Immediate brain plasticity after one hour of brain-computer interface (BCI)
Fecha
2019Versión
Acceso abierto / Sarbide irekia
Tipo
Artículo / Artikulua
Versión
Versión publicada / Argitaratu den bertsioa
Impacto
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10.1113/JP278118
Resumen
A brain-computer-interface (BCI) allows humans to control computational devices using only neural signals. However, it is still an open question, whether performing BCI also impacts on the brain itself, i.e. whether brain plasticity is induced. Here, we show rapid and spatially specific signs of brain plasticity measured with functional and structural MRI after only 1 h of purely mental BCI train ...
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A brain-computer-interface (BCI) allows humans to control computational devices using only neural signals. However, it is still an open question, whether performing BCI also impacts on the brain itself, i.e. whether brain plasticity is induced. Here, we show rapid and spatially specific signs of brain plasticity measured with functional and structural MRI after only 1 h of purely mental BCI training in BCI-naive subjects. We employed two BCI approaches with neurofeedback based on (i) modulations of EEG rhythms by motor imagery (MI-BCI) or (ii) event-related potentials elicited by visually targeting flashing letters (ERP-BCI). Before and after the BCI session we performed structural and functional MRI. For both BCI approaches we found increased T1-weighted MR signal in the grey matter of the respective target brain regions, such as occipital/parietal areas after ERP-BCI and precuneus and sensorimotor regions after MI-BCI. The latter also showed increased functional connectivity and higher task-evoked BOLD activity in the same areas. Our results demonstrate for the first time that BCI by means of targeted neurofeedback rapidly impacts on MRI measures of brain structure and function. The spatial specificity of BCI-induced brain plasticity promises therapeutic interventions tailored to individual functional deficits, for example in patients after stroke. [--]
Materias
Brain computer interface (BCI),
Brain plasticity,
EEG,
fMRI,
Functional connectivity,
Machine learning
Editor
Wiley
Publicado en
The Journal of Physiology, 2019
Departamento
Universidad Pública de Navarra. Departamento de Estadística, Informática y Matemáticas /
Nafarroako Unibertsitate Publikoa. Estatistika, Informatika eta Matematika Saila
Versión del editor
Entidades Financiadoras
This research was supported by the German Ministry for Education and Research as Berlin Big Data Center (01IS14013A) and the Berlin Center for Machine Learning (01IS18037I). This research was also supported by the Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (No. 2017‐0‐00451). K.R.M. acknowledges partial funding support by DFG (EXC 2046/1, project‐ID: 390685689). K.R.M. and C.V. gratefully acknowledge financial support from DFG (DFG SPP 1527, MU 987/14‐1). C.V. gratefully acknowledges financial support from MINECO (RYC‐2014‐15671).