Cargando…
Self-regulation learning as active inference: dynamic causal modeling of an fMRI neurofeedback task
INTRODUCTION: Learning to self-regulate brain activity by neurofeedback has been shown to lead to changes in the brain and behavior, with beneficial clinical and non-clinical outcomes. Neurofeedback uses a brain-computer interface to guide participants to change some feature of their brain activity....
Autores principales: | Vargas, Gabriela, Araya, David, Sepulveda, Pradyumna, Rodriguez-Fernandez, Maria, Friston, Karl J., Sitaram, Ranganatha, El-Deredy, Wael |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10465165/ https://www.ncbi.nlm.nih.gov/pubmed/37650101 http://dx.doi.org/10.3389/fnins.2023.1212549 |
Ejemplares similares
-
Self-Regulation of the Fusiform Face Area in Autism Spectrum: A Feasibility Study With Real-Time fMRI Neurofeedback
por: Pereira, Jaime A., et al.
Publicado: (2019) -
Semi-Automated and Direct Localization and Labeling of EEG Electrodes Using MR Structural Images for Simultaneous fMRI-EEG
por: Bhutada, Abhishek S., et al.
Publicado: (2020) -
Volitional control of the anterior insula in criminal psychopaths using real-time fMRI neurofeedback: a pilot study
por: Sitaram, Ranganatha, et al.
Publicado: (2014) -
Real-Time fMRI Neurofeedback Training as a Neurorehabilitation Approach on Depressive Disorders: A Systematic Review of Randomized Control Trials
por: González Méndez, Pamela P., et al.
Publicado: (2022) -
Connectivity-based neurofeedback: Dynamic causal modeling for real-time fMRI()
por: Koush, Yury, et al.
Publicado: (2013)