Presentation
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Spatio-temporal signatures of social verb processing in the human brain: An MEG study
Poster A26 in Poster Session A, Tuesday, October 24, 10:15 am - 12:00 pm CEST, Espace Vieux-Port
Lucia Amoruso1,2, Sebastian Moguilner3,4,5, Eduardo Castillo6, Tara Kleineschay6, Edinson Muñoz7, Manuel Carreiras1,2, Adolfo M. García3,5,7; 1Basque Center on Cognition, Brain and Language (BCBL), San Sebastian, Spain, 2Ikerbasque, Basque Foundation for Science, Bilbao, Spain, 3Cognitive Neuroscience Center (CNC), University of San Andres, Argentina, 4Trinity College Dublin (TCD), Dublin, Ireland, 5Global Brain Health Institute (GBHI), University of California San Francisco, United States, 6Magnetoencephalography Laboratory, Florida Hospital for Children, United States, 7Departamento de Lingüística y Literatura, Facultad de Humanidades, Universidad de Santiago de Chile, Santiago, Chile
Humans have a natural inclination to interact with one another and this is primarily done through language. Our advanced sociolinguistic abilities are thought to stem from our tendency to live in groups, with social verbs possibly playing a central role in shaping human experience. However, no study has yet examined the spatio-temporal dynamics underpinning the comprehension of verbs associated with social behavior, as opposed to those with low social relevance. To address this gap, we recorded MEG activity while participants engaged in a lexical decision task. During this task, participants were presented with social verbs (e.g., “educating”), non-social verbs (e.g., “typing”), and pseudoverbs (e.g., “lyming”), preceded by a grammatical context (“I am”), and instructed to determine whether the target item was a real word or not. All verbs were carefully matched based on critical linguistic variables, including concreteness, frequency, familiarity, AoA, and sensorimotor properties, among others. We performed a time-frequency analysis and compared social vs. non-social verbs in canonical frequency bands associated to linguistic and socio-cognitive processing (i.e., theta [~6 Hz], alpha [~10 Hz], and beta [~20 Hz]) using a cluster-based permutation approach. The brain generators of the sensor-level effects were further estimated using beamformer techniques. Finally, we performed a machine learning decoding analysis to determine the time span at which social and non-social verbs were maximally decoded on a trial-by-trial basis. Our results revealed that social verbs elicited stronger power decreases in the beta band (~20 Hz) compared to non-social verbs in right fronto-temporal sensors. Source localization analysis identified the involvement of the anterior temporal lobe, superior parietal, prefrontal, and motor/premotor cortices in the right hemisphere. Moreover, the decoding analysis demonstrated that trial-by-trial classification between the two conditions emerged between ~450-580ms with an accuracy of ~75%. Our findings suggest that the socialness of human behavior represents a unique dimension of conceptual knowledge, as evidenced by rightward modulations in beta oscillations during a time window associated to semantic processing. These results align with previous studies linking beta to action semantics and highlighting a key role of the right hemisphere in social cognition. Our study provides additional evidence supporting their involvement in processing the meaning of social verbs, offering new insights into the neurocognitive signatures of socialness in the human brain.
Topic Areas: Meaning: Lexical Semantics,