| Project/Area Number |
26330288
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Multi-year Fund |
|---|
| Section | 一般 |
|---|
| Research Field |
Soft computing
|
|---|
| Research Institution | Ritsumeikan University |
|---|
Principal Investigator |
Tsubo Yasuhiro 立命館大学, 情報理工学部, 准教授 (40384721)
|
|---|
| Co-Investigator(Renkei-kenkyūsha) |
ISOMURA Yoshikazu 玉川大学, 脳科学研究所, 教授 (00415077)
|
|---|
| Project Period (FY) |
2014-04-01 – 2017-03-31
|
| Project Status |
Completed (Fiscal Year 2016)
|
| Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2016: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2015: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2014: ¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
|
|---|
| Keywords | 脳・神経 / 神経科学 / 情報工学 / 生体生命情報学 / ソフトコンピューティング |
|---|
| Outline of Final Research Achievements |
Aiming to develop a complementary system to the conventional computer system, we attempted to construct a general stochastic information processor inspired by the stochastic property of neuronal activity. First, we expanded "constrained entropy maximization principle", which is an information processing principle obtained from an observation of cortical neural activity, so that it can be applied to general stochastic elements including a stochastic neuronal pulse generator. Second, by constructing cortical neural networks and analyzing their firing activity by using numerical simulation, we analyzed how the statistical property of the output spike sequence depends on the statistical properties of a local network structure such as the degree of bidirectional coupling and the number of triangular motifs.
|
