Title :
Characterization of the short-term plasticity of the dentate gyrus-CA3 system using nonlinear systems analysis
Author :
Gholmieh, G. ; Courellis, G.H. ; Song, D. ; Wang, Z. ; Marmarelis, V.Z. ; Berger, T.W.
Author_Institution :
Dept. of Biomed. Eng., Univ. of Southern California, Los Angeles, CA, USA
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.
Keywords :
Poisson distribution; Volterra equations; bioelectric phenomena; brain; medical computing; neural nets; neurophysiology; nonlinear dynamical systems; operating system kernels; physiological models; Volterra Poisson approach; afferents; data analyzing; dentate gyrus-CA3 system; disynaptic population spike; electrical shock; first order kernel; hippocampal region; monosynaptic population spike; nonlinear dynamics; nonlinear system analysis; paired impulse approach; perforant path; population level; population spike amplitude; random impulse sequence; second order kernel; short impulse train approach; short-term plasticity characteristic; time series; Biomedical engineering; Data acquisition; Data analysis; Electric shock; Frequency; Kernel; Neuroscience; Nonlinear systems; Signal processing; User interfaces;
Conference_Titel :
Engineering in Medicine and Biology Society, 2003. Proceedings of the 25th Annual International Conference of the IEEE
Print_ISBN :
0-7803-7789-3
DOI :
10.1109/IEMBS.2003.1279805