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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Dong Song Robinson, B.S. Hampson, R.E. Marmarelis, V.Z. Deadwyler, S.A. Berger, T.W. |
| Copyright Year | 2015 |
| Description | Author affiliation: Dept. of Physiol. & Pharmacology, Wake Forest Univ., Winston-Salem, NC, USA (Hampson, R.E.; Deadwyler, S.A.) || Dept. of Biomed. Eng., Univ. of Southern California, Los Angeles, CA, USA (Dong Song; Robinson, B.S.; Marmarelis, V.Z.; Berger, T.W.) |
| Abstract | In order to build hippocampal prostheses for restoring memory functions, we build multi-input, multi-output (MIMO) nonlinear dynamical models of the human hippocampus. Spike trains are recorded from the hippocampal CA3 and CA1 regions of epileptic patients performing a memory-dependent delayed match-to-sample task. Using CA3 and CA1 spike trains as inputs and outputs respectively, second-order sparse generalized Laguerre-Volterra models are estimated with group lasso and local coordinate descent methods to capture the nonlinear dynamics underlying the spike train transformations. These models can accurately predict the CA1 spike trains based on the ongoing CA3 spike trains and thus will serve as the computational basis of the hippocampal memory prosthesis. |
| Starting Page | 3961 |
| Ending Page | 3964 |
| File Size | 1566307 |
| Page Count | 4 |
| File Format | |
| ISSN | 1557170X |
| e-ISBN | 9781424492718 |
| DOI | 10.1109/EMBC.2015.7319261 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-08-25 |
| Publisher Place | Italy |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | MIMO Kernel Estimation Predictive models Computational modeling Prosthetics Neurons |
| Content Type | Text |
| Resource Type | Article |
| Subject | Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition |
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