VTA dopamine neuron activity encodes social interaction and promotes reinforcement learning through social prediction error

2021 ◽  
Author(s):  
Clément Solié ◽  
Benoit Girard ◽  
Beatrice Righetti ◽  
Malika Tapparel ◽  
Camilla Bellone
Keyword(s):  
Reinforcement Learning ◽  
Social Interaction ◽  
Prediction Error ◽  
Dopamine Neuron ◽  
Neuron Activity ◽  
Social Prediction

Involvement of Midbrain Dopamine Neuron Activity in Negative Reinforcement Learning in Mice

2021 ◽  
Author(s):  
Zhijun Diao ◽  
Li Yao ◽  
Qiangqiang Cheng ◽  
Meilin Wu ◽  
Yuanyuan Di ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Negative Reinforcement ◽  
Dopamine Neuron ◽  
Neuron Activity ◽  
Midbrain Dopamine

scholarly journals Hippocampal Cannabinoid Transmission Modulates Dopamine Neuron Activity: Impact on Rewarding Memory Formation and Social Interaction

2014 ◽  
Vol 40 (6) ◽  
pp. 1436-1447 ◽  
Author(s):  
Michael Loureiro ◽  
Justine Renard ◽  
Jordan Zunder ◽  
Steven R Laviolette
Keyword(s):  
Social Interaction ◽  
Memory Formation ◽  
Dopamine Neuron ◽  
Neuron Activity

scholarly journals Orexin receptor antagonists reverse aberrant dopamine neuron activity and related behaviors in a rodent model of stress-induced psychosis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hannah B. Elam ◽  
Stephanie M. Perez ◽  
Jennifer J. Donegan ◽  
Daniel J. Lodge
Keyword(s):  
United States ◽  
Sensorimotor Gating ◽  
The United States ◽  
Dopamine Neuron ◽  
Neuron Activity ◽  
Sprague Dawley ◽  
Post Traumatic Stress ◽  
Neuron Population ◽  
Population Activity ◽  
Novel Approach

AbstractPost-traumatic stress disorder (PTSD) is a prevalent condition affecting approximately 8% of the United States population and 20% of United States combat veterans. In addition to core symptoms of the disorder, up to 64% of individuals diagnosed with PTSD experience comorbid psychosis. Previous research has demonstrated a positive correlation between symptoms of psychosis and increases in dopamine transmission. We have recently demonstrated projections from the paraventricular nucleus of the thalamus (PVT) to the nucleus accumbens (NAc) can regulate dopamine neuron activity in the ventral tegmental area (VTA). Specifically, inactivation of the PVT leads to a reversal of aberrant dopamine system function and psychosis-like behavior. The PVT receives dense innervation from orexin containing neurons, therefore, targeting orexin receptors may be a novel approach to restore dopamine neuron activity and alleviate PTSD-associated psychosis. In this study, we induced stress-related pathophysiology in male Sprague Dawley rats using an inescapable foot-shock procedure. We observed a significant increase in VTA dopamine neuron population activity, deficits in sensorimotor gating, and hyperresponsivity to psychomotor stimulants. Administration of selective orexin 1 receptor (OX1R) and orexin 2 receptor (OX2R) antagonists (SB334867 and EMPA, respectively) or the FDA-approved, dual-orexin receptor antagonist, Suvorexant, were found to reverse stress-induced increases in dopamine neuron population activity. However, only Suvorexant and SB334867 were able to reverse deficits in behavioral corelates of psychosis. These results suggest that the orexin system may be a novel pharmacological target for the treatment of comorbid psychosis related to PTSD.

scholarly journals Prefrontal solution to the bias-variance tradeoff during reinforcement learning

2020 ◽  
Author(s):  
Dongjae Kim ◽  
Jaeseung Jeong ◽  
Sang Wan Lee
Keyword(s):  
Adaptive Control ◽  
Reinforcement Learning ◽  
Prediction Error ◽  
Brain Regions ◽  
Decision Task ◽  
Prediction Errors ◽  
Model Based ◽  
Model Free ◽  
Bias Variance ◽  
The Brain

AbstractThe goal of learning is to maximize future rewards by minimizing prediction errors. Evidence have shown that the brain achieves this by combining model-based and model-free learning. However, the prediction error minimization is challenged by a bias-variance tradeoff, which imposes constraints on each strategy’s performance. We provide new theoretical insight into how this tradeoff can be resolved through the adaptive control of model-based and model-free learning. The theory predicts the baseline correction for prediction error reduces the lower bound of the bias–variance error by factoring out irreducible noise. Using a Markov decision task with context changes, we showed behavioral evidence of adaptive control. Model-based behavioral analyses show that the prediction error baseline signals context changes to improve adaptability. Critically, the neural results support this view, demonstrating multiplexed representations of prediction error baseline within the ventrolateral and ventromedial prefrontal cortex, key brain regions known to guide model-based and model-free learning.One sentence summaryA theoretical, behavioral, computational, and neural account of how the brain resolves the bias-variance tradeoff during reinforcement learning is described.

scholarly journals Context-dependent multiplexing by individual VTA dopamine neurons

2018 ◽  
Author(s):  
Kremer Yves ◽  
Flakowski Jérôme ◽  
Rohner Clément ◽  
Lüscher Christian
Keyword(s):  
Prediction Error ◽  
Internal Representation ◽  
Dopamine Neurons ◽  
Neuron Activity ◽  
Movement Velocity ◽  
Tonic Firing ◽  
Reward Prediction ◽  
Directed Action ◽  
Operant Task

AbstractDopamine (DA) neurons of the ventral tegmental area (VTA) track external cues and rewards to generate a reward prediction error (RPE) signal during Pavlovian conditioning. Here we explored how RPE is implemented for a self-paced, operant task in freely moving mice. The animal could trigger a reward-predicting cue by remaining in a specific location of an operant box for a brief time before moving to a spout for reward collection. In vivo single-unit recordings revealed phasic responses to the cue and reward in correct trials, while with failures the activity paused, reflecting positive and negative error signals of a reward prediction. In addition, a majority of VTA DA neurons also encoded parameters of the goal-directed action (e.g. movement velocity, acceleration, distance to goal and licking) by changes in tonic firing rate. Such multiplexing of individual neurons was only apparent while the mouse was engaged in the task. We conclude that a multiplexed internal representation during the task modulates VTA DA neuron activity, indicating a multimodal prediction error that shapes behavioral adaptation of a self-paced goal-directed action.

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