A computational tool to simulate correlated activity in neural circuits

F J Veredas; F J Vico; J M Alonso

doi:10.1016/j.jneumeth.2003.12.026

A computational tool to simulate correlated activity in neural circuits

J Neurosci Methods. 2004 Jun 15;136(1):23-32. doi: 10.1016/j.jneumeth.2003.12.026.

Authors

F J Veredas¹, F J Vico, J M Alonso

Affiliation

¹ 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

PMID: 15126042
DOI: 10.1016/j.jneumeth.2003.12.026

Abstract

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.

Publication types

Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, P.H.S.

MeSH terms

Animals
Brain / anatomy & histology
Brain / physiology
Computational Biology / methods*
Computational Biology / statistics & numerical data
Computer Simulation
Humans
Models, Neurological
Nerve Net / anatomy & histology*
Nerve Net / physiology*
Neural Networks, Computer
Software*

Grants and funding

EY 05253/EY/NEI NIH HHS/United States