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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Gholmieh, G. Courellis, G.H. Song, D. Wang, Z. Marmarelis, V.Z. Berger, T.W. |
| Copyright Year | 2003 |
| Description | Author affiliation: Dept. of Biomed. Eng., Univ. of Southern California, Los Angeles, CA, USA (Gholmieh, G.; Courellis, G.H.; Song, D.) |
| Abstract | Short-term plasticity (STP) have been traditionally studied using the paired impulse approach and the short impulse train approach. A new method for studying STP has been recently introduced [1], In this article, this method has been modified to take into account the varying amplitude of the input. It was then applied to the dentate gyrus-CA3 system. The system was studied at the population level using the population spike (PS) amplitude. Random impulse sequences (electrical shocks) with constant intensity were used to stimulate the afferents to the dentate gyrus (perforant path). Monosynaptic and disynaptic population spikes were recorded from the dentate gyrus and the CA3 regions respectively. The PS amplitude time series of the dentate gyrus formed the input dataset while the PS amplitude time series of the CAS region formed the output dataset. The data was analyzed using the Volterra Poisson approach leading to the estimation of the first and second order kernels, which formed comprehensive and quantitative descriptors of the nonlinear dynamics of STP in the CA3 hippocampal region. |
| Sponsorship | Whitaker Found |
| Starting Page | 1929 |
| Ending Page | 1932 |
| File Size | 304283 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780377893 |
| ISSN | 1094687X |
| DOI | 10.1109/IEMBS.2003.1279805 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2003-09-17 |
| Publisher Place | Mexico |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Nonlinear systems Data acquisition Electric shock Data analysis Kernel User interfaces Biomedical engineering Neuroscience Signal processing Frequency |
| Content Type | Text |
| Resource Type | Article |
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