonable T1-weighted input image. It is freely available, runs on a wide variety of hardware and software platforms, and is open source.

Entorhinal Verrucae Geometry is Coincident and Correlates with Alzheimer's Lesions: a Combined Neuropathology and High-resolution Ex Vivo MRI Analysis

Entorhinal cortex displays a distinctive organization in layer II and forms small elevations on its surface called entorhinal verrucae. In Alzheimer's disease, the verrucae disappear due to neurofibrillary tangle formation and neuronal death. Isosurface models were reconstructed from high-resolution ex vivo MRI volumes scanned at 7.0 T and individual verruca were measured quantitatively for height, width, volume, and surface area on control and mild Alzheimer's cases. Mean verruca height was 0.13 ± 0.04 mm for our cognitively normal (controls) sample set whereas for mild AD samples mean height was 0.11 mm ± 0.05 mm (p < 0.001) in entorhinal cortex (n = 10 cases). These quantitative methods were validated by a significant correlation of verrucae height and volume with qualitative verrucae ratings (n = 36 cases). Entorhinal surfaces were significantly different from other cortical heights such as, cingulate, frontal, occipital, parietal and temporal cortices. Colocalization of verrucae with entorhinal islands was confirmed in ex vivo MRI and, moreover, verrucae ratings were negatively correlated to Braak and Braak pathological stage. This study characterizes novel methods to measure individual entorhinal verruca size, and shows that verrucae size correlates to Alzheimer's pathology. Taken together, these results suggest that verrucae may have the potential to serve as an early and specific morphological marker for mild cognitive impairment and Alzheimer's disease.

Genetic Influences on Hippocampal Volume Differ As a Function of Testosterone Level in Middle-aged Men

The hippocampus expresses a large number of androgen receptors; therefore, in men it is potentially vulnerable to the gradual age-related decline of testosterone levels. In the present study we sought to elucidate the nature of the relationship between testosterone and hippocampal volume in a sample of middle-aged male twins (average age 55.8 years). We found no evidence for a correlation between testosterone level and hippocampal volume, as well as no indication of shared genetic influences. However, a significant moderating effect of testosterone on the genetic and environmental determinants of hippocampal volume was observed. Genetic influences on hippocampal volume increased substantially as a function of increasing testosterone level, while environmental influences either decreased or remained stable. These findings provide evidence for an apparent gene-by-hormone interaction on hippocampal volume. To the best of our knowledge, this is the first study to demonstrate that the heritability of a brain structure in adults may be modified by an endogenous biological factor.

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