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Some adherents of CTM do deny that the brain runs an associative network (see, e.g., Gallistel and King 2009, who appear to deny that there is any scientific level of explanation that association is intimately involved in), but they do so on separate empirical grounds and not because of any logical inconsistency with an associative brain implementing a classical mind.
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In fact, the dopamine neurons in the brain implement a form of TD learning.
Cognitive neuroscientists study how the brain implements particular cognitive processes such as perception, learning, and decision-making.
Here, we investigate how the brain implements these learning processes simultaneously, and what determines the relative contribution of each system during decision-making.
Some doubt that the brain implements anything resembling digital computation, i.e., computation over discrete configurations of digits (Piccinini and Bahar 2013).
The neural network illuminates how the brain implements the Turing-style model, just as a description in terms of logic gates illuminates how a personal computer executes a program in a high-level programming language.
This was hypothesized to be a mechanism by which the brain implements modification of Tit-for-tat so as to prevent occasional defections for informational probing from unravelling cooperation permanently.
An influential theory of how our brain implements cognitive control is the conflict monitoring hypothesis.
If the brain implements predictive coding, then its functional architecture ought to have particular attributes.
Here we demonstrate that the brain implements an alternative solution in which retinal velocity patterns are themselves used to dissociate translations from rotations.
Whether the brain implements a nonlinear drive-reduction reward (as in Equation 2) or a linear approximation of it (as in Equation 13) can be examined experimentally.
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