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Learning is shaped by abrupt changes in neural engagement.
Hennig, Jay A; Oby, Emily R; Golub, Matthew D; Bahureksa, Lindsay A; Sadtler, Patrick T; Quick, Kristin M; Ryu, Stephen I; Tyler-Kabara, Elizabeth C; Batista, Aaron P; Chase, Steven M; Yu, Byron M.
Afiliação
  • Hennig JA; Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA. jhennig@andrew.cmu.edu.
  • Oby ER; Center for the Neural Basis of Cognition, Pittsburgh, PA, USA. jhennig@andrew.cmu.edu.
  • Golub MD; Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA, USA. jhennig@andrew.cmu.edu.
  • Bahureksa LA; Center for the Neural Basis of Cognition, Pittsburgh, PA, USA.
  • Sadtler PT; Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA, USA.
  • Quick KM; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.
  • Ryu SI; Center for the Neural Basis of Cognition, Pittsburgh, PA, USA.
  • Tyler-Kabara EC; Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA.
  • Batista AP; Department of Electrical Engineering, Stanford University, Stanford, CA, USA.
  • Chase SM; Center for the Neural Basis of Cognition, Pittsburgh, PA, USA.
  • Yu BM; Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA.
Nat Neurosci ; 24(5): 727-736, 2021 05.
Article em En | MEDLINE | ID: mdl-33782622
ABSTRACT
Internal states such as arousal, attention and motivation modulate brain-wide neural activity, but how these processes interact with learning is not well understood. During learning, the brain modifies its neural activity to improve behavior. How do internal states affect this process? Using a brain-computer interface learning paradigm in monkeys, we identified large, abrupt fluctuations in neural population activity in motor cortex indicative of arousal-like internal state changes, which we term 'neural engagement.' In a brain-computer interface, the causal relationship between neural activity and behavior is known, allowing us to understand how neural engagement impacted behavioral performance for different task goals. We observed stereotyped changes in neural engagement that occurred regardless of how they impacted performance. This allowed us to predict how quickly different task goals were learned. These results suggest that changes in internal states, even those seemingly unrelated to goal-seeking behavior, can systematically influence how behavior improves with learning.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Limite: Animals Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Limite: Animals Idioma: En Ano de publicação: 2021 Tipo de documento: Article