Abstract
Selective attention focuses cortical processing resources on relevant information in order to allow for adaptive behavior despite the potential overload of sensory information. This process involves a fundamental tradeoff: a lower magnitude of attentional selectivity leads to impaired task performance due to interference from irrelevant information, but stronger attentional selectivity impairs the ability to detect and react to unexpected (and potentially dangerous) events. A possible explanation of how the magnitude of attentional selectivity is determined is offered by theories of performance monitoring, which assume that detecting errors leads to adaptive attentional adjustments that serve to prevent such errors in the future. However, although numerous studies have identified stages of error processing in error-related brain activity, it is still unclear how these stages are related to adaptive attentional adjustments. We investigated the time course of attentional adjustments elicited by errors. Participants attended to one of two superimposed red and blue random-dot kinematograms (RDKs) in order to discriminate the direction (horizontal vs. vertical) of brief motion intervals of the target RDK, while ignoring concurrent compatible or incompatible motions of the distractor RDK. The RDKs flickered at different frequencies, thereby eliciting distinguishable steady-state visual evoked potentials (SSVEPs), allowing us to concurrently measure the time-course of attentional allocation to both RDKs. Attentional selectivity of SSVEPs was increased almost synchronously with the error response and prior to conscious error detection. The magnitude of these attentional readjustments was large compared to the overall magnitude of attentional selectivity and linked to the earliest stage of error processing. Our findings suggest that error-induced attentional adjustments are a key determinant of the magnitude of attentional selectivity and start prior to conscious error detection.
Meeting abstract presented at VSS 2017