Aperiodic dynamics and the self-organization of cognitive maps in autonomous agents
✍ Scribed by Derek Harter; Robert Kozma
- Publisher
- John Wiley and Sons
- Year
- 2006
- Tongue
- English
- Weight
- 400 KB
- Volume
- 21
- Category
- Article
- ISSN
- 0884-8173
No coin nor oath required. For personal study only.
✦ Synopsis
When we look at the dynamics produced by biological neuronal populations, we are immediately struck by the fact that aperiodic, chaotic-like dynamics appear to be the normal operating state of such systems. Recent work has shown that such aperiodic dynamics, at least in perceptual systems, may not only be the result of random perturbations experienced by the system from external stimulation, but that the brain itself generates aperiodic dynamics to deal more flexibly and reliably with noisy environmental stimulation. Complex systems concepts are helping us to understand the properties of nonlinear systems that are fundamental for the emergence of complex spatiotemporal patterns in natural and biological systems. Advances in neuroscience and computational neurodynamics are applying these concepts of self-organization to understanding the spatiotemporal patterns observed in biological brains. In this article, we introduce a neural population model that is capable of replicating the generation of these types of aperiodic dynamics observed in biological brains. We use the model to self-organize cognitive maps in an autonomous agent through the agent's interaction with its environment. We show how such high-dimensional spatiotemporal dynamics may be shaped by environmental input and learning to form chaotic attractors that come to represent "meanings" for the agent. We discuss how the internal generation of such aperiodic dynamics may aid in the formation and recognition of such noisy environmental stimuli in biological organisms in general and in our simulated agents specifically.