Can't get you out of my head: a connectionist model of cyclic rehearsal

Authors:
Herbert Jaeger;Douglas Eck
Affiliations:
Jacobs University Bremen;University of Montreal, Department of Computer Science, Canada
Venue:
ZiF'06 Proceedings of the Embodied communication in humans and machines, 2nd ZiF research group international conference on Modeling communication with robots and virtual humans
Year:
2006

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Abstract

Humans are able to perform a large variety of periodic activities in different modes, for instance cyclic rehearsal of phone numbers, humming a melody sniplet over and over again. These performances are, to a certain degree, robust against perturbations, and it often suffices to present a new pattern a few times only until it can be "picked up". From an abstract mathematical perspective, this implies that the brain, as a dynamical system, (1) hosts a very large number of cyclic attractors, such that (2) if the system is driven by external input with a cyclic motif, it can entrain to a closely corresponding attractor in a very short time. This chapter proposes a simple recurrent neural network architecture which displays these dynamical phenomena. The model builds on echo state networks (ESNs), which have recently become popular in machine learning and computational neuroscience.