Variable selection for motor cortical control of directions

Jing Hu; Jennie Si; Byron P. Olson; Jiping He

doi:10.1109/CNE.2005.1419557

Variable selection for motor cortical control of directions

Jing Hu, Jennie Si, Byron P. Olson, Jiping He

Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In our previous work, a non-stereotypical brain machine interface system was implemented with freely-moving rats, and a nonlinear support vector machine (SVM) classifier was used to map neural signals in the rats' motor cortices onto a set of discrete classes of directions (Left and Right). In this paper, we provide a comprehensive analysis about the selection of neurons and temporal parameters, which is critical to the success of the system. We also show that pre-processing by principal component analysis (PCA) can reduce dimensions and improve accuracy.

Original language	English (US)
Title of host publication	2nd International IEEE EMBS Conference on Neural Engineering
Pages	78-81
Number of pages	4
Volume	2005
DOIs	https://doi.org/10.1109/CNE.2005.1419557
State	Published - 2005
Event	2nd International IEEE EMBS Conference on Neural Engineering, 2005 - Arlington, VA, United States Duration: Mar 16 2005 → Mar 19 2005

Other

Other	2nd International IEEE EMBS Conference on Neural Engineering, 2005
Country/Territory	United States
City	Arlington, VA
Period	3/16/05 → 3/19/05

Keywords

Brain-machine interface
Motor cortical control
PCA
SVM
Variable selection

ASJC Scopus subject areas

Engineering(all)

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10.1109/CNE.2005.1419557

Cite this

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title = "Variable selection for motor cortical control of directions",

abstract = "In our previous work, a non-stereotypical brain machine interface system was implemented with freely-moving rats, and a nonlinear support vector machine (SVM) classifier was used to map neural signals in the rats' motor cortices onto a set of discrete classes of directions (Left and Right). In this paper, we provide a comprehensive analysis about the selection of neurons and temporal parameters, which is critical to the success of the system. We also show that pre-processing by principal component analysis (PCA) can reduce dimensions and improve accuracy.",

keywords = "Brain-machine interface, Motor cortical control, PCA, SVM, Variable selection",

author = "Jing Hu and Jennie Si and Olson, {Byron P.} and Jiping He",

year = "2005",

doi = "10.1109/CNE.2005.1419557",

language = "English (US)",

volume = "2005",

pages = "78--81",

booktitle = "2nd International IEEE EMBS Conference on Neural Engineering",

note = "2nd International IEEE EMBS Conference on Neural Engineering, 2005 ; Conference date: 16-03-2005 Through 19-03-2005",

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TY - GEN

T1 - Variable selection for motor cortical control of directions

AU - Hu, Jing

AU - Si, Jennie

AU - Olson, Byron P.

AU - He, Jiping

PY - 2005

Y1 - 2005

N2 - In our previous work, a non-stereotypical brain machine interface system was implemented with freely-moving rats, and a nonlinear support vector machine (SVM) classifier was used to map neural signals in the rats' motor cortices onto a set of discrete classes of directions (Left and Right). In this paper, we provide a comprehensive analysis about the selection of neurons and temporal parameters, which is critical to the success of the system. We also show that pre-processing by principal component analysis (PCA) can reduce dimensions and improve accuracy.

AB - In our previous work, a non-stereotypical brain machine interface system was implemented with freely-moving rats, and a nonlinear support vector machine (SVM) classifier was used to map neural signals in the rats' motor cortices onto a set of discrete classes of directions (Left and Right). In this paper, we provide a comprehensive analysis about the selection of neurons and temporal parameters, which is critical to the success of the system. We also show that pre-processing by principal component analysis (PCA) can reduce dimensions and improve accuracy.

KW - Brain-machine interface

KW - Motor cortical control

KW - PCA

KW - SVM

KW - Variable selection

UR - http://www.scopus.com/inward/record.url?scp=33744475348&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33744475348&partnerID=8YFLogxK

U2 - 10.1109/CNE.2005.1419557

DO - 10.1109/CNE.2005.1419557

M3 - Conference contribution

AN - SCOPUS:33744475348

VL - 2005

SP - 78

EP - 81

BT - 2nd International IEEE EMBS Conference on Neural Engineering

T2 - 2nd International IEEE EMBS Conference on Neural Engineering, 2005

Y2 - 16 March 2005 through 19 March 2005

ER -

Variable selection for motor cortical control of directions

Abstract

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Keywords

ASJC Scopus subject areas

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