Extraction of error related local field potentials from the striatum during environmental perturbations of a robotic arm

Shijia Geng, Noeline W. Prins, Eric A. Pohlmeyer, Abhishek Prasad, Justin C. Sanchez

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

A time-frequency analysis based on wavelet transform was carried out to extract error related local field potentials (LFPs) resulting from undesired action perturbations during the control of a robotic effector. During this study, a marmoset monkey controlled the movements of a robotic arm while periodically observing the arm unexpectedly moving to the incorrect target during perturbations. LFPs were recorded using a multi-electrode array implanted in the striatum. Results showed that the proposed signal processing method with a chosen classification threshold can effectively separate the perturbed and the normal situations. Obtaining such information during brain machine interfaces (BMI) tasks could improve the performance of BMI systems.

Original languageEnglish (US)
Title of host publication2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013
Pages993-996
Number of pages4
DOIs
StatePublished - Dec 1 2013
Event2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013 - San Diego, CA, United States
Duration: Nov 6 2013Nov 8 2013

Publication series

NameInternational IEEE/EMBS Conference on Neural Engineering, NER
ISSN (Print)1948-3546
ISSN (Electronic)1948-3554

Other

Other2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013
CountryUnited States
CitySan Diego, CA
Period11/6/1311/8/13

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering

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    Geng, S., Prins, N. W., Pohlmeyer, E. A., Prasad, A., & Sanchez, J. C. (2013). Extraction of error related local field potentials from the striatum during environmental perturbations of a robotic arm. In 2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013 (pp. 993-996). [6696103] (International IEEE/EMBS Conference on Neural Engineering, NER). https://doi.org/10.1109/NER.2013.6696103