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.
Katayama
Katsuki
K
Research Institute of Electrical Communication, Tohoku University, Sendai 980-8577, Japan. katayama@riec.tohoku.ac.jp
Yano
Masafumi
M
Horiguchi
Tsuyoshi
T
D000200:Action Potentials / Q000502:physiology; D001288:Attention / Q000502:physiology*; D006624:Hippocampus / Q000166:cytology / Q000502:physiology; D006801:Humans; D008959:Models, Neurological; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology; D013997:Time Factors; D014793:Visual Cortex / Q000166:cytology / Q000502:physiology; D014796:Visual Perception / Q000502:physiology*