Temporal Code-Driven Stimulation: Definition and Application to Electric Fish Signaling.

Closed-loop activity-dependent stimulation is a powerful methodology to assess information processing in biological systems. In this context, the development of novel protocols, their implementation in bioinformatics toolboxes and their application to different description levels open up a wide range of possibilities in the study of biological systems. We developed a methodology for studying biological signals representing them as temporal sequences of binary events.

Signature neural networks: definition and application to multidimensional sorting problems.

In this paper we present a self-organizing neural network paradigm that is able to discriminate information locally using a strategy for information coding and processing inspired in recent findings in living neural systems. The proposed neural network uses: 1) neural signatures to identify each unit in the network; 2) local discrimination of input information during the processing; and 3) a multicoding mechanism for information propagation regarding the who and the what of the information. The local discrimination implies a distinct processing as a function of the neural signature recognition and a local transient memory.

A discrete model of neural ensembles.

A discrete model of an ensemble of identical stochastic integrate-and-fire neurons is used to study the patterns of activity in populations of neurons that exchange excitatory messages. In a regime with small interactions among the units, the effect of the message exchange is to reduce the dispersion of the firing period of the individual neurons. In a strong interaction regime, a number of activity clusters emerge in the ensemble.