Cerebellar Motor Learning: When Is Cortical Plasticity Not Enough?

Abstract

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.

Modeling memory consolidation during posttraining periods in cerebellovestibular learning

“…This sliding mechanism is important for robust memory consolidation. In contrast, previous theoretical models (11)(12)(13)(14) use a nonHebbian rule, by which MF-VN synaptic weight decreases when the presynaptic MF and the PC innervating the same VN are coactive or coinactive, and it increases when only one of the two is active. Our model is therefore more biologically plausible with regard to the assumed learning rule.…”

“…In contrast to previous models (11)(12)(13)(14), our model takes into account the synaptic dynamics during posttraining periods explicitly and reproduces the posttraining memory transfer. Moreover, the explicit use of posttraining periods allows our model to naturally reproduce the spacing effect, whereby the total duration of posttraining periods is more important than that of training periods for long-term memory formation.…”

“…We also applied our model to OKR gain adaptation in gene-manipulated mice that exhibited peculiar changes in VOR gain (15)(16)(17). A computational model for VOR gain adaptation has been proposed (12), in which nuclear learning occurs simultaneously with cortical learning. In that model, nuclear memory forms fully during training and accumulates by repetition of training; posttraining periods were not considered explicitly, suggesting that the total duration of the training but not that of the posttraining periods determines the amount of nuclear memory formed.…”

“…Although several theoretical models have addressed the question of how multiple plasticity mechanisms work together in cerebellar motor learning (11)(12)(13)(14), none has explicitly taken the memory consolidation process during posttraining periods into consideration. Our model reproduced previously reported oculomotor behavioral data obtained from wild-type mice (8)(9)(10).…”

Distinct cerebellar engrams in short-term and long-term motor learning

“…long-term depression | high-voltage electron microscope | Golgi staining I mage stabilization in the visual field via the vestibulo-ocular reflex and optokinetic response requires accurate extraocular muscle synergies that rely on long-term plastic calibrations in the cerebellar flocculus (FL) and its downstream target vestibular nuclei (VN) (1)(2)(3)(4)(5)(6)(7)(8). Long-term depression (LTD) in parallel fiber-Purkinje cell (PF-PC) synapses has been postulated as a possible mechanism for this plastic calibration based on many lines of mutant mice that lack both LTD and learning (9)(10)(11)(12).…”