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Pubmed Article
Assessing corpus callosum changes in Alzheimers disease: comparison between tract-based spatial statistics and atlas-based tractography.
PLoS ONE
Tractography based on Diffusion Tensor Imaging (DTI) represents a valuable tool for investigating brain white matter (WM) microstructure, allowing the computation of damage-related diffusion parameters such as Fractional Anisotropy (FA) in specific WM tracts. This technique appears relevant in the study of pathologies in which brain disconnection plays a major role, such as, for instance, Alzheimers Disease (AD). Previous DTI studies have reported inconsistent results in defining WM abnormalities in AD and in its prodromal stage (i.e., amnestic Mild Cognitive Impairment; aMCI), especially when investigating the corpus callosum (CC). A reason for these inconsistencies is the use of different processing techniques, which may strongly influence the results. The aim of the current study was to compare a novel atlas-based tractography approach, that sub-divides the CC in eight portions, with Tract-Based Spatial Statistics (TBSS) when used to detect specific patterns of CC FA in AD at different clinical stages. FA data were obtained from 76 subjects (37 with mild AD, 19 with aMCI and 20 elderly healthy controls, HC) and analyzed using both methods. Consistent results were obtained for the two methods, concerning the comparisons AD vs. HC (significantly reduced FA in the whole CC of AD patients) and AD vs. aMCI (significantly reduced FA in the frontal portions of the CC in AD patients), thus identifying a relative preservation of the frontal CC regions in aMCI patients compared to AD. Conversely, the atlas-based method but not the TBSS showed the ability to detect a selective FA change in the CC parietal, left temporal and occipital regions of aMCI patients compared to HC. This finding indicates that an analysis including a higher number of voxels (with no restriction to tract skeletons) may detect characteristic pattern of FA in the CC of patients with preclinical AD, when brain atrophy is still modest.
Authors: Hans-Peter Müller, Jan Kassubek.
Published: 07-28-2013
ABSTRACT
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.
20 Related JoVE Articles!
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Developing Neuroimaging Phenotypes of the Default Mode Network in PTSD: Integrating the Resting State, Working Memory, and Structural Connectivity
Authors: Noah S. Philip, S. Louisa Carpenter, Lawrence H. Sweet.
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
51651
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DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions
Authors: Ardian Hana, Andreas Husch, Vimal Raj Nitish Gunness, Christophe Berthold, Anisa Hana, Georges Dooms, Hans Boecher Schwarz, Frank Hertel.
Institutions: Centre Hospitalier de Luxembourg, University of Applied Sciences Trier, Erasmus Universiteit Rotterdam, Centre Hospitalier de Luxembourg.
DTI is a technique that identifies white matter tracts (WMT) non-invasively in healthy and non-healthy patients using diffusion measurements. Similar to visual pathways (VP), WMT are not visible with classical MRI or intra-operatively with microscope. DTI will help neurosurgeons to prevent destruction of the VP while removing lesions adjacent to this WMT. We have performed DTI on fifty patients before and after surgery between March 2012 to January 2014. To navigate we used a 3DT1-weighted sequence. Additionally, we performed a T2-weighted and DTI-sequences. The parameters used were, FOV: 200 x 200 mm, slice thickness: 2 mm, and acquisition matrix: 96 x 96 yielding nearly isotropic voxels of 2 x 2 x 2 mm. Axial MRI was carried out using a 32 gradient direction and one b0-image. We used Echo-Planar-Imaging (EPI) and ASSET parallel imaging with an acceleration factor of 2 and b-value of 800 s/mm². The scanning time was less than 9 min. The DTI-data obtained were processed using a FDA approved surgical navigation system program which uses a straightforward fiber-tracking approach known as fiber assignment by continuous tracking (FACT). This is based on the propagation of lines between regions of interest (ROI) which is defined by a physician. A maximum angle of 50, FA start value of 0.10 and ADC stop value of 0.20 mm²/s were the parameters used for tractography. There are some limitations to this technique. The limited acquisition time frame enforces trade-offs in the image quality. Another important point not to be neglected is the brain shift during surgery. As for the latter intra-operative MRI might be helpful. Furthermore the risk of false positive or false negative tracts needs to be taken into account which might compromise the final results.
Medicine, Issue 90, Neurosurgery, brain, visual pathway, white matter tracts, visual cortex, optic chiasm, glioblastoma, meningioma, metastasis
51946
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MALDI Imaging Mass Spectrometry of Neuropeptides in Parkinson's Disease
Authors: Jörg Hanrieder, Anna Ljungdahl, Malin Andersson.
Institutions: Uppsala University, Chalmers University of Technology.
MALDI imaging mass spectrometry (IMS) is a powerful approach that facilitates the spatial analysis of molecular species in biological tissue samples2 (Fig.1). A 12 μm thin tissue section is covered with a MALDI matrix, which facilitates desorption and ionization of intact peptides and proteins that can be detected with a mass analyzer, typically using a MALDI TOF/TOF mass spectrometer. Generally hundreds of peaks can be assessed in a single rat brain tissue section. In contrast to commonly used imaging techniques, this approach does not require prior knowledge of the molecules of interest and allows for unsupervised and comprehensive analysis of multiple molecular species while maintaining high molecular specificity and sensitivity2. Here we describe a MALDI IMS based approach for elucidating region-specific distribution profiles of neuropeptides in the rat brain of an animal model Parkinson's disease (PD). PD is a common neurodegenerative disease with a prevalence of 1% for people over 65 of age3,4. The most common symptomatic treatment is based on dopamine replacement using L-DOPA5. However this is accompanied by severe side effects including involuntary abnormal movements, termed L-DOPA-induced dyskinesias (LID)1,3,6. One of the most prominent molecular change in LID is an upregulation of the opioid precursor prodynorphin mRNA7. The dynorphin peptides modulate neurotransmission in brain areas that are essentially involved in movement control7,8. However, to date the exact opioid peptides that originate from processing of the neuropeptide precursor have not been characterized. Therefore, we utilized MALDI IMS in an animal model of experimental Parkinson's disease and L-DOPA induced dyskinesia. MALDI imaging mass spectrometry proved to be particularly advantageous with respect to neuropeptide characterization, since commonly used antibody based approaches targets known peptide sequences and previously observed post-translational modifications. By contrast MALDI IMS can unravel novel peptide processing products and thus reveal new molecular mechanisms of neuropeptide modulation of neuronal transmission. While the absolute amount of neuropeptides cannot be determined by MALDI IMS, the relative abundance of peptide ions can be delineated from the mass spectra, giving insights about changing levels in health and disease. In the examples presented here, the peak intensities of dynorphin B, alpha-neoendorphin and substance P were found to be significantly increased in the dorsolateral, but not the dorsomedial, striatum of animals with severe dyskinesia involving facial, trunk and orolingual muscles (Fig. 5). Furthermore, MALDI IMS revealed a correlation between dyskinesia severity and levels of des-tyrosine alpha-neoendorphin, representing a previously unknown mechanism of functional inactivation of dynorphins in the striatum as the removal of N-terminal tyrosine reduces the dynorphin's opioid-receptor binding capacity9. This is the first study on neuropeptide characterization in LID using MALDI IMS and the results highlight the potential of the technique for application in all fields of biomedical research.
Medicine, Issue 60, Parkinson's disease, L-DOPA induced dyskinesia, striatum, opioid peptides, MALDI Imaging MS
3445
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Comprehensive Analysis of Transcription Dynamics from Brain Samples Following Behavioral Experience
Authors: Hagit Turm, Diptendu Mukherjee, Doron Haritan, Maayan Tahor, Ami Citri.
Institutions: The Hebrew University of Jerusalem.
The encoding of experiences in the brain and the consolidation of long-term memories depend on gene transcription. Identifying the function of specific genes in encoding experience is one of the main objectives of molecular neuroscience. Furthermore, the functional association of defined genes with specific behaviors has implications for understanding the basis of neuropsychiatric disorders. Induction of robust transcription programs has been observed in the brains of mice following various behavioral manipulations. While some genetic elements are utilized recurrently following different behavioral manipulations and in different brain nuclei, transcriptional programs are overall unique to the inducing stimuli and the structure in which they are studied1,2. In this publication, a protocol is described for robust and comprehensive transcriptional profiling from brain nuclei of mice in response to behavioral manipulation. The protocol is demonstrated in the context of analysis of gene expression dynamics in the nucleus accumbens following acute cocaine experience. Subsequent to a defined in vivo experience, the target neural tissue is dissected; followed by RNA purification, reverse transcription and utilization of microfluidic arrays for comprehensive qPCR analysis of multiple target genes. This protocol is geared towards comprehensive analysis (addressing 50-500 genes) of limiting quantities of starting material, such as small brain samples or even single cells. The protocol is most advantageous for parallel analysis of multiple samples (e.g. single cells, dynamic analysis following pharmaceutical, viral or behavioral perturbations). However, the protocol could also serve for the characterization and quality assurance of samples prior to whole-genome studies by microarrays or RNAseq, as well as validation of data obtained from whole-genome studies.
Behavior, Issue 90, Brain, behavior, RNA, transcription, nucleus accumbens, cocaine, high-throughput qPCR, experience-dependent plasticity, gene regulatory networks, microdissection
51642
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Setting Limits on Supersymmetry Using Simplified Models
Authors: Christian Gütschow, Zachary Marshall.
Institutions: University College London, CERN, Lawrence Berkeley National Laboratories.
Experimental limits on supersymmetry and similar theories are difficult to set because of the enormous available parameter space and difficult to generalize because of the complexity of single points. Therefore, more phenomenological, simplified models are becoming popular for setting experimental limits, as they have clearer physical interpretations. The use of these simplified model limits to set a real limit on a concrete theory has not, however, been demonstrated. This paper recasts simplified model limits into limits on a specific and complete supersymmetry model, minimal supergravity. Limits obtained under various physical assumptions are comparable to those produced by directed searches. A prescription is provided for calculating conservative and aggressive limits on additional theories. Using acceptance and efficiency tables along with the expected and observed numbers of events in various signal regions, LHC experimental results can be recast in this manner into almost any theoretical framework, including nonsupersymmetric theories with supersymmetry-like signatures.
Physics, Issue 81, high energy physics, particle physics, Supersymmetry, LHC, ATLAS, CMS, New Physics Limits, Simplified Models
50419
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Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations
Authors: Fijoy Vadakkumpadan, Hermenegild Arevalo, Natalia A. Trayanova.
Institutions: Johns Hopkins University.
Patient-specific simulations of heart (dys)function aimed at personalizing cardiac therapy are hampered by the absence of in vivo imaging technology for clinically acquiring myocardial fiber orientations. The objective of this project was to develop a methodology to estimate cardiac fiber orientations from in vivo images of patient heart geometries. An accurate representation of ventricular geometry and fiber orientations was reconstructed, respectively, from high-resolution ex vivo structural magnetic resonance (MR) and diffusion tensor (DT) MR images of a normal human heart, referred to as the atlas. Ventricular geometry of a patient heart was extracted, via semiautomatic segmentation, from an in vivo computed tomography (CT) image. Using image transformation algorithms, the atlas ventricular geometry was deformed to match that of the patient. Finally, the deformation field was applied to the atlas fiber orientations to obtain an estimate of patient fiber orientations. The accuracy of the fiber estimates was assessed using six normal and three failing canine hearts. The mean absolute difference between inclination angles of acquired and estimated fiber orientations was 15.4 °. Computational simulations of ventricular activation maps and pseudo-ECGs in sinus rhythm and ventricular tachycardia indicated that there are no significant differences between estimated and acquired fiber orientations at a clinically observable level.The new insights obtained from the project will pave the way for the development of patient-specific models of the heart that can aid physicians in personalized diagnosis and decisions regarding electrophysiological interventions.
Bioengineering, Issue 71, Biomedical Engineering, Medicine, Anatomy, Physiology, Cardiology, Myocytes, Cardiac, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, MRI, Diffusion Magnetic Resonance Imaging, Cardiac Electrophysiology, computerized simulation (general), mathematical modeling (systems analysis), Cardiomyocyte, biomedical image processing, patient-specific modeling, Electrophysiology, simulation
50125
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Detection of Neuritic Plaques in Alzheimer's Disease Mouse Model
Authors: Philip T.T. Ly, Fang Cai, Weihong Song.
Institutions: The University of British Columbia.
Alzheimer's disease (AD) is the most common neurodegenerative disorder leading to dementia. Neuritic plaque formation is one of the pathological hallmarks of Alzheimer's disease. The central component of neuritic plaques is a small filamentous protein called amyloid β protein (Aβ)1, which is derived from sequential proteolytic cleavage of the beta-amyloid precursor protein (APP) by β-secretase and γ-secretase. The amyloid hypothesis entails that Aγ-containing plaques as the underlying toxic mechanism in AD pathology2. The postmortem analysis of the presence of neuritic plaque confirms the diagnosis of AD. To further our understanding of Aγ neurobiology in AD pathogenesis, various mouse strains expressing AD-related mutations in the human APP genes were generated. Depending on the severity of the disease, these mice will develop neuritic plaques at different ages. These mice serve as invaluable tools for studying the pathogenesis and drug development that could affect the APP processing pathway and neuritic plaque formation. In this protocol, we employ an immunohistochemical method for specific detection of neuritic plaques in AD model mice. We will specifically discuss the preparation from extracting the half brain, paraformaldehyde fixation, cryosectioning, and two methods to detect neurotic plaques in AD transgenic mice: immunohistochemical detection using the ABC and DAB method and fluorescent detection using thiofalvin S staining method.
Neuroscience, Issue 53, Alzheimer’s disease, neuritic plaques, Amyloid β protein, APP, transgenic mouse
2831
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Examining the Characteristics of Episodic Memory using Event-related Potentials in Patients with Alzheimer's Disease
Authors: Erin Hussey, Brandon Ally.
Institutions: Vanderbilt University.
Our laboratory uses event-related EEG potentials (ERPs) to understand and support behavioral investigations of episodic memory in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer's disease (AD). Whereas behavioral data inform us about the patients' performance, ERPs allow us to record discrete changes in brain activity. Further, ERPs can give us insight into the onset, duration, and interaction of independent cognitive processes associated with memory retrieval. In patient populations, these types of studies are used to examine which aspects of memory are impaired and which remain relatively intact compared to a control population. The methodology for collecting ERP data from a vulnerable patient population while these participants perform a recognition memory task is reviewed. This protocol includes participant preparation, quality assurance, data acquisition, and data analysis. In addition to basic setup and acquisition, we will also demonstrate localization techniques to obtain greater spatial resolution and source localization using high-density (128 channel) electrode arrays.
Medicine, Issue 54, recognition memory, episodic memory, event-related potentials, dual process, Alzheimer's disease, amnestic mild cognitive impairment
2715
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Preparation of Acute Hippocampal Slices from Rats and Transgenic Mice for the Study of Synaptic Alterations during Aging and Amyloid Pathology
Authors: Diana M. Mathis, Jennifer L. Furman, Christopher M. Norris.
Institutions: University of Kentucky College of Public Health, University of Kentucky College of Medicine, University of Kentucky College of Medicine.
The rodent hippocampal slice preparation is perhaps the most broadly used tool for investigating mammalian synaptic function and plasticity. The hippocampus can be extracted quickly and easily from rats and mice and slices remain viable for hours in oxygenated artificial cerebrospinal fluid. Moreover, basic electrophysisologic techniques are easily applied to the investigation of synaptic function in hippocampal slices and have provided some of the best biomarkers for cognitive impairments. The hippocampal slice is especially popular for the study of synaptic plasticity mechanisms involved in learning and memory. Changes in the induction of long-term potentiation and depression (LTP and LTD) of synaptic efficacy in hippocampal slices (or lack thereof) are frequently used to describe the neurologic phenotype of cognitively-impaired animals and/or to evaluate the mechanism of action of nootropic compounds. This article outlines the procedures we use for preparing hippocampal slices from rats and transgenic mice for the study of synaptic alterations associated with brain aging and Alzheimer's disease (AD)1-3. Use of aged rats and AD model mice can present a unique set of challenges to researchers accustomed to using younger rats and/or mice in their research. Aged rats have thicker skulls and tougher connective tissue than younger rats and mice, which can delay brain extraction and/or dissection and consequently negate or exaggerate real age-differences in synaptic function and plasticity. Aging and amyloid pathology may also exacerbate hippocampal damage sustained during the dissection procedure, again complicating any inferences drawn from physiologic assessment. Here, we discuss the steps taken during the dissection procedure to minimize these problems. Examples of synaptic responses acquired in "healthy" and "unhealthy" slices from rats and mice are provided, as well as representative synaptic plasticity experiments. The possible impact of other methodological factors on synaptic function in these animal models (e.g. recording solution components, stimulation parameters) are also discussed. While the focus of this article is on the use of aged rats and transgenic mice, novices to slice physiology should find enough detail here to get started on their own studies, using a variety of rodent models.
Neuroscience, Issue 49, aging, amyloid, hippocampal slice, synaptic plasticity, Ca2+, CA1, electrophysiology
2330
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The Use of Magnetic Resonance Spectroscopy as a Tool for the Measurement of Bi-hemispheric Transcranial Electric Stimulation Effects on Primary Motor Cortex Metabolism
Authors: Sara Tremblay, Vincent Beaulé, Sébastien Proulx, Louis-Philippe Lafleur, Julien Doyon, Małgorzata Marjańska, Hugo Théoret.
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 (1H-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 1H-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 1H-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
51631
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An Investigation of the Effects of Sports-related Concussion in Youth Using Functional Magnetic Resonance Imaging and the Head Impact Telemetry System
Authors: Michelle Keightley, Stephanie Green, Nick Reed, Sabrina Agnihotri, Amy Wilkinson, Nancy Lobaugh.
Institutions: University of Toronto, University of Toronto, University of Toronto, Bloorview Kids Rehab, Toronto Rehab, Sunnybrook Health Sciences Centre, University of Toronto.
One of the most commonly reported injuries in children who participate in sports is concussion or mild traumatic brain injury (mTBI)1. Children and youth involved in organized sports such as competitive hockey are nearly six times more likely to suffer a severe concussion compared to children involved in other leisure physical activities2. While the most common cognitive sequelae of mTBI appear similar for children and adults, the recovery profile and breadth of consequences in children remains largely unknown2, as does the influence of pre-injury characteristics (e.g. gender) and injury details (e.g. magnitude and direction of impact) on long-term outcomes. Competitive sports, such as hockey, allow the rare opportunity to utilize a pre-post design to obtain pre-injury data before concussion occurs on youth characteristics and functioning and to relate this to outcome following injury. Our primary goals are to refine pediatric concussion diagnosis and management based on research evidence that is specific to children and youth. To do this we use new, multi-modal and integrative approaches that will: 1.Evaluate the immediate effects of head trauma in youth 2.Monitor the resolution of post-concussion symptoms (PCS) and cognitive performance during recovery 3.Utilize new methods to verify brain injury and recovery To achieve our goals, we have implemented the Head Impact Telemetry (HIT) System. (Simbex; Lebanon, NH, USA). This system equips commercially available Easton S9 hockey helmets (Easton-Bell Sports; Van Nuys, CA, USA) with single-axis accelerometers designed to measure real-time head accelerations during contact sport participation 3 - 5. By using telemetric technology, the magnitude of acceleration and location of all head impacts during sport participation can be objectively detected and recorded. We also use functional magnetic resonance imaging (fMRI) to localize and assess changes in neural activity specifically in the medial temporal and frontal lobes during the performance of cognitive tasks, since those are the cerebral regions most sensitive to concussive head injury 6. Finally, we are acquiring structural imaging data sensitive to damage in brain white matter.
Medicine, Issue 47, Mild traumatic brain injury, concussion, fMRI, youth, Head Impact Telemetry System
2226
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Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly
Authors: Joel Ramirez, Christopher J.M. Scott, Alicia A. McNeely, Courtney Berezuk, Fuqiang Gao, Gregory M. Szilagyi, Sandra E. Black.
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
50887
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A Comprehensive Protocol for Manual Segmentation of the Medial Temporal Lobe Structures
Authors: Matthew Moore, Yifan Hu, Sarah Woo, Dylan O'Hearn, Alexandru D. Iordan, Sanda Dolcos, Florin Dolcos.
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
50991
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Vascular Gene Transfer from Metallic Stent Surfaces Using Adenoviral Vectors Tethered through Hydrolysable Cross-linkers
Authors: Ilia Fishbein, Scott P. Forbes, Richard F. Adamo, Michael Chorny, Robert J. Levy, Ivan S. Alferiev.
Institutions: The Children's Hospital of Philadelphia, University of Pennsylvania.
In-stent restenosis presents a major complication of stent-based revascularization procedures widely used to re-establish blood flow through critically narrowed segments of coronary and peripheral arteries. Endovascular stents capable of tunable release of genes with anti-restenotic activity may present an alternative strategy to presently used drug-eluting stents. In order to attain clinical translation, gene-eluting stents must exhibit predictable kinetics of stent-immobilized gene vector release and site-specific transduction of vasculature, while avoiding an excessive inflammatory response typically associated with the polymer coatings used for physical entrapment of the vector. This paper describes a detailed methodology for coatless tethering of adenoviral gene vectors to stents based on a reversible binding of the adenoviral particles to polyallylamine bisphosphonate (PABT)-modified stainless steel surface via hydrolysable cross-linkers (HC). A family of bifunctional (amine- and thiol-reactive) HC with an average t1/2 of the in-chain ester hydrolysis ranging between 5 and 50 days were used to link the vector with the stent. The vector immobilization procedure is typically carried out within 9 hr and consists of several steps: 1) incubation of the metal samples in an aqueous solution of PABT (4 hr); 2) deprotection of thiol groups installed in PABT with tris(2-carboxyethyl) phosphine (20 min); 3) expansion of thiol reactive capacity of the metal surface by reacting the samples with polyethyleneimine derivatized with pyridyldithio (PDT) groups (2 hr); 4) conversion of PDT groups to thiols with dithiothreitol (10 min); 5) modification of adenoviruses with HC (1 hr); 6) purification of modified adenoviral particles by size-exclusion column chromatography (15 min) and 7) immobilization of thiol-reactive adenoviral particles on the thiolated steel surface (1 hr). This technique has wide potential applicability beyond stents, by facilitating surface engineering of bioprosthetic devices to enhance their biocompatibility through the substrate-mediated gene delivery to the cells interfacing the implanted foreign material.
Medicine, Issue 90, gene therapy, bioconjugation, adenoviral vectors, stents, local gene delivery, smooth muscle cells, endothelial cells, bioluminescence imaging
51653
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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Authors: Phoebe Spetsieris, Yilong Ma, Shichun Peng, Ji Hyun Ko, Vijay Dhawan, Chris C. Tang, David Eidelberg.
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
50319
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Modeling Astrocytoma Pathogenesis In Vitro and In Vivo Using Cortical Astrocytes or Neural Stem Cells from Conditional, Genetically Engineered Mice
Authors: Robert S. McNeill, Ralf S. Schmid, Ryan E. Bash, Mark Vitucci, Kristen K. White, Andrea M. Werneke, Brian H. Constance, Byron Huff, C. Ryan Miller.
Institutions: University of North Carolina School of Medicine, University of North Carolina School of Medicine, University of North Carolina School of Medicine, University of North Carolina School of Medicine, University of North Carolina School of Medicine, Emory University School of Medicine, University of North Carolina School of Medicine.
Current astrocytoma models are limited in their ability to define the roles of oncogenic mutations in specific brain cell types during disease pathogenesis and their utility for preclinical drug development. In order to design a better model system for these applications, phenotypically wild-type cortical astrocytes and neural stem cells (NSC) from conditional, genetically engineered mice (GEM) that harbor various combinations of floxed oncogenic alleles were harvested and grown in culture. Genetic recombination was induced in vitro using adenoviral Cre-mediated recombination, resulting in expression of mutated oncogenes and deletion of tumor suppressor genes. The phenotypic consequences of these mutations were defined by measuring proliferation, transformation, and drug response in vitro. Orthotopic allograft models, whereby transformed cells are stereotactically injected into the brains of immune-competent, syngeneic littermates, were developed to define the role of oncogenic mutations and cell type on tumorigenesis in vivo. Unlike most established human glioblastoma cell line xenografts, injection of transformed GEM-derived cortical astrocytes into the brains of immune-competent littermates produced astrocytomas, including the most aggressive subtype, glioblastoma, that recapitulated the histopathological hallmarks of human astrocytomas, including diffuse invasion of normal brain parenchyma. Bioluminescence imaging of orthotopic allografts from transformed astrocytes engineered to express luciferase was utilized to monitor in vivo tumor growth over time. Thus, astrocytoma models using astrocytes and NSC harvested from GEM with conditional oncogenic alleles provide an integrated system to study the genetics and cell biology of astrocytoma pathogenesis in vitro and in vivo and may be useful in preclinical drug development for these devastating diseases.
Neuroscience, Issue 90, astrocytoma, cortical astrocytes, genetically engineered mice, glioblastoma, neural stem cells, orthotopic allograft
51763
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Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
Authors: Jeffrey S. Phillips, Adam S. Greenberg, John A. Pyles, Sudhir K. Pathak, Marlene Behrmann, Walter Schneider, Michael J. Tarr.
Institutions: Center for the Neural Basis of Cognition, University of Pittsburgh, Carnegie Mellon University , University of Pittsburgh.
The study of complex computational systems is facilitated by network maps, such as circuit diagrams. Such mapping is particularly informative when studying the brain, as the functional role that a brain area fulfills may be largely defined by its connections to other brain areas. In this report, we describe a novel, non-invasive approach for relating brain structure and function using magnetic resonance imaging (MRI). This approach, a combination of structural imaging of long-range fiber connections and functional imaging data, is illustrated in two distinct cognitive domains, visual attention and face perception. Structural imaging is performed with diffusion-weighted imaging (DWI) and fiber tractography, which track the diffusion of water molecules along white-matter fiber tracts in the brain (Figure 1). By visualizing these fiber tracts, we are able to investigate the long-range connective architecture of the brain. The results compare favorably with one of the most widely-used techniques in DWI, diffusion tensor imaging (DTI). DTI is unable to resolve complex configurations of fiber tracts, limiting its utility for constructing detailed, anatomically-informed models of brain function. In contrast, our analyses reproduce known neuroanatomy with precision and accuracy. This advantage is partly due to data acquisition procedures: while many DTI protocols measure diffusion in a small number of directions (e.g., 6 or 12), we employ a diffusion spectrum imaging (DSI)1, 2 protocol which assesses diffusion in 257 directions and at a range of magnetic gradient strengths. Moreover, DSI data allow us to use more sophisticated methods for reconstructing acquired data. In two experiments (visual attention and face perception), tractography reveals that co-active areas of the human brain are anatomically connected, supporting extant hypotheses that they form functional networks. DWI allows us to create a "circuit diagram" and reproduce it on an individual-subject basis, for the purpose of monitoring task-relevant brain activity in networks of interest.
Neuroscience, Issue 69, Molecular Biology, Anatomy, Physiology, tractography, connectivity, neuroanatomy, white matter, magnetic resonance imaging, MRI
4125
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A Technique for Serial Collection of Cerebrospinal Fluid from the Cisterna Magna in Mouse
Authors: Li Liu, Karen Duff.
Institutions: Columbia University.
Alzheimer's disease (AD) is a progressive neurodegenerative disease that is pathologically characterized by extracellular deposition of β-amyloid peptide (Aβ) and intraneuronal accumulation of hyperphosphorylated tau protein. Because cerebrospinal fluid (CSF) is in direct contact with the extracellular space of the brain, it provides a reflection of the biochemical changes in the brain in response to pathological processes. CSF from AD patients shows a decrease in the 42 amino-acid form of Aβ (Aβ42), and increases in total tau and hyperphosphorylated tau, though the mechanisms responsible for these changes are still not fully understood. Transgenic (Tg) mouse models of AD provide an excellent opportunity to investigate how and why Aβ or tau levels in CSF change as the disease progresses. Here, we demonstrate a refined cisterna magna puncture technique for CSF sampling from the mouse. This extremely gentle sampling technique allows serial CSF samples to be obtained from the same mouse at 2-3 month intervals which greatly minimizes the confounding effect of between-mouse variability in Aβ or tau levels, making it possible to detect subtle alterations over time. In combination with Aβ and tau ELISA, this technique will be useful for studies designed to investigate the relationship between the levels of CSF Aβ42 and tau, and their metabolism in the brain in AD mouse models. Studies in Tg mice could provide important validation as to the potential of CSF Aβ or tau levels to be used as biological markers for monitoring disease progression, and to monitor the effect of therapeutic interventions. As the mice can be sacrificed and the brains can be examined for biochemical or histological changes, the mechanisms underlying the CSF changes can be better assessed. These data are likely to be informative for interpretation of human AD CSF changes.
Neuroscience, Issue 21, Cerebrospinal fluid, Alzheimer's disease, Transgenic mouse, β-amyloid, tau
960
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Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging
Authors: Rajesh K. Kana, Donna L. Murdaugh, Lauren E. Libero, Mark R. Pennick, Heather M. Wadsworth, Rishi Deshpande, Christi P. Hu.
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
3178
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Basics of Multivariate Analysis in Neuroimaging Data
Authors: Christian Georg Habeck.
Institutions: Columbia University.
Multivariate analysis techniques for neuroimaging data have recently received increasing attention as they have many attractive features that cannot be easily realized by the more commonly used univariate, voxel-wise, techniques1,5,6,7,8,9. Multivariate approaches evaluate correlation/covariance of activation across brain regions, rather than proceeding on a voxel-by-voxel basis. Thus, their results can be more easily interpreted as a signature of neural networks. Univariate approaches, on the other hand, cannot directly address interregional correlation in the brain. Multivariate approaches can also result in greater statistical power when compared with univariate techniques, which are forced to employ very stringent corrections for voxel-wise multiple comparisons. Further, multivariate techniques also lend themselves much better to prospective application of results from the analysis of one dataset to entirely new datasets. Multivariate techniques are thus well placed to provide information about mean differences and correlations with behavior, similarly to univariate approaches, with potentially greater statistical power and better reproducibility checks. In contrast to these advantages is the high barrier of entry to the use of multivariate approaches, preventing more widespread application in the community. To the neuroscientist becoming familiar with multivariate analysis techniques, an initial survey of the field might present a bewildering variety of approaches that, although algorithmically similar, are presented with different emphases, typically by people with mathematics backgrounds. We believe that multivariate analysis techniques have sufficient potential to warrant better dissemination. Researchers should be able to employ them in an informed and accessible manner. The current article is an attempt at a didactic introduction of multivariate techniques for the novice. A conceptual introduction is followed with a very simple application to a diagnostic data set from the Alzheimer s Disease Neuroimaging Initiative (ADNI), clearly demonstrating the superior performance of the multivariate approach.
JoVE Neuroscience, Issue 41, fMRI, PET, multivariate analysis, cognitive neuroscience, clinical neuroscience
1988
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JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

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In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.