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In traditional computational models of the human mind, it is assumed that mental processes respect the semantics of mental states, and the only computational explanation for such mental processes is a computing mechanism that manipulates symbols related to the semantic properties of mental states [14].
The model provided a computational explanation for the mechanisms of lateral control skill learning.
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The SYSTEM_MODEL is directed to give a computational explanation of how the interaction between CSNTC modules allows for a better cortico-cortical communication of coarse-grained information, e.g. to control the different movements to perform.
Successively, Computational Functionalism arises as an explanation for mental acts and states contrary to behaviorism and neurologism, arguing that mental operations could be computational functions capable of being realized in multiple ways in various material bases (Putnam-at the beginning).
The obtained computational results provide a possible explanation for the experimentally observed high diastereoselectivity.
With the help of these computational techniques, we developed an explanation for the final part of the pattern formation, i.e. structural dynamics related to the stripes fragmentation.
Evaluation of non-linear multi-modes poses huge computational challenges, which is the explanation for very limited reports on the subject in the literature so far.
Computational modelling offers a plausible explanation for this pronounced timing-dependence.
The computational simulation results provided a reasonable explanation for the structure-activity relationships of auxin and its synthetic analogues in view of energy.
The computational analysis thus provides a mechanistic explanation for the observed biomarker, which represents a novel testable hypothesis.
These computational results provide a possible mechanistic explanation for the extensive clinical manifestations observed in porphyria patients.
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