The Cerebellum: A Neuronal Learning Machine?

Raymond, Jennifer L.; Lisberger, Stephen G.; Mauk, Michael D.

doi:10.1126/science.272.5265.1126

Cited by 574 publications

(427 citation statements)

References 69 publications

Supporting

Mentioning

386

Contrasting

Unclassified

Order By: Relevance

“…The present findings underscore the similarities between eyelid conditioning and adaptation of the VOR, in that they are both forms of cerebellar motor learning that induce plasticity at two sites, one in the cerebellar cortex and another in their target neurons in the deep cerebellar/vestibular nuclei. As such, our results suggest the generality of two sites of plasticity in cerebellar learning (Raymond et al, 1996;Mauk, 1997;Mauk and Donegan, 1997).…”

Section: Cerebellar Learning Induces Plasticity In Target Nuclei Downmentioning

confidence: 63%

See 1 more Smart Citation

Learning-Induced Plasticity in Deep Cerebellar Nucleus

Ohyama¹,

Nores²,

Medina³

et al. 2006

J. Neurosci.

139

131

View full text Add to dashboard Cite

Evidence that cerebellar learning involves more than one site of plasticity comes from, in part, pavlovian eyelid conditioning, where disconnecting the cerebellar cortex abolishes one component of learning, response timing, but spares the expression of abnormally timed short-latency responses (SLRs). Here, we provide evidence that SLRs unmasked by cerebellar cortex lesions are mediated by an associative form of learning-induced plasticity in the anterior interpositus nucleus (AIN) of the cerebellum. We used pharmacological inactivation and/or electrical microstimulation of various sites afferent and efferent to the AIN to systematically eliminate alternative candidate sites of plasticity upstream or downstream from this structure. Collectively, the results suggest that cerebellar learning is mediated in part by plasticity in target nuclei downstream of the cerebellar cortex. These data demonstrate an instance in which an aspect of associative learning, SLRs, can be used as an index of plasticity at a specific site in the brain.

show abstract

Section: Cerebellar Learning Induces Plasticity In Target Nuclei Downmentioning

confidence: 63%

“…We previously hypothesized that these short-latency responses (SLRs) (see Fig. 1) are mediated by plasticity in the AIN (Raymond et al, 1996;Mauk and Donegan, 1997).…”

Section: Introductionmentioning

confidence: 99%

Learning-Induced Plasticity in Deep Cerebellar Nucleus

Ohyama¹,

Nores²,

Medina³

et al. 2006

J. Neurosci.

139

131

View full text Add to dashboard Cite

show abstract

“…As an example, it appears that many classical aspects of perception, such as geometry, most likely do not exclusively belong to the percept domain of a Vision system, but include the response domain. This is supported by recent reseach about the motor system, and in particular the cerebellum [25].…”

Section: Object Properties -Part Percept -Part Responsementioning

confidence: 64%

“…The execution of such response model sets then has to be implemented in some separate response sequencing unit. It appears likely that the cerebellum may have such a function [25].…”

Section: Percept Linkmentioning

confidence: 99%

See 1 more Smart Citation

From multidimensional signals to the generation of responses

Granlund

1997

Algebraic Frames for the Perception-Action Cycle

View full text Add to dashboard Cite

Abstract. It has become increasingly apparent that perception cannot be treated in isolation from the response generation, firstly because a very high degree of integration is required between different levels of percepts and corresponding response primitives. Secondly, it turns out that the response to be produced at a given instance is as much dependent upon the state of the system, as the percepts impinging upon the system. The state of the system is in consequence the combination of the responses produced and the percepts associated with these responses. Thirdly, it has become apparent that many classical aspects of perception, such as geometry, probably do not belong to the percept domain of a Vision system, but to the response domain. There are not yet solutions available to all of these problems. In consequence, this overview will focus on what are considered crucial problems for the future, rather than on the solutions available today. It will discuss hierarchical architectures for combination of percept and response primitives, and the concept of combined percept-response invariances as important structural elements for Vision. It will be maintained that learning is essential to obtain the necessary flexibility and adaptivity. In consequence, it will be argued that invariances for the purpose of vision are not geometrical but derived from the percept-response interaction with the environment. The issue of information representation becomes extremely important in distributed structures of the types foreseen, where uncertainty of information has to be stated for update of models and associated data.

show abstract

Ultrastructural change at rat cerebellothalamic synapses associated with volitional motor adaptation

Aumann

Horne

1999

J. Comp. Neurol.

View full text Add to dashboard Cite

The Cerebellum: A Neuronal Learning Machine?

Cited by 574 publications

References 69 publications

Learning-Induced Plasticity in Deep Cerebellar Nucleus

Learning-Induced Plasticity in Deep Cerebellar Nucleus

From multidimensional signals to the generation of responses

Ultrastructural change at rat cerebellothalamic synapses associated with volitional motor adaptation

Contact Info

Product

Resources

About