Modeling nucleus accumbens. A computational model from single cell to circuit level

DOI10.1007/s10827-020-00769-yzbMath1489.92008OpenAlexW3100069670WikidataQ101467460 ScholiaQ101467460MaRDI QIDQ2137294

Rahmi Elibol, Neslihan Serap Sengor

Publication date: 16 May 2022

Published in: Journal of Computational Neuroscience (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10827-020-00769-y

zbMATH Keywords

computational modellocal field potentialnucleus accumbensmedium spiny neuron

Mathematics Subject Classification ID

Neural biology (92C20) Neural networks for/in biological studies, artificial life and related topics (92B20)

Uses Software

• Brian

Cites Work

• Heterarchical reinforcement-learning model for integration of multiple cortico-striatal loops: fMRI examination in stimulus-action-reward association learning
• Firing patterns in the adaptive exponential integrate-and-fire model
• Analysis of recurrent cortico-basal ganglia-thalamic loops for working memory
• A computational model of action selection in the basal ganglia. I: A new functional anatomy
• A computational model of action selection in the basal ganglia. II: Analysis and simulation of behaviour
• Individual Differences in Nucleus Accumbens Dopamine Receptors Predict Development of Addiction-Like Behavior: A Computational Approach
• Making Working Memory Work: A Computational Model of Learning in the Prefrontal Cortex and Basal Ganglia

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