The claustrum and the insula are closely juxtaposed in the brain of the prosimian primate, the gray mouse lemur (Microcebus murinus). Whether the claustrum has closer affinities with the cortex or the striatum has been debated for many decades. Our observation of histological sections from primate brains and genomic data in the mouse suggest former. Given this, the present study compares the connections of the two structures in Microcebus using high angular resolution diffusion imaging (HARDI, with 72 directions), with a very small voxel size (90 micra), and probabilistic fiber tractography. High angular and spatial resolution diffusion imaging is non-destructive, requires no surgical interventions, and the connection of each and every voxel can be mapped, whereas in conventional tract tracer studies only a few specific injection sites can be assayed. Our data indicate that despite the high genetic and spatial affinities between the two structures, their connectivity patterns are very different. The claustrum connects with many cortical areas and the olfactory bulb; its strongest probabilistic connections are with the entorhinal cortex, suggesting that the claustrum may have a role in spatial memory and navigation. By contrast, the insula connects with many subcortical areas, including the brainstem and thalamic structures involved in taste and visceral feelings. Overall, the connections of the Microcebus claustrum and insula are similar to those of the rodents, cat, macaque, and human, validating our results. The insula in the Microcebus connects with the dorsolateral frontal cortex in contrast to the mouse insula, which has stronger connections with the ventromedial frontal lobe, yet this is consistent with the dorsolateral expansion of the frontal cortex in primates. In addition to revealing the connectivity patterns of the Microcebus brain, our study demonstrates that HARDI, at high resolutions, can be a valuable tool for mapping fiber pathways for multiple sites in fixed brains in rare and difficult-to-obtain species.

Aesthetic responses to visual art comprise multiple types of experiences, from sensation and perception to emotion and self-reflection. Moreover, aesthetic experience is highly individual, with observers varying significantly in their responses to the same artwork. Combining fMRI and behavioral analysis of individual differences in aesthetic response, we identify two distinct patterns of neural activity exhibited by different sub-networks. Activity increased linearly with observers' ratings (4-level scale) in sensory (occipito-temporal) regions. Activity in the striatum (STR) also varied linearly with ratings, with below-baseline activations for low-rated artworks. In contrast, a network of frontal regions showed a step-like increase only for the most moving artworks ("4" ratings) and non-differential activity for all others. This included several regions belonging to the "default mode network"(DMN) previously associated with self-referential mentation. Our results suggest that aesthetic experience involves the integration of sensory and emotional reactions in a manner linked with their personal relevance.

BACKGROUND Primary monosymptomatic nocturnal enuresis (PMNE) is a common disorder in school-aged children. Previous studies have suggested that a developmental delay might play a role in the pathology of children with PMNE. However, microstructural abnormalities in the brains of these children have not been thoroughly investigated. METHODOLOGY/PRINCIPAL FINDINGS In this work, we evaluated structural changes in the brains of children with PMNE using diffusion tensor imaging (DTI). Two groups consisting of 26 children with PMNE and 26 healthy controls were scanned using magnetic resonance DTI. The diffusion parameters of fractional anisotropy (FA) and mean diffusivity (MD) were subjected to whole-brain, voxel-wise group comparisons using statistical parametric mapping (SPM). When compared to healthy subjects, children with PMNE showed both a decrease in FA and an increase in MD in the thalamus. MD also increased in the frontal lobe, the anterior cingulate cortex and the insula; these areas are all involved in controlling micturition. The significant changes seen in the thalamus could affect both urine storage and arousal from sleep. CONCLUSIONS/SIGNIFICANCE The microstructure abnormalities were observed in the thalamus, the medial frontal gyrus, the anterior cingulate cortex and the insula, which are involved in micturition control network. This indicates developmental delay in these areas may be the cause of PMNE.

PURPOSE Benign epilepsy with centrotemporal spikes (BECTS), the most common childhood epilepsy syndrome, is a neurodevelopmental disorder with a genetic influence. Despite its signature electroencephalographic pattern and distinct focal motor seizure semiology, little is known about the underlying brain anatomic alteration and the corresponding cognitive consequences. Given the motor manifestations of seizures in BECTS, we hypothesize that anatomic networks in BECTS involve a distributed corticostriatal circuit. METHODS We investigated volumetric differences and shape deformities of caudate, putamen, pallidum, and thalamus in a group of children with new- and recent-onset BECTS (N =  3) compared to healthy controls (N = 54). We correlated specific subcortical volumes in BECTS that were significantly different from those in healthy controls with performances in executive function. KEY FINDINGS Children with BECTS demonstrated significantly hypertrophied putamen, which was selective among the subcortical regions examined. Shape analysis showed dorsoventral elongation of the left caudate and bilateral putamen, with subnuclei expansion in ventral and dorsal striatum. Larger putamen volumes were linked to better cognitive performances on two complementary executive function tests. SIGNIFICANCE Children with BECTS showed aberrant volume and shape in subcortical regions that are critical for both motor processing and executive function. It is of importance to note that the hypertrophy appears to be cognitively adaptive, as enlargement was associated with improved cognitive performances. The anatomic abnormalities and their cognitive effects are evident in a group of children with new- and recent-onset epilepsy, suggesting that the structural brain anomalies occurred before the diagnosis of epilepsy.

Defining the structural and functional connectivity of the human brain (the human "connectome") is a basic challenge in neuroscience. Recently, techniques for noninvasively characterizing structural connectivity networks in the adult brain have been developed using diffusion and high-resolution anatomic MRI. The purpose of this study was to establish a framework for assessing structural connectivity in the newborn brain at any stage of development and to show how network properties can be derived in a clinical cohort of six-month old infants sustaining perinatal hypoxic ischemic encephalopathy (HIE). Two different anatomically unconstrained parcellation schemes were proposed and the resulting network metrics were correlated with neurological outcome at 6 months. Elimination and correction of unreliable data, automated parcellation of the cortical surface, and assembling the large-scale baby connectome allowed an unbiased study of the network properties of the newborn brain using graph theoretic analysis. In the application to infants with HIE, a trend to declining brain network integration and segregation was observed with increasing neuromotor deficit scores.

Introduction: Attention deficit hyperactivity disorder (ADHD) captures a heterogeneous group of children, who are characterized by a range of cognitive and behavioral symptoms. Previous resting-state functional connectivity MRI (rs-fcMRI) studies have sought to understand the neural correlates of ADHD by comparing connectivity measurements between those with and without the disorder, focusing primarily on cortical-striatal circuits mediated by the thalamus. To integrate the multiple phenotypic features associated with ADHD and help resolve its heterogeneity, it is helpful to determine how specific circuits relate to unique cognitive domains of the ADHD syndrome. Spatial working memory has been proposed as a key mechanism in the pathophysiology of ADHD. Methods: We correlated the rs-fcMRI of five thalamic regions of interest (ROIs) with spatial span working memory scores in a sample of 67 children aged 7-11 years [ADHD and typically developing children (TDC)]. In an independent dataset, we then examined group differences in thalamo-striatal functional connectivity between 70 ADHD and 89 TDC (7-11 years) from the ADHD-200 dataset. Thalamic ROIs were created based on previous methods that utilize known thalamo-cortical loops and rs-fcMRI to identify functional boundaries in the thalamus. Results/Conclusion: Using these thalamic regions, we found atypical rs-fcMRI between specific thalamic groupings with the basal ganglia. To identify the thalamic connections that relate to spatial working memory in ADHD, only connections identified in both the correlational and comparative analyses were considered. Multiple connections between the thalamus and basal ganglia, particularly between medial and anterior dorsal thalamus and the putamen, were related to spatial working memory and also altered in ADHD. These thalamo-striatal disruptions may be one of multiple atypical neural and cognitive mechanisms that relate to the ADHD clinical phenotype.

BACKGROUND Stereotactic targets for thalamotomy are usually derived from population-based coordinates. Individual anatomy is used only to scale the coordinates based on the location of some internal guide points. While on conventional MR imaging the thalamic nuclei are indistinguishable, recently it has become possible to identify individual thalamic nuclei using different connectivity profiles, as defined by MR diffusion tractography. METHODOLOGY AND PRINCIPAL FINDINGS Here we investigated the inter-individual variation of the location of target nuclei for thalamotomy: the putative ventralis oralis posterior (Vop) and the ventral intermedius (Vim) nucleus as defined by probabilistic tractography. We showed that the mean inter-individual distance of the peak Vop location is 7.33 mm and 7.42 mm for Vim. The mean overlap between individual Vop nuclei was 40.2% and it was 31.8% for Vim nuclei. As a proof of concept, we also present a patient who underwent Vop thalamotomy for untreatable tremor caused by traumatic brain injury and another patient who underwent Vim thalamotomy for essential tremor. The probabilistic tractography indicated that the successful tremor control was achieved with lesions in the Vop and Vim respectively. CONCLUSIONS Our data call attention to the need for a better appreciation of the individual anatomy when planning stereotactic functional neurosurgery.

STUDY OBJECTIVE This study aims at providing a quantitative description of intrinsic spindle frequency and density (number of spindles/min) in cortical areas using deep intracerebral recordings in humans. PATIENTS OR PARTICIPANTS Thirteen patients suffering from pharmaco-resistant focal epilepsy and investigated through deep intracortical EEG in frontal, parietal, temporal, occipital, insular, and limbic cortices including the hippocampus were included. METHODS Spindle waves were detected from the ongoing EEG during slow wave sleep (SWS) by performing a time-frequency analysis on filtered signals (band-pass filter: 10-16 Hz). Then, spindle intrinsic frequency was determined using a fast Fourier transform, and spindle density (number of spindles per minute) was computed. RESULTS Firstly, we showed that sleep spindles were recorded in all explored cortical areas, except temporal neocortex. In particular, we observed the presence of spindles during SWS in areas such as the insular cortex, medial parietal cortex, occipital cortex, and cingulate gyrus. Secondly, we demonstrated that both spindle frequency and density smoothly change along the caudo-rostral axis, from fast frequent posterior spindles to slower and less frequent anterior spindles. Thirdly, we identified the presence of spindle frequency oscillations in the hippocampus and the entorhinal cortex. CONCLUSIONS Spindling activity is widespread among cortical areas, which argues for the fundamental role of spindles in cortical functions. Mechanisms of caudo-rostral gradient modulation in spindle frequency and density may result from a complex interplay of intrinsic properties and extrinsic modulation of thalamocortical and corticothalamic neurons.

A fundamental assumption in neuroscience is that brain structure determines function. Accordingly, functionally distinct regions of cortex should be structurally distinct in their connections to other areas. We tested this hypothesis in relation to face selectivity in the fusiform gyrus. By using only structural connectivity, as measured through diffusion-weighted imaging, we were able to predict functional activation to faces in the fusiform gyrus. These predictions outperformed two control models and a standard group-average benchmark. The structure-function relationship discovered from the initial participants was highly robust in predicting activation in a second group of participants, despite differences in acquisition parameters and stimuli. This approach can thus reliably estimate activation in participants who cannot perform functional imaging tasks and is an alternative to group-activation maps. Additionally, we identified cortical regions whose connectivity was highly influential in predicting face selectivity within the fusiform, suggesting a possible mechanistic architecture underlying face processing in humans.

Even in the simplest laboratory tasks older adults generally take more time to respond than young adults. One of the reasons for this age-related slowing is that older adults are reluctant to commit errors, a cautious attitude that prompts them to accumulate more information before making a decision (Rabbitt, 1979). This suggests that age-related slowing may be partly due to unwillingness on behalf of elderly participants to adopt a fast-but-careless setting when asked. We investigate the neuroanatomical and neurocognitive basis of age-related slowing in a perceptual decision-making task where cues instructed young and old participants to respond either quickly or accurately. Mathematical modeling of the behavioral data confirmed that cueing for speed encouraged participants to set low response thresholds, but this was more evident in younger than older participants. Diffusion weighted structural images suggest that the more cautious threshold settings of older participants may be due to a reduction of white matter integrity in corticostriatal tracts that connect the pre-SMA to the striatum. These results are consistent with the striatal account of the speed-accuracy tradeoff according to which an increased emphasis on response speed increases the cortical input to the striatum, resulting in global disinhibition of the cortex. Our findings suggest that the unwillingness of older adults to adopt fast speed-accuracy tradeoff settings may not just reflect a strategic choice that is entirely under voluntary control, but that it may also reflect structural limitations: age-related decrements in brain connectivity.

A fully probabilistic framework is presented for estimating local probability density functions on parameters of interest in a model of diffusion. This technique is applied to the estimation of parameters in the diffusion tensor model, and also to a simple partial volume model of diffusion. In both cases the parameters of interest include parameters defining local fiber direction. A technique is then presented for using these density functions to estimate global connectivity (i.e., the probability of the existence of a connection through the data field, between any two distant points), allowing for the quantification of belief in tractography results. This technique is then applied to the estimation of the cortical connectivity of the human thalamus. The resulting connectivity distributions correspond well with predictions from invasive tracer methods in nonhuman primate.

A fundamental issue in neuroscience is the relation between structure and function. However, gross landmarks do not correspond well to microstructural borders and cytoarchitecture cannot be visualized in a living brain used for functional studies. Here, we used diffusion-weighted and functional MRI to test structure-function relations directly. Distinct neocortical regions were defined as volumes having similar connectivity profiles and borders identified where connectivity changed. Without using prior information, we found an abrupt profile change where the border between supplementary motor area (SMA) and pre-SMA is expected. Consistent with this anatomical assignment, putative SMA and pre-SMA connected to motor and prefrontal regions, respectively. Excellent spatial correlations were found between volumes defined by using connectivity alone and volumes activated during tasks designed to involve SMA or pre-SMA selectively. This finding demonstrates a strong relationship between structure and function in medial frontal cortex and offers a strategy for testing such correspondences elsewhere in the brain.

The aim of this study is to propose methods for assessing the reproducibility of diffusion tractography algorithms in future clinical studies and to show their application to the tractography algorithm developed in our unit, fast marching tractography (FMT). FMT estimates anatomical connectivity between brain regions using the information provided by diffusion tensor imaging. Three major white-matter pathways were investigated in 11 normal subjects--anterior callosal fibers, optic radiations, and pyramidal tracts. FMT was used to generate maps of connectivity metric, and regions of voxels with highest connectivity metric to an anatomically defined starting point were identified for each tract under investigation. The reproducibilities of tract-"normalized" volume (NV) and fractional anisotropy (FA) measurements were assessed over such regions. The values of tract volumes are consistent with the postmortem data. Coefficients of variation (CVs) for FA and NV ranged from 1.7 to 7.1% and from 2.2 to 18.6%, respectively. CVs were lowest in the anterior callosal fibers (range: 1.7- 7.8%), followed by the optic radiations (range: 1.2-18.6%) and pyramidal tracts (range: 2.6-15.5%), suggesting that fiber organization plays a role in determining the level of FMT reproducibility. In conclusion, these findings underline the importance of assessing the reliability of diffusion tractography before investigating white matter pathology.

The goal of probabilistic tractography is to obtain a connectivity index along a white matter pathway that reflects fibre organization and is sensitive to pathological abnormalities contributing to disability. Here, we present the development of voxel-based connectivity measures along the tractography-derived corticospinal tract (CST). We investigated whether these connectivity measures are different in patients with amyotrophic lateral sclerosis (ALS) and correlate with the rate of disease progression. We also investigated whether fractional anisotropy (FA), which reflects directional coherence of fibre tracts, is reduced in the CST of ALS patients and relates to disease progression rate. Thirteen patients with probable or definite ALS and 19 healthy subjects were studied. The probabilistic tractography algorithm segmented the bilateral CST, along which FA and connectivity values were obtained. To take into account the asymmetric distribution of connectivity values, two summary statistic measures that focused on voxels with higher connectivity values were selected and then used in the analysis, together with the mean connectivity and the mean FA. To complete the analysis, the same summary measures for FA were included. Differences in all these indices between patients with moderate or rapid disease progression rate and controls were investigated using linear regression, adjusted for age and white matter fraction. The association between FA or connectivity in the CST and the disease progression rate was assessed using linear regression. Patients with a rapid disease progression rate had significantly lower summary connectivity measures than controls in the left CST, but there was only a borderline statistical difference in mean connectivity. Patients with rapid progression had a significantly lower mean FA, and any other FA measure, in both CSTs than controls. When only patients were considered, strong associations between the rate of disease progression and all the connectivity measures in the left CST were found (P-values between P < 0.001 and P = 0.002, partial correlation coefficients between -0.90 and -0.82). However, there was no evidence of an association between disease progression rate and any of the FA measures in the bilateral CST. Our findings suggest that FA and connectivity provide complementary information, since FA is sensitive to the detection of all the group differences, whereas the summary connectivity measures correlate with disease progression rate. The development of such connectivity measures raises their potential as markers of disease progression in ALS, and provides guidance for their use in other neurological diseases.

The medial geniculate body (MGB) of the thalamus is a key component of the auditory system. It is involved in relaying and transforming auditory information to the cortex and in top-down modulation of processing in the midbrain, brainstem, and ear. Functional imaging investigations of this region in humans, however, have been limited by the difficulty of distinguishing MGB from other thalamic nuclei. Here, we introduce two methods for reliably delineating MGB anatomically in individuals based on conventional and diffusion MRI data. The first uses high-resolution proton density weighted scanning optimized for subcortical grey-white contrast. The second uses diffusion-weighted imaging and probabilistic tractography to automatically segment the medial and lateral geniculate nuclei from surrounding structures based on their distinctive patterns of connectivity to the rest of the brain. Both methods produce highly replicable results that are consistent with published atlases. Importantly, both methods rely on commonly available imaging sequences and standard hardware, a significant advantage over previously described approaches. In addition to providing useful approaches for identifying the MGB and LGN in vivo, our study offers further validation of diffusion tractography for the parcellation of grey matter regions on the basis of their connectivity patterns.

Tractography uses diffusion tensor imaging data to trace white matter pathways in vivo within the brain. We have constructed group maps that represent three major white matter tracts-the anterior callosal fibers, optic radiations, and pyramidal tracts-in a group of 21 volunteers. For each individual tract the fast marching tractography (FMT) algorithm was used to generate a VSC (voxel scale connectivity) map in native space. Using SPM99 these maps were transformed into a standard reference frame and three group mapping techniques were investigated: the first averaged the individual VSC maps, the second produced maps that demonstrate intersubject tract variability and degree of overlap, and the third used an SPM analysis to construct a statistical image that represents the group effect. The group maps reconstructed for each tract under investigation conform well to known anatomy and are consistent with data derived from postmortem human brains. Greater intersubject variability is found around the terminal projections of the tracts adjacent to cerebral cortex, whereas the "core" of each tract is characterized by lower variability. No significant differences were found between the left and right side of the pyramidal tracts and optic radiations. The group mapping techniques utilize the VSC maps in different but complementary ways. In the future, group mapping could investigate in vivo white matter differences between normal subjects and patients affected by neurological and psychiatric diseases.

Quantitative diffusion analysis of white matter (WM) tracts has been utilised in many diseases for determining damage to, and changes in, WM tracts throughout the brain. However, there are limited studies investigating associations between quantitative measures in WM tracts and anatomically linked grey matter (GM), due to the difficulty in determining GM regions connected with a given WM tract. This work describes a straightforward method for extending a WM tract through GM based on geometry. The tract is extended by following a straight line from each point on the tract boundary to the outer boundary of the cortex. A comparison between a multiplanar 2D approach and a 3D method was made. This study also tested an analysis pipeline from tracking WM tracts to quantifying magnetisation transfer ratios (MTR) in the associated cortical GM, and assessed the applicability of the method to healthy control subjects. Tract and associated cortical volumes and MTR values for the cortico-spinal tracts, genu and body of the corpus callosum were extracted; the between-subjects standard deviation was calculated. It was found that a multiplanar 2D approach produced a more anatomically plausible volume of GM than a 3D approach, at the expense of possible overestimation of the GM volume. The between-subjects standard deviation of the tract specific quantitative measurements (from both the WM and GM masks) ranged between 1.2 and 7.3% for the MTR measures, and between 10 and 45% for the absolute volume measures. The results show that the method can be used to produce anatomically plausible extensions of the WM tracts through the GM, and regions defined in this way yield reliable estimates of the MTR from the regions.

Schippers, Renken and Keysers (NeuroImage, 2011) present a simulation of multi-subject lag-based causality estimation. We fully agree that single-subject evaluations (e.g., Smith et al., 2011) need to be revisited in the context of multi-subject studies, and Schippers' paper is a good example, including detailed multi-level simulation and cross-subject statistical modelling. The authors conclude that "the average chance to find a significant Granger causality effect when no actual influence is present in the data stays well below the p-level imposed on the second level statistics" and that "when the analyses reveal a significant directed influence, this direction was accurate in the vast majority of the cases". Unfortunately, we believe that the general meaning that may be taken from these statements is not supported by the paper's results, as there may in reality be a systematic (group-average) difference in haemodynamic delay between two brain areas. While many statements in the paper (e.g., the final two sentences) do refer to this problem, we fear that the overriding message that many readers may take from the paper could cause misunderstanding.

BACKGROUND White matter (WM) and grey matter (GM) brain damage in multiple sclerosis (MS) is widespread, but the extent of cerebellar involvement and impact on disability needs to be clarified. OBJECTIVE This study aimed to assess cerebellar WM and GM atrophy and the degree of fibre coherence in the main cerebellar connections, and their contribution to disability in relapsing-remitting MS (RRMS) and primary progressive MS (PPMS). METHODS Fourteen patients with RRMS, 12 patients with PPMS and 16 healthy controls were recruited. Cerebellar WM and GM volumes and tractography-derived measures from the middle and superior cerebellar peduncles, including fractional anisotropy (FA), mean diffusivity (MD), and directional diffusivities, were quantified from magnetic resonance imaging (MRI). Patients were assessed on clinical scores, including the MS Functional Composite score subtests. Linear regression models were used to compare imaging measures between 12 RRMS, 11 PPMS and 16 controls, and investigate their association with clinical scores. RESULTS Patients with PPMS showed reduced FA and increased radial diffusivity in the middle cerebellar peduncle compared with controls and patients with RRMS. In PPMS, lower cerebellar WM volume was associated with worse performance on the upper limb test. In the same patient group, we found significant relationships between superior cerebellar peduncle FA and upper limb function, and between superior cerebellar peduncle FA, MD and radial diffusivity and speed of walking. CONCLUSION These findings indicate reduced fibre coherence in the main cerebellar connections, and link damage in the whole cerebellar WM, and, in particular, in the superior cerebellar peduncle, to motor deficit in PPMS.

BACKGROUND Previous work showed that pericalcarine cortical volume loss is evident early after presentation with acute clinically isolated optic neuritis (ON). The aims of this study were:(1) to determine whether pericalcarine atrophy in patients with ON is associated with conversion to multiple sclerosis (MS);(2) to investigate whether regional atrophy preferentially affects pericalcarine cortex; and (3) to investigate potential causes of early pericalcarine atrophy using MRI. METHODS 28 patients with acute ON and 10 controls underwent structural MRI (brain and optic nerves) and were followed-up over 12 months. Associations between the development of MS, optic nerve, optic radiation and pericalcarine cortical damage measures were investigated using multiple linear regression models. Regional cortical volumetric differences between patients and controls were calculated using t tests. RESULTS The development of MS at 12 months was associated with greater whole brain and optic radiation lesion loads, shorter acute optic nerve lesions and smaller pericalcarine cortical volume at baseline. Regional atrophy was not evident in other sampled cortical regions. Pericalcarine atrophy was not directly associated with whole brain lesion load, optic radiation measures or optic nerve lesion length. However, the association between pericalcarine atrophy and MS was not independent of these parameters. CONCLUSIONS Reduced pericalcarine cortical volumes in patients with early clinically isolated ON were associated with the development of MS but volumes of other cortical regions were not. Hence pericalcarine cortical regions appear particularly susceptible to early damage. These findings could be explained by a combination of pathological effects to visual grey and white matter in patients with ON.

Regional structural and functional variations in the posteromedial cortex (PMC) have been found in both animals and humans, strongly suggesting the presence of subdivisions. However, there is no consensus on how to subdivide the human PMC. Here, we investigated the anatomical parcellation scheme and the connectivity pattern of each subdivision of the human PMC using diffusion tensor imaging data from 2 independent groups of volunteers. The parcellation analyses of the 2 datasets consistently demonstrated that the human PMC can be parcellated into 5 subregions. The dorsal portion of the PMC was subdivided into anterior, central, and posterior subregions, which participate in sensorimotor, associative, and visual functions. The ventral PMC contained a transitional region in the dorsal portion and a ventral subregion that is the core of the default mode network. The parcellation results for the human PMC and its anatomical connectivity patterns were further supported by evidence from the macaque PMC. Furthermore, functional connectivity analysis revealed that each subregion exhibited a specific pattern similar to that of its anatomical connectivity. The proposed parcellation scheme may facilitate the study of the human PMC at a subtler level and improve our understanding of its functions.

The parcellation of the cortex via its anatomical properties has been an important research endeavor for over a century. To date, however, a universally accepted parcellation scheme for the human brain still remains elusive. In the current review, we explore the use of in vivo diffusion imaging and white matter tractography as a non-invasive method for the structural and functional parcellation of the human cerebral cortex, discussing the strengths and limitations of the current approaches. Cortical parcellation via white matter connectivity is based on the premise that, as connectional anatomy determines functional organization, it should be possible to segregate functionally-distinct cortical regions by identifying similarities and differences in connectivity profiles. Recent studies have provided initial evidence in support of the efficacy of this connectional parcellation methodology. Such investigations have identified distinct cortical subregions which correlate strongly with functional regions identified via fMRI and meta-analyses. Furthermore, a strong parallel between the cortical regions defined via tractographic and more traditional cytoarchitectonic parcellation methods has been observed. However, the degree of correspondence and relative functional importance of cytoarchitectonic- versus connectivity-derived parcellations still remains unclear. Diffusion tractography remains one of the only methods capable of visualizing the structural networks of the brain in vivo. As such, it is of vital importance to continue to improve the accuracy of the methodology and to extend its potential applications in the study of cognition in neurological health and disease.

The inferior parietal lobule (IPL) is a functionally and anatomically heterogeneous region. Much of the information about the anatomical connectivity and parcellation of this region was obtained from histological studies on non-human primates. However, whether these findings from non-human primates can be applied to the human inferior parietal lobule, especially the left inferior parietal lobule, which shows evidence of considerable evolution from primates to humans, remains unclear. In this study, diffusion MRI was employed to investigate the anatomical connectivities of the human left inferior parietal lobule. Using a new algorithm, spectral clustering with edge-weighted centroidal voronoi tessellations, to search for regional variations in the probabilistic connectivity profiles of all left inferior parietal lobule voxels with all the rest of the brain identified six subregions with distinctive connectivity properties in the left inferior parietal lobule. Consistent with cytoarchitectonic findings, four subregions were found in the left supramarginal gyrus and two subregions in the left angular gyrus. The specific connectivity patterns of each subregion of the left inferior parietal lobule were supported by both the anatomical and functional connectivity properties for each subregion, as calculated by a meta-analysis-based target method and by voxel-based whole brain anatomical and functional connectivity analyses. The proposed parcellation scheme for the human left inferior parietal lobule and the maximum probability map for each subregion may facilitate more detailed future studies of this brain area.

Sophisticated image analysis methods have been developed for the human brain, but such tools still need to be adapted and optimized for quantitative small animal imaging. We propose a framework for quantitative anatomical phenotyping in mouse models of neurological and psychiatric conditions. The framework encompasses an atlas space, image acquisition protocols, and software tools to register images into this space. We show that a suite of segmentation tools (Avants, Epstein et al. 2008) designed for human neuroimaging can be incorporated into a pipeline for segmenting mouse brain images acquired with multispectral magnetic resonance imaging (MR) protocols. We present a flexible approach for segmenting such hyperimages, optimizing registration, and identifying optimal combinations of image channels for particular structures. Brain imaging with T1, T2* and T2 contrast yielded accuracy in the range of 83% for hippocampus and caudate putamen (Hc and CPu), but only 54% in white matter tracts, and 44% for the ventricles. The addition of diffusion tensor parameter images improved accuracy for large gray matter structures (by >5%), white matter (10%), and ventricles (15%). The use of Markov Random Field segmentation further improved overall accuracy in the C57BL/6 strain by 6%; so Dice coefficients for Hc and CPu reached 93%, for white matter 79%, for ventricles 68%, and for substantia nigra 80%. We demonstrate the segmentation pipeline for the widely used C57BL/6 strain, and two test strains (BXD29, APP/TTA). This approach appears promising for characterizing temporal changes in mouse models of human neurological and psychiatric conditions, and may provide anatomical constraints for other preclinical imaging, e.g. fMRI and molecular imaging. This is the first demonstration that multiple MR imaging modalities combined with multivariate segmentation methods lead to significant improvements in anatomical segmentation in the mouse brain.

The claustrum and the insula are closely juxtaposed in the brain of the prosimian primate, the gray mouse lemur (Microcebus murinus). Whether the claustrum has closer affinities with the cortex or the striatum has been debated for many decades. Our observation of histological sections from primate brains and genomic data in the mouse suggest former. Given this, the present study compares the connections of the two structures in Microcebus using high angular resolution diffusion imaging (HARDI, with 72 directions), with a very small voxel size (90 micra), and probabilistic fiber tractography. High angular and spatial resolution diffusion imaging is non-destructive, requires no surgical interventions, and the connection of each and every voxel can be mapped, whereas in conventional tract tracer studies only a few specific injection sites can be assayed. Our data indicate that despite the high genetic and spatial affinities between the two structures, their connectivity patterns are very different. The claustrum connects with many cortical areas and the olfactory bulb; its strongest probabilistic connections are with the entorhinal cortex, suggesting that the claustrum may have a role in spatial memory and navigation. By contrast, the insula connects with many subcortical areas, including the brainstem and thalamic structures involved in taste and visceral feelings. Overall, the connections of the Microcebus claustrum and insula are similar to those of the rodents, cat, macaque, and human, validating our results. The insula in the Microcebus connects with the dorsolateral frontal cortex in contrast to the mouse insula, which has stronger connections with the ventromedial frontal lobe, yet this is consistent with the dorsolateral expansion of the frontal cortex in primates. In addition to revealing the connectivity patterns of the Microcebus brain, our study demonstrates that HARDI, at high resolutions, can be a valuable tool for mapping fiber pathways for multiple sites in fixed brains in rare and difficult-to-obtain species.

BACKGROUND AND PURPOSE:Neurosurgical interventions of the thalamus rely on transferring stereotactic coordinates from an atlas onto the patient's MR brain images. We propose a prototype application for performing thalamus target map individualization by fusing patient-specific thalamus geometric information and diffusion tensor tractography.MATERIALS AND METHODS:Previously, our workgroup developed a thalamus atlas by fusing anatomic information from 7 histologically processed thalami. Thalamocortical connectivity maps were generated from DTI scans of 40 subjects by using a previously described procedure and were mapped to a standard neuroimaging space. These data were merged into a statistical shape model describing the morphologic variability of the thalamic outline, nuclei, and connectivity landmarks. This model was used to deform the atlas to individual images. Postmortem MR imaging scans were used to quantify the accuracy of nuclei predictions.RESULTS:Reliable tractography-based markers were located in the ventral lateral thalamus, with the somatosensory connections coinciding with the VPLa and VPLp nuclei; and motor/premotor connections, with the VLpv and VLa nuclei. Prediction accuracy of thalamus outlines was higher with the SSM approach than the ACPC alignment of data (0.56 mm versus 1.24; Dice overlap: 0.87 versus 0.7); for individual nuclei: 0.65 mm, Dice: 0.63 (SSM); 1.24 mm, Dice: 0.4 (ACPC).CONCLUSIONS:Previous studies have already applied DTI to the thalamus. As a further step in this direction, we demonstrate a hybrid approach by using statistical shape models, which have the potential to cope with intersubject variations in individual thalamus geometry.

The mediodorsal thalamic nucleus is recognized as an association hub mediating interconnections with mainly the prefrontal cortex. Tracer studies in primates and in vivo diffusion tensor tractography findings in both humans and monkeys confirm its role in relaying networks that connect to the dorsolateral prefrontal, orbitofrontal, frontal medial and cingulate cortex. Our study was designed to use in vivo probabilistic tractography to describe the pathways emerging from or projecting to the mediodorsal nucleus; moreover, to use such information to automatically define subdivisions based on the divergence of remote structural connections. Diffusion tensor MR imaging data of 156 subjects were utilized to perform connectivity-based segmentation of the mediodorsal nucleus by employing a k-means clustering algorithm. Two domains were revealed (medial and lateral) that are separated from each other by a sagittally oriented plane. For each subject, general assessment of cognitive performance by means of the Wechsler Abbreviated Scale of Intelligence and measures of Delis-Kaplan Executive Function System (D-KEFS) test was utilized. Inter-subject variability in terms of connectivity-based cluster sizes was discovered and the relative sizes of the lateral mediodorsal domain correlated with the individuals' performance in the D-KEFS Sorting test (r = 0.232, p = 0.004). Our results show that the connectivity-based parcellation technique applied to the mediodorsal thalamic nucleus delivers a single subject level descriptor of connectional topography; furthermore, we revealed a possible weak interaction between executive performance and the size of the thalamic area from which pathways converge to the lateral prefrontal cortex.

Is there a common structural and functional cortical architecture that can be quantitatively encoded and precisely reproduced across individuals and populations? This question is still largely unanswered due to the vast complexity, variability, and nonlinearity of the cerebral cortex. Here, we hypothesize that the common cortical architecture can be effectively represented by group-wise consistent structural fiber connections and take a novel data-driven approach to explore the cortical architecture. We report a dense and consistent map of 358 cortical landmarks, named Dense Individualized and Common Connectivity-based Cortical Landmarks (DICCCOLs). Each DICCCOL is defined by group-wise consistent white-matter fiber connection patterns derived from diffusion tensor imaging (DTI) data. Our results have shown that these 358 landmarks are remarkably reproducible over more than one hundred human brains and possess accurate intrinsically established structural and functional cross-subject correspondences validated by large-scale functional magnetic resonance imaging data. In particular, these 358 cortical landmarks can be accurately and efficiently predicted in a new single brain with DTI data. Thus, this set of 358 DICCCOL landmarks comprehensively encodes the common structural and functional cortical architectures, providing opportunities for many applications in brain science including mapping human brain connectomes, as demonstrated in this work.

Interregional connections of the brain measured with diffusion tractography can be used to infer valuable information regarding both brain structure and function. However, different tractography algorithms can generate networks that exhibit different characteristics, resulting in poor reproducibility across studies. Therefore, it is important to benchmark different tractography algorithms to quantitatively assess their performance. Here we systematically evaluated a newly introduced tracking algorithm, global tractography, to derive anatomical brain networks in a fiber phantom, 2 post-mortem macaque brains, and 20 living humans, and compared the results with an established local tracking algorithm. Our results demonstrated that global tractography accurately characterized the phantom network in terms of graph-theoretic measures, and significantly outperformed the local tracking approach. Results in brain tissues (post-mortem macaques and in vivo humans), however, showed that although the performance of global tractography demonstrated a trend of improvement, the results were not vastly different than that of local tractography, possibly resulting from the increased fiber complexity of real tissues. When using macaque tracer-derived connections as the ground truth, we found that both global and local algorithms generated non-random patterns of false negative and false positive connections that were probably related to specific fiber systems and largely independent of the tractography algorithm or tissue type (post-mortem vs. in vivo) used in the current study. Moreover, a close examination of the transcallosal motor connections, reconstructed via either global or local tractography, demonstrated that the lateral transcallosal fibers in humans and macaques did not exhibit the denser homotopic connections found in primate tracer studies, indicating the need for more robust brain mapping techniques based on diffusion MRI data.

The habenula, located in the posterior thalamus, is implicated in a wide array of functions. Animal anatomical studies have indicated that the structure receives inputs from a number of brain regions (e.g., frontal areas, hypothalamic, basal ganglia) and sends efferent connections predominantly to the brain stem (e.g., periaqueductal gray, raphe, interpeduncular nucleus). The role of the habenula in pain and its anatomical connectivity are well-documented in animals but not in humans. In this study, for the first time, we show how high-field magnetic resonance imaging can be used to detect habenula activation to noxious heat. Functional maps revealed significant, localized, and bilateral habenula responses. During pain processing, functional connectivity analysis demonstrated significant functional correlations between the habenula and the periaqueductal gray and putamen. Probabilistic tractography was used to assess connectivity of afferent (e.g., putamen) and efferent (e.g., periaqueductal gray) pathways previously reported in animals. We believe that this study is the first report of habenula activation by experimental pain in humans. Since the habenula connects forebrain structures with brain stem structures, we suggest that the findings have important implications for understanding sensory and emotional processing in the brain during both acute and chronic pain.