Ahissar E et al. (1992). Dependence of cortical plasticity on correlated activity of single neurons and on behavioral context. Science (New York, N.Y.). 257 [PubMed]
Au-Young SM, Shen H, Yang CR. (1999). Medial prefrontal cortical output neurons to the ventral tegmental area (VTA) and their responses to burst-patterned stimulation of the VTA: neuroanatomical and in vivo electrophysiological analyses. Synapse (New York, N.Y.). 34 [PubMed]
Barad M, Bourtchouladze R, Winder DG, Golan H, Kandel E. (1998). Rolipram, a type IV-specific phosphodiesterase inhibitor, facilitates the establishment of long-lasting long-term potentiation and improves memory. Proceedings of the National Academy of Sciences of the United States of America. 95 [PubMed]
Barto AG, Sutton RS. (1998). Reinforcement learning: an introduction.
Barto AG, Sutton RS, Anderson CW. (1983). Neuronlike elements that can solve difficult learning control problems IEEE Trans Systems Man Cybern. 13
Bi GQ, Poo MM. (1998). Synaptic modifications in cultured hippocampal neurons: dependence on spike timing, synaptic strength, and postsynaptic cell type. The Journal of neuroscience : the official journal of the Society for Neuroscience. 18 [PubMed]
Calabresi P et al. (2000). Dopamine and cAMP-regulated phosphoprotein 32 kDa controls both striatal long-term depression and long-term potentiation, opposing forms of synaptic plasticity. The Journal of neuroscience : the official journal of the Society for Neuroscience. 20 [PubMed]
Cass WA, Gerhardt GA. (1995). In vivo assessment of dopamine uptake in rat medial prefrontal cortex: comparison with dorsal striatum and nucleus accumbens. Journal of neurochemistry. 65 [PubMed]
Centonze D et al. (1999). Unilateral dopamine denervation blocks corticostriatal LTP. Journal of neurophysiology. 82 [PubMed]
Choi S, Lovinger DM. (1997). Decreased probability of neurotransmitter release underlies striatal long-term depression and postnatal development of corticostriatal synapses. Proceedings of the National Academy of Sciences of the United States of America. 94 [PubMed]
Connors BW, Gutnick MJ. (1990). Intrinsic firing patterns of diverse neocortical neurons. Trends in neurosciences. 13 [PubMed]
Dayan P, Abbott L. (2001). Neural encoding: Firing rates and spike statistics Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems.
Drew PJ, Abbott LF. (2006). Extending the effects of spike-timing-dependent plasticity to behavioral timescales. Proceedings of the National Academy of Sciences of the United States of America. 103 [PubMed]
Frey U, Morris RG. (1997). Synaptic tagging and long-term potentiation. Nature. 385 [PubMed]
Frey U, Schroeder H, Matthies H. (1990). Dopaminergic antagonists prevent long-term maintenance of posttetanic LTP in the CA1 region of rat hippocampal slices. Brain research. 522 [PubMed]
Fusi S, Drew PJ, Abbott LF. (2005). Cascade models of synaptically stored memories. Neuron. 45 [PubMed]
Garris PA, Ciolkowski EL, Pastore P, Wightman RM. (1994). Efflux of dopamine from the synaptic cleft in the nucleus accumbens of the rat brain. The Journal of neuroscience : the official journal of the Society for Neuroscience. 14 [PubMed]
Gerstner W, Kempter R, Van_hemmen J. (1999). Spike-based compared to rate-based Hebbian learning Advances In Neural Information Processing Systems. 11
Gerstner W, Kempter R, van Hemmen JL, Wagner H. (1996). A neuronal learning rule for sub-millisecond temporal coding. Nature. 383 [PubMed]
Gurden H, Takita M, Jay TM. (2000). Essential role of D1 but not D2 receptors in the NMDA receptor-dependent long-term potentiation at hippocampal-prefrontal cortex synapses in vivo. The Journal of neuroscience : the official journal of the Society for Neuroscience. 20 [PubMed]
Houk JC, Adams JL, Barto AGA. (1995). A model of how the basal ganglia generate and use neural signals that predict reinforcement. Models Of Information Processing In The Basal Ganglia.
Houk JC, Beiser DG, Davis JL. (1995). Models of Information Processing in the Basal Ganglia.
Hull CL. (1943). Principles of behavior.
Impey S et al. (1996). Induction of CRE-mediated gene expression by stimuli that generate long-lasting LTP in area CA1 of the hippocampus. Neuron. 16 [PubMed]
Izhikevich EM. (2006). Polychronization: computation with spikes. Neural computation. 18 [PubMed]
Izhikevich EM, Gally JA, Edelman GM. (2004). Spike-timing dynamics of neuronal groups. Cerebral cortex (New York, N.Y. : 1991). 14 [PubMed]
Jay TM, Burette F, Laroche S. (1996). Plasticity of the hippocampal-prefrontal cortex synapses. Journal of physiology, Paris. 90 [PubMed]
Klopf AH. (1982). The hedonistic neuron.
Koene RA, Hasselmo ME. (2005). An integrate-and-fire model of prefrontal cortex neuronal activity during performance of goal-directed decision making. Cerebral cortex (New York, N.Y. : 1991). 15 [PubMed]
Lauwereyns J, Watanabe K, Coe B, Hikosaka O. (2002). A neural correlate of response bias in monkey caudate nucleus. Nature. 418 [PubMed]
Levy WB, Steward O. (1983). Temporal contiguity requirements for long-term associative potentiation/depression in the hippocampus. Neuroscience. 8 [PubMed]
Lisman J. (1989). A mechanism for the Hebb and the anti-Hebb processes underlying learning and memory. Proceedings of the National Academy of Sciences of the United States of America. 86 [PubMed]
Ljungberg T, Apicella P, Schultz W. (1992). Responses of monkey dopamine neurons during learning of behavioral reactions. Journal of neurophysiology. 67 [PubMed]
Markram H, Lübke J, Frotscher M, Sakmann B. (1997). Regulation of synaptic efficacy by coincidence of postsynaptic APs and EPSPs. Science (New York, N.Y.). 275 [PubMed]
Minsky ML. (1963). Steps toward artificial intelligence Computers and thought.
Montague PR, Dayan P, Sejnowski TJ. (1996). A framework for mesencephalic dopamine systems based on predictive Hebbian learning. The Journal of neuroscience : the official journal of the Society for Neuroscience. 16 [PubMed]
Montague PR et al. (2004). Dynamic gain control of dopamine delivery in freely moving animals. The Journal of neuroscience : the official journal of the Society for Neuroscience. 24 [PubMed]
Otani S, Daniel H, Roisin MP, Crepel F. (2003). Dopaminergic modulation of long-term synaptic plasticity in rat prefrontal neurons. Cerebral cortex (New York, N.Y. : 1991). 13 [PubMed]
Otmakhova NA, Lisman JE. (1996). D1/D5 dopamine receptor activation increases the magnitude of early long-term potentiation at CA1 hippocampal synapses. The Journal of neuroscience : the official journal of the Society for Neuroscience. 16 [PubMed]
Otmakhova NA, Lisman JE. (1998). D1/D5 dopamine receptors inhibit depotentiation at CA1 synapses via cAMP-dependent mechanism. The Journal of neuroscience : the official journal of the Society for Neuroscience. 18 [PubMed]
Pan WX, Schmidt R, Wickens JR, Hyland BI. (2005). Dopamine cells respond to predicted events during classical conditioning: evidence for eligibility traces in the reward-learning network. The Journal of neuroscience : the official journal of the Society for Neuroscience. 25 [PubMed]
Pasupathy A, Miller EK. (2005). Different time courses of learning-related activity in the prefrontal cortex and striatum. Nature. 433 [PubMed]
Pavlov IP. (1927). Conditioned reflexes..
Rao RP, Sejnowski TJ. (2001). Spike-timing-dependent Hebbian plasticity as temporal difference learning. Neural computation. 13 [PubMed]
Schirmer A, Tang SL, Penney TB, Gunter TC, Chen HC. (2005). Brain responses to segmentally and tonally induced semantic violations in Cantonese. Journal of cognitive neuroscience. 17 [PubMed]
Schultz W. (1998). Predictive reward signal of dopamine neurons. Journal of neurophysiology. 80 [PubMed]
Schultz W. (2002). Getting formal with dopamine and reward. Neuron. 36 [PubMed]
Schultz W. (2007). Reward Signals Scholarpedia (Forthcoming).
Schultz W, Dayan P, Montague PR. (1997). A neural substrate of prediction and reward. Science (New York, N.Y.). 275 [PubMed]
Seamans JK, Yang CR. (2004). The principal features and mechanisms of dopamine modulation in the prefrontal cortex. Progress in neurobiology. 74 [PubMed]
Seung HS. (2003). Learning in spiking neural networks by reinforcement of stochastic synaptic transmission. Neuron. 40 [PubMed]
Song S, Miller KD, Abbott LF. (2000). Competitive Hebbian learning through spike-timing-dependent synaptic plasticity. Nature neuroscience. 3 [PubMed]
Suri RE, Schultz W. (2001). Temporal difference model reproduces anticipatory neural activity. Neural computation. 13 [PubMed]
Sutton RS. (1988). Learning to predict by the method of temporal diferences Machine Learning. 3
Swadlow HA. (1990). Efferent neurons and suspected interneurons in S-1 forelimb representation of the awake rabbit: receptive fields and axonal properties. Journal of neurophysiology. 63 [PubMed]
Swadlow HA. (1994). Efferent neurons and suspected interneurons in motor cortex of the awake rabbit: axonal properties, sensory receptive fields, and subthreshold synaptic inputs. Journal of neurophysiology. 71 [PubMed]
Watanabe M. (1996). Reward expectancy in primate prefrontal neurons. Nature. 382 [PubMed]
Wightman RM, Zimmerman JB. (2007). Control of dopamine extracellular concentration in rat striatum by impulse flow and uptake. Brain Res Brain Res Rev. 15
Wörgötter F, Porr B. (2005). Temporal sequence learning, prediction, and control: a review of different models and their relation to biological mechanisms. Neural computation. 17 [PubMed]
van Hemmen JL, Gerstner W, Kempter R. (1999). Hebbian learning and spiking neurons Physical Review E. 59
Antunes G, Faria da Silva SF, Simoes de Souza FM. (2018). Mirror Neurons Modeled Through Spike-Timing-Dependent Plasticity are Affected by Channelopathies Associated with Autism Spectrum Disorder. International journal of neural systems. 28 [PubMed]
Assisi C, Stopfer M, Bazhenov M. (2020). Optimality of sparse olfactory representations is not affected by network plasticity. PLoS computational biology. 16 [PubMed]
Baladron J, Nambu A, Hamker FH. (2019). The subthalamic nucleus-external globus pallidus loop biases exploratory decisions towards known alternatives: a neuro-computational study. The European journal of neuroscience. 49 [PubMed]
Bittner KC, Milstein AD, Grienberger C, Romani S, Magee JC. (2017). Behavioral time scale synaptic plasticity underlies CA1 place fields. Science (New York, N.Y.). 357 [PubMed]
Brzosko Z, Zannone S, Schultz W, Clopath C, Paulsen O. (2017). Sequential neuromodulation of Hebbian plasticity offers mechanism for effective reward-based navigation. eLife. 6 [PubMed]
Chadderdon GL, Neymotin SA, Kerr CC, Lytton WW. (2012). Reinforcement learning of targeted movement in a spiking neuronal model of motor cortex. PloS one. 7 [PubMed]
Clopath C, Ziegler L, Vasilaki E, Büsing L, Gerstner W. (2008). Tag-trigger-consolidation: a model of early and late long-term-potentiation and depression. PLoS computational biology. 4 [PubMed]
Dumont G, Ermentrout GB, Gutkin B. (2017). Macroscopic phase-resetting curves for spiking neural networks. Physical review. E. 96 [PubMed]
Dura-Bernal S et al. (2015). Cortical Spiking Network Interfaced with Virtual Musculoskeletal Arm and Robotic Arm. Frontiers in neurorobotics. 9 [PubMed]
Esposito U, Giugliano M, Vasilaki E. (2014). Adaptation of short-term plasticity parameters via error-driven learning may explain the correlation between activity-dependent synaptic properties, connectivity motifs and target specificity. Frontiers in computational neuroscience. 8 [PubMed]
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]
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]
Lytton WW et al. (2017). Evolutionary algorithm optimization of biological learning parameters in a biomimetic neuroprosthesis. IBM Journal of Research and Development (Computational Neuroscience special issue). 61(2/3)
Manninen T, Saudargiene A, Linne ML. (2020). Astrocyte-mediated spike-timing-dependent long-term depression modulates synaptic properties in the developing cortex. PLoS computational biology. 16 [PubMed]
Mozafari M, Kheradpisheh SR, Masquelier T, Nowzari-Dalini A, Ganjtabesh M. (2018). First-Spike-Based Visual Categorization Using Reward-Modulated STDP IEEE Transactions on Neural Networks and Learning Systems.
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]
Neymotin SA, Chadderdon GL, Kerr CC, Francis JT, Lytton WW. (2013). Reinforcement learning of two-joint virtual arm reaching in a computer model of sensorimotor cortex. Neural computation. 25 [PubMed]
Richmond P, Buesing L, Giugliano M, Vasilaki E. (2011). Democratic population decisions result in robust policy-gradient learning: a parametric study with GPU simulations. PloS one. 6 [PubMed]
Rivest F, Kalaska JF, Bengio Y. (2010). Alternative time representation in dopamine models. Journal of computational neuroscience. 28 [PubMed]
Solinas SMG, Edelmann E, Leßmann V, Migliore M. (2019). A kinetic model for Brain-Derived Neurotrophic Factor mediated spike timing-dependent LTP. PLoS computational biology. 15 [PubMed]
Zannone S, Brzosko Z, Paulsen O, Clopath C. (2018). Acetylcholine-modulated plasticity in reward-driven navigation: a computational study. Scientific reports. 8 [PubMed]