Learning the contributions of the motor, premotor, and posterior parietal cortices for hand trajectory reconstruction in a brain machine interface

Justin C. Sanchez, Deniz Erdogmus, Yadunandana Rao, Jose C. Principe, Miguel Nicolelis, Johan Wessberg

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

19 Scopus citations

Abstract

The ability to record, in real-time, the activity of hundreds of cortical neurons gives the ability to selectively study the function of clusters of cortical neurons in Brain Machine Interface (BMI) experiments. We have demonstrated using a recursive multilayer perceptron (RMLP) that using the appropriate signal processing theory in a well-chosen parsimonious model, we can develop constructs that agree with basic physiological modeling of neural control. By looking through the trained model, we have found interesting relationships between the neuronal firing and the movement. The RMLP allows us to continuously study the relationship between neural activity and behavior without the active interference of the experimenter. The findings presented in this study offer an opportunity for the neuroscience community to compare the cortical interactions as constructed by the RMLP to what is known about motor neurophysiology.

Original languageEnglish (US)
Title of host publicationInternational IEEE/EMBS Conference on Neural Engineering, NER
PublisherIEEE Computer Society
Pages59-62
Number of pages4
Volume2003-January
ISBN (Print)0780375793
DOIs
StatePublished - 2003
Externally publishedYes
Event1st International IEEE EMBS Conference on Neural Engineering - Capri Island, Italy
Duration: Mar 20 2003Mar 22 2003

Other

Other1st International IEEE EMBS Conference on Neural Engineering
CountryItaly
CityCapri Island
Period3/20/033/22/03

Keywords

  • Animals
  • Biomedical signal processing
  • Finite impulse response filter
  • Interference
  • Machine learning
  • Multilayer perceptrons
  • Neurons
  • Neurophysiology
  • Neuroscience
  • Predictive models

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering

Fingerprint Dive into the research topics of 'Learning the contributions of the motor, premotor, and posterior parietal cortices for hand trajectory reconstruction in a brain machine interface'. Together they form a unique fingerprint.

Cite this