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Towards neural co-processors for the brain: combining decoding and encoding in brain-computer interfaces.

Rajesh Pn Rao1

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Brain-computer interfaces are evolving to integrate neural decoding and encoding, acting as brain co-processors. This advancement enables applications like neuro-rehabilitation and functional augmentation through artificial neural networks.

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Artificial Intelligence

Background:

  • Brain-computer interfaces (BCIs) traditionally focus on neural decoding for prosthetic control.
  • A paradigm shift is emerging towards integrated neural decoding and encoding within a single device.

Purpose of the Study:

  • To review progress in simultaneous neural decoding and encoding for closed-loop BCI applications.
  • To introduce a unifying framework for developing advanced brain co-processor devices.

Main Methods:

  • Review of recent advancements in simultaneous decoding and encoding techniques.
  • Development of a unifying framework utilizing artificial neural networks and deep learning.

Main Results:

  • Demonstration of a framework for creating 'neural co-processors'.
  • These co-processors can jointly optimize functions with the nervous system.

Conclusions:

  • Integrated neural decoding and encoding represent the next frontier in BCIs.
  • Neural co-processors offer potential for neuro-rehabilitation, limb reanimation, and cognitive enhancement.