Journal ArticleDOI
Central pattern generating and recognizing in olfactory bulb: A correlation learning rule
TLDR
An input correlation rule is applied to a set of fully interconnected coupled oscillators that comprises a dynamical model of the olfactory bulb so as to form “templates” of oscillators with strengthened interconnection in respect to inputs classed as “learned.”About:
This article is published in Neural Networks.The article was published on 1988-01-01. It has received 119 citations till now. The article focuses on the topics: Learning rule & Artificial neural network.read more
Citations
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Journal ArticleDOI
Phantom auditory perception (tinnitus): mechanisms of generation and perception
TL;DR: Existing theories and their extrapolation are presented, together with some new potential mechanisms of tinnitus generation, encompassing the involvement of calcium and calcium channels in cochlear function, with implications for malfunction and aging of the auditory and vestibular systems.
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Model of biological pattern recognition with spatially chaotic dynamics
Yong Yao,Walter J. Freeman +1 more
TL;DR: Computer simulation of the dynamics of a distributed model of the olfactory system that is aimed at understanding the role of chaos in biological pattern recognition shows that the adaptive behavior of the system is scaling invariant, and it is independent of the initial conditions at the transition from one wing to another.
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Original Contribution: Dynamic link of memory-Chaotic memory map in nonequilibrium neural networks
TL;DR: It is suggested that the cortical chaos may serve for dynamically linking true memory as well as a memory search in nonequilibrium neural networks.
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Odour-modulated collective network oscillations of olfactory interneurons in a terrestrial mollusc
Alan Gelperin,David W. Tank +1 more
TL;DR: A network of olfactory inter-neurons in the cerebral ganglion of the terrestrial mollusc Limax maximus also displays coherent oscillations in LFP which are modified by odour input, which could be central to the odour recognition and odour learning ability of Limax.
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Chaotic resonance — methods and applications for robust classification of noisy and variable patterns
Robert Kozma,Walter J. Freeman +1 more
TL;DR: A theory of stochastic chaos is developed, in which aperiodic outputs with 1/f2 spectra are formed by the interaction of globally connected nodes that are individually governed by point attractors under perturbation by continuous white noise.
References
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Neural networks and physical systems with emergent collective computational abilities
TL;DR: A model of a system having a large number of simple equivalent components, based on aspects of neurobiology but readily adapted to integrated circuits, produces a content-addressable memory which correctly yields an entire memory from any subpart of sufficient size.
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A Nonlinear Mapping for Data Structure Analysis
TL;DR: An algorithm for the analysis of multivariate data is presented along with some experimental results that is based upon a point mapping of N L-dimensional vectors from the L-space to a lower-dimensional space such that the inherent data "structure" is approximately preserved.
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How brains make chaos in order to make sense of the world
TL;DR: A model to describe the neural dynamics responsible for odor recognition and discrimination is developed and it is hypothesized that chaotic behavior serves as the essential ground state for the neural perceptual apparatus and a mechanism for acquiring new forms of patterned activity corresponding to new learned odors is proposed.