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A systems neurophysiology approach to voluntary event coding
Mechanisms responsible for the integration of perceptual events and appropriate actions (sensorimotor processes) have been subject to intense research. Different theoretical frameworks have been put forward with the “Theory of Event Coding (TEC)” being one of the most influential. In the current stu...
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Published in: | NeuroImage (Orlando, Fla.) Fla.), 2016-07, Vol.135, p.324-332 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Mechanisms responsible for the integration of perceptual events and appropriate actions (sensorimotor processes) have been subject to intense research. Different theoretical frameworks have been put forward with the “Theory of Event Coding (TEC)” being one of the most influential. In the current study, we focus on the concept of ‘event files’ within TEC and examine what sub-processes being dissociable by means of cognitive-neurophysiological methods are involved in voluntary event coding. This was combined with EEG source localization. We also introduce reward manipulations to delineate the neurophysiological sub-processes most relevant for performance variations during event coding. The results show that processes involved in voluntary event coding included predominantly stimulus categorization, feature unbinding and response selection, which were reflected by distinct neurophysiological processes (the P1, N2 and P3 ERPs). On a system's neurophysiological level, voluntary event-file coding is thus related to widely distributed parietal-medial frontal networks. Attentional selection processes (N1 ERP) turned out to be less important. Reward modulated stimulus categorization in parietal regions likely reflecting aspects of perceptual decision making but not in other processes. The perceptual categorization stage appears central for voluntary event-file coding. |
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ISSN: | 1053-8119 1095-9572 |
DOI: | 10.1016/j.neuroimage.2016.05.007 |