Blunted Frontostriatal Blood Oxygen Level-Dependent Signals Predict Stimulant and Marijuana Use

Candidate biomarkers in psychiatric disorders: state of the field

The field of psychiatry is hampered by a lack of robust, reliable and valid biomarkers that can aid in objectively diagnosing patients and providing individualized treatment recommendations. Here we review and critically evaluate the evidence for the most promising biomarkers in the psychiatric neuroscience literature for autism spectrum disorder, schizophrenia, anxiety disorders and post-traumatic stress disorder, major depression and bipolar disorder, and substance use disorders. Candidate biomarkers reviewed include various neuroimaging, genetic, molecular and peripheral assays, for the purposes of determining susceptibility or presence of illness, and predicting treatment response or safety. This review highlights a critical gap in the biomarker validation process. An enormous societal investment over the past 50 years has identified numerous candidate biomarkers. However, to date, the overwhelming majority of these measures have not been proven sufficiently reliable, valid and useful to be adopted clinically. It is time to consider whether strategic investments might break this impasse, focusing on a limited number of promising candidates to advance through a process of definitive testing for a specific indication. Some promising candidates for definitive testing include the N170 signal, an event-related brain potential measured using electroencephalography, for subgroup identification within autism spectrum disorder; striatal resting-state functional magnetic resonance imaging (fMRI) measures, such as the striatal connectivity index (SCI) and the functional striatal abnormalities (FSA) index, for prediction of treatment response in schizophrenia; error-related negativity (ERN), an electrophysiological index, for prediction of first onset of generalized anxiety disorder, and resting-state and structural brain connectomic measures for prediction of treatment response in social anxiety disorder. Alternate forms of classification may be useful for conceptualizing and testing potential biomarkers. Collaborative efforts allowing the inclusion of biosystems beyond genetics and neuroimaging are needed, and online remote acquisition of selected measures in a naturalistic setting using mobile health tools may significantly advance the field. Setting specific benchmarks for well-defined target application, along with development of appropriate funding and partnership mechanisms, would also be crucial. Finally, it should never be forgotten that, for a biomarker to be actionable, it will need to be clinically predictive at the individual level and viable in clinical settings.

A Systematic Review on Common and Distinct Neural Correlates of Risk-taking in Substance-related and Non-substance Related Addictions

Both substance-related as well as non-substance-related addictions may include recurrent engagement in risky actions despite adverse outcomes. We here apply a unified approach and review task-based neuroimaging studies on substance-related (SRAs) and non-substance related addictions (NSRAs) to examine commonalities and differences in neural correlates of risk-taking in these two addiction types. To this end, we conducted a systematic review adhering to the PRISMA guidelines. Two databases were searched with predefined search terms to identify neuroimaging studies on risk-taking tasks in individuals with addiction disorders. In total, 19 studies on SRAs (comprising a total of 648 individuals with SRAs) and 10 studies on NSRAs (comprising a total of 187 individuals with NSRAs) were included. Risk-related brain activation in SRAs and NSRAs was summarized individually and subsequently compared to each other. Results suggest convergent altered risk-related neural processes, including hyperactivity in the OFC and the striatum. As characteristic for both addiction types, these brain regions may represent an underlying mechanism of suboptimal decision-making. In contrast, decreased DLPFC activity may be specific to SRAs and decreased IFG activity could only be identified for NSRAs. The precuneus and posterior cingulate show elevated activity in SRAs, while findings regarding these areas were mixed in NSRAs. Additional scarce evidence suggests decreased ventral ACC activity and increased dorsal ACC activity in both addiction types. Associations between identified activation patterns with drug use severity underpin the clinical relevance of these findings. However, this exploratory evidence should be interpreted with caution and should be regarded as preliminary. Future research is needed to evaluate the findings gathered by this review.

Unlocking the reinforcement-learning circuits of the orbitofrontal cortex

Neuroimaging studies have consistently identified the orbitofrontal cortex (OFC) as being affected in individuals with neuropsychiatric disorders. OFC dysfunction has been proposed to be a key mechanism by which decision-making impairments emerge in diverse clinical populations, and recent studies employing computational approaches have revealed that distinct reinforcement-learning mechanisms of decision-making differ among diagnoses. In this perspective, we propose that these computational differences may be linked to select OFC circuits and present our recent work that has used a neurocomputational approach to understand the biobehavioral mechanisms of addiction pathology in rodent models. We describe how combining translationally analogous behavioral paradigms with reinforcement-learning algorithms and sophisticated neuroscience techniques in animals can provide critical insights into OFC pathology in biobehavioral disorders. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

The Neuroscience of Drug Reward and Addiction

Drug consumption is driven by a drug's pharmacological effects, which are experienced as rewarding, and is influenced by genetic, developmental, and psychosocial factors that mediate drug accessibility, norms, and social support systems or lack thereof. The reinforcing effects of drugs mostly depend on dopamine signaling in the nucleus accumbens, and chronic drug exposure triggers glutamatergic-mediated neuroadaptations in dopamine striato-thalamo-cortical (predominantly in prefrontal cortical regions including orbitofrontal cortex and anterior cingulate cortex) and limbic pathways (amygdala and hippocampus) that, in vulnerable individuals, can result in addiction. In parallel, changes in the extended amygdala result in negative emotional states that perpetuate drug taking as an attempt to temporarily alleviate them. Counterintuitively, in the addicted person, the actual drug consumption is associated with an attenuated dopamine increase in brain reward regions, which might contribute to drug-taking behavior to compensate for the difference between the magnitude of the expected reward triggered by the conditioning to drug cues and the actual experience of it. Combined, these effects result in an enhanced motivation to "seek the drug" (energized by dopamine increases triggered by drug cues) and an impaired prefrontal top-down self-regulation that favors compulsive drug-taking against the backdrop of negative emotionality and an enhanced interoceptive awareness of "drug hunger." Treatment interventions intended to reverse these neuroadaptations show promise as therapeutic approaches for addiction.

What Difference Does it Make? Risk-Taking Behavior in Obesity after a Loss is Associated with Decreased Ventromedial Prefrontal Cortex Activity

Altered activity in decision-making neural circuitry may underlie the maladaptive food choices found in obesity. Here, we aimed to identify the brain regions purportedly underpinning risk-taking behavior in individuals with obesity. Twenty-three adult women with obesity and twenty-three healthy weight controls completed the Risky Gains Task during functional magnetic resonance imaging (fMRI). This task allows participants to choose between a safe option for a small, guaranteed monetary reward and risky options with larger rewards. fMRI analyses comparing losing trials to winning trials found that participants with obesity presented decreased activity in the left anterior insula in comparison to controls (p < 0.05, AlphaSim corrected). Moreover, left insula activation during losses vs. wins was negatively correlated with UPPS-P questionnaire sensation seeking scores. During safe vs. risky trials following a loss, the control group exhibited increased activation in the ventromedial prefrontal cortex (vmPFC) (p < 0.05, AlphaSim corrected) in comparison to the OB group. Moreover, vmPFC response in the obesity group during post-loss trials was negatively correlated with risky choices on the task overall. As a whole, our findings support that diminished tuning of the insula towards interoceptive signals may lead to a lack of input to the vmPFC when weighing the costs and benefits of risky choices.

Psychiatry and developmental psychopathology: Unifying themes and future directions

In the past 35 years, developmental psychopathology has grown into a flourishing discipline that shares a scientific agenda with contemporary psychiatry. In this editorial, which introduces the special issue, we describe the history of developmental psychopathology, including core principles that bridge allied disciplines. These include (1) emphasis on interdisciplinary research, (2) elucidation of multicausal pathways to seemingly single disorders (phenocopies), (3) description of divergent multifinal outcomes from common etiological start points (pathoplasticity), and (4) research conducted across multiple levels of analysis spanning genes to environments. Next, we discuss neurodevelopmental models of psychopathology, and provide selected examples. We emphasize differential neuromaturation of subcortical and cortical neural networks and connectivity, and how both acute and protracted environmental insults can compromise neural structure and function. To date, developmental psychopathology has placed greater emphasis than psychiatry on neuromaturational models of mental illness. However, this gap is closing rapidly as advances in technology render etiopathophysiologies of psychopathology more interrogable. We end with suggestions for future interdisciplinary research, including the need to evaluate measurement invariance across development, and to construct more valid assessment methods where indicated.