A computational tool to simulate correlated activity in neural circuits.
A new computational approach to study correlated neural activity is presented. Simulating Elementary Neural NEtworks for Correlation Analysis (SENNECA) is a specific-purpose simulator oriented to small circuits of realistic neurons. The model neuron that it implements can reproduce a wide scope of integrate-and-fire models by simply adjusting the parameter set. Three different distributions of SENNECA are available: an easy-to-use web-based version, a Matlab (Windows and Linux) script, and a C++ class library for low-level coding. The main features of the simulator are explained, and several examples of neural activity analysis are given to illustrate the potential of this new tool.
Veredas
F J
FJ
Departamento de Lenguajes y Ciencias de la Computación, ETSI Informática, Universidad de Málaga, Bulevar de Louis Pasteur s/n, E-29071 Málaga, Spain. fvn@geb.uma.es
Vico
F J
FJ
Alonso
J M
JM
D000818:Animals; D001921:Brain / Q000033:anatomy & histology / Q000502:physiology; D019295:Computational Biology / Q000379:methods* / Q000706:statistics & numerical data; D003198:Computer Simulation; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000033:anatomy & histology* / Q000502:physiology*; D016571:Neural Networks, Computer; D012984:Software