1989 Fiscal Year Final Research Report Summary
Analysis on High-Speed Computation Mechanisms of the Brain Based on Impulse-Processing Neural Networks
| Project/Area Number |
63460143
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| Research Category |
Grant-in-Aid for General Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
計測・制御工学
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| Research Institution | Tokyo Institute of Technology |
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Principal Investigator |
ICHIKAWA Atsunobu Tokyo Institute of Technology, Dept. Electronic Chem., Professor, 総理工, 教授 (60016714)
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| Co-Investigator(Kenkyū-buntansha) |
KUROGI Shuichi Kyushu Institute of Technology, Faculty of Engineering, Research Associate, 工学部, 助手 (40178124)
NAKAMURA Kiyohiko Tokyo Institute of Technology, Dept. Electronic Chem., Research Associate, 総理工, 助手 (10172397)
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| Project Period (FY) |
1988 – 1989
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| Keywords | Neural Network / Parallel Processing / Neuropopulation / Behavioral Learning / Synaptic Plasticity |
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| Research Abstract |
Analysis of behavior of impulse-processing neuropopulations based on physiological data has shown that neuropopulations of the brain can detect millisecond time differences in their activations and that the capacity has sufficient robustness against noises. This suggests a possibility that timing of activities of neural nuclei may control parallel processing of the brain in the several millisecond range to achieve high-speed computation.
A mathematical model of reward-mediated learning mechanisms of the neocortico-thalamic system was proposed using the model of impulse-processing neuropopulations. The model describes as functions of physiological parameters of single neurons how long the short-memory of the brain must last to perform the reward-mediated learning how many repetitions of learning are required for learning accomplishment. These functions provide theoretical estimation on the behavior of the above system according to physiological data on single neurons, which enables us to test the proposed model by examinig agreement of the estimation with real behavior of the system.
Behavior of the auditory pathway from ear to cortex, which is anatomically divided into five divisions, was investigated by constructing a mathematical model of the pathway according to physiological data on the five divisions. Computer simulation of the model behavior has shown,that the proposed model provides not only the capacity of recognizing isolated syllables and connected words in continuous speech but also describes typical response of single neurons observed in the real auditory system. This supports assumptions introduced to construct our model.
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