Sensory Reinforced Corticostriatal Plasticity.

Corticostriatal dopamine plasticity reinforcement. sensory timing

Journal

Current neuropharmacology
ISSN: 1875-6190
Titre abrégé: Curr Neuropharmacol
Pays: United Arab Emirates
ID NLM: 101157239

Informations de publication

Date de publication:
01 Aug 2023
Historique:
received: 29 10 2022
revised: 04 02 2023
accepted: 10 02 2023
medline: 3 8 2023
pubmed: 3 8 2023
entrez: 3 8 2023
Statut: aheadofprint

Résumé

Regional changes in corticostriatal transmission induced by phasic dopaminergic signals are an essential feature of the neural network responsible for instrumental reinforcement during discovery of an action. However, the timing of signals that are thought to contribute to the induction of corticostriatal plasticity is difficult to reconcile within the framework of behavioural reinforcement learning, because the reinforcer is normally delayed relative to the selection and execution of causally-related actions. While recent studies have started to address the relevance of delayed reinforcement signals and their impact on corticostriatal processing, our objective was to establish a model in which a sensory reinforcer triggers appropriately delayed reinforcement signals relayed to the striatum via intact neuronal pathways and to investigate the effects on corticostriatal plasticity. We measured corticostriatal plasticity with electrophysiological recordings using a light flash as a natural sensory reinforcer, and pharmacological manipulations were applied in an in vivo anesthetized rat model preparation. We demonstrate that the spiking of striatal neurons evoked by single-pulse stimulation of the motor cortex can be potentiated by a natural sensory reinforcer, operating through intact afferent pathways, with signal timing approximating that required for behavioural reinforcement. The pharmacological blockade of dopamine receptors attenuated the observed potentiation of corticostriatal neurotransmission. This novel in vivo model of corticostriatal plasticity offers a behaviourally relevant framework to address the physiological, anatomical, cellular, and molecular bases of instrumental reinforcement learning.

Sections du résumé

BACKGROUND BACKGROUND
Regional changes in corticostriatal transmission induced by phasic dopaminergic signals are an essential feature of the neural network responsible for instrumental reinforcement during discovery of an action. However, the timing of signals that are thought to contribute to the induction of corticostriatal plasticity is difficult to reconcile within the framework of behavioural reinforcement learning, because the reinforcer is normally delayed relative to the selection and execution of causally-related actions.
OBJECTIVE OBJECTIVE
While recent studies have started to address the relevance of delayed reinforcement signals and their impact on corticostriatal processing, our objective was to establish a model in which a sensory reinforcer triggers appropriately delayed reinforcement signals relayed to the striatum via intact neuronal pathways and to investigate the effects on corticostriatal plasticity.
METHODS METHODS
We measured corticostriatal plasticity with electrophysiological recordings using a light flash as a natural sensory reinforcer, and pharmacological manipulations were applied in an in vivo anesthetized rat model preparation.
RESULTS RESULTS
We demonstrate that the spiking of striatal neurons evoked by single-pulse stimulation of the motor cortex can be potentiated by a natural sensory reinforcer, operating through intact afferent pathways, with signal timing approximating that required for behavioural reinforcement. The pharmacological blockade of dopamine receptors attenuated the observed potentiation of corticostriatal neurotransmission.
CONCLUSION CONCLUSIONS
This novel in vivo model of corticostriatal plasticity offers a behaviourally relevant framework to address the physiological, anatomical, cellular, and molecular bases of instrumental reinforcement learning.

Identifiants

pubmed: 37533245
pii: CN-EPUB-133306
doi: 10.2174/1570159X21666230801110359
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.

Auteurs

Nicolas Vautrelle (N)

Department of Anatomy, Brain Health Research Centre, University of Otago, Dunedin 9054, New Zeal.
Department of Psychology, University of Sheffield, Sheffield, S10 2TP, UK.

Véronique Coizet (V)

Department of Psychology, University of Sheffield, Sheffield, S10 2TP, UK.
Université Joseph Fourier, Inserm, U1216, Institut des Neurosciences de Grenoble, 38706 La Tronche Cedex, France.

Mariana Leriche (M)

Department of Anatomy, Brain Health Research Centre, University of Otago, Dunedin 9054, New Zeal.
Department of Psychology, University of Sheffield, Sheffield, S10 2TP, UK.

Lionel Dahan (L)

Department of Psychology, University of Sheffield, Sheffield, S10 2TP, UK.
Université de Toulouse, UPS, Centre de Recherches sur la Cognition Animale, 118 Route de Narbonne, F-31062 Toulouse Cedex 9, France.

Jan M Schulz (JM)

Department of Anatomy, Brain Health Research Centre, University of Otago, Dunedin 9054, New Zeal.
Department of Biomedicine, University of Basel, CH - 4056 Basel, Switzerland.

Yan-Feng Zhang (YF)

Department of Anatomy, Brain Health Research Centre, University of Otago, Dunedin 9054, New Zealand.
Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Hatherly Laboratories, Exeter EX4 4PS, United Kingdom.

Abdelhafid Zeghbib (A)

Department of Psychology, University of Sheffield, Sheffield, S10 2TP, UK.

Paul G Overton (PG)

Department of Psychology, University of Sheffield, Sheffield, S10 2TP, UK.

Enrico Bracci (E)

Department of Psychology, University of Sheffield, Sheffield, S10 2TP, UK.

Peter Redgrave (P)

Department of Psychology, University of Sheffield, Sheffield, S10 2TP, UK.

John N J Reynolds (JNJ)

Department of Anatomy, Brain Health Research Centre, University of Otago, Dunedin 9054, New Zeala.

Classifications MeSH