S4.5 The sensorimotor grounding of language and speech

Abstract

Lateral inhibition and neuronal adaptation, the main candidate mechanisms previously proposed to underlie the generation of the mismatch negativity (MMN) response as elicited in passive oddball experiments, fail to explain why the MMN is larger for familiar stimuli (e.g., words) than for unfamiliar ones (e.g., pseudowords). We aimed to identify a set of neuronal mechanisms that could explain the above result. Taking language as our working domain, we built a neural-network model of the language-related brain areas, simulating lateral inhibition, neuronal adaptation and long-term synaptic plasticity (learning) cortical mechanisms. After “teaching” the network a set of artificial words, we stimulated its “auditory” cortex with words and pseudowords in an oddball manner, while systematically varying strength of adaptation, lateral and global inhibition (the model correlate of attention). Using magneto-encephalography (MEG) we then recorded neurophysiological responses to words and pseudowords when subjects were asked to attend to the spoken input or ignore it. Models including adaptation and/or lateral inhibition successfully generated MMN responses; however, adaptation-only networks failed to replicate the larger MMN response to words than to pseudowords. Both simulated and recorded brain responses were significantly larger to pseudowords than to words when attention was directed to the input material, while the opposite pattern emerged in the “ignore” condition. Adaptation and lateral inhibition alone cannot explain the larger brain responses to familiar patterns compared to unfamiliar ones observed in passive oddball tasks, a result that our account can explain in terms of re-activation of memory traces that emerged in the cortex by means of learning. Our MEG results confirm the model’s prediction that the former (words pseudowords) and the opposite (pseudowords words) pattern of results can be produced by the modulation of a single cognitive resource: attention.