A cellular mechanism of reward-related learning
By John N. J. Reynolds, Brian Hyland, J. Wickens. Nature, 2001
852 citations recorded by the source corpus.
Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Neurology
View Paper: https://www.semanticscholar.org/paper/435c755a6c573da0e213fa6dacbf5197c2f0e2e1
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cellular and Molecular Neuroscience
- Wolfram Schultz
- Yael Niv
- Michael J Frank
- Andrea Soltoggio
- Wulfram Gerstner
- Xiao-Jing Wang
- Nathaniel D. Daw
- Kenji Doya
In Cognitive Neuroscience
- Wolfram Schultz
- Michael J Frank
- Nathaniel D. Daw
- Xiao-Jing Wang
- Yael Niv
- Peter S. Dayan
- Andrea Soltoggio
- Wulfram Gerstner
In Neurology
- Wolfram Schultz
- Yael Niv
- R. Malenka
- Xiao-Jing Wang
- Michael J Frank
- Kevin N. Gurney
- Kenji Doya
- Nathaniel D. Daw
Citations in the corpus
- TD models of reward predictive responses in dopamine neurons (2002, background): “activity seems to induce long-term changes in corticostriatal transmission (Schultz, 1998; Reynolds, Hyland, & Wickens, 2001 ).”
- Mesolimbic Dopamine Signals the Value of Work (2015, neutral): “No reinforcing effect was seen if the same optogenetic stimulation was given in littermate controls (n = 6 Th-Cre− rats, laser main effect F(1,5) = 2.”
- Convergent evidence for abnormal striatal synaptic plasticity in dystonia (2009, neutral): “how context-sensitive motor behavior is shaped (Reynolds et al., 2001;Wickens et al., 2003).”
- Loss of bidirectional striatal synaptic plasticity in L-DOPA–induced dyskinesia (2003, background): “LTP is induced in striatal spiny neurons both in vitro and in vivo after repetitive high-frequency stimulation (HFS) of glutamatergic corticostriatal afferents, and this striatal LTP may represent a cellular substrate for motor learnin”
- What is reinforced by phasic dopamine signals? (2008, background): “ThepresenceofDAhasbeen shown to be critical for LTP (Calabresi et al., 2000; Calabresi et al., 2007; Kerr and Wickens, 2001; Reynolds et al., 2001).”
- Computational models of reinforcement learning: the role of dopamine as a reward signal (2010, background): “DA was shown to modulate plasticity in the striatum (Calabresi et al. 2007; Centonze et al. 2003; Kerr and Wickens 2001; Pawlak and Kerr 2008; Reynolds et al. 2001), the amygdala (Bissière et al. 2003), PFC (Huang et al. 2007; Kolomiets et al. 2009) and hippocampus (Frey et al. 1989, 1990, 1991;…”
- Dynamic reorganization of striatal circuits during the acquisition and consolidation of a skill (2009, background): “Long-term synaptic plasticity in the striatum has been observed with a variety of protocols in brain slices and in anesthetized animal”
- Goals and Habits in the Brain (2013, neutral): “…as Neuron 80, October 16, 2013 ª2013 The Authors 317 reporting the temporal difference prediction error for reward (Montague et al., 1996; Schultz et al., 1997) that underpins model-free evaluation and control via its influence over activity and plasticity (Reynolds et al., 2001; Frank, 2005).”
- Model-based predictions for dopamine (2017, neutral): “The algorithm also provides a simple way to learn such values using prediction errors, which is thought to be implemented in the brain through dopaminemodulated plasticity in corticostriatal synapses [7,8] (Figure 1, left).”
- Evolutionary and Computational Advantages of Neuromodulated Plasticity (2008, background): “Studies on mammalian brains have identified modulatory activity in the cerebellar synapse (Dittman and Regehr, 1997), neostriatum (Arbuthnott et al., 2000; Kerr and Wickens, 2001; Reynolds et al., 2001), dorsal”