Literature DB >> 24916296

Automatic and controlled processing in the corticocerebellar system.

Narender Ramnani1.   

Abstract

During learning, performance changes often involve a transition from controlled processing in which performance is flexible and responsive to ongoing error feedback, but effortful and slow, to a state in which processing becomes swift and automatic. In this state, performance is unencumbered by the requirement to process feedback, but its insensitivity to feedback reduces its flexibility. Many properties of automatic processing are similar to those that one would expect of forward models, and many have suggested that these may be instantiated in cerebellar circuitry. Since hierarchically organized frontal lobe areas can both send and receive commands, I discuss the possibility that they can act both as controllers and controlled objects and that their behaviors can be independently modeled by forward models in cerebellar circuits. Since areas of the prefrontal cortex contribute to this hierarchically organized system and send outputs to the cerebellar cortex, I suggest that the cerebellum is likely to contribute to the automation of cognitive skills, and to the formation of habitual behavior which is resistant to error feedback. An important prerequisite to these ideas is that cerebellar circuitry should have access to higher order error feedback that signals the success or failure of cognitive processing. I have discussed the pathways through which such feedback could arrive via the inferior olive and the dopamine system. Cerebellar outputs inhibit both the inferior olive and the dopamine system. It is possible that learned representations in the cerebellum use this as a mechanism to suppress the processing of feedback in other parts of the nervous system. Thus, cerebellar processes that control automatic performance may be completed without triggering the engagement of controlled processes by prefrontal mechanisms.
© 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  automatic; cerebellum; cognitive; controlled; dual systems; forward models; learning; prefrontal cortex; skills

Mesh:

Year:  2014        PMID: 24916296     DOI: 10.1016/B978-0-444-63356-9.00010-8

Source DB:  PubMed          Journal:  Prog Brain Res        ISSN: 0079-6123            Impact factor:   2.453


  20 in total

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