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Our results for the first time revealed how a strategy to achieve the matching behavior is beneficial to reward maximization, and how the ignorance of the relevant information leads to the matching behavior.
This effectively discourages frequent switching, and animals then often exhibit the matching behavior captured by Equation 1.
In contrast, the matching strategy with the incorrect selection of information sources may replicate various deviations from the matching behavior, such as the under/over-matching observed in various situations [25] [28].
Decision-making models to reproduce the matching behavior have been proposed[9], [16], [17], and recent computational studies pointed out possible origins of matching behavior in biological neural systems[18], [19].
We start this inquiry by asking whether the matching behavior was optimal in this task.
To gain insight into the processes leading to the matching behavior, we modeled the animals' trial-to-trial behavior using a mechanistic model.
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The model also explained very faithfully the animals' matching behavior and their behavior just after the payoff ratio transition.
This is because when we scanned in the lateral center of the cell nucleus, the focus will also be located in the axial center of the cell nucleus, while the interesting THG phase matching behavior under the tightly focused Gaussian beam play a role.
The finding that matching behavior is observed in a task that does not impose it provides important insights into the nature of matching behavior.
A question of particular interest is why the animals exhibited matching behavior in this task.
This width dependence allows explaining gate voltage matching behavior in the sub-threshold area used in low power analog applications.
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