Budget Amount *help |
¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2020: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2019: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2018: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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Outline of Final Research Achievements |
In this study, we introduced brain anatomical structures that are ubiquitous across brain regions as initial constraint into recurrent neural network (RNNs). We evaluated their roles in computation and showed that the structural distinction between excitatory and inhibitory neurons contributes to prevent overfitting. Moreover, the partial connectivity contributes to the improvement of fault tolerance of RNNs. These structures complementarily work and improve the performance and fault tolerance of the network.
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