scholarly journals Deletion of the alternative splice variant KChIP4a in midbrain dopamine neurons selectively enhances extinction learning

2018 ◽  
Author(s):  
Kauê Machado Costa ◽  
Jochen Roeper
Keyword(s):  
Splice Variant ◽  
Dopamine Neuron ◽  
Dopamine Neurons ◽  
Prediction Errors ◽  
Β Subunit ◽  
Extinction Learning ◽  
Negative Prediction ◽  
Midbrain Dopamine ◽  
Specific Deletion ◽  
Midbrain Dopamine Neurons

AbstractInhibition of midbrain dopamine neurons is thought to underlie the signaling of events that are less rewarding than expected and drive learning based on these negative prediction errors. It has recently been shown that Kv4.3 channels influence the integration of inhibitory inputs in specific subpopulations of dopamine neurons. The functional properties of Kv4.3 channels are themselves strongly determined by the binding of auxiliary β-subunits; among them KChIP4a stands-out for its unique combination of modulatory effects. These include decreasing surface membrane trafficking and slowing inactivation kinetics. Therefore, we hypothesized that KChIP4a expression in dopamine neurons could play a crucial role in behavior, in particular by affecting the computation of negative prediction errors. We developed a mouse line where the alternative exon that codes for the KChIP4a splice variant was selectively deleted in midbrain dopamine neurons. In a reward-based reinforcement learning task, we observed that dopamine neuron-specific KChIP4a deletion selectively accelerated the rate of extinction learning, without impacting the acquisition of conditioned responses. We further found that this effect was due to a faster decrease in the initiation rate of goal-directed behaviors, and not faster increases in action disengagement. Furthermore, computational fitting of the behavioral data with a Rescorla-Wagner model confirmed that the observed phenotype was attributable to a selective increase in the learning rate from negative prediction errors. Finally, KChIP4a deletion did not affect performance in other dopamine-sensitive behavioral tasks that did not involve learning from disappointing events, including an absence of effects on working memory, locomotion and novelty preference. Taken together, our results demonstrate that an exon- and midbrain dopamine neuron-specific deletion of an A-type K+ channel β-subunit leads to a selective gain of function in extinction learning.One Sentence SummaryExon- and midbrain dopamine neuron-specific deletion of the Kv4 channel β-subunit KChIP4a selectively accelerates extinction learning

scholarly journals Purity and Enrichment of Laser-Microdissected Midbrain Dopamine Neurons

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Amanda L. Brown ◽  
Trevor A. Day ◽  
Christopher V. Dayas ◽  
Doug W. Smith
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Dopamine Neuron ◽  
Dopamine Neurons ◽  
Acid Decarboxylase ◽  
Cell Groups ◽  
Midbrain Dopamine ◽  
High Degree ◽  
Midbrain Dopamine Neurons

The ability to microdissect individual cells from the nervous system has enormous potential, as it can allow for the study of gene expression in phenotypically identified cells. However, if the resultant gene expression profiles are to be accurately ascribed, it is necessary to determine the extent of contamination by nontarget cells in the microdissected sample. Here, we show that midbrain dopamine neurons can be laser-microdissected to a high degree of enrichment and purity. The average enrichment for tyrosine hydroxylase (TH) gene expression in the microdissected sample relative to midbrain sections was approximately 200-fold. For the dopamine transporter (DAT) and the vesicular monoamine transporter type 2 (Vmat2), average enrichments were approximately 100- and 60-fold, respectively. Glutamic acid decarboxylase (Gad65) expression, a marker for GABAergic neurons, was several hundredfold lower than dopamine neuron-specific genes. Glial cell and glutamatergic neuron gene expression were not detected in microdissected samples. Additionally, SN and VTA dopamine neurons had significantly different expression levels of dopamine neuron-specific genes, which likely reflects functional differences between the two cell groups. This study demonstrates that it is possible to laser-microdissect dopamine neurons to a high degree of cell purity. Therefore gene expression profiles can be precisely attributed to the targeted microdissected cells.

scholarly journals Midbrain dopamine neurons provide teaching signals for goal-directed navigation

2021 ◽  
Author(s):  
Karolina Farrell ◽  
Armin Lak ◽  
Aman B Saleem
Keyword(s):  
Virtual Reality ◽  
Visual Cues ◽  
Task Engagement ◽  
Dopamine Neurons ◽  
List Type ◽  
Prediction Errors ◽  
Learning Stage ◽  
Midbrain Dopamine ◽  
Improved Performance ◽  
Midbrain Dopamine Neurons

SummaryIn naturalistic environments, animals navigate in order to harvest rewards. Successful goal-directed navigation requires learning to accurately estimate location and select optimal state-dependent actions. Midbrain dopamine neurons are known to be involved in reward value learning1–13. They have also been linked to reward location learning, as they play causal roles in place preference14,15 and enhance spatial memory16–21. Dopamine neurons are therefore ideally placed to provide teaching signals for goal-directed navigation. To test this, we imaged dopamine neural activity as mice learned to navigate in a closed-loop virtual reality corridor and lick to report the reward location. Across learning, phasic dopamine responses developed to visual cues and trial outcome that resembled reward prediction errors and indicated the animal’s estimate of the reward location. We also observed the development of pre-reward ramping activity, the slope of which was modulated by both learning stage and task engagement. The slope of the dopamine ramp was correlated with the accuracy of licks in the next trial, suggesting that the ramp sculpted accurate location-specific action during navigation. Our results indicate that midbrain dopamine neurons, through both their phasic and ramping activity, provide teaching signals for improving goal-directed navigation.HighlightsWe investigated midbrain dopamine activity in mice learning a goal-directed navigation task in virtual realityPhasic dopamine signals reflected prediction errors with respect to subjective estimate of reward locationA slow ramp in dopamine activity leading up to reward location developed over learning and was enhanced with task engagementPositive ramp slopes were followed by improved performance on subsequent trials, suggesting a teaching role during goal-directed navigation

scholarly journals Rethinking dopamine as generalized prediction error

2017 ◽  
Author(s):  
Matthew P.H. Gardner ◽  
Geoffrey Schoenbaum ◽  
Samuel J. Gershman
Keyword(s):  
Reinforcement Learning ◽  
Prediction Error ◽  
Dopamine Neurons ◽  
Prediction Errors ◽  
Model Free ◽  
Reward Prediction ◽  
Midbrain Dopamine ◽  
Sensory Prediction ◽  
Lines Of Evidence ◽  
Midbrain Dopamine Neurons

AbstractMidbrain dopamine neurons are commonly thought to report a reward prediction error, as hypothesized by reinforcement learning theory. While this theory has been highly successful, several lines of evidence suggest that dopamine activity also encodes sensory prediction errors unrelated to reward. Here we develop a new theory of dopamine function that embraces a broader conceptualization of prediction errors. By signaling errors in both sensory and reward predictions, dopamine supports a form of reinforcement learning that lies between model-based and model-free algorithms. This account remains consistent with current canon regarding the correspondence between dopamine transients and reward prediction errors, while also accounting for new data suggesting a role for these signals in phenomena such as sensory preconditioning and identity unblocking, which ostensibly draw upon knowledge beyond reward predictions.

scholarly journals In vivo patch-clamp recordings reveal distinct subthreshold signatures and threshold dynamics of midbrain dopamine neurons

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Kanako Otomo ◽  
Jessica Perkins ◽  
Anand Kulkarni ◽  
Strahinja Stojanovic ◽  
Jochen Roeper ◽  
...  
Keyword(s):  
Membrane Potential ◽  
Action Potential ◽  
Dopamine Neuron ◽  
Dopamine Neurons ◽  
Firing Patterns ◽  
Action Potential Threshold ◽  
Midbrain Dopamine ◽  
Potential Threshold ◽  
Midbrain Dopamine Neurons

AbstractThe in vivo firing patterns of ventral midbrain dopamine neurons are controlled by afferent and intrinsic activity to generate sensory cue and prediction error signals that are essential for reward-based learning. Given the absence of in vivo intracellular recordings during the last three decades, the subthreshold membrane potential events that cause changes in dopamine neuron firing patterns remain unknown. To address this, we established in vivo whole-cell recordings and obtained over 100 spontaneously active, immunocytochemically-defined midbrain dopamine neurons in isoflurane-anaesthetized adult mice. We identified a repertoire of subthreshold membrane potential signatures associated with distinct in vivo firing patterns. Dopamine neuron activity in vivo deviated from single-spike pacemaking by phasic increases in firing rate via two qualitatively distinct biophysical mechanisms: 1) a prolonged hyperpolarization preceding rebound bursts, accompanied by a hyperpolarizing shift in action potential threshold; and 2) a transient depolarization leading to high-frequency plateau bursts, associated with a depolarizing shift in action potential threshold. Our findings define a mechanistic framework for the biophysical implementation of dopamine neuron firing patterns in the intact brain.

scholarly journals Dopamine neuron morphology and output are differentially controlled by mTORC1 and mTORC2

2021 ◽  
Author(s):  
Polina Kosillo ◽  
Kamran M. Ahmed ◽  
Bradley M. Roberts ◽  
Stephanie J. Cragg ◽  
Helen S. Bateup
Keyword(s):  
Therapeutic Strategies ◽  
Structure And Function ◽  
Dopamine Neuron ◽  
Dopamine Neurons ◽  
Intrinsic Excitability ◽  
Brain Disorders ◽  
Neuron Morphology ◽  
Midbrain Dopamine ◽  
And Function ◽  
Specific Deletion

The mTOR pathway is an essential regulator of cell growth and metabolism. Midbrain dopamine neurons are particularly sensitive to mTOR signaling status as activation or inhibition of mTOR alters their morphology and physiology. mTOR exists in two distinct multiprotein complexes termed mTORC1 and mTORC2. How each of these complexes affect dopamine neuron properties and whether they act together or independently is unknown. Here we investigated this in mice with dopamine neuron-specific deletion of Rptor or Rictor, which encode obligatory components of mTORC1 or mTORC2, respectively. We find that inhibition of mTORC1 strongly and broadly impacts dopamine neuron structure and function causing somatodendritic and axonal hypotrophy, increased intrinsic excitability, decreased dopamine production, and impaired dopamine release. In contrast, inhibition of mTORC2 has more subtle effects, with selective alterations to the output of ventral tegmental area dopamine neurons. As mTOR is involved in several brain disorders caused by dopaminergic dysregulation including Parkinson's disease and addiction, our results have implications for understanding the pathophysiology and potential therapeutic strategies for these diseases.

scholarly journals Midbrain dopamine neurons compute inferred and cached value prediction errors in a common framework

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Brian F Sadacca ◽  
Joshua L Jones ◽  
Geoffrey Schoenbaum
Keyword(s):  
Dopamine Neurons ◽  
Prediction Errors ◽  
Temporal Difference ◽  
Use Value ◽  
Value Prediction ◽  
Reward Prediction ◽  
Common Framework ◽  
Midbrain Dopamine ◽  
Midbrain Dopamine Neurons ◽  
Do So

Midbrain dopamine neurons have been proposed to signal reward prediction errors as defined in temporal difference (TD) learning algorithms. While these models have been extremely powerful in interpreting dopamine activity, they typically do not use value derived through inference in computing errors. This is important because much real world behavior – and thus many opportunities for error-driven learning – is based on such predictions. Here, we show that error-signaling rat dopamine neurons respond to the inferred, model-based value of cues that have not been paired with reward and do so in the same framework as they track the putative cached value of cues previously paired with reward. This suggests that dopamine neurons access a wider variety of information than contemplated by standard TD models and that, while their firing conforms to predictions of TD models in some cases, they may not be restricted to signaling errors from TD predictions.

scholarly journals Subthreshold repertoire and threshold dynamics of midbrain dopamine neuron firing in vivo

2020 ◽  
Author(s):  
Kanako Otomo ◽  
Jessica Perkins ◽  
Anand Kulkarni ◽  
Strahinja Stojanovic ◽  
Jochen Roeper ◽  
...  
Keyword(s):  
Action Potential ◽  
Prediction Error ◽  
Dopamine Neuron ◽  
Dopamine Neurons ◽  
Threshold Dynamics ◽  
Action Potential Threshold ◽  
Midbrain Dopamine ◽  
Potential Threshold ◽  
Midbrain Dopamine Neurons

AbstractThe firing pattern of ventral midbrain dopamine neurons is controlled by afferent and intrinsic activity to generate prediction error signals that are essential for reward-based learning. Given the absence of intracellular in vivo recordings in the last three decades, the subthreshold membrane potential events that cause changes in dopamine neuron firing patterns remain unknown. By establishing stable in vivo whole-cell recordings of >100 spontaneously active midbrain dopamine neurons in anaesthetized mice, we identified the repertoire of subthreshold membrane potential signatures associated with distinct in vivo firing patterns. We demonstrate that dopamine neuron in vivo activity deviates from a single spike pacemaker pattern by eliciting transient increases in firing rate generated by at least two diametrically opposing biophysical mechanisms: a transient depolarization resulting in high frequency plateau bursts associated with a reactive, depolarizing shift in action potential threshold; and a prolonged hyperpolarization preceding slower rebound bursts characterized by a predictive, hyperpolarizing shift in action potential threshold. Our findings therefore illustrate a framework for the biophysical implementation of prediction error and sensory cue coding in dopamine neurons by tuning action potential threshold dynamics.

scholarly journals Rethinking dopamine as generalized prediction error

2018 ◽  
Vol 285 (1891) ◽  
pp. 20181645 ◽  
Author(s):  
Matthew P. H. Gardner ◽  
Geoffrey Schoenbaum ◽  
Samuel J. Gershman
Keyword(s):  
Reinforcement Learning ◽  
Prediction Error ◽  
Dopamine Neurons ◽  
Prediction Errors ◽  
Model Free ◽  
Reward Prediction ◽  
Midbrain Dopamine ◽  
Sensory Prediction ◽  
Lines Of Evidence ◽  
Midbrain Dopamine Neurons

Midbrain dopamine neurons are commonly thought to report a reward prediction error (RPE), as hypothesized by reinforcement learning (RL) theory. While this theory has been highly successful, several lines of evidence suggest that dopamine activity also encodes sensory prediction errors unrelated to reward. Here, we develop a new theory of dopamine function that embraces a broader conceptualization of prediction errors. By signalling errors in both sensory and reward predictions, dopamine supports a form of RL that lies between model-based and model-free algorithms. This account remains consistent with current canon regarding the correspondence between dopamine transients and RPEs, while also accounting for new data suggesting a role for these signals in phenomena such as sensory preconditioning and identity unblocking, which ostensibly draw upon knowledge beyond reward predictions.

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