Literature DB >> 12657892

Neural prosthetic control signals from plan activity.

Krishna V Shenoy1, Daniella Meeker, Shiyan Cao, Sohaib A Kureshi, Bijan Pesaran, Christopher A Buneo, Aaron P Batista, Partha P Mitra, Joel W Burdick, Richard A Andersen.   

Abstract

The prospect of assisting disabled patients by translating neural activity from the brain into control signals for prosthetic devices, has flourished in recent years. Current systems rely on neural activity present during natural arm movements. We propose here that neural activity present before or even without natural arm movements can provide an important, and potentially advantageous, source of control signals. To demonstrate how control signals can be derived from such plan activity we performed a computational study with neural activity previously recorded from the posterior parietal cortex of rhesus monkeys planning arm movements. We employed maximum likelihood decoders to estimate movement direction and to drive finite state machines governing when to move. Performance exceeded 90% with as few as 40 neurons.

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Year:  2003        PMID: 12657892     DOI: 10.1097/00001756-200303240-00013

Source DB:  PubMed          Journal:  Neuroreport        ISSN: 0959-4965            Impact factor:   1.837


  44 in total

1.  Properties of spike train spectra in two parietal reach areas.

Authors:  C A Buneo; M R Jarvis; A P Batista; R A Andersen
Journal:  Exp Brain Res       Date:  2003-08-28       Impact factor: 1.972

2.  A neural representation of sequential states within an instructed task.

Authors:  Michael Campos; Boris Breznen; Richard A Andersen
Journal:  J Neurophysiol       Date:  2010-08-25       Impact factor: 2.714

3.  Attention and intention, decoded!

Authors:  Alexandra List; Ayelet Landau
Journal:  J Neurosci       Date:  2006-06-28       Impact factor: 6.167

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.  Asynchronous decoding of dexterous finger movements using M1 neurons.

Authors:  Vikram Aggarwal; Soumyadipta Acharya; Francesco Tenore; Hyun-Chool Shin; Ralph Etienne-Cummings; Marc H Schieber; Nitish V Thakor
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2008-02       Impact factor: 3.802

6.  Neural decoding of hand motion using a linear state-space model with hidden states.

Authors:  Wei Wu; Jayant E Kulkarni; Nicholas G Hatsopoulos; Liam Paninski
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2009-06-02       Impact factor: 3.802

7.  Factor-analysis methods for higher-performance neural prostheses.

Authors:  Gopal Santhanam; Byron M Yu; Vikash Gilja; Stephen I Ryu; Afsheen Afshar; Maneesh Sahani; Krishna V Shenoy
Journal:  J Neurophysiol       Date:  2009-03-18       Impact factor: 2.714

Review 8.  Advanced neurotechnologies for chronic neural interfaces: new horizons and clinical opportunities.

Authors:  Daryl R Kipke; William Shain; György Buzsáki; E Fetz; Jaimie M Henderson; Jamille F Hetke; Gerwin Schalk
Journal:  J Neurosci       Date:  2008-11-12       Impact factor: 6.167

9.  Cognitive enhancement: methods, ethics, regulatory challenges.

Authors:  Nick Bostrom; Anders Sandberg
Journal:  Sci Eng Ethics       Date:  2009-06-19       Impact factor: 3.525

10.  Modeling task-specific neuronal ensembles improves decoding of grasp.

Authors:  Ryan J Smith; Alcimar B Soares; Adam G Rouse; Marc H Schieber; Nitish V Thakor
Journal:  J Neural Eng       Date:  2018-02-02       Impact factor: 5.379

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