scholarly journals Models of heterogeneous dopamine signaling in an insect learning and memory center

2021 ◽  
Vol 17 (8) ◽  
pp. e1009205
Author(s):  
Linnie Jiang ◽  
Ashok Litwin-Kumar
Keyword(s):  
Mushroom Body ◽  
Internal State ◽  
Dopamine Neurons ◽  
Population Activity ◽  
Insect Learning ◽  
External Reinforcement ◽  
Learned Behaviors ◽  
Dopamine Signaling ◽  
And Behavior ◽  
Task Parameters

The Drosophila mushroom body exhibits dopamine dependent synaptic plasticity that underlies the acquisition of associative memories. Recordings of dopamine neurons in this system have identified signals related to external reinforcement such as reward and punishment. However, other factors including locomotion, novelty, reward expectation, and internal state have also recently been shown to modulate dopamine neurons. This heterogeneity is at odds with typical modeling approaches in which these neurons are assumed to encode a global, scalar error signal. How is dopamine dependent plasticity coordinated in the presence of such heterogeneity? We develop a modeling approach that infers a pattern of dopamine activity sufficient to solve defined behavioral tasks, given architectural constraints informed by knowledge of mushroom body circuitry. Model dopamine neurons exhibit diverse tuning to task parameters while nonetheless producing coherent learned behaviors. Notably, reward prediction error emerges as a mode of population activity distributed across these neurons. Our results provide a mechanistic framework that accounts for the heterogeneity of dopamine activity during learning and behavior.

scholarly journals Models of heterogeneous dopamine signaling in an insect learning and memory center

2019 ◽  
Author(s):  
Linnie Jiang ◽  
Ashok Litwin-Kumar
Keyword(s):  
Mushroom Body ◽  
Internal State ◽  
Dopamine Neurons ◽  
Insect Learning ◽  
External Reinforcement ◽  
Learned Behaviors ◽  
Architectural Constraints ◽  
Dopamine Signaling ◽  
And Behavior ◽  
Task Parameters

AbstractThe Drosophila mushroom body exhibits dopamine dependent synaptic plasticity that underlies the acquisition of associative memories. Recordings of dopamine neurons in this system have identified signals related to external reinforcement such as reward and punishment. However, other factors including locomotion, novelty, reward expectation, and internal state have also recently been shown to modulate dopamine neurons. This heterogeneity is at odds with typical modeling approaches in which these neurons are assumed to encode a global, scalar error signal. How is dopamine dependent plasticity coordinated in the presence of such heterogeneity? We develop a modeling approach that infers a pattern of dopamine activity sufficient to solve defined behavioral tasks, given architectural constraints informed by knowledge of mushroom body circuitry. Model dopamine neurons exhibit diverse tuning to task parameters while nonetheless producing coherent learned behaviors. Our results provide a mechanistic framework that accounts for the heterogeneity of dopamine activity during learning and behavior.

scholarly journals Distinct roles for dopamine clearance mechanisms in regulating behavioral flexibility

2021 ◽  
Author(s):  
Clio Korn ◽  
Thomas Akam ◽  
Kristian H. R. Jensen ◽  
Cristiana Vagnoni ◽  
Anna Huber ◽  
...  
Keyword(s):  
Decision Making ◽  
Behavioral Flexibility ◽  
Dopamine Neurons ◽  
Nucleus Accumbens Core ◽  
Comt Inhibition ◽  
Improved Performance ◽  
Dopamine Signaling ◽  
Precise Relationship ◽  
And Behavior ◽  
Kinetics Of

AbstractDopamine plays a crucial role in adaptive behavior, and dysfunctional dopamine is implicated in multiple psychiatric conditions characterized by inflexible or inconsistent choices. However, the precise relationship between dopamine and flexible decision making remains unclear. One reason is that, while many studies have focused on the activity of dopamine neurons, efficient dopamine signaling also relies on clearance mechanisms, notably the dopamine transporter (DAT), which predominates in striatum, and catechol-O-methyltransferase (COMT), which predominates in cortex. The exact locus, extent, and timescale of the effects of DAT and COMT are uncertain. Moreover, there is limited data on how acute disruption of either mechanism affects flexible decision making strategies mediated by cortico-striatal networks. To address these issues, we combined pharmacological modulation of DAT and COMT with electrochemistry and behavior in mice. DAT blockade, but not COMT inhibition, regulated sub-second dopamine release in the nucleus accumbens core, but surprisingly neither clearance mechanism affected evoked release in prelimbic cortex. This was not due to a lack of sensitivity, as both amphetamine and atomoxetine changed the kinetics of sub-second release. In a multi-step decision making task where mice had to respond to reversals in either reward probabilities or the choice sequence to reach the goal, DAT blockade selectively impaired, and COMT inhibition improved, performance after reward reversals, but neither manipulation affected the adaptation of choices after action-state transition reversals. Together, our data suggest that DAT and COMT shape specific aspects of behavioral flexibility by regulating different aspects of the kinetics of striatal and cortical dopamine, respectively.

scholarly journals Distinct roles for dopamine clearance mechanisms in regulating behavioral flexibility

2019 ◽  
Author(s):  
Clio Korn ◽  
Thomas Akam ◽  
Kristian H R Jensen ◽  
Cristiana Vagnoni ◽  
Anna Huber ◽  
...  
Keyword(s):  
Decision Making ◽  
Behavioral Flexibility ◽  
Dopamine Neurons ◽  
Nucleus Accumbens Core ◽  
Comt Inhibition ◽  
Clearance Mechanism ◽  
Improved Performance ◽  
Dopamine Signaling ◽  
Precise Relationship ◽  
And Behavior

Dopamine plays a crucial role in adaptive behavior, and dysfunctional dopamine is implicated in multiple psychiatric conditions characterized by inflexible or inconsistent choices. However, the precise relationship between dopamine and flexible decision making remains unclear. One reason is that, while many studies have focused on the activity of dopamine neurons, efficient dopamine signaling also relies on clearance mechanisms, notably the dopamine transporter (DAT), which predominates in striatum, and catechol-O-methyltransferase (COMT), which predominates in cortex. The exact locus, extent, and timescale of the effects of DAT and COMT are uncertain. Moreover, there is limited data on how acute disruption of either mechanism affects flexible decision making strategies mediated by cortico-striatal networks. To address these issues, we combined pharmacological modulation of DAT and COMT with electrochemistry and behavior in mice. DAT blockade, but not COMT inhibition, regulated sub-second dopamine release in the nucleus accumbens core, but surprisingly neither clearance mechanism affected evoked release in prelimbic cortex. This was not due to a lack of sensitivity, as both amphetamine and atomoxetine changed the kinetics of sub-second release. In a multi-step decision making task where mice had to respond to reversals in either reward probabilities or the choice sequence to reach the goal, DAT blockade selectively impaired, and COMT inhibition improved, performance after reward reversals, but neither manipulation affected the adaptation of choices after action-state transition reversals. Together, our data suggest that DAT and COMT shape specific aspects of behavioral flexibility by regulating striatal and cortical dopamine, respectively, at fast and slow timescales.

scholarly journals Learning is shaped by abrupt changes in neural engagement

2020 ◽  
Author(s):  
Jay A. Hennig ◽  
Emily R. Oby ◽  
Matthew D. Golub ◽  
Lindsay A. Bahureksa ◽  
Patrick T. Sadtler ◽  
...  
Keyword(s):  
Neural Activity ◽  
Internal State ◽  
Neural Population ◽  
Behavioral Performance ◽  
Population Activity ◽  
Large Fluctuations ◽  
Abrupt Changes ◽  
Internal States ◽  
Task Goals ◽  
And Behavior

AbstractInternal states such as arousal, attention, and motivation are known to modulate brain-wide neural activity, but how these processes interact with learning is not well understood. During learning, the brain must modify the neural activity it produces to improve behavioral performance. How do internal states affect the evolution of this learning process? Using a brain-computer interface (BCI) learning paradigm in non-human primates, we identified large fluctuations in neural population activity in motor cortex (M1) indicative of arousal-like internal state changes. These fluctuations drove population activity along dimensions we term neural engagement axes. Neural engagement increased abruptly at the start of learning, and then gradually retreated. In a BCI, the causal relationship between neural activity and behavior is known. This allowed us to understand how these changes impacted behavioral performance for different task goals. We found that neural engagement interacted with learning, helping to explain why animals learned some task goals more quickly than others.

scholarly journals Midbrain dopamine neurons signal aversion in a reward-context-dependent manner

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Hideyuki Matsumoto ◽  
Ju Tian ◽  
Naoshige Uchida ◽  
Mitsuko Watabe-Uchida
Keyword(s):  
Dopamine Neurons ◽  
Prediction Errors ◽  
Dependent Manner ◽  
Value Prediction ◽  
Signal Value ◽  
Aversive Events ◽  
High Reward ◽  
Midbrain Dopamine ◽  
Dopamine Signaling ◽  
Reward And Punishment

Dopamine is thought to regulate learning from appetitive and aversive events. Here we examined how optogenetically-identified dopamine neurons in the lateral ventral tegmental area of mice respond to aversive events in different conditions. In low reward contexts, most dopamine neurons were exclusively inhibited by aversive events, and expectation reduced dopamine neurons’ responses to reward and punishment. When a single odor predicted both reward and punishment, dopamine neurons’ responses to that odor reflected the integrated value of both outcomes. Thus, in low reward contexts, dopamine neurons signal value prediction errors (VPEs) integrating information about both reward and aversion in a common currency. In contrast, in high reward contexts, dopamine neurons acquired a short-latency excitation to aversive events that masked their VPE signaling. Our results demonstrate the importance of considering the contexts to examine the representation in dopamine neurons and uncover different modes of dopamine signaling, each of which may be adaptive for different environments.

Stress and Bipolar Disorder

2020 ◽  
pp. 297-328
Author(s):  
Richard McCarty
Keyword(s):  
Bipolar Disorder ◽  
Animal Models ◽  
Molecular Mechanisms ◽  
Clock Genes ◽  
Mood State ◽  
Mouse Strains ◽  
Transporter Protein ◽  
Circadian Clock Genes ◽  
Dopamine Signaling ◽  
And Behavior

Animal models of bipolar disorder (BD) should capture the switching of mood states from mania to depression and vice versa. Dopamine signaling pathways in brain, including variations in the dopamine transporter protein, have been a focus of many animal models of BD. Another aspect of BD in humans is reflected in circadian and seasonal changes in onset of symptoms. Other animal models of BD include the Myshkin and Madison mouse strains, both of which display mania-like behavior that is reversed by treatment with lithium or valproic acid. Another experimental approach has been to manipulate circadian clock genes and examine effects on dopamine signaling and behavior. Finally, manipulations of risk genes for BD in laboratory mice have advanced our understanding of the molecular mechanisms involved in extreme alterations in mood state.

D2 receptor genotype and striatal dopamine signaling predict motor cortical activity and behavior in humans

NeuroImage ◽  
2011 ◽  
Vol 54 (4) ◽  
pp. 2915-2921 ◽  
Author(s):  
Leonardo Fazio ◽  
Giuseppe Blasi ◽  
Paolo Taurisano ◽  
Apostolos Papazacharias ◽  
Raffaella Romano ◽  
...  
Keyword(s):  
D2 Receptor ◽  
Cortical Activity ◽  
Striatal Dopamine ◽  
Motor Cortical ◽  
Dopamine Signaling ◽  
And Behavior

2A1-B10 A Study on a cricket's neuronal modeling for behavior selection : Consideration to between internal state and behavior selection

2009 ◽  
Vol 2009 (0) ◽  
pp. _2A1-B10_1-_2A1-B10_2
Author(s):  
Takashi FUJII ◽  
Kuniaki KAWABATA ◽  
Hitoshi AONUMA ◽  
Tsuyoshi SUZUKI ◽  
Masatoshi ASHIKAGA ◽  
...  
Keyword(s):  
Internal State ◽  
Neuronal Modeling ◽  
And Behavior ◽  
Behavior Selection

scholarly journals Stimulus-specific neural encoding of a persistent, internal defensive state in the hypothalamus

2019 ◽  
Author(s):  
Ann Kennedy ◽  
Prabhat S. Kunwar ◽  
Lingyun Li ◽  
Daniel Wagenaar ◽  
David J. Anderson
Keyword(s):  
Neural Activity ◽  
Internal State ◽  
Stress Hormones ◽  
Ventromedial Hypothalamus ◽  
Persistent Activity ◽  
Neural Encoding ◽  
Population Activity ◽  
Defensive Responses ◽  
Neuroendocrine Mechanisms ◽  
Threatening Stimuli

SummaryPersistent neural activity has been described in cortical, hippocampal, and motor networks as mediating short-term working memory of transiently encountered stimuli1–4. Internal emotion states such as fear also exhibit persistence following exposure to an inciting stimulus5,6, but such persistence is typically attributed to circulating stress hormones7–9; whether persistent neural activity also plays a role has not been established. SF1+/Nr5a1+ neurons in the dorsomedial and central subdivision of the ventromedial hypothalamus (VMHdm/c) are necessary for innate and learned defensive responses to predators10–13. Optogenetic activation of VMHdmSF1 neurons elicits defensive behaviors that can outlast stimulation11,14, suggesting it induces a persistent internal state of fear or anxiety. Here we show that VMHdmSF1 neurons exhibit persistent activity lasting tens of seconds, in response to naturalistic threatening stimuli. This persistent activity was correlated with, and required for, persistent thigmotaxic (anxiety-like) behavior in an open-field assay. Microendoscopic imaging of VMHdmSF1 neurons revealed that persistence reflects dynamic temporal changes in population activity, rather than simply synchronous, slow decay of simultaneously activated neurons. Unexpectedly, distinct but overlapping VMHdmSF1 subpopulations were persistently activated by different classes of threatening stimuli. Computational modeling suggested that recurrent neural networks (RNNs) incorporating slow excitation and a modest degree of neurochemical or spatial bias can account for persistent activity that maintains stimulus identity, without invoking genetically determined “labeled lines”15. Our results provide causal evidence that persistent neural activity, in addition to well-established neuroendocrine mechanisms, can contribute to the ability of emotion states to outlast their inciting stimuli, and suggest a mechanism that could prevent over-generalization of defensive responses without the need to evolve hardwired circuits specific for each type of threat.

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