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Katsuki Katayama

Publications and source records attributed to Katsuki Katayama.

2 recordsLinked to original sources

Neural network model of selective visual attention using Hodgkin-Huxley equation.

We propose a mathematical model of selective visual attention using a two-layered neural network with neurons described by the Hodgkin-Huxley equation in order to investigate part of the assumption proposed by Desimone and Duncan. The neural network consists of a layer of hippocampal formation and of visual cortex. A frequency of firing and a firing time for each neuron and also a correlation of the firing times between neurons are calculated numerically to clarify an attention state, a nonattention state, and an attention shift. We find that synchronous phenomena occur not only for the frequency but also for the firing time between the neurons in the hippocampal formation and those in a part of the visual cortex in our model. It also turns out that the attention shift is performed quickly in our model.

Action Potentials↗

Models of MT and MST areas using wake-sleep algorithm.

We present two-layered neural network models with Q (> or =2)-states neurons for a system with middle temporal (MT) neurons and medial superior temporal (MST) neurons by using a wake-sleep algorithm proposed by Hinton et al.; we notice that the wake-sleep algorithm consists of local learning rules. We first investigate a model with binary neurons for response properties of the MST neurons to optical flows as for various types of motion. We next extend the model with binary neurons to a model with Q (> or =3)-states neurons and investigate the response properties of the MST neurons for various values of Q (> or =3). We obtain better response properties for the model with Q (> or =3)-states neurons than for the one with binary neurons.

Algorithms↗