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The complex behavior of the bifurcating neuron is characterized. It is shown to be capable of exhibiting phase-locking and synchronization, and that it exhibits a host of firing modalities that parallel those observed by neurophysiologists in the living neuron including chaotic firing and that it is capable of bifurcating between these firing modalities depending on the nature of its input. The implications of this complex behavior for the introduction of a new generation of bifurcating neural networks, that are capable of using chaos as adaptive intrinsic noise, for self-annealing and directed intelligent search of the phase-space of bifurcating networks are discussed. It is argued that the bifurcating neuron concept is key to building new physical structures (bifurcating networks) in which one can study the roles of bifurcation, synchronicity, and chaos in collective nonlinear dynamical signal processing and is moreover key to modeling and understanding higher-level cortical signal processing such as feature-binding and cognition, and that its ease of implementation in analog hardware promises to offer important technological benefits. |
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CITATIONS
Cited by 1 scholarly publication.
Neurons
Neural networks
Capacitors
Action potentials
Resistance
Oscillators
Chaos
