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Here, we ask whether frontotemporal cortex is functionally dissociated into distributed lexical and category-specific semantic networks. To this end, fMRI activation patterns elicited during the processing of words from different semantic categories were categorized using k-means cluster algorithms. Results showed a distributed pattern of inferiorfrontal, superiortemporal, and fusiform activation shared by different word categories. This shared activation contrasted with patterns of category-specific semantic activation in widely distributed neural systems. Clustering revealed congruent functional specificity of focal area activations in frontal and temporal cortex; thus suggesting a correspondence between functional partitionings of frontocentral mirror neuron systems and those of inferiortemporal lexical and semantic circuits. Action words related to the face, arms, and legs specifically activated the motor system in a somatotopic manner, whereas form-related words activated prefrontal areas. Similar functional specificity was evident in temporal cortex, where a different semantic topography emerged for form- and action-related words. Results were replicated in a separate data set, therefore recommending fMRI cluster analysis as a reliable method for scrutinizing the brain basis of lexical, semantic, and conceptual systems in humans. As focal modules do not explain the distributed character of functionally specific clusters and their distinct topographies are at variance with general distributed processing accounts, the functionally-homogenous distributed clusters specific to semantic types are best explained by specifically-distributed cortical circuits which, similar to Hebbian cell assemblies, represent functional units with specific roles in cognitive processing, especially in lexical and semantic access and memory., (2009 Wiley-Liss, Inc.)

Detailed knowledge of the anatomy and connectivity pattern of cortico-basal ganglia circuits is essential to an understanding of abnormal cortical function and pathophysiology associated with a wide range of neurological and neuropsychiatric diseases. We aim to study the spatial extent and topography of human basal ganglia connectivity in vivo. Additionally, we explore at an anatomical level the hypothesis of coexistent segregated and integrative cortico-basal ganglia loops. We use probabilistic tractography on magnetic resonance diffusion weighted imaging data to segment basal ganglia and thalamus in 30 healthy subjects based on their cortical and subcortical projections. We introduce a novel method to define voxel-based connectivity profiles that allow representation of projections from a source to more than one target region. Using this method, we localize specific relay nuclei within predefined functional circuits. We find strong correlation between tractography-based basal ganglia parcellation and anatomical data from previously reported invasive tracing studies in nonhuman primates. Additionally, we show in vivo the anatomical basis of segregated loops and the extent of their overlap in prefrontal, premotor, and motor networks. Our findings in healthy humans support the notion that probabilistic diffusion tractography can be used to parcellate subcortical gray matter structures on the basis of their connectivity patterns. The coexistence of clearly segregated and also overlapping connections from cortical sites to basal ganglia subregions is a neuroanatomical correlate of both parallel and integrative networks within them. We believe that this method can be used to examine pathophysiological concepts in a number of basal ganglia-related disorders.

In this paper we propose a generic automatic approach for the parcellation of the cortical surface into labeled gyri. These gyri are defined from a set of pairs of sulci selected by the user. The selected sulci are first automatically identified in the data, then projected onto the cortical surface. The parcellation stems from two nested Voronoï diagrams computed geodesically to the cortical surface. The first diagram provides the zones of influence of the sulci. The boundary between the two zones of influence of each selected pair of sulci stands for a gyrus seed. A second diagram yields the gyrus parcellation. The distance underlying the Voronoï diagram allows the method to interpolate the gyrus boundaries where the limiting sulci are interrupted. The method is illustrated with 12 different hemispheres.

In this paper, we propose a new representation of the cortical surface that may be used to study the cortex folding process and to recover some putative stable anatomical landmarks called sulcal roots usually buried in the depth of adult brains. This representation is a primal sketch derived from a scale space computed for the mean curvature of the cortical surface. This scale-space stems from a diffusion equation geodesic to the cortical surface. The primal sketch is made up of objects defined from mean curvature minima and saddle points. The resulting sketch aims first at highlighting significant elementary cortical folds, second at representing the fold merging process during brain growth. The relevance of the framework is illustrated by the study of central sulcus sulcal roots from antenatal to adult age. Some results are proposed for ten different brains. Some preliminary results are also provided for superior temporal sulcus.

A methodology for fMRI data analysis confined to the cortex, Cortical Surface Mapping (CSM), is presented. CSM retains the flexibility of the General Linear Model based estimation, but the procedures involved are adapted to operate on the cortical surface, while avoiding to resort to explicit flattening. The methodology is tested by means of simulations and application to a real fMRI protocol. The results are compared with those obtained with a standard, volume-oriented approach (SPM), and it is shown that CSM leads to local differences in sensitivity, with generally higher sensitivity for CSM in two of the three subjects studied. The discussion provided is focused on the benefits of the introduction of anatomical information in fMRI data analysis, and the relevance of CSM as a step toward this goal.