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Weighted neurofeedback facilitates greater self-regulation of functional connectivity between the primary motor area and cerebellum.
Vargas, Patricia; Sitaram, Ranganatha; Sepúlveda, Pradyumna; Montalba, Cristian; Rana, Mohit; Torres, Rafael; Tejos, Cristián; Ruiz, Sergio.
Afiliação
  • Vargas P; Interdisciplinary Center for Neuroscience, Department of Psychiatry, Faculty of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile.
  • Sitaram R; Laboratory for Brain-Machine Interfaces and Neuromodulation, Pontificia Universidad Católica de Chile, Santiago, Chile.
  • Sepúlveda P; Biomedical Imaging Center, Pontificia Universidad Católica de Chile, Santiago, Chile.
  • Montalba C; Interdisciplinary Center for Neuroscience, Department of Psychiatry, Faculty of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile.
  • Rana M; Laboratory for Brain-Machine Interfaces and Neuromodulation, Pontificia Universidad Católica de Chile, Santiago, Chile.
  • Torres R; Institute for Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile.
  • Tejos C; Multimodal Functional Brain Imaging Hub, St. Jude Children's Research Hospital, Memphis, TN, United States of America.
  • Ruiz S; Institute of Cognitive Neuroscience (ICN), University College London, London, England.
J Neural Eng ; 18(5)2021 10 14.
Article em En | MEDLINE | ID: mdl-34587606
Objective.Brain-computer interface (BCI) is a tool that can be used to train brain self-regulation and influence specific activity patterns, including functional connectivity, through neurofeedback. The functional connectivity of the primary motor area (M1) and cerebellum play a critical role in motor recovery after a brain injury, such as stroke. The objective of this study was to determine the feasibility of achieving control of the functional connectivity between M1 and the cerebellum in healthy subjects. Additionally, we aimed to compare the brain self-regulation of two different feedback modalities and their effects on motor performance.Approach.Nine subjects were trained with a real-time functional magnetic resonance imaging BCI system. Two groups were conformed: equal feedback group (EFG), which received neurofeedback that weighted the contribution of both regions of interest (ROIs) equally, and weighted feedback group (WFG) that weighted each ROI differentially (30% cerebellum; 70% M1). The magnitude of the brain activity induced by self-regulation was evaluated with the blood-oxygen-level-dependent (BOLD) percent change (BPC). Functional connectivity was assessed using temporal correlations between the BOLD signal of both ROIs. A finger-tapping task was included to evaluate the effect of brain self-regulation on motor performance.Main results.A comparison between the feedback modalities showed that WFG achieved significantly higher BPC in M1 than EFG. The functional connectivity between ROIs during up-regulation in WFG was significantly higher than EFG. In general, both groups showed better tapping speed in the third session compared to the first. For WFG, there were significant correlations between functional connectivity and tapping speed.Significance.The results show that it is possible to train healthy individuals to control M1-cerebellum functional connectivity with rtfMRI-BCI. Besides, it is also possible to use a weighted feedback approach to facilitate a higher activity of one region over another.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neurorretroalimentação / Autocontrole / Córtex Motor Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neurorretroalimentação / Autocontrole / Córtex Motor Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article