Conditioned Standard BCI CODEC – A theoretical proposal

[Display omitted] Despite recent technological advances in Brain-Computer Interfaces, we continue to struggle with acquiring high-resolution (spatial and temporal) deep brain neural activity patterns. Making sense of the measured data regarding its correlation to the higher-level cognitive processes...

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Bibliographic Details
Published inBiologically inspired cognitive architectures Vol. 24; pp. 21 - 30
Main Author Pankovski, Toso
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.04.2018
Subjects
Brain interface
Deep brain
Hebbian learning
Neuroplasticity
Standard BCI CODEC
Brain interface
Neuroplasticity
Standard BCI CODEC
Hebbian learning
Deep brain
Online AccessGet full text
ISSN2212-683X
2212-6848
DOI10.1016/j.bica.2018.04.004

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Summary:[Display omitted] Despite recent technological advances in Brain-Computer Interfaces, we continue to struggle with acquiring high-resolution (spatial and temporal) deep brain neural activity patterns. Making sense of the measured data regarding its correlation to the higher-level cognitive processes is an even bigger challenge. The author of this study proposes a standardized invasive in vivo method for (a) extracting and (b) decoding deep brain neural dynamics using multielectrode array implants. Based on neuroplasticity, the method would enforce neural conditioning, which would decode and convey neural correlates’ activities onto the multielectrode array pins. Applied inversely, it would allow encoding and eliciting desired sensations in the subject’s brain. A simple unsupervised recurrent neural network model is built to demonstrate the method. This study is theoretical, and an experimental animal trial is proposed to test the demonstrated method.
ISSN:2212-683X
2212-6848
DOI:10.1016/j.bica.2018.04.004