A cortical integrate-and-fire neural network model for blind decoding of visual prosthetic stimulation

Calvin D. Eiber, John W. Morley, Nigel H. Lovell, Gregg J. Suaning

Research output: Chapter in Book / Conference PaperConference Paperpeer-review

Abstract

We present a computational model of the optic pathway which has been adapted to simulate cortical responses to visual-prosthetic stimulation. This model reproduces the statistically observed distributions of spikes for cortical recordings of sham and maximum-intensity stimuli, while simultaneously generating cellular receptive fields consistent with those observed using traditional visual neuroscience methods. By inverting this model to generate candidate phosphenes which could generate the responses observed to novel stimulation strategies, we hope to aid the development of said strategies in-vivo before being deployed in clinical settings.
Original languageEnglish
Title of host publicationProceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2014): Discovering, Innovating, and Engineering Future Biomedicine, 26-30 August 2014, Chicago, Illinois
PublisherIEEE
Pages1715-1718
Number of pages4
DOIs
Publication statusPublished - 2014
EventIEEE Engineering in Medicine and Biology Society. Annual International Conference -
Duration: 11 Jul 2022 → …

Publication series

Name
ISSN (Print)1557-170X

Conference

ConferenceIEEE Engineering in Medicine and Biology Society. Annual International Conference
Period11/07/22 → …

Keywords

  • blind decoding
  • computer simulation
  • neurophysiology
  • prosthesis
  • visual perception

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