Functional and structural mapping of human cerebral cortex: solutions are in the surfaces

The Human Connectome Project: Progress and Prospects

As the first phase of one of the most ambitious projects in the history of neuroscience comes to a close, one early and influential leader and his younger colleague explain its evolution and underpinnings. Its goal “is to build a ‘network map’ that will shed light on the anatomical and functional connectivity within the healthy human brain, as well as to produce a body of data that will facilitate research into brain disorders such as dyslexia, autism, Alzheimer’s disease, and schizophrenia.”

A Customizable Multimodality Imaging Compound That Relates External Landmarks to Internal Structures

Numerous research and clinical interventions, such as targeting drug deliveries or surgeries and finding blood clots, abscesses, or lesions, require accurate localization of various body parts. Individual differences in anatomy make it hard to use typical stereotactic procedures that rely on external landmarks and standardized atlases. For instance, it is not unusual to incorrectly place a craniotomy in brain surgery. This project was thus performed to find a new and easy method to correctly establish the relationship between external landmarks and medical scans of internal organs, such as specific regions of the brain.

METHODS

This paper introduces an MRI, CT, and radiographically visible compound that can be applied to any surface and therefore provide an external reference point to an internal (eye-invisible) structure.

RESULTS

Tested on nonhuman primates and isolated brain scans, this compound showed up with the same color in different scan types, making practical work possible. Conventional, and mostly of specific utility, products such as contrast agents were differentially colored or completely failed to show up and were not flexible.

CONCLUSION

This compound can be customized to have different viscosities, colors, odors, and other characteristics. It can also be mixed with hardening materials such as acrylic for industrial or engineering uses, for example. Laparoscopy wands, electroencephalogram leads, and other equipment could also be embedded with or surrounded by the compound for ease in 3-dimensional visualizations. A pending U.S. patent endorses this invention.

Multiresolution Diffeomorphic Mapping for Cortical Surfaces

Due to the convoluted folding pattern of the cerebral cortex, accurate alignment of cortical surfaces remains challenging. In this paper, we present a multiresolution diffeomorphic surface mapping algorithm under the framework of large deformation diffeomorphic metric mapping (LDDMM). Our algorithm takes advantage of multiresolution analysis (MRA) for surfaces and constructs cortical surfaces at multiresolution. This family of multiresolution surfaces are used as natural sparse priors of the cortical anatomy and provide the anchor points where the parametrization of deformation vector fields is supported. This naturally constructs tangent bundles of diffeomorphisms at different resolution levels and hence generates multiresolution diffeomorphic transformation. We show that our construction of multiresolution LDDMM surface mapping can potentially reduce computational cost and improves the mapping accuracy of cortical surfaces.

Cortical Morphology in Patients with Orthostatic Intolerance

BACKGROUND

We evaluated the cortical morphology in patients with orthostatic intolerance.

METHODS

Thirty patients with orthostatic intolerance, as well as age- and sex-matched normal controls, were enrolled in this study. We divided the patients into orthostatic hypotension (n = 22) and postural tachycardia syndrome (n = 8) groups based on their response to a head-up tilt table test. We analyzed whole-brain T1-weighted MRI images using FreeSurfer 5.1. The measures of cortical morphology were compared between the groups.

RESULTS

The cortical thickness in the right hemisphere, including the medial orbitofrontal, peri-calcarine, post-central, inferior temporal, and lateral occipital cortex, and in the peri-calcarine cortex of the left hemisphere was thinned in patients with orthostatic hypotension compared to normal controls. The other measures of cortical morphology, including the surface area, volume, and curvatures, did not differ between patients with orthostatic hypotension and normal controls. However, none of the measures of cortical morphology differed between patients with postural tachycardia syndrome and normal controls.

CONCLUSIONS

We demonstrated that the cortical morphology significantly changed in patients with orthostatic hypotension but not in patients with postural tachycardia syndrome compared to normal controls. These findings support the hypothesis that orthostatic intolerance is a heterogeneous syndrome.

Executive function and depressive symptoms of retardation in nonelderly stroke patients

The depression-executive dysfunction syndrome, a late-onset depression of vascular origin with executive dysfunction and psychomotor retardation, has also been described after stroke. We verified whether this syndrome also occurs in nonelderly stroke patients by investigating the association between domains of depressive symptoms with executive functions in 87 first-ever ischemic stroke patients. The retardation domain of the 31-item Hamilton Rating Scale for Depression was associated with decreased performance on verbal fluency (assessed with FAS). The association was maintained for younger patients (aged <60 years) after adjusting for confounders. This result supports the clinical presentation of depression-executive dysfunction syndrome in younger stroke patients. Confirmation of this finding, its neural correlates, and clinical implication deserve further investigation.

Functional and anatomical properties of human visual cortical fields

Human visual cortical fields (VCFs) vary in size and anatomical location across individual subjects. Here, we used functional magnetic resonance imaging (fMRI) with retinotopic stimulation to identify VCFs on the cortical surface. We found that aligning and averaging VCF activations across the two hemispheres provided clear delineation of multiple retinotopic fields in visual cortex. The results show that VCFs have consistent locations and extents in different subjects that provide stable and accurate landmarks for functional and anatomical mapping. Interhemispheric comparisons revealed minor differences in polar angle and eccentricity tuning in comparable VCFs in the left and right hemisphere, and somewhat greater intersubject variability in the right than left hemisphere. We then used the functional boundaries to characterize the anatomical properties of VCFs, including fractional anisotropy (FA), magnetization transfer ratio (MTR) and the ratio of T1W and T2W images and found significant anatomical differences between VCFs and between hemispheres.

Heritability of subcortical and limbic brain volume and shape in multiplex-multigenerational families with schizophrenia

BACKGROUND

Brain abnormalities of subcortical and limbic nuclei are common in patients with schizophrenia, and variation in these structures is considered a putative endophenotype for the disorder. Multiplex-multigenerational families with schizophrenia provide an opportunity to investigate the impact of shared genetic ancestry, but these families have not been previously examined to study structural brain abnormalities. We estimate the heritability of subcortical and hippocampal brain volumes in multiplex-multigenerational families and the heritability of subregions using advanced shape analysis.

METHODS

The study comprised 439 participants from two sites who underwent 3T structural magnetic resonance imaging. The participants included 190 European-Americans from 32 multiplex-multigenerational families with schizophrenia and 249 healthy comparison subjects. Subcortical and hippocampal volume and shape were measured in 14 brain structures. Heritability was estimated for volume and shape.

RESULTS

Volume and shape were heritable in families. Estimates of heritability in subcortical and limbic volumes ranged from .45 in the right hippocampus to .84 in the left putamen. The shape of these structures was heritable (range, .40-.49), and specific subregional shape estimates of heritability tended to exceed heritability estimates of volume alone.

CONCLUSIONS

These results demonstrate that volume and shape of subcortical and limbic brain structures are potential endophenotypic markers in schizophrenia. The specificity obtained using shape analysis may improve selection of imaging phenotypes that better reflect the underlying neurobiology. Our findings can aid in the identification of specific genetic targets that affect brain structure and function in schizophrenia.

The association of post-stroke anhedonia with salivary cortisol levels and stroke lesion in hippocampal/parahippocampal region

BACKGROUND

Anhedonia constitutes a coherent construct, with neural correlates and negative clinical impact, independent of depression. However, little is known about the neural correlates of anhedonia in stroke patients. In this study, we investigated the association of post-stroke anhedonia with salivary cortisol levels and stroke location and volume.

PATIENTS AND METHODS

A psychiatrist administered the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition to identify anhedonia in 36 inpatients, without previous depression, consecutively admitted in a neurology clinic in the first month after a first-ever ischemic stroke. Salivary cortisol levels were assessed in the morning, evening, and after a dexamethasone suppression test. We used magnetic resonance imaging and a semi-automated brain morphometry method to assess stroke location, and the MRIcro program according to the Brodmann Map to calculate the lesion volume.

RESULTS

Patients with anhedonia had significantly larger diurnal variation (P-value =0.017) and higher morning levels of salivary cortisol (1,671.9±604.0 ng/dL versus 1,103.9±821.9 ng/dL; P-value =0.022), and greater stroke lesions in the parahippocampal gyrus (Brodmann area 36) compared to those without anhedonia (10.14 voxels; standard deviation ±17.72 versus 0.86 voxels; standard deviation ±4.64; P-value =0.027). The volume of lesion in the parahippocampal gyrus (Brodmann area 36) was associated with diurnal variation of salivary cortisol levels (rho=0.845; P-value =0.034) only in anhedonic patients.

CONCLUSION

Our findings suggest that anhedonia in stroke patients is associated with the volume of stroke lesion in the parahippocampal gyrus and with dysfunction of the hypothalamic-pituitary-adrenal axis.

Individualized diffeomorphic mapping of brains with large cortical infarcts

Whole brain mapping of stroke patients with large cortical infarcts is not trivial due to the complexity of infarcts' anatomical location and appearance in magnetic resonance image. In this study, we proposed an individualized diffeomorphic mapping framework for solving this problem. This framework is based on our recent work of large deformation diffeomorphic metric mapping (LDDMM) in Du et al. (2011) and incorporates anatomical features, such as sulcal/gyral curves, cortical surfaces, brain intensity image, and masks of infarcted regions, in order to align a normal brain to the brain of stroke patients. We applied this framework to synthetic data and data of stroke patients and validated the mapping accuracy in terms of the alignment of gyral/sulcal curves, sulcal regions, and brain segmentation. Our results revealed that this framework provided comparable mapping results for stroke patients and healthy controls, suggesting the importance of incorporating individualized anatomical features in whole brain mapping of brains with large cortical infarcts.

Graph-based inter-subject pattern analysis of FMRI data

In brain imaging, solving learning problems in multi-subjects settings is difficult because of the differences that exist across individuals. Here we introduce a novel classification framework based on group-invariant graphical representations, allowing to overcome the inter-subject variability present in functional magnetic resonance imaging (fMRI) data and to perform multivariate pattern analysis across subjects. Our contribution is twofold: first, we propose an unsupervised representation learning scheme that encodes all relevant characteristics of distributed fMRI patterns into attributed graphs; second, we introduce a custom-designed graph kernel that exploits all these characteristics and makes it possible to perform supervised learning (here, classification) directly in graph space. The well-foundedness of our technique and the robustness of the performance to the parameter setting are demonstrated through inter-subject classification experiments conducted on both artificial data and a real fMRI experiment aimed at characterizing local cortical representations. Our results show that our framework produces accurate inter-subject predictions and that it outperforms a wide range of state-of-the-art vector- and parcel-based classification methods. Moreover, the genericity of our method makes it is easily adaptable to a wide range of potential applications. The dataset used in this study and an implementation of our framework are available at http://dx.doi.org/10.6084/m9.figshare.1086317.

Metric optimization for surface analysis in the Laplace-Beltrami embedding space

In this paper, we present a novel approach for the intrinsic mapping of anatomical surfaces and its application in brain mapping research. Using the Laplace-Beltrami eigen-system, we represent each surface with an isometry invariant embedding in a high dimensional space. The key idea in our system is that we realize surface deformation in the embedding space via the iterative optimization of a conformal metric without explicitly perturbing the surface or its embedding. By minimizing a distance measure in the embedding space with metric optimization, our method generates a conformal map directly between surfaces with highly uniform metric distortion and the ability of aligning salient geometric features. Besides pairwise surface maps, we also extend the metric optimization approach for group-wise atlas construction and multi-atlas cortical label fusion. In experimental results, we demonstrate the robustness and generality of our method by applying it to map both cortical and hippocampal surfaces in population studies. For cortical labeling, our method achieves excellent performance in a cross-validation experiment with 40 manually labeled surfaces, and successfully models localized brain development in a pediatric study of 80 subjects. For hippocampal mapping, our method produces much more significant results than two popular tools on a multiple sclerosis study of 109 subjects.

Hidden synaptic differences in a neural circuit underlie differential behavioral susceptibility to a neural injury

Individuals vary in their responses to stroke and trauma, hampering predictions of outcomes. One reason might be that neural circuits contain hidden variability that becomes relevant only when those individuals are challenged by injury. We found that in the mollusc, Tritonia diomedea, subtle differences between animals within the neural circuit underlying swimming behavior had no behavioral relevance under normal conditions but caused differential vulnerability of the behavior to a particular brain lesion. The extent of motor impairment correlated with the site of spike initiation in a specific neuron in the neural circuit, which was determined by the strength of an inhibitory synapse onto this neuron. Artificially increasing or decreasing this inhibitory synaptic conductance with dynamic clamp correspondingly altered the extent of motor impairment by the lesion without affecting normal operation. The results suggest that neural circuit differences could serve as hidden phenotypes for predicting the behavioral outcome of neural damage.

Motivated Memories: Effects of Reward and Recollection in the Core Recollection Network and Beyond

fMRI was employed to assess whether the neural correlates of accurate source memory are modulated by the reward value of recollected information. Study items comprised pictures of objects, each paired with a depiction of 1 of 2 coins. The reward value of the coins ($2.00 vs. $0.02) was disclosed after study. At test, a source memory procedure was employed in which subjects discriminated between studied and unstudied objects and, for objects judged studied, indicated the identity of the coin paired with the object at study. Correct judgments earned a reward corresponding to the value of the coin, whereas incorrect judgments were penalized. No regions were identified where the magnitude of recollection effects was modulated by reward. Exclusive effects of source accuracy were evident in the hippocampus. Different striatal sub-regions demonstrated exclusive recollection effects, exclusive reward effects, and overlap between the 2 effects. The left angular gyrus and medial prefrontal cortex were additively responsive to source accuracy and the reward. The findings suggest that reward value and recollection success are conjointly but independently represented in at least 2 cortical regions and that striatal retrieval success effects cannot be accounted for in terms of a single construct, such as goal satisfaction.

Sleep deficits in mild cognitive impairment are related to increased levels of plasma amyloid-β and cortical thinning

Evidence suggests that amyloid-beta (Aβ) depositions parallel sleep deficits in Alzheimer's disease (AD). However, it remains unknown whether impaired sleep and changes in plasma Aβ levels are related in amnestic mild cognitive impairment (aMCI) subjects, and whether both markers are further associated with cortical thinning in canonical AD regions. To jointly address this issue, we investigated relationships between changes in physiological sleep and plasma Aβ concentrations in 21 healthy old (HO) adults and 21 aMCI subjects, and further assessed whether these two factors were associated with cortical loss in each group. aMCI, but not HO subjects, showed significant relationships between disrupted slow-wave sleep (SWS) and increased plasma levels of Aβ42. We also found that shortened rapid-eye movement (REM) sleep in aMCI correlated with thinning of the posterior cingulate, precuneus, and postcentral gyrus; whereas higher levels of Aβ40 and Aβ42 accounted for grey matter (GM) loss of posterior cingulate and entorhinal cortex, respectively. These results support preliminary relationships between Aβ burden and altered sleep physiology observed in animal models of AD amyloidosis, and provide precise cortical correlates of these changes in older adults with aMCI. Taken together, these findings open new research avenues on the combined role of sleep, peripheral Aβ levels and cortical integrity in tracking the progression from normal aging to early neurodegeneration.

Local analysis of human cortex in MRI brain volume

This paper describes a method for subcortical identification and labeling of 3D medical MRI images. Indeed, the ability to identify similarities between the most characteristic subcortical structures such as sulci and gyri is helpful for human brain mapping studies in general and medical diagnosis in particular. However, these structures vary greatly from one individual to another because they have different geometric properties. For this purpose, we have developed an efficient tool that allows a user to start with brain imaging, to segment the border gray/white matter, to simplify the obtained cortex surface, and to describe this shape locally in order to identify homogeneous features. In this paper, a segmentation procedure using geometric curvature properties that provide an efficient discrimination for local shape is implemented on the brain cortical surface. Experimental results demonstrate the effectiveness and the validity of our approach.

Measuring the dynamic longitudinal cortex development in infants by reconstruction of temporally consistent cortical surfaces

Quantitative measurement of the dynamic longitudinal cortex development during early postnatal stages is of great importance to understand the early cortical structural and functional development. Conventional methods usually reconstruct the cortical surfaces of longitudinal images from the same subject independently, which often generate longitudinally-inconsistent cortical surfaces and thus lead to inaccurate measurement of cortical changes, especially for vertex-wise mapping of cortical development. This paper aims to address this problem by presenting a method to reconstruct temporally-consistent cortical surfaces from longitudinal infant brain MR images, for accurate and consistent measurement of the dynamic cortex development in infants. Specifically, the longitudinal development of the inner cortical surface is first modeled by a deformable growth sheet with elasto-plasticity property to establish longitudinally smooth correspondences of the inner cortical surfaces. Then, the modeled longitudinal inner cortical surfaces are jointly deformed to locate both inner and outer cortical surfaces with a spatial-temporal deformable surface method. The method has been applied to 13 healthy infants, each with 6 serial MR scans acquired at 2 weeks, 3 months, 6 months, 9 months, 12 months and 18 months of age. Experimental results showed that our method with the incorporated longitudinal constraints can reconstruct the longitudinally-dynamic cortical surfaces from serial infant MR images more consistently and accurately than the previously published methods. By using our method, for the first time, we can characterize the vertex-wise longitudinal cortical thickness development trajectory at multiple time points in the first 18 months of life. Specifically, we found the highly age-related and regionally-heterogeneous developmental trajectories of the cortical thickness during this period, with the cortical thickness increased most from 3 to 6 months (16.2%) and least from 9 to 12 months (less than 0.1%). Specifically, the central sulcus only underwent significant increase of cortical thickness from 6 to 9 months and the occipital cortex underwent significant increase from 0 to 9 months, while the frontal, temporal and parietal cortices grew continuously in this first 18 months of life. The adult-like spatial patterns of cortical thickness were generally present at 18 months of age. These results provided detailed insights into the dynamic trajectory of the cortical thickness development in infants.

Effects of spatial pattern scale of brain activity on the sensitivity of DOT, fMRI, EEG and MEG

The objective of this work is to quantify how patterns of cortical activity at different spatial scales are measured by noninvasive functional neuroimaging sensors. We simulated cortical activation patterns at nine different spatial scales in a realistic head model and propagated this activity to magnetoencephalography (MEG), electroencephalography (EEG), diffuse optical tomography (DOT), and functional magnetic resonance imaging (fMRI) sensors in arrangements that are typically used in functional neuroimaging studies. We estimated contrast transfer functions (CTF), correlation distances in sensor space, and the minimum resolvable spatial scale of cortical activity for each modality. We found that CTF decreases as the spatial extent of cortical activity decreases, and that correlations between nearby sensors depend on the spatial extent of cortical activity. For cortical activity on the intermediate spatial scale of 6.7 cm(2), the correlation distances (r>0.5) were 1.0 cm for fMRI, 2.0 cm for DOT, 12.8 for EEG, 9.5 cm for MEG magnetometers and 9.7 cm for MEG gradiometers. The resolvable spatial pattern scale was found to be 1.43 cm(2) for MEG magnetometers, 0.88 cm(2) for MEG gradiometers, 376 cm(2) for EEG, 0.75 cm(2) for DOT, and 0.072 cm(2) for fMRI. These findings show that sensitivity to cortical activity varies substantially as a function of spatial scale within and between the different imaging modalities. This information should be taken into account when interpreting neuroimaging data and when choosing the number of nodes for network analyses in sensor space.

Mapping individual brains to guide restorative therapy after stroke: Rationale and pilot studies

Some treatments under development to improve motor outcome after stroke require information about organization of individual subject's brain. The current study aimed to characterize normal inter-subject differences in localization of motor functions, and to consider these findings in relation to a potential treatment of motor deficits after stroke. Functional MRI (fMRI) scanning in 14 subjects examined right index finger tapping, shoulder rotation, or facial movement. The largest activation cluster in left sensorimotor cortex was identified for each task, and its center expressed in Talairach stereotaxic coordinates. Across subjects, each task showed considerable variability in activation site coordinates. For example, during finger tapping, the range for center of activation was 7 mm in the x-axis, 19 mm in the y-axis, and 11 mm in the z-axis. The mean value for center of activation was significantly different for all three coordinates for all pairwise task comparisons. However, the distribution of activation site centers for the finger task overlapped with the other two tasks in the x- and y-axes, and with the shoulder task in the z-axis. On average, the center of activation for the three motor tasks were spatially separated and somatotopically distributed. However, across the population, there was considerable overlap in the center of activation site, especially for finger and shoulder movements. Restorative therapies that aim to target specific body segments, such as the hand, in the post-stroke motor system may need to map the individual brain rather than rely on population averages. Initial details are presented of a study using this approach to evaluate such a therapy.

The cognitive significance of resonating neurons in the cerebral cortex

Most neural fibers of the cerebral cortex engage in electric signaling, but one particular fiber, the apical dendrite of the pyramidal neuron, specializes in electric resonating. This dendrite extends upward from somas of pyramidal neurons, the most numerous neurons of the cortex. The apical dendrite is embedded in a recurrent corticothalamic circuit that induces surges of electric current to move repeatedly down the dendrite. Narrow bandwidths of surge frequency (resonating) enable cortical circuits to use specific carrier frequencies, which isolate the processing of those circuits from other circuits. Resonating greatly enhances the intensity and duration of electrical activity of a neuron over a narrow frequency range, which underlies attention in its various modes. Within the minicolumn, separation of the central resonating circuit from the surrounding signal processing network separates "having" subjective impressions from "thinking about" them. Resonating neurons in the insular cortex apparently underlie cognitive impressions of feelings.

Automated parcellation of the brain surface generated from magnetic resonance images

We have developed a fast and reliable pipeline to automatically parcellate the cortical surface into sub-regions. The pipeline can be used to study brain changes associated with psychiatric and neurological disorders. First, a genus zero cortical surface for one hemisphere is generated from the magnetic resonance images at the parametric boundary of the white matter and the gray matter. Second, a hemisphere-specific surface atlas is registered to the cortical surface using geometry features mapped in the spherical domain. The deformation field is used to warp statistic labels from the atlas to the subject surface. The Dice index of the labeled surface area is used to evaluate the similarity between the automated labels with the manual labels on the subject. The average Dice across 24 regions on 14 testing subjects is 0.86. Alternative evaluations have also chosen to show the accuracy and flexibility of the present method. The point-wise accuracy of 14 testing subjects is above 86% in average. The experiment shows that the present method is highly consistent with FreeSurfer (>99% of the surface area), using the same set of labels.

Age- and gender-related regional variations of human brain cortical thickness, complexity, and gradient in the third decade

Brain functional and cytoarchitectural maturation continue until adulthood, but little is known about the evolution of the regional pattern of cortical thickness (CT), complexity (CC), and intensity or gradient (CG) in young adults. We attempted to detect global and regional age- and gender-related variations of brain CT, CC, and CG, in 28 healthy young adults (19-33 years) using a three-dimensional T1 -weighted magnetic resonance imaging sequence and surface-based methods. Whole brain interindividual variations of CT and CG were similar to that in the literature. As a new finding, age- and gender-related variations significantly affected brain complexity (P < 0.01) on posterior cingulate and middle temporal cortices (age), and the fronto-orbital cortex (gender), all in the right hemisphere. Regions of interest analyses showed age and gender significant interaction (P < 0.05) on the temporopolar, inferior, and middle temporal-entorrhinal cortices bilaterally, as well as left inferior parietal. In addition, we found significant inverse correlations between CT and CC and between CT and CG over the whole brain and markedly in precentral and occipital areas. Our findings differ in details from previous reports and may correlate with late brain maturation and learning plasticity in young adults' brain in the third decade.

Genetics of brain structure: contributions from the Vietnam Era Twin Study of Aging

Understanding the genetics of neuropsychiatric disorders requires an understanding of the genetics of brain structure and function. The Vietnam Era Twin Study of Aging (VETSA) is a longitudinal behavioral genetic study focused on cognitive and brain aging. Here, we describe basic science work carried out within the VETSA MRI study that provides meaningful contributions toward the study of neuropsychiatric disorders. VETSA produced the first comprehensive assessment of the heritability of cortical and subcortical brain structure sizes, all within the same individuals. We showed that neocortical thickness and surface area are largely genetically distinct. With continuous neocortical thickness maps, we demonstrated regional specificity of genetic influences, and that genetic factors did not conform to traditional regions of interest (ROIs). However, there was some evidence for different genetic factors accounting for different types of cortex, and for genetic relationships across cortical regions corresponding to anatomical and functional connectivity and brain maturation patterns. With continuous neocortical surface area maps, we confirmed the anterior-posterior gradient of genetic influences on cortical area patterning demonstrated in animal models. Finally, we used twin methods to create the first map of cortical ROIs based entirely on genetically informative data. We conclude that these genetically based cortical phenotypes may be more appropriate for genetic studies than traditional ROIs based on structure or function. Our results also suggest that cortical volume-the product of thickness and surface area-is a problematic phenotype for genetic studies because two independent sets of genes may be obscured. Examples supporting the validity of these conclusions are provided.

Ricci Flow-based Spherical Parameterization and Surface Registration

This paper presents an improved Euclidean Ricci flow method for spherical parameterization. We subsequently invent a scale space processing built upon Ricci energy to extract robust surface features for accurate surface registration. Since our method is based on the proposed Euclidean Ricci flow, it inherits the properties of Ricci flow such as conformality, robustness and intrinsicalness, facilitating efficient and effective surface mapping. Compared with other surface registration methods using curvature or sulci pattern, our method demonstrates a significant improvement for surface registration. In addition, Ricci energy can capture local differences for surface analysis as shown in the experiments and applications.

Definition of a stereotactic 3-dimensional magnetic resonance imaging template of the human insula

BACKGROUND

This study proposes a 3-dimensional (3-D) template of the insula in the bicommissural reference system with posterior commissure (PC) as the center of coordinates.

OBJECTIVE

Using the bicommissural anterior commissure (AC)-PC reference system, this study aimed to define a template and design a method for the 3-D reconstruction of the human insula that may be used at an individual level during stereotactic surgery.

METHODS

Magnetic resonance imaging (MRI)-based morphometric analysis was performed on 100 cerebral cortices with normal insulae based on a 3-step procedure: Step 1: AC-PC reference system-based reconstruction of the insula from the 1-mm thick 3-D T1-weighted MRI slices. Step 2: Digitalization and superposition of the data obtained in the 3 spatial planes. Step 3: Representation of pixels as colors on a scale corresponding to the probability of localization of each insular anatomic component.

RESULTS

The morphometric analysis of the insula confirmed our previously reported findings of a more complex shape delimited by 4 peri-insular sulci. A very significant correlation between the coordinates of the main insular structures and the length of AC-PC was demonstrated. This close correlation allowed us to develop a method that allows the 3-D reconstruction of the insula from MRI slices and only requires the localization of AC and PC. This process defines an area deemed to contain insula with 100% probability.

CONCLUSION

This 3-D reconstruction of the insula should be useful to improve its localization and other cortical areas and allow the differentiation of insular cortex from opercular cortex.

Hemispherically-unified surface maps of human cerebral cortex: reliability and hemispheric asymmetries

Understanding the anatomical and structural organization of the cerebral cortex is facilitated by surface-based analysis enabled by FreeSurfer, Caret, and related tools. Here, we examine the precision of FreeSurfer parcellation of the cortex and introduce a method to align FreeSurfer-registered left and right hemispheres onto a common template in order to characterize hemispheric asymmetries. The results are visualized using Mollweide projections, an area-preserving map. The regional distribution, inter-hemispheric asymmetries and intersubject variability in cortical curvature, sulcal depth, cortical thickness, and cortical surface area of 138 young, right handed subjects were analyzed on the Mollweide projection map of the common spherical space. The results show that gyral and sulcal structures are aligned with high but variable accuracy in different cortical regions and show consistent hemispheric asymmetries that are maximal in posterior temporal regions.

Morphometry of corpus callosum in Williams syndrome: shape as an index of neural development

Brain abnormalities in Williams syndrome (WS) have been consistently reported, despite few studies have devoted attention to connectivity between different brain regions in WS. In this study, we evaluated corpus callosum (CC) morphometry: bending angle, length, thickness and curvature of CC using a new shape analysis method in a group of 17 individuals with WS matched with a typically developing group. We used this multimethod approach because we hypothesized that neurodevelopmental abnormalities might result in both volume changes and structure deformation. Overall, we found reduced absolute CC cross-sectional area and volume in WS (mean CC and subsections). In parallel, we observed group differences regarding CC shape and thickness. Specifically, CC of WS is morphologically different, characterized by a larger bending angle and being more curved in the posterior part. Moreover, although CC in WS is shorter, a larger relative thickness of CC was found in all callosal sections. Finally, groups differed regarding the association between CC measures, age, white matter volume and cognitive performance. In conclusions, abnormal patterns of CC morphology and shape may be implicated in WS cognitive and behavioural phenotype.

Focal cortical damage parallels cognitive impairment in minimal hepatic encephalopathy

Little attention has been paid to cortical integrity in patients with minimal hepatic encephalopathy (MHE), although cognitive functions affected in early stages of liver disease are mainly allocated in different neocortical structures. Here we used cortical surface-based analysis techniques to investigate if patterns of cortical thinning accompany the mildest form of HE. To aim this goal, cortical thickness obtained from high-resolution 3T magnetic resonance imaging (MRI) was measured in patients with no MHE (NMHE), MHE, and healthy controls. Further correlation analyses were performed to examine whether scores in the critical flicker frequency (CFF) test, and blood ammonia levels accounted for the loss of cortical integrity in different stages of liver disease. Finally, we assessed group differences in volume of different subcortical regions and their potential relationships with CFF scores/blood ammonia levels. Results showed a focal thinning of the superior temporal cortex and precuneus in MHE patients when compared with NMHE and controls. Relationships between blood ammonia levels and cortical thickness of the calcarine sulcus accounted for impaired visual judgment in patients with MHE when compared to NMHE. Regression analyses between cortical thickness and CFF predicted differences between controls and the two groups of HE patients, but failed to discriminate between patients with NMHE and MHE. Taking together, these findings provide the first report of cortical thinning in MHE patients, and they yield novel insights into the neurobiological basis of cognitive impairment associated with early stages of liver diseases.

Consistent reconstruction of cortical surfaces from longitudinal brain MR images

Accurate and consistent reconstruction of cortical surfaces from longitudinal human brain MR images is of great importance in studying longitudinal subtle change of the cerebral cortex. This paper presents a novel deformable surface method for consistent and accurate reconstruction of inner, central and outer cortical surfaces from longitudinal brain MR images. Specifically, the cortical surfaces of the group-mean image of all aligned longitudinal images of the same subject are first reconstructed by a deformable surface method, which is driven by a force derived from the Laplace's equation. And then the longitudinal cortical surfaces are consistently reconstructed by jointly deforming the cortical surfaces of the group-mean image to all longitudinal images. The proposed method has been successfully applied to two sets of longitudinal human brain MR images. Both qualitative and quantitative experimental results demonstrate the accuracy and consistency of the proposed method. Furthermore, the reconstructed longitudinal cortical surfaces are used to measure the longitudinal changes of cortical thickness in both normal and diseased groups, where the overall decline trend of cortical thickness has been clearly observed. Meanwhile, the longitudinal cortical thickness also shows its potential in distinguishing different clinical groups.

Cortical parcellations of the macaque monkey analyzed on surface-based atlases

Surface-based atlases provide a valuable way to analyze and visualize the functional organization of cerebral cortex. Surface-based registration (SBR) is a primary method for aligning individual hemispheres to a surface-based atlas. We used landmark-constrained SBR to register many published parcellation schemes to the macaque F99 surface-based atlas. This enables objective comparison of both similarities and differences across parcellations. Cortical areas in the macaque vary in surface area by more than 2 orders of magnitude. Based on a composite parcellation derived from 3 major sources, the total number of macaque neocortical and transitional cortical areas is estimated to be about 130-140 in each hemisphere.

Parcellations and hemispheric asymmetries of human cerebral cortex analyzed on surface-based atlases

We report on surface-based analyses that enhance our understanding of human cortical organization, including its convolutions and its parcellation into many distinct areas. The surface area of human neocortex averages 973 cm(2) per hemisphere, based on cortical midthickness surfaces of 2 cohorts of subjects. We implemented a method to register individual subjects to a hybrid version of the FreeSurfer "fsaverage" atlas whose left and right hemispheres are in precise geographic correspondence. Cortical folding patterns in the resultant population-average "fs_LR" midthickness surfaces are remarkably similar in the left and right hemispheres, even in regions showing significant asymmetry in 3D position. Both hemispheres are equal in average surface area, but hotspots of surface area asymmetry are present in the Sylvian Fissure and elsewhere, together with a broad pattern of asymmetries that are significant though small in magnitude. Multiple cortical parcellation schemes registered to the human atlas provide valuable reference data sets for comparisons with other studies. Identified cortical areas vary in size by more than 2 orders of magnitude. The total number of human neocortical areas is estimated to be ∼150 to 200 areas per hemisphere, which is modestly larger than a recent estimate for the macaque.

Cortical cartography and Caret software

Caret software is widely used for analyzing and visualizing many types of fMRI data, often in conjunction with experimental data from other modalities. This article places Caret's development in a historical context that spans three decades of brain mapping--from the early days of manually generated flat maps to the nascent field of human connectomics. It also highlights some of Caret's distinctive capabilities. This includes the ease of visualizing data on surfaces and/or volumes and on atlases as well as individual subjects. Caret can display many types of experimental data using various combinations of overlays (e.g., fMRI activation maps, cortical parcellations, areal boundaries), and it has other features that facilitate the analysis and visualization of complex neuroimaging datasets.

Stroke lesion in cortical neural circuits and post-stroke incidence of major depressive episode: a 4-month prospective study

OBJECTIVE

Little is known about the relevance of lesion in neural circuits reported to be associated with major depressive disorder. We investigated the association between lesion stroke size in the limbic-cortical-striatal-pallidal-thalamic (LCSPT) circuit and incidence of major depressive episode (MDE).

METHODS

We enrolled 68 patients with first-ever ischemic stroke and no history of major depressive disorder. Neurological and psychiatric examinations were performed at three time-points. We diagnosed major depressive episode, following DSM-IV criteria. Lesion location and volume were determined with magnetic resonance imaging, using a semi-automated method based on the Brodmann Cytoarchitectonic Atlas.

RESULTS

Twenty-one patients (31%) experienced major depressive episode. Larger lesions in the left cortical regions of the LCSPT circuit (3,760 vs. 660 mm3; P = 0.004) were associated with higher incidence of MDE. Secondary analyses revealed that major depressive episode was associated with larger lesions in areas of the medial prefrontal cortex including the ventral (BA24) and dorsal anterior cingulate cortex (BA32) and subgenual cortex (BA25); and also the subiculum (BA28/36) and amygdala (BA34).

CONCLUSIONS

Our findings indicate that depression due to stroke is aetiologically related to the disruption of the left LCSPT circuit and support the relevance of the medial prefrontal cortex dysfunction in the pathophysiology of depression.

Landmark optimization using local curvature for point-based nonlinear rodent brain image registration

Purpose. To develop a technique to automate landmark selection for point-based interpolating transformations for nonlinear medical image registration. Materials and Methods. Interpolating transformations were calculated from homologous point landmarks on the source (image to be transformed) and target (reference image). Point landmarks are placed at regular intervals on contours of anatomical features, and their positions are optimized along the contour surface by a function composed of curvature similarity and displacements of the homologous landmarks. The method was evaluated in two cases (n = 5 each). In one, MRI was registered to histological sections; in the second, geometric distortions in EPI MRI were corrected. Normalized mutual information and target registration error were calculated to compare the registration accuracy of the automatically and manually generated landmarks. Results. Statistical analyses demonstrated significant improvement (P < 0.05) in registration accuracy by landmark optimization in most data sets and trends towards improvement (P < 0.1) in others as compared to manual landmark selection.

CoRPORATE: cortical reconstruction by pruning outliers with Reeb analysis and topology-preserving evolution

In this paper we propose a novel system for the accurate reconstruction of cortical surfaces from magnetic resonance images. At the core of our system is a novel framework for outlier detection and pruning by integrating intrinsic Reeb analysis of Laplace-Beltrami eigen-functions with topology-preserving evolution for localized filtering of outliers, which avoids unnecessary smoothing and shrinkage of cortical regions with high curvature. In our experiments, we compare our method with FreeSurfer and illustrate that our results can better capture cortical geometry in deep sulcal regions. To demonstrate the robustness of our method, we apply it to over 1300 scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We show that cross-sectional group differences and longitudinal changes can be detected successfully with our method.

Measuring structural-functional correspondence: spatial variability of specialised brain regions after macro-anatomical alignment

The central question of the relationship between structure and function in the human brain is still not well understood. In order to investigate this fundamental relationship we create functional probabilistic maps from a large set of mapping experiments and compare the location of functionally localised regions across subjects using different whole-brain alignment schemes. To avoid the major problems associated with meta-analysis approaches, all subjects are scanned using the same paradigms, the same scanner and the same analysis pipeline. We show that an advanced, curvature driven cortex based alignment (CBA) scheme largely removes macro-anatomical variability across subjects. Remaining variability in the observed spatial location of functional regions, thus, reflects the "true" functional variability, i.e. the quantified variability is a good estimator of the underlying structural-functional correspondence. After localising 13 widely studied functional areas, we found a large variability in the degree to which functional areas respect macro-anatomical boundaries across the cortex. Some areas, such as the frontal eye fields (FEF) are strongly bound to a macro-anatomical location. Fusiform face area (FFA) on the other hand, varies in its location along the length of the fusiform gyrus even though the gyri themselves are well aligned across subjects. Language areas were found to vary greatly across subjects whilst a high degree of overlap was observed in sensory and motor areas. The observed differences in functional variability for different specialised areas suggest that a more complete estimation of the structure-function relationship across the whole cortex requires further empirical studies with an expanded test battery.

Whole brain diffeomorphic metric mapping via integration of sulcal and gyral curves, cortical surfaces, and images

This paper introduces a novel large deformation diffeomorphic metric mapping algorithm for whole brain registration where sulcal and gyral curves, cortical surfaces, and intensity images are simultaneously carried from one subject to another through a flow of diffeomorphisms. To the best of our knowledge, this is the first time that the diffeomorphic metric from one brain to another is derived in a shape space of intensity images and point sets (such as curves and surfaces) in a unified manner. We describe the Euler-Lagrange equation associated with this algorithm with respect to momentum, a linear transformation of the velocity vector field of the diffeomorphic flow. The numerical implementation for solving this variational problem, which involves large-scale kernel convolution in an irregular grid, is made feasible by introducing a class of computationally friendly kernels. We apply this algorithm to align magnetic resonance brain data. Our whole brain mapping results show that our algorithm outperforms the image-based LDDMM algorithm in terms of the mapping accuracy of gyral/sulcal curves, sulcal regions, and cortical and subcortical segmentation. Moreover, our algorithm provides better whole brain alignment than combined volumetric and surface registration (Postelnicu et al., 2009) and hierarchical attribute matching mechanism for elastic registration (HAMMER) (Shen and Davatzikos, 2002) in terms of cortical and subcortical volume segmentation.

The generation of tetrahedral mesh models for neuroanatomical MRI

In this article, we describe a detailed method for automatically generating tetrahedral meshes from 3D images having multiple region labels. An adaptively sized tetrahedral mesh modeling approach is described that is capable of producing meshes conforming precisely to the voxelized regions in the image. Efficient tetrahedral mesh improvement is then performed minimizing an energy function containing three terms: a smoothing term to remove the voxelization, a fidelity term to maintain continuity with the image data, and a novel elasticity term to prevent the tetrahedra from becoming flattened or inverted as the mesh deforms while allowing the voxelization to be removed entirely. The meshing algorithm is applied to structural MR image data that has been automatically segmented into 56 neuroanatomical sub-divisions as well as on two other examples. The resulting tetrahedral representation has several desirable properties such as tetrahedra with dihedral angles away from 0 and 180 degrees, smoothness, and a high resolution. Tetrahedral modeling via the approach described here has applications in modeling brain structure in normal as well as diseased brain in human and non-human data and facilitates examination of 3D object deformations resulting from neurological illness (e.g. Alzheimer's disease), development, and/or aging.

Local Heschl's Gyrus-based coordinate system for intersubject comparison of M50 auditory response modeled by single equivalent current dipole

Allocating electromagnetic auditory responses to active regions in the human auditory cortex can be difficult because of high interindividual variability of the relevant structures. Location and orientation of the primary auditory cortex (Heschl's Gyrus) and the temporal plane vary with individual features such as age, gender, handedness, or between healthy subjects and patients with a psychiatric disorder (e.g., schizophrenia). Here, we propose a reference coordinate system that considers the individual MRI-based position, orientation and length of the primary auditory cortex to account for interindividual variability. Transformation of the M50 dipole localizations in this new HG-(Heschl's-Gyrus)-coordinate system, accomplished for 10 healthy subjects and 10 schizophrenia patients, confirmed group difference more precisely than other registration methods. We suggest to use the HG-coordinate system for localization of functional measures and evaluation of brain activity differences between groups or measurement conditions.

Learning task-optimal registration cost functions for localizing cytoarchitecture and function in the cerebral cortex

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

Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature

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

Connectivity-based parcellation of the cortical mantle using q-ball diffusion imaging

This paper exploits the idea that each individual brain region has a specific connection profile to create parcellations of the cortical mantle using MR diffusion imaging. The parcellation is performed in two steps. First, the cortical mantle is split at a macroscopic level into 36 large gyri using a sulcus recognition system. Then, for each voxel of the cortex, a connection profile is computed using a probabilistic tractography framework. The tractography is performed from q fields using regularized particle trajectories. Fiber ODF are inferred from the q-balls using a sharpening process focusing the weight around the q-ball local maxima. A sophisticated mask of propagation computed from a T1-weighted image perfectly aligned with the diffusion data prevents the particles from crossing the cortical folds. During propagation, the particles father child particles in order to improve the sampling of the long fascicles. For each voxel, intersection of the particle trajectories with the gyri lead to a connectivity profile made up of only 36 connection strengths. These profiles are clustered on a gyrus by gyrus basis using a K-means approach including spatial regularization. The reproducibility of the results is studied for three subjects using spatial normalization.

A combined surface and volumetric registration (SAVOR) framework to study cortical biomarkers and volumetric imaging data

Constructing a one to one correspondence between whole brain MR image scans is a problem of critical importance in neuroimaging analyses. We present a framework to combine the strength of both surface-based and volumetric-based analyses for consistent, bijective data transfer between brain coordinate systems.

Gyral folding pattern analysis via surface profiling

Folding is an essential shape characteristic of the human cerebral cortex. Descriptors of cortical folding patterns have been studied for decades. However, many previous studies are either based on local shape descriptors such as curvature, or based on global descriptors such as gyrification index or spherical wavelets. This paper proposes a gyrus-scale folding pattern analysis technique via cortical surface profiling. Firstly, we sample the cortical surface into 2D profiles and model them using a power function. This step provides both the flexibility of representing arbitrary shape by profiling and the compactness of representing shape by parametric modeling. Secondly, based on the estimated model parameters, we extract affine-invariant features on the cortical surface, and apply the affinity propagation clustering algorithm to parcellate the cortex into cortical regions with strict hierarchy and smooth transitions among them. Finally, a second-round surface profiling is performed on the parcellated cortical surface, and the number of hinges is detected to describe the gyral folding pattern. We have applied the surface profiling method to two normal brain datasets and a schizophrenia patient dataset. The experimental results demonstrate that the proposed method can accurately classify human gyri into 2-hinge, 3-hinge and 4-hinge patterns. The distribution of these folding patterns on brain lobes and the relationship between fiber density and gyral folding patterns are further investigated. Results from the schizophrenia dataset are consistent with commonly found abnormality in former studies by others, which demonstrates the potential clinical applications of the proposed technique.

A computational model of cerebral cortex folding

The geometric complexity and variability of the human cerebral cortex have long intrigued the scientific community. As a result, quantitative description of cortical folding patterns and the understanding of underlying folding mechanisms have emerged as important research goals. This paper presents a computational 3D geometric model of cerebral cortex folding initialized by MRI data of a human fetal brain and deformed under the governance of a partial differential equation modeling cortical growth. By applying different simulation parameters, our model is able to generate folding convolutions and shape dynamics of the cerebral cortex. The simulations of this 3D geometric model provide computational experimental support to the following hypotheses: (1) Mechanical constraints of the skull regulate the cortical folding process. (2) The cortical folding pattern is dependent on the global cell growth rate of the whole cortex. (3) The cortical folding pattern is dependent on relative rates of cell growth in different cortical areas. (4) The cortical folding pattern is dependent on the initial geometry of the cortex.