Animal to human translational paradigms relevant for approach avoidance conflict decision making

The neurocomputational link between defensive cardiac states and approach-avoidance arbitration under threat

Avoidance, a hallmark of anxiety-related psychopathology, often comes at a cost; avoiding threat may forgo the possibility of a reward. Theories predict that optimal approach-avoidance arbitration depends on threat-induced psychophysiological states, like freezing-related bradycardia. Here we used model-based fMRI analyses to investigate whether and how bradycardia states are linked to the neurocomputational underpinnings of approach-avoidance arbitration under varying reward and threat magnitudes. We show that bradycardia states are associated with increased threat-induced avoidance and more pronounced reward-threat value comparison (i.e., a stronger tendency to approach vs. avoid when expected reward outweighs threat). An amygdala-striatal-prefrontal circuit supports approach-avoidance arbitration under threat, with specific involvement of the amygdala and dorsal anterior cingulate (dACC) in integrating reward-threat value and bradycardia states. These findings highlight the role of human freezing states in value-based decision making, relevant for optimal threat coping. They point to a specific role for amygdala/dACC in state-value integration under threat.

Astrocyte-mediated regulation of BLAWFS1 neurons alleviates risk-assessment deficits in DISC1-N mice

Assessing and responding to threats is vital in everyday life. Unfortunately, many mental illnesses involve impaired risk assessment, affecting patients, families, and society. The brain processes behind these behaviors are not well understood. We developed a transgenic mouse model (disrupted-in-schizophrenia 1 [DISC1]-N) with a disrupted avoidance response in risky settings. Our study utilized single-nucleus RNA sequencing and path-clamp coupling with real-time RT-PCR to uncover a previously undescribed group of glutamatergic neurons in the basolateral amygdala (BLA) marked by Wolfram syndrome 1 (WFS1) expression, whose activity is modulated by adjacent astrocytes. These neurons in DISC1-N mice exhibited diminished firing ability and impaired communication with the astrocytes. Remarkably, optogenetic activation of these astrocytes reinstated neuronal excitability via D-serine acting on BLAWFS1 neurons' NMDA receptors, leading to improved risk-assessment behavior in the DISC1-N mice. Our findings point to BLA astrocytes as a promising target for treating risk-assessment dysfunctions in mental disorders.

Rodent tests of depression and anxiety: Construct validity and translational relevance

Behavioral testing constitutes the primary method to measure the emotional states of nonhuman animals in preclinical research. Emerging as the characteristic tool of the behaviorist school of psychology, behavioral testing of animals, particularly rodents, is employed to understand the complex cognitive and affective symptoms of neuropsychiatric disorders. Following the symptom-based diagnosis model of the DSM, rodent models and tests of depression and anxiety focus on behavioral patterns that resemble the superficial symptoms of these disorders. While these practices provided researchers with a platform to screen novel antidepressant and anxiolytic drug candidates, their construct validity-involving relevant underlying mechanisms-has been questioned. In this review, we present the laboratory procedures used to assess depressive- and anxiety-like behaviors in rats and mice. These include constructs that rely on stress-triggered responses, such as behavioral despair, and those that emerge with nonaversive training, such as cognitive bias. We describe the specific behavioral tests that are used to assess these constructs and discuss the criticisms on their theoretical background. We review specific concerns about the construct validity and translational relevance of individual behavioral tests, outline the limitations of the traditional, symptom-based interpretation, and introduce novel, ethologically relevant frameworks that emphasize simple behavioral patterns. Finally, we explore behavioral monitoring and morphological analysis methods that can be integrated into behavioral testing and discuss how they can enhance the construct validity of these tests.

Cognitive Signatures of Depressive and Anhedonic Symptoms and Affective States Using Computational Modeling and Neurocognitive Testing

BACKGROUND

Deeper phenotyping may improve our understanding of depression. Because depression is heterogeneous, extracting cognitive signatures associated with severity of depressive symptoms, anhedonia, and affective states is a promising approach.

METHODS

Sequential sampling models decomposed behavior from an adaptive approach-avoidance conflict task into computational parameters quantifying latent cognitive signatures. Fifty unselected participants completed clinical scales and the approach-avoidance conflict task by either approaching or avoiding trials offering monetary rewards and electric shocks.

RESULTS

Decision dynamics were best captured by a sequential sampling model with linear collapsing boundaries varying by net offer values, and with drift rates varying by trial-specific reward and aversion, reflecting net evidence accumulation toward approach or avoidance. Unlike conventional behavioral measures, these computational parameters revealed distinct associations with self-reported symptoms. Specifically, passive avoidance tendencies, indexed by starting point biases, were associated with greater severity of depressive symptoms (R = 0.34, p = .019) and anhedonia (R = 0.49, p = .001). Depressive symptoms were also associated with slower encoding and response execution, indexed by nondecision time (R = 0.37, p = .011). Higher reward sensitivity for offers with negative net values, indexed by drift rates, was linked to more sadness (R = 0.29, p = .042) and lower positive affect (R = -0.33, p = .022). Conversely, higher aversion sensitivity was associated with more tension (R = 0.33, p = .025). Finally, less cautious response patterns, indexed by boundary separation, were linked to more negative affect (R = -0.40, p = .005).

CONCLUSIONS

We demonstrated the utility of multidimensional computational phenotyping, which could be applied to clinical samples to improve characterization and treatment selection.

Estimating foraging behavior in rodents using a modified paradigm measuring threat imminence dynamics

Animals need to respond to threats to avoid danger and approach rewards. In nature, these responses did not evolve alone but are always accompanied by motivational conflict. A semi-naturalistic threat imminence continuum model models the approach-avoidance conflict and is able to integrate multiple behaviors into a single paradigm. However, its comprehensive application is hampered by the lack of a detailed protocol and data about some fundamental factors including sex, age, and motivational level. Here, we modified a previously established paradigm measuring threat imminence continuum dynamics, involving modifications of training and testing protocols, and utilization of commercial materials combined with open science codes, making it easier to replicate. We demonstrate that foraging behavior is modulated by age, hunger level, and sex. This paradigm can be used to study foraging behaviors in animals in a more naturalistic manner with relevance to human approach-avoid conflicts and associated psychopathologies.

Approach-avoidance reinforcement learning as a translational and computational model of anxiety-related avoidance

Although avoidance is a prevalent feature of anxiety-related psychopathology, differences in the measurement of avoidance between humans and non-human animals hinder our progress in its theoretical understanding and treatment. To address this, we developed a novel translational measure of anxiety-related avoidance in the form of an approach-avoidance reinforcement learning task, by adapting a paradigm from the non-human animal literature to study the same cognitive processes in human participants. We used computational modelling to probe the putative cognitive mechanisms underlying approach-avoidance behaviour in this task and investigated how they relate to subjective task-induced anxiety. In a large online study (n = 372), participants who experienced greater task-induced anxiety avoided choices associated with punishment, even when this resulted in lower overall reward. Computational modelling revealed that this effect was explained by greater individual sensitivities to punishment relative to rewards. We replicated these findings in an independent sample (n = 627) and we also found fair-to-excellent reliability of measures of task performance in a sub-sample retested 1 week later (n = 57). Our findings demonstrate the potential of approach-avoidance reinforcement learning tasks as translational and computational models of anxiety-related avoidance. Future studies should assess the predictive validity of this approach in clinical samples and experimental manipulations of anxiety.

Placing Approach-Avoidance Conflict Within the Framework of Multi-objective Reinforcement Learning

Many psychiatric disorders are marked by impaired decision-making during an approach-avoidance conflict. Current experiments elicit approach-avoidance conflicts in bandit tasks by pairing an individual's actions with consequences that are simultaneously desirable (reward) and undesirable (harm). We frame approach-avoidance conflict tasks as a multi-objective multi-armed bandit. By defining a general decision-maker as a limiting sequence of actions, we disentangle the decision process from learning. Each decision maker can then be identified as a multi-dimensional point representing its long-term average expected outcomes, while different decision making models can be associated by the geometry of their 'feasible region', the set of all possible long term performances on a fixed task. We introduce three example decision-makers based on popular reinforcement learning models and characterize their feasible regions, including whether they can be Pareto optimal. From this perspective, we find that existing tasks are unable to distinguish between the three examples of decision-makers. We show how to design new tasks whose geometric structure can be used to better distinguish between decision-makers. These findings are expected to guide the design of approach-avoidance conflict tasks and the modeling of resulting decision-making behavior.

Decision-making for concurrent reward and threat is differentially modulated by trauma exposure and PTSD symptom severity

Trauma exposure, particularly interpersonal violence (IPV) traumas, are significant risk factors for development of mental health disorders, particularly posttraumatic stress disorder (PTSD). Studies attempting to disentangle mechanisms by which trauma confers risk and maintenance of PTSD have often investigated threat or reward learning in isolation. However, real-world decision-making often involves navigating concurrent and conflicting probabilities for threat and reward. We sought to understand how threat and reward learning interact to impact decision-making, and how these processes are modulated by trauma exposure and PTSD symptom severity. 429 adult participants with a range of trauma exposure and symptom severities completed an online version of the two stage Markov task, where participants make a series of decisions towards the goal of obtaining a reward, that embedded an intermediate threat or neutral image along the sequence of decisions to be made. This task design afforded the possibility to differentiate between threat avoidance vs diminished reward learning in the presence of threat, and whether these two processes reflect model-based vs model-free decision-making. Results demonstrated that trauma exposure severity, particularly IPV exposure, was associated with impairment in model-based learning for reward independent of threat, as well as with model-based threat avoidance. PTSD symptom severity was associated with diminished model-based learning for reward in the presence of threat, consistent with a threat-induced impairment in cognitively-demanding strategies for reward learning, but no evidence of heightened threat avoidance. These results highlight the complex interactions between threat and reward learning as a function of trauma exposure and PTSD symptom severity. Findings have potential implications for treatment augmentation and suggest a need for continued research.

A randomized clinical trial of behavioral activation and exposure-based therapy for adults with generalized anxiety disorder

Objective

Exposure-based therapy (EXP) and behavioral activation (BA) are empirically-supported behavioral intervention techniques that target avoidance and approach behavior to alleviate symptoms. Although EXP is an established treatment for generalized anxiety disorder (GAD), the effectiveness of BA for GAD has not been directly tested or compared with that of EXP. This study examined the efficacy of EXP and BA for adults with GAD.

Method

In a randomized clinical trial (clinicaltrials.gov: NCT02807480) with partial blinding in Tulsa, OK, 102 adults with GAD were allocated to manualized, 10-session EXP or BA between April 2016-April 2021. Primary analyses were intention-to-treat and included the 94 (46 EXP, 48 BA) participants who started treatment. The GAD-7 self-report scale was the primary outcome measure.

Results

Similar GAD-7 declines were observed at post-treatment for EXP (d=-0.97 [95% CI -1.40 to -0.53]) and BA (d=-1.14 [95% CI -1.57 to -0.70]), and were maintained through 6-month follow-up (EXP: d=-2.13, BA: d=-1.98). Compared to EXP, BA yielded more rapid declines in anxiety and depression scores during therapy (d=0.75-0.77), as well as lower anxiety and depression scores (d=0.13-0.14) and greater participant-rated improvement (d=0.64) at post-treatment. Bayesian analyses indicated 74-99% probability of greater change in BA than EXP at post-treatment.

Conclusions

BA and EXP are both effective in treating GAD, and BA may confer greater benefit during treatment. Future research is warranted to inform personalized treatment approaches.

Electric foot-shock induces neurobehavioral aberrations due to imbalance in oxidative status, stress hormone, neurochemical profile, and irregular cortical-beta wave pattern in rats: A validated animal model of anxiety

Neuropsychiatric disorders can be modeled on animals to investigate the neural mechanism underlying these disorders. Models of neuropsychiatric disorders, such as anxiety, basically aim to produce the signs and symptoms of human anxiety disorders in laboratory animals. Electric foot-shock is recommended to induce anxiety-like symptoms in rodents. For this purpose, however, a range of current intensities is available in the literature. The present study aims to modify the existing practices of generating anxiety-like symptoms through electric foot-shock by identifying an optimum current intensity and combing it with behavioral paradigms to produce a rat model of anxiety. Furthermore, the validity of the model was confirmed by checking the fulfillment of three validity criteria necessary for the development of any disease model including face validity, construct validity, and predictive validity. In the current study, after pre-testing, 1.0 mA electric intensity was selected to produce the model of anxiety. The results showed that the induction of 1.0 mA electric foot-shock induces abnormal behavioral effects which were similar to anxiety-like effects as evident by social interaction test, light-dark transition test, and open field test. Moreover, aberrations in the levels of the stress hormone, oxidative stress parameters, hippocampal neurotransmitter levels, and cortical-EEG wave pattern were also observed in the rat model of anxiety which were successfully overcome using diazepam. In conclusion, the outcome of our study suggests that electric foot-shock can be an adequate stressor to produce a validated animal model of anxiety and this model can be confidently used to identify and screen new and/or novel anxiolytics.

Quantifying aberrant approach-avoidance conflict in psychopathology: A review of computational approaches

Making effective decisions during approach-avoidance conflict is critical in daily life. Aberrant decision-making during approach-avoidance conflict is evident in a range of psychological disorders, including anxiety, depression, trauma-related disorders, substance use disorders, and alcohol use disorders. To help clarify etiological pathways and reveal novel intervention targets, clinical research into decision-making is increasingly adopting a computational psychopathology approach. This approach uses mathematical models that can identify specific decision-making related processes that are altered in mental health disorders. In our review, we highlight foundational approach-avoidance conflict research, followed by more in-depth discussion of computational approaches that have been used to model behavior in these tasks. Specifically, we describe the computational models that have been applied to approach-avoidance conflict (e.g., drift-diffusion, active inference, and reinforcement learning models), and provide resources to guide clinical researchers who may be interested in applying computational modeling. Finally, we identify notable gaps in the current literature and potential future directions for computational approaches aimed at identifying mechanisms of approach-avoidance conflict in psychopathology.

Understanding clinical fear and anxiety through the lens of human fear conditioning

Fear is an adaptive emotion that mobilizes defensive resources upon confrontation with danger. However, fear becomes maladaptive and can give rise to the development of clinical anxiety when it exceeds the degree of threat, generalizes broadly across stimuli and contexts, persists after the danger is gone or promotes excessive avoidance behaviour. Pavlovian fear conditioning has been the prime research instrument that has led to substantial progress in understanding the multi-faceted psychological and neurobiological mechanisms of fear in past decades. In this Perspective, we suggest that fruitful use of Pavlovian fear conditioning as a laboratory model of clinical anxiety requires moving beyond the study of fear acquisition to associated fear conditioning phenomena: fear extinction, generalization of conditioned fear and fearful avoidance. Understanding individual differences in each of these phenomena, not only in isolation but also in how they interact, will further strengthen the external validity of the fear conditioning model as a tool with which to study maladaptive fear as it manifests in clinical anxiety.

The action dynamics of approach-avoidance conflict during decision-making

Approach-avoidance conflict is observed in the competing motivations towards the benefits and away from the costs of a decision. The current study investigates the action dynamics of response motion during such conflicts in an attempt to characterise their dynamic resolution. An approach-avoidance conflict was generated by varying the appetitive consequences of a decision (i.e., point rewards and shorter participation time) in the presence of simultaneous aversive consequences (i.e., shock probability). Across two experiments, approach-avoidance conflict differentially affected response trajectories. Approach trajectories were less complex than avoidance trajectories and, as approach and avoidance motivations neared equipotentiality, response trajectories were more deflected from the shortest route to the eventual choice. Consistency in the location of approach and avoidance response options reduced variability in performance enabling more sensitive estimates of dynamic conflict. The time course of competing influences on response trajectories including trial-to-trial effects and conflict between approach and avoidance were estimated using regression analyses. We discuss these findings in terms of a dynamic theory of approach-avoidance that we hope will lead to insights of practical relevance in the field of maladaptive avoidance.

Computational perspectives on human fear and anxiety

Fear and anxiety are adaptive emotions that serve important defensive functions, yet in excess, they can be debilitating and lead to poor mental health. Computational modelling of behaviour provides a mechanistic framework for understanding the cognitive and neurobiological bases of fear and anxiety, and has seen increasing interest in the field. In this brief review, we discuss recent developments in the computational modelling of human fear and anxiety. Firstly, we describe various reinforcement learning strategies that humans employ when learning to predict or avoid threat, and how these relate to symptoms of fear and anxiety. Secondly, we discuss initial efforts to explore, through a computational lens, approach-avoidance conflict paradigms that are popular in animal research to measure fear- and anxiety-relevant behaviours. Finally, we discuss negative biases in decision-making in the face of uncertainty in anxiety.

Preclinical and clinical evidence on the approach-avoidance conflict evaluation as an integrative tool for psychopathology

The approach-avoidance conflict (AAC), i.e. the competing tendencies to undertake goal-directed actions or to withdraw from everyday life challenges, stands at the basis of humans' existence defining behavioural and personality domains. Gray's Reinforcement Sensitivity Theory posits that a stable bias toward approach or avoidance represents a psychopathological trait associated with excessive sensitivity to reward or punishment. Optogenetic studies in rodents and imaging studies in humans associated with cross-species AAC paradigms granted new emphasis to the hippocampus as a hub of behavioural inhibition. For instance, recent functional neuroimaging studies show that functional brain activity in the human hippocampus correlates with threat perception and seems to underlie passive avoidance. Therefore, our commentary aims to (i) discuss the inhibitory role of the hippocampus in approach-related behaviours and (ii) promote the integration of functional neuroimaging with cross-species AAC paradigms as a means of diagnostic, therapeutic, follow up and prognosis refinement in psychiatric populations.

Got milk? Maternal immune activation during the mid-lactational period affects nutritional milk quality and adolescent offspring sensory processing in male and female rats

Previous studies have underscored the importance of breastfeeding and parental care on offspring development and behavior. However, their contribution as dynamic variables in animal models of early life stress are often overlooked. In the present study, we investigated how lipopolysaccharide (LPS)-induced maternal immune activation (MIA) on postnatal day (P)10 affects maternal care, milk, and offspring development. MIA was associated with elevated milk corticosterone concentrations on P10, which recovered by P11. In contrast, both milk triglyceride and percent creamatocrit values demonstrated a prolonged decrease following inflammatory challenge. Adolescent MIA offspring were heavier, which is often suggestive of poor early life nutrition. While MIA did not decrease maternal care quality, there was a significant compensatory increase in maternal licking and grooming the day following inflammatory challenge. However, this did not protect against disrupted neonatal huddling or later-life alterations in sensorimotor gating, conditioned fear, mechanical allodynia, or reductions in hippocampal parvalbumin expression in MIA offspring. MIA-associated changes in brain and behavior were likely driven by differences in milk nutritional values and not by direct exposure to LPS or inflammatory molecules as neither LPS binding protein nor interleukin-6 milk levels differed between groups. These findings reflected comparable microbiome and transcriptomic patterns at the genome-wide level. Animal models of early life stress can impact both parents and their offspring. One mechanism that can mediate the effects of such stressors is changes to maternal lactation quality which our data show can confer multifaceted and compounding effects on offspring physiology and behavior.

Large-scale neural network computations and multivariate representations during approach-avoidance conflict decision-making

Many real-world situations require navigating decisions for both reward and threat. While there has been significant progress in understanding mechanisms of decision-making and mediating neurocircuitry separately for reward and threat, there is limited understanding of situations where reward and threat contingencies compete to create approach-avoidance conflict (AAC). Here, we leverage computational learning models, independent component analysis (ICA), and multivariate pattern analysis (MVPA) approaches to understand decision-making during a novel task that embeds concurrent reward and threat learning and manipulates congruency between reward and threat probabilities. Computational modeling supported a modified reinforcement learning model where participants integrated reward and threat value into a combined total value according to an individually varying policy parameter, which was highly predictive of decisions to approach reward vs avoid threat during trials where the highest reward option was also the highest threat option (i.e., approach-avoidance conflict). ICA analyses demonstrated unique roles for salience, frontoparietal, medial prefrontal, and inferior frontal networks in differential encoding of reward vs threat prediction error and value signals. The left frontoparietal network uniquely encoded degree of conflict between reward and threat value at the time of choice. MVPA demonstrated that delivery of reward and threat could accurately be decoded within salience and inferior frontal networks, respectively, and that decisions to approach reward vs avoid threat were predicted by the relative degree to which these reward vs threat representations were active at the time of choice. This latter result suggests that navigating AAC decisions involves generating mental representations for possible decision outcomes, and relative activation of these representations may bias subsequent decision-making towards approaching reward or avoiding threat accordingly.

Using deep learning to study emotional behavior in rodent models

Quantifying emotional aspects of animal behavior (e.g., anxiety, social interactions, reward, and stress responses) is a major focus of neuroscience research. Because manual scoring of emotion-related behaviors is time-consuming and subjective, classical methods rely on easily quantified measures such as lever pressing or time spent in different zones of an apparatus (e.g., open vs. closed arms of an elevated plus maze). Recent advancements have made it easier to extract pose information from videos, and multiple approaches for extracting nuanced information about behavioral states from pose estimation data have been proposed. These include supervised, unsupervised, and self-supervised approaches, employing a variety of different model types. Representations of behavioral states derived from these methods can be correlated with recordings of neural activity to increase the scope of connections that can be drawn between the brain and behavior. In this mini review, we will discuss how deep learning techniques can be used in behavioral experiments and how different model architectures and training paradigms influence the type of representation that can be obtained.

The Scientific Study of Consciousness Cannot and Should Not Be Morally Neutral

A target question for the scientific study of consciousness is how dimensions of consciousness, such as the ability to feel pain and pleasure or reflect on one's own experience, vary in different states and animal species. Considering the tight link between consciousness and moral status, answers to these questions have implications for law and ethics. Here we point out that given this link, the scientific community studying consciousness may face implicit pressure to carry out certain research programs or interpret results in ways that justify current norms rather than challenge them. We show that because consciousness largely determines moral status, the use of nonhuman animals in the scientific study of consciousness introduces a direct conflict between scientific relevance and ethics-the more scientifically valuable an animal model is for studying consciousness, the more difficult it becomes to ethically justify compromises to its well-being for consciousness research. Finally, in light of these considerations, we call for a discussion of the immediate ethical corollaries of the body of knowledge that has accumulated and for a more explicit consideration of the role of ideology and ethics in the scientific study of consciousness.

Striatal reactivity during emotion and reward relates to approach-avoidance conflict behaviour and is altered in adults with anxiety or depression

BACKGROUND

We have previously reported activation in reward, salience and executive control regions during functional MRI (fMRI) using an approach-avoidance conflict (AAC) decision-making task with healthy adults. Further investigations into how anxiety and depressive disorders relate to differences in neural responses during AAC can inform their understanding and treatment. We tested the hypothesis that people with anxiety or depression have altered neural activation during AAC.

METHODS

We compared 118 treatment-seeking adults with anxiety or depression and 58 healthy adults using linear mixed-effects models to examine group-level differences in neural activation (fMRI) during AAC decision-making. Correlational analyses examined relationships between behavioural and neural measures.

RESULTS

Adults with anxiety or depression had greater striatal engagement when reacting to affective stimuli (p = 0.008, d = 0.31) regardless of valence, and weaker striatal engagement during reward feedback (p = 0.046, d = -0.27) regardless of the presence of monetary reward. They also had blunted amygdala activity during decision-making (p = 0.023, d = -0.32) regardless of the presence of conflict. Across groups, approach behaviour during conflict decision-making was inversely correlated with striatal activation during affective stimuli (p < 0.001, r = -0.28) and positively related to striatal activation during reward feedback (p < 0.001, r = 0.27).

LIMITATIONS

Our transdiagnostic approach did not allow for comparisons between specific anxiety disorders, and our cross-sectional approach did not allow for causal inference.

CONCLUSION

Anxiety and depression were associated with altered neural responses to AAC. Findings were consistent with the role of the striatum in action selection and reward responsivity, and they point toward striatal reactivity as a future treatment target. Blunting of amygdala activity in anxiety or depression may indicate a compensatory response to inhibit affective salience and maintain approach.

Parallel ventral hippocampus-lateral septum pathways differentially regulate approach-avoidance conflict

The ability to resolve an approach-avoidance conflict is critical to adaptive behavior. The ventral CA3 (vCA3) and CA1 (vCA1) subfields of the ventral hippocampus (vHPC) have been shown to facilitate avoidance and approach behavior, respectively, in the face of motivational conflict, but the neural circuits by which this subfield-specific regulation is implemented is unknown. We demonstrate that two distinct pathways from these subfields to lateral septum (LS) contribute to this divergent control. In Long-Evans rats, chemogenetic inhibition of the vCA3- LS caudodorsal (cd) pathway potentiated approach towards a learned conflict-eliciting stimulus, while inhibition of the vCA1-LS rostroventral (rv) pathway potentiated approach non-specifically. Additionally, vCA3-LScd inhibited animals were less hesitant to explore food during environmental uncertainty, while the vCA1- LSrv inhibited animals took longer to initiate food exploration. These findings suggest that the vHPC influences multiple behavioral systems via differential projections to the LS, which in turn send inhibitory projections to motivational centres of the brain.

Measuring maladaptive avoidance: from animal models to clinical anxiety

Avoiding stimuli that predict danger is required for survival. However, avoidance can become maladaptive in individuals who overestimate threat and thus avoid safe situations as well as dangerous ones. Excessive avoidance is a core feature of anxiety disorders, post-traumatic stress disorder (PTSD), and obsessive-compulsive disorder (OCD). This avoidance prevents patients from confronting maladaptive threat beliefs, thereby maintaining disordered anxiety. Avoidance is associated with high levels of psychosocial impairment yet is poorly understood at a mechanistic level. Many objective laboratory assessments of avoidance measure adaptive avoidance, in which an individual learns to successfully avoid a truly noxious stimulus. However, anxiety disorders are characterized by maladaptive avoidance, for which there are fewer objective laboratory measures. We posit that maladaptive avoidance behavior depends on a combination of three altered neurobehavioral processes: (1) threat appraisal, (2) habitual avoidance, and (3) trait avoidance tendency. This heterogeneity in underlying processes presents challenges to the objective measurement of maladaptive avoidance behavior. Here we first review existing paradigms for measuring avoidance behavior and its underlying neural mechanisms in both human and animal models, and identify how existing paradigms relate to these neurobehavioral processes. We then propose a new framework to improve the translational understanding of maladaptive avoidance behavior by adapting paradigms to better differentiate underlying processes and mechanisms and applying these paradigms in clinical populations across diagnoses with the goal of developing novel interventions to engage specific identified neurobehavioral targets.

The prefrontal cortex, pathological anxiety, and anxiety disorders

Anxiety is experienced in response to threats that are distal or uncertain, involving changes in one's subjective state, autonomic responses, and behavior. Defensive and physiologic responses to threats that involve the amygdala and brainstem are conserved across species. While anxiety responses typically serve an adaptive purpose, when excessive, unregulated, and generalized, they can become maladaptive, leading to distress and avoidance of potentially threatening situations. In primates, anxiety can be regulated by the prefrontal cortex (PFC), which has expanded in evolution. This prefrontal expansion is thought to underlie primates' increased capacity to engage high-level regulatory strategies aimed at coping with and modifying the experience of anxiety. The specialized primate lateral, medial, and orbital PFC sectors are connected with association and limbic cortices, the latter of which are connected with the amygdala and brainstem autonomic structures that underlie emotional and physiological arousal. PFC pathways that interface with distinct inhibitory systems within the cortex, the amygdala, or the thalamus can regulate responses by modulating neuronal output. Within the PFC, pathways connecting cortical regions are poised to reduce noise and enhance signals for cognitive operations that regulate anxiety processing and autonomic drive. Specialized PFC pathways to the inhibitory thalamic reticular nucleus suggest a mechanism to allow passage of relevant signals from thalamus to cortex, and in the amygdala to modulate the output to autonomic structures. Disruption of specific nodes within the PFC that interface with inhibitory systems can affect the negative bias, failure to regulate autonomic arousal, and avoidance that characterize anxiety disorders.

The Good, the Bad, and the Ugly-Chances, Challenges, and Clinical Implications of Avoidance Research in Psychosomatic Medicine

Avoidance behaviors are shaped by associative learning processes in response to fear of impending threats, particularly physical harm. As part of a defensive repertoire, avoidance is highly adaptive in case of acute danger, serving a potent protective function. However, persistent or excessive fear and maladaptive avoidance are considered key factors in the etiology and pathophysiology of anxiety- and stress-related psychosomatic disorders. In these overlapping conditions, avoidance can increase the risk of mental comorbidities and interfere with the efficacy of cognitive behavioral treatment approaches built on fear extinction. Despite resurging interest in avoidance research also in the context of psychosomatic medicine, especially in conditions associated with pain, disturbed interoception, and disorders of the gut-brain axis, current study designs and their translation into the clinical context face significant challenges limiting both, the investigation of mechanisms involved in avoidance and the development of novel targeted treatment options. We herein selectively review the conceptual framework of learning and memory processes, emphasizing how classical and operant conditioning, fear extinction, and return of fear shape avoidance behaviors. We further discuss pathological avoidance and safety behaviors as hallmark features in psychosomatic diseases, with a focus on anxiety- and stress-related disorders. Aiming to emphasize chances of improved translational knowledge across clinical conditions, we further point out limitations in current experimental avoidance research. Based on these considerations, we propose means to improve existing avoidance paradigms to broaden our understanding of underlying mechanisms, moderators and mediators of avoidance, and to inspire tailored treatments for patients suffering from psychosomatic disorders.

Neural correlates and determinants of approach-avoidance conflict in the prelimbic prefrontal cortex

The recollection of environmental cues associated with threat or reward allows animals to select the most appropriate behavioral responses. Neurons in the prelimbic (PL) cortex respond to both threat- and reward-associated cues. However, it remains unknown whether PL regulates threat-avoidance vs. reward-approaching responses when an animals’ decision depends on previously associated memories. Using a conflict model in which male Long–Evans rats retrieve memories of shock- and food-paired cues, we observed two distinct phenotypes during conflict: (1) rats that continued to press a lever for food (Pressers) and (2) rats that exhibited a complete suppression in food seeking (Non-pressers). Single-unit recordings revealed that increased risk-taking behavior in Pressers is associated with persistent food-cue responses in PL, and reduced spontaneous activity in PL glutamatergic (PL^GLUT) neurons during conflict. Activating PL^GLUT neurons in Pressers attenuated food-seeking responses in a neutral context, whereas inhibiting PL^GLUT neurons in Non-pressers reduced defensive responses and increased food approaching during conflict. Our results establish a causal role for PL^GLUT neurons in mediating individual variability in memory-based risky decision-making by regulating threat-avoidance vs. reward-approach behaviors.

Fear conditioning and extinction in obsessive-compulsive disorder: A systematic review

Laboratory experiments using fear conditioning and extinction protocols help lay the groundwork for designing, testing, and optimizing innovative treatments for anxiety-related disorders. Yet, there is limited basic research on fear conditioning and extinction in obsessive-compulsive disorder (OCD). This is surprising because exposure-based treatments based on associative learning principles are among the most popular and effective treatment options for OCD. Here, we systematically review and critically assess existing aversive conditioning and extinction studies of OCD. Across 12 studies, there was moderate evidence that OCD is associated with abnormal acquisition of conditioned responses that differ from comparison groups. There was relatively stronger evidence of OCD's association with impaired extinction processes. This included multiple studies finding elevated conditioned responses during extinction learning and poorer threat/safety discrimination during recall, although a minority of studies yielded results inconsistent with this conclusion. Overall, the conditioning model holds value for OCD research, but more work is necessary to clarify emerging patterns of results and increase clinical translational utility to the level seen in other anxiety-related disorders. We detail limitations in the literature and suggest next steps, including modeling OCD with more complex conditioning methodology (e.g., semantic/conceptual generalization, avoidance) and improving individual-differences assessment with dimensional techniques.

The Role of the Dorsal-Lateral Prefrontal Cortex in Reward Sensitivity During Approach-Avoidance Conflict

Approach-Avoidance conflict (AAC) arises from decisions with embedded positive and negative outcomes, such that approaching leads to reward and punishment and avoiding to neither. Despite its importance, the field lacks a mechanistic understanding of which regions are driving avoidance behavior during conflict. In the current task, we utilized transcranial magnetic stimulation (TMS) and drift-diffusion modeling to investigate the role of one of the most prominent regions relevant to AAC-the dorsolateral prefrontal cortex (dlPFC). The first experiment uses in-task disruption to examine the right dlPFC's (r-dlPFC) causal role in avoidance behavior. The second uses single TMS pulses to probe the excitability of the r-dlPFC, and downstream cortical activations, during avoidance behavior. Disrupting r-dlPFC during conflict decision-making reduced reward sensitivity. Further, r-dlPFC was engaged with a network of regions within the lateral and medial prefrontal, cingulate, and temporal cortices that associate with behavior during conflict. Together, these studies use TMS to demonstrate a role for the dlPFC in reward sensitivity during conflict and elucidate the r-dlPFC's network of cortical regions associated with avoidance behavior. By identifying r-dlPFC's mechanistic role in AAC behavior, contextualized within its conflict-specific downstream neural connectivity, we advance dlPFC as a potential neural target for psychiatric therapeutics.

Defensive freezing and its relation to approach-avoidance decision-making under threat

Successful responding to acutely threatening situations requires adequate approach-avoidance decisions. However, it is unclear how threat-induced states-like freezing-related bradycardia-impact the weighing of the potential outcomes of such value-based decisions. Insight into the underlying computations is essential, not only to improve our models of decision-making but also to improve interventions for maladaptive decisions, for instance in anxiety patients and first-responders who frequently have to make decisions under acute threat. Forty-two participants made passive and active approach-avoidance decisions under threat-of-shock when confronted with mixed outcome-prospects (i.e., varying money and shock amounts). Choice behavior was best predicted by a model including individual action-tendencies and bradycardia, beyond the subjective value of the outcome. Moreover, threat-related bradycardia (high-vs-low threat) interacted with subjective value, depending on the action-context (passive-vs-active). Specifically, in action-contexts incongruent with participants' intrinsic action-tendencies, stronger bradycardia related to diminished effects of subjective value on choice across participants. These findings illustrate the relevance of testing approach-avoidance decisions in relatively ecologically valid conditions of acute and primarily reinforced threat. These mechanistic insights into approach-avoidance conflict-resolution may inspire biofeedback-related techniques to optimize decision-making under threat. Critically, the findings demonstrate the relevance of incorporating internal psychophysiological states and external action-contexts into models of approach-avoidance decision-making.

Long-term stability of computational parameters during approach-avoidance conflict in a transdiagnostic psychiatric patient sample

Maladaptive behavior during approach-avoidance conflict (AAC) is common to multiple psychiatric disorders. Using computational modeling, we previously reported that individuals with depression, anxiety, and substance use disorders (DEP/ANX; SUDs) exhibited differences in decision uncertainty and sensitivity to negative outcomes versus reward (emotional conflict) relative to healthy controls (HCs). However, it remains unknown whether these computational parameters and group differences are stable over time. We analyzed 1-year follow-up data from a subset of the same participants (N = 325) to assess parameter stability and relationships to other clinical and task measures. We assessed group differences in the entire sample as well as a subset matched for age and IQ across HCs (N = 48), SUDs (N = 29), and DEP/ANX (N = 121). We also assessed 2-3 week reliability in a separate sample of 30 HCs. Emotional conflict and decision uncertainty parameters showed moderate 1-year intra-class correlations (.52 and .46, respectively) and moderate to excellent correlations over the shorter period (.84 and .54, respectively). Similar to previous baseline findings, parameters correlated with multiple response time measures (ps < .001) and self-reported anxiety (r = .30, p < .001) and decision difficulty (r = .44, p < .001). Linear mixed effects analyses revealed that patients remained higher in decision uncertainty (SUDs, p = .009) and lower in emotional conflict (SUDs, p = .004, DEP/ANX, p = .02) relative to HCs. This computational modelling approach may therefore offer relatively stable markers of transdiagnostic psychopathology.

Test-retest reliability of approach-avoidance conflict decision-making during functional magnetic resonance imaging in healthy adults

Neural and behavioral mechanisms during approach-avoidance conflict decision-making are relevant across various psychiatric disorders, particularly anxiety disorders. Studies using approach-avoidance conflict paradigms in healthy adults have identified preliminary neural mechanisms, but findings must be replicated and demonstrated as reliable before further application. This study sought to replicate previous findings and examine test-retest reliability of behavioral (approach behavior, reaction time) and neural (regions of interest [ROIs]) responses during an approach-avoidance conflict task conducted during functional magnetic resonance imaging (fMRI). Thirty healthy adults completed an approach-avoidance conflict task during fMRI on two occasions (mean interval: 17 days; range: 11-32). Effects of task condition during three task phases (decision-making, affective outcome and monetary reward) and intraclass correlation coefficients (ICCs) were calculated across time points. Results replicated that approach behavior was modulated by conflict during decision-making. ROI activations were replicated such that dorsal anterior cingulate cortex (dACC) was modulated by conflict during decision-making, and dACC, striatum, and anterior insula were modulated by valence during affective outcomes (p's <.0083). Approach behavior during conflict demonstrated excellent reliability (ICCs ≥.77). Activation of dACC during conflict decision-making and anterior insula during negative outcomes demonstrated fair reliability (ICCs = .51 and .54), and dACC and striatum activation demonstrated good reliability during negative outcomes (ICCs = .63 and .69). Two additional ROIs (amygdala, left dorsolateral prefrontal cortex) showed good reliability during negative outcomes (ICCs ≥.60). These results characterize several specific behavioral and neuroimaging responses that are replicable and sufficiently reliable during approach-avoidance conflict decision-making to support future utility.

A distinct parabrachial-to-lateral hypothalamus circuit for motivational suppression of feeding by nociception

The motivation to eat is not only shaped by nutrition but also competed by external stimuli including pain. How the mouse hypothalamus, the feeding regulation center, integrates nociceptive inputs to modulate feeding is unclear. Within the key nociception relay center parabrachial nucleus (PBN), we demonstrated that neurons projecting to the lateral hypothalamus (^LHPBN) are nociceptive yet distinct from danger-encoding central amygdala-projecting (^CeAPBN) neurons. Activation of ^LHPBN strongly suppressed feeding by limiting eating frequency and also reduced motivation to work for food reward. Refined approach-avoidance paradigm revealed that suppression of ^LHPBN, but not ^CeAPBN, sustained motivation to obtain food. The effect of ^LHPBN neurons on feeding was reversed by suppressing downstream LH^VGluT2 neurons. Thus, distinct from a circuit for fear and escape responses, ^LHPBN neurons channel nociceptive signals to LH^VGluT2 neurons to suppress motivational drive for feeding. Our study provides a new perspective in understanding feeding regulation by external competing stimuli.

Perirhinal Cortex is Involved in the Resolution of Learned Approach-Avoidance Conflict Associated with Discrete Objects

The rodent ventral and primate anterior hippocampus have been implicated in approach-avoidance (AA) conflict processing. It is unclear, however, whether this structure contributes to AA conflict detection and/or resolution, and if its involvement extends to conditions of AA conflict devoid of spatial/contextual information. To investigate this, neurologically healthy human participants first learned to approach or avoid single novel visual objects with the goal of maximizing earned points. Approaching led to point gain and loss for positive and negative objects, respectively, whereas avoidance had no impact on score. Pairs of these objects, each possessing nonconflicting (positive-positive/negative-negative) or conflicting (positive-negative) valences, were then presented during functional magnetic resonance imaging. Participants either made an AA decision to score points (Decision task), indicated whether the objects had identical or differing valences (Memory task), or followed a visual instruction to approach or avoid (Action task). Converging multivariate and univariate results revealed that within the medial temporal lobe, perirhinal cortex, rather than the anterior hippocampus, was predominantly associated with object-based AA conflict resolution. We suggest the anterior hippocampus may not contribute equally to all learned AA conflict scenarios and that stimulus information type may be a critical and overlooked determinant of the neural mechanisms underlying AA conflict behavior.

The Importance of Common Currency Tasks in Translational Psychiatry

Purpose of Review

Common currency tasks are tasks that investigate the same phenomenon in different species. In this review, we discuss how to ensure the translational validity of common currency tasks, summarise their benefits, present recent research in this area and offer future directions and recommendations.

Recent Findings

We discuss the strengths and limitations of three specific examples where common currency tasks have added to our understanding of psychiatric constructs—affective bias, reversal learning and goal-based decision making.

Summary

Overall, common currency tasks offer the potential to improve drug discovery in psychiatry. We recommend that researchers prioritise construct validity above face validity when designing common currency tasks and suggest that the evidence for construct validity is summarised in papers presenting research in this area.

Elevated costly avoidance in anxiety disorders: Patients show little downregulation of acquired avoidance in face of competing rewards for approach

BACKGROUND

Pathological avoidance is a transdiagnostic characteristic of anxiety disorders. Avoidance conditioning re-emerged as a translational model to examine mechanisms and treatment of avoidance. However, its validity for anxiety disorders remains unclear.

METHODS

This study tested for altered avoidance in patients with anxiety disorders compared to matched controls (n = 40/group) using instrumental conditioning assessing low-cost avoidance (avoiding a single aversive outcome) and costly avoidance (avoidance conflicted with gaining rewards). Autonomic arousal and threat expectancy were assessed as indicators of conditioned fear. Associations with dimensional symptom severity were examined.

RESULTS

Patients and controls showed frequent low-cost avoidance without group differences. Controls subsequently inhibited avoidance to gain rewards, which was amplified when aversive outcomes discontinued. In contrast, patients failed to reduce avoidance when aversive and positive outcomes competed (elevated costly avoidance) and showed limited reduction when aversive outcomes discontinued (persistent costly avoidance). Interestingly, elevated costly avoidance was not linked to higher conditioned fear in patients. Moreover, individual data revealed a bimodal distribution of costly avoidance: Some patients showed persistent avoidance, others showed little to no avoidance. Persistent versus low avoiders did not differ in other task-related variables, response to gains and losses in absence of threat, sociodemographic data, or clinical characteristics.

CONCLUSIONS

Findings suggest that anxious psychopathology is associated with a deficit to inhibit avoidance in presence of competing positive outcomes. This offers novel perspectives for research on mechanisms and treatment of anxiety disorders.

Motivational competition and the paraventricular thalamus

Although significant progress has been made in understanding the behavioral and brain mechanisms for motivational systems, much less is known about competition between motivational states or motivational conflict (e.g., approach - avoidance conflict). Despite being produced under diverse conditions, behavior during motivational competition has two signatures: bistability and metastability. These signatures reveal the operation of positive feedback mechanisms in behavioral selection. Different neuronal architectures can instantiate this selection to achieve bistability and metastability in behavior, but each relies on circuit-level inhibition to achieve rapid and stable selection between competing tendencies. Paraventricular thalamus (PVT) is identified as critical to this circuit level inhibition, resolving motivational competition via its extensive projections to local inhibitory networks in the ventral striatum and extended amygdala, enabling adaptive responding under motivational conflict.

Posttraumatic Stress Disorder and the Developing Adolescent Brain

Posttraumatic stress disorder (PTSD) in adolescents is common and debilitating. In contrast to adult PTSD, relatively little is known about the neurobiology of adolescent PTSD, nor about how current treatments may alter adolescent neurodevelopment to allow recovery from PTSD. Improving our understanding of biological mechanisms of adolescent PTSD, taken in the context of neurodevelopment, is crucial for developing novel and personalized treatment approaches. In this review, we highlight prevailing constructs of PTSD and current findings on these domains in adolescent PTSD. Notably, little data exist in adolescent PTSD for prominent adult PTSD constructs, including threat learning and attentional threat bias. Most work to date has examined general threat processing, emotion regulation, and their neural substrates. These studies suggest that adolescent PTSD, while phenomenologically similar to adult PTSD, shows unique neurodevelopmental substrates that may impair recovery but could also be targeted in the context of adolescent neuroplasticity to improve outcomes. Both cross-sectional and longitudinal data suggest abnormal frontolimbic development compared with typically developing youths, a pattern that may differ from resilient youths. Whether current treatments such as trauma-focused psychotherapy engage these targets and restore healthy neurodevelopment remains an open question. We end our review by highlighting emerging areas and knowledge gaps that could be addressed to better characterize the biology underlying adolescent PTSD. Emerging studies in computational modeling of decision making, caregiver-related transmission of traumatic stress, and other areas may offer new targets that could harness adolescent neurobehavioral plasticity to improve resilience and recovery for some of our most vulnerable youths.

Incentive-based, instructed, and social observational extinction of avoidance: Fear-opposite actions and their influence on fear extinction

Avoidance is a transdiagnostic symptom of clinical anxiety and its reduction a major focus of cognitive-behavioral treatments. This study examined the instrumental extinction of goal-directed avoidance by means of incentives, verbal instruction, and social observation and their influence on fear extinction. Participants acquired conditioned fear and instrumental avoidance responses (N = 160). In four randomized groups, the reduction of avoidance by incentives for non-avoidance, instructions to refrain from avoidance, and social observation of non-avoidance was compared to no intervention before removing the aversive outcome. Conditioned fear when avoidance became unavailable subsequently was tested. Incentives, instruction, and observation all reduced avoidance better than no intervention, however, with different degrees and influence on conditioned fear. Incentives and instructions strongly reduced avoidance despite high levels of fear (i.e., fear-opposite actions). This initiated fear extinction, thereby reducing conditioned fear when avoidance became unavailable. Social observation directly reduced conditioned fear, presumably because it conveyed additional information about the absence of the aversive outcome. However, observation only moderately reduced avoidance and resulted in higher fear when avoidance became unavailable. The effects of social observation may depend on the nuances of the demonstrator's behavior. The clear effects of incentive and instructions provide support for clinical interventions to reduce avoidance during exposure therapy and can serve as experimental models for their controlled investigation.

Greater decision uncertainty characterizes a transdiagnostic patient sample during approach-avoidance conflict: a computational modelling approach

BACKGROUND

Imbalances in approach-avoidance conflict (AAC) decision-making (e.g., sacrificing rewards to avoid negative outcomes) are considered central to multiple psychiatric disorders. We used computational modelling to examine 2 factors that are often not distinguished in descriptive analyses of AAC: decision uncertainty and sensitivity to negative outcomes versus rewards (emotional conflict).

METHODS

A previously validated AAC task was completed by 478 participants, including healthy controls (n = 59), people with substance use disorders (n = 159) and people with depression and/or anxiety disorders who did not have substance use disorders (n = 260). Using an active inference model, we estimated individual-level values for a model parameter that reflected decision uncertainty and another that reflected emotional conflict. We also repeated analyses in a subsample (59 healthy controls, 161 people with depression and/or anxiety disorders, 56 people with substance use disorders) that was propensity-matched for age and general intelligence.

RESULTS

The model showed high accuracy (72%). As further validation, parameters correlated with reaction times and self-reported task motivations in expected directions. The emotional conflict parameter further correlated with self-reported anxiety during the task (r = 0.32, p < 0.001), and the decision uncertainty parameter correlated with self-reported difficulty making decisions (r = 0.45, p < 0.001). Compared to healthy controls, people with depression and/or anxiety disorders and people with substance use disorders showed higher decision uncertainty in the propensity-matched sample (t = 2.16, p = 0.03, and t = 2.88, p = 0.005, respectively), with analogous results in the full sample; people with substance use disorders also showed lower emotional conflict in the full sample (t = 3.17, p = 0.002).

LIMITATIONS

This study was limited by heterogeneity of the clinical sample and an inability to examine learning.

CONCLUSION

These results suggest that reduced confidence in how to act, rather than increased emotional conflict, may explain maladaptive approach-avoidance behaviours in people with psychiatric disorders.

Greater decision uncertainty characterizes a transdiagnostic patient sample during approach-avoidance conflict: a computational modelling approach

BACKGROUND

Imbalances in approach-avoidance conflict (AAC) decision-making (e.g., sacrificing rewards to avoid negative outcomes) are considered central to multiple psychiatric disorders. We used computational modelling to examine 2 factors that are often not distinguished in descriptive analyses of AAC: decision uncertainty and sensitivity to negative outcomes versus rewards (emotional conflict).

METHODS

A previously validated AAC task was completed by 478 participants, including healthy controls (n = 59), people with substance use disorders (n = 159) and people with depression and/or anxiety disorders who did not have substance use disorders (n = 260). Using an active inference model, we estimated individual-level values for a model parameter that reflected decision uncertainty and another that reflected emotional conflict. We also repeated analyses in a subsample (59 healthy controls, 161 people with depression and/or anxiety disorders, 56 people with substance use disorders) that was propensity-matched for age and general intelligence.

RESULTS

The model showed high accuracy (72%). As further validation, parameters correlated with reaction times and self-reported task motivations in expected directions. The emotional conflict parameter further correlated with self-reported anxiety during the task (r = 0.32, p < 0.001), and the decision uncertainty parameter correlated with self-reported difficulty making decisions (r = 0.45, p < 0.001). Compared to healthy controls, people with depression and/or anxiety disorders and people with substance use disorders showed higher decision uncertainty in the propensity-matched sample (t = 2.16, p = 0.03, and t = 2.88, p = 0.005, respectively), with analogous results in the full sample; people with substance use disorders also showed lower emotional conflict in the full sample (t = 3.17, p = 0.002).

LIMITATIONS

This study was limited by heterogeneity of the clinical sample and an inability to examine learning.

CONCLUSION

These results suggest that reduced confidence in how to act, rather than increased emotional conflict, may explain maladaptive approach-avoidance behaviours in people with psychiatric disorders.

Human social defeat and approach-avoidance: Escalating social-evaluative threat and threat of aggression increases social avoidance

Basic research on avoidance by Murray Sidman laid the foundation for advances in the classification, conceptualization and treatment of avoidance in psychological disorders. Contemporary avoidance research is explicitly translational and increasingly focused on how competing appetitive and aversive contingencies influence avoidance. In this laboratory investigation, we examined the effects of escalating social-evaluative threat and threat of social aggression on avoidance of social interactions. During social-defeat learning, 38 adults learned to associate 9 virtual peers with an increasing probability of receiving negative evaluations. Additionally, 1 virtual peer was associated with positive evaluations. Next, in an approach-avoidance task with social-evaluative threat, 1 peer associated with negative evaluations was presented alongside the peer associated with positive evaluations. Approaching peers produced a positive or a probabilistic negative evaluation, while avoiding peers prevented a negative evaluation (and forfeited a positive evaluation). In an approach-avoidance task with social aggression, virtual peers gave and took money away from participants. Escalating social-evaluative threat and aggression increased avoidance, ratings of feeling threatened and threat expectancy and decreased ratings of peer favorableness. These findings underscore the potential of coupling social defeat and approach-avoidance paradigms for translational research on the neurobehavioral mechanisms of social approach-avoidance decision-making and anxiety.

Individual differences in costly fearful avoidance and the relation to psychophysiology

Excessive avoidance behaviour is a cardinal symptom of anxiety disorders. Avoidance is not only associated with the benefits of avoiding threats, but also with the costs of missing out on rewards upon exploration. Psychological and psychophysiological mechanisms contributing to these costly avoidance decisions in prospect of mixed outcomes remain unclear. We developed a novel Fearful Avoidance Task (FAT) that resembles characteristics of real-life approach-avoidance conflicts, enabling to disentangle reward and threat effects. Using the FAT, we investigated individual differences in avoidance behaviour and anticipatory psychophysiological states (i.e. startle reflex and skin conductance) in a relatively large sample of 343 (78 females) participants. Avoidance under acute threat of shock depends on a trade-off between perceived reward and threat. Both increased startle and skin conductance in the absence of threat of shock emerged as predictors of increased avoidance (potentially indicative of fear generalization). Increased avoidance was also associated with female sex and trait anxiety, dependent on reward and threat levels. Our findings highlight distinct possible predictors of heightened avoidance and add to mechanistic understanding of how individual propensity for costly avoidance may emerge. Distinct avoidance typologies based on differential reward and threat sensitivities may have different mechanistic origins and thereby could benefit from different treatment strategies.

Arbitration of Approach-Avoidance Conflict by Ventral Hippocampus

When environmental cues or stimuli that represent both rewarding and aversive outcomes are presented, complex computations must be made in order to determine whether approach or avoidance is the better behavioral strategy. In many neuropsychiatric illnesses these computations can be skewed. In some instances, circumstances that may normally warrant avoidance instead promote approach, thus producing compulsive-like behavioral strategies that are inflexible in response to new or conflicting information. Alternatively, high sensitivity to aversion or low sensitivity to reward can result in the failure to achieve goals and loss of resilience that characterizes depressive disorders. Increases in compulsive-like behavior have been found to be associated with disrupted signaling in regions that regulate response to conflicting stimuli, including the hippocampus. Classic behavioral inhibition theories of hippocampus function in anxiety suggest that the hippocampus blocks aberrant behavior in response to anxiety related cues or stimuli. The hippocampus may act to block approach in the face of conflicting stimuli. Dysregulations of hippocampal function, as may be present in neuropsychiatric disorders, may therefore promote aberrant approach behavior. The ventral hippocampus (vHPC) subregion is key for coordinating this approach/avoidance conflict resolution, likely through its participation with cortico-striatal and mesolimbic circuits. We revisit Gray's behavioral inhibition theory of HPC function, first posited in the 1980s, and interpret in the context of new knowledge on vHPC function gained through modern technology. Taken together with the extant, classical literature on hippocampal function, we propose that these new findings suggest that vHPC circuits balance behavioral response to conflicting stimuli in a manner that is both state- and context-dependent and, further, that disruption of specific vHPC circuits tips the balance in favor of biased approach or avoidance behavioral strategies.

Molecular and neurocircuitry mechanisms of social avoidance

Humans and animals live in social relationships shaped by actions of approach and avoidance. Both are crucial for normal physical and mental development, survival, and well-being. Active withdrawal from social interaction is often induced by the perception of threat or unpleasant social experience and relies on adaptive mechanisms within neuronal networks associated with social behavior. In case of confrontation with overly strong or persistent stressors and/or dispositions of the affected individual, maladaptive processes in the neuronal circuitries and its associated transmitters and modulators lead to pathological social avoidance. This review focuses on active, fear-driven social avoidance, affected circuits within the mesocorticolimbic system and associated regions and a selection of molecular modulators that promise translational potential. A comprehensive review of human research in this field is followed by a reflection on animal studies that offer a broader and often more detailed range of analytical methodologies. Finally, we take a critical look at challenges that could be addressed in future translational research on fear-driven social avoidance.

Hippocampal Representation of Threat Features and Behavior in a Human Approach-Avoidance Conflict Anxiety Task

Decisions under threat are crucial to survival and require integration of distinct situational features, such as threat probability and magnitude. Recent evidence from human lesion and neuroimaging studies implicated anterior hippocampus (aHC) and amygdala in approach-avoidance decisions under threat, and linked their integrity to cautious behavior. Here we sought to elucidate how threat dimensions and behavior are represented in these structures. Twenty human participants (11 female) completed an approach-avoidance conflict task during high-resolution fMRI. Participants could gather tokens under threat of capture by a virtual predator, which would lead to token loss. Threat probability (predator wake-up rate) and magnitude (amount of token loss) varied on each trial. To disentangle effects of threat features, and ensuing behavior, we performed a multifold parametric analysis. We found that high threat probability and magnitude related to BOLD signal in left aHC/entorhinal cortex. However, BOLD signal in this region was better explained by avoidance behavior than by these threat features. A priori ROI analysis confirmed the relation of aHC BOLD response with avoidance. Exploratory subfield analysis revealed that this relation was specific to anterior CA2/3 but not CA1. Left lateral amygdala responded to low and high, but not intermediate, threat probability. Our results suggest that aHC BOLD signal is better explained by avoidance behavior than by threat features in approach-avoidance conflict. Rather than representing threat features in a monotonic manner, it appears that aHC may compute approach-avoidance decisions based on integration of situational threat features represented in other neural structures.SIGNIFICANCE STATEMENT An effective threat anticipation system is crucial to survival across species. Natural threats, however, are diverse and have distinct features. To be able to adapt to different modes of danger, the brain needs to recognize these features, integrate them, and use them to modify behavior. Our results disclose the human anterior hippocampus as a likely arbiter of approach-avoidance decisions harnessing compound environmental information while partially replicating previous findings and blending into recent efforts to illuminate the neural basis of approach-avoidance conflict in humans.

BNST transient activity associates with approach behavior in a stressful environment and is modulated by the parabrachial nucleus

Studies demonstrate a role for the bed nucleus of the stria terminalis (BNST) in modulating affective behavior and stress-reward integration. To explore the dynamic nature of in vivo BNST activity associated with anxiety-like behavior in a stress-inducing context, we utilized fiber photometry and detected BNST calcium transients in mice during the novelty-suppressed feeding task (NSFT). Phasic BNST activity emerged time-locked to novel object or food pellet approach during NSFT. The parabrachial nucleus (PBN) has a large input to the BNST and is thought to function as a danger signal, in arousal responses and in feeding behavior. To explore a potential role for the PBN as a contributor to BNST activity in NSFT, we investigated whether chemogenetic regulation of PBN activity altered the dynamic BNST response synchronized to NSFT approach behavior. We found that activation of the hM3D(G_q) DREADD in the PBN enhanced the observed transient signal in the BNST synchronized to the consummatory food approach, and was associated at the behavioral level with increased latency to consume food. Because the PBN has multiple efferent pathways, we next used a transsynaptic anterograde AAV-based strategy to express hM3D(G_q) specifically in PBN-innervated BNST (BNST^PBN) neurons in male and female mice. Activation of hM3D(G_q) in these BNST^PBN neurons increased latency to consume food in female, but not male mice. To further explore the population of BNST neurons contributing to phasic BNST activity associated with NSFT, we turned to PKCδ neurons in BNST. BNST(PKCδ) neurons are implicated in stress and food-related behavior, and we previously found that the expression of this kinase is regulated in the BNST by stress in a sex-dependent manner. Here, we demonstrate close apposition of CGRP, a marker of PBN terminals, adjacent to BNST(PKCδ) cells. Finally, we find that PKCδ-expressing BNST cells exhibit a large transient signal synchronized to the consummatory food approach similar to that seen with bulk BNST activity measures. Taken together these data demonstrate phasic BNST activity at a global and cell-specific level that is driven in part by PBN activity at the time of NSFT consummatory approach behavior.

Predictors of risky foraging behaviour in healthy young people

During adolescence and early adulthood, learning when to avoid threats and when to pursue rewards becomes crucial. Using a risky foraging task, we investigated individual differences in this dynamic across 781 individuals aged 14-24 years who were split into a hypothesis-generating discovery sample and a hold-out confirmation sample. Sex was the most important predictor of cautious behaviour and performance. Males earned one standard deviation (or 20%) more reward than females, collected more reward when there was little to lose and reduced foraging to the same level as females when potential losses became high. Other independent predictors of cautiousness and performance were self-reported daringness, IQ and self-reported cognitive complexity. We found no evidence for an impact of age or maturation. Thus, maleness, a high IQ or self-reported cognitive complexity, and self-reported daringness predicted greater success in risky foraging, possibly due to better exploitation of low-risk opportunities in high-risk environments.