1995 Fiscal Year Final Research Report Summary
Self-Organization of Polymorphic Circuits in Cultured Neural Networks
| Project/Area Number |
06454660
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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 |
Biophysics
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| Research Institution | TOHOKU UNIVERSITY |
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Principal Investigator |
YANO Masafumi Tohoku University Research Institute of Electrical Communication, 電気通信研究所, 教授 (80119635)
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| Co-Investigator(Kenkyū-buntansha) |
MAKINO Yoshinari Tohoku University Research Institute of Electrical Communication, 電気通信研究所, 助手 (90250844)
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| Project Period (FY) |
1994 – 1995
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| Keywords | Neural Network / Polymorphic Circuit / Monoamines / Information Processing in Brain |
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| Research Abstract |
In general, an anatomical neural network in sensory and motor systems subserves various functions of information processing. This is so-called "polymorphic" network concept. A polymorphic network is a network embedded with multiple circuits which are defined by functional interactions between neurons. For undersatanding the function of the brain such as sensory perception, motor control, learning or memory, it is very important to clarify emerging principles of the polymorphic circuits. In this research, we have made physiological and modeling studies about the self-organization of the polymorphic circuits, and obtained following results.
1. Using a KYS oscillator as a neural element, we modeled a central pattern generator (CPG) of the motor system. The polymorphic property of the CPG could be emerged by controlling intrinsic neural property such as postinhibitory rebound and resting membrane potential, without changing synaptic connectivity.
2. Isolated olfactory network of slug's CNS showed polymorphic property by perfusing biogenic monoamines in extracellular solution. This suggested that monoamines play important roles in emerging the polymorphic property of a biological sensory networks.
3. In biological systems, monoamines change intrinsic neural properties through the intracellular Ca^<++>. Therefore we studied a network-dynamics of the intracellular Ca^<++> with computational simulation, and demonstrated that global Ca^<++> patterns in a network could be emerged according to various external conditions.
These results suggest how the polymorphic property is controlled in biological network, and might provide a new insight into rules for neural network operation.
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