Subjective arousal, or feelings of activation and alertness, can dynamically modulate affect, behavior, and cognition. Momentary changes in subjective arousal have typically been assessed with self-report in humans, which may alter those very feelings. Although researchers have traditionally used pupil size as a physiological index of arousal, links between pupil dynamics and momentary changes in subjective arousal remain unclear. Here, we combined continuous pupillometry with repeated self-report probes of changing arousal as individuals engaged in a modified Monetary Incentive Delay task. Across Virtual Reality (N = 28; 12 females, 16 males) and Functional Magnetic Resonance Imaging (N = 27; 15 females, 12 males) studies, tonic and phasic pupil measures jointly predicted subsequent self-reported arousal beyond stated incentive value and at a temporal lag of ∼1.5-3.5 s. Neural activity associated with pupil dynamics further predicted pupil size, self-reported arousal, and behavioral motivation in held-out data. Together, these convergent findings establish pupil size as a temporally precise marker of momentary fluctuations in self-reported arousal.

People must often sustain cognitive effort to achieve important goals. Although current models recognize that subcortical valuation regions are important for initiating such effort, they have not seen them as playing meaningful roles in sustaining effort throughout task performance. Here, we demonstrate that core subcortical valuation regions-the basolateral amygdala (BLA) and nucleus accumbens (NAcc)-contribute to sustaining cognitive effort on a challenging working memory task. First, convergent univariate and multivariate analyses revealed that the BLA and NAcc represented incentive value, cognitive effort demands, or both, during every task period (encoding, maintenance, and probe/response). Second, trial-to-trial fluctuations in BLA/NAcc multivariate value coding predicted both the strength of frontoparietal cortical engagement and behavioral performance. Third, the BLA and NAcc functionally interacted with frontoparietal regions throughout the task, suggesting that they work in a coordinated manner. These findings reveal a continuous and dynamic role for subcortical valuation regions in sustaining cognitive effort.

Vivid images of wildlife can motivate environmental advocacy and charitable giving, yet the mechanisms that drive their broad appeal remain unclear. To investigate how wildlife images influence online behavior, we combined behavioral experiments, neuroimaging data, and large-scale social media engagement data from National Geographic's Instagram. Consistent with findings on charitable giving to humans, activity in brain circuits associated with anticipatory affect (i.e. the nucleus accumbens or NAcc) and value integration (i.e. the medial prefrontal cortex or MPFC) predicted individual liking and donations to depicted wildlife. Further, group MPFC activity forecast aggregate engagement (i.e. likes controlling for followers) with wildlife images on social media. Auxiliary analyses indicated that neural activity in circuits associated with socioemotional processing (i.e. facial salience and mentalizing) correlated with MPFC activity. In a neurally inspired model, these socioemotional features forecast social media engagement in other wildlife images online. Together, these findings imply that neural activity not only forecasts engagement with wildlife imagery on social media but can also inform theoretical models of which wildlife image features most powerfully promote sustainable behavior.

Although charitable aid requests often include multiple salient affective features, their interactive effects on donation behavior and the neuropsychological mechanisms underlying their combined influence remain unclear. In four studies, including six behavioral experiments and one Functional Magnetic Resonance Imaging (fMRI) experiment, we examine how the affective congruence of request features influences giving decisions. Across studies, requests with affectively congruent features, regardless of valence, elicited greater donations. The impact of affective congruence was mediated by increased positive aroused affect experienced by donors. Convergently, at the neural level, congruent requests elicited greater activity in the Nucleus Accumbens (NAcc), a brain region associated with positive aroused affect. Increased NAcc activity subsequently predicted donation decisions, bridging responses to stimulus input and behavioral output. These findings suggest that both positive and negatively valenced charitable requests can effectively increase donations if their salient affective features are congruent through neuro-affective mechanisms that support positive aroused affect. These results contribute to a deeper understanding of how affective congruence in charitable appeals engage neural reward systems to drive prosocial behavior. By identifying the NAcc as a bridge from request stimulus to giving behavior, these data illustrate the intersection of emotion, decision-making, and prosociality at both behavioral and neural levels.

Psychiatric disorders are multifactorial and effective treatments are lacking. Probable contributing factors to the challenges in therapeutic development include the complexity of the human brain and the high polygenicity of psychiatric disorders. Combining well-powered genome-wide and brain-wide genetics and transcriptomics analyses can deepen our understanding of the etiology of psychiatric disorders. Here, we leverage two landmark resources to infer the cell types involved in the etiology of schizophrenia, other psychiatric disorders and informative comparison of brain phenotypes. We found both cortical and subcortical neuronal associations for schizophrenia, bipolar disorder and depression. These cell types included somatostatin interneurons, excitatory neurons from the retrosplenial cortex and eccentric medium spiny-like neurons from the amygdala. In contrast we found T cell and B cell associations with multiple sclerosis and microglial associations with Alzheimer's disease. We provide a framework for a cell-type-based classification system that can lead to drug repurposing or development opportunities and personalized treatments. This work formalizes a data-driven, cellular and molecular model of complex brain disorders.

The strength of a given transcranial magnetic stimulation (TMS) pulse decays rapidly with distance. Male and female bone structure reliably differs by the shape of the frontal bone, mandible, and inion. Given the morphology of these structures constitutes much of the scalp-to-cortex distance (STCD), we hypothesized that females have shorter STCDs and thereby receive stronger TMS electrical field strengths, relative to males. Head models (n = 411; 197 female, 214 male) were constructed from MRIs of healthy participants (ages 18-90). STCD and peak electrical field strength were measured at 50 EEG 10-20 sites (SimNIBSv3.2). Linear models (bootstrapped and Benajamini-Hochberg multiple comparison-corrected) evaluated the influence of sex on STCD and electrical field strength. Females had significantly shorter STCDs at 27/50 sites and stronger TMS electrical fields at 18/50. When normalized by data collected at the motor cortex, females had significantly shorter STCD at 40/49 sites and stronger TMS electrical fields at 29/49 sites. The largest effect size differences were detected at the frontal, temporal, and occipital poles, and the cerebellum. Interestingly, STCD at the motor cortex was not different between sexes, suggesting the motor cortex-based dosing strategies produce unequal electrical fields between sexes. These data provide a mathematically grounded explanation for sex-differences in clinical outcome and may be relevant to other modalities that depend on electromagnetic signals (e.g., EEG, MEG).

To survive and thrive, animals must navigate risk by anticipating and avoiding potential losses while approaching potential gains. Although researchers have leveraged neuroimaging to predict risky choices in humans, consensus on unitary versus distinct underlying neural and psychological mechanisms remains elusive. Across four functional magnetic resonance imaging studies (combined n = 230), we tested univariate and multivariate models predicting trial-by-trial risky gambling choices in an original sample, replicated predictive features in an independent sample, and generalized predictive features to samples playing a different gambling task. Prechoice activity in distinct circuits predicted subsequent risky (i.e. nucleus accumbens [NAcc] and medial prefrontal cortex [MPFC]) versus safe (i.e. anterior insula [AIns]) choices. A triple dissociation analysis distinguished these neural predictors of risky choice from neural activity associated with sensory input and motor output. Prechoice NAcc and MPFC activity was further associated with individuals' preferences for risky choices, while AIns activity was associated with individuals' preferences for safe choices. Finally, prechoice AIns activity in response to risky gambles was associated with lower levels of debt in real life (controlling for demographic, behavioral, and self-report measures). Together, these convergent findings reveal distinct and replicable neural predictors of risky choice, which generalize across analyses, tasks, and individuals.

Accurate forecasts of population-level behavior critically inform institutional choices and public policy. While neuroforecasting research suggests that measurements of group brain activity can improve forecasting accuracy relative to behavior, less is known about how and when brain activity can effectively improve out-of-sample forecasts. We analyzed neural and behavioral data collected in two experiments to forecast choice in more vs. less demographically representative aggregate internet markets in order to test when forecasts based on brain activity generalize better than behavior. In both experiments, while the accuracy of market forecasts based on behavior varied as a function of sample representativeness, market forecasts based on brain activity remained significant regardless of sample representativeness. These findings are consistent with the notion that brain activity associated with early affective responses can generalize across individuals to index aggregate choice more broadly than downstream behavior. Thus, brain activity from limited samples may reveal generalizable components of choice that can improve market forecasts. These findings inform theory regarding which components of individual choice generalize to improve market forecasts and provide insights into mechanisms that underlie the effective application of neuroforecasting.

BackgroundRandomized, placebo-controlled clinical trials (RCTs) employing repetitive transcranial magnetic stimulation (TMS) in the treatment of alcohol use disorder (AUD) have shown promising results. However, the mechanism(s) by which TMS produces improved outcomes in AUD are not established. The goal of these secondary analyses was to assess for longitudinal changes in brain volumes and neurometabolites in the left dorsolateral prefrontal cortex (DLPFC)—the stimulation site—across two published RCTs evaluating intermittent theta burst (iTBS) as an adjunct treatment for AUD.Materials and methodsVeterans with AUD (n = 44) were recruited from a residential treatment program at the VA Palo Alto Health Care System. Participants in this report were in RCTs evaluating the efficacy of iTBS for the treatment of AUD. Across studies, 21 participants were randomized to active iTBS and 23 to sham iTBS (2–3 iTBS active or sham sessions/day), delivered over approximately 2 weeks. Bilateral volumes of the rostral and caudal middle frontal and superior frontal gyri left DLPFC neurometabolites were quantitated pre- and post-iTBS sessions.ResultsOver the 2-week assessment interval, significant volume increases were observed, collapsed across groups, in the bilateral rostral and caudal middle frontal and superior frontal gyri, as well as in the left DLPFC choline-containing compounds. No group (active vs. sham) × time (2-week assessment interval) interactions were apparent for any measure. Preliminary simple effect tests for volumes indicated that the active group demonstrated significant increases in the bilateral rostral and caudal middle frontal and superior frontal gyri, while the sham group only showed significantly increased left superior frontal volume. Preliminary simple effect tests for metabolites indicated that the active group had significant increases in left DLPFC choline-containing and creatine-containing compounds, and sham showed no significant metabolite changes. In the active group, a higher number of iTBS pulses delivered at the target treatment level was significantly associated with greater increases in left DLPFC n-acetylaspartate, glutamate, and gamma-aminobutyric acid.ConclusionThis study provided novel preliminary indications that iTBS promoted adaptive structural and neurometabolic changes in the left DLPFC site of stimulation in those with AUD. Replication of these findings in a larger sample and examination of other neuroimaging-based markers of TMS-induced neurobiological changes are critical to informing modifications of existing TMS protocols to maximize durable positive treatment outcomes in those with AUD.

Persuasive communication in marketing, political, and health domains influences sales, elections, and public health. We present a mega-analysis (a pooled analysis of raw data) of 16 functional MRI datasets (572 participants, 739 messages, and 21,688 experimental trials) assessing the neural correlates of the effectiveness of messages in individual message receivers and at scale (in large groups of message receivers who did not undergo neuroimaging). Existing theories suggest that decision-making is driven by expected rewards and perceived social relevance associated with the expected outcomes of a given choice. Consistent with these theories, we find that (i) brain activity implicated in reward and social processing is associated with message effectiveness in individuals and at scale across diverse domains (e.g. marketing and health campaigns); (ii) exploratory analysis further suggests language, emotion, and sensorimotor processes as pertinent to message effectiveness; and (iii) brain activity provides complementary information on message effectiveness at scale beyond self-reports provided by the same neuroimaging participants. This study offers novel insights into the neurocognitive mechanisms underlying effective messaging, highlights a path toward greater unity and efficiency in persuasion research, and suggests practical intervention targets for message design.

Over a quarter of a century later, most rodent researchers know that specific types of rat Ultrasonic Vocalizations (USVs) appear to index distinct affective states endowed with arousal, value, and motivational force. Few know the story, however, of how we accidentally stumbled upon 50 kilohertz (50 kHz) USVs in the context of rat play by turning the wrong dial on a bat detector, which I recollect here. The tale of that mistake highlights the critical roles of serendipity, preparation, openness, persistence, and a supportive environment in scientific discovery.

Rapidly acting therapeutics like 3,4-methylenedioxymethamphetamine (MDMA) are promising treatments for disorders such as posttraumatic stress disorder (PTSD). However, understanding who benefits most and the underlying neural mechanisms remains a critical gap. Stratifying individuals by neural circuit profiles could help differentiate neural, behavioral, and affective responses to MDMA, enabling personalized treatment strategies. To investigate whether baseline stratification of individuals based on negative affect circuit profiles, particularly in response to nonconscious threat stimuli, can differentiate acute responses to MDMA. This randomized clinical trial, implementing a double-blinded, within-participant, placebo- and baseline-controlled design, was conducted at Stanford University School of Medicine between November 2, 2021, and November 9, 2022, for wave 1 data collection. Participants had used MDMA on at least 2 prior occasions, but not in the past 6 months, and had subthreshold PTSD symptoms and early life trauma but no current psychiatric disorders. Data were analyzed from March 1, 2023, to January 1, 2024. Participants completed 4 visits: 1 baseline session followed by 1 placebo session and 2 MDMA sessions in a randomized order, totaling 64 visits. Baseline functional magnetic resonance imaging (fMRI) assessed the negative affect circuit using a nonconscious threat processing task (NTN). Primary outcomes included activity and connectivity of amygdala and subgenual anterior cingulate cortex (sgACC) defining the negative affect circuit. Secondary outcomes were behavioral measures of implicit threat bias, likability of threat expressions, and affective assessments. Sixteen participants (10 [63%] female; mean [SD] age, 40.8 [7.6] years) were stratified into subgroups with high and low levels of NTN activity in the amygdala (NTNA+ [n = 8] and NTNA− [n = 8], respectively), based on a median split of baseline nonconscious threat-evoked fMRI responses. Following administration of the 120 mg of MDMA vs placebo, the NTNA+ subgroup showed significant reductions in amygdala (contrast estimate [CE], −1.43; 95% CI, −2.60 to −0.27; Cohen d, −1.22; P = .02) and sgACC activity (CE, −1.48; 95% CI, −2.42 to −0.54; Cohen d, −1.56; P = .004), increased sgACC-amygdala connectivity (CE, 0.65; 95% CI, 0.02-1.28; Cohen d, 1.02; P = .04), and increased likability of threat expressions (CE, 14.38; 95% CI, 1.46-27.29; Cohen d, 0.86; P = .03) compared with the NTNA− subgroup. In this randomized clinical trial of MDMA’s acute profiles, 120 mg of MDMA acutely normalized negative affect circuit reactivity in participants stratified by heightened amygdala reactivity at baseline, demonstrating the potential of neuroimaging to identify prospective biomarkers and guide personalized MDMA-based therapies. ClinicalTrials.gov Identifier: NCT04060108

Importance:Rapidly acting therapeutics like 3,4-methylenedioxymethamphetamine (MDMA) are promising treatments for disorders such as posttraumatic stress disorder (PTSD). However, understanding who benefits most and the underlying neural mechanisms remains a critical gap. Stratifying individuals by neural circuit profiles could help differentiate neural, behavioral, and affective responses to MDMA, enabling personalized treatment strategies. Objective:To investigate whether baseline stratification of individuals based on negative affect circuit profiles, particularly in response to nonconscious threat stimuli, can differentiate acute responses to MDMA. Design, Setting, and Participants:This randomized clinical trial, implementing a double-blinded, within-participant, placebo- and baseline-controlled design, was conducted at Stanford University School of Medicine between November 2, 2021, and November 9, 2022, for wave 1 data collection. Participants had used MDMA on at least 2 prior occasions, but not in the past 6 months, and had subthreshold PTSD symptoms and early life trauma but no current psychiatric disorders. Data were analyzed from March 1, 2023, to January 1, 2024. Interventions:Participants completed 4 visits: 1 baseline session followed by 1 placebo session and 2 MDMA sessions in a randomized order, totaling 64 visits. Baseline functional magnetic resonance imaging (fMRI) assessed the negative affect circuit using a nonconscious threat processing task (NTN). Main Outcomes and Measures:Primary outcomes included activity and connectivity of amygdala and subgenual anterior cingulate cortex (sgACC) defining the negative affect circuit. Secondary outcomes were behavioral measures of implicit threat bias, likability of threat expressions, and affective assessments. Results:Sixteen participants (10 [63%] female; mean [SD] age, 40.8 [7.6] years) were stratified into subgroups with high and low levels of NTN activity in the amygdala (NTNA+ [n = 8] and NTNA- [n = 8], respectively), based on a median split of baseline nonconscious threat-evoked fMRI responses. Following administration of the 120 mg of MDMA vs placebo, the NTNA+ subgroup showed significant reductions in amygdala (contrast estimate [CE], -1.43; 95% CI, -2.60 to -0.27; Cohen d, -1.22; P = .02) and sgACC activity (CE, -1.48; 95% CI, -2.42 to -0.54; Cohen d, -1.56; P = .004), increased sgACC-amygdala connectivity (CE, 0.65; 95% CI, 0.02-1.28; Cohen d, 1.02; P = .04), and increased likability of threat expressions (CE, 14.38; 95% CI, 1.46-27.29; Cohen d, 0.86; P = .03) compared with the NTNA- subgroup. Conclusions and Relevance:In this randomized clinical trial of MDMA's acute profiles, 120 mg of MDMA acutely normalized negative affect circuit reactivity in participants stratified by heightened amygdala reactivity at baseline, demonstrating the potential of neuroimaging to identify prospective biomarkers and guide personalized MDMA-based therapies. Trial Registration:ClinicalTrials.gov Identifier: NCT04060108.

Early adolescent drinking onset is linked to myriad negative consequences. Using the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) baseline to year 8 data, this study (1) leveraged best subsets selection and Cox Proportional Hazards regressions to identify the most robust predictors of adolescent first and regular drinking onset, and (2) examined the clinical utility of drinking onset in forecasting later binge drinking and withdrawal effects. Baseline predictors included youth psychodevelopmental characteristics, cognition, brain structure, family, peer, and neighborhood domains. Participants (N=538) were alcohol-naïve at baseline. The strongest predictors of first and regular drinking onset were positive alcohol expectancies (Hazard Ratios [HRs]=1.67–1.87), easy home alcohol access (HRs=1.62–1.67), more parental solicitation (e.g., inquiring about activities; HRs=1.72–1.76), and less parental control and knowledge (HRs=.72–.73). Robust linear regressions showed earlier first and regular drinking onset predicted earlier transition into binge and regular binge drinking (βs=0.57–0.95). Zero-inflated Poisson regressions revealed that delayed first and regular drinking increased the likelihood (Incidence Rate Ratios [IRR]=1.62 and IRR=1.29, respectively) of never experiencing withdrawal. Findings identified behavioral and environmental factors predicting temporal paths to youthful drinking, dissociated first from regular drinking initiation, and revealed adverse sequelae of younger drinking initiation, supporting efforts to delay drinking onset.

BACKGROUND: Patients with stimulant use disorder experience high rates of relapse. While neurobehavioral mechanisms involved in initiating drug use have been studied extensively, less research has focused on relapse.METHODS: To assess motivational processes involved in relapse and diagnosis, we acquired functional magnetic resonance imaging responses to nondrug (monetary) gains and losses in detoxified patients with stimulant use disorder (n = 68) and community control participants (n = 42). In a prospective multimodal design, we combined imaging of brain function, brain structure, and behavior to longitudinally track subsequent risk for relapse.RESULTS: At the 6-month follow-up assessment, 27 patients remained abstinent, but 33 had relapsed. Patients with blunted anterior insula (AIns) activity during loss anticipation were more likely to relapse, an association that remained robust after controlling for potential confounds (i.e., craving, negative mood, years of use, age, and gender). Lower AIns activity during loss anticipation was associated with lower self-reported negative arousal to loss cues and slower behavioral responses to avoid losses, which also independently predicted relapse. Furthermore, AIns activity during loss anticipation was associated with the structural coherence of a tract connecting the AIns and the nucleus accumbens, as was functional connectivity between the AIns and nucleus accumbens during loss processing. However, these neurobehavioral responses did not differ between patients and control participants.CONCLUSIONS: Taken together, the results of the current study show that neurobehavioral markers predicted relapse above and beyond conventional self-report measures, with a cross-validated accuracy of 72.7%. These findings offer convergent multimodal evidence that implicates blunted avoidance motivation in relapse to stimulant use and may therefore guide interventions targeting individuals who are most vulnerable to relapse.

As social media becomes a key channel for news consumption and sharing, proliferating partisan and mainstream news sources must increasingly compete for users’ attention. While affective qualities of news content may promote engagement, it is not clear whether news source bias influences affective content production or virality, or whether any differences have changed over time. We analyzed the sentiment of ~30 million posts (on twitter.com) from 182 U.S. news sources that ranged from extreme left to right bias over the course of a decade (2011-2020). Biased news sources (on both left and right) produced more high arousal negative affective content than balanced sources. High arousal negative content also increased reposting for biased versus balanced sources. The combination of increased prevalence and virality for high arousal negative affective content was not evident for other types of affective content. Over a decade, the virality of high arousal negative affective content also increased, particularly in balanced news sources, and in posts about politics. Together, these findings reveal that high arousal negative affective content may promote the spread of news from biased sources, and conversely imply that sentiment analysis tools might help social media users to counteract these trends.