Dynamic Neural Network Derived from the Olfactory System with Examples of Applications

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概要

• 論文の詳細を見る

• The dynamics of an artificial neural network derived from a biological system, and its two applications to engineering problems are examined. The model has a multi-layer structure simulating the primary and secondary components in the olfactory system. The basic element in each layer is an oscillator which simulates the interactions between excitatory and inhibitory local neuron populations. Chaotic dynamics emerges from interactions within and between the layers, which are connected to each other by feedforward and feedback lines with distributed delays. A set of electroencephalogram (EEG)obtained from mammalian olfactory system yields aperiodic oscillation with 1/f characteristics in its FFT power spectrum. The EEG also reveals abrupt state transitions between a basal and an activated state. The activated state with each inhalation consists of a burst of oscillation at a common time-varying instantaneous frequency that is spatially amplitude-modulated (AM). The spatial pattern of the activated state seems to represent the class of the input to the system, which simulates the input from sensory receptors. The KIII model of the olfactory system yields sustained aperiodic oscillation with "1/f" spectrum by adjustment of its parameters. Input in the form of a spatially distributed step function induces a state transition to an activated state. This property gives the model its utility in pattern classification. Four different methods (SD, RMS, PCA and FFT) were applied to extract AM patterns of the common output wave forms of the model. The pattern classification capability of the model was evaluated, and synchronization of the output wave form was shown to be crucial in PCA and FFT methods. This synchronization has also been suggested to have an important role in biological systems related to the information extraction by spatiotemporal integration of the output of a transmitting area of cortex by a receiving area.

• 社団法人電子情報通信学会の論文
• 1995-07-25

著者

• Freeman W

  Univ. California Ca Usa

• Shimoide Koji

  Asahikasei Microsystems Co., Ltd.

• Freeman Walter

  Department of Molecular and Cellbiology, University of California

• Shimoide Koji

  Asahikasei Microsystems Co. Ltd.

• Freeman Walter

  Department Of Molecular & Cell Biology University Of California At Berkeley

関連論文

• Dynamic Neural Network Derived from the Olfactory System with Examples of Applications
• Indirect biological measures of consciousness from field studies of brains as dynamical systems

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