Hauptman, M. | bioRxiv Science

bioRxiv2023

Neural specialization for 'visual' concepts emerges in the absence of vision

Vision provides a key source of information about many concepts, including living things (e.g., tiger) and visual events (e.g., sparkle). According to a prominent theoretical framework, neural specialization for different conceptual categories is shaped by sensory features, e.g., living things are neurally dissociable from navigable places because living things concepts depend more on visual features. We tested this framework by comparing the neural basis of visual concepts across sighted (n=22) and congenitally blind (n=21) adults. Participants judged the similarity of words varying in their reliance on vision while undergoing fMRI. We compared neural responses to living things nouns (birds, mammals) and place nouns (natural, manmade). In addition, we compared visual event verbs (e.g., sparkle) to non-visual events (sound emission, hand motion, mouth motion). People born blind exhibited distinctive univariate and multivariate responses to living things in a temporo-parietal semantic network activated by nouns, including the precuneus (PC). To our knowledge, this is the first demonstration that neural selectivity for living things does not require vision. We additionally observed preserved neural signatures of visual light events in the left middle temporal gyrus (LMTG+). Across a wide range of semantic types, neural representations of sensory concepts develop independent of sensory experience. Significance StatementVision offers a key source of information about major conceptual categories, including animals and light emission events. Comparing neural signatures of concepts in congenitally blind and sighted people tests the contribution of visual experience to conceptual representation. Sighted and congenitally blind participants heard visual nouns (e.g., tiger) and verbs (e.g., sparkle), as well as less visual nouns (e.g., barn) and verbs (e.g., squeak) while undergoing fMRI. Contrary to previous claims, both univariate and multivariate approaches reveal similar representations of animals and light emission verbs across groups. Across a broad range of semantic types, visual concepts develop independent of visual experience. These results challenge theories that emphasize the role of sensory information in conceptual representation.

neuroscience↗

bioRxiv2022

Non-literal language processing is jointly supported by the language and Theory of Mind networks: Evidence from a novel meta-analytic fMRI approach

Going beyond the literal meaning of utterances is key to communicative success. However, the mechanisms that support non-literal inferences remain debated. Using a novel meta-analytic approach, we evaluate the contribution of linguistic, social-cognitive, and executive mechanisms to non-literal interpretation. We identified 74 fMRI experiments (n=1,430 participants) from 2001-2021 that contrasted non-literal language comprehension with a literal control condition, spanning ten phenomena (e.g., metaphor, irony, indirect speech). Applying the activation likelihood estimation approach to the 825 activation peaks yielded six left-lateralized clusters. We then evaluated the locations of both the individual-study peaks and the clusters against probabilistic functional atlases (cf. macroanatomy, as is typically done) for three candidate brain networks--the language-selective network (Fedorenko et al., 2011), which supports language processing, the Theory of Mind (ToM) network (Saxe & Kanwisher, 2003), which supports social inferences, and the domain-general Multiple-Demand (MD) network (Duncan, 2010), which supports executive control. These atlases were created by overlaying individual activation maps of participants who performed robust and extensively validated localizer tasks that target each network in question (n=806 for language; n=198 for ToM; n=691 for MD). We found that both the individual-study peaks and the ALE clusters fell primarily within the language network and the ToM network. These results suggest that non-literal processing is supported by both i) mechanisms that process literal linguistic meaning, and ii) mechanisms that support general social inference. They thus undermine a strong divide between literal and non-literal aspects of language and challenge the claim that non-literal processing requires additional executive resources.

neuroscience↗