Neural Correlates of Reinforcement Learning in Mid-lateral Cerebellum

Sendhilnathan, Naveen; Semework, Mulugeta; Goldberg, Michael E.; Ipata, Anna E.

doi:10.1016/j.neuron.2020.05.021

Cited by 26 publications

(51 citation statements)

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“…A final alternative is that reward signals in the cerebellum are found more laterally in the cerebellum and thus reflect internal modelling of reward that is not directly connected to movement (Heffley and Hull, 2019;Sendhilnathan et al, 2020;Tsutsumi et al, 2019). Considering other recent results showing that climbing fibers provide predictive signals about movement parameters (Streng et al, 2018) the canonical view is still widely accepted (Apps et al, 2018;Sokolov et al, 2017).…”

Section: Multiple Cortical Loops With the Basal Ganglia And The Cerebmentioning

confidence: 99%

A Revised Computational Neuroanatomy for Motor Control

Haar

Donchin

2020

Journal of Cognitive Neuroscience

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We discuss a new framework for understanding the structure of motor control. Our approach integrates existing models of motor control with the reality of hierarchical cortical processing and the parallel segregated loops that characterize cortical–subcortical connections. We also incorporate the recent claim that cortex functions via predictive representation and optimal information utilization. Our framework assumes each cortical area engaged in motor control generates a predictive model of a different aspect of motor behavior. In maintaining these predictive models, each area interacts with a different part of the cerebellum and BG. These subcortical areas are thus engaged in domain-appropriate system identification and optimization. This refocuses the question of division of function among different cortical areas. What are the different aspects of motor behavior that are predictively modeled? We suggest that one fundamental division is between modeling of task and body whereas another is the model of state and action. Thus, we propose that the posterior parietal cortex, somatosensory cortex, premotor cortex, and motor cortex represent task state, body state, task action, and body action, respectively. In the second part of this review, we demonstrate how this division of labor can better account for many recent findings of movement encoding, especially in the premotor and posterior parietal cortices.

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Section: Multiple Cortical Loops With the Basal Ganglia And The Cerebmentioning

confidence: 99%

A Revised Computational Neuroanatomy for Motor Control

Haar

Donchin

2020

Journal of Cognitive Neuroscience

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“…Recent physiological recording studies in behaving animals have highlighted the role of cerebellum in reward processing (10)(11)(12)(76)(77)(78)(79)(80). Specifically, individual GrCs can encode reward delivery, omission, or expectation (10).…”

Section: Discussionmentioning

confidence: 99%

The Relationship between Birth Timing, Circuit Wiring, and Physiological Response Properties of Cerebellar Granule Cells

Shuster

Wagner

Pan-Doh

et al. 2021

Preprint

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Cerebellar granule cells (GrCs) are usually regarded as a uniform cell type that collectively expands the coding space of the cerebellum by integrating diverse combinations of mossy fiber inputs. Accordingly, stable molecularly or physiologically defined GrC subtypes within a single cerebellar region have not been reported. The only known cellular properties that distinguishes otherwise homogeneous GrCs is the correspondence between GrC birthtime and the depth of the molecular layer to which their axons (parallel fibers) project. To determine the role birth timing plays in GrC wiring and function, we developed genetic strategies to access early- and late-born GrCs. We initiated retrograde monosynaptic rabies virus tracing from control, early-born, and late-born GrCs, revealing the different patterns of mossy fiber input to GrCs in vermis lobule 6 and simplex, as well as to early- and late-born GrCs of vermis lobule 6: sensory and motor nuclei provide more input to early-born GrCs, while basal pontine and cerebellar nuclei provide more input to late-born GrCs. In vivo multi-depth 2-photon Ca2+ imaging of parallel fibers of early- and late-born GrCs revealed representations of diverse task variables and stimuli by both populations, with differences in the proportions of parallel fibers encoding movement, reward anticipation, and reward consumption. Our results suggest neither organized parallel processing nor completely random organization of mossy fiber-->GrC circuitry, but instead a moderate influence of birth timing on GrC wiring and encoding. Our imaging data also suggest that GrCs can represent general aversiveness, in addition to recently described reward representations.

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“…Spontaneous increases or decreases in SS discharge can, on occasion, precede as well as follow the occurrence of CSs in the same Purkinje cell (64,(201)(202)(203)(204). Under certain stimulus and recording conditions the modulation SS discharge occurs in the absence of modulation of CS discharge.…”

Section: Cerebellar Functions and Cellular Mechanismsmentioning

confidence: 99%

“…Under certain stimulus and recording conditions the modulation SS discharge occurs in the absence of modulation of CS discharge. In these instances, the SSs are often regarded as a consequence of a mossy fiber→granule cell→parallel fiber→Purkinje cell throughput that is independent of the climbing fiber pathway with the possible exception of undefined "novel" responses evoked by climbing fibers (201)(202)(203)(204). Given the significance of sagittal zones in lobules IX-X it would seem useful to learn if zonal architecture also influences the responses of Purkinje cells in other cerebellar lobules.…”

Section: Cerebellar Functions and Cellular Mechanismsmentioning

confidence: 99%

Adaptive Balance in Posterior Cerebellum

Barmack

Pettorossi

2021

Front. Neurol.

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Vestibular and optokinetic space is represented in three-dimensions in vermal lobules IX-X (uvula, nodulus) and hemisphere lobule X (flocculus) of the cerebellum. Vermal lobules IX-X encodes gravity and head movement using the utricular otolith and the two vertical semicircular canals. Hemispheric lobule X encodes self-motion using optokinetic feedback about the three axes of the semicircular canals. Vestibular and visual adaptation of this circuitry is needed to maintain balance during perturbations of self-induced motion. Vestibular and optokinetic (self-motion detection) stimulation is encoded by cerebellar climbing and mossy fibers. These two afferent pathways excite the discharge of Purkinje cells directly. Climbing fibers preferentially decrease the discharge of Purkinje cells by exciting stellate cell inhibitory interneurons. We describe instances adaptive balance at a behavioral level in which prolonged vestibular or optokinetic stimulation evokes reflexive eye movements that persist when the stimulation that initially evoked them stops. Adaptation to prolonged optokinetic stimulation also can be detected at cellular and subcellular levels. The transcription and expression of a neuropeptide, corticotropin releasing factor (CRF), is influenced by optokinetically-evoked olivary discharge and may contribute to optokinetic adaptation. The transcription and expression of microRNAs in floccular Purkinje cells evoked by long-term optokinetic stimulation may provide one of the subcellular mechanisms by which the membrane insertion of the GABAA receptors is regulated. The neurosteroids, estradiol (E2) and dihydrotestosterone (DHT), influence adaptation of vestibular nuclear neurons to electrically-induced potentiation and depression. In each section of this review, we discuss how adaptive changes in the vestibular and optokinetic subsystems of lobule X, inferior olivary nuclei and vestibular nuclei may contribute to the control of balance.

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Neural Correlates of Reinforcement Learning in Mid-lateral Cerebellum

Cited by 26 publications

References 0 publications

A Revised Computational Neuroanatomy for Motor Control

A Revised Computational Neuroanatomy for Motor Control

The Relationship between Birth Timing, Circuit Wiring, and Physiological Response Properties of Cerebellar Granule Cells

Adaptive Balance in Posterior Cerebellum

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