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De Novo Brain-Computer Interfacing Deforms Manifold of Populational Neural Activity Patterns in Human Cerebral Cortex.
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- Author(s): Iwama S;Iwama S;Iwama S; Zhang Y; Zhang Y; Ushiba J; Ushiba J
- Source:
ENeuro [eNeuro] 2022 Nov 28; Vol. 9 (6). Date of Electronic Publication: 2022 Nov 28 (Print Publication: 2022).- Publication Type:
Journal Article- Language:
English - Source:
- Additional Information
- Source: Publisher: Society for Neuroscience Country of Publication: United States NLM ID: 101647362 Publication Model: Electronic-Print Cited Medium: Internet ISSN: 2373-2822 (Electronic) Linking ISSN: 23732822 NLM ISO Abbreviation: eNeuro Subsets: MEDLINE
- Publication Information: Original Publication: [Washington, DC] : Society for Neuroscience, [2014]-
- Subject Terms:
- Abstract: Human brains are capable of modulating innate activities to adapt to novel environments and tasks; for sensorimotor neural system this means acquisition of a rich repertoire of activity patterns that improve behavioral performance. To directly map the process of acquiring the neural repertoire during tasks onto performance improvement, we analyzed net neural populational activity during the learning of its voluntary modulation by brain-computer interface (BCI) operation in female and male humans. The recorded whole-head high-density scalp electroencephalograms (EEGs) were subjected to dimensionality reduction algorithm to capture changes in cortical activity patterns represented by the synchronization of neuronal oscillations during adaptation. Although the preserved variance of targeted features in the reduced dimensions was 20%, we found systematic interactions between the activity patterns and BCI classifiers that detected motor attempt; the neural manifold derived in the embedded space was stretched along with motor-related features of EEG by model-based fixed classifiers but not with adaptive classifiers that were constantly recalibrated to user activity. Moreover, the manifold was deformed to be orthogonal to the boundary by de novo classifiers with a fixed decision boundary based on biologically unnatural features. Collectively, the flexibility of human cortical signaling patterns (i.e., neural plasticity) is only induced by operation of a BCI whose classifier required fixed activities, and the adaptation could be induced even the requirement is not consistent with biologically natural responses. These principles of neural adaptation at a macroscopic level may underlie the ability of humans to learn wide-ranging behavioral repertoires and adapt to novel environments.
Competing Interests: J.U. is a founder and representative director of the university startup company, LIFESCAPES Inc., involved in the research, development, and sales of rehabilitation devices including brain-computer interfaces, he receives a salary from LIFESCAPES Inc., and holds shares in LIFESCAPES Inc. This company does not have any relationships with the device or setup used in the current study. All other authors declare no competing financial interests.
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- Publication Date: Date Created: 20221114 Date Completed: 20221130 Latest Revision: 20221222
- Publication Date: 20231215
- Accession Number: PMC9721308
- Accession Number: 10.1523/ENEURO.0145-22.2022
- Accession Number: 36376067
- Source:
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