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Grin and bear it! Neural consequences of a voluntary decision to act or inhibit action
Action inhibition is an important part of everyday human behaviour. Most previous studies of action inhibition have focussed on stop-signals. Here, we consider the case where participants themselves decide to inhibit, or not inhibit, a prepotent action. Participants received electric stimulation tha...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer-Verlag
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3483109/ https://www.ncbi.nlm.nih.gov/pubmed/23007721 http://dx.doi.org/10.1007/s00221-012-3263-9 |
Sumario: | Action inhibition is an important part of everyday human behaviour. Most previous studies of action inhibition have focussed on stop-signals. Here, we consider the case where participants themselves decide to inhibit, or not inhibit, a prepotent action. Participants received electric stimulation that elicited an itchy feeling on the wrist. If they made a hand withdrawal movement, this would interrupt the stimulation, and halt the itch. In a factorial design, participants were given external instructions to withdraw their hand when they felt the itch, or to inhibit the natural withdrawal response, and bear the itch. In another condition, they were asked to internally choose between withdrawal and inhibition of withdrawal. Event-related potentials revealed differences between processing of the sensory consequences of internally decided and externally–instructed action and inhibition decisions. Specifically, potentials evoked by itchy stimuli were enhanced in internally decided inhibition trials, as compared to externally instructed inhibition trials. In contrast, processing of itchy stimuli was reduced in internally decided action trials, as compared to externally instructed action trials. These results show that internal decisions lead to different perceptual processing of the consequences of action and inhibition and suggest that features of decision processes can be measured via their consequences. |
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