Toward an integrative perspective on the neural mechanisms underlying persistent maladaptive behaviors

Decision neuroscience and neuroeconomics: Recent progress and ongoing challenges

In the past decade, decision neuroscience and neuroeconomics have developed many new insights in the study of decision making. This review provides an overarching update on how the field has advanced in this time period. Although our initial review a decade ago outlined several theoretical, conceptual, methodological, empirical, and practical challenges, there has only been limited progress in resolving these challenges. We summarize significant trends in decision neuroscience through the lens of the challenges outlined for the field and review examples where the field has had significant, direct, and applicable impacts across economics and psychology. First, we review progress on topics including reward learning, explore-exploit decisions, risk and ambiguity, intertemporal choice, and valuation. Next, we assess the impacts of emotion, social rewards, and social context on decision making. Then, we follow up with how individual differences impact choices and new exciting developments in the prediction and neuroforecasting of future decisions. Finally, we consider how trends in decision-neuroscience research reflect progress toward resolving past challenges, discuss new and exciting applications of recent research, and identify new challenges for the field. This article is categorized under: Psychology > Reasoning and Decision Making Psychology > Emotion and Motivation.

Neuroadaptations and TGF-β signaling: emerging role in models of neuropsychiatric disorders

Neuropsychiatric diseases are manifested by maladaptive behavioral plasticity. Despite the greater understanding of the neuroplasticity underlying behavioral adaptations, pinpointing precise cellular mediators has remained elusive. This has stymied the development of pharmacological interventions to combat these disorders both at the level of progression and relapse. With increased knowledge on the putative role of the transforming growth factor (TGF- β) family of proteins in mediating diverse neuroadaptations, the influence of TGF-β signaling in regulating maladaptive cellular and behavioral plasticity underlying neuropsychiatric disorders is being increasingly elucidated. The current review is focused on what is currently known about the TGF-β signaling in the central nervous system in mediating cellular and behavioral plasticity related to neuropsychiatric manifestations.

Repetitive transcranial magnetic stimulation as a potential treatment approach for cannabis use disorder

The expanding legalization of cannabis across the United States is associated with increases in cannabis use, and accordingly, an increase in the number and severity of individuals with cannabis use disorder (CUD). The lack of FDA-approved pharmacotherapies and modest efficacy of psychotherapeutic interventions means that many of those who seek treatment for CUD relapse within the first few months. Consequently, there is a pressing need for innovative, evidence-based treatment development for CUD. Preliminary evidence suggests that repetitive transcranial magnetic stimulation (rTMS) may be a novel, non-invasive therapeutic neuromodulation tool for the treatment of a variety of substance use disorders (SUDs), including recently receiving FDA clearance (August 2020) for use as a smoking cessation aid in tobacco cigarette smokers. However, the potential of rTMS for CUD has not yet been reviewed. This paper provides a primer on therapeutic neuromodulation techniques for SUDs, with a particular focus on reviewing the current status of rTMS research in people who use cannabis. Lastly, future directions are proposed for rTMS treatment development in CUD, with suggestions for study design parameters and clinical endpoints based on current gold-standard practices for therapeutic neuromodulation research.

Family history of depression is associated with alterations in task-dependent connectivity between the cerebellum and ventromedial prefrontal cortex

BACKGROUND

A family history of major depressive disorder (MDD) increases the likelihood of a future depressive episode, which itself poses a significant risk for disruptions in reward processing and social cognition. However, it is unclear whether a family history of MDD is associated with alterations in the neural circuitry underlying reward processing and social cognition.

METHODS

We subdivided 279 participants from the Human Connectome Project into three groups: 71 with a lifetime history of MDD, 103 with a family history (FH) of MDD, and 105 healthy controls (HCs). We then evaluated task-based functional magnetic resonance imaging data on a social cognition and a reward processing task and found a region of the ventromedial prefrontal cortex (vmPFC) that responded to both tasks, independent of the group. To investigate whether the vmPFC shows alterations in functional connectivity between groups, we conducted psychophysiological interaction analyses using the vmPFC as a seed region.

RESULTS

We found that FH (relative to HC) was associated with increased sadness scores, and MDD (relative to both FH and HC) was associated with increased sadness and MDD symptoms. Additionally, the FH group had increased vmPFC functional connectivity within the nucleus accumbens, left dorsolateral PFC, and subregions of the cerebellum relative to HC during the social cognition task.

CONCLUSIONS

These findings suggest that aberrant neural mechanisms among those with a familial risk of MDD may underlie vulnerability to altered social cognition.

The Role of Social Reward and Corticostriatal Connectivity in Substance Use

This report describes an ongoing R03 grant that explores the links between trait reward sensitivity, substance use, and neural responses to social and nonsocial reward. Although previous research has shown that trait reward sensitivity and neural responses to reward are linked to substance use, whether this relationship is impacted by how people process social stimuli remains unclear. We are investigating these questions via a neuroimaging study with college-aged participants, using individual difference measures that examine the relation between substance use, social context, and trait reward sensitivity with tasks that measure reward anticipation, strategic behavior, social reward consumption, and the influence of social context on reward processing. We predict that substance use will be tied to distinct patterns of striatal dysfunction. Specifically, reward hyposensitive individuals will exhibit blunted striatal responses to social and non-social reward and enhanced connectivity with the orbitofrontal cortex; in contrast, reward hypersensitive individuals will exhibit enhanced striatal responses to social and non-social reward and blunted connectivity with the orbitofrontal cortex. We also will examine the relation between self-reported reward sensitivity, substance use, and striatal responses to social reward and social context. We predict that individuals reporting the highest levels of substance use will show exaggerated striatal responses to social reward and social context, independent of self-reported reward sensitivity. Examining corticostriatal responses to reward processing will help characterize the relation between reward sensitivity, social context and substance use while providing a foundation for understanding risk factors and isolating neurocognitive mechanisms that may be targeted to increase the efficacy of interventions.

Obesity is associated with reduced orbitofrontal cortex volume: A coordinate-based meta-analysis

Neural models of obesity vary in their focus upon prefrontal and striatal differences. Animal and human studies suggest that differential functioning of the orbitofrontal cortex is associated with obesity. However, meta-analyses of functional neuroimaging studies have not found a clear relationship between the orbitofrontal cortex and obesity. Meta-analyses of structural imaging studies of obesity have shown mixed findings with regards to an association with reduced orbitofrontal cortex gray matter volume. To clarify these findings, we conducted a meta-analysis of 25 voxel-based morphometry studies, and found that greater body mass index is associated with decreased gray matter volume in the right orbitofrontal cortex (Brodmanns' areas 10 and 11), where family-wise corrected p < .05, N = 7,612. Use of the right orbitofrontal cortex as a seed in a Neurosynth Network Coactivation analysis showed that this region is associated with activity in the left frontal medial cortex, left temporal lobe, right precuneus cortex, posterior division of the left middle temporal gyrus, and right frontal pole. When Neurosynth Network Coactivation results were submitted as regions of interest in the Human Connectome Project data, we found that greater body mass index was associated with greater activity in left frontal medial cortex response to the Gambling Task, where p < .05, although this did not survive Bonferroni-correction. Our findings highlight the importance of the orbitofrontal cortex structure and functioning in neural models of obesity. Exploratory analyses suggest more studies are needed that examine the functional significance of reduced orbitofrontal cortex gray matter volume in obesity, and the effect of age and weight changes on this relationship using longitudinal designs.

Know safety, no fear

Every day we are bombarded by stimuli that must be assessed for their potential for harm or benefit. Once a stimulus is learned to predict harm, it can elicit fear responses. Such learning can last a lifetime but is not always beneficial for an organism. For an organism to thrive in its environment, it must know when to engage in defensive, avoidance behaviors and when to engage in non-defensive, approach behaviors. Fear should be suppressed in situations that are not dangerous: when a novel, innocuous stimulus resembles a feared stimulus, when a feared stimulus no longer predicts harm, or when there is an option to avoid harm. A cardinal feature of anxiety disorders is the inability to suppress fear adaptively. In PTSD, for instance, learned fear is expressed inappropriately in safe situations and is resistant to extinction. In this review, we discuss mechanisms of suppressing fear responses during stimulus discrimination, fear extinction, and active avoidance, focusing on the well-studied tripartite circuit consisting of the amygdala, medial prefrontal cortex and hippocampus.

The study of active avoidance: A platform for discussion

Traditional active avoidance tasks have advanced the field of aversive learning and memory for decades and are useful for studying simple avoidance responses in isolation; however, these tasks have limited clinical relevance because they do not model several key features of clinical avoidance. In contrast, platform-mediated avoidance (PMA) more closely resembles clinical avoidance because the response i) is associated with an unambiguous safe location, ii) is not associated with an artificial termination of the warning signal, and iii) is associated with a decision-based appetitive cost. Recent findings on the neuronal circuits of PMA have confirmed that amygdala-striatal circuits are essential for avoidance. In PMA, however, the prelimbic cortex facilitates the avoidance response early during the warning signal, perhaps through disinhibition of the striatum. Future studies on avoidance should account for additional factors such as sex differences and social interactions that will advance our understanding of maladaptive avoidance contributing to neuropsychiatric disorders.

Meta-analysis of reward processing in major depressive disorder reveals distinct abnormalities within the reward circuit

Many neuroimaging studies have investigated reward processing dysfunction in major depressive disorder. These studies have led to the common idea that major depressive disorder is associated with blunted responses within the reward circuit, particularly in the ventral striatum. Yet, the link between major depressive disorder and reward-related responses in other regions remains inconclusive, thus limiting our understanding of the pathophysiology of major depressive disorder. To address this issue, we performed a coordinate-based meta-analysis of 41 whole-brain neuroimaging studies encompassing reward-related responses from a total of 794 patients with major depressive disorder and 803 healthy controls. Our findings argue against the common idea that major depressive disorder is primarily linked to deficits within the reward system. Instead, our results demonstrate that major depressive disorder is associated with opposing abnormalities in the reward circuit: hypo-responses in the ventral striatum and hyper-responses in the orbitofrontal cortex. The current findings suggest that dysregulated corticostriatal connectivity may underlie reward-processing abnormalities in major depressive disorder, providing an empirical foundation for a more refined understanding of abnormalities in the reward circuitry in major depressive disorder.

Holistic Reinforcement Learning: The Role of Structure and Attention

Compact representations of the environment allow humans to behave efficiently in a complex world. Reinforcement learning models capture many behavioral and neural effects but do not explain recent findings showing that structure in the environment influences learning. In parallel, Bayesian cognitive models predict how humans learn structured knowledge but do not have a clear neurobiological implementation. We propose an integration of these two model classes in which structured knowledge learned via approximate Bayesian inference acts as a source of selective attention. In turn, selective attention biases reinforcement learning towards relevant dimensions of the environment. An understanding of structure learning will help to resolve the fundamental challenge in decision science: explaining why people make the decisions they do.