ArticleNeuroImage. Clinical2019
Electrophysiological correlates of feedback processing in subarachnoid hemorrhage patients.
Article in NeuroImage. Clinical, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Reward-based decision-making in mesial temporal lobe epilepsy patients with unilateral hippocampal sclerosis pre- and post-surgery.NeuroImage. Clinical · 2022Article
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6 authors.
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Abstract
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.
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