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An Exploratory Study of Large-Scale Brain Networks during Gambling Using SEEG.
Taylor, Christopher; Breault, Macauley Smith; Dorman, Daniel; Greene, Patrick; Sacré, Pierre; Sampson, Aaron; Niebur, Ernst; Stuphorn, Veit; González-Martínez, Jorge; Sarma, Sridevi.
Afiliação
  • Taylor C; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
  • Breault MS; The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
  • Dorman D; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
  • Greene P; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
  • Sacré P; Department of Electrical Engineering and Computer Science, University of Liège, 4000 Liège, Belgium.
  • Sampson A; Solomon Snyder Department of Neuroscience, Johns Hopkins University, Baltimore, MD 21218, USA.
  • Niebur E; Solomon Snyder Department of Neuroscience, Johns Hopkins University, Baltimore, MD 21218, USA.
  • Stuphorn V; Solomon Snyder Department of Neuroscience, Johns Hopkins University, Baltimore, MD 21218, USA.
  • González-Martínez J; School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.
  • Sarma S; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Brain Sci ; 14(8)2024 Jul 31.
Article em En | MEDLINE | ID: mdl-39199467
ABSTRACT
Decision-making is a cognitive process involving working memory, executive function, and attention. However, the connectivity of large-scale brain networks during decision-making is not well understood. This is because gaining access to large-scale brain networks in humans is still a novel process. Here, we used SEEG (stereoelectroencephalography) to record neural activity from the default mode network (DMN), dorsal attention network (DAN), and frontoparietal network (FN) in ten humans while they performed a gambling task in the form of the card game, "War". By observing these networks during a decision-making period, we related the activity of and connectivity between these networks. In particular, we found that gamma band activity was directly related to a participant's ability to bet logically, deciding what betting amount would result in the highest monetary gain or lowest monetary loss throughout a session of the game. We also found connectivity between the DAN and the relation to a participant's performance. Specifically, participants with higher connectivity between and within these networks had higher earnings. Our preliminary findings suggest that connectivity and activity between these networks are essential during decision-making.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Brain Sci Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Suíça

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Brain Sci Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Suíça