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Tissue-type partial volume modelling is generally an ill-posed problem in single-shell diffusion MRI. On the other hand, T1w images are typically acquired along with the diffusion data, and allow for an accurate estimation of the tissue partial volume fractions (PVFs). We propose in this paper to compare different data driven approach to predict the T1w-derived PVFs from the diffusion data. The aim is to alleviate the within subject mis-registration between the two modalities. Our experiments show that the random forests is the most accurate and scalable method for predicting the tissue partial volume fractions. Additionally, such predictions can be used to inform the fitting of the two-compartment model to retrieve a diffusion tensor that is not biased by partial volume effects or constraints.

Item does not contain fulltext The degree to which genetic factors influence brain connectivity is beginning to be understood. Large-scale efforts are underway to map the profile of genetic effects in various brain regions. The NIH-funded Human Connectome Project (HCP) is providing data valuable for analyzing the degree of genetic influence underlying brain connectivity revealed by state-of-the-art neuroimaging methods. We calculated the heritability of the fractional anisotropy (FA) measure derived from diffusion tensor imaging (DTI) reconstruction in 481 HCP subjects (194/287 M/F) consisting of 57/60 pairs of mono- and dizygotic twins, and 246 siblings. FA measurements were derived using (Enhancing NeuroImaging Genetics through Meta-Analysis) ENIGMA DTI protocols and heritability estimates were calculated using the SOLAR-Eclipse imaging genetic analysis package. We compared heritability estimates derived from HCP data to those publicly available through the ENIGMA-DTI consortium, which were pooled together from five-family based studies across the US, Europe, and Australia. FA measurements from the HCP cohort for eleven major white matter tracts were highly heritable (h(2)=0.53-0.90, p

Background Previously, we showed experimentally that saturation of slow-wave activity provides a potentially individualized neurophysiologic endpoint for perception loss during anesthesia. Furthermore, it is clear that induction and emergence from anesthesia are not symmetrically reversible processes. The observed hysteresis is potentially underpinned by a neural inertia mechanism as proposed in animal studies. Methods In an advanced secondary analysis of 393 individual electroencephalographic data sets, we used slow-wave activity dose-response relationships to parameterize slow-wave activity saturation during induction and emergence from surgical anesthesia. We determined whether neural inertia exists in humans by comparing slow-wave activity dose responses on induction and emergence. Results Slow-wave activity saturation occurs for different anesthetics and when opioids and muscle relaxants are used during surgery. There was wide interpatient variability in the hypnotic concentrations required to achieve slow-wave activity saturation. Age negatively correlated with power at slow-wave activity saturation. On emergence, we observed abrupt decreases in slow-wave activity dose responses coincident with recovery of behavioral responsiveness in ~33% individuals. These patients are more likely to have lower power at slow-wave activity saturation, be older, and suffer from short-term confusion on emergence. Conclusions Slow-wave activity saturation during surgical anesthesia implies that large variability in dosing is required to achieve a targeted potential loss of perception in individual patients. A signature for neural inertia in humans is the maintenance of slow-wave activity even in the presence of very-low hypnotic concentrations during emergence from anesthesia.

Over long timescales, neuronal dynamics can be robust to quite large perturbations, such as changes in white matter connectivity and grey matter structure through processes including learning, aging, development and certain disease processes. One possible explanation is that robust dynamics are facilitated by homeostatic mechanisms that can dynamically rebalance brain networks. In this study, we simulate a cortical brain network using the Wilson-Cowan neural mass model with conduction delays and noise, and use inhibitory synaptic plasticity (ISP) to dynamically achieve a spatially local balance between excitation and inhibition. Using MEG data from 55 subjects we find that ISP enables us to simultaneously achieve high correlation with multiple measures of functional connectivity, including amplitude envelope correlation and phase locking. Further, we find that ISP successfully achieves local E/I balance, and can consistently predict the functional connectivity computed from real MEG data, for a much wider range of model parameters than is possible with a model without ISP., Author summary Recently there has been much interest in investigating the role of synaptic plasticity in supporting healthy brain activity. In particular, the balance between excitation and inhibition in the brain is believed to play a critical role in brain dynamics, and it is likely that this balance is regulated by homeostatic mechanisms. Biophysical models of the brain have previously been used to predict functional connectivity, but are typically extremely sensitive to changes in parameter values and require extremely fine tuning to achieve realistic dynamics. In this study, we investigated whether including a homeostatic plasticity mechanism would improve the robustness of simulated neural dynamics. We focused on functional connectivity in MEG data, which can resolve fast oscillations in neural activity, unlike fMRI. We found that including a simple plasticity rule to balance excitation and inhibition resulted in more realistic model predictions, and reduced sensitivity to changes in model parameters.

Objectives: The goal of this study was to better understand the changes in tissue microstructure that underlie white matter diffusion changes in ALS patients. Methods: Diffusion tensor imaging was carried out in postmortem brains of 4 ALS patients and two subjects without neurological disease on a 7T MRI scanner using steady-state free precession sequences. Fractional anisotropy (FA) was measured in the genu, body, and splenium of the corpus callosum in formalin-fixed hemispheres. FA of the body and genu was expressed as ratio to FA of the splenium, a region unaffected in ALS. After imaging, tissue sections of the same segments of the callosum were stained for markers of different tissue components. Coded image fields were rated for pathological changes by blinded raters. Results: The FA body/FA splenium ratio was reduced in ALS patients compared to controls. Patchy areas of myelin pallor and cells immunostained for CD68, a microglial-macrophage marker, were only observed in the body of the callosum of ALS patients. Blinded ratings showed increased CD68+ microglial cells in the body of the corpus callosum in ALS patients, especially those with C9orf72 mutations, and increased reactive astrocytes throughout the callosum. Conclusion: Reduced FA of the corpus callosum in ALS results from complex changes in tissue microstructure. Callosal segments with reduced FA had large numbers of microglia-macrophages in addition to loss of myelinated axons and astrogliosis. Microglial inflammation contributed to reduced FA in ALS, and may contribute to a pro-inflammatory state, but further work is needed to determine their role. Keywords: 7T MRI, Amyotrophic lateral sclerosis, Microglia, Motor neuron disease, Pathology, Steady-state free precession

UK Biobank is a large-scale prospective epidemiological study with all data accessible to researchers worldwide. It is currently in the process of bringing back 100,000 of the original participants for brain, heart and body MRI, carotid ultrasound and low-dose bone/fat x-ray. The brain imaging component covers 6 modalities (T1, T2 FLAIR, susceptibility weighted MRI, Resting fMRI, Task fMRI and Diffusion MRI). Raw and processed data from the first 10,000 imaged subjects has recently been released for general research access. To help convert this data into useful summary information we have developed an automated processing and QC (Quality Control) pipeline that is available for use by other researchers. In this paper we describe the pipeline in detail, following a brief overview of UK Biobank brain imaging and the acquisition protocol. We also describe several quantitative investigations carried out as part of the development of both the imaging protocol and the processing pipeline.

Experience-dependent reorganisation of functional maps in the cerebral cortex is well described in the primary sensory cortices. However, there is relatively little evidence for such cortical reorganisation over the short-term. Using human somatosensory cortex as a model, we investigated the effects of a 24 hr gluing manipulation in which the right index and right middle fingers (digits 2 and 3) were adjoined with surgical glue. Somatotopic representations, assessed with two 7 tesla fMRI protocols, revealed rapid off-target reorganisation in the non-manipulated fingers following gluing, with the representation of the ring finger (digit 4) shifted towards the little finger (digit 5) and away from the middle finger (digit 3). These shifts were also evident in two behavioural tasks conducted in an independent cohort, showing reduced sensitivity for discriminating the temporal order of stimuli to the ring and little fingers, and increased substitution errors across this pair on a speeded reaction time task. DOI: http://dx.doi.org/10.7554/eLife.17280.001, eLife digest The areas of the brain that receive inputs from our senses have a map-like structure. In an area called the visual cortex this map represents our field of vision; in the auditory cortex, it represents the range of different tones we can hear. The sense of touch is processed in the somatosensory cortex: an area of the brain that is organised around a map of the body, with adjacent regions of the cortex representing adjacent regions of the body. The clear structure of these brain regions makes them ideal for exploring how the organisation of the brain changes over time. How quickly can changes to the touch inputs that the brain receives cause the map in the somatosensory cortex to reorganise? Can these effects be produced in just 24 hours? And would this remapping affect how we perceive touch? To investigate these questions, Kolasinski et al. glued together the right index and right middle fingers of healthy human volunteers. This separated the middle and ring fingers: a pair that usually move together due to the anatomical structure of the hand. Functional magnetic resonance imaging of the brain’s activity revealed that within 24 hours of the gluing, the brain’s representation of the ring finger moved away from that of the middle finger, and towards the representation of the little finger. A perceptual judgment task mirrored this finding: after 24 hours of gluing, the participants became better at distinguishing between the middle and ring fingers and worse at distinguishing between the ring and little fingers. This is a powerful demonstration of the human brain’s potential to adapt and reorganise rapidly to changes to sensory inputs. The sense of touch declines gradually with age and may also be reduced as a result of disease such as stroke. A long-term challenge is to understand how the sensory regions of the brain change during this loss of sensation. Further research could then investigate how to maintain the structure of the cortical map to prolong or restore high quality touch sensation. DOI: http://dx.doi.org/10.7554/eLife.17280.002

Microscopic features (i.e., microstructure) of axons affect neural circuit activity through characteristics such as conduction speed. Deeper understanding of structure-function relationships and translating this into human neuroscience has been limited by the paucity of studies relating axonal microstructure in white matter pathways to functional connectivity (synchrony) between macroscopic brain regions. Using magnetic resonance imaging data in 11354 subjects, we constructed multi-variate models that predict the functional connectivity of pairs of brain regions from the microstructural signature of white matter pathways that connect them. Microstructure-derived models provide predictions of functional connectivity that were significant in up to 86% of the brain region pairs considered. These relationships are specific to the relevant white matter pathway and have high reproducibility. The microstructure-function relationships are associated to genetic variants (single-nucleotide polymorphisms), co-located with genes DAAM1 and LPAR1, that have previously been reported to play a role in neural development. Our results demonstrate that variation in white matter microstructure across individuals consistently and specifically predicts functional connectivity, and that this relationship is underpinned by genetic variability.

Decoding neural algorithms is one of the major goals of neuroscience. It is generally accepted that brain computations rely on the orchestration of neural activity at local scales, as well as across the brain through long-range connections. Understanding the relationship between brain activity and connectivity is therefore a prerequisite to cracking the neural code. In the past few decades, tremendous technological advances have been achieved in connectivity measurement techniques. We now possess a battery of tools to measure brain activity and connections at all available scales. A great source of excitement are the new in vivo tools that allow us to measure structural and functional connections noninvasively. Here, we discuss how these new technologies may contribute to deciphering the neural code. © 2013 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals, Inc. on behalf of New York Academy of Sciences.

Previous imaging studies that investigated morphometric group differences of subcortical regions outside the substantia nigra between non-demented Parkinson's patients and controls either did not find any significant differences, or reported contradictory results. Here, we performed a comprehensive morphometric analysis of 20 cognitively normal, early-stage PD patients and 19 matched control subjects. In addition to relatively standard analyses of whole-brain grey matter volume and overall regional volumes, we examined subtle localized surface shape differences in striatal and limbic grey matter structures and tested their utility as a diagnostic marker. Voxel-based morphometry and volumetric comparisons did not reveal significant group differences. Shape analysis, on the other hand, demonstrated significant between-group shape differences for the right pallidum. Careful diffusion tractography analysis showed that the affected parts of the pallidum are connected subcortically with the subthalamic nucleus, the pedunculopontine nucleus, and the thalamus and cortically with the frontal lobe. Additionally, microstructural measurements along these pathways, but not along other pallidal connections, were significantly different between the two groups. Vertex-wise linear discriminant analysis, however, revealed limited accuracy of pallidal shape for the discrimination between patients and controls. We conclude that localized disease-related changes in the right pallidum in early Parkinson's disease, undetectable using standard voxel-based morphometry or volumetry, are evident using sensitive shape analysis. However, the subtle nature of these changes makes it unlikely that shape analysis alone will be useful for early diagnosis.

At macroscopic scales, the human connectome is composed of anatomically distinct brain areas, the structural pathways connecting them, and their functional interactions. Successful annotation of phenotypic associations with variation in the connectome and cataloguing of neurophenotypes promise to transform our understanding of the human brain. This review provides a survey of magnetic resonance imaging-based measurements of functional and structural connectivity. We highlight emerging areas of development and inquiry, and emphasize the importance of integrating structural and functional perspectives on brain architecture.

Purpose: To examine the effects of the reconstruction algorithm of magnitude images from multi-channel diffusion MRI on fibre orientation estimation. Theory and Methods: It is well established that the method used to combine signals from different coil elements in multi-channel MRI can have an impact on the properties of the reconstructed magnitude image. Utilising a root-sum-of-squares (RSoS) approach results in a magnitude signal that follows an effective non-central-distribution. As a result, the noise floor, the minimum measurable in the absence of any true signal, is elevated. This is particularly relevant for diffusion-weighted MRI, where the signal attenuation is of interest. Results: In this study, we illustrate problems that such image reconstruction characteristics may cause in the estimation of fibre orientations, both for model-based and model-free approaches, when modern 32-channel coils are employed. We further propose an alternative image reconstruction method that is based on sensitivity encoding (SENSE) and preserves the Rician nature of the single-channel, magnitude MR signal. We show that for the same k-space data, RSoS can cause excessive overfitting and reduced precision in orientation estimation compared to the SENSE-based approach. Conclusion: These results highlight the importance of choosing the appropriate image reconstruction method for tractography studies that use multi-channel receiver coils for diffusion MRI acquisition.

Objectives The goal of this study was to better understand the changes in tissue microstructure that underlie white matter diffusion changes in ALS patients. Methods Diffusion tensor imaging was carried out in postmortem brains of 4 ALS patients and two subjects without neurological disease on a 7 T MRI scanner using steady-state free precession sequences. Fractional anisotropy (FA) was measured in the genu, body, and splenium of the corpus callosum in formalin-fixed hemispheres. FA of the body and genu was expressed as ratio to FA of the splenium, a region unaffected in ALS. After imaging, tissue sections of the same segments of the callosum were stained for markers of different tissue components. Coded image fields were rated for pathological changes by blinded raters. Results The FA body/FA splenium ratio was reduced in ALS patients compared to controls. Patchy areas of myelin pallor and cells immunostained for CD68, a microglial-macrophage marker, were only observed in the body of the callosum of ALS patients. Blinded ratings showed increased CD68 + microglial cells in the body of the corpus callosum in ALS patients, especially those with C9orf72 mutations, and increased reactive astrocytes throughout the callosum. Conclusion Reduced FA of the corpus callosum in ALS results from complex changes in tissue microstructure. Callosal segments with reduced FA had large numbers of microglia-macrophages in addition to loss of myelinated axons and astrogliosis. Microglial inflammation contributed to reduced FA in ALS, and may contribute to a pro-inflammatory state, but further work is needed to determine their role., Highlights • Diffusion-weighted SSFP and histology were carried out on 4 ALS and 2 control brains. • The FA of the splenium, an unaffected region, was a control for differences in PMI. • The FA body/FA splenium was reduced in ALS compared to controls. • The body of the callosum had increased CD68 + activated microglia and astrogliosis.

Background:Several studies have demonstrated benefits of rehabilitation in multiple sclerosis (MS). However, the neuroscientific foundations for rehabilitation in MS are poorly established. Objectives:As rehabilitation and motor learning share similar mechanisms of brain plasticity, we test whether the dynamics of skill learning are preserved in MS patients relative to controls. Methods:MS patients and controls learned a repeating sequence of hand movements and were assessed for short-term learning. Long-term learning was tested in another cohort of patients and controls practising the same sequence daily for two weeks. Results:Despite differences in baseline performance, the dynamics and extent of improvements were comparable between MS and control groups for both the short- and long-term learning. Even the most severely damaged patients were capable of performance improvements of similar magnitude to that seen in controls. After one week of training patients performed as well as the controls at baseline. Conclusions:Mechanisms for short- and long-term plasticity may compensate for impaired functional connectivity in MS to mediate behavioural improvements. Future studies are needed to define the neurobiological substrates of this plasticity and the extent to which mechanisms of plasticity in patients may be distinct from those used for motor learning in controls.

Recently, the assumption of evolutionary continuity between humans and non-human primates has been used to bolster the hypothesis that human language is mediated espe-cially by the ventral extreme capsule pathway that mediates auditory object recognition in macaques. Here, we argue for the importance of evolutionary divergence in understand-ing brain language evolution. We present new comparative data reinforcing our previous conclusion that the dorsal arcuate fasciculus pathway was more significantly modified than the ventral extreme capsule pathway in human evolution.Twenty-six adult human and twenty-six adult chimpanzees were imaged with diffusion-weighted MRI and probabilistic tractography was used to track and compare the dorsal and ventral language pathways. Based on these and other data, we argue that the arcuate fasciculus is likely to be the pathway most essential for higher-order aspects of human language such as syntax and lexical-semantics.

In this chapter we describe the underlying principles and most common techniques in diffusion tractography. We cover deterministic streamline tractography and several different probabilistic approaches. We aim to provide a conceptual understanding of the different approaches, but where necessary we introduce mathematical concepts for the more advanced reader. We further address issues of interpretation of tractography results, and of designing a tractography study. We hope the chapter covers the major themes and issues in current tractography research and will provide a reference for both users of diffusion tractography and for those researching new methodological techniques. We end with a discussion of the areas that we believe will make the most fruitful advances in tractography research in the coming years. © 2014 Elsevier Inc. All rights reserved.

Even if a number of methods have been proposed for resolving crossing fibres from diffusion-weighted (DW) MRI, other complex fibre geometries have drawn minimal attention. In this study, we focus on fibre orientation dispersion induced by within-voxel fanning. We use a multi-compartment, model-based approach to estimate fibre dispersion. A Bingham distribution is employed to represent a continuum of fibre orientations, centred around a main orientation. We evaluate the accuracy of the model for different simulated fanning geometries, under different acquisition protocols and we illustrate the high SNR and angular resolution needs. We apply the proposed model on high-quality, postmortem macaque data and present whole-brain maps of fibre dispersion. © 2012 IEEE.

Orthonormal function expansions have been used extensively in the context of linear and nonlinear systems identification, since they result in a significant reduction in the number of required free parameters. In particular, Laguerre basis expansions of Volterra kernels have been used successfully for physiological systems identification, due to the exponential decaying characteristics of the Laguerre orthonormal basis and the inherent nonlinearities that characterize such systems. A critical aspect of the Laguerre expansion technique is the selection of the model structural parameters, i.e., polynomial model order, number of Laguerre functions in the expansion and value of the Laguerre parameter α, which determines the rate of exponential decay. This selection is typically made by trial-and-error procedures on the basis of the model prediction error. In the present paper, we formulate the Laguerre expansion technique in a Bayesian framework and derive analytically the posterior distribution of the a parameter, as well as the model evidence, in order to infer on the expansion structural parameters. We also demonstrate the performance of the proposed method by simulated examples and compare it to alternative statistical criteria for model order selection. © 2008 IEEE.

In this article, we highlight an issue that arises when using multiple b-values in a model-based analysis of diffusion MR data for tractography. The non-monoexponential decay, commonly observed in experimental data, is shown to induce overfitting in the distribution of fiber orientations when not considered in the model. Extra fiber orientations perpendicular to the main orientation arise to compensate for the slower apparent signal decay at higher b-values. We propose a simple extension to the ball and stick model based on a continuous gamma distribution of diffusivities, which significantly improves the fitting and reduces the overfitting. Using in vivo experimental data, we show that this model outperforms a simpler, noise floor model, especially at the interfaces between brain tissues, suggesting that partial volume effects are a major cause of the observed non-monoexponential decay. This model may be helpful for future data acquisition strategies that may attempt to combine multiple shells to improve estimates of fiber orientations in white matter and near the cortex. Copyright © 2012 Wiley Periodicals, Inc.

Short-term (STM) and long-term memory (LTM) have largely been considered as separate brain systems reflecting fronto-parietal and medial temporal lobe (MTL) functions, respectively. This functional dichotomy has been called into question by evidence of deficits on aspects of working memory in patients with MTL damage, suggesting a potentially direct hippocampal contribution to STM. As the hippocampus has direct anatomical connections with the thalamus, we tested the hypothesis that damage to thalamic nuclei regulating cortico-cortical interactions may contribute to STM deficits in patients with hippocampal dysfunction. We used diffusion-weighted magnetic resonance imaging-based tractography to identify anatomical subdivisions in patients with MTL epilepsy. From these, we measured resting-state functional connectivity with detailed cortical divisions of the frontal, temporal, and parietal lobes. Whereas thalamo-temporal functional connectivity reflected LTM performance, thalamo-prefrontal functional connectivity specifically predicted STM performance. Notably, patients with hippocampal volume loss showed thalamic volume loss, most prominent in the pulvinar region, not detected in patients with normal hippocampal volumes. Aberrant thalamo-cortical connectivity in the epileptic hemisphere was mirrored in a loss of behavioral association with STM performance specifically in patients with hippocampal atrophy. These findings identify thalamo-cortical disruption as a potential mechanism contributing to STM deficits in the context of MTL damage.

In functional magnetic resonance imaging (fMRI), cerebral activity has been increasingly considered as the consequence of a network activation. Selecting the brain regions relevant for the network has thus become a key issue. We propose to define the so-called large-scale functional network involved in a particular task as a set of regions exhibiting strong intrinsic homogeneity, as well as at least one strong long-distance inter-regional interaction. We develop a method to identify such a network, and we validate it on a real dataset, in a context where the existence of a distributed network has already been demonstrated. Our results are compatible with previous studies. This new tool is thus promising for selecting regions when analyzing functional connectivity in fMRI. © 2004 IEEE.

Background. Failure of adaptive plasticity with increasing pathology is suggested to contribute to progression of disability in multiple sclerosis (MS). However, functional impairments can be reduced with practice, suggesting that brain plasticity is preserved even in patients with substantial damage. Objective. Here, functional magnetic resonance imaging (fMRI) was used to probe systems-level mechanisms of brain plasticity associated with improvements in visuomotor performance in MS patients and related to measures of microstructural damage. Methods. 23 MS patients and 12 healthy controls underwent brain fMRI during the first practice session of a visuomotor task (short-term practice) and after 2 weeks of daily practice with the same task (longer-term practice). Participants also underwent a structural brain MRI scan. Results. Patients performed more poorly than controls at baseline. Nonetheless, with practice, patients showed performance improvements similar to controls and independent of the extent of MRI measures of brain pathology. Different relationships between performance improvements and activations were found between groups: greater short-term improvements were associated with lower activation in the sensorimotor, posterior cingulate, and parahippocampal cortices for patients, whereas greater long-term improvements correlated with smaller activation reductions in the visual cortex of controls. Conclusions. Brain plasticity for visuomotor practice is preserved in MS patients despite a high burden of cerebral pathology. Cognitive systems different from those acting in controls contribute to this plasticity in patients. These findings challenge the notion that increasing pathology is accompanied by an outright failure of adaptive plasticity, supporting a neuroscientific rationale for recovery-oriented strategies even in chronically disabled patients.

The human dorsal frontal cortex has been associated with the most sophisticated aspects of cognition, including those that are thought to be especially refined in humans. Here we used diffusion-weighted magnetic resonance imaging (DW-MRI) and functional MRI (fMRI) in humans and macaques to infer and compare the organization of dorsal frontal cortex in the two species. Using DW-MRI tractography-based parcellation, we identified 10 dorsal frontal regions lying between the human inferior frontal sulcus and cingulate cortex. Patterns of functional coupling between each area and the rest of the brain were then estimated with fMRI and compared with functional coupling patterns in macaques. Areas in human medial frontal cortex, including areas associated with high-level social cognitive processes such as theory of mind, showed a surprising degree of similarity in their functional coupling patterns with the frontal pole, medial prefrontal, and dorsal prefrontal convexity in the macaque. We failed to find evidence for “new” regions in human medial frontal cortex. On the lateral surface, comparison of functional coupling patterns suggested correspondences in anatomical organization distinct from those that are widely assumed. A human region sometimes referred to as lateral frontal pole more closely resembled area 46, rather than the frontal pole, of the macaque. Overall the pattern of results suggest important similarities in frontal cortex organization in humans and other primates, even in the case of regions thought to carry out uniquely human functions. The patterns of interspecies correspondences are not, however, always those that are widely assumed.

Tractography based on diffusion MRI offers the promise of characterizing many aspects of long-distance connectivity in the brain, but requires quantitative validation to assess its strengths and limitations. Here, we evaluate tractography's ability to estimate the presence and strength of connections between areas of macaque neocortex by comparing its results with published data from retrograde tracer injections. Probabilistic tractography was performed on high-quality postmortem diffusion imaging scans from two Old World monkey brains. Tractography connection weights were estimated using a fractional scaling method based on normalized streamline density. We found a correlation between log-transformed tractography and tracer connection weights of r = 0.59, twice that reported in a recent study on the macaque. Using a novel method to estimate interareal connection lengths from tractography streamlines, we regressed out the distance dependence of connection strength and found that the correlation between tractography and tracers remains positive, albeit substantially reduced. Altogether, these observations provide a valuable, data-driven perspective on both the strengths and limitations of tractography for analyzing interareal corticocortical connectivity in nonhuman primates and a framework for assessing future tractography methodological refinements objectively.Tractography based on diffusion MRI has great potential for a variety of applications, including estimation of comprehensive maps of neural connections in the brain ("connectomes"). Here, we describe methods to assess quantitatively tractography's performance in detecting interareal cortical connections and estimating connection strength by comparing it against published results using neuroanatomical tracers. We found the correlation of tractography's estimated connection strengths versus tracer to be twice that of a previous study. Using a novel method for calculating interareal cortical distances, we show that tractography-based estimates of connection strength have useful predictive power beyond just interareal separation. By freely sharing these methods and datasets, we provide a valuable resource for future studies in cortical connectomics.

The hand area of the primary somatosensory cortex contains detailed finger topography, thought to be shaped and maintained by daily life experience. Here we utilise phantom sensations and ultra high-field neuroimaging to uncover preserved, though latent, representation of amputees’ missing hand. We show that representation of the missing hand’s individual fingers persists in the primary somatosensory cortex even decades after arm amputation. By demonstrating stable topography despite amputation, our finding questions the extent to which continued sensory input is necessary to maintain organisation in sensory cortex, thereby reopening the question what happens to a cortical territory once its main input is lost. The discovery of persistent digit topography of amputees’ missing hand could be exploited for the development of intuitive and fine-grained control of neuroprosthetics, requiring neural signals of individual digits. DOI: http://dx.doi.org/10.7554/eLife.15292.001, eLife digest The brain has a remarkable ability to adapt to changes in circumstances. But what happens to the brain when it loses a key source of input, for example, following the amputation of a limb? A region of the brain known as primary somatosensory cortex processes sensory inputs from all over the body. The more sensitive an area of the body is, the more fine-grained its representation is in the cortex. For example, the hand is represented with a highly detailed map, with each finger represented seperately. The brain is thought to require ongoing sensory signals from the body to maintain these detailed representations in the cortex. Indeed, textbooks typically state that the brain will ‘overwrite’ its representation of a body part if input from that area no longer arrives. According to this view, people who have lost a hand should show little or no activity in the area of primary somatosensory cortex that used to represent it. However, many people who have had a limb amputated continue to experience vivid sensations of the missing limb long after its loss. When asked to move their so-called ‘phantom’ limb, these individuals report being able to feel the movement. Kikkert, Kolasinski et al. now show, using advanced imaging techniques, that the brains of individuals with phantom hands continue to represent the missing hand several decades after its loss. Indeed, asking the subjects to move individual fingers of their phantom hand activates fine-grained representations of those fingers, similar to those seen in two-handed controls. By showing that the brain ‘remembers’ an amputated hand, Kikkert, Kolasinski et al. demonstrate that ongoing sensory input is not required to maintain representations of the body in somatosensory cortex. This, in turn, offers new hope for developing prosthetic limbs that are under direct brain control. If the brain continues to represent individual fingers many years after their loss, it should be possible to exploit those pathways to achieve intuitive fine-grained control of artificial fingers. DOI: http://dx.doi.org/10.7554/eLife.15292.002

In this review we consider how Bayesian logic can help neuroscientists to understand behaviour and brain function. Firstly, we review some key characteristics of Bayesian systems - they integrate information making rational use of uncertainty, they apply prior knowledge in the interpretation of new observations, and (for several reasons) they are very effective learners. Secondly, we illustrate how some well-known psychological phenomena including visual illusions, categorical perception and attention can be understood in terms of Bayesian inference. We also consider how formal models can clarify our understanding of psychological constructs, by giving a truly computational definition of psychological processes. Finally, we consider how probabilistic representations and hence Bayesian algorithms could be implemented by neural populations. In particular, we explore how different types of population coding may lead to different predictions about activity in both single-unit and imaging studies, and draw a distinction in this context between the representation of parameters and implementation of computations.

Contains fulltext : 160510.pdf (Publisher’s version ) (Open Access) We compared the course and cortical projections of white matter fibers passing through the extreme capsule in humans and macaques. Previous comparisons of this tract have suggested a uniquely human posterior projection, but these studies have always employed different techniques in the different species. Here we used the same technique, diffusion MRI, in both species to avoid attributing differences in techniques to differences in species. Diffusion MRI-based probabilistic tractography was performed from a seed area in the extreme capsule in both human and macaques. We compared in vivo data of humans and macaques as well as one high-resolution ex vivo macaque dataset. Tractography in the macaque was able to replicate most results known from macaque tracer studies, including selective innervation of frontal cortical areas and targets in the superior temporal cortex. In addition, however, we also observed some tracts that are not commonly reported in macaque tracer studies and that are more reminiscent of results previously only reported in the human. In humans, we show that the ventrolateral prefrontal cortex innervations are broadly similar to those in the macaque. These results suggest that evolutionary changes in the human extreme capsule fiber complex are likely more gradual than punctuated. Further, they demonstrate both the potential and limitations of diffusion MRI tractography. 13 p.

Background. Motor practice is an important component of neurorehabilitation. Imaging studies in healthy individuals show that dynamic brain activation changes with practice. Defining patterns of functional brain plasticity associated with motor practice following stroke could guide rehabilitation. Objective. The authors aimed to test whether practice-related changes in brain activity differ after stroke and to explore spatial relationships between activity changes and patterns of structural degeneration. Methods. They studied 10 patients at least 6 months after left-hemisphere subcortical strokes and 18 healthy controls. Diffusion-weighted magnetic resonance imaging (MRI) was acquired at baseline, and functional MRI (fMRI) was acquired during performance of a visuomotor tracking task before and after a 15-day period of practice of the same task. Results. Smaller short-term practice effects at baseline correlated with lower fractional anisotropy in the posterior limbs of the internal capsule (PLIC) bilaterally in patients ( t > 3; cluster P < .05). After 15 days of motor practice a Group × Time interaction ( z > 2.3; cluster P < .05) was found in the basal ganglia, thalamus, inferior frontal gyrus, superior temporal gyrus, and insula. In these regions, healthy controls showed decreases and patients showed increases in activity with practice. Some regions of interest had a loss of white matter connectivity at baseline. Conclusions. Performance gains with motor practice can be associated with increased activity in regions that have been either directly or indirectly impaired by loss of connectivity. These results suggest that neurorehabilitation interventions may be associated with compensatory adaptation of intact brain regions as well as enhanced activity in regions with impaired structural connectivity.

OBJECTIVE: The Stockholm Neonatal Project involves a prospective, cross-sectional, population-based, cohort monitored for 12 to 17 years after birth; it was started with the aim of investigating the long-term structural correlates of preterm birth and comparing findings with reports on similar cohorts. METHODS: High-resolution anatomic and diffusion tensor imaging data measuring diffusion in 30 directions were collected by using a 1.5-T MRI scanner. A total of 143 adolescents (12.18–17.7 years of age) participated in the study, including 74 formerly preterm infants with birth weights of ≤1500 g (range: 645–1486 g) and 69 term control subjects. The 2 groups were well matched with respect to demographic and socioeconomic data. The anatomic MRI data were used for calculation of total brain volumes and voxelwise comparison of gray matter (GM) volumes. The diffusion tensor imaging data were used for voxelwise comparison of white matter (WM) microstructural integrity. RESULTS: The formerly preterm individuals possessed 8.8% smaller GM volume and 9.4% smaller WM volume. The GM and WM volumes of individuals depended on gestational age and birth weight. The reduction in GM could be attributed bilaterally to the temporal lobes, central, prefrontal, orbitofrontal, and parietal cortices, caudate nuclei, hippocampi, and thalami. Lower fractional anisotropy was observed in the posterior corpus callosum, fornix, and external capsules. CONCLUSIONS: Although preterm birth was found to be a risk factor regarding long-term structural brain development, the outcome was milder than in previous reports. This may be attributable to differences in social structure and neonatal care practices.

In this work, we propose a symmetrical multimodal EEG/fMRI information fusion approach dedicated to the identification of event-related bioelectric and hemodynamic responses. Unlike existing, asymmetrical EEG/fMRI data fusion algorithms, we build a joint EEG/fMRI generative model that explicitly accounts for local coupling/uncoupling of bioelectric and hemodynamic activities, which are supposed to share a common substrate. Under a dedicated assumption of spatio-temporal separability, the spatial profile of the common EEG/fMRI sources is introduced as an unknown hierarchical prior on both markers of cerebral activity. Thereby, a devoted Variational Bayesian (VB) learning scheme is derived to infer common EEG/fMRI sources from a joint EEG/fMRI dataset. This yields an estimate of the common spatial profile, which is built as a trade-off between information extracted from EEG and fMRI datasets. Furthermore, the spatial structure of the EEG/fMRI coupling/uncoupling is learned exclusively from the data. The proposed data generative model and devoted VBEM learning scheme thus provide an un-supervised well-balanced approach for the fusion of EEG/fMRI information. We first demonstrate our approach on synthetic data. Results show that, in contrast to classical EEG/fMRI fusion approach, the method proved efficient and robust regardless of the EEG/fMRI discordance level. We apply the method on EEG/fMRI recordings from a patient with epilepsy, in order to identify brain areas involved during the generation of epileptic spikes. The results are validated using intracranial EEG measurements.

Background Deep brain stimulation (DBS) of the anterior cingulate cortex (ACC) is a new treatment for alleviating intractable neuropathic pain. However, it fails to help some patients. The large size of the ACC and the intersubject variability make it difficult to determine the optimal site to position DBS electrodes. The aim of this work was therefore to compare the ACC connectivity of patients with successful versus unsuccessful DBS outcomes to help guide future electrode placement. Methods Diffusion magnetic resonance imaging (dMRI) and probabilistic tractography were performed preoperatively in 8 chronic pain patients (age 53.4 ± 6.1 years, 2 females) with ACC DBS, of whom 6 had successful (SO) and 2 unsuccessful outcomes (UOs) during a period of trialing. Results The number of patients was too small to demonstrate any statistically significant differences. Nevertheless, we observed differences between patients with successful and unsuccessful outcomes in the fiber tract projections emanating from the volume of activated tissue around the electrodes. A strong connectivity to the precuneus area seems to predict unsuccessful outcomes in our patients (UO: 160n/SO: 27n), with ( n ), the number of streamlines per nonzero voxel. On the other hand, connectivity to the thalamus and brainstem through the medial forebrain bundle (MFB) was only observed in SO patients. Conclusions These findings could help improve presurgical planning by optimizing electrode placement, to selectively target the tracts that help to relieve patients' pain and to avoid those leading to unwanted effects.

Decades of detailed anatomical tracer studies in non-human animals point to a rich and complex organization of long-range white matter connections in the brain. State-of-the art in vivo imaging techniques are striving to achieve a similar level of detail in humans, but multiple technical factors can limit their sensitivity and fidelity. In this review, we mostly focus on magnetic resonance imaging of the brain. We highlight some of the key challenges in analyzing and interpreting in vivo connectomics data, particularly in relation to what is known from classical neuroanatomy in laboratory animals. We further illustrate that, despite the challenges, in vivo imaging methods can be very powerful and provide information on connections that is not available by any other means.

Item does not contain fulltext Imaging of the cerebellar cortex, deep cerebellar nuclei and their connectivity are gaining attraction, due to the important role the cerebellum plays in cognition and motor control. Atlases of the cerebellar cortex and nuclei are used to locate regions of interest in clinical and neuroscience studies. However, the white matter that connects these relay stations is of at least similar functional importance. Damage to these cerebellar white matter tracts may lead to serious language, cognitive and emotional disturbances, although the pathophysiological mechanism behind it is still debated. Differences in white matter integrity between patients and controls might shed light on structure-function correlations. A probabilistic parcellation atlas of the cerebellar white matter would help these studies by facilitating automatic segmentation of the cerebellar peduncles, the localization of lesions and the comparison of white matter integrity between patients and controls. In this work a digital three-dimensional probabilistic atlas of the cerebellar white matter is presented, based on high quality 3T, 1.25mm resolution diffusion MRI data from 90 subjects participating in the Human Connectome Project. The white matter tracts were estimated using probabilistic tractography. Results over 90 subjects were symmetrical and trajectories of superior, middle and inferior cerebellar peduncles resembled the anatomy as known from anatomical studies. This atlas will contribute to a better understanding of cerebellar white matter architecture. It may eventually aid in defining structure-function correlations in patients with cerebellar disorders.

Diffusion-weighted imaging (DWI) tractography is a technique with great potential to characterize the in vivo anatomical position and integrity of white matter tracts. Tractography, however, remains an estimation of white matter tracts, and false-positive and false-negative rates are not available. The goal of the present study was to compare postmortem tractography of the dentatorubrothalamic tract (DRTT) by its 3D histological reconstruction, to estimate the reliability of the tractography algorithm in this specific tract. Recent studies have shown that the cerebellum is involved in cognitive, language and emotional functions besides its role in motor control. However, the exact working mechanism of the cerebellum is still to be elucidated. As the DRTT is the main output tract it is of special interest for the neuroscience and clinical community. A postmortem human brain specimen was scanned on a 7T MRI scanner using a diffusion-weighted steady-state free precession sequence. Tractography was performed with PROBTRACKX. The specimen was subsequently serially sectioned and stained for myelin using a modified Heidenhain–Woelke staining. Image registration permitted the 3D reconstruction of the histological sections and comparison with MRI. The spatial concordance between the two modalities was evaluated using ROC analysis and a similarity index (SI). ROC curves showed a high sensitivity and specificity in general. Highest measures were observed in the superior cerebellar peduncle with an SI of 0.72. Less overlap was found in the decussation of the DRTT at the level of the mesencephalon. The study demonstrates high spatial accuracy of postmortem probabilistic tractography of the DRTT when compared to a 3D histological reconstruction. This gives hopeful prospect for studying structure–function correlations in patients with cerebellar disorders using tractography of the DRTT. Electronic supplementary material The online version of this article (doi:10.1007/s00429-015-1115-7) contains supplementary material, which is available to authorized users.

The brains of odontocetes (toothed whales) look grossly different from their terrestrial relatives. Because of their adaptation to the aquatic environment and their reliance on echolocation, the odontocetes' auditory system is both unique and crucial to their survival. Yet, scant data exist about the functional organization of the cetacean auditory system. A predominant hypothesis is that the primary auditory cortex lies in the suprasylvian gyrus along the vertex of the hemispheres, with this position induced by expansion of ‘associative′ regions in lateral and caudal directions. However, the precise location of the auditory cortex and its connections are still unknown. Here, we used a novel diffusion tensor imaging (DTI) sequence in archival post-mortem brains of a common dolphin ( Delphinus delphis ) and a pantropical dolphin ( Stenella attenuata ) to map their sensory and motor systems. Using thalamic parcellation based on traditionally defined regions for the primary visual (V1) and auditory cortex (A1), we found distinct regions of the thalamus connected to V1 and A1. But in addition to suprasylvian-A1, we report here, for the first time, the auditory cortex also exists in the temporal lobe, in a region near cetacean-A2 and possibly analogous to the primary auditory cortex in related terrestrial mammals (Artiodactyla). Using probabilistic tract tracing, we found a direct pathway from the inferior colliculus to the medial geniculate nucleus to the temporal lobe near the sylvian fissure. Our results demonstrate the feasibility of post-mortem DTI in archival specimens to answer basic questions in comparative neurobiology in a way that has not previously been possible and shows a link between the cetacean auditory system and those of terrestrial mammals. Given that fresh cetacean specimens are relatively rare, the ability to measure connectivity in archival specimens opens up a plethora of possibilities for investigating neuroanatomy in cetaceans and other species.

There has been much interest in using magnetic resonance diffusion imaging to provide information about anatomical connectivity in the brain by measuring the anisotropic diffusion of water in white matter tracts. One of the measures most commonly derived from diffusion data is fractional anisotropy (FA), which quantifies how strongly directional the local tract structure is. Many imaging studies are starting to use FA images (and other diffusion-derived parameters) in voxelwise statistical analyses, in order to localize brain changes related to development, degeneration, and disease. However, in order to compare such local changes in diffusion parameters across subjects, it is necessary to solve the ‘correspondence problem,’ to determine which location in each subject's diffusion images corresponds to the equivalent anatomical location in the other subjects. Some researchers have used generic registration methods to try to achieve correspondence, some have used region-of-interest approaches, some have used tractography to parameterize diffusion parameters according to anatomical location, and some have combined different aspects of all of these approaches to attempt to achieve robust and accurate correspondence. This article describes many such approaches in the literature, discusses the potential richness available when using more diffusion-derived information than purely the FA, and also illustrates some of the dangers that the researcher should be aware of when interpreting the analysis of multi-subject diffusion MRI studies.

The periaqueductal gray matter (PAG) is a midbrain structure, involved in key homeostatic neurobiological functions, such as pain modulation and cardiorespiratory control. Animal research has identified four subdivisional columns that differ in both connectivity and function. Until now these findings have not been replicated in humans. This study used high‐resolution brainstem optimized diffusion magnetic resonance imaging and probabilistic tractography to segment the human PAG into four subdivisions, based on voxel connectivity profiles. We identified four distinct subdivisions demonstrating high spatial concordance with the columns of the animal model. The resolution of these subdivisions for individual subjects permitted detailed examination of their structural connectivity without the requirement of an a priori starting location. Interestingly patterns of forebrain connectivity appear to be different to those found in nonhuman studies, whereas midbrain and hindbrain connectivity appears to be maintained. Although there are similarities in the columnar structure of the PAG subdivisions between humans and nonhuman animals, there appears to be different patterns of cortical connectivity. This suggests that the functional organization of the PAG may be different between species, and as a consequence, functional studies in nonhumans may not be directly translatable to humans. This highlights the need for focused functional studies in humans. Hum Brain Mapp 36:3459–3471, 2015. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

The striatum acts in conjunction with the cortex to control and execute functions that are impaired by abnormal dopamine neurotransmission in disorders such as Parkinson's and schizophrenia. To date, in vivo quantification of striatal dopamine has been restricted to structure-based striatal subdivisions. Here, we present a multimodal imaging approach that quantifies the endogenous dopamine release following the administration of d-amphetamine in the functional subdivisions of the striatum of healthy humans with [(11)C]PHNO and [(11)C]Raclopride positron emission tomography ligands. Using connectivity-based (CB) parcellation, we subdivided the striatum into functional subregions based on striato-cortical anatomical connectivity information derived from diffusion magnetic resonance imaging (MRI) and probabilistic tractography. Our parcellation showed that the functional organization of the striatum was spatially coherent across individuals, congruent with primate data and previous diffusion MRI studies, with distinctive and overlapping networks. d-amphetamine induced the highest dopamine release in the limbic followed by the sensory, motor, and executive areas. The data suggest that the relative regional proportions of D2-like receptors are unlikely to be responsible for this regional dopamine release pattern. Notably, the homogeneity of dopamine release was significantly higher within the CB functional subdivisions in comparison with the structural subdivisions. These results support an association between local levels of dopamine release and cortical connectivity fingerprints.

Group neuroimaging studies of the cerebral cortex benefit from accurate, surface-based, cross-subject alignment for investigating brain architecture, function and connectivity. There is an increasing amount of high quality data available. However, establishing how different modalities correlate across groups remains an open research question. One reason for this is that the current methods for registration, based on cortical folding, provide sub-optimal alignment of some functional subregions of the brain. A more flexible framework is needed that will allow robust alignment of multiple modalities. We adapt the Fast Primal-Dual (Fast-PD) approach for discrete Markov Random Field (MRF) optimisation to spherical registration by reframing the deformation labels as a discrete set of rotations and propose a novel regularisation term, derived from the geodesic distance between rotation matrices. This formulation allows significant flexibility in the choice of similarity metric. To this end we propose a new multivariate cost function based on the discretisation of a graph-based mutual information measure. Results are presented for alignment driven by scalar metrics of curvature and myelination, and multivariate features derived from functional task performance. These experiments demonstrate the potential of this approach for improving the integration of complementary brain data sets in the future.

The diffusion of water in brain tissue is affected by the local tissue microstructure. Magnetic resonance diffusion imaging is sensitive to these effects, and, in addition to tractography-based studies of long-range connectivity information, there has been a great deal of interest in using voxelwise measures derived from diffusion data as local markers of the tissue microstructure. Diffusion anisotropy describes how variable the diffusion is in different directions and is most commonly quantified via a measure known as fractional anisotropy. Registration is the spatial adjustment of one image to match another. The contents of the "input" image are moved around within the image matrix until they are well aligned with the contents of the "reference" image. Localized/voxelwise analysis of multi-subject diffusion MRI data has a clear role to play, for example in tracking changes in white matter caused by disease. Although careful tractography-based analyses will increasingly have a role to play, whole-brain voxelwise analyzes provide a powerful complement to such approaches, by allowing the entire data set to be investigated in a straightforward manner. The strengths of VBM-style voxelwise analyses are that they are fully automated, simple to apply, investigate the whole brain, and do not require pre-specifying and pre-localizing regions or features of interest. The main limitation relates to problems caused by alignment inaccuracies, including the danger of misinterpreting apparent results in voxels that do not in fact correspond to white matter in all subjects. © 2009 Copyright © 2009 Elsevier Inc. All rights reserved.

Systematic mapping of long-distance pathways in the human brain (the “macro-connectome”) represents a grand challenge for the coming century. Diffusion imaging and resting-state functional MRI represent the two main modalities for examining the macro-connectome in vivo. However, the fidelity with which these two complementary techniques reflect true connectional anatomy is yet to be thoroughly assessed. We review a set of neuroanatomical observations in the macaque monkey that frame our understanding of brain connectivity for primates, including humans. We then describe approaches used by the Human Connectome Project (HCP) to improve data acquisition, analysis, and visualization for diffusion and functional imaging. We also analyze methodological biases and limitations in diffusion imaging and tractography, and discuss options for reducing their impact.

The altered state of consciousness produced by general anesthetics is associated with a variety of changes in the brain's electrical activity. Under hyperpolarizing influences such as anesthetic drugs, cortical neurons oscillate at ~1 Hz, which is measurable as slow waves in the electroencephalogram (EEG). We have administered propofol anesthesia to 16 subjects and found that, after they had lost behavioral responsiveness (response to standard sensory stimuli), each individual's EEG slow-wave activity (SWA) rose to saturation and then remained constant despite increasing drug concentrations. We then simultaneously collected functional magnetic resonance imaging and EEG data in 12 of these subjects during propofol administration and sensory stimulation. During the transition to SWA saturation, the thalamocortical system became isolated from sensory stimuli, whereas internal thalamocortical exchange persisted. Rather, an alternative and more fundamental cortical network (which includes the precuneus) responded to all sensory stimulation. We conclude that SWA saturation is a potential individualized indicator of perception loss that could prove useful for monitoring depth of anesthesia and studying altered states of consciousness.

Behavioral studies indicate that older adults exhibit normal motor sequence learning (MSL), but paradoxically, show impaired consolidation of the new memory trace. However, the neural and physiological mechanisms underlying this impairment are entirely unknown. Here, we sought to identify, through functional magnetic resonance imaging during MSL and electroencephalographic (EEG) recordings during daytime sleep, the functional correlates and physiological characteristics of this age‐related motor memory deficit. As predicted, older subjects did not exhibit sleep‐dependent gains in performance (i.e., behavioral changes that reflect consolidation) and had reduced sleep spindles compared with young subjects. Brain imaging analyses also revealed that changes in activity across the retention interval in the putamen and related brain regions were associated with sleep spindles. This change in striatal activity was increased in young subjects, but reduced by comparison in older subjects. These findings suggest that the deficit in sleep‐dependent motor memory consolidation in elderly individuals is related to a reduction in sleep spindle oscillations and to an associated decrease of activity in the cortico‐striatal network. Hum Brain Mapp 35:3625–3645, 2014. © 2013 Wiley Periodicals, Inc.

This article is a comparative study of white matter projections from ventral prefrontal cortex (vPFC) between human and macaque brains. We test whether the organizational rules that vPFC connections follow in macaques are preserved in humans. These rules concern the trajectories of some of the white matter projections from vPFC and how the position of regions in the vPFC dictate the trajectories of their projections in the white matter. To address this question, we present a novel approach that combines direct tracer measurements of entire white matter trajectories in macaque monkeys with diffusion MRI tractography of both macaques and humans. The approach allows us to provide explicit validation of diffusion tractography and transfer tractography strategies across species to test the extent to which inferences from macaques can be applied to human neuroanatomy. Apart from one exception, we found a remarkable overlap between the two techniques in the macaque. Furthermore, the organizational principles followed by vPFC tracts in macaques are preserved in humans.