Analysing the Changing Brain: Immediate Brain Plasticity After One Hour of BCI

In this brief contribution I will discuss recent directions of our research where nonlinear learning methods are employed for analysing multimodal brain data, both in the context of BCI and beyond - essentially summarizing some steps taken by the BBCI team and co-workers. Clearly, unavoidably and intentionally this abstract will have a high overlap to prior own contributions and touch upon ongoing unpublished respectively pre-pulished work, nevertheless extensively providing pointers to various research directions.

[1]  Vince D. Calhoun,et al.  A review of multivariate methods for multimodal fusion of brain imaging data , 2012, Journal of Neuroscience Methods.

[2]  Stefan Haufe,et al.  The Berlin Brain-Computer Interface: Progress Beyond Communication and Control , 2016, Front. Neurosci..

[3]  K.-R. Muller,et al.  Optimizing Spatial filters for Robust EEG Single-Trial Analysis , 2008, IEEE Signal Processing Magazine.

[4]  Wojciech Samek,et al.  Transferring Subspaces Between Subjects in Brain--Computer Interfacing , 2012, IEEE Transactions on Biomedical Engineering.

[5]  Febo Cincotti,et al.  Towards Noninvasive Hybrid Brain–Computer Interfaces: Framework, Practice, Clinical Application, and Beyond , 2015, Proceedings of the IEEE.

[6]  Arno Villringer,et al.  Immediate brain plasticity after one hour of brain–computer interface (BCI) , 2019, The Journal of physiology.

[7]  Klaus-Robert Müller,et al.  Introduction to machine learning for brain imaging , 2011, NeuroImage.

[8]  Klaus-Robert Müller,et al.  Learning From More Than One Data Source: Data Fusion Techniques for Sensorimotor Rhythm-Based Brain–Computer Interfaces , 2015, Proceedings of the IEEE.

[9]  Stefan Haufe,et al.  Single-trial analysis and classification of ERP components — A tutorial , 2011, NeuroImage.

[10]  Pramod K. Varshney,et al.  Multisensor Data Fusion , 1997, IEA/AIE.

[11]  Steven Lemm,et al.  A novel mechanism for evoked responses in the human brain , 2007, The European journal of neuroscience.

[12]  Motoaki Kawanabe,et al.  Divergence-Based Framework for Common Spatial Patterns Algorithms , 2014, IEEE Reviews in Biomedical Engineering.

[13]  Klaus-Robert Müller,et al.  Enhanced Performance by a Hybrid Nirs–eeg Brain Computer Interface , 2022 .