Striatal dopamine explains novelty-induced behavioral dynamics and individual variability in threat prediction

Harlequin mice exhibit cognitive impairment, severe loss of Purkinje cells and a compromised bioenergetic status due to the absence of Apoptosis Inducing Factor

The functional integrity of the central nervous system relies on complex mechanisms in which the mitochondria are crucial actors because of their involvement in a multitude of bioenergetics and biosynthetic pathways. Mitochondrial diseases are among the most prevalent groups of inherited neurological disorders, affecting up to 1 in 5000 adults and despite considerable efforts around the world there is still limited curative treatments. Harlequin mice correspond to a relevant model of recessive X-linked mitochondrial disease due to a proviral insertion in the first intron of the Apoptosis-inducing factor gene, resulting in an almost complete depletion of the corresponding protein. These mice exhibit progressive degeneration of the retina, optic nerve, cerebellum, and cortical regions leading to irremediable blindness and ataxia, reminiscent of what is observed in patients suffering from mitochondrial diseases. We evaluated the progression of cerebellar degeneration in Harlequin mice, especially for Purkinje cells and its relationship with bioenergetics failure and behavioral damage. For the first time to our knowledge, we demonstrated that Harlequin mice display cognitive and emotional impairments at early stage of the disease with further deteriorations as ataxia aggravates. These functions, corresponding to higher-order cognitive processing, have been assigned to a complex network of reciprocal connections between the cerebellum and many cortical areas which could be dysfunctional in these mice. Consequently, Harlequin mice become a suitable experimental model to test innovative therapeutics, via the targeting of mitochondria which can become available to a large spectrum of neurological diseases.

Frontal Norepinephrine Represents a Threat Prediction Error Under Uncertainty

BACKGROUND

To adapt to threats in the environment, animals must predict them and engage in defensive behavior. While the representation of a prediction error signal for reward has been linked to dopamine, a neuromodulatory prediction error for aversive learning has not been identified.

METHODS

We measured and manipulated norepinephrine release during threat learning using optogenetics and a novel fluorescent norepinephrine sensor.

RESULTS

We found that norepinephrine response to conditioned stimuli reflects aversive memory strength. When delays between auditory stimuli and footshock are introduced, norepinephrine acts as a prediction error signal. However, temporal difference prediction errors do not fully explain norepinephrine dynamics. To explain noradrenergic signaling, we used an updated reinforcement learning model with uncertainty about time and found that it explained norepinephrine dynamics across learning and variations in temporal and auditory task structure.

CONCLUSIONS

Norepinephrine thus combines cognitive and affective information into a predictive signal and links time with the anticipation of danger.

A qualitative systematic review of adolescent's perceptions of sleep: Awareness of, barriers to and strategies for promoting healthy sleep patterns

AIMS

To consolidate adolescents' perspectives regarding various aspects of sleep and offer insights to promote healthier sleep habits during their critical developmental years.

METHODS/DATA SOURCES

Six electronic databases (PubMed, CINAHL, Embase, Scopus, PsycINFO and Web of Science) were searched from their inception dates to June 2023. Data were extracted and meta-summarised using Sandelowski and Barroso's approach and synthesised using Thomas and Harden's thematic analysis framework.

RESULTS

Meta-synthesis from 11 peer-reviewed published studies identified four main themes: (1) Awareness and understanding of sleep's significance, (2) The shadows and radiance of slumber, (3) Traversing the sleepscape: trouble bubbles and (4) Illuminating the path: Guiding lights to enhanced sleep.

CONCLUSION/IMPLICATIONS

Our review findings suggest a lack of awareness and guidance regarding the significance of sleep and the cultivation of good sleep habits among adolescents. Identified barriers to adequate sleep encompass various factors, including overthinking, poor habits, family/environmental influences, extensive technology use, peer pressure, the fear of missing out, academic demands and involvement in extracurricular activities. Strategies to improve adolescents' sleep health involve multiple sleep strategies, including sleep education, workshops/seminars, parental involvement, incorporating digital well-being practices, the promotion of relaxation techniques and the provision of essential resources. Prioritising sleep health and implementing targeted interventions are key steps to empower adolescents, create supportive environments and shape a healthier future generation. Future research endeavours should focus on evaluating the effectiveness of interventions and exploring the influence of cultural factors.

IMPACT

There exists a notable lack of awareness and guidance regarding the significance of sleep and the cultivation of good sleep habits among adolescents. Barriers to achieving adequate sleep among adolescents include overthinking, poor habits, family/environmental influences, extensive technology use, peer pressure, the fear of missing out, academic demands and involvement in extracurricular activities. The collaboration between healthcare institutions, professionals and educational institutions is crucial to facilitate (1) the implementation of sleep education workshops/seminars targeting adolescents, (2) increased parental involvement and role-modelling to instil good sleep practices among adolescents and (3) enhanced integration of digital well-being practices, the promotion of relaxation techniques and accessibility to essential sleep hygiene resources.

REPORTING METHOD

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.

PATIENT OR PUBLIC CONTRIBUTION

No patient or public contribution.

TRIAL AND PROTOCOL REGISTRATION

This review was registered on the Prospective Register of Systematic Reviews (CRD42023403775).

A feature-specific prediction error model explains dopaminergic heterogeneity

The hypothesis that midbrain dopamine (DA) neurons broadcast a reward prediction error (RPE) is among the great successes of computational neuroscience. However, recent results contradict a core aspect of this theory: specifically that the neurons convey a scalar, homogeneous signal. While the predominant family of extensions to the RPE model replicates the classic model in multiple parallel circuits, we argue that these models are ill suited to explain reports of heterogeneity in task variable encoding across DA neurons. Instead, we introduce a complementary 'feature-specific RPE' model, positing that individual ventral tegmental area DA neurons report RPEs for different aspects of an animal's moment-to-moment situation. Further, we show how our framework can be extended to explain patterns of heterogeneity in action responses reported among substantia nigra pars compacta DA neurons. This theory reconciles new observations of DA heterogeneity with classic ideas about RPE coding while also providing a new perspective of how the brain performs reinforcement learning in high-dimensional environments.

Explaining dopamine through prediction errors and beyond

The most influential account of phasic dopamine holds that it reports reward prediction errors (RPEs). The RPE-based interpretation of dopamine signaling is, in its original form, probably too simple and fails to explain all the properties of phasic dopamine observed in behaving animals. This Perspective helps to resolve some of the conflicting interpretations of dopamine that currently exist in the literature. We focus on the following three empirical challenges to the RPE theory of dopamine: why does dopamine (1) ramp up as animals approach rewards, (2) respond to sensory and motor features and (3) influence action selection? We argue that the prediction error concept, once it has been suitably modified and generalized based on an analysis of each computational problem, answers each challenge. Nonetheless, there are a number of additional empirical findings that appear to demand fundamentally different theoretical explanations beyond encoding RPE. Therefore, looking forward, we discuss the prospects for a unifying theory that respects the diversity of dopamine signaling and function as well as the complex circuitry that both underlies and responds to dopaminergic transmission.

Rethinking dopamine-guided action sequence learning

As opposed to those requiring a single action for reward acquisition, tasks necessitating action sequences demand that animals learn action elements and their sequential order and sustain the behaviour until the sequence is completed. With repeated learning, animals not only exhibit precise execution of these sequences but also demonstrate enhanced smoothness and efficiency. Previous research has demonstrated that midbrain dopamine and its major projection target, the striatum, play crucial roles in these processes. Recent studies have shown that dopamine from the substantia nigra pars compacta (SNc) and the ventral tegmental area (VTA) serve distinct functions in action sequence learning. The distinct contributions of dopamine also depend on the striatal subregions, namely the ventral, dorsomedial and dorsolateral striatum. Here, we have reviewed recent findings on the role of striatal dopamine in action sequence learning, with a focus on recent rodent studies.

Toward a neuroscience of natural behavior

One of the most exciting new developments in systems neuroscience is the progress being made toward neurophysiological experiments that move beyond simplified laboratory settings and address the richness of natural behavior. This is enabled by technological advances such as wireless recording in freely moving animals, automated quantification of behavior, and new methods for analyzing large data sets. Beyond new empirical methods and data, however, there is also a need for new theories and concepts to interpret that data. Such theories need to address the particular challenges of natural behavior, which often differ significantly from the scenarios studied in traditional laboratory settings. Here, we discuss some strategies for developing such novel theories and concepts and some example hypotheses being proposed.

Computational models of intrinsic motivation for curiosity and creativity

We link Ivancovsky et al.'s novelty-seeking model (NSM) to computational models of intrinsically motivated behavior and learning. We argue that dissociating different forms of curiosity, creativity, and memory based on the involvement of distinct intrinsic motivations (e.g., surprise and novelty) is essential to empirically test the conceptual claims of the NSM.

Mesolimbic Neural Response Dynamics Predict Future Individual Alcohol Drinking in Mice

BACKGROUND

Individual variability in response to rewarding stimuli is a striking but understudied phenomenon. The mesolimbic dopamine system is critical in encoding the reinforcing properties of both natural reward and alcohol; however, how innate or baseline differences in the response dynamics of this circuit define individual behavior and shape future vulnerability to alcohol remain unknown.

METHODS

Using naturalistic behavioral assays, a voluntary alcohol drinking paradigm, in vivo fiber photometry, in vivo electrophysiology, and chemogenetics, we investigated how differences in mesolimbic neural circuit activity contribute to the individual variability seen in reward processing and, by proxy, alcohol drinking.

RESULTS

We first characterized heterogeneous behavioral and neural responses to natural reward and defined how these baseline responses predicted future individual alcohol-drinking phenotypes in male mice. We then determined spontaneous ventral tegmental area dopamine neuron firing profiles associated with responses to natural reward that predicted alcohol drinking. Using a dual chemogenetic approach, we mimicked specific mesolimbic dopamine neuron firing activity before or during voluntary alcohol drinking to link unique neurophysiological profiles to individual phenotype. We show that hyperdopaminergic individuals exhibit a lower neuronal response to both natural reward and alcohol that predicts lower levels of alcohol consumption in the future.

CONCLUSIONS

These findings reveal unique, circuit-specific neural signatures that predict future individual vulnerability or resistance to alcohol and expand the current knowledge base on how some individuals are able to titrate their alcohol consumption whereas others go on to engage in unhealthy alcohol-drinking behaviors.

Multimodal sensory control of motor performance by glycinergic interneurons of the mouse spinal cord deep dorsal horn

Sensory feedback is integral for contextually appropriate motor output, yet the neural circuits responsible remain elusive. Here, we pinpoint the medial deep dorsal horn of the mouse spinal cord as a convergence point for proprioceptive and cutaneous input. Within this region, we identify a population of tonically active glycinergic inhibitory neurons expressing parvalbumin. Using anatomy and electrophysiology, we demonstrate that deep dorsal horn parvalbumin-expressing interneuron (dPV) activity is shaped by convergent proprioceptive, cutaneous, and descending input. Selectively targeting spinal dPVs, we reveal their widespread ipsilateral inhibition onto pre-motor and motor networks and demonstrate their role in gating sensory-evoked muscle activity using electromyography (EMG) recordings. dPV ablation altered limb kinematics and step-cycle timing during treadmill locomotion and reduced the transitions between sub-movements during spontaneous behavior. These findings reveal a circuit basis by which sensory convergence onto dorsal horn inhibitory neurons modulates motor output to facilitate smooth movement and context-appropriate transitions.

Lightning Pose: improved animal pose estimation via semi-supervised learning, Bayesian ensembling, and cloud-native open-source tools

Contemporary pose estimation methods enable precise measurements of behavior via supervised deep learning with hand-labeled video frames. Although effective in many cases, the supervised approach requires extensive labeling and often produces outputs that are unreliable for downstream analyses. Here, we introduce "Lightning Pose," an efficient pose estimation package with three algorithmic contributions. First, in addition to training on a few labeled video frames, we use many unlabeled videos and penalize the network whenever its predictions violate motion continuity, multiple-view geometry, and posture plausibility (semi-supervised learning). Second, we introduce a network architecture that resolves occlusions by predicting pose on any given frame using surrounding unlabeled frames. Third, we refine the pose predictions post-hoc by combining ensembling and Kalman smoothing. Together, these components render pose trajectories more accurate and scientifically usable. We release a cloud application that allows users to label data, train networks, and predict new videos directly from the browser.

Lateral entorhinal cortex subpopulations represent experiential epochs surrounding reward

During goal-directed navigation, 'what' information, describing the experiences occurring in periods surrounding a reward, can be combined with spatial 'where' information to guide behavior and form episodic memories. This integrative process likely occurs in the hippocampus, which receives spatial information from the medial entorhinal cortex; however, the source of the 'what' information is largely unknown. Here, we show that mouse lateral entorhinal cortex (LEC) represents key experiential epochs during reward-based navigation tasks. We discover separate populations of neurons that signal goal approach and goal departure and a third population signaling reward consumption. When reward location is moved, these populations immediately shift their respective representations of each experiential epoch relative to reward, while optogenetic inhibition of LEC disrupts learning the new reward location. Therefore, the LEC contains a stable code of experiential epochs surrounding and including reward consumption, providing reward-centric information to contextualize the spatial information carried by the medial entorhinal cortex.

Curiosity: primate neural circuits for novelty and information seeking

For many years, neuroscientists have investigated the behavioural, computational and neurobiological mechanisms that support value-based decisions, revealing how humans and animals make choices to obtain rewards. However, many decisions are influenced by factors other than the value of physical rewards or second-order reinforcers (such as money). For instance, animals (including humans) frequently explore novel objects that have no intrinsic value solely because they are novel and they exhibit the desire to gain information to reduce their uncertainties about the future, even if this information cannot lead to reward or assist them in accomplishing upcoming tasks. In this Review, I discuss how circuits in the primate brain responsible for detecting, predicting and assessing novelty and uncertainty regulate behaviour and give rise to these behavioural components of curiosity. I also briefly discuss how curiosity-related behaviours arise during postnatal development and point out some important reasons for the persistence of curiosity across generations.

An opponent striatal circuit for distributional reinforcement learning

Machine learning research has achieved large performance gains on a wide range of tasks by expanding the learning target from mean rewards to entire probability distributions of rewards - an approach known as distributional reinforcement learning (RL)1. The mesolimbic dopamine system is thought to underlie RL in the mammalian brain by updating a representation of mean value in the striatum2,3, but little is known about whether, where, and how neurons in this circuit encode information about higher-order moments of reward distributions4. To fill this gap, we used high-density probes (Neuropixels) to acutely record striatal activity from well-trained, water-restricted mice performing a classical conditioning task in which reward mean, reward variance, and stimulus identity were independently manipulated. In contrast to traditional RL accounts, we found robust evidence for abstract encoding of variance in the striatum. Remarkably, chronic ablation of dopamine inputs disorganized these distributional representations in the striatum without interfering with mean value coding. Two-photon calcium imaging and optogenetics revealed that the two major classes of striatal medium spiny neurons - D1 and D2 MSNs - contributed to this code by preferentially encoding the right and left tails of the reward distribution, respectively. We synthesize these findings into a new model of the striatum and mesolimbic dopamine that harnesses the opponency between D1 and D2 MSNs5-15 to reap the computational benefits of distributional RL.

Curiosity-driven exploration: foundations in neuroscience and computational modeling

Curiosity refers to the intrinsic desire of humans and animals to explore the unknown, even when there is no apparent reason to do so. Thus far, no single, widely accepted definition or framework for curiosity has emerged, but there is growing consensus that curious behavior is not goal-directed but related to seeking or reacting to information. In this review, we take a phenomenological approach and group behavioral and neurophysiological studies which meet these criteria into three categories according to the type of information seeking observed. We then review recent computational models of curiosity from the field of machine learning and discuss how they enable integrating different types of information seeking into one theoretical framework. Combinations of behavioral and neurophysiological studies along with computational modeling will be instrumental in demystifying the notion of curiosity.

Cell type specificity for circuit output in the midbrain dopaminergic system

Midbrain dopaminergic neurons are a relatively small group of neurons in the mammalian brain controlling a wide range of behaviors. In recent years, increasingly sophisticated tracing, imaging, transcriptomic, and machine learning approaches have provided substantial insights into the anatomical, molecular, and functional heterogeneity of dopaminergic neurons. Despite this wealth of new knowledge, it remains unclear whether and how the diverse features defining dopaminergic subclasses converge to delineate functional ensembles within the dopaminergic system. Here, we review recent studies investigating various aspects of dopaminergic heterogeneity and discuss how development, behavior, and disease influence subtype characteristics. We then outline what further approaches could be pursued to gain a more inclusive picture of dopaminergic diversity, which could be crucial to understanding the functional architecture of this system.

CHL1 depletion affects dopamine receptor D2-dependent modulation of mouse behavior

Introduction

The dopaminergic system plays a key role in the appropriate functioning of the central nervous system, where it is essential for emotional balance, arousal, reward, and motor control. The cell adhesion molecule close homolog of L1 (CHL1) contributes to dopaminergic system development, and CHL1 and the dopamine receptor D2 (D2R) are associated with mental disorders like schizophrenia, addiction, autism spectrum disorder and depression.

Methods

Here, we investigated how the interplay between CHL1 and D2R affects the behavior of young adult male and female wild-type (CHL+/+) and CHL1-deficient (CHL1-/-) mice, when D2R agonist quinpirole and antagonist sulpiride are applied.

Results

Low doses of quinpirole (0.02 mg/kg body weight) induced hypolocomotion of CHL1+/+ and CHL1-/- males and females, but led to a delayed response in CHL1-/- mice. Sulpiride (1 mg/kg body weight) affected locomotion of CHL1-/- females and social interaction of CHL1+/+ females as well as social interactions of CHL1-/- and CHL1+/+ males. Quinpirole increased novelty-seeking behavior of CHL1-/- males compared to CHL1+/+ males. Vehicle-treated CHL1-/- males and females showed enhanced working memory and reduced stress-related behavior.

Discussion

We propose that CHL1 regulates D2R-dependent functions in vivo. Deficiency of CHL1 leads to abnormal locomotor activity and emotionality, and to sex-dependent behavioral differences.

Striatum supports fast learning but not memory recall

Animals learn to carry out motor actions in specific sensory contexts to achieve goals. The striatum has been implicated in producing sensory-motor associations, yet its contribution to memory formation or recall is not clear. To investigate the contribution of striatum to these processes, mice were taught to associate a cue, consisting of optogenetic activation of striatum-projecting neurons in visual cortex, with forelimb reaches to access food pellets. As necessary to direct learning, striatal neural activity encoded both the sensory context and outcome of reaching. With training, the rate of cued reaching increased, but brief optogenetic inhibition of striatal activity arrested learning and prevented trial-to-trial improvements in performance. However, the same manipulation did not affect performance improvements already consolidated into short- (within an hour) or long-term (across days) memories. Hence, striatal activity is necessary for trial-to-trial improvements in task performance, leading to plasticity in other brain areas that mediate memory recall.

Striatal Dopamine Signals and Reward Learning

We are constantly bombarded by sensory information and constantly making decisions on how to act. In order to optimally adapt behavior, we must judge which sequences of sensory inputs and actions lead to successful outcomes in specific circumstances. Neuronal circuits of the basal ganglia have been strongly implicated in action selection, as well as the learning and execution of goal-directed behaviors, with accumulating evidence supporting the hypothesis that midbrain dopamine neurons might encode a reward signal useful for learning. Here, we review evidence suggesting that midbrain dopaminergic neurons signal reward prediction error, driving synaptic plasticity in the striatum underlying learning. We focus on phasic increases in action potential firing of midbrain dopamine neurons in response to unexpected rewards. These dopamine neurons prominently innervate the dorsal and ventral striatum. In the striatum, the released dopamine binds to dopamine receptors, where it regulates the plasticity of glutamatergic synapses. The increase of striatal dopamine accompanying an unexpected reward activates dopamine type 1 receptors (D1Rs) initiating a signaling cascade that promotes long-term potentiation of recently active glutamatergic input onto striatonigral neurons. Sensorimotor-evoked glutamatergic input, which is active immediately before reward delivery will thus be strengthened onto neurons in the striatum expressing D1Rs. In turn, these neurons cause disinhibition of brainstem motor centers and disinhibition of the motor thalamus, thus promoting motor output to reinforce rewarded stimulus-action outcomes. Although many details of the hypothesis need further investigation, altogether, it seems likely that dopamine signals in the striatum might underlie important aspects of goal-directed reward-based learning.

Surprise and novelty in the brain

Notions of surprise and novelty have been used in various experimental and theoretical studies across multiple brain areas and species. However, 'surprise' and 'novelty' refer to different quantities in different studies, which raises concerns about whether these studies indeed relate to the same functionalities and mechanisms in the brain. Here, we address these concerns through a systematic investigation of how different aspects of surprise and novelty relate to different brain functions and physiological signals. We review recent classifications of definitions proposed for surprise and novelty along with links to experimental observations. We show that computational modeling and quantifiable definitions enable novel interpretations of previous findings and form a foundation for future theoretical and experimental studies.

Inhibitory Pedunculopontine Neurons Gate Dopamine-Mediated Motor Actions of Unsigned Valence

BACKGROUND

The pedunculopontine nucleus (PPN) maintains a bidirectional connectivity with the basal ganglia that supports their shared roles in the selection and execution of motor actions. Previous studies identified a role for PPN neurons in goal-directed behavior, but the cellular substrates underlying this function have not been elucidated. We recently revealed the existence of a monosynaptic GABAergic input from the PPN that inhibits dopamine neurons of the substantia nigra. Activation of this pathway interferes with the execution of learned motor sequences when the actions are rewarded, even though the inhibition of dopamine neurons did not shift the value of the action, hence suggesting executive control over the gating of behavior.

OBJECTIVE

To test the attributes of the inhibition of dopamine neurons by the PPN in the context of goal-directed behavior regardless of whether the outcome is positive or negative.

METHODS

We delivered optogenetic stimulation to PPN GABAergic axon terminals in the substantia nigra during a battery of behavioral tasks with positive and negative valence.

RESULTS

Inhibition of dopamine neurons by PPN optogenetic activation during an appetitive task impaired the initiation and overall execution of the behavioral sequence without affecting the consumption of reward. During an active avoidance task, the same activation impaired the ability of mice to avoid a foot shock, but their escape response was unaffected. In addition, responses to potential threats were significantly attenuated.

CONCLUSION

Our results show that PPN GABAergic neurons modulate learned, goal-directed behavior of unsigned valence without affecting overall motor behavior.

Anatomical and Functional Comparison of the Caudate Tail in Primates and the Tail of the Striatum in Rodents: Implications for Sensory Information Processing and Habitual Behavior

The tail of the striatum (TS) is located at the caudal end in the striatum. Recent studies have advanced our knowledge of the anatomy and function of the TS but also raised questions about the differences between rodent and primate TS. In this review, we compare the anatomy and function of the TS in rodent and primate brains. The primate TS is expanded more caudally during brain development in comparison with the rodent TS. Additionally, five sensory inputs from the cortex and thalamus converge in the rodent TS, but this convergence is not observed in the primate TS. The primate TS, including the caudate tail and putamen tail, primarily receives inputs from the visual areas, implying a specialized function in processing visual inputs for action generation. This anatomical difference leads to further discussion of cellular circuit models to comprehend how the primate brain processes a wider range of complex visual stimuli to produce habitual behavior as compared with the rodent brain. Examining these differences and considering possible neural models may provide better understanding of the anatomy and function of the primate TS.

Dopamine Release Plateau and Outcome Signals in Dorsal Striatum Contrast with Classic Reinforcement Learning Formulations

We recorded dopamine release signals in medial and lateral sectors of the striatum as mice learned consecutive visual cue-outcome conditioning tasks including cue association, cue discrimination, reversal, and probabilistic discrimination task versions. Dopamine release responses in medial and lateral sites exhibited learning-related changes within and across phases of acquisition. These were different for the medial and lateral sites. In neither sector could these be accounted for by classic reinforcement learning as applied to dopamine-containing neuron activity. Cue responses ranged from initial sharp peaks to modulated plateau responses. In the medial sector, outcome (reward) responses during cue conditioning were minimal or, initially, negative. By contrast, in lateral sites, strong, transient dopamine release responses occurred at both cue and outcome. Prolonged, plateau release responses to cues emerged in both regions when discriminative behavioral responses became required. In most sites, we found no evidence for a transition from outcome to cue signaling, a hallmark of temporal difference reinforcement learning as applied to midbrain dopamine activity. These findings delineate reshaping of dopamine release activity during learning and suggest that current views of reward prediction error encoding need review to accommodate distinct learning-related spatial and temporal patterns of striatal dopamine release in the dorsal striatum.

Opponent learning with different representations in the cortico-basal ganglia pathways can develop obsession-compulsion cycle

Obsessive-compulsive disorder (OCD) has been suggested to be associated with impairment of model-based behavioral control. Meanwhile, recent work suggested shorter memory trace for negative than positive prediction errors (PEs) in OCD. We explored relations between these two suggestions through computational modeling. Based on the properties of cortico-basal ganglia pathways, we modeled human as an agent having a combination of successor representation (SR)-based system that enables model-based-like control and individual representation (IR)-based system that only hosts model-free control, with the two systems potentially learning from positive and negative PEs in different rates. We simulated the agent's behavior in the environmental model used in the recent work that describes potential development of obsession-compulsion cycle. We found that the dual-system agent could develop enhanced obsession-compulsion cycle, similarly to the agent having memory trace imbalance in the recent work, if the SR- and IR-based systems learned mainly from positive and negative PEs, respectively. We then simulated the behavior of such an opponent SR+IR agent in the two-stage decision task, in comparison with the agent having only SR-based control. Fitting of the agents' behavior by the model weighing model-based and model-free control developed in the original two-stage task study resulted in smaller weights of model-based control for the opponent SR+IR agent than for the SR-only agent. These results reconcile the previous suggestions about OCD, i.e., impaired model-based control and memory trace imbalance, raising a novel possibility that opponent learning in model(SR)-based and model-free controllers underlies obsession-compulsion. Our model cannot explain the behavior of OCD patients in punishment, rather than reward, contexts, but it could be resolved if opponent SR+IR learning operates also in the recently revealed non-canonical cortico-basal ganglia-dopamine circuit for threat/aversiveness, rather than reward, reinforcement learning, and the aversive SR + appetitive IR agent could actually develop obsession-compulsion if the environment is modeled differently.

Semaglutide reduces alcohol intake and relapse-like drinking in male and female rats

BACKGROUND

Glucagon-like peptide1 receptor (GLP-1R) agonists have been found to reduce alcohol drinking in rodents and overweight patients with alcohol use disorder (AUD). However, the probability of low semaglutide doses, an agonist with higher potency and affinity for GLP-1R, to attenuate alcohol-related responses in rodents and the underlying neuronal mechanisms is unknown.

METHODS

In the intermittent access model, we examined the ability of semaglutide to decrease alcohol intake and block relapse-like drinking, as well as imaging the binding of fluorescently marked semaglutide to nucleus accumbens (NAc) in both male and female rats. The suppressive effect of semaglutide on alcohol-induced locomotor stimulation and in vivo dopamine release in NAc was tested in male mice. We evaluated effect of semaglutide on the in vivo release of dopamine metabolites (DOPAC and HVA) and gene expression of enzymes metabolising dopamine (MAOA and COMT) in male mice.

FINDINGS

In male and female rats, acute and repeated semaglutide administration reduced alcohol intake and prevented relapse-like drinking. Moreover, fluorescently labelled semaglutide was detected in NAc of alcohol-drinking male and female rats. Further, semaglutide attenuated the ability of alcohol to cause hyperlocomotion and to elevate dopamine in NAc in male mice. As further shown in male mice, semaglutide enhanced DOPAC and HVA in NAc when alcohol was onboard and increased the gene expression of COMT and MAOA.

INTERPRETATION

Altogether, this indicates that semaglutide reduces alcohol drinking behaviours, possibly via a reduction in alcohol-induced reward and NAc dependent mechanisms. As semaglutide also decreased body weight of alcohol-drinking rats of both sexes, upcoming clinical studies should test the plausibility that semaglutide reduces alcohol intake and body weight in overweight AUD patients.

FUNDING

Swedish Research Council (2019-01676), LUA/ALF (723941) from the Sahlgrenska University Hospital and the Swedish brain foundation.

A Hypothalamic Circuit Underlying the Dynamic Control of Social Homeostasis

Social grouping increases survival in many species, including humans1,2. By contrast, social isolation generates an aversive state (loneliness) that motivates social seeking and heightens social interaction upon reunion3-5. The observed rebound in social interaction triggered by isolation suggests a homeostatic process underlying the control of social drive, similar to that observed for physiological needs such as hunger, thirst or sleep3,6. In this study, we assessed social responses in multiple mouse strains and identified the FVB/NJ line as exquisitely sensitive to social isolation. Using FVB/NJ mice, we uncovered two previously uncharacterized neuronal populations in the hypothalamic preoptic nucleus that are activated during social isolation and social rebound and that orchestrate the behavior display of social need and social satiety, respectively. We identified direct connectivity between these two populations of opposite function and with brain areas associated with social behavior, emotional state, reward, and physiological needs, and showed that animals require touch to assess the presence of others and fulfill their social need, thus revealing a brain-wide neural system underlying social homeostasis. These findings offer mechanistic insight into the nature and function of circuits controlling instinctive social need and for the understanding of healthy and diseased brain states associated with social context.

Dopamine in the rodent tail of striatum regulates behavioral variability in response to threatening novel objects

Mice display variability in fear-like responses to many external salient events, such as encountering unexpected novel objects, but the neural basis of this variability has been unclear. Akiti et al. (2022) demonstrate that dopamine in the tail of the rodent striatum predicts and regulates salience-related variability in individuals' behavioral responses to unexpected novel objects.

Behavioural and dopaminergic signatures of resilience

Chronic stress can have lasting adverse consequences in some individuals, yet others are resilient to the same stressor1,2. Susceptible and resilient individuals exhibit differences in the intrinsic properties of mesolimbic dopamine (DA) neurons after the stressful experience is over3-8. However, the causal links between DA, behaviour during stress and individual differences in resilience are unknown. Here we recorded behaviour in mice simultaneously with DA neuron activity in projections to the nucleus accumbens (NAc) (which signals reward9-12) and the tail striatum (TS) (which signals threat13-16) during social defeat. Supervised and unsupervised behavioural quantification revealed that during stress, resilient and susceptible mice use different behavioural strategies and have distinct activity patterns in DA terminals in the NAc (but not the TS). Neurally, resilient mice have greater activity near the aggressor, including at the onset of fighting back. Conversely, susceptible mice have greater activity at the offset of attacks and onset of fleeing. We also performed optogenetic stimulation of NAc-projecting DA neurons in open loop (randomly timed) during defeat or timed to specific behaviours using real-time behavioural classification. Both open-loop and fighting-back-timed activation promoted resilience and reorganized behaviour during defeat towards resilience-associated patterns. Together, these data provide a link between DA neural activity, resilience and resilience-associated behaviour during the experience of stress.