Accounting for uncertainty: inhibition for neural inference in the cerebellum

Palacios, Ensor Rafael; Houghton, Conor; Chadderton, Paul

doi:10.1098/rspb.2021.0276

Cited by 10 publications

(12 citation statements)

References 91 publications

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“…This net input drives state estimation depending on the connectivity matrix involving glom and grc , and is weighted or contextualised by its precision via goc inhibition, setting grc response gain and threshold 43 ; this weighting by controls how much mf drives the network, based on the context-dependent precision or relevance of incoming information. On the other hand, the last term, , incorporates feedback from Pjc representing hidden causes .…”

Section: Resultsmentioning

confidence: 99%

Cerebellar state estimation enables resilient coupling across behavioural domains

Palacios,

Chadderton,

Friston

et al. 2024

Sci Rep

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Cerebellar computations are necessary for fine behavioural control and may rely on internal models for estimation of behaviourally relevant states. Here, we propose that the central cerebellar function is to estimate how states interact with each other, and to use these estimates to coordinates extra-cerebellar neuronal dynamics underpinning a range of interconnected behaviours. To support this claim, we describe a cerebellar model for state estimation that includes state interactions, and link this model with the neuronal architecture and dynamics observed empirically. This is formalised using the free energy principle, which provides a dual perspective on a system in terms of both the dynamics of its physical—in this case neuronal—states, and the inferential process they entail. As a demonstration of this proposal, we simulate cerebellar-dependent synchronisation of whisking and respiration, which are known to be tightly coupled in rodents, as well as limb and tail coordination during locomotion. In summary, we propose that the ubiquitous involvement of the cerebellum in behaviour arises from its central role in precisely coupling behavioural domains.

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Section: Resultsmentioning

confidence: 99%

Cerebellar state estimation enables resilient coupling across behavioural domains

Palacios,

Chadderton,

Friston

et al. 2024

Sci Rep

Self Cite

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“…Excitatory granule cells make up the cerebellar granular layer. Interaction of these cells with inhibitory Golgi cells can help determine network responses to external stimuli [ 54 ]. Hence, a functional change in granule cells may directly affect information integration within the cerebellar computational network and subsequently affect motor learning.…”

Section: Discussionmentioning

confidence: 99%

NR1 Splicing Variant NR1a in Cerebellar Granule Neurons Constitutes a Better Motor Learning in the Mouse

Tan,

Jiang,

et al. 2023

Cerebellum

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As an excitatory neuron in the cerebellum, the granule cells play a crucial role in motor learning. The assembly of NMDAR in these neurons varies in developmental stages, while the significance of this variety is still not clear. In this study, we found that motor training could specially upregulate the expression level of NR1a, a splicing form of NR1 subunit. Interestingly, overexpression of this splicing variant in a cerebellar granule cell-specific manner dramatically elevated the NMDAR binding activity. Furthermore, the NR1a transgenic mice did not only show an enhanced motor learning, but also exhibit a higher efficacy for motor training in motor learning. Our results suggested that as a “junior” receptor, NR1a facilitates NMDAR activity as well as motor skill learning.

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“…The middle layer contains Purkinje cells, and the outermost molecular layer contains stellate and basket cells. Among these cerebellar neurons, cerebellar granule cells, which are known to be excitatory cells [10], are the most vulnerable to MeHg in humans [11].…”

Section: Involvement Of Local Redox Ability In Site-specific Cerebell...mentioning

confidence: 99%

Cellular Conditions Responsible for Methylmercury-Mediated Neurotoxicity

Fujimura

Usuki

2022

IJMS

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Methylmercury (MeHg) is a widely known environmental pollutant that causes severe neurotoxicity. MeHg-induced neurotoxicity depends on various cellular conditions, including differences in the characteristics of tissues and cells, exposure age (fetal, childhood, or adulthood), and exposure levels. Research has highlighted the importance of oxidative stress in the pathogenesis of MeHg-induced toxicity and the site- and cell-specific nature of MeHg-induced neurotoxicity. The cerebellar granule cells and deeper layer cerebrocortical neurons are vulnerable to MeHg. In contrast, the hippocampal neurons are resistant to MeHg, even at high mercury accumulation levels. This review summarizes the mechanisms underlying MeHg-mediated intracellular events that lead to site-specific neurotoxicity. Specifically, we discuss the mechanisms associated with the redox ability, neural outgrowth and synapse formation, cellular signaling pathways, epigenetics, and the inflammatory conditions of microglia.

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Accounting for uncertainty: inhibition for neural inference in the cerebellum

Cited by 10 publications

References 91 publications

Cerebellar state estimation enables resilient coupling across behavioural domains

Cerebellar state estimation enables resilient coupling across behavioural domains

NR1 Splicing Variant NR1a in Cerebellar Granule Neurons Constitutes a Better Motor Learning in the Mouse

Cellular Conditions Responsible for Methylmercury-Mediated Neurotoxicity

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