Cerebellar motor learning: when is cortical plasticity not enough?

Classical Marr-Albus theories of cerebellar learning employ only cortical sites of plasticity. However, tests of these theories using adaptive calibration of the vestibulo-ocular reflex (VOR) have indicated plasticity in both cerebellar cortex and the brainstem. To resolve this long-standing conflic...

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Main Authors: John Porrill, Paul Dean
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2007-10-01
Series:PLoS Computational Biology
Online Access:https://doi.org/10.1371/journal.pcbi.0030197
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author John Porrill
Paul Dean
author_facet John Porrill
Paul Dean
author_sort John Porrill
collection DOAJ
description Classical Marr-Albus theories of cerebellar learning employ only cortical sites of plasticity. However, tests of these theories using adaptive calibration of the vestibulo-ocular reflex (VOR) have indicated plasticity in both cerebellar cortex and the brainstem. To resolve this long-standing conflict, we attempted to identify the computational role of the brainstem site, by using an adaptive filter version of the cerebellar microcircuit to model VOR calibration for changes in the oculomotor plant. With only cortical plasticity, introducing a realistic delay in the retinal-slip error signal of 100 ms prevented learning at frequencies higher than 2.5 Hz, although the VOR itself is accurate up to at least 25 Hz. However, the introduction of an additional brainstem site of plasticity, driven by the correlation between cerebellar and vestibular inputs, overcame the 2.5 Hz limitation and allowed learning of accurate high-frequency gains. This "cortex-first" learning mechanism is consistent with a wide variety of evidence concerning the role of the flocculus in VOR calibration, and complements rather than replaces the previously proposed "brainstem-first" mechanism that operates when ocular tracking mechanisms are effective. These results (i) describe a process whereby information originally learnt in one area of the brain (cerebellar cortex) can be transferred and expressed in another (brainstem), and (ii) indicate for the first time why a brainstem site of plasticity is actually required by Marr-Albus type models when high-frequency gains must be learned in the presence of error delay.
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spelling doaj.art-64f1c3f6b95648c29318698b540a21a32022-12-21T23:39:05ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582007-10-013101935195010.1371/journal.pcbi.0030197Cerebellar motor learning: when is cortical plasticity not enough?John PorrillPaul DeanClassical Marr-Albus theories of cerebellar learning employ only cortical sites of plasticity. However, tests of these theories using adaptive calibration of the vestibulo-ocular reflex (VOR) have indicated plasticity in both cerebellar cortex and the brainstem. To resolve this long-standing conflict, we attempted to identify the computational role of the brainstem site, by using an adaptive filter version of the cerebellar microcircuit to model VOR calibration for changes in the oculomotor plant. With only cortical plasticity, introducing a realistic delay in the retinal-slip error signal of 100 ms prevented learning at frequencies higher than 2.5 Hz, although the VOR itself is accurate up to at least 25 Hz. However, the introduction of an additional brainstem site of plasticity, driven by the correlation between cerebellar and vestibular inputs, overcame the 2.5 Hz limitation and allowed learning of accurate high-frequency gains. This "cortex-first" learning mechanism is consistent with a wide variety of evidence concerning the role of the flocculus in VOR calibration, and complements rather than replaces the previously proposed "brainstem-first" mechanism that operates when ocular tracking mechanisms are effective. These results (i) describe a process whereby information originally learnt in one area of the brain (cerebellar cortex) can be transferred and expressed in another (brainstem), and (ii) indicate for the first time why a brainstem site of plasticity is actually required by Marr-Albus type models when high-frequency gains must be learned in the presence of error delay.https://doi.org/10.1371/journal.pcbi.0030197
spellingShingle John Porrill
Paul Dean
Cerebellar motor learning: when is cortical plasticity not enough?
PLoS Computational Biology
title Cerebellar motor learning: when is cortical plasticity not enough?
title_full Cerebellar motor learning: when is cortical plasticity not enough?
title_fullStr Cerebellar motor learning: when is cortical plasticity not enough?
title_full_unstemmed Cerebellar motor learning: when is cortical plasticity not enough?
title_short Cerebellar motor learning: when is cortical plasticity not enough?
title_sort cerebellar motor learning when is cortical plasticity not enough
url https://doi.org/10.1371/journal.pcbi.0030197
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