Event Abstract

Explaining Attention and Language interactions: magnetic MMN validation of neurocomputational predictions

  • 1 Medical Research Council and Cognition and Brain Sciences Unit, United Kingdom

Recent simulations obtained with a neurobiologically realistic neural network model of the left perisylvian language cortex suggest that words are represented in the human brain as strongly connected circuits that are both distributed and functionally discrete (Garagnani et al., 2008). Such a model replicates, explains and reconciles existing divergent patterns of neurophysiological data (N400 and mismatch negativity), and makes precise, testable predictions about the brain responses to words and pseudowords under variable amounts of attentional load. In particular, due to their strong internal connections, the action-perception circuits for words that spontaneously emerged in the network exhibited functionally discrete activation dynamics, which were only marginally affected by changes in availability of processing resources. Thus, the model predicts relative stability of brain responses to familiar words as a function of attention, but strong attention dependence of neurophysiological responses to unfamiliar items - pseudowords - that had not been previously learned (and, therefore, lacked corresponding memory representations). This dependence can be explained by the different amounts of attentional/processing resources available and, therefore, different degrees of competition between multiple memory circuits partially activated by items lacking lexical traces. We tested these predictions in a novel magneto-encephalography (MEG) experiment and presented subjects with familiar words and matched unfamiliar pseudowords during an attention demanding task (Attend) and under distraction (Ignore). The magnetic mismatch negativity (MMN) response to words showed relative immunity to changes in attention levels, whereas the MMN to pseudowords exhibited profound variability: the amplitude was enhanced above that to words in the Attend condition, and reduced below it in the Ignore condition. These results confirm the model’s predictions and provide evidence in support of the hypothesis that words are represented in the brain as functionally discrete and distributed action-perception circuits.

Conference: MMN 09 Fifth Conference on Mismatch Negativity (MMN) and its Clinical and Scientific Applications, Budapest, Hungary, 4 Apr - 7 Apr, 2009.

Presentation Type: Poster Presentation

Topic: Poster Presentations

Citation: Garagnani M, Shtyrov Y and Pulvermüller F (2009). Explaining Attention and Language interactions: magnetic MMN validation of neurocomputational predictions. Conference Abstract: MMN 09 Fifth Conference on Mismatch Negativity (MMN) and its Clinical and Scientific Applications. doi: 10.3389/conf.neuro.09.2009.05.133

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Received: 26 Mar 2009; Published Online: 26 Mar 2009.

* Correspondence: Max Garagnani, Medical Research Council and Cognition and Brain Sciences Unit, Cambridge, United Kingdom, challet@inci-cnrs.unistra.fr

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