Publications

Abstract

A class of semantic theories defines concepts in terms of statistical distributions of lexical items, basing meaning on vectors of word co-occurrence frequencies. A different approach emphasizes abstract hierarchical taxonomic relationships among concepts. However, the functional relevance of these different accounts and how they capture information-encoding of meaning in the brain still remains elusive.

We investigated to what extent distributional and taxonomic models explained word-elicited neural responses using cross-validated representational similarity analysis (RSA) of functional magnetic resonance imaging (fMRI) and novel model comparisons.

Our findings show that the brain encodes both types of semantic similarities, but in distinct cortical regions. Posterior middle temporal regions reflected word links based on hierarchical taxonomies, along with the action-relatedness of the semantic word categories. In contrast, distributional semantics best predicted the representational patterns in left inferior frontal gyrus (LIFG, BA 47). Both representations coexisted in angular gyrus supporting semantic binding and integration. These results reveal that neuronal networks with distinct cortical distributions across higher-order association cortex encode different representational properties of word meanings. Taxonomy may shape long-term lexical-semantic representations in memory consistently with sensorimotor details of semantic categories, whilst distributional knowledge in the LIFG (BA 47) enable semantic combinatorics in the context of language use.

Our approach helps to elucidate the nature of semantic representations essential for understanding human language.

Abstract

Language comprehension engages a distributed network of frontotemporal, parietal, and sensorimotor regions, but it is still unclear how meaning of words and their semantic relationships are represented and processed within these regions and to which degrees lexico-semantic representations differ between regions and semantic types. We used fMRI and representational similarity analysis to relate word-elicited multivoxel patterns to semantic similarity between action and object words. In left inferior frontal (BA 44-45-47), left posterior middle temporal and left precentral cortex, the similarity of brain response patterns reflected semantic similarity among action-related verbs, as well as across lexical classes-between action verbs and tool-related nouns and, to a degree, between action verbs and food nouns, but not between action verbs and animal nouns. Instead, posterior inferior temporal cortex exhibited a reverse response pattern, which reflected the semantic similarity among object-related nouns, but not action-related words. These results show that semantic similarity is encoded by a range of cortical areas, including multimodal association (e.g., anterior inferior frontal, posterior middle temporal) and modality-preferential (premotor) cortex and that the representational geometries in these regions are partly dependent on semantic type, with semantic similarity among action-related words crossing lexical-semantic category boundaries.

Abstract

Real-time estimation of what we will do next is a crucial prerequisite
of purposive behavior. During the planning of goal-oriented actions, for
instance, the temporal and causal organization of upcoming subsequent
moves needs to be predicted based on our knowledge of events. A forward
computation of sequential structure is also essential for planning
contiguous discourse segments and syntactic patterns in language. The
neural encoding of sequential event knowledge and its domain dependency
is a central issue in cognitive neuroscience. Converging evidence shows
the involvement of a dedicated neural substrate, including the
prefrontal cortex and Broca's area, in the representation and the
processing of sequential event structure. After reviewing major
representational models of sequential mechanisms in action and language,
we discuss relevant neuropsychological and neuroimaging findings on the
temporal organization of sequencing and sequence processing in both
domains, suggesting that sequential event knowledge may be modularly
organized through prefrontal and frontal subregions.