Decoding the information structure underlying the neural representation of concepts

Abstract

The nature of the representational code underlying conceptual knowledge remains a major unsolved problem in cognitive neuroscience. We assessed the extent to which different representational systems contribute to the instantiation of lexical concepts in high-level, heteromodal cortical areas previously associated with semantic cognition. We found that lexical semantic information can be reliably decoded from a wide range of heteromodal cortical areas in the frontal, parietal, and temporal cortex. In most of these areas, we found a striking advantage for experience-based representational structures (i.e., encoding information about sensory-motor, affective, and other features of phenomenal experience), with little evidence for independent taxonomic or distributional organization. These results were found independently for object and event concepts. Our findings indicate that concept representations in the heteromodal cortex are based, at least in part, on experiential information. They also reveal that, in most heteromodal areas, event concepts have more heterogeneous representations (i.e., they are more easily decodable) than object concepts and that other areas beyond the traditional “semantic hubs” contribute to semantic cognition, particularly the posterior cingulate gyrus and the precuneus.

A Distributed Network for Multimodal Experiential Representation of Concepts

“…These areas closely correspond to those identified in a neuroimaging meta-analysis of semantic word processing (Binder et al, 2009). This idea is further supported by neuroimaging findings suggesting that the precuneus, posterior cingulate gyrus, angular gyrus, dorsomedial and ventrolateral prefrontal cortex, and lateral temporal areas encode multimodal information about the sensory-motor content of concepts (Bonner et al, 2013;Fernandino et al, 2016aFernandino et al, , 2016bFernandino et al, , 2022Murphy et al, 2018).…”

Decoding face recognition abilities in the human brain

“…To our knowledge, none have explored the link between semantic brain representations and high-level recognition processes. Yet, recent studies using computational techniques have shown that semantic processes account for an important part of the representations in brain areas of both the perceptual and memory stream 18,[70][71][72] . Here, we expanded our understanding of the nature of brain representations supporting real-world recognition ability.…”

“…Finally, we found that face recognition ability is also associated with semantic computations that extend beyond basic-level visual categorisation in a late time-window around the P600 component (Eimer et al, 2012; Shen et al, 2016; van Herten et al, 2005). Recent studies using computational techniques have shown that word representations derived from models of natural language processing explain significant variance in the visual ventral stream (Dwivedi et al, 2021; Fernandino et al, 2022; Popham et al, 2021). The current study goes beyond this recent work in two ways.…”

Unraveling the functional attributes of the language connectome: crucial subnetworks, flexibility and variability

“…Semantic grounding, i.e., the semantic links between words and their actions, referent objects and related concepts, appears to depend on semantic circuits that bring together both the circuits related to word form (perisylvian, Net1) and conceptual circuits that underlie, among other aspects, sensory-motor experience (extrasylvian, including Net4). The involvement of the motor system in speech perception and understanding has been observed in various contexts (Fernandino et al 2022;Schomers et Pulvermüller 2016;Skipper, Devlin, et Lametti 2017 andsee Pulvermüller 2018 for the hypothesis of neural reuse of action perception circuits in language), which may explain why Net4 is globally engaged regardless of the subprocess involved in the language tasks (Figure 4A). Finally, several neurotransmitters are involved in the regulation of the activity of sensorimotor regions.…”