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Neurofeedback through the lens of reinforcement learning.
Lubianiker, Nitzan; Paret, Christian; Dayan, Peter; Hendler, Talma.
Afiliación
  • Lubianiker N; School of Psychological Sciences, Gershon H. Gordon Faculty of Social Sciences, Tel Aviv University, Tel Aviv, Israel; Sagol Brain Institute, Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel. Electronic address: nitzanlubi@gmail.com.
  • Paret C; School of Psychological Sciences, Gershon H. Gordon Faculty of Social Sciences, Tel Aviv University, Tel Aviv, Israel; Sagol Brain Institute, Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel; Department of Psychosomatic Medicine and Psychotherapy, Central Insti
  • Dayan P; Max Planck Institute for Biological Cybernetics, Tübingen, Germany; University of Tübingen, Tübingen, Germany.
  • Hendler T; School of Psychological Sciences, Gershon H. Gordon Faculty of Social Sciences, Tel Aviv University, Tel Aviv, Israel; Sagol Brain Institute, Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel; Sagol school of Neuroscience, Tel Aviv University, Tel Aviv, Israel;
Trends Neurosci ; 45(8): 579-593, 2022 08.
Article en En | MEDLINE | ID: mdl-35550813
Despite decades of experimental and clinical practice, the neuropsychological mechanisms underlying neurofeedback (NF) training remain obscure. NF is a unique form of reinforcement learning (RL) task, during which participants are provided with rewarding feedback regarding desired changes in neural patterns. However, key RL considerations - including choices during practice, prediction errors, credit-assignment problems, or the exploration-exploitation tradeoff - have infrequently been considered in the context of NF. We offer an RL-based framework for NF, describing different internal states, actions, and rewards in common NF protocols, thus fashioning new proposals for characterizing, predicting, and hastening the course of learning. In this way we hope to advance current understanding of neural regulation via NF, and ultimately to promote its effectiveness, personalization, and clinical utility.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neurorretroalimentación Tipo de estudio: Guideline Límite: Humans Idioma: En Revista: Trends Neurosci Año: 2022 Tipo del documento: Article Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neurorretroalimentación Tipo de estudio: Guideline Límite: Humans Idioma: En Revista: Trends Neurosci Año: 2022 Tipo del documento: Article Pais de publicación: Reino Unido