Comparison of deterministic and stochastic state transitions in the brain from the perspective of control theory (IMAGE)

University of Tokyo

Comparison of deterministic and stochastic state transitions in the brain from the perspective of control theory

Caption

The previous framework (left) fails to take into account noises of the brain. The brain state transitions were written as point-to-point, the dynamics as deterministic, and the control cost as the integral of the squared control input. In the current framework (right), the research team introduced a stochastic model, in which brain state transitions were considered as probability distribution to probability distribution, dynamics as stochastic process, and the control cost as KL divergence.

Credit

Shunsuke Kamiya, The University of Tokyo

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