| Budget Amount *help |
¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2018: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2017: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2016: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Outline of Final Research Achievements |
I developed a model to explain neural activity from the viewpoint of the simplicity of neural circuits. Assuming that a circuit capable of performing a task is formed in the cerebral cortex, the algorithmic information theory enables us to regard the circuit as the simplest circuit capable of performing the task. Here the simplicity of a circuit or probability of a circuit in a population of randomly generated circuits was measured by the L2-norm of the connection weight matrix of the neurons. I obtained the simplest circuits capable of performing several tasks to formulate the problem as an optimization problem of the correlation matrix of firing activity by using the kernel representation of recurrent neural networks with infinite neurons. I found that the simplest circuit exhibited sustained and ramping activities, which are observed in motor areas of the cerebral cortex.
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