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  A cerebellar internal model calibrates a feedback controller involved in sensorimotor control

Markov, D. A., Petrucco, L., Kist, A. M., & Portugues, R. (2021). A cerebellar internal model calibrates a feedback controller involved in sensorimotor control. Nature Communications, 12: 6694. doi:10.1038/s41467-021-26988-0.

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 Urheber:
Markov, Daniil A.1, Autor           
Petrucco, Luigi1, Autor           
Kist, Andreas M.1, Autor           
Portugues, Ruben1, Autor           
Affiliations:
1Max Planck Research Group: Sensorimotor Control / Portugues, MPI of Neurobiology, Max Planck Society, ou_2054291              

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 Zusammenfassung: Animals can adjust their behavior in response to changes in the
environment when these changes can be predicted. Here the authors show
the role of the cerebellum in zebrafish that change their swimming as
they adjust to long-lasting changes in visual feedback
Animals must adapt their behavior to survive in a changing environment.
Behavioral adaptations can be evoked by two mechanisms: feedback control
and internal-model-based control. Feedback controllers can maintain the
sensory state of the animal at a desired level under different
environmental conditions. In contrast, internal models learn the
relationship between the motor output and its sensory consequences and
can be used to recalibrate behaviors. Here, we present multiple
unpredictable perturbations in visual feedback to larval zebrafish
performing the optomotor response and show that they react to these
perturbations through a feedback control mechanism. In contrast, if a
perturbation is long-lasting, fish adapt their behavior by updating a
cerebellum-dependent internal model. We use modelling and functional
imaging to show that the neuronal requirements for these mechanisms are
met in the larval zebrafish brain. Our results illustrate the role of
the cerebellum in encoding internal models and how these can calibrate
neuronal circuits involved in reactive behaviors depending on the
interactions between animal and environment.

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 Datum: 2021-11-18
 Publikationsstatus: Erschienen
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 Identifikatoren: ISI: 000720682300030
DOI: 10.1038/s41467-021-26988-0
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Projektinformation

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Projektname : Munich Cluster for Systems Neurology (EXC 2145 SyNergy—ID 390857198)
Grant ID : 390857198
Förderprogramm : Germany’s Excellence Strategy
Förderorganisation : Deutsche Forschungsgemeinschaft (DFG)

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Titel: Nature Communications
  Kurztitel : Nat. Commun.
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: London : Nature Publishing Group
Seiten: - Band / Heft: 12 Artikelnummer: 6694 Start- / Endseite: - Identifikator: ISSN: 2041-1723
CoNE: https://pure.mpg.de/cone/journals/resource/2041-1723