Rostro-caudal Architecture of the Frontal Lobes in Humans

The Dimensionality of Neural Coding for Cognitive Control Is Gradually Transformed within the Lateral Prefrontal Cortex

Cognitive control relies on neural representations that are inherently high-dimensional and distributed across multiple subregions in the prefrontal cortex (PFC). Traditional approaches tackle prefrontal representation by reducing it into a unidimensional measure (univariate amplitude) or using it to distinguish a limited number of alternatives (pattern classification). In contrast, representational similarity analysis (RSA) enables flexibly formulating various hypotheses about informational contents underlying the neural codes, explicitly comparing hypotheses, and examining the representational alignment between brain regions. Here, we used a multifaceted paradigm wherein the difficulty of cognitive control was manipulated separately for five cognitive tasks. We used RSA to unveil representational contents, measure the representational alignment between regions, and quantify representational generality versus specificity. We found a graded transition in the lateral PFC: The dorsocaudal PFC was tuned to task difficulty (indexed by reaction times), preferentially connected with the parietal cortex, and representationally generalizable across domains. The ventrorostral PFC was tuned to the abstract structure of tasks, preferentially connected with the temporal cortex, and representationally specific. The middle PFC (interposed between the dorsocaudal and ventrorostral PFC) was tuned to individual task sets and ranked in the middle in terms of connectivity and generalizability. Furthermore, whether a region was dimensionally rich or sparse covaried with its functional profile: Low dimensionality (only gist) in the dorsocaudal PFC dovetailed with better generality, whereas high dimensionality (gist plus details) in the ventrorostral PFC corresponded with better ability to encode subtleties. Our findings, collectively, demonstrate how cognitive control is decomposed into distinct facets that transition steadily along prefrontal subregions.

Addressing Inconsistency in Functional Neuroimaging: A Replicable Data-Driven Multi-Scale Functional Atlas for Canonical Brain Networks

The advent of multiple neuroimaging methodologies has greatly aided in the conceptualization of large-scale functional brain networks in the field of cognitive neuroscience. However, there is inconsistency across studies in both nomenclature and the functional entities being described. There is a need for a unifying framework that standardizes terminology across studies while also bringing analyses and results into the same reference space. Here we present a whole-brain atlas of canonical functional brain networks derived from more than 100,000 resting-state fMRI datasets. These data-driven functional networks are highly replicable across datasets and capture information from multiple spatial scales. We have organized, labeled, and described the networks with terms familiar to the fields of cognitive and affective neuroscience in order to optimize their utility in future neuroimaging analyses and enhance the accessibility of new findings. The benefits of this atlas are not limited to future template-based or reference-guided analyses, but also extend to other data-driven neuroimaging approaches across modalities, such as those using blind independent component analysis (ICA). Future studies utilizing this atlas will contribute to greater harmonization and standardization in functional neuroimaging research.

Are we ready to cure post-stroke cognitive impairment? Many key prerequisites can be achieved quickly and easily

PURPOSE

Post-stroke (PS) cognitive impairment (CI) is frequent and its devastating functional and vital consequences are well known. Despite recent guidelines, they are still largely neglected. A large number of recent studies have re-examined the epidemiology, diagnosis, imaging determinants and management of PSCI. The aim of this update is to determine whether these new data answer the questions that are essential to reducing PSCI, the unmet needs, and steps still to be taken.

METHODS

Literature review of stroke unit-era studies examining key steps in the management of PSCI: epidemiology and risk factors, diagnosis (cognitive profile and assessments), imaging determinants (quantitative measures, voxelwise localization, the disconnectome and associated Alzheimer's disease [AD]) and treatment (secondary prevention, symptomatic drugs, rehabilitation and noninvasive brain stimulation) of PSCI.

FINDINGS

(1) the prevalence of PSCI of approximately 50% is probably underestimated; (2) the sensitivity of screening tests should be improved to detect mild PSCI; (3) comprehensive assessment is now well-defined and should include apathy; (4) easily available factors can identify patients at high risk of PSCI; (5) key imaging determinants are the location and volume of the lesion and the resulting disconnection, associated AD and brain atrophy; WMH, ePVS, microhemorrhages, hemosiderosis, and cortical microinfarcts may contribute to cognitive impairment but are more likely to be markers of brain vulnerability or associated AD that reduce PS recovery; (6) remote and online assessment is a promising approach for selected patients; (7) secondary stroke prevention has not been proven to prevent PSCI; (8) symptomatic drugs are ineffective in treating PSCI and apathy; (9) in addition to cognitive rehabilitation, the benefits of training platforms and computerized training are yet to be documented; (10) the results and the magnitude of improvement of noninvasive brain stimulation, while very promising, need to be substantiated by large, high-quality, sham-controlled RCTs.

DISCUSSION AND CONCLUSION

These major advances pave the way for the reduction of PSCI. They include (1) the development of more sensitive screening tests applicable to all patients and (2) online remote assessment; crossvalidation of (3) clinical and (4) imaging factors to (5) identify patients at risk, as well as (6) factors that prompt a search for associated AD; (7) the inclusion of cognitive outcome as a secondary endpoint in acute and secondary stroke prevention trials; and (8) the validation of the benefit of noninvasive brain stimulation through high-quality, randomized, sham-controlled trials. Many of these objectives can be rapidly and easily attained.

A new open, high-resolution, multishell, diffusion-weighted imaging dataset of the living squirrel monkey

Although very well adapted to brain study, Magnetic Resonance Imaging (MRI) remains limited by the facilities and capabilities required to acquire data, especially for non-human primates. Addressing the data gaps resulting from these limitations requires making data more accessible and open. In contempt of the regular use of Saimiri sciureus in neuroscience research, in vivo diffusion has yet to be openly available for this species. Here we built and made openly available a unique new resource consisting of a high-resolution, multishell diffusion-weighted dataset in the anesthetized Saimiri sciureus. The data were acquired on 11 individuals with an 11.7 T MRI scanner (isotropic resolution of 400 µm³). This paper presents an overview of our dataset and illustrates some of its possible use through example analyses. To assess the quality of our data, we analyzed long-range connections (whole-brain tractography), microstructure (Neurite Orientation Dispersion and Density Imaging), and axon diameter in the corpus callosum (ActiveAx). Constituting an essential new resource for primate evolution studies, all data are openly available.

Graded functional organisation in the left inferior frontal gyrus: evidence from task-free and task-based functional connectivity

The left inferior frontal gyrus (LIFG) has been ascribed key roles in numerous cognitive domains, including language, executive function and social cognition. However, its functional organisation, and how the specific areas implicated in these cognitive domains relate to each other, is unclear. Possibilities include that the LIFG underpins a domain-general function or, alternatively, that it is characterized by functional differentiation, which might occur in either a discrete or a graded pattern. The aim of the present study was to explore the topographical organisation of the LIFG using a bimodal data-driven approach. To this end, we extracted functional connectivity (FC) gradients from 1) the resting-state fMRI time-series of 150 participants (77 female), and 2) patterns of co-activation derived meta-analytically from task data across a diverse set of cognitive domains. We then sought to characterize the FC differences driving these gradients with seed-based resting-state FC and meta-analytic co-activation modelling analyses. Both analytic approaches converged on an FC profile that shifted in a graded fashion along two main organisational axes. An anterior-posterior gradient shifted from being preferentially associated with high-level control networks (anterior LIFG) to being more tightly coupled with perceptually-driven networks (posterior). A second dorsal-ventral axis was characterized by higher connectivity with domain-general control networks on one hand (dorsal LIFG), and with the semantic network, on the other (ventral). These results provide novel insights into a graded functional organisation of the LIFG underpinning both task-free and task-constrained mental states, and suggest that the LIFG is an interface between distinct large-scale functional networks.

Assessment of structural disconnections in gliomas: comparison of indirect and direct approaches

Gliomas are amongst the most common primary brain tumours in adults and are often associated with poor prognosis. Understanding the extent of white matter (WM) which is affected outside the tumoral lesion may be of paramount importance to explain cognitive deficits and the clinical progression of the disease. To this end, we explored both direct (i.e., tractography based) and indirect (i.e., atlas-based) approaches to quantifying WM structural disconnections in a cohort of 44 high- and low-grade glioma patients. While these methodologies have recently gained popularity in the context of stroke and other pathologies, to our knowledge, this is the first time they are applied in patients with brain tumours. More specifically, in this work, we present a quantitative comparison of the disconnection maps provided by the two methodologies by applying well-known metrics of spatial similarity, extension, and correlation. Given the important role the oedematous tissue plays in the physiopathology of tumours, we performed these analyses both by including and excluding it in the definition of the tumoral lesion. This was done to investigate possible differences determined by this choice. We found that direct and indirect approaches offer two distinct pictures of structural disconnections in patients affected by brain gliomas, presenting key differences in several regions of the brain. Following the outcomes of our analysis, we eventually discuss the strengths and pitfalls of these two approaches when applied in this critical field.

A tale of two gradients: differences between the left and right hemispheres predict semantic cognition

Decomposition of whole-brain functional connectivity patterns reveals a principal gradient that captures the separation of sensorimotor cortex from heteromodal regions in the default mode network (DMN). Functional homotopy is strongest in sensorimotor areas, and weakest in heteromodal cortices, suggesting there may be differences between the left and right hemispheres (LH/RH) in the principal gradient, especially towards its apex. This study characterised hemispheric differences in the position of large-scale cortical networks along the principal gradient, and their functional significance. We collected resting-state fMRI and semantic, working memory and non-verbal reasoning performance in 175 + healthy volunteers. We then extracted the principal gradient of connectivity for each participant, tested which networks showed significant hemispheric differences on the gradient, and regressed participants’ behavioural efficiency in tasks outside the scanner against interhemispheric gradient differences for each network. LH showed a higher overall principal gradient value, consistent with its role in heteromodal semantic cognition. One frontotemporal control subnetwork was linked to individual differences in semantic cognition: when it was nearer heteromodal DMN on the principal gradient in LH, participants showed more efficient semantic retrieval—and this network also showed a strong hemispheric difference in response to semantic demands but not working memory load in a separate study. In contrast, when a dorsal attention subnetwork was closer to the heteromodal end of the principal gradient in RH, participants showed better visual reasoning. Lateralization of function may reflect differences in connectivity between control and heteromodal regions in LH, and attention and visual regions in RH.

Functionnectome as a framework to analyse the contribution of brain circuits to fMRI

In recent years, the field of functional neuroimaging has moved away from a pure localisationist approach of isolated functional brain regions to a more integrated view of these regions within functional networks. However, the methods used to investigate functional networks rely on local signals in grey matter and are limited in identifying anatomical circuitries supporting the interaction between brain regions. Mapping the brain circuits mediating the functional signal between brain regions would propel our understanding of the brain's functional signatures and dysfunctions. We developed a method to unravel the relationship between brain circuits and functions: The Functionnectome. The Functionnectome combines the functional signal from fMRI with white matter circuits' anatomy to unlock and chart the first maps of functional white matter. To showcase this method's versatility, we provide the first functional white matter maps revealing the joint contribution of connected areas to motor, working memory, and language functions. The Functionnectome comes with an open-source companion software and opens new avenues into studying functional networks by applying the method to already existing datasets and beyond task fMRI.

The Graded Change in Connectivity across the Ventromedial Prefrontal Cortex Reveals Distinct Subregions

The functional heterogeneity of the ventromedial prefrontal cortex (vmPFC) suggests it may include distinct functional subregions. To date these have not been well elucidated. Regions with differentiable connectivity (and as a result likely dissociable functions) may be identified using emergent data-driven approaches. However, prior parcellations of the vmPFC have only considered hard splits between distinct regions, although both hard and graded connectivity changes may exist. Here we determine the full pattern of change in structural and functional connectivity across the vmPFC for the first time and extract core distinct regions. Both structural and functional connectivity varied along a dorsomedial to ventrolateral axis from relatively dorsal medial wall regions to relatively lateral basal orbitofrontal cortex. The pattern of connectivity shifted from default mode network to sensorimotor and multimodal semantic connections. This finding extends the classical distinction between primate medial and orbital regions by demonstrating a similar gradient in humans for the first time. Additionally, core distinct regions in the medial wall and orbitofrontal cortex were identified that may show greater correspondence to functional differences than prior hard parcellations. The possible functional roles of the orbitofrontal cortex and medial wall are discussed.

Reward-related choices determine information timing and flow across macaque lateral prefrontal cortex

Prefrontal cortex is critical for cognition. Although much is known about the representation of cognitive variables in the prefrontal cortex, much less is known about the spatio-temporal neural dynamics that underlie cognitive operations. In the present study, we examined information timing and flow across the lateral prefrontal cortex (LPFC), while monkeys carried out a two-armed bandit reinforcement learning task in which they had to learn to select rewarding actions or rewarding objects. When we analyzed signals independently within subregions of the LPFC, we found a task-specific, caudo-rostral gradient in the strength and timing of signals related to chosen objects and chosen actions. In addition, when we characterized information flow among subregions, we found that information flow from action to object representations was stronger from the dorsal to ventral LPFC, and information flow from object to action representations was stronger from the ventral to dorsal LPFC. The object to action effects were more pronounced in object blocks, and also reflected learning specifically in these blocks. These results suggest anatomical segregation followed by the rapid integration of information within the LPFC.

Previous studies provided conflicting evidence on the functional organization of the lateral prefrontal cortex. The authors show task-specific information flows along the caudo-rostral and dorso-ventral axes, reflecting the cognitive process of identifying the location or identity of a valuable object.

BigBrain 3D atlas of cortical layers: Cortical and laminar thickness gradients diverge in sensory and motor cortices

Histological atlases of the cerebral cortex, such as those made famous by Brodmann and von Economo, are invaluable for understanding human brain microstructure and its relationship with functional organization in the brain. However, these existing atlases are limited to small numbers of manually annotated samples from a single cerebral hemisphere, measured from 2D histological sections. We present the first whole-brain quantitative 3D laminar atlas of the human cerebral cortex. It was derived from a 3D histological atlas of the human brain at 20-micrometer isotropic resolution (BigBrain), using a convolutional neural network to segment, automatically, the cortical layers in both hemispheres. Our approach overcomes many of the historical challenges with measurement of histological thickness in 2D, and the resultant laminar atlas provides an unprecedented level of precision and detail. We utilized this BigBrain cortical atlas to test whether previously reported thickness gradients, as measured by MRI in sensory and motor processing cortices, were present in a histological atlas of cortical thickness and which cortical layers were contributing to these gradients. Cortical thickness increased across sensory processing hierarchies, primarily driven by layers III, V, and VI. In contrast, motor-frontal cortices showed the opposite pattern, with decreases in total and pyramidal layer thickness from motor to frontal association cortices. These findings illustrate how this laminar atlas will provide a link between single-neuron morphology, mesoscale cortical layering, macroscopic cortical thickness, and, ultimately, functional neuroanatomy.

Using deep learning to segment the layers of the cerebral cortex, this study presents the first whole brain quantitative atlas of cortical and laminar structure. This laminar atlas provides a novel framework for bridging between the scales of neuroscience.

Connectivity Gradient in the Human Left Inferior Frontal Gyrus: Intraoperative Cortico-Cortical Evoked Potential Study

In the dual-stream model of language processing, the exact connectivity of the ventral stream to the anterior temporal lobe remains elusive. To investigate the connectivity between the inferior frontal gyrus (IFG) and the lateral part of the temporal and parietal lobes, we integrated spatiotemporal profiles of cortico-cortical evoked potentials (CCEPs) recorded intraoperatively in 14 patients who had undergone surgical resection for a brain tumor or epileptic focus. Four-dimensional visualization of the combined CCEP data showed that the pars opercularis (Broca’s area) is connected to the posterior temporal cortices and the supramarginal gyrus, whereas the pars orbitalis is connected to the anterior lateral temporal cortices and angular gyrus. Quantitative topographical analysis of CCEP connectivity confirmed an anterior–posterior gradient of connectivity from IFG stimulus sites to the temporal response sites. Reciprocality analysis indicated that the anterior part of the IFG is bidirectionally connected to the temporal or parietal area. This study shows that each IFG subdivision has different connectivity to the temporal lobe with an anterior–posterior gradient and supports the classical connectivity concept of Dejerine; that is, the frontal lobe is connected to the temporal lobe through the arcuate fasciculus and also a double fan-shaped structure anchored at the limen insulae.

Anosognosia for hemiplegia as a tripartite disconnection syndrome

The syndrome of Anosognosia for Hemiplegia (AHP) can provide unique insights into the neurocognitive processes of motor awareness. Yet, prior studies have only explored predominately discreet lesions. Using advanced structural neuroimaging methods in 174 patients with a right-hemisphere stroke, we were able to identify three neural systems that contribute to AHP, when disconnected or directly damaged: the (i) premotor loop (ii) limbic system, and (iii) ventral attentional network. Our results suggest that human motor awareness is contingent on the joint contribution of these three systems.

Frontal pathways in cognitive control: direct evidence from intraoperative stimulation and diffusion tractography

A key aspect of cognitive control is the management of conflicting incoming information to achieve a goal, termed 'interference control'. Although the role of the right frontal lobe in interference control is evident, the white matter tracts subserving this cognitive process remain unclear. To investigate this, we studied the effect of transient network disruption (by means of direct electrical stimulation) and permanent disconnection (resulting from neurosurgical resection) on interference control processes, using the Stroop test in the intraoperative and extraoperative neurosurgical setting. We evaluated the sites at which errors could be produced by direct electrical stimulation during an intraoperative Stroop test in 34 patients with frontal right hemisphere glioma. Lesion-symptom mapping was used to evaluate the relationship between the resection cavities and postoperative performance on the Stroop test of this group compared with an additional 29 control patients who did not perform the intraoperative test (63 patients in total aged 17-77 years; 28 female). We then examined tract disruption and disconnection in a subset of eight patients who underwent both the intraoperative Stroop test and high angular resolution diffusion imaging (HARDI) tractography. The results showed that, intraoperatively, the majority of sites associated with errors during Stroop test performance and concurrent subcortical stimulation clustered in a region of white matter medial to the right inferior frontal gyrus, lateral and superior to the striatum. Patients who underwent the intraoperative test maintained cognitive control ability at the 1-month follow-up (P = 0.003). Lesion-symptom analysis showed resection of the right inferior frontal gyrus was associated with slower postoperative Stroop test ability (corrected for multiple comparisons, 5000 permutations). The stimulation sites associated with intraoperative errors most commonly corresponded with the inferior fronto-striatal tracts and anterior thalamic radiation (over 75% of patients), although the latter was commonly resected without postoperative deficits on the Stroop test (in 60% of patients). Our results show converging evidence to support a critical role for the inferior frontal gyrus in interference control processes. The intraoperative data combined with tractography suggests that cortico-subcortical tracts, over cortico-cortical connections, may be vital in maintaining efficiency of cognitive control processes. This suggests the importance of their preservation during resection of right frontal tumours.

The role of diffusion MRI in neuroscience

Diffusion-weighted imaging has pushed the boundaries of neuroscience by allowing us to examine the white matter microstructure of the living human brain. By doing so, it has provided answers to fundamental neuroscientific questions, launching a new field of research that had been largely inaccessible. We briefly summarize key questions that have historically been raised in neuroscience concerning the brain's white matter. We then expand on the benefits of diffusion-weighted imaging and its contribution to the fields of brain anatomy, functional models and plasticity. In doing so, this review highlights the invaluable contribution of diffusion-weighted imaging in neuroscience, presents its limitations and proposes new challenges for future generations who may wish to exploit this powerful technology to gain novel insights.

The architecture of functional lateralisation and its relationship to callosal connectivity in the human brain

Functional lateralisation is a fundamental principle of the human brain. However, a comprehensive taxonomy of functional lateralisation and its organisation in the brain is missing. Here, we report the first complete map of functional hemispheric asymmetries in the human brain, reveal its low dimensional structure, and its relationship with structural inter-hemispheric connectivity. Our results suggest that the lateralisation of brain functions is distributed along four functional axes: symbolic communication, perception/action, emotion, and decision-making. The similarity between this finding and recent work on neurological symptoms give rise to new hypotheses on the mechanisms that support brain recovery after a brain lesion. We also report that cortical regions showing asymmetries in task-evoked activity have reduced connections with the opposite hemisphere. This latter result suggests that during evolution, brain size expansion led to functional lateralisation to avoid excessive conduction delays between the hemispheres.

Effect of different spatial normalization approaches on tractography and structural brain networks

To facilitate the comparison of white matter morphologic connectivity across target populations, it is invaluable to map the data to a standardized neuroanatomical space. Here, we evaluated direct streamline normalization (DSN), where the warping was applied directly to the streamlines, with two publically available approaches that spatially normalize the diffusion data and then reconstruct the streamlines. Prior work has shown that streamlines generated after normalization from reoriented diffusion data do not reliably match the streamlines generated in native space. To test the impact of these different normalization methods on quantitative tractography measures, we compared the reproducibility of the resulting normalized connectivity matrices and network metrics with those originally obtained in native space. The two methods that reconstruct streamlines after normalization led to significant differences in network metrics with large to huge standardized effect sizes, reflecting a dramatic alteration of the same subject’s native connectivity. In contrast, after normalizing with DSN we found no significant difference in network metrics compared with native space with only very small-to-small standardized effect sizes. DSN readily outperformed the other methods at preserving native space connectivity and introduced novel opportunities to define connectome networks without relying on gray matter parcellations.

Direct streamline normalization (DSN) directly warps the streamlines into any template space by using the transformations output from Advanced Normalization Tools (ANTs). DSN overcomes the limitations of diffusion weighted images (DWI) spatial normalization. It allows DWIs to be acquired with any desired sampling scheme. Fiber orientation distributions (FODs) or orientation distribution functions (ODFs) can also be reconstructed using any desired method and streamlines generated using any algorithm. Most importantly, it avoids the problem of generating tracts from FODs or ODFs that have become distorted because of spatial normalization. Our results show that DSN has minimal influence on tractography measures such as tract count and structure and does not significantly alter structural networks with only very small to small effect sizes. We have developed a framework in Python that works with most diffusion software platforms. It is available at http://github.com/clintg6/DSN.

Modulation of network-to-network connectivity via spike-timing-dependent noninvasive brain stimulation

Human cognitive abilities and behavior are linked to functional coupling of many brain regions organized in distinct networks. Gaining insights on the role those networks' dynamics play in cognition and pathology requires their selective, reliable, and reversible manipulation. Here we document the possibility to manipulate the interplay between two brain networks in a controlled manner, by means of a Transcranial Magnetic Stimulation (TMS) protocol inducing spike timing dependent plasticity (STDP). Pairs of TMS pulses at specific inter-stimulus intervals, repeatedly delivered over two negatively correlated nodes of the default mode network (DMN) and the task-positive network (TPN) defined on the basis of individual functional magnetic resonance imaging (fMRI) data, induced a modulation of network-to-network connectivity, even reversing correlation from negative to slightly positive in 30% of cases. Results also suggest a baseline-dependent effect, with a greater connectivity modulation observed in participants with weaker between-networks connectivity strength right before TMS. Finally, modulation of task-evoked fMRI activity patterns during a sustained attention task was also observed after stimulation, with a faster or slower switch between rest and task blocks according to the timing of TMS pulses. The present findings promote paired associative TMS as a promising technique for controlled manipulation of fMRI connectivity dynamics in humans, as well as the causal investigation of brain-behavior relations.

Visual brain plasticity induced by central and peripheral visual field loss

Disorders that specifically affect central and peripheral vision constitute invaluable models to study how the human brain adapts to visual deafferentation. We explored cortical changes after the loss of central or peripheral vision. Cortical thickness (CoTks) and resting-state cortical entropy (rs-CoEn), as a surrogate for neural and synaptic complexity, were extracted in 12 Stargardt macular dystrophy, 12 retinitis pigmentosa (tunnel vision stage), and 14 normally sighted subjects. When compared to controls, both groups with visual loss exhibited decreased CoTks in dorsal area V3d. Peripheral visual field loss also showed a specific CoTks decrease in early visual cortex and ventral area V4, while central visual field loss in dorsal area V3A. Only central visual field loss exhibited increased CoEn in LO-2 area and FG1. Current results revealed biomarkers of brain plasticity within the dorsal and the ventral visual streams following central and peripheral visual field defects.

Groupwise structural parcellation of the whole cortex: A logistic random effects model based approach

Current theories hold that brain function is highly related to long-range physical connections through axonal bundles, namely extrinsic connectivity. However, obtaining a groupwise cortical parcellation based on extrinsic connectivity remains challenging. Current parcellation methods are computationally expensive; need tuning of several parameters or rely on ad-hoc constraints. Furthermore, none of these methods present a model for the cortical extrinsic connectivity of the cortex. To tackle these problems, we propose a parsimonious model for the extrinsic connectivity and an efficient parceling technique based on clustering of tractograms. Our technique allows the creation of single subject and groupwise parcellations of the whole cortex. The parcellations obtained with our technique are in agreement with structural and functional parcellations in the literature. In particular, the motor and sensory cortex are subdivided in agreement with the human homunculus of Penfield. We illustrate this by comparing our resulting parcels with the motor strip mapping included in the Human Connectome Project data.

Is There Evidence for a Rostral-Caudal Gradient in Fronto-Striatal Loops and What Role Does Dopamine Play?

Research has shown that the lateral prefrontal cortex (LPFC) may be hierarchically organized along a rostral-caudal functional gradient such that control processing becomes progressively more abstract from caudal to rostral frontal regions. Here, we briefly review the most recent functional MRI, neuropsychological, and electrophysiological evidence in support of a hierarchical LPFC organization. We extend these observations by discussing how such a rostral-caudal gradient may also exist in the striatum and how the dopaminergic system may play an important role in the hierarchical organization of fronto-striatal loops. There is evidence indicating that a rostral-caudal gradient of dopamine receptor density may exist in both frontal and striatal regions. Here we formulate the hypothesis that dopamine may be an important neuromodulator in hierarchical processing, whereby frontal and striatal regions that have higher dopamine receptor density may have a larger influence over regions that exhibit lower dopamine receptor density. We conclude by highlighting directions for future research that will help elucidating the role dopamine might play in hierarchical frontal-striatal interactions.

Early bilateral and massive compromise of the frontal lobes

The frontal lobes are one of the most complex brain structures involved in both domain-general and specific functions. The goal of this work was to assess the anatomical and cognitive affectations from a unique case with massive bilateral frontal affectation. We report the case of GC, an eight-year old child with nearly complete affectation of bilateral frontal structures and spared temporal, parietal, occipital, and cerebellar regions. We performed behavioral, neuropsychological, and imaging (MRI, DTI, fMRI) evaluations. Neurological and neuropsychological examinations revealed a mixed pattern of affected (executive control/abstraction capacity) and considerably preserved (consciousness, language, memory, spatial orientation, and socio-emotional) functions. Both structural (DTI) and functional (fMRI) connectivity evidenced abnormal anterior connections of the amygdala and parietal networks. In addition, brain structural connectivity analysis revealed almost complete loss of frontal connections, with atypical temporo-posterior pathways. Similarly, functional connectivity showed an aberrant frontoparietal network and relative preservation of the posterior part of the default mode network and the visual network. We discuss this multilevel pattern of behavioral, structural, and functional connectivity results. With its unique pattern of compromised and preserved structures and functions, this exceptional case offers new constraints and challenges for neurocognitive theories.

Parallel trends in cortical gray and white matter architecture and connections in primates allow fine study of pathways in humans and reveal network disruptions in autism

Noninvasive imaging and tractography methods have yielded information on broad communication networks but lack resolution to delineate intralaminar cortical and subcortical pathways in humans. An important unanswered question is whether we can use the wealth of precise information on pathways from monkeys to understand connections in humans. We addressed this question within a theoretical framework of systematic cortical variation and used identical high-resolution methods to compare the architecture of cortical gray matter and the white matter beneath, which gives rise to short- and long-distance pathways in humans and rhesus monkeys. We used the prefrontal cortex as a model system because of its key role in attention, emotions, and executive function, which are processes often affected in brain diseases. We found striking parallels and consistent trends in the gray and white matter architecture in humans and monkeys and between the architecture and actual connections mapped with neural tracers in rhesus monkeys and, by extension, in humans. Using the novel architectonic portrait as a base, we found significant changes in pathways between nearby prefrontal and distant areas in autism. Our findings reveal that a theoretical framework allows study of normal neural communication in humans at high resolution and specific disruptions in diverse psychiatric and neurodegenerative diseases.

Frontal Cortex and the Hierarchical Control of Behavior

The frontal lobes are important for cognitive control, yet their functional organization remains controversial. An influential class of theory proposes that the frontal lobes are organized along their rostrocaudal axis to support hierarchical cognitive control. Here, we take an updated look at the literature on hierarchical control, with particular focus on the functional organization of lateral frontal cortex. Our review of the evidence supports neither a unitary model of lateral frontal function nor a unidimensional abstraction gradient. Rather, separate frontal networks interact via local and global hierarchical structure to support diverse task demands.

Concurrent white matter bundles and grey matter networks using independent component analysis

Developments in non-invasive diffusion MRI tractography techniques have permitted the investigation of both the anatomy of white matter pathways connecting grey matter regions and their structural integrity. In parallel, there has been an expansion in automated techniques aimed at parcellating grey matter into distinct regions based on functional imaging. Here we apply independent component analysis to whole-brain tractography data to automatically extract brain networks based on their associated white matter pathways. This method decomposes the tractography data into components that consist of paired grey matter ‘nodes’ and white matter ‘edges’, and automatically separates major white matter bundles, including known cortico-cortical and cortico-subcortical tracts. We show how this framework can be used to investigate individual variations in brain networks (in terms of both nodes and edges) as well as their associations with individual differences in behaviour and anatomy. Finally, we investigate correspondences between tractography-based brain components and several canonical resting-state networks derived from functional MRI.

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Parcellation of whole brain grey matter based on diffusion tractography using ICA.

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Data driven patterns of connectivity correspond to region-of-interest based tractography.

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Both hard and soft parcellations show good split-half reliability.

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Cortical and subcortical parcels correspond to known resting state networks.

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ICA provides a principled data-reduction step for tractography data.

Age-related mapping of intracortical myelin from late adolescence to middle adulthood using T1 -weighted MRI

Magnetic resonance imaging (MRI) studies in humans have reported that the T₁ -weighted signal in the cerebral cortex follows an inverted "U" trajectory over the lifespan. Here, we investigated the T₁ -weighted signal trajectory from late adolescence to middle adulthood in humans to characterize the age range when mental illnesses tend to present, and efficacy of treatments are evaluated. We compared linear to quadratic predictors of age on signal in 67 healthy individuals, 17-45 years old. We investigated ¼, ½, and ¾ depths in the cortex representing intracortical myelin (ICM), in the superficial white matter (SWM), and in a reference deep white matter tract. We found that the quadratic fit was superior in all regions of the cortex, while signal in the SWM and deep white matter showed no global dependence on age over this range. The signal trajectory in any region followed a similar shape regardless of cortical depth. The quadratic fit was analyzed in 70 cortical regions to obtain the age of maximum signal intensity. We found that visual, cingulate, and left ventromedial prefrontal cortices peak first around 34 years old, whereas motor and premotor areas peak latest at ∼38 years. Our analysis suggests that ICM trajectories over this range can be modeled well in small cohorts of subjects using quadratic functions, which are amenable to statistical analysis, thus suitable for investigating regional changes in ICM with disease. This study highlights a novel approach to map ICM trajectories using an age range that coincides with the onset of many mental illnesses. Hum Brain Mapp 38:3691-3703, 2017. © 2017 Wiley Periodicals, Inc.

Topographic organization of the cerebral cortex and brain cartography

One of the most specific but also challenging properties of the brain is its topographic organization into distinct modules or cortical areas. In this paper, we first review the concept of topographic organization and its historical development. Next, we provide a critical discussion of the current definition of what constitutes a cortical area, why the concept has been so central to the field of neuroimaging and the challenges that arise from this view. A key aspect in this discussion is the issue of spatial scale and hierarchy in the brain. Focusing on in-vivo brain parcellation as a rapidly expanding field of research, we highlight potential limitations of the classical concept of cortical areas in the context of multi-modal parcellation and propose a revised interpretation of cortical areas building on the concept of neurobiological atoms that may be aggregated into larger units within and across modalities. We conclude by presenting an outlook on the implication of this revised concept for future mapping studies and raise some open questions in the context of brain parcellation.

Functional segregation and integration within fronto-parietal networks

Experimental data on monkeys and functional studies in humans support the existence of a complex fronto-parietal system activating for cognitive and motor tasks, which may be anatomically supported by the superior longitudinal fasciculus (SLF). Advanced tractography methods have recently allowed the separation of the three branches of the SLF but are not suitable for their functional investigation. In order to gather comprehensive information about the functional organisation of these fronto-parietal connections, we used an innovative method, which combined tractography of the SLF in the largest dataset so far (129 participants) with 14 meta-analyses of functional magnetic resonance imaging (fMRI) studies. We found that frontal and parietal functions can be clustered into a dorsal spatial/motor network associated with the SLF I, and a ventral non-spatial/motor network associated with the SLF III. Further, all the investigated functions activated a middle network mostly associated with the SLF II. Our findings suggest that dorsal and ventral fronto-parietal networks are segregated but also share regions of activation, which may support flexible response properties or conscious processing. In sum, our novel combined approach provided novel findings on the functional organisation of fronto-parietal networks, and may be successfully applied to other brain connections.

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We used a novel approach to investigate fronto-parietal functions.

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These are segregated into a dorsal spatial and a ventral non-spatial network.

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These networks rely on the superior longitudinal fasciculus (1st and 3rd branch).

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They overlap on areas with flexible response properties that rely on the 2nd branch.