Dynamical estimation of neuron and network properties III: network analysis using neuron spike times.
Estimating the behavior of a network of neurons requires accurate models of the individual neurons along with accurate characterizations of the connections among them. Whereas for a single cell, measurements of the intracellular voltage are technically feasible and sufficient to characterize a useful model of its behavior, making sufficient numbers of simultaneous intracellular measurements to characterize even small networks is infeasible. This paper builds on prior work on single neurons to explore whether knowledge of the time of spiking of neurons in a network, once the nodes (neurons) have been characterized biophysically, can provide enough information to usefully constrain the functional architecture of the network: the existence of synaptic links among neurons and their strength. Using standardized voltage and synaptic gating variable waveforms associated with a spike, we demonstrate that the functional architecture of a small network of model neurons can be established.
Department of Physics, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA , 92093-0402, USA, cknowlton@physics.ucsd.edu.
Chris
C
Knowlton
C Daniel
CD
Meliza
Daniel
D
Margoliash
Henry D I
HD
Abarbanel
D000200:Action Potentials; D000818:Animals; D003198:Computer Simulation; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009474:Neurons / Q000502:physiology*; D012044:Regression Analysis