NeuroImage (Apr 2020)

Using temporal EEG signal decomposition to identify specific neurophysiological correlates of distractor-response bindings proposed by the theory of event coding

  • Antje Opitz,
  • Christian Beste,
  • Ann-Kathrin Stock

Journal volume & issue
Vol. 209
p. 116524

Abstract

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The ability to cope with distracting information is a major requirement for goal-directed behavior. It is particularly challenged when distracting information is either potentially relevant or temporally close to goal-directed responses, resulting in so-called distractor-response bindings. According to the theory of event coding (TEC), distractor-response bindings should be reflected by processes in the event file, but not in object file (which stores stimulus features) or the action file (which stores response features). But even though the predictions of this theory are quite elaborated, their electrophysiological underpinnings and the associated functional neuroanatomical structures have remained largely elusive. To examine this, we used a distractor-response binding paradigm in combination with temporal EEG signal decomposition (RIDE) and source localization techniques. We showed that distractor-response binding effects are exclusively evident in the N450 time window of the central C-cluster. Source reconstructions revealed that distractor-response binding effects were associated with brain regions involved in updating internal representations by using task-relevant information to decide on response execution (temporo-parietal junction, BA40), alongside with brain regions involved in conflict resolution processes (right middle frontal gyrus, BA8). Our results suggest that RIDE can be used to dissociate binding processes from stimulus- and response-related processes. On top of this, the results of EEG decomposition match the key assumption of the TEC, that distractor-response bindings occur in event files, but not in object files or action files. The results show how cognitive-theoretical frameworks, such as the TEC, can directly be mapped onto the underlying neurophysiological processes using EEG signal decomposition.

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