Past experience shapes the neural circuits recruited for future learning

Neural circuit research using molecular barcode technology

In neuroscience research, the primary goal is to understand the complex morphological and anatomical structures of the brain and their physiological and behavioral functional relationships or to understand the causality of diseases that manifest as dysfunction of the brain, and various technologies have been developed to achieve this goal. These include imaging techniques such as magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), and positron emission tomography (PET), which noninvasively visualize brain structure and activity; electrophysiological techniques that measure intracellular potentials and currents and analyze cell electrical properties to understand brain activity; techniques to explore how gene expression affects brain function; genetic methods such as gene knockout/knock-in to study how brain cells function; and computational neuroscience methods such as mathematical modeling and simulation to understand the principles of how brain networks operate. Among these, recent advances, particularly the development of 'single-cell omics analysis,' have led to a paradigm shift in neuroscience research. This technique allows the comprehensive study of the unique genetic and molecular characteristics of individual brain cells at the single-cell level. In this paper, I review the application of single-cell omics analysis, which has advanced dramatically in recent years, to various neuroscience problems, mainly how it contributes to the structure and function of neural circuits, a modality unique to the cranial nervous system.

Parallel processing of past and future memories through reactivation and synaptic plasticity mechanisms during sleep

Every day, we experience new episodes and store new memories. Although memories are stored in corresponding engram cells, how different sets of engram cells are selected for current and next episodes, and how they create their memories, remains unclear. Here we show that in male mice, hippocampal CA1 neurons show an organized synchronous activity in prelearning home cage sleep that correlates with the learning ensembles only in engram cells, termed preconfigured ensembles. Moreover, after learning, a subset of nonengram cells develops population activity, which is constructed during postlearning offline periods, and then emerges to represent engram cells for new learning. Our model suggests a potential role of synaptic depression and scaling in the reorganization of the activity of nonengram cells. Together, our findings indicate that during offline periods there are two parallel processes occurring: conserving of past memories through reactivation, and preparation for upcoming ones through offline synaptic plasticity mechanisms.

Partially dissociable roles of the orbitofrontal cortex and dorsal hippocampus in context-dependent hierarchical associations

Reward cues are often ambiguous; what is good in one context is not necessarily good in another. To solve this ambiguity, animals form hierarchical associations in which the context gates the retrieval of appropriate cue-evoked memories. These hierarchical associations regulate cue-elicited behavior and influence subsequent learning, promoting the inference of context-dependency. The orbitofrontal cortex (OFC) and dorsal hippocampus (DH) are both proposed to encode a "cognitive map" encompassing hierarchical, context-dependent associations. However, OFC- and DH-specific contributions to the different functional properties of hierarchical associations remain controversial. Using chemogenetic inactivation in rats, we show that the OFC is essential to both properties of hierarchical associations (performance regulation and learning bias). In contrast, DH's role appears limited to the contextual learning bias conferred by hierarchical associations. This work establishes the OFC as a critical orchestrator of hierarchical associations and provides insights into the extended circuits mediating the functional properties of these associations.

Neural correlates of learning and memory are altered by early-life stress

The ability to learn and remember, which is fundamental for behavioral adaptation, is susceptible to stressful experiences during the early postnatal period, such as abnormal levels of maternal care. The exact mechanisms underlying these effects still remain elusive. This study examined whether early life stress (ELS) alters memory and brain activation patterns in male mice. Therefore, we examined the expression of the immediate early genes (IEGs) c-Fos and Arc in the dentate gyrus (DG) and basolateral amygdala (BLA) after training and memory retrieval in a fear conditioning task. Furthermore, we examined the potential of RU38486 (RU486), a glucocorticoid receptor antagonist, to mitigate ELS-induced memory deficits by blocking stress signalling during adolescence. Arc::dVenus reporter mice, which allow investigating experience-dependent expression of the immediate early gene Arc also at more remote time points, were exposed to ELS by housing dams and offspring with limited bedding and nesting material (LBN) between postnatal days (PND) 2-9 and trained in a fear conditioning task at adult age. We found that ELS reduced both fear acquisition and contextual memory retrieval. RU486 did not prevent these effects. ELS reduced the number of Arc::dVenus+ cells in DG and BLA after training, while the number of c-Fos+ cells were left unaffected. After memory retrieval, ELS decreased c-Fos+ cells in the ventral DG and BLA. ELS also altered the colocalization of c-Fos+ cells with Arc::dVenus+ cells in the ventral DG, possibly indicating impaired engram allocation in the ventral DG after memory retrieval. In conclusion, this study shows that ELS alters neuronal activation patterns after fear acquisition and retrieval, which may provide mechanistic insights into enduring impact of ELS on the processing of fear memories, possibly via changes in cell (co-) activation and engram cell allocation.

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.

A dorsal hippocampus-prodynorphinergic dorsolateral septum-to-lateral hypothalamus circuit mediates contextual gating of feeding

Adaptive regulation of feeding depends on linkage of internal states and food outcomes with contextual cues. Human brain imaging has identified dysregulation of a hippocampal-lateral hypothalamic area (LHA) network in binge eating, but mechanistic instantiation of underlying cell-types and circuitry is lacking. Here, we identify an evolutionary conserved and discrete Prodynorphin (Pdyn)-expressing subpopulation of Somatostatin (Sst)-expressing inhibitory neurons in the dorsolateral septum (DLS) that receives primarily dorsal, but not ventral, hippocampal inputs. DLS(Pdyn) neurons inhibit LHA GABAergic neurons and confer context- and internal state-dependent calibration of feeding. Viral deletion of Pdyn in the DLS mimicked effects seen with optogenetic silencing of DLS Pdyn INs, suggesting a potential role for DYNORPHIN-KAPPA OPIOID RECEPTOR signaling in contextual regulation of food-seeking. Together, our findings illustrate how the dorsal hippocampus has evolved to recruit an ancient LHA feeding circuit module through Pdyn DLS inhibitory neurons to link contextual information with regulation of food consumption.

The cognitive (lateral) hypothalamus

Despite the physiological complexity of the hypothalamus, its role is typically restricted to initiation or cessation of innate behaviors. For example, theories of lateral hypothalamus argue that it is a switch to turn feeding 'on' and 'off' as dictated by higher-order structures that render when feeding is appropriate. However, recent data demonstrate that the lateral hypothalamus is critical for learning about food-related cues. Furthermore, the lateral hypothalamus opposes learning about information that is neutral or distal to food. This reveals the lateral hypothalamus as a unique arbitrator of learning capable of shifting behavior toward or away from important events. This has relevance for disorders characterized by changes in this balance, including addiction and schizophrenia. Generally, this suggests that hypothalamic function is more complex than increasing or decreasing innate behaviors.

Liraglutide restores impaired associative learning in individuals with obesity

Survival under selective pressure is driven by the ability of our brain to use sensory information to our advantage to control physiological needs. To that end, neural circuits receive and integrate external environmental cues and internal metabolic signals to form learned sensory associations, consequently motivating and adapting our behaviour. The dopaminergic midbrain plays a crucial role in learning adaptive behaviour and is particularly sensitive to peripheral metabolic signals, including intestinal peptides, such as glucagon-like peptide 1 (GLP-1). In a single-blinded, randomized, controlled, crossover basic human functional magnetic resonance imaging study relying on a computational model of the adaptive learning process underlying behavioural responses, we show that adaptive learning is reduced when metabolic sensing is impaired in obesity, as indexed by reduced insulin sensitivity (participants: N = 30 with normal insulin sensitivity; N = 24 with impaired insulin sensitivity). Treatment with the GLP-1 receptor agonist liraglutide normalizes impaired learning of sensory associations in men and women with obesity. Collectively, our findings reveal that GLP-1 receptor activation modulates associative learning in people with obesity via its central effects within the mesoaccumbens pathway. These findings provide evidence for how metabolic signals can act as neuromodulators to adapt our behaviour to our body's internal state and how GLP-1 receptor agonists work in clinics.

A Theory of Mental Frameworks

Problem-solving skills are highly valued in modern society and are often touted as core elements of school mission statements, desirable traits for job applicants, and as some of the most complex thinking that the brain is capable of executing. While learning to problem-solve is a goal of education, and many strategies, methodologies, and activities exist to help teachers guide the development of these skills, there are few formal curriculum structures or broader frameworks that guide teachers toward the achievement of this educational objective. Problem-solving skills have been called "higher order cognitive functions" in cognitive neuroscience as they involve multiple complex networks in the brain, rely on constant rehearsal, and often take years to form. Children of all ages employ problem solving, from a newborn seeking out food to children learning in school settings, or adults tackling real-world conflicts. These skills are usually considered the end product of a good education when in fact, in order to be developed they comprise an ongoing process of learning. "Ways of thinking" have been studied by philosophers and neuroscientists alike, to pinpoint cognitive preferences for problem solving approaches that develop from exposure to distinct models, derived from and resulting in certain heuristics used by learners. This new theory paper suggests a novel understanding of the brain's approach to problem solving that structures existing problem-solving frameworks into an organized design. The authors surveyed problem-solving frameworks from business administration, design, engineering, philosophy, psychology, education, neuroscience and other learning sciences to assess their differences and similarities. This review lead to an appreciation that different problem-solving frameworks from different fields respond more or less accurately and efficiently depending on the kinds of problems being tackled, leading to our conclusion that a wider range of frameworks may help individuals approach more varied problems across fields, and that such frameworks can be organized in school curriculum. This paper proposes that explicit instruction of "mental frameworks" may help organize and formalize the instruction of thinking skills that underpin problem-solving-and by extension-that the more such models a person learns, the more tools they will have for future complex problem-solving. To begin, this paper explains the theoretical underpinnings of the mental frameworks concept, then explores some existing mental frameworks which are applicable to all age groups and subject areas. The paper concludes with a list of five limitations to this proposal and pairs them with counter-balancing benefits.

Rewarding-unrewarding prediction signals under a bivalent context in the primate lateral hypothalamus

Animals can expect rewards under equivocal situations. The lateral hypothalamus (LH) is thought to process motivational information by producing valence signals of reward and punishment. Despite rich studies using rodents and non-human primates, these signals have been assessed separately in appetitive and aversive contexts; therefore, it remains unclear what information the LH encodes in equivocal situations. To address this issue, macaque monkeys were conditioned under a bivalent context in which reward and punishment were probabilistically delivered, in addition to appetitive and aversive contexts. The monkeys increased approaching behavior similarly in the bivalent and appetitive contexts as the reward probability increased. They increased avoiding behavior under the bivalent and aversive contexts as the punishment probability increased, but the mean frequency was lower under the bivalent context than under the aversive context. The population activity correlated with these mean behaviors. Moreover, the LH produced fine prediction signals of reward expectation, uncertainty, and predictability consistently in the bivalent and appetitive contexts by recruiting context-independent and context-dependent subpopulations of neurons, while it less produced punishment signals in the aversive and bivalent contexts. Further, neural ensembles encoded context information and "rewarding-unrewarding" and "reward-punishment" valence. These signals may motivate individuals robustly in equivocal environments.

Modulation of aversive value coding in the vertebrate and invertebrate brain

Avoiding potentially dangerous situations is key for the survival of any organism. Throughout life, animals learn to avoid environments, stimuli or actions that can lead to bodily harm. While the neural bases for appetitive learning, evaluation and value-based decision-making have received much attention, recent studies have revealed more complex computations for aversive signals during learning and decision-making than previously thought. Furthermore, previous experience, internal state and systems level appetitive-aversive interactions seem crucial for learning specific aversive value signals and making appropriate choices. The emergence of novel methodologies (computation analysis coupled with large-scale neuronal recordings, neuronal manipulations at unprecedented resolution offered by genetics, viral strategies and connectomics) has helped to provide novel circuit-based models for aversive (and appetitive) valuation. In this review, we focus on recent vertebrate and invertebrate studies yielding strong evidence that aversive value information can be computed by a multitude of interacting brain regions, and that past experience can modulate future aversive learning and therefore influence value-based decisions.

Disruptions in network plasticity precede deficits in memory following inhibition of retinoid signaling

Retinoic acid, the active metabolite of vitamin A, is important for vertebrate cognition and hippocampal plasticity, but few studies have examined its role in invertebrate learning and memory, and its actions in the invertebrate central nervous system are currently unknown. Using the mollusc Lymnaea stagnalis, we examined operant conditioning of the respiratory behavior, controlled by a well-defined central pattern generator (CPG), and used citral to inhibit retinoic acid signaling. Both citral- and vehicle-treated animals showed normal learning, but citral-treated animals failed to exhibit long-term memory at 24 h. Cohorts of citral- or vehicle-treated animals were dissected into semi-intact preparations, either 1 h after training, or after the memory test 24 h later. Simultaneous electrophysiological recordings from the CPG pacemaker cell (right pedal dorsal 1; RPeD1) and an identified motorneuron (VI) were made while monitoring respiratory activity (pneumostome opening). Activity of the CPG pneumostome opener interneuron (input 3 interneuron; IP3) was also monitored indirectly. Vehicle-treated conditioned preparations showed significant changes in network parameters immediately after learning, such as reduced motorneuron bursting activity (from IP3 input), delayed pneumostome opening, and decoupling of coincident IP3 input within the network. However, citral-treated preparations failed to exhibit these network changes and more closely resembled naïve preparations. Importantly, these citral-induced differences were manifested immediately after training and before any overt changes in the behavioral response (memory impairment). These studies shed light on where and when retinoid signaling might affect a central pattern-generating network to promote memory formation during conditioning of a homeostatic behavior.NEW & NOTEWORTHY We provide novel evidence for how conditioning-induced changes in a CPG network are disrupted when retinoid signaling is inhibited. Inhibition of retinoic acid signaling prevents long-term memory formation following operant conditioning, but has no effect on learning. Simultaneous electrophysiological and behavioral analyses indicate network changes immediately following learning, but these changes are prevented with inhibition of retinoid signaling, before any overt changes in behavior. These data suggest sites for retinoid actions during memory formation.

Dopamine signaling in the nucleus accumbens core mediates latent inhibition

Studies investigating the neural mechanisms by which associations between cues and predicted outcomes control behavior often use associative learning frameworks to understand the neural control of behavior. These frameworks do not always account for the full range of effects that novelty can have on behavior and future associative learning. Here, in mice, we show that dopamine in the nucleus accumbens core is evoked by novel, neutral stimuli, and the trajectory of this response over time tracked habituation to these stimuli. Habituation to novel cues before associative learning reduced future associative learning, a phenomenon known as latent inhibition. Crucially, trial-by-trial dopamine response patterns tracked this phenomenon. Optogenetic manipulation of dopamine responses to the cue during the habituation period bidirectionally influenced future associative learning. Thus, dopamine signaling in the nucleus accumbens core has a causal role in novelty-based learning in a way that cannot be predicted based on purely associative factors.

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 work^7-15 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 VTA_DA neurons timed to the transition between the reward and cue reduces both of these components of backward conditioning. These findings suggest VTA_DA 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 VTA_DA 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.

Cognitive experience alters cortical involvement in goal-directed navigation

Neural activity in the mammalian cortex has been studied extensively during decision tasks, and recent work aims to identify under what conditions cortex is actually necessary for these tasks. We discovered that mice with distinct cognitive experiences, beyond sensory and motor learning, use different cortical areas and neural activity patterns to solve the same navigation decision task, revealing past learning as a critical determinant of whether cortex is necessary for goal-directed navigation. We used optogenetics and calcium imaging to study the necessity and neural activity of multiple cortical areas in mice with different training histories. Posterior parietal cortex and retrosplenial cortex were mostly dispensable for accurate performance of a simple navigation task. In contrast, these areas were essential for the same simple task when mice were previously trained on complex tasks with delay periods or association switches. Multiarea calcium imaging showed that, in mice with complex-task experience, single-neuron activity had higher selectivity and neuron–neuron correlations were weaker, leading to codes with higher task information. Therefore, past experience is a key factor in determining whether cortical areas have a causal role in goal-directed navigation.

Advancements in the Quest to Map, Monitor, and Manipulate Neural Circuitry

Neural circuits and the cells that comprise them represent the functional units of the brain. Circuits relay and process sensory information, maintain homeostasis, drive behaviors, and facilitate cognitive functions such as learning and memory. Creating a functionally-precise map of the mammalian brain requires anatomically tracing neural circuits, monitoring their activity patterns, and manipulating their activity to infer function. Advancements in cell-type-specific genetic tools allow interrogation of neural circuits with increased precision. This review provides a broad overview of recombination-based and activity-driven genetic targeting approaches, contemporary viral tracing strategies, electrophysiological recording methods, newly developed calcium, and voltage indicators, and neurotransmitter/neuropeptide biosensors currently being used to investigate circuit architecture and function. Finally, it discusses methods for acute or chronic manipulation of neural activity, including genetically-targeted cellular ablation, optogenetics, chemogenetics, and over-expression of ion channels. With this ever-evolving genetic toolbox, scientists are continuing to probe neural circuits with increasing resolution, elucidating the structure and function of the incredibly complex mammalian brain.

Hypothalamic deep brain stimulation as a strategy to manage anxiety disorders

SignificanceAnxiety disorders are among the most prevalent mental illnesses worldwide. Despite significant advances in their treatment, many patients remain treatment resistant. Thus, new treatment modalities and targets are much needed. Therefore, we developed a deep brain stimulation therapy that targets a recently identified anxiety center in the lateral hypothalamus. We show that this therapy rapidly silences anxiety-implicated neurons and immediately relieves diverse anxiety symptoms in a variety of stressful situations. This therapeutic effect occurs without acute or chronic side effects that are typical of many existing treatments, such as physical sedation or memory deficits. These findings identify a clinically applicable new therapeutic strategy for helping patients to manage treatment-resistant anxiety.

The prediction-error hypothesis of schizophrenia: new data point to circuit-specific changes in dopamine activity

Schizophrenia is a severe psychiatric disorder affecting 21 million people worldwide. People with schizophrenia suffer from symptoms including psychosis and delusions, apathy, anhedonia, and cognitive deficits. Strikingly, schizophrenia is characterised by a learning paradox involving difficulties learning from rewarding events, whilst simultaneously 'overlearning' about irrelevant or neutral information. While dysfunction in dopaminergic signalling has long been linked to the pathophysiology of schizophrenia, a cohesive framework that accounts for this learning paradox remains elusive. Recently, there has been an explosion of new research investigating how dopamine contributes to reinforcement learning, which illustrates that midbrain dopamine contributes in complex ways to reinforcement learning, not previously envisioned. This new data brings new possibilities for how dopamine signalling contributes to the symptomatology of schizophrenia. Building on recent work, we present a new neural framework for how we might envision specific dopamine circuits contributing to this learning paradox in schizophrenia in the context of models of reinforcement learning. Further, we discuss avenues of preclinical research with the use of cutting-edge neuroscience techniques where aspects of this model may be tested. Ultimately, it is hoped that this review will spur to action more research utilising specific reinforcement learning paradigms in preclinical models of schizophrenia, to reconcile seemingly disparate symptomatology and develop more efficient therapeutics.

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.

Higher-Order Conditioning and Dopamine: Charting a Path Forward

Higher-order conditioning involves learning causal links between multiple events, which then allows one to make novel inferences. For example, observing a correlation between two events (e.g., a neighbor wearing a particular sports jersey), later helps one make new predictions based on this knowledge (e.g., the neighbor's wife's favorite sports team). This type of learning is important because it allows one to benefit maximally from previous experiences and perform adaptively in complex environments where many things are ambiguous or uncertain. Two procedures in the lab are often used to probe this kind of learning, second-order conditioning (SOC) and sensory preconditioning (SPC). In second-order conditioning (SOC), we first teach subjects that there is a relationship between a stimulus and an outcome (e.g., a tone that predicts food). Then, an additional stimulus is taught to precede the predictive stimulus (e.g., a light leads to the food-predictive tone). In sensory preconditioning (SPC), this order of training is reversed. Specifically, the two neutral stimuli (i.e., light and tone) are first paired together and then the tone is paired separately with food. Interestingly, in both SPC and SOC, humans, rodents, and even insects, and other invertebrates will later predict that both the light and tone are likely to lead to food, even though they only experienced the tone directly paired with food. While these processes are procedurally similar, a wealth of research suggests they are associatively and neurobiologically distinct. However, midbrain dopamine, a neurotransmitter long thought to facilitate basic Pavlovian conditioning in a relatively simplistic manner, appears critical for both SOC and SPC. These findings suggest dopamine may contribute to learning in ways that transcend differences in associative and neurological structure. We discuss how research demonstrating that dopamine is critical to both SOC and SPC places it at the center of more complex forms of cognition (e.g., spatial navigation and causal reasoning). Further, we suggest that these more sophisticated learning procedures, coupled with recent advances in recording and manipulating dopamine neurons, represent a new path forward in understanding dopamine's contribution to learning and cognition.