Journal of Cognitive NeuroscienceNeurosciencePeer-reviewed journal article
Linking the brain with behaviour: the neural dynamics of success and failure in goal-directed behaviour
Abstract
The human brain is extremely flexible and capable of rapidly selecting relevant information in accordance with task goals. Regions of frontoparietal cortex flexibly represent relevant task information such as task rules and stimulus features when participants perform tasks successfully, but less is known about how information processing breaks down when participants make mistakes. This is important for understanding whether and when information coding recorded with neuroimaging is directly meaningful for behaviour. Here, we used magnetoencephalography (MEG) to assess the temporal dynamics of information processing, and linked neural responses with goal-directed behaviour by analysing how they changed on behavioural error. Participants performed a difficult stimulus-response task using two stimulus-response mapping rules. We used time-resolved multivariate pattern analysis to characterise the progression of information coding from perceptual information about the stimulus, cue and rule coding, and finally, motor response. Response-aligned analyses revealed a ramping up of perceptual information prior to a correct response, suggestive of internal evidence accumulation. Strikingly, when participants made a stimulus-related error, and not when they made other types of errors, patterns of activity initially reflected the stimulus presented, but later reversed, and accumulated towards a representation of the incorrect stimulus. This suggests that the patterns recorded at later timepoints reflect an internally generated stimulus representation that was used to make the (incorrect) decision. These results illustrate the orderly and overlapping temporal dynamics of information coding in perceptual decision-making and show a clear link between neural patterns in the late stages of processing and behaviour.
- organism: human
- assay: electronic health records
- research focus: cell type annotation
- approach: statistical model
- Citations
- 13
- FWCI
- 1.55
- Field percentile
- top 20%
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