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Brain control and information transfer.

Edward J Tehovnik1, Lewis L Chen2

  • 1Brain Institute, UFRN, Av. Nascimento de Castro 2155, Natal, 59056-450, Brazil. tehovnikej@gmail.com.

Experimental Brain Research
|August 31, 2015
PubMed
Summary
This summary is machine-generated.

The intact body is crucial for brain information transfer and motor control. Bypassing the body significantly degrades neural signal robustness, impacting learning and environmental interaction.

Keywords:
Brain–machine interfacesFeedbackInformation theoryLearningSensorimotor behaviourSystems neuroscience

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Area of Science:

  • Neuroscience
  • Robotics
  • Information Theory

Background:

  • The brain requires an intact body to process external information and generate motor responses.
  • Motor control neural circuits depend on feedback loops for context-dependent conditioning.
  • Hebb's principles emphasize the necessity of an intact body for learning and interaction.

Purpose of the Study:

  • To review the essential role of the body in brain information transfer and motor control.
  • To evaluate the robustness of neuronal signals when bypassing the body versus using the body.
  • To explore implications for brain-machine interface (BMI) development.

Main Methods:

  • Information theory applied to published neurophysiological data.
  • Comparison of neuronal signal robustness between body-intact and body-bypass conditions.
  • Review of motor control and neural circuit conditioning principles.

Main Results:

  • Neuronal signals obtained by bypassing the body show significantly degraded information transfer.
  • The intact body enhances the robustness of neuronal signals during natural behavior.
  • Body sensations are vital for sustained information transfer and associative learning.

Conclusions:

  • Body sensations are integral to, not just feedback for, movement.
  • The body is essential for robust information transfer, learning, and environmental exploration.
  • Findings have significant implications for designing more effective brain-machine interfaces.