Synchronous Phenomena for Two-Layered Neural Network with Chaotic Neurons
We propose a mathematical model of visual selective attention using a two-layered neural network, based on an assumption proposed by Desimone and Duncan. We use a spiking neuron model proposed by Hayashi and Ishizuka, which generates periodic spikes, quasiperiodic spikes and chaotic spikes. The neural network consists of a layer of hippocampal formation and that of visual cortex. In order to clarify an attention shift, we solve numerically a set of the first-order ordinary differential equations, which describe a time-evolution of neurons. The visual selective attention is considered as the synchronous phenomena between the firing times of the neurons in the hippocampal formation and those in a part of the visual cortex in the present model.
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- 1.Crick, F.: Function of the Thalamic Reticular Complex: The searchlight hypothesis. In: Proceedings of the National Academy of Sciences USA 81, pp. 4586–4590 (1984)Google Scholar
- 2.Desimone, R., Duncan, J.: Neural Mechanisms of Selective Visual Attention. Annu. Rev. Neurosci., 193–222 (1995)Google Scholar
- 4.Iijima, T., Witter, M.P., Ichikawa, M., Tominaga, T., Kajiwara, R., Matsumoto, G.: Entorhinal-Hippocampal Interactions Revealed by Real-Time Imaging. Science, 1176–1179 (1996)Google Scholar