Literature DB >> 11707094

Subprocesses of performance monitoring: a dissociation of error processing and response competition revealed by event-related fMRI and ERPs.

M Ullsperger1, D Y von Cramon.   

Abstract

Performance monitoring can be implemented in the brain by two possible systems, one monitoring for response competition or one detecting errors. Two current models of performance monitoring have different views on these monitoring subsystems. While the error detection model proposes a specific error detection system, the response competition model denies the necessity of a specific error detector and favors a more general unitary system evaluating response conflict. Both models suggest that the frontomedian wall in the vicinity of the anterior cingulate sulcus plays an important role in performance monitoring. The present study investigates the hemodynamic and electrophysiological correlates of response competition and error processing. Twelve young healthy participants performed a speeded, modified flanker task, while fMRI signals and ERPs were measured in separate sessions. The event-related fMRI shows that networks involving the frontomedian wall are activated during both response competition and error processing. However, an anatomical dissociation was found: while error processing preferentially activates the human homologue of the cingulate motor area (CMA, BA 24c') in the depth of the anterior cingulate sulcus, response competition is accompanied by activation of the pre-SMA and mesial BA 8. The ERP waveforms for erroneous trials exhibit a large error-related negativity, which is most likely generated in the CMA. These results suggest that the CMA plays a major role in error processing. Further fMRI activations in the lateral prefrontal and primary motor cortex are discussed with respect to performance monitoring and its influence on task set reconfiguration. Copyright 2001 Academic Press.

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Mesh:

Year:  2001        PMID: 11707094     DOI: 10.1006/nimg.2001.0935

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


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