Chao TC, Chen CM. (2005). Learning-induced synchronization and plasticity of a developing neural network. Journal of computational neuroscience. 19 [PubMed]
Gluck MA, Moustafa AA. (2011). A neurocomputational model of dopamine and prefrontal-striatal interactions during multicue category learning by Parkinson patients. J Cogn Neurosci. 23(1)
Gurney KN, Humphries MD, Redgrave P. (2015). A new framework for cortico-striatal plasticity: behavioural theory meets in vitro data at the reinforcement-action interface. PLoS biology. 13 [PubMed]
Guthrie M, Leblois A, Garenne A, Boraud T. (2013). Interaction between cognitive and motor cortico-basal ganglia loops during decision making: a computational study. Journal of neurophysiology. 109 [PubMed]
Kato A, Morita K. (2016). Forgetting in Reinforcement Learning Links Sustained Dopamine Signals to Motivation. PLoS computational biology. 12 [PubMed]
Legenstein R, Pecevski D, Maass W. (2008). A learning theory for reward-modulated spike-timing-dependent plasticity with application to biofeedback. PLoS computational biology. 4 [PubMed]
Morita K, Kato A. (2014). Striatal dopamine ramping may indicate flexible reinforcement learning with forgetting in the cortico-basal ganglia circuits. Frontiers in neural circuits. 8 [PubMed]
Moustafa AA, Cohen MX, Sherman SJ, Frank MJ. (2008). A role for dopamine in temporal decision making and reward maximization in parkinsonism. The Journal of neuroscience : the official journal of the Society for Neuroscience. 28 [PubMed]
Mulcahy G, Atwood B, Kuznetsov A. (2020). Basal ganglia role in learning rewarded actions and executing previously learned choices: Healthy and diseased states. PloS one. 15 [PubMed]
Nakano T, Doi T, Yoshimoto J, Doya K. (2010). A kinetic model of dopamine- and calcium-dependent striatal synaptic plasticity. PLoS computational biology. 6 [PubMed]
Nakano T, Otsuka M, Yoshimoto J, Doya K. (2015). A spiking neural network model of model-free reinforcement learning with high-dimensional sensory input and perceptual ambiguity. PloS one. 10 [PubMed]
Nakano T, Yoshimoto J, Doya K. (2013). A model-based prediction of the calcium responses in the striatal synaptic spines depending on the timing of cortical and dopaminergic inputs and post-synaptic spikes. Frontiers in computational neuroscience. 7 [PubMed]
Roelfsema PR, van Ooyen A. (2005). Attention-gated reinforcement learning of internal representations for classification. Neural computation. 17 [PubMed]
Soltani A, Wang XJ. (2006). A biophysically based neural model of matching law behavior: melioration by stochastic synapses. The Journal of neuroscience : the official journal of the Society for Neuroscience. 26 [PubMed]
Ursino M, Baston C. (2018). Aberrant learning in Parkinson's disease: A neurocomputational study on bradykinesia. The European journal of neuroscience. 47 [PubMed]
Ursino M et al. (2020). Mathematical modeling and parameter estimation of levodopa motor response in patients with parkinson disease. PloS one. 15 [PubMed]