An Empirical Evaluation Framework for Qualifying Dynamic Neural Fields

Lucian Alecu (1, 2) , Hervé Frezza-Buet (2)

1 CORTEX - Neuromimetic intelligence
2 SUPELEC-Campus Metz

In this paper, the behavior of dynamic neural fields is studied through the lens of performance. As an alternative to the currently available analytical instruments, an empirical evaluation methodology is proposed in order to examine the dynamic quality of a field. This consists of simulating the field through various key scenarios and compare the observed behavior to an optimal expected one. Some desired effects concerning the evolution of an ideal field are inspected, and a performance criterion is defined accordingly. Practically, this approach implements a generic benchmark framework for qualifying neural fields, allowing to inspect the evolution of the model in different key situations. The presented methodology provides a basis for a methodological computational approach towards adjusting the free parameters of the fields in order to satisfy specific desired properties.

Mots clés: Neuronal models; Simulation

Domaines: Neurosciences [q-bio.NC]; Neurosciences

Lucian Alecu, Hervé Frezza-Buet. An Empirical Evaluation Framework for Qualifying Dynamic Neural Fields. Deuxième conférence française de Neurosciences Computationnelles, "Neurocomp08", Oct 2008, Marseille, France. ⟨hal-00331551⟩