Literature DB >> 21763517

A dynamical systems view of motor preparation: implications for neural prosthetic system design.

Krishna V Shenoy1, Matthew T Kaufman, Maneesh Sahani, Mark M Churchland.   

Abstract

Neural prosthetic systems aim to help disabled patients suffering from a range of neurological injuries and disease by using neural activity from the brain to directly control assistive devices. This approach in effect bypasses the dysfunctional neural circuitry, such as an injured spinal cord. To do so, neural prostheses depend critically on a scientific understanding of the neural activity that drives them. We review here several recent studies aimed at understanding the neural processes in premotor cortex that precede arm movements and lead to the initiation of movement. These studies were motivated by hypotheses and predictions conceived of within a dynamical systems perspective. This perspective concentrates on describing the neural state using as few degrees of freedom as possible and on inferring the rules that govern the motion of that neural state. Although quite general, this perspective has led to a number of specific predictions that have been addressed experimentally. It is hoped that the resulting picture of the dynamical role of preparatory and movement-related neural activity will be particularly helpful to the development of neural prostheses, which can themselves be viewed as dynamical systems under the control of the larger dynamical system to which they are attached.
Copyright © 2011 Elsevier B.V. All rights reserved.

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Year:  2011        PMID: 21763517      PMCID: PMC3665515          DOI: 10.1016/B978-0-444-53355-5.00003-8

Source DB:  PubMed          Journal:  Prog Brain Res        ISSN: 0079-6123            Impact factor:   2.453


  104 in total

1.  An optogenetic toolbox designed for primates.

Authors:  Ilka Diester; Matthew T Kaufman; Murtaza Mogri; Ramin Pashaie; Werapong Goo; Ofer Yizhar; Charu Ramakrishnan; Karl Deisseroth; Krishna V Shenoy
Journal:  Nat Neurosci       Date:  2011-01-30       Impact factor: 24.884

2.  Neural variability in premotor cortex provides a signature of motor preparation.

Authors:  Mark M Churchland; Byron M Yu; Stephen I Ryu; Gopal Santhanam; Krishna V Shenoy
Journal:  J Neurosci       Date:  2006-04-05       Impact factor: 6.167

Review 3.  Biological pattern generation: the cellular and computational logic of networks in motion.

Authors:  Sten Grillner
Journal:  Neuron       Date:  2006-12-07       Impact factor: 17.173

Review 4.  Volitional control of neural activity: implications for brain-computer interfaces.

Authors:  Eberhard E Fetz
Journal:  J Physiol       Date:  2007-01-18       Impact factor: 5.182

5.  Long-term motor cortex plasticity induced by an electronic neural implant.

Authors:  Andrew Jackson; Jaideep Mavoori; Eberhard E Fetz
Journal:  Nature       Date:  2006-10-22       Impact factor: 49.962

6.  Mixture of trajectory models for neural decoding of goal-directed movements.

Authors:  Byron M Yu; Caleb Kemere; Gopal Santhanam; Afsheen Afshar; Stephen I Ryu; Teresa H Meng; Maneesh Sahani; Krishna V Shenoy
Journal:  J Neurophysiol       Date:  2007-02-28       Impact factor: 2.714

7.  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

8.  The predictive value for performance speed of preparatory changes in neuronal activity of the monkey motor and premotor cortex.

Authors:  A Riehle; J Requin
Journal:  Behav Brain Res       Date:  1993-02-26       Impact factor: 3.332

9.  The involvement of monkey premotor cortex neurones in preparation of visually cued arm movements.

Authors:  M Godschalk; R N Lemon; H G Kuypers; J van der Steen
Journal:  Behav Brain Res       Date:  1985 Nov-Dec       Impact factor: 3.332

10.  HermesC: low-power wireless neural recording system for freely moving primates.

Authors:  Cynthia A Chestek; Vikash Gilja; Paul Nuyujukian; Ryan J Kier; Florian Solzbacher; Stephen I Ryu; Reid R Harrison; Krishna V Shenoy
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2009-06-02       Impact factor: 3.802

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  31 in total

1.  Heterogeneous attractor cell assemblies for motor planning in premotor cortex.

Authors:  Maurizio Mattia; Pierpaolo Pani; Giovanni Mirabella; Stefania Costa; Paolo Del Giudice; Stefano Ferraina
Journal:  J Neurosci       Date:  2013-07-03       Impact factor: 6.167

2.  Motor adaptation and generalization of reaching movements using motor primitives based on spatial coordinates.

Authors:  Hirokazu Tanaka; Terrence J Sejnowski
Journal:  J Neurophysiol       Date:  2014-11-26       Impact factor: 2.714

3.  Sensory feedback independent pre-song vocalizations correlate with time to song initiation.

Authors:  Divya Rao; Satoshi Kojima; Raghav Rajan
Journal:  J Exp Biol       Date:  2019-04-09       Impact factor: 3.312

Review 4.  Perspectives on classical controversies about the motor cortex.

Authors:  Mohsen Omrani; Matthew T Kaufman; Nicholas G Hatsopoulos; Paul D Cheney
Journal:  J Neurophysiol       Date:  2017-06-14       Impact factor: 2.714

5.  Pre-Bout Neural Activity Changes in Premotor Nucleus HVC Correlate with Successful Initiation of Learned Song Sequence.

Authors:  Raghav Rajan
Journal:  J Neurosci       Date:  2018-05-31       Impact factor: 6.167

6.  Behavioral and neural signatures of readiness to initiate a learned motor sequence.

Authors:  Raghav Rajan; Allison J Doupe
Journal:  Curr Biol       Date:  2012-12-13       Impact factor: 10.834

7.  Macrocircuits: decision networks.

Authors:  Jeffrey D Schall
Journal:  Curr Opin Neurobiol       Date:  2012-12-13       Impact factor: 6.627

8.  Neural dynamics of reaching following incorrect or absent motor preparation.

Authors:  K Cora Ames; Stephen I Ryu; Krishna V Shenoy
Journal:  Neuron       Date:  2014-01-22       Impact factor: 17.173

9.  Sequential selection of economic good and action in medial frontal cortex of macaques during value-based decisions.

Authors:  Xiaomo Chen; Veit Stuphorn
Journal:  Elife       Date:  2015-11-27       Impact factor: 8.140

10.  Intention estimation in brain-machine interfaces.

Authors:  Joline M Fan; Paul Nuyujukian; Jonathan C Kao; Cynthia A Chestek; Stephen I Ryu; Krishna V Shenoy
Journal:  J Neural Eng       Date:  2014-02       Impact factor: 5.379

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