Contour enhancement, short-term memory, and constancies in reverberating neural networks

Author(s): Grossberg, S. |

Year: 1973

Citation: Studies in Applied Mathematics, 52, 213-257

Abstract: A model of the nonlinear dynamics of reverberating on-center off-surround networks of nerve cells, or of cell populations, is analysed. The on-center off-surround anatomy allows patterns to be processed across populations without saturating the populations response to large inputs. The signals between populations are made sigmoid functions of population activity in order to quench network noise, and yet store sufficiently intense patterns in short term memory (STM). There exists a quenching threshold: a population s activity will be quenched along with network noise if it falls below the threshold; the pattern of suprathreshold population activities is contour enhanced and stored in STM. Varying arousal level can therefore influence which pattern features will be stored. The total suprathreshold activity of the network is carefully regulated. Applications to seizure and hallucinatory phenomena, to position codes for motor control, to pattern discrimination, to influences of novel events on storage of redundant relevant cues, and to the construction of a sensory-drive heterarchy are mentioned, along with possible anatomical substrates in neocortex, hypothalamus, and hippocampus.

Topics: Biological Learning, Mathematical Foundations of Neural Networks, Models: Other,

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