Literature DB >> 26319545

Brain control and information transfer.

Edward J Tehovnik1, Lewis L Chen2.   

Abstract

In this review, we examine the importance of having a body as essential for the brain to transfer information about the outside world to generate appropriate motor responses. We discuss the context-dependent conditioning of the motor control neural circuits and its dependence on the completion of feedback loops, which is in close agreement with the insights of Hebb and colleagues, who have stressed that for learning to occur the body must be intact and able to interact with the outside world. Finally, we apply information theory to data from published studies to evaluate the robustness of the neuronal signals obtained by bypassing the body (as used for brain-machine interfaces) versus via the body to move in the world. We show that recording from a group of neurons that bypasses the body exhibits a vastly degraded level of transfer of information as compared to that of an entire brain using the body to engage in the normal execution of behaviour. We conclude that body sensations provide more than just feedback for movements; they sustain the necessary transfer of information as animals explore their environment, thereby creating associations through learning. This work has implications for the development of brain-machine interfaces used to move external devices.

Entities:  

Keywords:  Brain–machine interfaces; Feedback; Information theory; Learning; Sensorimotor behaviour; Systems neuroscience

Mesh:

Year:  2015        PMID: 26319545     DOI: 10.1007/s00221-015-4423-5

Source DB:  PubMed          Journal:  Exp Brain Res        ISSN: 0014-4819            Impact factor:   1.972


  123 in total

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Authors:  E N Eskandar; J A Assad
Journal:  Nat Neurosci       Date:  1999-01       Impact factor: 24.884

2.  Ascertaining the importance of neurons to develop better brain-machine interfaces.

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Journal:  IEEE Trans Biomed Eng       Date:  2004-06       Impact factor: 4.538

3.  The effect of target modality on visual and proprioceptive contributions to the control of movement distance.

Authors:  Fabrice R Sarlegna; Robert L Sainburg
Journal:  Exp Brain Res       Date:  2007-01       Impact factor: 1.972

Review 4.  A neural substrate of prediction and reward.

Authors:  W Schultz; P Dayan; P R Montague
Journal:  Science       Date:  1997-03-14       Impact factor: 47.728

5.  Instability of the eye in the dark and proprioception.

Authors:  A Fiorentini; L Maffei
Journal:  Nature       Date:  1977-09-22       Impact factor: 49.962

6.  A high-performance brain-computer interface.

Authors:  Gopal Santhanam; Stephen I Ryu; Byron M Yu; Afsheen Afshar; Krishna V Shenoy
Journal:  Nature       Date:  2006-07-13       Impact factor: 49.962

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Authors:  J F Kalaska; R Caminiti; A P Georgopoulos
Journal:  Exp Brain Res       Date:  1983       Impact factor: 1.972

8.  Impairments of reaching movements in patients without proprioception. I. Spatial errors.

Authors:  J Gordon; M F Ghilardi; C Ghez
Journal:  J Neurophysiol       Date:  1995-01       Impact factor: 2.714

Review 9.  The roles of vision and proprioception in the planning of reaching movements.

Authors:  Fabrice R Sarlegna; Robert L Sainburg
Journal:  Adv Exp Med Biol       Date:  2009       Impact factor: 2.622

10.  Multi-electrode stimulation in somatosensory cortex increases probability of detection.

Authors:  Boubker Zaaimi; Ricardo Ruiz-Torres; Sara A Solla; Lee E Miller
Journal:  J Neural Eng       Date:  2013-08-28       Impact factor: 5.379

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  2 in total

1.  Intracortical Microstimulation Modulates Cortical Induced Responses.

Authors:  Mathias Benjamin Voigt; Prasandhya Astagiri Yusuf; Andrej Kral
Journal:  J Neurosci       Date:  2018-07-27       Impact factor: 6.167

2.  An optical brain-to-brain interface supports rapid information transmission for precise locomotion control.

Authors:  Lihui Lu; Ruiyu Wang; Minmin Luo
Journal:  Sci China Life Sci       Date:  2020-03-20       Impact factor: 6.038

  2 in total

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