Information Dynamics and Emergent Computation in Recurrent Circuits of
T. Natschlaeger and W. Maass
An efficient method using Bayesian and linear classifiers is presented for
analyzing the dynamics of information in high dimensional circuit states, and
applied to investigate emergent computation in generic cortical microcircuit
models. It is shown that such recurrent circuits of spiking neurons have an
inherent capability to carry out rapid computations on complex spike
patterns, merging information contained in the order of spike arrival with
previously acquired context information.
Reference: T. Natschlaeger and W. Maass.
Information dynamics and emergent computation in recurrent circuits of spiking
In S. Thrun, L. Saul, and B. Schoelkopf, editors, Proc. of NIPS 2003,
Advances in Neural Information Processing Systems, volume 16, pages
1255-1262, Cambridge, 2004. MIT Press.