Diffusion tensor imaging (DTI) techniques provide information on the microstructural processes of the cerebral white matter (WM) in vivo. The present applications are designed to investigate differences of WM involvement patterns in different brain diseases, especially neurodegenerative disorders, by use of different DTI analyses in comparison with matched controls.
DTI data analysis is performed in a variate fashion, i.e. voxelwise comparison of regional diffusion direction-based metrics such as fractional anisotropy (FA), together with fiber tracking (FT) accompanied by tractwise fractional anisotropy statistics (TFAS) at the group level in order to identify differences in FA along WM structures, aiming at the definition of regional patterns of WM alterations at the group level. Transformation into a stereotaxic standard space is a prerequisite for group studies and requires thorough data processing to preserve directional inter-dependencies. The present applications show optimized technical approaches for this preservation of quantitative and directional information during spatial normalization in data analyses at the group level. On this basis, FT techniques can be applied to group averaged data in order to quantify metrics information as defined by FT. Additionally, application of DTI methods, i.e. differences in FA-maps after stereotaxic alignment, in a longitudinal analysis at an individual subject basis reveal information about the progression of neurological disorders. Further quality improvement of DTI based results can be obtained during preprocessing by application of a controlled elimination of gradient directions with high noise levels.
In summary, DTI is used to define a distinct WM pathoanatomy of different brain diseases by the combination of whole brain-based and tract-based DTI analysis.
25 Related JoVE Articles!
How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index
Institutions: University of Geneva School of Medicine, École Polytechnique Fédérale de Lausanne, University Hospital Center and University of Lausanne, Massachusetts General Hospital.
Cortical folding (gyrification) is determined during the first months of life, so that adverse events occurring during this period leave traces that will be identifiable at any age. As recently reviewed by Mangin and colleagues2
, several methods exist to quantify different characteristics of gyrification. For instance, sulcal morphometry can be used to measure shape descriptors such as the depth, length or indices of inter-hemispheric asymmetry3
. These geometrical properties have the advantage of being easy to interpret. However, sulcal morphometry tightly relies on the accurate identification of a given set of sulci and hence provides a fragmented description of gyrification. A more fine-grained quantification of gyrification can be achieved with curvature-based measurements, where smoothed absolute mean curvature is typically computed at thousands of points over the cortical surface4
. The curvature is however not straightforward to comprehend, as it remains unclear if there is any direct relationship between the curvedness and a biologically meaningful correlate such as cortical volume or surface. To address the diverse issues raised by the measurement of cortical folding, we previously developed an algorithm to quantify local gyrification with an exquisite spatial resolution and of simple interpretation. Our method is inspired of the Gyrification Index5
, a method originally used in comparative neuroanatomy to evaluate the cortical folding differences across species. In our implementation, which we name l
ocal Gyrification Index (l
), we measure the amount of cortex buried within the sulcal folds as compared with the amount of visible cortex in circular regions of interest. Given that the cortex grows primarily through radial expansion6
, our method was specifically designed to identify early defects of cortical development.
In this article, we detail the computation of local Gyrification Index, which is now freely distributed as a part of the FreeSurfer
Software (http://surfer.nmr.mgh.harvard.edu/, Martinos Center for Biomedical Imaging, Massachusetts General Hospital). FreeSurfer
provides a set of automated reconstruction tools of the brain's cortical surface from structural MRI data. The cortical surface extracted in the native space of the images with sub-millimeter accuracy is then further used for the creation of an outer surface, which will serve as a basis for the l
GI calculation. A circular region of interest is then delineated on the outer surface, and its corresponding region of interest on the cortical surface is identified using a matching algorithm as described in our validation study1
. This process is repeatedly iterated with largely overlapping regions of interest, resulting in cortical maps of gyrification for subsequent statistical comparisons (Fig. 1). Of note, another measurement of local gyrification with a similar inspiration was proposed by Toro and colleagues7
, where the folding index at each point is computed as the ratio of the cortical area contained in a sphere divided by the area of a disc with the same radius. The two implementations differ in that the one by Toro et al. is based on Euclidian distances and thus considers discontinuous patches of cortical area, whereas ours uses a strict geodesic algorithm and include only the continuous patch of cortical area opening at the brain surface in a circular region of interest.
Medicine, Issue 59, neuroimaging, brain, cortical complexity, cortical development
Adaptation of Semiautomated Circulating Tumor Cell (CTC) Assays for Clinical and Preclinical Research Applications
Institutions: London Health Sciences Centre, Western University, London Health Sciences Centre, Lawson Health Research Institute, Western University.
The majority of cancer-related deaths occur subsequent to the development of metastatic disease. This highly lethal disease stage is associated with the presence of circulating tumor cells (CTCs). These rare cells have been demonstrated to be of clinical significance in metastatic breast, prostate, and colorectal cancers. The current gold standard in clinical CTC detection and enumeration is the FDA-cleared CellSearch system (CSS). This manuscript outlines the standard protocol utilized by this platform as well as two additional adapted protocols that describe the detailed process of user-defined marker optimization for protein characterization of patient CTCs and a comparable protocol for CTC capture in very low volumes of blood, using standard CSS reagents, for studying in vivo
preclinical mouse models of metastasis. In addition, differences in CTC quality between healthy donor blood spiked with cells from tissue culture versus patient blood samples are highlighted. Finally, several commonly discrepant items that can lead to CTC misclassification errors are outlined. Taken together, these protocols will provide a useful resource for users of this platform interested in preclinical and clinical research pertaining to metastasis and CTCs.
Medicine, Issue 84, Metastasis, circulating tumor cells (CTCs), CellSearch system, user defined marker characterization, in vivo, preclinical mouse model, clinical research
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Institutions: The Feinstein Institute for Medical Research.
The scaled subprofile model (SSM)1-4
is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1
). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance patterns and corresponding subject scores. Each pattern, termed a group invariant subprofile (GIS), is an orthogonal principal component that represents a spatially distributed network of functionally interrelated brain regions. Large global mean scalar effects that can obscure smaller network-specific contributions are removed by the inherent logarithmic conversion and mean centering of the data2,5,6
. Subjects express each of these patterns to a variable degree represented by a simple scalar score that can correlate with independent clinical or psychometric descriptors7,8
. Using logistic regression analysis of subject scores (i.e.
pattern expression values), linear coefficients can be derived to combine multiple principal components into single disease-related spatial covariance patterns, i.e.
composite networks with improved discrimination of patients from healthy control subjects5,6
. Cross-validation within the derivation set can be performed using bootstrap resampling techniques9
. Forward validation is easily confirmed by direct score evaluation of the derived patterns in prospective datasets10
. Once validated, disease-related patterns can be used to score individual patients with respect to a fixed reference sample, often the set of healthy subjects that was used (with the disease group) in the original pattern derivation11
. These standardized values can in turn be used to assist in differential diagnosis12,13
and to assess disease progression and treatment effects at the network level7,14-16
. We present an example of the application of this methodology to FDG PET data of Parkinson's Disease patients and normal controls using our in-house software to derive a characteristic covariance pattern biomarker of disease.
Medicine, Issue 76, Neurobiology, Neuroscience, Anatomy, Physiology, Molecular Biology, Basal Ganglia Diseases, Parkinsonian Disorders, Parkinson Disease, Movement Disorders, Neurodegenerative Diseases, PCA, SSM, PET, imaging biomarkers, functional brain imaging, multivariate spatial covariance analysis, global normalization, differential diagnosis, PD, brain, imaging, clinical techniques
Fabrication And Characterization Of Photonic Crystal Slow Light Waveguides And Cavities
Institutions: University of St Andrews.
Slow light has been one of the hot topics in the photonics community in the past decade, generating great interest both from a fundamental point of view and for its considerable potential for practical applications. Slow light photonic crystal waveguides, in particular, have played a major part and have been successfully employed for delaying optical signals1-4
and the enhancement of both linear5-7
and nonlinear devices.8-11
Photonic crystal cavities achieve similar effects to that of slow light waveguides, but over a reduced band-width. These cavities offer high Q-factor/volume ratio, for the realization of optically12
pumped ultra-low threshold lasers and the enhancement of nonlinear effects.14-16
Furthermore, passive filters17
have been demonstrated, exhibiting ultra-narrow line-width, high free-spectral range and record values of low energy consumption.
To attain these exciting results, a robust repeatable fabrication protocol must be developed. In this paper we take an in-depth look at our fabrication protocol which employs electron-beam lithography for the definition of photonic crystal patterns and uses wet and dry etching techniques. Our optimised fabrication recipe results in photonic crystals that do not suffer from vertical asymmetry and exhibit very good edge-wall roughness. We discuss the results of varying the etching parameters and the detrimental effects that they can have on a device, leading to a diagnostic route that can be taken to identify and eliminate similar issues.
The key to evaluating slow light waveguides is the passive characterization of transmission and group index spectra. Various methods have been reported, most notably resolving the Fabry-Perot fringes of the transmission spectrum20-21
and interferometric techniques.22-25
Here, we describe a direct, broadband measurement technique combining spectral interferometry with Fourier transform analysis.26
Our method stands out for its simplicity and power, as we can characterise a bare photonic crystal with access waveguides, without need for on-chip interference components, and the setup only consists of a Mach-Zehnder interferometer, with no need for moving parts and delay scans.
When characterising photonic crystal cavities, techniques involving internal sources21
or external waveguides directly coupled to the cavity27
impact on the performance of the cavity itself, thereby distorting the measurement. Here, we describe a novel and non-intrusive technique that makes use of a cross-polarised probe beam and is known as resonant scattering (RS), where the probe is coupled out-of plane into the cavity through an objective. The technique was first demonstrated by McCutcheon et al.28
and further developed by Galli et al.29
Physics, Issue 69, Optics and Photonics, Astronomy, light scattering, light transmission, optical waveguides, photonics, photonic crystals, Slow-light, Cavities, Waveguides, Silicon, SOI, Fabrication, Characterization
Cortical Source Analysis of High-Density EEG Recordings in Children
Institutions: UCL Institute of Child Health, University College London.
EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and signal processing make it possible to exploit information from other imaging modalities like structural MRI that provide high spatial resolution to overcome this constraint1
. This is especially useful for investigations that require high resolution in the temporal as well as spatial domain. In addition, due to the easy application and low cost of EEG recordings, EEG is often the method of choice when working with populations, such as young children, that do not tolerate functional MRI scans well. However, in order to investigate which neural substrates are involved, anatomical information from structural MRI is still needed. Most EEG analysis packages work with standard head models that are based on adult anatomy. The accuracy of these models when used for children is limited2
, because the composition and spatial configuration of head tissues changes dramatically over development3
In the present paper, we provide an overview of our recent work in utilizing head models based on individual structural MRI scans or age specific head models to reconstruct the cortical generators of high density EEG. This article describes how EEG recordings are acquired, processed, and analyzed with pediatric populations at the London Baby Lab, including laboratory setup, task design, EEG preprocessing, MRI processing, and EEG channel level and source analysis.
Behavior, Issue 88, EEG, electroencephalogram, development, source analysis, pediatric, minimum-norm estimation, cognitive neuroscience, event-related potentials
Studying Food Reward and Motivation in Humans
Institutions: University of Cambridge, University of Cambridge, University of Cambridge, Addenbrooke's Hospital.
A key challenge in studying reward processing in humans is to go beyond subjective self-report measures and quantify different aspects of reward such as hedonics, motivation, and goal value in more objective ways. This is particularly relevant for the understanding of overeating and obesity as well as their potential treatments. In this paper are described a set of measures of food-related motivation using handgrip force as a motivational measure. These methods can be used to examine changes in food related motivation with metabolic (satiety) and pharmacological manipulations and can be used to evaluate interventions targeted at overeating and obesity. However to understand food-related decision making in the complex food environment it is essential to be able to ascertain the reward goal values that guide the decisions and behavioral choices that people make. These values are hidden but it is possible to ascertain them more objectively using metrics such as the willingness to pay and a method for this is described. Both these sets of methods provide quantitative measures of motivation and goal value that can be compared within and between individuals.
Behavior, Issue 85, Food reward, motivation, grip force, willingness to pay, subliminal motivation
Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
Institutions: University of Zurich.
Mori's Uncanny Valley Hypothesis1,2
proposes that the perception of humanlike characters such as robots and, by extension, avatars (computer-generated characters) can evoke negative or positive affect (valence) depending on the object's degree of visual and behavioral realism along a dimension of human likeness
) (Figure 1
). But studies of affective valence of subjective responses to variously realistic non-human characters have produced inconsistent findings 3, 4, 5, 6
. One of a number of reasons for this is that human likeness is not perceived as the hypothesis assumes. While the DHL can be defined following Mori's description as a smooth linear change in the degree of physical humanlike similarity, subjective perception of objects along the DHL can be understood in terms of the psychological effects of categorical perception (CP) 7
. Further behavioral and neuroimaging investigations of category processing and CP along the DHL and of the potential influence of the dimension's underlying category structure on affective experience are needed. This protocol therefore focuses on the DHL and allows examination of CP. Based on the protocol presented in the video as an example, issues surrounding the methodology in the protocol and the use in "uncanny" research of stimuli drawn from morph continua to represent the DHL are discussed in the article that accompanies the video. The use of neuroimaging and morph stimuli to represent the DHL in order to disentangle brain regions neurally responsive to physical human-like similarity from those responsive to category change and category processing is briefly illustrated.
Behavior, Issue 76, Neuroscience, Neurobiology, Molecular Biology, Psychology, Neuropsychology, uncanny valley, functional magnetic resonance imaging, fMRI, categorical perception, virtual reality, avatar, human likeness, Mori, uncanny valley hypothesis, perception, magnetic resonance imaging, MRI, imaging, clinical techniques
A Comprehensive Protocol for Manual Segmentation of the Medial Temporal Lobe Structures
Institutions: University of Illinois Urbana-Champaign, University of Illinois Urbana-Champaign, University of Illinois Urbana-Champaign.
The present paper describes a comprehensive protocol for manual tracing of the set of brain regions comprising the medial temporal lobe (MTL): amygdala, hippocampus, and the associated parahippocampal regions (perirhinal, entorhinal, and parahippocampal proper). Unlike most other tracing protocols available, typically focusing on certain MTL areas (e.g.
, amygdala and/or hippocampus), the integrative perspective adopted by the present tracing guidelines allows for clear localization of all MTL subregions. By integrating information from a variety of sources, including extant tracing protocols separately targeting various MTL structures, histological reports, and brain atlases, and with the complement of illustrative visual materials, the present protocol provides an accurate, intuitive, and convenient guide for understanding the MTL anatomy. The need for such tracing guidelines is also emphasized by illustrating possible differences between automatic and manual segmentation protocols. This knowledge can be applied toward research involving not only structural MRI investigations but also structural-functional colocalization and fMRI signal extraction from anatomically defined ROIs, in healthy and clinical groups alike.
Neuroscience, Issue 89, Anatomy, Segmentation, Medial Temporal Lobe, MRI, Manual Tracing, Amygdala, Hippocampus, Perirhinal Cortex, Entorhinal Cortex, Parahippocampal Cortex
The Use of Magnetic Resonance Spectroscopy as a Tool for the Measurement of Bi-hemispheric Transcranial Electric Stimulation Effects on Primary Motor Cortex Metabolism
Institutions: University of Montréal, McGill University, University of Minnesota.
Transcranial direct current stimulation (tDCS) is a neuromodulation technique that has been increasingly used over the past decade in the treatment of neurological and psychiatric disorders such as stroke and depression. Yet, the mechanisms underlying its ability to modulate brain excitability to improve clinical symptoms remains poorly understood 33
. To help improve this understanding, proton magnetic resonance spectroscopy (1
H-MRS) can be used as it allows the in vivo
quantification of brain metabolites such as γ-aminobutyric acid (GABA) and glutamate in a region-specific manner 41
. In fact, a recent study demonstrated that 1
H-MRS is indeed a powerful means to better understand the effects of tDCS on neurotransmitter concentration 34
. This article aims to describe the complete protocol for combining tDCS (NeuroConn MR compatible stimulator) with 1
H-MRS at 3 T using a MEGA-PRESS sequence. We will describe the impact of a protocol that has shown great promise for the treatment of motor dysfunctions after stroke, which consists of bilateral stimulation of primary motor cortices 27,30,31
. Methodological factors to consider and possible modifications to the protocol are also discussed.
Neuroscience, Issue 93, proton magnetic resonance spectroscopy, transcranial direct current stimulation, primary motor cortex, GABA, glutamate, stroke
Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly
Institutions: Sunnybrook Health Sciences Centre, University of Toronto.
Obtaining in vivo
human brain tissue volumetrics from MRI is often complicated by various technical and biological issues. These challenges are exacerbated when significant brain atrophy and age-related white matter changes (e.g.
Leukoaraiosis) are present. Lesion Explorer (LE) is an accurate and reliable neuroimaging pipeline specifically developed to address such issues commonly observed on MRI of Alzheimer's disease and normal elderly. The pipeline is a complex set of semi-automatic procedures which has been previously validated in a series of internal and external reliability tests1,2
. However, LE's accuracy and reliability is highly dependent on properly trained manual operators to execute commands, identify distinct anatomical landmarks, and manually edit/verify various computer-generated segmentation outputs.
LE can be divided into 3 main components, each requiring a set of commands and manual operations: 1) Brain-Sizer, 2) SABRE, and 3) Lesion-Seg. Brain-Sizer's manual operations involve editing of the automatic skull-stripped total intracranial vault (TIV) extraction mask, designation of ventricular cerebrospinal fluid (vCSF), and removal of subtentorial structures. The SABRE component requires checking of image alignment along the anterior and posterior commissure (ACPC) plane, and identification of several anatomical landmarks required for regional parcellation. Finally, the Lesion-Seg component involves manual checking of the automatic lesion segmentation of subcortical hyperintensities (SH) for false positive errors.
While on-site training of the LE pipeline is preferable, readily available visual teaching tools with interactive training images are a viable alternative. Developed to ensure a high degree of accuracy and reliability, the following is a step-by-step, video-guided, standardized protocol for LE's manual procedures.
Medicine, Issue 86, Brain, Vascular Diseases, Magnetic Resonance Imaging (MRI), Neuroimaging, Alzheimer Disease, Aging, Neuroanatomy, brain extraction, ventricles, white matter hyperintensities, cerebrovascular disease, Alzheimer disease
Training Synesthetic Letter-color Associations by Reading in Color
Institutions: University of Amsterdam.
Synesthesia is a rare condition in which a stimulus from one modality automatically and consistently triggers unusual sensations in the same and/or other modalities. A relatively common and well-studied type is grapheme-color synesthesia, defined as the consistent experience of color when viewing, hearing and thinking about letters, words and numbers. We describe our method for investigating to what extent synesthetic associations between letters and colors can be learned by reading in color in nonsynesthetes. Reading in color is a special method for training associations in the sense that the associations are learned implicitly while the reader reads text as he or she normally would and it does not require explicit computer-directed training methods. In this protocol, participants are given specially prepared books to read in which four high-frequency letters are paired with four high-frequency colors. Participants receive unique sets of letter-color pairs based on their pre-existing preferences for colored letters. A modified Stroop task is administered before and after reading in order to test for learned letter-color associations and changes in brain activation. In addition to objective testing, a reading experience questionnaire is administered that is designed to probe for differences in subjective experience. A subset of questions may predict how well an individual learned the associations from reading in color. Importantly, we are not claiming that this method will cause each individual to develop grapheme-color synesthesia, only that it is possible for certain individuals to form letter-color associations by reading in color and these associations are similar in some aspects to those seen in developmental grapheme-color synesthetes. The method is quite flexible and can be used to investigate different aspects and outcomes of training synesthetic associations, including learning-induced changes in brain function and structure.
Behavior, Issue 84, synesthesia, training, learning, reading, vision, memory, cognition
Developing Neuroimaging Phenotypes of the Default Mode Network in PTSD: Integrating the Resting State, Working Memory, and Structural Connectivity
Institutions: Alpert Medical School, Brown University, University of Georgia.
Complementary structural and functional neuroimaging techniques used to examine the Default Mode Network (DMN) could potentially improve assessments of psychiatric illness severity and provide added validity to the clinical diagnostic process. Recent neuroimaging research suggests that DMN processes may be disrupted in a number of stress-related psychiatric illnesses, such as posttraumatic stress disorder (PTSD).
Although specific DMN functions remain under investigation, it is generally thought to be involved in introspection and self-processing. In healthy individuals it exhibits greatest activity during periods of rest, with less activity, observed as deactivation, during cognitive tasks, e.g.
, working memory. This network consists of the medial prefrontal cortex, posterior cingulate cortex/precuneus, lateral parietal cortices and medial temporal regions.
Multiple functional and structural imaging approaches have been developed to study the DMN. These have unprecedented potential to further the understanding of the function and dysfunction of this network. Functional approaches, such as the evaluation of resting state connectivity and task-induced deactivation, have excellent potential to identify targeted neurocognitive and neuroaffective (functional) diagnostic markers and may indicate illness severity and prognosis with increased accuracy or specificity. Structural approaches, such as evaluation of morphometry and connectivity, may provide unique markers of etiology and long-term outcomes. Combined, functional and structural methods provide strong multimodal, complementary and synergistic approaches to develop valid DMN-based imaging phenotypes in stress-related psychiatric conditions. This protocol aims to integrate these methods to investigate DMN structure and function in PTSD, relating findings to illness severity and relevant clinical factors.
Medicine, Issue 89, default mode network, neuroimaging, functional magnetic resonance imaging, diffusion tensor imaging, structural connectivity, functional connectivity, posttraumatic stress disorder
Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
Institutions: University of Pennsylvania.
It is now appreciated that condition-relevant information can be present within distributed patterns of functional magnetic resonance imaging (fMRI) brain activity, even for conditions with similar levels of univariate activation. Multi-voxel pattern (MVP) analysis has been used to decode this information with great success. FMRI investigators also often seek to understand how brain regions interact in interconnected networks, and use functional connectivity (FC) to identify regions that have correlated responses over time. Just as univariate analyses can be insensitive to information in MVPs, FC may not fully characterize the brain networks that process conditions with characteristic MVP signatures. The method described here, informational connectivity (IC), can identify regions with correlated changes in MVP-discriminability across time, revealing connectivity that is not accessible to FC. The method can be exploratory, using searchlights to identify seed-connected areas, or planned, between pre-selected regions-of-interest. The results can elucidate networks of regions that process MVP-related conditions, can breakdown MVPA searchlight maps into separate networks, or can be compared across tasks and patient groups.
Neuroscience, Issue 89, fMRI, MVPA, connectivity, informational connectivity, functional connectivity, networks, multi-voxel pattern analysis, decoding, classification, method, multivariate
Magnetic Resonance Imaging Quantification of Pulmonary Perfusion using Calibrated Arterial Spin Labeling
Institutions: University of California San Diego - UCSD, University of California San Diego - UCSD, University of California San Diego - UCSD.
This demonstrates a MR imaging method to measure the spatial distribution of pulmonary blood flow in healthy subjects
during normoxia (inspired O2
, fraction (FI
) = 0.21) hypoxia (FI
= 0.125), and hyperoxia
= 1.00). In addition, the physiological responses of the subject are monitored in the MR scan environment. MR images
were obtained on a 1.5 T GE MRI scanner during a breath hold from a sagittal slice in the right lung at functional residual capacity. An arterial
spin labeling sequence (ASL-FAIRER) was used to measure the spatial distribution of pulmonary blood flow 1,2
and a multi-echo fast
gradient echo (mGRE) sequence 3
was used to quantify the regional proton (i.e. H2
O) density, allowing the quantification
of density-normalized perfusion for each voxel (milliliters blood per minute per gram lung tissue).
With a pneumatic switching valve and facemask equipped with a 2-way non-rebreathing valve, different oxygen concentrations
were introduced to the subject in the MR scanner through the inspired gas tubing. A metabolic cart collected expiratory gas via expiratory tubing. Mixed expiratory O2
concentrations, oxygen consumption, carbon dioxide production, respiratory exchange ratio,
respiratory frequency and tidal volume were measured. Heart rate and oxygen saturation were monitored using pulse-oximetry.
Data obtained from a normal subject showed that, as expected, heart rate was higher in hypoxia (60 bpm) than during normoxia (51) or hyperoxia (50) and the arterial oxygen saturation (SpO2
) was reduced during hypoxia to 86%. Mean ventilation was 8.31 L/min BTPS during hypoxia, 7.04 L/min during normoxia, and 6.64 L/min during hyperoxia. Tidal volume was 0.76 L during hypoxia, 0.69 L during normoxia, and 0.67 L during hyperoxia.
Representative quantified ASL data showed that the mean density normalized perfusion was 8.86 ml/min/g during hypoxia, 8.26 ml/min/g during normoxia and 8.46 ml/min/g during hyperoxia, respectively. In this subject, the relative dispersion4
, an index of global heterogeneity, was increased in hypoxia (1.07 during hypoxia, 0.85 during normoxia, and 0.87 during hyperoxia) while the fractal dimension (Ds), another index of heterogeneity reflecting vascular branching structure, was unchanged (1.24 during hypoxia, 1.26 during normoxia, and 1.26 during hyperoxia).
Overview. This protocol will demonstrate the acquisition of data to measure the distribution of pulmonary perfusion noninvasively under conditions of normoxia, hypoxia, and hyperoxia using a magnetic resonance imaging technique known as arterial spin labeling (ASL).
Rationale: Measurement of pulmonary blood flow and lung proton density using MR technique offers high spatial resolution images which can be quantified and the ability to perform repeated measurements under several different physiological conditions. In human studies, PET, SPECT, and CT are commonly used as the alternative techniques. However, these techniques involve exposure to ionizing radiation, and thus are not suitable for repeated measurements in human subjects.
Medicine, Issue 51, arterial spin labeling, lung proton density, functional lung imaging, hypoxic pulmonary vasoconstriction, oxygen consumption, ventilation, magnetic resonance imaging
Investigating the Neural Mechanisms of Aware and Unaware Fear Memory with fMRI
Institutions: University of Alabama at Birmingham.
Pavlovian fear conditioning is often used in combination with functional magnetic resonance imaging (fMRI) in humans to investigate the neural substrates of associative learning 1-5
. In these studies, it is important to provide behavioral evidence of conditioning to verify that differences in brain activity are learning-related and correlated with human behavior.
Fear conditioning studies often monitor autonomic responses (e.g. skin conductance response; SCR) as an index of learning and memory 6-8
. In addition, other behavioral measures can provide valuable information about the learning process and/or other cognitive functions that influence conditioning. For example, the impact unconditioned stimulus (UCS) expectancies have on the expression of the conditioned response (CR) and unconditioned response (UCR) has been a topic of interest in several recent studies 9-14
. SCR and UCS expectancy measures have recently been used in conjunction with fMRI to investigate the neural substrates of aware and unaware fear learning and memory processes 15
. Although these cognitive processes can be evaluated to some degree following the conditioning session, post-conditioning assessments cannot measure expectations on a trial-to-trial basis and are susceptible to interference and forgetting, as well as other factors that may distort results 16,17
Monitoring autonomic and behavioral responses simultaneously with fMRI provides a mechanism by which the neural substrates that mediate complex relationships between cognitive processes and behavioral/autonomic responses can be assessed. However, monitoring autonomic and behavioral responses in the MRI environment poses a number of practical problems. Specifically, 1) standard behavioral and physiological monitoring equipment is constructed of ferrous material that cannot be safely used near the MRI scanner, 2) when this equipment is placed outside of the MRI scanning chamber, the cables projecting to the subject can carry RF noise that produces artifacts in brain images, 3) artifacts can be produced within the skin conductance signal by switching gradients during scanning, 4) the fMRI signal produced by the motor demands of behavioral responses may need to be distinguished from activity related to the cognitive processes of interest. Each of these issues can be resolved with modifications to the setup of physiological monitoring equipment and additional data analysis procedures. Here we present a methodology to simultaneously monitor autonomic and behavioral responses during fMRI, and demonstrate the use of these methods to investigate aware and unaware memory processes during fear conditioning.
Neuroscience, Issue 56, fMRI, conditioning, learning, memory, fear, contingency awareness, neuroscience, skin conductance
Simultaneous fMRI and Electrophysiology in the Rodent Brain
Institutions: Emory University, Georgia Institute of Technology, Emory University.
To examine the neural basis of the blood oxygenation level dependent (BOLD) magnetic resonance imaging (MRI) signal, we have developed a rodent model in which functional MRI data and in vivo
intracortical recording can be performed simultaneously. The combination of MRI and electrical recording is technically challenging because the electrodes used for recording distort the MRI images and the MRI acquisition induces noise in the electrical recording. To minimize the mutual interference of the two modalities, glass microelectrodes were used rather than metal and a noise removal algorithm was implemented for the electrophysiology data. In our studies, two microelectrodes were separately implanted in bilateral primary somatosensory cortices (SI) of the rat and fixed in place. One coronal slice covering the electrode tips was selected for functional MRI. Electrode shafts and fixation positions were not included in the image slice to avoid imaging artifacts. The removed scalp was replaced with toothpaste to reduce susceptibility mismatch and prevent Gibbs ringing artifacts in the images. The artifact structure induced in the electrical recordings by the rapidly-switching magnetic fields during image acquisition was characterized by averaging all cycles of scans for each run. The noise structure during imaging was then subtracted from original recordings. The denoised time courses were then used for further analysis in combination with the fMRI data. As an example, the simultaneous acquisition was used to determine the relationship between spontaneous fMRI BOLD signals and band-limited intracortical electrical activity. Simultaneous fMRI and electrophysiological recording in the rodent will provide a platform for many exciting applications in neuroscience in addition to elucidating the relationship between the fMRI BOLD signal and neuronal activity.
Neuroscience, Issue 42, fMRI, electrophysiology, rat, BOLD, brain, resting state
High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain
Institutions: The University of Texas at Austin.
Functional MRI (fMRI) is a widely used tool for non-invasively measuring correlates of human brain activity. However, its use has mostly been focused upon measuring activity on the surface of cerebral cortex rather than in subcortical regions such as midbrain and brainstem. Subcortical fMRI must overcome two challenges: spatial resolution and physiological noise. Here we describe an optimized set of techniques developed to perform high-resolution fMRI in human SC, a structure on the dorsal surface of the midbrain; the methods can also be used to image other brainstem and subcortical structures.
High-resolution (1.2 mm voxels) fMRI of the SC requires a non-conventional approach. The desired spatial sampling is obtained using a multi-shot (interleaved) spiral acquisition1
. Since, T2
* of SC tissue is longer than in cortex, a correspondingly longer echo time (TE
~ 40 msec) is used to maximize functional contrast. To cover the full extent of the SC, 8-10 slices are obtained. For each session a structural anatomy with the same slice prescription as the fMRI is also obtained, which is used to align the functional data to a high-resolution reference volume.
In a separate session, for each subject, we create a high-resolution (0.7 mm sampling) reference volume using a T1
-weighted sequence that gives good tissue contrast. In the reference volume, the midbrain region is segmented using the ITK-SNAP software application2
. This segmentation is used to create a 3D surface representation of the midbrain that is both smooth and accurate3
. The surface vertices and normals are used to create a map of depth from the midbrain surface within the tissue4
Functional data is transformed into the coordinate system of the segmented reference volume. Depth associations of the voxels enable the averaging of fMRI time series data within specified depth ranges to improve signal quality. Data is rendered on the 3D surface for visualization.
In our lab we use this technique for measuring topographic maps of visual stimulation and covert and overt visual attention within the SC1
. As an example, we demonstrate the topographic representation of polar angle to visual stimulation in SC.
Neuroscience, Issue 63, fMRI, midbrain, brainstem, colliculus, BOLD, brain, Magentic Resonance Imaging, MRI
Brain Imaging Investigation of the Memory-Enhancing Effect of Emotion
Institutions: University of Alberta, University of Illinois, Urbana-Champaign, Duke University, University of Illinois, Urbana-Champaign.
Emotional events tend to be better remembered than non-emotional events1,2
. One goal of cognitive and affective neuroscientists is
to understand the neural mechanisms underlying this enhancing effect of emotion on memory. A method that has proven particularly influential in the
investigation of the memory-enhancing effect of emotion is the so-called subsequent memory paradigm (SMP). This method was originally used to investigate the
neural correlates of non-emotional memories3
, and more recently we and others also applied it successfully to studies of emotional memory (reviewed in4, 5-7
Here, we describe a protocol that allows investigation of the neural correlates of the memory-enhancing effect of emotion using the SMP in conjunction with
event-related functional magnetic resonance imaging (fMRI). An important feature of the SMP is that it allows separation of brain activity specifically
associated with memory from more general activity associated with perception. Moreover, in the context of investigating the impact of emotional stimuli,
SMP allows identification of brain regions whose activity is susceptible to emotional modulation of both general/perceptual and memory-specific processing.
This protocol can be used in healthy subjects8-15
, as well as in clinical patients where there are alterations in the neural correlates of emotion perception
and biases in remembering emotional events, such as those suffering from depression and post-traumatic stress disorder (PTSD)16, 17
Neuroscience, Issue 51, Affect, Recognition, Recollection, Dm Effect, Neuroimaging
Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging
Institutions: University of Alabama at Birmingham.
Newly emerging theories suggest that the brain does not function as a cohesive unit in autism, and this discordance is reflected in the behavioral symptoms displayed by individuals with autism. While structural neuroimaging findings have provided some insights into brain abnormalities in autism, the consistency of such findings is questionable. Functional neuroimaging, on the other hand, has been more fruitful in this regard because autism is a disorder of dynamic processing and allows examination of communication between cortical networks, which appears to be where the underlying problem occurs in autism. Functional connectivity is defined as the temporal correlation of spatially separate neurological events1. Findings from a number of recent fMRI studies have supported the idea that there is weaker coordination between different parts of the brain that should be working together to accomplish complex social or language problems2,3,4,5,6
. One of the mysteries of autism is the coexistence of deficits in several domains along with relatively intact, sometimes enhanced, abilities. Such complex manifestation of autism calls for a global and comprehensive examination of the disorder at the neural level. A compelling recent account of the brain functioning in autism, the cortical underconnectivity theory,2,7
provides an integrating framework for the neurobiological bases of autism. The cortical underconnectivity theory of autism suggests that any language, social, or psychological function that is dependent on the integration of multiple brain regions is susceptible to disruption as the processing demand increases. In autism, the underfunctioning of integrative circuitry in the brain may cause widespread underconnectivity. In other words, people with autism may interpret information in a piecemeal fashion at the expense of the whole. Since cortical underconnectivity among brain regions, especially the frontal cortex and more posterior areas 3,6
, has now been relatively well established, we can begin to further understand brain connectivity as a critical component of autism symptomatology.
A logical next step in this direction is to examine the anatomical connections that may mediate the functional connections mentioned above. Diffusion Tensor Imaging (DTI) is a relatively novel neuroimaging technique that helps probe the diffusion of water in the brain to infer the integrity of white matter fibers. In this technique, water diffusion in the brain is examined in several directions using diffusion gradients. While functional connectivity provides information about the synchronization of brain activation across different brain areas during a task or during rest, DTI helps in understanding the underlying axonal organization which may facilitate the cross-talk among brain areas. This paper will describe these techniques as valuable tools in understanding the brain in autism and the challenges involved in this line of research.
Medicine, Issue 55, Functional magnetic resonance imaging (fMRI), MRI, Diffusion tensor imaging (DTI), Functional Connectivity, Neuroscience, Developmental disorders, Autism, Fractional Anisotropy
Brain Imaging Investigation of the Neural Correlates of Emotional Autobiographical Recollection
Institutions: University of Alberta, Edmonton, University of Illinois, Urbana-Champaign, University of Illinois, Urbana-Champaign, University of Illinois, Urbana-Champaign.
Recollection of emotional autobiographical memories (AMs) is important to healthy cognitive and affective functioning 1
- remembering positive AMs is associated with increased personal well-being and self-esteem 2
, whereas remembering and ruminating on negative AMs may lead to affective disorders 3
. Although significant progress has been made in understanding the brain mechanisms underlying AM retrieval in general (reviewed in 4, 5
), less is known about the effect of emotion on the subjective re-experience of AMs and the associated neural correlates. This is in part due to the fact that, unlike the investigations of the emotion effect on memory for laboratory-based micro
events (reviewed in 6, 7-9
), often times AM studies do not have a clear focus on the emotional aspects of remembering personal
events (but see 10
). Here, we present a protocol that allows investigation of the neural correlates of recollecting emotional AMs using functional magnetic resonance imaging (fMRI). Cues for these memories are collected prior to scanning by means of an autobiographical memory questionnaire (AMQ), therefore allowing for proper selection of emotional AMs based on their phenomenological properties (i.e., intensity, vividness, personal significance). This protocol can be used in healthy and clinical populations alike.
Neuroscience, Issue 54, Personal Memories, Retrieval Focus, Cognitive Distraction, Emotion Regulation, Neuroimaging
Correlating Behavioral Responses to fMRI Signals from Human Prefrontal Cortex: Examining Cognitive Processes Using Task Analysis
Institutions: Centre for Vision Research, York University, Centre for Vision Research, York University.
The aim of this methods paper is to describe how to implement a neuroimaging technique to examine complementary brain processes engaged by two similar tasks. Participants' behavior during task performance in an fMRI scanner can then be correlated to the brain activity using the blood-oxygen-level-dependent signal. We measure behavior to be able to sort correct trials, where the subject performed the task correctly and then be able to examine the brain signals related to correct performance. Conversely, if subjects do not perform the task correctly, and these trials are included in the same analysis with the correct trials we would introduce trials that were not only for correct performance. Thus, in many cases these errors can be used themselves to then correlate brain activity to them. We describe two complementary tasks that are used in our lab to examine the brain during suppression of an automatic responses: the stroop1
and anti-saccade tasks. The emotional stroop paradigm instructs participants to either report the superimposed emotional 'word' across the affective faces or the facial 'expressions' of the face stimuli1,2
. When the word and the facial expression refer to different emotions, a conflict between what must be said and what is automatically read occurs. The participant has to resolve the conflict between two simultaneously competing processes of word reading and facial expression. Our urge to read out a word leads to strong 'stimulus-response (SR)' associations; hence inhibiting these strong SR's is difficult and participants are prone to making errors. Overcoming this conflict and directing attention away from the face or the word requires the subject to inhibit bottom up processes which typically directs attention to the more salient stimulus. Similarly, in the anti-saccade task3,4,5,6
, where an instruction cue is used to direct only attention to a peripheral stimulus location but then the eye movement is made to the mirror opposite position. Yet again we measure behavior by recording the eye movements of participants which allows for the sorting of the behavioral responses into correct and error trials7
which then can be correlated to brain activity. Neuroimaging now allows researchers to measure different behaviors of correct and error trials that are indicative of different cognitive processes and pinpoint the different neural networks involved.
Neuroscience, Issue 64, fMRI, eyetracking, BOLD, attention, inhibition, Magnetic Resonance Imaging, MRI
Brain Imaging Investigation of the Neural Correlates of Emotion Regulation
Institutions: University of Illinois, Urbana-Champaign, University of Alberta, Edmonton, University of Alberta, Edmonton, University of Alberta, Edmonton, University of Alberta, Edmonton, University of Illinois, Urbana-Champaign, University of Illinois, Urbana-Champaign.
The ability to control/regulate emotions is an important coping mechanism in the face of emotionally stressful situations. Although significant progress has been made in understanding conscious/deliberate emotion regulation (ER), less is known about non-conscious/automatic ER and the associated neural correlates. This is in part due to the problems inherent in the unitary concepts of automatic and conscious processing1
. Here, we present a protocol that allows investigation of the neural correlates of both deliberate and automatic ER using functional magnetic resonance imaging (fMRI). This protocol allows new avenues of inquiry into various aspects of ER. For instance, the experimental design allows manipulation of the goal to regulate emotion (conscious vs. non-conscious), as well as the intensity of the emotional challenge (high vs. low). Moreover, it allows investigation of both immediate (emotion perception) and long-term effects (emotional memory) of ER strategies on emotion processing. Therefore, this protocol may contribute to better understanding of the neural mechanisms of emotion regulation in healthy behaviour, and to gaining insight into possible causes of deficits in depression and anxiety disorders in which emotion dys
regulation is often among the core debilitating features.
Neuroscience, Issue 54, Emotion Suppression, Automatic Emotion Control, Deliberate Emotion Control, Goal Induction, Neuroimaging
Brain Imaging Investigation of the Impairing Effect of Emotion on Cognition
Institutions: University of Alberta, University of Alberta, University of Illinois, Duke University , Duke University , VA Medical Center, Yale University, University of Illinois, University of Illinois.
Emotions can impact cognition by exerting both enhancing
(e.g., better memory for emotional events) and impairing
(e.g., increased emotional distractibility) effects (reviewed in 1
). Complementing our recent protocol 2
describing a method that allows investigation of the neural correlates of the memory-enhancing effect of emotion (see also 1, 3-5
), here we present a protocol that allows investigation of the neural correlates of the detrimental impact of emotion on cognition. The main feature of this method is that it allows identification of reciprocal modulations between activity in a ventral neural system, involved in 'hot' emotion processing (HotEmo
system), and a dorsal system, involved in higher-level 'cold' cognitive/executive processing (ColdEx
system), which are linked to cognitive performance and to individual variations in behavior (reviewed in 1
). Since its initial introduction 6
, this design has proven particularly versatile and influential in the elucidation of various aspects concerning the neural correlates of the detrimental impact of emotional distraction on cognition, with a focus on working memory (WM), and of coping with such distraction 7,11
, in both healthy 8-11
and clinical participants 12-14
Neuroscience, Issue 60, Emotion-Cognition Interaction, Cognitive/Emotional Interference, Task-Irrelevant Distraction, Neuroimaging, fMRI, MRI
Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
Institutions: Baylor College of Medicine, Michael E. DeBakey VA Medical Center, University of California, Los Angeles, University of California, Los Angeles.
Functional connectivity MRI (fcMRI) is an fMRI method that examines the connectivity of different brain areas based on the correlation of BOLD signal fluctuations over time. Temporal Lobe Epilepsy (TLE) is the most common type of adult epilepsy and involves multiple brain networks. The default mode network (DMN) is involved in conscious, resting state cognition and is thought to be affected in TLE where seizures cause impairment of consciousness. The DMN in epilepsy was examined using seed based fcMRI. The anterior and posterior hubs of the DMN were used as seeds in this analysis. The results show a disconnection between the anterior and posterior hubs of the DMN in TLE during the basal state. In addition, increased DMN connectivity to other brain regions in left TLE along with decreased connectivity in right TLE is revealed. The analysis demonstrates how seed-based fcMRI can be used to probe cerebral networks in brain disorders such as TLE.
Medicine, Issue 90, Default Mode Network (DMN), Temporal Lobe Epilepsy (TLE), fMRI, MRI, functional connectivity MRI (fcMRI), blood oxygenation level dependent (BOLD)
Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
Institutions: Yale School of Medicine, Yale School of Medicine, New York University , New York University , New York University .
Most of the choices we make have uncertain consequences. In some cases the probabilities for different possible outcomes are precisely known, a condition termed "risky". In other cases when probabilities cannot be estimated, this is a condition described as "ambiguous". While most people are averse to both risk and ambiguity1,2
, the degree of those aversions vary substantially across individuals, such that the subjective value
of the same risky or ambiguous option can be very different for different individuals. We combine functional MRI (fMRI) with an experimental economics-based method3
to assess the neural representation of the subjective values of risky and ambiguous options4
. This technique can be now used to study these neural representations in different populations, such as different age groups and different patient populations.
In our experiment, subjects make consequential choices between two alternatives while their neural activation is tracked using fMRI. On each trial subjects choose between lotteries that vary in their monetary amount and in either the probability of winning that amount or the ambiguity level associated with winning. Our parametric design allows us to use each individual's choice behavior to estimate their attitudes towards risk and ambiguity, and thus to estimate the subjective values that each option held for them. Another important feature of the design is that the outcome of the chosen lottery is not revealed during the experiment, so that no learning can take place, and thus the ambiguous options remain ambiguous and risk attitudes are stable. Instead, at the end of the scanning session one or few trials are randomly selected and played for real money. Since subjects do not know beforehand which trials will be selected, they must treat each and every trial as if it and it alone was the one trial on which they will be paid. This design ensures that we can estimate the true subjective value of each option to each subject. We then look for areas in the brain whose activation is correlated with the subjective value of risky options and for areas whose activation is correlated with the subjective value of ambiguous options.
Neuroscience, Issue 67, Medicine, Molecular Biology, fMRI, magnetic resonance imaging, decision-making, value, uncertainty, risk, ambiguity