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The Journal of Neuroscience : the... May 2014Schizophrenia is associated with upregulation of dopamine (DA) release in the caudate nucleus. The caudate has dense connections with the orbitofrontal cortex (OFC) via...
Schizophrenia is associated with upregulation of dopamine (DA) release in the caudate nucleus. The caudate has dense connections with the orbitofrontal cortex (OFC) via the frontostriatal loops, and both areas exhibit pathophysiological change in schizophrenia. Despite evidence that abnormalities in dopaminergic neurotransmission and prefrontal cortex function co-occur in schizophrenia, the influence of OFC DA on caudate DA and reinforcement processing is poorly understood. To test the hypothesis that OFC dopaminergic dysfunction disrupts caudate dopamine function, we selectively depleted dopamine from the OFC of marmoset monkeys and measured striatal extracellular dopamine levels (using microdialysis) and dopamine D2/D3 receptor binding (using positron emission tomography), while modeling reinforcement-related behavior in a discrimination learning paradigm. OFC dopamine depletion caused an increase in tonic dopamine levels in the caudate nucleus and a corresponding reduction in D2/D3 receptor binding. Computational modeling of behavior showed that the lesion increased response exploration, reducing the tendency to persist with a recently chosen response side. This effect is akin to increased response switching previously seen in schizophrenia and was correlated with striatal but not OFC D2/D3 receptor binding. These results demonstrate that OFC dopamine depletion is sufficient to induce striatal hyperdopaminergia and changes in reinforcement learning relevant to schizophrenia.
Topics: Animals; Callithrix; Caudate Nucleus; Dopamine; Female; Frontal Lobe; Learning; Male; Reinforcement, Psychology; Up-Regulation
PubMed: 24872570
DOI: 10.1523/JNEUROSCI.0718-14.2014 -
Nature Communications Jul 2022Optimal behavior requires interpreting environmental cues that indicate when to perform actions. Dopamine is important for learning about reward-predicting events, but...
Optimal behavior requires interpreting environmental cues that indicate when to perform actions. Dopamine is important for learning about reward-predicting events, but its role in adapting to inhibitory cues is unclear. Here we show that when mice can earn rewards in the absence but not presence of an auditory cue, dopamine level in the ventral striatum accurately reflects reward availability in real-time over a sustained period (80 s). In addition, unpredictable transitions between different states of reward availability are accompanied by rapid (~1-2 s) dopamine transients that deflect negatively at the onset and positively at the offset of the cue. This Dopamine encoding of reward availability and transitions between reward availability states is not dependent on reward or activity evoked dopamine release, appears before mice learn the task and is sensitive to motivational state. Our findings are consistent across different techniques including electrochemical recordings and fiber photometry with genetically encoded optical sensors for calcium and dopamine.
Topics: Animals; Cues; Dopamine; Mice; Nucleus Accumbens; Reward; Ventral Striatum
PubMed: 35778414
DOI: 10.1038/s41467-022-31377-2 -
Journal of Neurophysiology Jun 2021Motor learning is a core aspect of human life and appears to be ubiquitous throughout the animal kingdom. Dopamine, a neuromodulator with a multifaceted role in synaptic... (Comparative Study)
Comparative Study Review
Motor learning is a core aspect of human life and appears to be ubiquitous throughout the animal kingdom. Dopamine, a neuromodulator with a multifaceted role in synaptic plasticity, may be a key signaling molecule for motor skill learning. Though typically studied in the context of reward-based associative learning, dopamine appears to be necessary for some types of motor learning. Mesencephalic dopamine structures are highly conserved among vertebrates, as are some of their primary targets within the basal ganglia, a subcortical circuit important for motor learning and motor control. With a focus on the benefits of cross-species comparisons, this review examines how "model-free" and "model-based" computational frameworks for understanding dopamine's role in associative learning may be applied to motor learning. The hypotheses that dopamine could drive motor learning either by functioning as a reward prediction error, through passive facilitating of normal basal ganglia activity, or through other mechanisms are examined in light of new studies using humans, rodents, and songbirds. Additionally, new paradigms that could enhance our understanding of dopamine's role in motor learning by bridging the gap between the theoretical literature on motor learning in humans and other species are discussed.
Topics: Animals; Brain; Dopamine; Humans; Learning; Models, Biological; Motor Skills; Primates; Rodentia; Songbirds
PubMed: 33978497
DOI: 10.1152/jn.00648.2020 -
Cell Communication and Signaling : CCS Jan 2024Parkinson's disease (PD), a chronic and severe neurodegenerative disease, is pathologically characterized by the selective loss of nigrostriatal dopaminergic neurons....
BACKGROUND
Parkinson's disease (PD), a chronic and severe neurodegenerative disease, is pathologically characterized by the selective loss of nigrostriatal dopaminergic neurons. Dopamine (DA), the neurotransmitter produced by dopaminergic neurons, and its metabolites can covalently modify proteins, and dysregulation of this process has been implicated in neuronal loss in PD. However, much remains unknown about the protein targets.
METHODS
In the present work, we designed and synthesized a dopamine probe (DA-P) to screen and identify the potential protein targets of DA using activity-based protein profiling (ABPP) technology in combination with liquid chromatography-tandem mass spectrometry (LC-MS/MS). In situ pull-down assays, cellular thermal shift assays (CETSAs) and immunofluorescence were performed to confirm the DA modifications on these hits. To investigate the effects of DA modifications, we measured the enzymatic activities of these target proteins, evaluated glycolytic stress and mitochondrial respiration by Seahorse tests, and systematically analyzed the changes in metabolites with unbiased LC-MS/MS-based non-targeted metabolomics profiling.
RESULTS
We successfully identified three glycolytic proteins, aldolase A, α-enolase and pyruvate kinase M2 (PKM2), as the binding partners of DA. DA bound to Glu166 of α-enolase, Cys49 and Cys424 of PKM2, and Lys230 of aldolase A, inhibiting the enzymatic activities of α-enolase and PKM2 and thereby impairing ATP synthesis, resulting in mitochondrial dysfunction.
CONCLUSIONS
Recent research has revealed that enhancing glycolysis can offer protection against PD. The present study identified that the glycolytic pathway is vulnerable to disruption by DA, suggesting a promising avenue for potential therapeutic interventions. Safeguarding glycolysis against DA-related disruption could be a potential therapeutic intervention for PD.
Topics: Humans; Parkinson Disease; Dopamine; Fructose-Bisphosphate Aldolase; Chromatography, Liquid; Neurodegenerative Diseases; Tandem Mass Spectrometry; Proteins; Phosphopyruvate Hydratase
PubMed: 38287374
DOI: 10.1186/s12964-024-01478-0 -
Neuroscience Research Feb 2024Dopamine neurons have long been thought to facilitate learning by broadcasting reward prediction error (RPE), a teaching signal used in machine learning, but more recent... (Review)
Review
Dopamine neurons have long been thought to facilitate learning by broadcasting reward prediction error (RPE), a teaching signal used in machine learning, but more recent work has advanced alternative models of dopamine's computational role. Here, I revisit this critical issue and review new experimental evidences that tighten the link between dopamine activity and RPE. First, I introduce the recent observation of a gradual backward shift of dopamine activity that had eluded researchers for over a decade. I also discuss several other findings, such as dopamine ramping, that were initially interpreted to conflict but later found to be consistent with RPE. These findings improve our understanding of neural computation in dopamine neurons.
Topics: Dopaminergic Neurons; Dopamine; Reward; Conditioning, Classical
PubMed: 37451506
DOI: 10.1016/j.neures.2023.07.003 -
Current Biology : CB Dec 2021Dopamine has been suggested to encode cue-reward prediction errors during Pavlovian conditioning, signaling discrepancies between actual versus expected reward predicted...
Dopamine has been suggested to encode cue-reward prediction errors during Pavlovian conditioning, signaling discrepancies between actual versus expected reward predicted by the cues. While this theory has been widely applied to reinforcement learning concerning instrumental actions, whether dopamine represents action-outcome prediction errors and how it controls sequential behavior remain largely unknown. The vast majority of previous studies examining dopamine responses primarily have used discrete reward-predictive stimuli, whether Pavlovian conditioned stimuli for which no action is required to earn reward or explicit discriminative stimuli that essentially instruct an animal how and when to respond for reward. Here, by training mice to perform optogenetic intracranial self-stimulation, we examined how self-initiated goal-directed behavior influences nigrostriatal dopamine transmission during single and sequential instrumental actions, in behavioral contexts with minimal overt changes in the animal's external environment. We found that dopamine release evoked by direct optogenetic stimulation was dramatically reduced when delivered as the consequence of the animal's own action, relative to non-contingent passive stimulation. This dopamine suppression generalized to food rewards was specific to the reinforced action, was temporally restricted to counteract the expected outcome, and exhibited sequence-selectivity consistent with hierarchical control of sequential behavior. These findings demonstrate that nigrostriatal dopamine signals sequence-specific prediction errors in action-outcome associations, with fundamental implications for reinforcement learning and instrumental behavior in health and disease.
Topics: Animals; Conditioning, Classical; Cues; Dopamine; Mice; Reinforcement, Psychology; Reward
PubMed: 34637751
DOI: 10.1016/j.cub.2021.09.040 -
The Analyst Feb 2020Fast-scan cyclic voltammetry (FSCV) is used with carbon-fiber microelectrodes for the real-time detection of neurotransmitters on the subsecond time scale. With FSCV,... (Review)
Review
Fast-scan cyclic voltammetry (FSCV) is used with carbon-fiber microelectrodes for the real-time detection of neurotransmitters on the subsecond time scale. With FSCV, the potential is ramped up from a holding potential to a switching potential and back, usually at a 400 V s-1 scan rate and a frequency of 10 Hz. The plot of current vs. applied potential, the cyclic voltammogram (CV), has a very different shape for FSCV than for traditional cyclic voltammetry collected at scan rates which are 1000-fold slower. Here, we explore the theory of FSCV, with a focus on dopamine detection. First, we examine the shape of the CVs. Background currents, which are 100-fold higher than faradaic currents, are subtracted out. Peak separation is primarily due to slow electron transfer kinetics, while the symmetrical peak shape is due to exhaustive electrolysis of all the adsorbed neurotransmitters. Second, we explain the origins of the dopamine waveform, and the factors that limit the holding potential (oxygen reduction), switching potential (water oxidation), scan rate (electrode instability), and repetition rate (adsorption). Third, we discuss data analysis, from data visualization with color plots, to the automated algorithms like principal components regression that distinguish dopamine from pH changes. Finally, newer applications are discussed, including optimization of waveforms for analyte selectivity, carbon nanomaterial electrodes that trap dopamine, and basal level measurements that facilitate neurotransmitter measurements on a longer time scale. FSCV theory is complex, but understanding it enables better development of new techniques to monitor neurotransmitters in vivo.
Topics: Animals; Data Analysis; Dopamine; Electrochemistry; Humans; Time Factors
PubMed: 31922176
DOI: 10.1039/c9an01586h -
Neuron Feb 2016Cognitive control is subjectively costly, suggesting that engagement is modulated in relationship to incentive state. Dopamine appears to play key roles. In particular,... (Review)
Review
Cognitive control is subjectively costly, suggesting that engagement is modulated in relationship to incentive state. Dopamine appears to play key roles. In particular, dopamine may mediate cognitive effort by two broad classes of functions: (1) modulating the functional parameters of working memory circuits subserving effortful cognition, and (2) mediating value-learning and decision-making about effortful cognitive action. Here, we tie together these two lines of research, proposing how dopamine serves "double duty", translating incentive information into cognitive motivation.
Topics: Animals; Brain; Cognition; Decision Making; Dopamine; Humans; Learning; Memory, Short-Term; Motivation; Neural Pathways
PubMed: 26889810
DOI: 10.1016/j.neuron.2015.12.029 -
Acta Medica Okayama Jun 2008Oxidative stress, including the reactive oxygen or nitrogen species generated in the enzymatical oxidationor auto-oxidation of an excess amount of dopamine, is thought... (Review)
Review
Oxidative stress, including the reactive oxygen or nitrogen species generated in the enzymatical oxidationor auto-oxidation of an excess amount of dopamine, is thought to play an important role in dopaminergic neurotoxicity. Dopamine and its metabolites containing 2 hydroxyl residues exert cytotoxicityin dopaminergic neuronal cells, primarily due to the generation of highly reactive dopamine and DOPA quinones. Dopamine and DOPA quinones may irreversibly alter protein function through the formation of 5-cysteinyl-catechols on the proteins. Furthermore, the quinone formation is closely linked to other representative hypotheses such as mitochondrial dysfunction, inflammation, oxidative stress, and dysfunction of the ubiquitin-proteasome system, in the pathogenesis of neurodegenerative diseases. Therefore, pathogenic effects of the dopamine quinone have recently focused on dopaminergicneuron-specific oxidative stress. In this article, we primarily review recent studies on the pathogenicity of quinone formation, in addition to several neuroprotective approaches against dopaminequinone-induced dysfunction of dopaminergic neurons.
Topics: Animals; Disease Models, Animal; Dopamine; Free Radicals; Humans; Neurons; Oxidative Stress; Parkinson Disease
PubMed: 18596830
DOI: 10.18926/AMO/30942 -
Science Advances Dec 2023In the mammalian brain, midbrain dopamine neuron activity is hypothesized to encode reward prediction errors that promote learning and guide behavior by causing rapid...
In the mammalian brain, midbrain dopamine neuron activity is hypothesized to encode reward prediction errors that promote learning and guide behavior by causing rapid changes in dopamine levels in target brain regions. This hypothesis (and alternatives regarding dopamine's role in punishment-learning) has limited direct evidence in humans. We report intracranial, subsecond measurements of dopamine release in human striatum measured, while volunteers (i.e., patients undergoing deep brain stimulation surgery) performed a probabilistic reward and punishment learning choice task designed to test whether dopamine release encodes only reward prediction errors or whether dopamine release may also encode adaptive punishment learning signals. Results demonstrate that extracellular dopamine levels can encode both reward and punishment prediction errors within distinct time intervals via independent valence-specific pathways in the human brain.
Topics: Animals; Humans; Dopamine; Punishment; Reward; Learning; Brain; Mammals
PubMed: 38039368
DOI: 10.1126/sciadv.adi4927