Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-10688
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Main Title: Immediate brain plasticity after one hour of brain–computer interface (BCI)
Author(s): Nierhaus, Till
Vidaurre, Carmen
Sannelli, Claudia
Müller, Klaus-Robert
Villringer, Arno
Type: Article
URI: https://depositonce.tu-berlin.de/handle/11303/11799
http://dx.doi.org/10.14279/depositonce-10688
License: https://creativecommons.org/licenses/by/4.0/
Abstract: 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.
Subject(s): brain computer interface
BCI
EEG
fMRI
functional connectivity
machine learning
brain plasticity
Issue Date: 6-Nov-2019
Date Available: 28-Oct-2020
Language Code: en
DDC Class: 610 Medizin und Gesundheit
Sponsor/Funder: DFG, 172415596, SPP 1527: Autonomes Lernen
BMBF, 01IS18037I, Verbundprojekt BIFOLD-BZML: Berlin Institute for the Foundations of Learning and Data
BMBF, 01IS14013A, Verbundprojekt: BBDC - Berliner Kompetenzzentrum für Big Data
DFG, 390685689, EXC 2046: MATH+: Berlin Mathematics Research Center
Journal Title: The Journal of Physiology
Publisher: Wiley
Publisher DOI: 10.1113/JP278118
EISSN: 1469-7793
ISSN: 0022-3751
TU Affiliation(s): Fak. 4 Elektrotechnik und Informatik » Inst. Softwaretechnik und Theoretische Informatik » FG Maschinelles Lernen
Appears in Collections:Technische Universität Berlin » Publications

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