Dopamine Release in the Nucleus Accumbens Core Encodes the General Excitatory Components of Learning.

Dopamine release in the nucleus accumbens core (NAcC) is generally considered to be a proxy for phasic firing of the ventral tegmental area dopamine (VTADA) neurons. Thus, dopamine release in NAcC is hypothesized to reflect a unitary role in reward prediction error signaling. However, recent studies reveal more diverse roles of dopamine neurons, which support an emerging idea that dopamine regulates learning differently in distinct circuits. To understand whether the NAcC might regulate a unique component of learning, we recorded dopamine release in NAcC while male rats performed a backward conditioning task where a reward is followed by a neutral cue. We used this task because we can delineate different components of learning, which include sensory-specific inhibitory and general excitatory components. Furthermore, we have shown that VTADA neurons are necessary for both the specific and general components of backward associations. Here, we found that dopamine release in NAcC increased to the reward across learning while reducing to the cue that followed as it became more expected. This mirrors the dopamine prediction error signal seen during forward conditioning and cannot be accounted for temporal-difference reinforcement learning. Subsequent tests allowed us to dissociate these learning components and revealed that dopamine release in NAcC reflects the general excitatory component of backward associations, but not their sensory-specific component. These results emphasize the importance of examining distinct functions of different dopamine projections in reinforcement learning.

The effect of stress and reward on encoding future fear memories.

Prior experience changes the way we learn about our environment. Stress predisposes individuals to developing psychological disorders, just as positive experiences protect from this eventuality (Kirkpatrick & Heller, 2014; Koenigs & Grafman, 2009; Pechtel & Pizzagalli, 2011). Yet current models of how the brain processes information often do not consider a role for prior experience. The considerable literature that examines how stress impacts the brain is an exception to this. This research demonstrates that stress can bias the interpretation of ambiguous events towards being aversive in nature, owed to changes in amygdala physiology (Holmes et al., 2013; Perusini et al., 2016; Rau et al., 2005; Shors et al., 1992). This is thought to be an important model for how people develop anxiety disorders, like post-traumatic stress disorder (PTSD; Rau et al., 2005). However, more recent evidence suggests that experience with reward learning can also change the neural circuits that are involved in learning about fear (Sharpe et al., 2021). Specifically, the lateral hypothalamus, a region typically restricted to modulating feeding and reward behavior, can be recruited to encode fear memories after experience with reward learning. This review discusses the literature on how stress and reward change the way we acquire and encode memories for aversive events, offering a testable model of how these regions may interact to promote either adaptive or maladaptive fear memories.

Dopamine errors drive excitatory and inhibitory components of backward conditioning in an outcome-specific manner.

For over two decades, phasic activity in midbrain dopamine neurons was considered synonymous with the prediction error in temporal-difference reinforcement learning.1-4 Central to this proposal is the notion that reward-predictive stimuli become endowed with the scalar value of predicted rewards. When these cues are subsequently encountered, their predictive value is compared to the value of the actual reward received, allowing for the calculation of prediction errors.5,6 Phasic firing of dopamine neurons was proposed to reflect this computation,1,2 facilitating the backpropagation of value from the predicted reward to the reward-predictive stimulus, thus reducing future prediction errors. There are two critical assumptions of this proposal: (1) that dopamine errors can only facilitate learning about scalar value and not more complex features of predicted rewards, and (2) that the dopamine signal can only be involved in anticipatory cue-reward learning in which cues or actions precede rewards. Recent work7-15 has challenged the first assumption, demonstrating that phasic dopamine signals across species are involved in learning about more complex features of the predicted outcomes, in a manner that transcends this value computation. Here, we tested the validity of the second assumption. Specifically, we examined whether phasic midbrain dopamine activity would be necessary for backward conditioning-when a neutral cue reliably follows a rewarding outcome.16-20 Using a specific Pavlovian-to-instrumental transfer (PIT) procedure,21-23 we show rats learn both excitatory and inhibitory components of a backward association, and that this association entails knowledge of the specific identity of the reward and cue. We demonstrate that brief optogenetic inhibition of VTADA neurons timed to the transition between the reward and cue reduces both of these components of backward conditioning. These findings suggest VTADA neurons are capable of facilitating associations between contiguously occurring events, regardless of the content of those events. We conclude that these data may be in line with suggestions that the VTADA error acts as a universal teaching signal. This may provide insight into why dopamine function has been implicated in myriad psychological disorders that are characterized by very distinct reinforcement-learning deficits.

BehaviorDEPOT is a simple, flexible tool for automated behavioral detection based on markerless pose tracking.

Quantitative descriptions of animal behavior are essential to study the neural substrates of cognitive and emotional processes. Analyses of naturalistic behaviors are often performed by hand or with expensive, inflexible commercial software. Recently, machine learning methods for markerless pose estimation enabled automated tracking of freely moving animals, including in labs with limited coding expertise. However, classifying specific behaviors based on pose data requires additional computational analyses and remains a significant challenge for many groups. We developed BehaviorDEPOT (DEcoding behavior based on POsitional Tracking), a simple, flexible software program that can detect behavior from video timeseries and can analyze the results of experimental assays. BehaviorDEPOT calculates kinematic and postural statistics from keypoint tracking data and creates heuristics that reliably detect behaviors. It requires no programming experience and is applicable to a wide range of behaviors and experimental designs. We provide several hard-coded heuristics. Our freezing detection heuristic achieves above 90% accuracy in videos of mice and rats, including those wearing tethered head-mounts. BehaviorDEPOT also helps researchers develop their own heuristics and incorporate them into the software's graphical interface. Behavioral data is stored framewise for easy alignment with neural data. We demonstrate the immediate utility and flexibility of BehaviorDEPOT using popular assays including fear conditioning, decision-making in a T-maze, open field, elevated plus maze, and novel object exploration.

Optogenetic stimulation of the basolateral amygdala accelerates acquisition of object-context associations.

The basolateral complex of the amygdala (BLA) is capable of modulating memory and is thought to do so via projections to regions such as the hippocampus. The present study used optogenetic stimulation of glutamatergic projection neurons in the BLA as rats learned object-context associations during a well-studied hippocampus-dependent memory task. Relative to a control condition, optogenetic BLA stimulation resulted in the accelerated acquisition of when stimulation was delivered following correct choices but not when it was delivered during the intertrial interval. These results extend prior examples of amygdala-mediated memory enhancement to a canonical example of hippocampus-dependent memory and provide an opportunity for future dissection of amygdalar modulation of object-context associative memory. (PsycInfo Database Record (c) 2021 APA, all rights reserved).