Manipulating Reward Sensitivity Using Reward Circuit-Targeted Transcranial Magnetic Stimulation

A meta-analysis of electrophysiological biomarkers of reward and error monitoring in substance misuse

Substance use disorders are characterized by marked changes in reward and error processing. The primary objective of this meta-analysis was to estimate effect sizes for the reward positivity (RewP) and error-related negativity (ERN), two event-related potential indicators of outcome monitoring, in substance users compared to controls. The secondary objective was to test for moderation by demographic, substance type, and EEG experiment parameters. Final PubMed searches were performed in August 2023. Inclusion criteria were substance use disorder/dependence or validated self-report of substance misuse, RewP/ERN means available, healthy control comparison group, non-acute drug study, peer-reviewed journal, English language, and human participants. Selection bias was tested through modified Egger's regression and exploratory 3-parameter selection model tests. The RewP results (19 studies, 1641 participants) did not support an overall effect (Hedges' g = 0.07, 95% CI [-0.44, 0.58], p = .777) and nor effect of any moderators. The ERN results (20 studies, 1022 participants) indicated no significant overall effect (g = 0.41, 95%CI [-0.05, 0.88]). Subgroup analyses indicated that cocaine users had a blunted ERN compared to controls (g = 1.12, 95%CI [0.77, 1.47]). There was limited evidence for publication/small study bias. Although the results indicate a potential dissociation between substance types, this meta-analysis revealed the need for additional research on the RewP/ERN in substance using populations and for better designed experiments that adequately address research questions.

Development of a multivariate prediction model for antidepressant resistant depression using reward-related predictors

Introduction

Individuals with depression who do not respond to two or more courses of serotonergic antidepressants tend to have greater deficits in reward processing and greater internalizing symptoms, yet there is no validated self-report method to determine the likelihood of treatment resistance based on these symptom dimensions.

Methods

This online case-control study leverages machine learning techniques to identify differences in self-reported anhedonia and internalizing symptom profiles of antidepressant non-responders compared to responders and healthy controls, as an initial proof-of-concept for relating these indicators to medication responsiveness. Random forest classifiers were used to identify a subset from a set of 24 reward predictors that distinguished among serotonergic medication resistant, non-resistant, and non-depressed individuals recruited online (N = 393). Feature selection was implemented to refine model prediction and improve interpretability.

Results

Accuracies for full predictor models ranged from .54 to .71, while feature selected models retained 3-5 predictors and generated accuracies of .42 to .70. Several models performed significantly above chance. Sensitivity for non-responders was greatest after feature selection when compared to only responders, reaching .82 with 3 predictors. The predictors retained from feature selection were then explored using factor analysis at the item level and cluster analysis of the full data to determine empirically driven data structures.

Discussion

Non-responders displayed 3 distinct symptom profiles along internalizing dimensions of anxiety, anhedonia, motivation, and cognitive function. Results should be replicated in a prospective cohort sample for predictive validity; however, this study demonstrates validity for using a limited anhedonia and internalizing self-report instrument for distinguishing between antidepressant resistant and responsive depression profiles.

The Stress Phenotyping Framework: A multidisciplinary biobehavioral approach for assessing and therapeutically targeting maladaptive stress physiology

Although dysregulated stress biology is becoming increasingly recognized as a key driver of lifelong disparities in chronic disease, we presently have no validated biomarkers of toxic stress physiology; no biological, behavioral, or cognitive treatments specifically focused on normalizing toxic stress processes; and no agreed-upon guidelines for treating stress in the clinic or evaluating the efficacy of interventions that seek to reduce toxic stress and improve human functioning. We address these critical issues by (a) systematically describing key systems and mechanisms that are dysregulated by stress; (b) summarizing indicators, biomarkers, and instruments for assessing stress response systems; and (c) highlighting therapeutic approaches that can be used to normalize stress-related biopsychosocial functioning. We also present a novel multidisciplinary Stress Phenotyping Framework that can bring stress researchers and clinicians one step closer to realizing the goal of using precision medicine-based approaches to prevent and treat stress-associated health problems.

Non-invasive stimulation reveals ventromedial prefrontal cortex function in reward prediction and reward processing

Introduction

Studies suggest an involvement of the ventromedial prefrontal cortex (vmPFC) in reward prediction and processing, with reward-based learning relying on neural activity in response to unpredicted rewards or non-rewards (reward prediction error, RPE). Here, we investigated the causal role of the vmPFC in reward prediction, processing, and RPE signaling by transiently modulating vmPFC excitability using transcranial Direct Current Stimulation (tDCS).

Methods

Participants received excitatory or inhibitory tDCS of the vmPFC before completing a gambling task, in which cues signaled varying reward probabilities and symbols provided feedback on monetary gain or loss. We collected self-reported and evaluative data on reward prediction and processing. In addition, cue-locked and feedback-locked neural activity via magnetoencephalography (MEG) and pupil diameter using eye-tracking were recorded.

Results

Regarding reward prediction (cue-locked analysis), vmPFC excitation (versus inhibition) resulted in increased prefrontal activation preceding loss predictions, increased pupil dilations, and tentatively more optimistic reward predictions. Regarding reward processing (feedback-locked analysis), vmPFC excitation (versus inhibition) resulted in increased pleasantness, increased vmPFC activation, especially for unpredicted gains (i.e., gain RPEs), decreased perseveration in choice behavior after negative feedback, and increased pupil dilations.

Discussion

Our results support the pivotal role of the vmPFC in reward prediction and processing. Furthermore, they suggest that transient vmPFC excitation via tDCS induces a positive bias into the reward system that leads to enhanced anticipation and appraisal of positive outcomes and improves reward-based learning, as indicated by greater behavioral flexibility after losses and unpredicted outcomes, which can be seen as an improved reaction to the received feedback.

The Association Between Prenatal Maternal Stress and Adolescent Affective Outcomes is Mediated by Childhood Maltreatment and Adolescent Behavioral Inhibition System Sensitivity

Prenatal maternal stress is linked to offspring outcomes; however, there is little research on adolescents, behavioral, transdiagnostic outcomes, or the mechanisms through which relations operate. We examined, in N = 268 adolescents (Mage = 15.31 years; SD = 1.063; 57.8% boys) whether prenatal maternal stress is associated with adolescent affective outcomes; whether this association is mediated, serially, by childhood home atmosphere and adolescent behavioral inhibition system (BIS) sensitivity; and whether mediational effects are moderated by adolescent attention-deficit/hyperactivity disorder or maternal internalizing symptomology. Prenatal maternal daily stress and major life events were associated with adolescent outcomes through childhood negative atmosphere/neglect and BIS sensitivity, with no evidence of moderation. Results have implications regarding the effect of prenatal maternal stress on offspring outcomes and regarding corresponding sensitive periods.

A guide for concurrent TMS-fMRI to investigate functional brain networks

Transcranial Magnetic Stimulation (TMS) allows for the direct activation of neurons in the human neocortex and has proven to be fundamental for causal hypothesis testing in cognitive neuroscience. By administering TMS concurrently with functional Magnetic Resonance Imaging (fMRI), the effect of cortical TMS on activity in distant cortical and subcortical structures can be quantified by varying the levels of TMS output intensity. However, TMS generates significant fluctuations in the fMRI time series, and their complex interaction warrants caution before interpreting findings. We present the methodological challenges of concurrent TMS-fMRI and a guide to minimize induced artifacts in experimental design and post-processing. Our study targeted two frontal-striatal circuits: primary motor cortex (M1) projections to the putamen and lateral prefrontal cortex (PFC) projections to the caudate in healthy human participants. We found that TMS parametrically increased the BOLD signal in the targeted region and subcortical projections as a function of stimulation intensity. Together, this work provides practical steps to overcome common challenges with concurrent TMS-fMRI and demonstrates how TMS-fMRI can be used to investigate functional brain networks.