Spiking Laguerre Volterra networks—predicting neuronal activity from local field potentials

K Kostoglou, KP Michmizos, P Stathis… - Journal of neural …, 2024 - iopscience.iop.org
Objective. Understanding the generative mechanism between local field potentials (LFP)
and neuronal spiking activity is a crucial step for understanding information processing in …

Methodology of recurrent Laguerre–Volterra network for modeling nonlinear dynamic systems

K Geng, VZ Marmarelis - IEEE transactions on neural networks …, 2016 - ieeexplore.ieee.org
In this paper, we have introduced a general modeling approach for dynamic nonlinear
systems that utilizes a variant of the simulated annealing algorithm for training the Laguerre …

Mechanism-based and input-output modeling of the key neuronal connections and signal transformations in the CA3-CA1 regions of the hippocampus

K Geng, DC Shin, D Song, RE Hampson… - Neural …, 2017 - ieeexplore.ieee.org
This letter examines the results of input-output (nonparametric) modeling based on the
analysis of data generated by a mechanism-based (parametric) model of CA3-CA1 neuronal …

Multi-input, multi-output neuronal mode network approach to modeling the encoding dynamics and functional connectivity of neural systems

K Geng, DC Shin, D Song, RE Hampson… - Neural …, 2019 - direct.mit.edu
This letter proposes a novel method, multi-input, multi-output neuronal mode network (MIMO-
NMN), for modeling encoding dynamics and functional connectivity in neural ensembles …

Nonlinear Dynamic Modeling of Biomedical Systems with Laguerre-Volterra Network

K Geng - 2017 - search.proquest.com
In this dissertation, a novel recurrent Laguerre-Volterra Network (LVN) is formulated to
successfully approximate the classic Hodgkin-Huxley (HH) model. The results indicate that …