Electrophysiological correlates of feedback processing in subarachnoid hemorrhage patients

Patients with subarachnoid hemorrhage (SAH) secondary to anterior communicating artery (AComA) aneurysm rupture often experience deficits in executive functioning and decision-making. Effective decision-making is based on the subjects' ability to adjust their performance based on feedback proce...

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Detalhes bibliográficos
Autores: Gómez Andrés, Alba, Suades, Anna, Cucurell, David, Miquel, Maria Angels de, Juncadella i Puig, Montserrat, Rodríguez Fornells, Antoni
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2019
País:España
Recursos:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:2445/171631
Acesso em linha:https://hdl.handle.net/2445/171631
Access Level:acceso abierto
Palavra-chave:Aneurismes
Hemorràgia
Aneurysms
Hemorrhage
Descrição
Resumo:Patients with subarachnoid hemorrhage (SAH) secondary to anterior communicating artery (AComA) aneurysm rupture often experience deficits in executive functioning and decision-making. Effective decision-making is based on the subjects' ability to adjust their performance based on feedback processing, ascribing either positive or negative value to the actions performed reinforcing the most adaptive behavior in an appropriate temporal framework. A crucial brain structure associated to feedback processing is the medial prefrontal cortex (mPFC), a brain region frequently damaged after AComA aneurysm rupture. In the present study, we recorded electrophysiological responses (event-related potentials (ERPs') and oscillatory activity (time frequency analysis) during a gambling task in a series of 15 SAH patients. Previous studies have identified a feedback related negativity (FRN) component associated with an increase on frontal medial theta power in response to negative feedback or monetary losses, which is thought to reflect the degree of negative prediction error. Our findings show a decreased FRN component in response to negative feedback and a delayed increase of theta oscillatory activity in the SAH patient group when compared to the healthy controls, indicating a reduced sensitivity to negative feedback processing and an effortful signaling of cognitive control and monitoring processes lengthened in time, respectively. These results provide us with novel neurophysiological markers regarding feedback processing and performance monitoring patterns in SAH patients, illustrating a dysfunctional reinforcement learning system probably contributing to the maladaptive day-to-day functioning in these patients.