Ferath Kherif

Evidence for Segregated and Integrative Connectivity Patterns in the Human Basal Ganglia

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.

Motor cortex maps articulatory features of speech sounds

The processing of spoken language has been attributed to areas in the superior temporal lobe, where speech stimuli elicit the greatest activation. However, neurobiological and psycholinguistic models have long postulated that knowledge about the articulatory features of individual phonemes has an important role in their perception and in speech comprehension. To probe the possible involvement of specific motor circuits in the speech-perception process, we used event-related functional MRI and presented experimental subjects with spoken syllables, including [p] and [t] sounds, which are produced by movements of the lips or tongue, respectively. Physically similar nonlinguistic signal-correlated noise patterns were used as control stimuli. In localizer experiments, subjects had to silently articulate the same syllables and, in a second task, move their lips or tongue. Speech perception most strongly activated superior temporal cortex. Crucially, however, distinct motor regions in the precentral gyrus sparked by articulatory movements of the lips and tongue were also differentially activated in a somatotopic manner when subjects listened to the lip- or tongue-related phonemes. This sound-related somatotopic activation in precentral gyrus shows that, during speech perception, specific motor circuits are recruited that reflect phonetic distinctive features of the speech sounds encountered, thus providing direct neuroimaging support for specific links between the phonological mechanisms for speech perception and production.

Multivariate voxel-based morphometry successfully differentiates schizophrenia patients from healthy controls

Currently available laboratory procedures might provide additional information to psychiatric diagnostic systems for more valid classifications of mental disorders. To identify the correlative pattern of gray matter distribution that best discriminates schizophrenia patients from healthy subjects, we applied discriminant function analysis techniques using the multivariate linear model and the voxel-based morphometry. The first analysis was conducted to obtain a statistical model that classified 30 male healthy subjects and 30 male schizophrenia patients diagnosed according to current operational criteria. The second analysis was performed to prospectively validate the statistical model by successfully classifying a new cohort that consisted of 16 male healthy subjects and 16 male schizophrenia patients. Inferences about the structural relevance of the gray matter distribution could be made if the individual profile of pattern expression could be linked to the specific diagnosis of each subject. The result was that 90% of the subjects were correctly classified by the eigenimage, and the Jackknife approach revealed well above chance accuracy. The pattern of the eigenimage was characterized by positive loadings indicating gray matter decline in the patients in the lateral and medial prefrontal regions, insula, lateral temporal regions, medial temporal structures, and thalamus as well as the negative loadings reflecting gray matter increase in the patients in the putamen and cerebellum. When the eigenimage derived from the original cohort was applied to classify data from the second cohort, it correctly assigned more than 80% of the healthy subjects and schizophrenia patients. These findings suggest that the characteristic distribution of gray matter changes may be of diagnostic value for schizophrenia.

A primal sketch of the cortex mean curvature: a morphogenesis based approach to study the variability of the folding patterns

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.

Detection of fMRI activation using Cortical Surface Mapping

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. Hum. Brain Mapping 12:79–93, 2001.

Automatized clustering and functional geometry of human parietofrontal networks for language, space, and number

Human functional MRI studies frequently reveal the joint activation of parietal and of lateral and mesial frontal areas during various cognitive tasks. To analyze the geometrical organization of those networks, we used an automatized clustering algorithm that parcels out sets of areas based on their similar profile of task-related activations or deactivations. This algorithm allowed us to reanalyze published fMRI data (Simon, O., Mangin, J.F., Cohen, L., Le Bihan, D., Dehaene, S., 2002. Topographical layout of hand, eye, calculation, and language-related areas in the human parietal lobe. Neuron 33, 475-487) and to reproduce the previously observed geometrical organization of activations for saccades, attention, grasping, pointing, calculation, and language processing in the parietal lobe. Further, we show that this organization extends to lateral and mesial prefrontal regions. Relative to the parietal lobe, the prefrontal functional geometry is characterized by a partially symmetrical anteroposterior ordering of activations, a decreased representation of effector-specific tasks, and a greater emphasis on higher cognitive functions of attention, higher-order spatial representation, calculation, and language. Anatomically, our results in humans are closely homologous to the known connectivity of parietal and frontal regions in the macaque monkey.

Group analysis in functional neuroimaging: selecting subjects using similarity measures

Standard group analyses of fMRI data rely on spatial and temporal averaging of individuals. This averaging operation is only sensible when the mean is a good representation of the group. This is not the case if subjects are not homogeneous, and it is therefore a major concern in fMRI studies to assess this group homogeneity. We present a method that provides relevant distances or similarity measures between temporal series of brain functional images belonging to different subjects. The method allows a multivariate comparison between data sets of several subjects in the time or in the space domain. These analyses assess the global intersubject variability before averaging subjects and drawing conclusions across subjects, at the population level. We adapt the RV coefficient to measure meaningful spatial or temporal similarities and use multidimensional scaling to give a visual representation of each subjects position with respect to other subjects in the group. We also provide a measure for detecting subjects that may be outliers. Results show that the method is a powerful tool to detect subjects with specific temporal or spatial patterns, and that, despite the apparent loss of information, restricting the analysis to a homogeneous subgroup of subjects does not reduce the statistical sensitivity of standard group fMRI analyses.

The role of the left head of caudate in suppressing irrelevant words

Suppressing irrelevant words is essential to successful speech production and is expected to involve general control mechanisms that reduce interference from task-unrelated processing. To investigate the neural mechanisms that suppress visual word interference, we used fMRI and a Stroop task, using a block design with an event-related analysis. Participants indicated with a finger press whether a visual stimulus was colored pink or blue. The stimulus was either the written word “BLUE,” the written word “PINK,” or a string of four Xs, with word interference introduced when the meaning of the word and its color were “incongruent” (e.g., BLUE in pink hue) relative to congruent (e.g., BLUE in blue) or neutral (e.g., XXXX in pink). The participants also made color decisions in the presence of spatial interference rather than word interference (i.e., the Simon task). By blocking incongruent, congruent, and neutral trials, we identified activation related to the mechanisms that suppress interference as that which was greater at the end relative to the start of incongruency. This highlighted the role of the left head of caudate in the control of word interference but not spatial interference. The response in the left head of caudate contrasted to bilateral inferior frontal activation that was greater at the start than at the end of incongruency, and to the dorsal anterior cingulate gyrus which responded to a change in the motor response. Our study therefore provides novel insights into the role of the left head of caudate in the mechanisms that suppress word interference.

Explaining Function with Anatomy: Language Lateralization and Corpus Callosum Size

The anatomy of the corpus callosum (CC) has been advocated as a potential marker for functional lateralization because its size is supposedly proportional to the number of fibers connecting the hemispheres. Previous morphometric studies of this relationship have compared CC size in groups of subjects who are more or less likely to show differences in their lateralization (e.g., left vs right handers). The findings, however, have been inconsistent, and to our knowledge, no previous study has directly compared CC size with lateralization assessed by functional imaging data. We therefore combined anatomical measurements of CC size with left versus right hemisphere language activation in 74 normal subjects. After controlling for perceptual and motor output effects, as well as for global white-matter volume, handedness, gender and age, we found that subjects who had a larger CC showed more left lateralization for language in posterior temporal and inferior frontal regions. Examination of these effects revealed that, as CC size increased, stronger lateralization resulted from more left hemisphere activation in both regions as well as reduced right hemisphere activation in the posterior temporal region. Our observations provide the first clear evidence in normal subjects that the midsagittal surface area of the CC contributes to the degree to which language is functionally lateralized. We discuss the complex interhemispheric processes that might underlie this effect.

Imagery or meaning? Evidence for a semantic origin of category-specific brain activity in metabolic imaging.

Category‐specific brain activation distinguishing between semantic word types has imposed challenges on theories of semantic representations and processes. However, existing metabolic imaging data are still ambiguous about whether these category‐specific activations reflect processes involved in accessing the semantic representation of the stimuli, or secondary processes such as deliberate mental imagery. Further information about the response characteristics of category‐specific activation is still required. Our study for the first time investigated the differential impact of word frequency on functional magnetic resonance imaging (fMRI) responses to action‐related words and visually related words, respectively. First, we corroborated previous results showing that action‐relatedness modulates neural responses in action‐related areas, while word imageability modulates activation in object processing areas. Second, we provide novel results showing that activation negatively correlated with word frequency in the left fusiform gyrus was specific for visually related words, while in the left middle temporal gyrus word frequency effects emerged only for action‐related words. Following the dominant view in the literature that effects of word frequency mainly reflect access to lexico‐semantic information, we suggest that category‐specific brain activation reflects distributed neuronal ensembles, which ground language and concepts in perception‐action systems of the human brain. Our approach can be applied to any event‐related data using single‐stimulus presentation, and allows a detailed characterization of the functional role of category‐specific activation patterns.