Literature DB >> 28625485

Motor Cortical Visuomotor Feedback Activity Is Initially Isolated from Downstream Targets in Output-Null Neural State Space Dimensions.

Sergey D Stavisky1, Jonathan C Kao2, Stephen I Ryu3, Krishna V Shenoy4.   

Abstract

Neural circuits must transform new inputs into outputs without prematurely affecting downstream circuits while still maintaining other ongoing communication with these targets. We investigated how this isolation is achieved in the motor cortex when macaques received visual feedback signaling a movement perturbation. To overcome limitations in estimating the mapping from cortex to arm movements, we also conducted brain-machine interface (BMI) experiments where we could definitively identify neural firing patterns as output-null or output-potent. This revealed that perturbation-evoked responses were initially restricted to output-null patterns that cancelled out at the neural population code readout and only later entered output-potent neural dimensions. This mechanism was facilitated by the circuit's large null space and its ability to strongly modulate output-potent dimensions when generating corrective movements. These results show that the nervous system can temporarily isolate portions of a circuit's activity from its downstream targets by restricting this activity to the circuit's output-null neural dimensions.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  brain-machine interface; motor control; motor cortex; sensorimotor system; visuomotor feedback

Mesh:

Year:  2017        PMID: 28625485      PMCID: PMC5547570          DOI: 10.1016/j.neuron.2017.05.023

Source DB:  PubMed          Journal:  Neuron        ISSN: 0896-6273            Impact factor:   17.173


  61 in total

1.  Complex movements evoked by microstimulation of precentral cortex.

Authors:  Michael S A Graziano; Charlotte S R Taylor; Tirin Moore
Journal:  Neuron       Date:  2002-05-30       Impact factor: 17.173

2.  Role of corticospinal suppression during motor preparation.

Authors:  Julie Duque; Richard B Ivry
Journal:  Cereb Cortex       Date:  2009-01-06       Impact factor: 5.357

3.  A high performing brain-machine interface driven by low-frequency local field potentials alone and together with spikes.

Authors:  Sergey D Stavisky; Jonathan C Kao; Paul Nuyujukian; Stephen I Ryu; Krishna V Shenoy
Journal:  J Neural Eng       Date:  2015-05-06       Impact factor: 5.379

Review 4.  A perspective on multisensory integration and rapid perturbation responses.

Authors:  Tyler Cluff; Frédéric Crevecoeur; Stephen H Scott
Journal:  Vision Res       Date:  2014-07-09       Impact factor: 1.886

5.  Closed-loop decoder adaptation shapes neural plasticity for skillful neuroprosthetic control.

Authors:  Amy L Orsborn; Helene G Moorman; Simon A Overduin; Maryam M Shanechi; Dragan F Dimitrov; Jose M Carmena
Journal:  Neuron       Date:  2014-06-18       Impact factor: 17.173

6.  A closed-loop human simulator for investigating the role of feedback control in brain-machine interfaces.

Authors:  John P Cunningham; Paul Nuyujukian; Vikash Gilja; Cindy A Chestek; Stephen I Ryu; Krishna V Shenoy
Journal:  J Neurophysiol       Date:  2010-10-13       Impact factor: 2.714

7.  Long-Term Stability of Motor Cortical Activity: Implications for Brain Machine Interfaces and Optimal Feedback Control.

Authors:  Robert D Flint; Michael R Scheid; Zachary A Wright; Sara A Solla; Marc W Slutzky
Journal:  J Neurosci       Date:  2016-03-23       Impact factor: 6.167

8.  Neural constraints on learning.

Authors:  Patrick T Sadtler; Kristin M Quick; Matthew D Golub; Steven M Chase; Stephen I Ryu; Elizabeth C Tyler-Kabara; Byron M Yu; Aaron P Batista
Journal:  Nature       Date:  2014-08-28       Impact factor: 49.962

9.  Robust Brain-Machine Interface Design Using Optimal Feedback Control Modeling and Adaptive Point Process Filtering.

Authors:  Maryam M Shanechi; Amy L Orsborn; Jose M Carmena
Journal:  PLoS Comput Biol       Date:  2016-04-01       Impact factor: 4.475

10.  Uniform and Non-uniform Perturbations in Brain-Machine Interface Task Elicit Similar Neural Strategies.

Authors:  Michelle Armenta Salas; Stephen I Helms Tillery
Journal:  Front Syst Neurosci       Date:  2016-08-23
View more
  35 in total

1.  Amplitude modulations of cortical sensory responses in pulsatile evidence accumulation.

Authors:  Sue Ann Koay; Stephan Thiberge; Carlos D Brody; David W Tank
Journal:  Elife       Date:  2020-12-02       Impact factor: 8.140

2.  Gain control in the sensorimotor system.

Authors:  Eiman Azim; Kazuhiko Seki
Journal:  Curr Opin Physiol       Date:  2019-03-22

3.  Learning is shaped by abrupt changes in neural engagement.

Authors:  Aaron P Batista; Steven M Chase; Byron M Yu; Jay A Hennig; Emily R Oby; Matthew D Golub; Lindsay A Bahureksa; Patrick T Sadtler; Kristin M Quick; Stephen I Ryu; Elizabeth C Tyler-Kabara
Journal:  Nat Neurosci       Date:  2021-03-29       Impact factor: 24.884

Review 4.  Latent Factors and Dynamics in Motor Cortex and Their Application to Brain-Machine Interfaces.

Authors:  Chethan Pandarinath; K Cora Ames; Abigail A Russo; Ali Farshchian; Lee E Miller; Eva L Dyer; Jonathan C Kao
Journal:  J Neurosci       Date:  2018-10-31       Impact factor: 6.167

5.  The critical stability task: quantifying sensory-motor control during ongoing movement in nonhuman primates.

Authors:  Kristin M Quick; Jessica L Mischel; Patrick J Loughlin; Aaron P Batista
Journal:  J Neurophysiol       Date:  2018-06-27       Impact factor: 2.714

6.  Correlations Between Primary Motor Cortex Activity with Recent Past and Future Limb Motion During Unperturbed Reaching.

Authors:  Tomohiko Takei; Frédéric Crevecoeur; Troy M Herter; Kevin P Cross; Stephen H Scott
Journal:  J Neurosci       Date:  2018-07-23       Impact factor: 6.167

7.  Speech-related dorsal motor cortex activity does not interfere with iBCI cursor control.

Authors:  Sergey D Stavisky; Francis R Willett; Donald T Avansino; Leigh R Hochberg; Krishna V Shenoy; Jaimie M Henderson
Journal:  J Neural Eng       Date:  2020-02-05       Impact factor: 5.379

Review 8.  Computation Through Neural Population Dynamics.

Authors:  Saurabh Vyas; Matthew D Golub; David Sussillo; Krishna V Shenoy
Journal:  Annu Rev Neurosci       Date:  2020-07-08       Impact factor: 12.449

9.  Done in 100 ms: path-dependent visuomotor transformation in the human upper limb.

Authors:  Chao Gu; J Andrew Pruszynski; Paul L Gribble; Brian D Corneil
Journal:  J Neurophysiol       Date:  2017-12-06       Impact factor: 2.714

10.  Motor Cortex Embeds Muscle-like Commands in an Untangled Population Response.

Authors:  Abigail A Russo; Sean R Bittner; Sean M Perkins; Jeffrey S Seely; Brian M London; Antonio H Lara; Andrew Miri; Najja J Marshall; Adam Kohn; Thomas M Jessell; Laurence F Abbott; John P Cunningham; Mark M Churchland
Journal:  Neuron       Date:  2018-02-01       Impact factor: 17.173

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.