Fractionating the anterior temporal lobe : MVPA reveals differential responses to input and conceptual modality

Words activate cortical regions in accordance with their modality of presentation (i.e., written vs. spoken), yet there is a long-standing debate about whether patterns of activity in any specific brain region capture modality-invariant conceptual information. Deficits in patients with semantic dementia highlight the anterior temporal lobe (ATL) as an amodal store of semantic knowledge but these studies do not permit precise localisation of this function. The current investigation used multiple imaging methods in healthy participants to examine functional dissociations within ATL. Multi-voxel pattern analysis identified spatially segregated regions: a response to input modality in anterior superior temporal gyrus (aSTG) and a response to meaning in more ventral anterior temporal lobe (vATL). This functional dissociation was supported by resting-state connectivity that found greater coupling for aSTG with primary auditory cortex and vATL with the default mode network. A meta-analytic decoding of these connectivity patterns implicated aSTG in processes closely tied to auditory processing (such as phonology and language) and vATL in meaning-based tasks (such as comprehension or social cognition). Thus we provide converging evidence for the segregation of meaning and input modality in the ATL

Social Distance Evaluation in Human Parietal Cortex

Across cultures, social relationships are often thought of, described, and acted out in terms of physical space (e.g. “close friends” “high lord”). Does this cognitive mapping of social concepts arise from shared brain resources for processing social and physical relationships? Using fMRI, we found that the tasks of evaluating social compatibility and of evaluating physical distances engage a common brain substrate in the parietal cortex. The present study shows the possibility of an analytic brain mechanism to process and represent complex networks of social relationships. Given parietal cortex's known role in constructing egocentric maps of physical space, our present findings may help to explain the linguistic, psychological and behavioural links between social and physical space

Brain-mediated Transfer Learning of Convolutional Neural Networks

The human brain can effectively learn a new task from a small number of samples, which indicate that the brain can transfer its prior knowledge to solve tasks in different domains. This function is analogous to transfer learning (TL) in the field of machine learning. TL uses a well-trained feature space in a specific task domain to improve performance in new tasks with insufficient training data. TL with rich feature representations, such as features of convolutional neural networks (CNNs), shows high generalization ability across different task domains. However, such TL is still insufficient in making machine learning attain generalization ability comparable to that of the human brain. To examine if the internal representation of the brain could be used to achieve more efficient TL, we introduce a method for TL mediated by human brains. Our method transforms feature representations of audiovisual inputs in CNNs into those in activation patterns of individual brains via their association learned ahead using measured brain responses. Then, to estimate labels reflecting human cognition and behavior induced by the audiovisual inputs, the transformed representations are used for TL. We demonstrate that our brain-mediated TL (BTL) shows higher performance in the label estimation than the standard TL. In addition, we illustrate that the estimations mediated by different brains vary from brain to brain, and the variability reflects the individual variability in perception. Thus, our BTL provides a framework to improve the generalization ability of machine-learning feature representations and enable machine learning to estimate human-like cognition and behavior, including individual variability

Influences génétiques et environnementales sur la variabilité et l’unicité des activations cérébrales chez l’humain : un devis familial de jumeaux sur la base de données d’imagerie cérébrale du Human Connectome Project

Le comportement humain est à la fois singulier et universel. La singularité serait principalement due aux trajectoires de vie propre à chaque individu (variant entre autres selon leur culture) alors que l’universalité émanerait d’une nature universelle ancrée dans un génome universel. Démêler les influences de la nature et de la culture sur le comportement humain est le Saint Graal de l’anthropologie biologique. J’aborde cette question en explorant les effets génétiques et environnementaux sur les bases psychiques du comportement. Plus particulièrement, je teste l’hypothèse que la singularité et l’universalité comportementales humaines s’observent au plan psychique par l’exploration de leur substrat neurobiologique, et que ce substrat possède à la fois un ancrage génétique et environnemental. À l’aide de données d’imagerie par résonance magnétique fonctionnelle (IRMf) recueillies auprès de 862 participants du Human Connectome Project (HCP), j’analyse les activations cérébrales liées à sept tâches socio-cognitives qui recoupent diverses facultés, dont le langage, la mémoire, la prise de risque, la logique, les émotions, la motricité et le raisonnement social. Après avoir groupé les sujets selon la similarité de leurs patrons d’activation cérébrale (c.-à-d. leurs sous-types neurobiologiques), j’estime l’influence génétique et environnementale sur la variabilité interindividuelle de ces divers sous-types. Les résultats démontrent bel et bien l’existence d’un regroupement des sujets selon la similarité de leurs cartes d’activation cérébrale lors d’une même tâche socio-cognitive, ce qui reflète à la fois le caractère singulier et universel des corrélats neuronaux d’un comportement observable. La variabilité interindividuelle constatée dans ces regroupements cérébraux témoigne quant à elle d’effets génétiques (héritabilité) ainsi qu’environnementaux (environnementalité), dont les ampleurs respectives varient selon la nature de la tâche effectuée. De plus, les sous-types cérébraux mis à jour révèlent une association avec les mesures comportementales et de performance effectuées lors des diverses tâches à l’étude. Enfin, les sous-types neurobiologiques résultant des diverses tâches partagent certaines bases génétiques. Dans leur ensemble, ces résultats appuient la notion que le comportement humain, ainsi que les processus neurobiologiques le sous-tendant, sont des phénotypes au même titre qu’un caractère morphologique ou physiologique, c’est-à-dire qu’ils sont le résultat de l’expression conjointe de bases génétiques (nature) et environnementales (culture).Human behaviour is both singular and universal. Singularity is believed to be mainly due to life trajectories unique to each individual (influenced among others by culture), whereas universality would stem from a universal nature resulting from a panhuman genome. Unravelling the influences of nature and nurture on human behaviour is the Holy Grail of biological anthropology. I approach this issue by exploring genetic and environmental influences on the neuropsychological underpinnings of behaviour. In particular, I test the hypothesis that the singularity and universality of human behaviour are also observed at the psychological level through the exploration of the neurobiological basis of behaviour, and that these bases have both genetic and environmental sources. Using Functional Magnetic Resonance Imaging (fMRI) data of 862 participants from the Human Connectome Project (HCP), I analyze brain activation related to 7 socio-cognitive tasks covering language, memory, risk taking, logic, emotions, motor skills, and social reasoning. After grouping subjects according to the similarity of their brain activation patterns (neurobiological subtypes), I estimate the genetic and environmental influences on the variation between participants on these subtypes. The inter-individual variability in cerebral groupings appears to have both genetic (heritability) and environmental (environmentality) sources that vary according to the particular psychological task involved. Moreover, these neurobiological subtypes show an association with behavioural and performance measures assessed by the socio-cognitive tasks. Finally, the neurobiological subtypes across the 7 tasks share common genetic links. Overall, the results support the notion that human behaviour, as well as its underlying neurobiological processes, are phenotypes in the same way as morphology or physiology, i.e., are the results of the integrated expression of a genetic basis (nature) and environmental influences (nurture)

Neural correlates of generation and inhibition of verbal association patterns in mood disorders

Objectives: Thought disorders such as rumination or flight of ideas are frequent in patients with mood disorders, and not systematically linked to mood state. These symptoms point to anomalies in cognitive processes mediating the generation and control of thoughts; for example, associative thinking and inhibition. However, their neural substrates are not known. Method: To obtain an ecological measure of neural processes underlying the generation and suppression of spontaneous thoughts, we designed a free word association task during fMRI allowing us to explore verbal associative patterns in patients with mood disorders and matched controls. Participants were presented with emotionally negative, positive or neutral words, and asked to produce two words either related or unrelated to these stimuli. Results: Relative to controls, patients produced a reverse pattern of answer typicality for the related vs unrelated conditions. Controls activated larger semantic and executive control networks, as well as basal ganglia, precuneus and middle frontal gyrus. Unlike controls, patients activated fusiform gyrus, parahippocampal gyrus and medial prefrontal cortex for emotional stimuli. Conclusions: Mood disorder patients are impaired in automated associative processes, but prone to produce more unique/personal associations through activation of memory and self-related area

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

Markov models for fMRI correlation structure: is brain functional connectivity small world, or decomposable into networks?

Correlations in the signal observed via functional Magnetic Resonance Imaging (fMRI), are expected to reveal the interactions in the underlying neural populations through hemodynamic response. In particular, they highlight distributed set of mutually correlated regions that correspond to brain networks related to different cognitive functions. Yet graph-theoretical studies of neural connections give a different picture: that of a highly integrated system with small-world properties: local clustering but with short pathways across the complete structure. We examine the conditional independence properties of the fMRI signal, i.e. its Markov structure, to find realistic assumptions on the connectivity structure that are required to explain the observed functional connectivity. In particular we seek a decomposition of the Markov structure into segregated functional networks using decomposable graphs: a set of strongly-connected and partially overlapping cliques. We introduce a new method to efficiently extract such cliques on a large, strongly-connected graph. We compare methods learning different graph structures from functional connectivity by testing the goodness of fit of the model they learn on new data. We find that summarizing the structure as strongly-connected networks can give a good description only for very large and overlapping networks. These results highlight that Markov models are good tools to identify the structure of brain connectivity from fMRI signals, but for this purpose they must reflect the small-world properties of the underlying neural systems

A Role for the Motor System in Binding Abstract Emotional Meaning

Sensorimotor areas activate to action- and object-related words, but their role in abstract meaning processing is still debated. Abstract emotion words denoting body internal states are a critical test case because they lack referential links to objects. If actions expressing emotion are crucial for learning correspondences between word forms and emotions, emotion word–evoked activity should emerge in motor brain systems controlling the face and arms, which typically express emotions. To test this hypothesis, we recruited 18 native speakers and used event-related functional magnetic resonance imaging to compare brain activation evoked by abstract emotion words to that by face- and arm-related action words. In addition to limbic regions, emotion words indeed sparked precentral cortex, including body-part–specific areas activated somatotopically by face words or arm words. Control items, including hash mark strings and animal words, failed to activate precentral areas. We conclude that, similar to their role in action word processing, activation of frontocentral motor systems in the dorsal stream reflects the semantic binding of sign and meaning of abstract words denoting emotions and possibly other body internal states

Identification of Proper and Common Names in the Anterior Temporal Lobe: An FMRI Study

Temporal lobe epilepsy is a neurological disease that affects millions of individuals worldwide. They are usually treated through surgical resection of portions of the anterior temporal lobe (ATL). Surgical resection is effective for seizure control, but produces language and verbal memory deficits such as anomic aphasia, which adversely affects an individual\u27s quality of life. The purpose of this study was to develop a functional MRI protocol for mapping the function of ATL in healthy subjects, and to better understand the role of the ATL and other regions of the semantic system. Such a protocol may ultimately be used by surgeons to predict and reduce or prevent side effects of cognitive decline that occur after ATL resection in epilepsy patients. The aims were: (1) To study the ATL response to associations with abstract and concrete concepts and (2) To study the ATL response to names of people and places, and the information associated with these names. Our results indicated that ATL and inferior parietal areas are modulated by the amount of information associated with proper names. ATL is activated for abstract and concrete words relative to nonwords but is not modulated by associative measures. Angular and posterior cingulate gyri, on the other hand, are modulated by information associated with both common and proper names, underlining their role in semantic representations. A very high degree of overlap between person- and word-specific networks suggests that a common semantic system underlies both types of knowledge, rather than segregation of social and non-social knowledge. These results also demonstrate robust activation of ATL by proper and common names, and point to their potential use in mapping eloquent and functionally relevant cortex in epilepsy patients