Tag: Fear and threat response

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Conditioned accumbal dopamine transients forecast individual preference for drug versus natural rewards and compulsive behavior

Nature Neuroscience, Published online: 26 June 2026; doi:10.1038/s41593-026-02331-y

Pascoli et al. show that nucleus accumbens dopamine transients evoked by reward-predictive cues encode subjective reward value in mice, predicting individual preference for drugs over natural rewards and forecasting vulnerability to compulsive drug-seeking behavior.

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Global trends and neurobiological frontiers of manual therapy in sleep disorders: integrating bibliometrics with clinical evidence

BackgroundSleep disorders not only impair nocturnal rest but also significantly compromise daytime functioning, emotional regulation, and overall mental well-being. Beyond conventional pharmacological treatments, manual therapy has emerged as a promising non-pharmacological intervention. Specifically, emerging evidence suggests its benefits may extend to alleviating psychological distress and enhancing mood. This study employs a bibliometric approach to systematically investigate the current status, research hotspots, and future trends of manual therapy for sleep disorders, with an emphasis on its psycho-physiological outcomes.MethodsPublications related to manual therapy for sleep disorders were retrieved from the Web of Science Core Collection (WoSCC). Bibliometric visualizations and analyses were conducted using VOSviewer and CiteSpace. Furthermore, clinical trial records from PubMed were extracted to assess the translational and clinical advancements in this field.ResultsThe analysis included 594 publications originating from 321 institutions across 63 countries. The overall trend demonstrates a consistent annual increase in both publication volume and citation impact, reflecting escalating academic interest. Keyword and literature co-occurrence analyses indicate that exploring neurobiological mechanisms and circadian rhythm regulation are the predominant research frontiers.ConclusionBibliometric evidence indicates that research on manual therapy for sleep disorders is evolving toward multidimensional and interdisciplinary integration. Manual therapy increasingly emerges as a key complementary treatment, exerting therapeutic effects via the regulation of 5-hydroxytryptamine (5-HT) and the Hypothalamic-Pituitary-Adrenal axis (HPA axis). Its safety and efficacy represent distinct advantages; however, future clinical translation necessitates multi-center validation and standardized sham-controlled protocols.
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Functional Outcome Prediction in Young Adults With Mental Health Symptoms Using Machine Learning and Large Language Models: Longitudinal Observational Study

Background: Functional impairments associated with mental health conditions are on the rise. Predicting functional outcomes may improve the targeting of preventive interventions. While prognostic models have primarily focused on psychosis, early recognition services require a transdiagnostic approach. Objective: This study aimed to predict global functioning within a 2-year follow-up using baseline clinical and structural magnetic resonance imaging (MRI) data in a population-based sample of young, help-seeking individuals presenting with affective and anxiety symptoms as well as attention-deficit hyperactivity disorder. Methods: We classified 357 help-seeking individuals aged 18‐35 years recruited from 9 sites as “impaired” (Global Assessment of Functioning [GAF] ≤60; n=228) or “nonimpaired” (GAF>60; n=129) at year 1 and/or year 2 follow-up. GAF classification group status at follow-up was predicted using linear support vector machine (SVM), decision tree, and large language model (LLM) Llama-3 using clinical assessments and/or structural MRI. Leave-one-site-out (SVM) or external sample (LLM) was used for validation. Results: SVM achieved balanced accuracy of 69.2% using clinical features only. Items related to baseline occupational functioning, interpersonal relationships, cognitive functioning, psychotic and affective symptoms, as well as the presence of anxiety disorder, were most predictive. The decision tree further reduced the feature set to 5 predictive items, achieving balanced accuracy of 76.6%. Although amygdala and hippocampal subregions achieved balanced accuracy of 57.1%, structural MRI did not improve the overall prediction. Llama-3 performed comparably well to SVM (balanced accuracy of 72.6%). Conclusions: Machine learning demonstrated good performance in predicting global functioning. Interestingly, the out-of-the-box LLM performed comparably well without being trained or fine-tuned, highlighting the potential of leveraging free-text data for mental health prognosis.
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A computational pipeline for a neurotransmitter-centric analysis of the effects of psychiatric medication on EEG spectral power

IntroductionTraditional pharmaco-electroencephalography (EEG) studies have mainly examined the effects of psychotropic medications at the level of individual drugs or broad drug classes, limiting biological specificity and clinical translation. This study aimed to determine whether modeling EEG spectral power changes according to the engagement of distinct neurotransmitter systems provides a more mechanistic understanding of psychotropic drug effects in a real-world clinical population.MethodsWe analyzed 4,128 EEG sessions from 2,083 patients in the Temple University Hospital EEG Corpus, a large heterogeneous dataset. EEG data were preprocessed and segmented into canonical frequency bands (delta, theta, alpha, beta, and gamma). Psychotropic medication data were systematically extracted and coded at the receptor level for serotonin, dopamine, norepinephrine, histamine, and acetylcholine systems using the Neuroscience-based Nomenclature framework. Receptor profiles were summarized to represent each patient’s overall neurotransmitter engagement (agonistic, neutral, antagonistic, or mixed). Linear mixed-effects models were applied to assess relationships between neurotransmitter profiles and log-transformed spectral power while controlling for electrode location and patient-level variability.ResultsFrequency- and region-specific EEG patterns were identified across neurotransmitter systems. Dopamine antagonists were associated with higher delta and theta power at central electrode locations and lower alpha power at occipital and temporal locations, whereas dopamine agonists were associated with higher delta activity at occipital locations and increased frontal gamma power. Serotonin antagonists showed associations with elevated slow-wave and alpha power, while serotonin agonists were linked to increased frontal alpha, decreased occipital alpha, and enhanced temporal gamma power. Both norepinephrine antagonists and agonists showed positive relationships with delta power, with a broader topographical pattern for antagonists. Theta power was positively associated with norepinephrine antagonists and negatively associated with norepinephrine agonists. Norepinephrine antagonists were related to lower temporal alpha and higher frontal and parietal gamma power. Histamine antagonists and mixed histaminergic agents were associated with lower delta, theta, and alpha power. Acetylcholine antagonists were linked to higher delta, theta, and alpha power across electrode locations.DiscussionModeling psychotropic medication effects on EEG at the neurotransmitter receptor level offers a biologically grounded and clinically relevant improvement over traditional drug class-based approaches. This neurotransmitter-centric framework enhances mechanistic interpretability and may support the development of EEG biomarkers for personalized, mechanism-based psychiatric care.
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CEST MRI reveals nicotine-induced alterations in glutamate-associated molecular connectivity in the mouse brain

IntroductionUnderstanding how neurotransmitter systems organize into large-scale networks is essential for elucidating the mechanisms through which drugs, diseases, and behavioral states alter brain function. Existing imaging modalities such as functional MRI (fMRI) and positron emission tomography (PET) provide measures of hemodynamic and metabolic connectivity, but cannot noninvasively map neurotransmitter-associated networks with high spatial resolution. Herein, we introduce a chemical exchange saturation transfer (CEST) MRI-based framework for mapping glutamate-associated molecular connectivity and apply it to characterize nicotine-induced network reorganization in the mouse brain.MethodsMale C57BL/6 mice underwent dynamic glutamate-weighted CEST (gluCEST) MRI before and after seven days of nicotine exposure. Regional glutamate-weighted CEST time series were extracted from 51 brain regions, and connectivity was evaluated using within-subject temporal correlation and inter-subject covariance analyses.ResultsGraph theory analyses identified four baseline glutamate-associated modules involving frontal-sensorimotor, cortico-hippocampal, intra-hippocampal, and cortico-striatal circuits. Nicotine exposure attenuated these baseline networks in analyses performed without global signal regression (GSR) and with conditional GSR, whereas full GSR reduced the apparent magnitude of these effects. Nicotine also reduced nodal strength in the CA1 and insular cortex. In contrast, nicotine selectively strengthened a thalamo-striato-motor circuit involving the motor cortex, mediodorsal and ventral thalamic nuclei, and caudoputamen. This pattern remained evident even under full GSR. Subject-level covariance analysis confirmed widespread nicotine-induced attenuation of glutamate-associated connectivity and revealed a distinct sensory-limbic module involving the lateral geniculate nucleus, amygdala, and piriform cortex that was selectively disrupted following nicotine exposure.DiscussionThese results demonstrate the feasibility of dynamic gluCEST MRI for mapping glutamate-associated molecular connectivity in vivo and detecting pharmacologically induced network remodeling. This approach provides a noninvasive platform for investigating glutamatergic dysregulation in addiction, neuropsychiatric disorders, and therapeutic response.
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Prevalence and Predictors of Self-Reported Adverse Experiences in Digital Meditation Training: 2 Randomized Controlled Trials

Background: Digital meditation-based interventions (MBIs) reach vast global audiences with millions of active users, yet concerns persist about the frequency and nature of adverse experiences (ie, AExs) occurring during meditation training. Some researchers have argued that AExs are substantially underdetected and reflect iatrogenic harm caused by meditation (ie, adverse effects [AEfs]). Others contend that these experiences largely reflect common stressors that would be experienced without meditation. These competing perspectives underscore the need for further research, particularly in the context of digital MBIs, the most widely used form of meditation training. Objective: This study examined the prevalence, predictors, and subjective evaluations of AExs during a digital MBI and tested whether reported experiences may be caused by meditation practice via comparisons between meditation-exposed and nonexposed participants. Methods: Data were drawn from 2 trials of the Healthy Minds Program. Exploratory study 1 (n=315) consisted of a sample of distressed US undergraduate students to estimate the prevalence of AExs and identify baseline predictors. Preregistered confirmatory study 2 (n=594) sampled distressed US adults from all 50 states to replicate findings from study 1 and to examine participants’ subjective evaluations of AExs. Study 2 additionally compared AEx rates between participants who did and did not complete guided meditations to assess whether AExs could be caused by meditation exposure. Study 3 (n=87) used qualitative methods to analyze study 1 participants’ responses to an open-ended question regarding their strategies for coping with AExs. Results: In studies 1 and 2, 27.9% (88/315) and 10.1% (40/396) of participants, respectively, reported at least one AEx during the study period, with 6.7% (21/315) and 3% (12/396) reporting functional impairment, largely aligning with previous research. Critically, in study 2, rates of AExs did not significantly differ between participants who did and did not complete guided meditations, suggesting that these experiences were not caused by meditation practice. Higher baseline depression, anxiety, loneliness, experiential avoidance, and perceived barriers to meditation predicted more frequent AExs. In studies 1 and 2, 89.8% (79/88) and 90% (36/40) of participants who reported AExs, respectively, indicated that they were glad to have learned to meditate. Qualitative analyses showed that participants used diverse coping strategies, often using skills learned through the Healthy Minds Program. Conclusions: AExs were relatively common but occurred at comparable rates among participants who did and did not meditate, challenging claims that such experiences were caused by meditation practice in distressed individuals. Although a small subset of participants reported some degree of functional impairment, most evaluated their AExs as tolerable and described their overall MBI experience as positive. Together, these findings highlight the importance of distinguishing AExs that likely reflect epiphenomena of preexisting distress or symptoms from iatrogenic harm attributable to MBIs. Trial Registration: Study 1: ClinicalTrials.gov NCT04741529; https://clinicaltrials.gov/study/NCT04741529; Study 2: ClinicalTrials.gov NCT06282523; https://clinicaltrials.gov/study/NCT06282523
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Beyond aesthetic outcomes: psychodermatological benefits of botulinum toxin treatment in the upper facial third. A narrative review

BackgroundBotulinum toxin type A (BoNT-A) is widely used in aesthetic dermatology, particularly for dynamic wrinkles in the upper facial third. Beyond cosmetic effects, BoNT-A may influence emotional processing through the skin-brain axis. This narrative review synthesizes evidence on psychological and psychiatric outcomes of upper facial BoNT-A treatment, with a focus on mechanisms extending beyond aesthetics.MethodsA structured search was conducted in PubMed, Scopus, and Web of Science through January 2026. Search terms included “botulinum toxin,” “upper facial third,” “psychodermatology,” “facial feedback,” “depression,” “anxiety,” and “psychiatric disorders.” Original studies, randomized controlled trials (RCTs), observational studies, systematic reviews, and meta-analyses assessing psychological, psychiatric, or neurobiological outcomes were included.ResultsUpper facial BoNT-A is associated with clinically meaningful reductions in depressive and anxiety symptoms, and improvements in self-perception and social functioning. Inhibition of corrugator and procerus muscles modulates afferent signaling to limbic structures, supporting the facial feedback hypothesis. Neuroimaging evidence demonstrates attenuated amygdala activation after BoNT-A treatment. Psychosocial improvements may reinforce these neurobiological effects. Evidence in bipolar disorder and personality disorders remains limited and methodologically heterogeneous. Caution is advised in patients with body dysmorphic disorder.ConclusionsBoNT-A in the upper facial third provides psychodermatological benefits beyond aesthetics, improving emotional regulation and affective symptoms. It should be considered a complementary intervention within a biopsychosocial framework. Future large-scale RCTs with standardized psychiatric and neurobiological endpoints are warranted.
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Gaming-based program for internet gaming disorder: feasibility and preliminary outcomes of a structured camp program

BackgroundAlthough controlled trials support several psychosocial interventions for adolescent internet gaming disorder (IGD), short, highly structured residential camp formats remain underreported, particularly regarding feasibility, safety, and process data from routine service settings.ObjectiveTo evaluate the feasibility, safety, and short-term entry-to-exit signals of a structured gaming-based camp program using retrospective, de-identified routinely collected service data, with a focus on implementation evidence for a brief, highly structured residential format.MethodsWe conducted a single-group entry-to-exit evaluation of a 7-day structured camp in 12 adolescents aged 11–16 years clinically diagnosed with IGD by psychiatrists using DSM-5 criteria. Entry and exit assessments were organized hierarchically, with the Gaming Disorder Screening Scale (GDSS), the Game Addiction Scale–7 (GAS-7), and the Visual Analog Scale (VAS) craving score as primary outcomes; the Barratt Impulsiveness Scale–11 (BIS-11), Zung Self-Rating Depression Scale (SDS), Zung Self-Rating Anxiety Scale (SAS), Social Avoidance and Distress Scale (SADS), and Chinese version of the Interpersonal Reactivity Index (IRI-C) as supportive secondary outcomes; and camp residential counselor–rated Conners scores and the Stroop task as exploratory external-rating and objective complementary indicators, respectively. Wilcoxon signed-rank tests reported effect size r and Hodges–Lehmann (HL) median difference with 95% CI. Exploratory Spearman correlations examined baseline characteristics and change.ResultsCompletion was 100% (12/12) and attendance 98.6% (142/144), with no serious adverse events; two participants had a brief single-session interruption (coded as non-attendance for that session-person) but completed subsequent sessions and exit assessment. Primary outcomes decreased at exit: GDSS 50.00 (SD 8.32) to 28.67 (SD 8.98), p<0.001, r=0.88, HL −20.5 (95% CI −27.0 to −16.5); GAS-7 21.50 (SD 6.57) to 13.33 (SD 4.44), p=0.003, r=0.89, HL −8.5 (95% CI −12.5 to −6.0); VAS 4.25 (SD 2.63) to 2.75 (SD 2.05), p=0.012, r=0.85, HL −2.0 (95% CI −3.0 to −1.0). High-risk GDSS decreased from 66.7% to 0%, GAS-7 positivity from 58.3% to 8.3%, and moderate-to-severe craving from 58.3% to 25.0%. BIS-11, SDS, and IRI-C showed supportive short-term changes, and counselor-rated Conners scores showed exploratory external-rating changes, whereas SAS and SADS did not. Stroop reaction time decreased and accuracy increased in both conditions, while interference effects did not change significantly. Baseline PSQI correlated with change in VAS craving (ρ=0.767, p=0.004).ConclusionsThis pilot program evaluation suggests that a short, highly structured gaming-based residential camp can be delivered feasibly and safely and may be associated with short-term reductions in IGD symptom severity and craving. Its main value is to provide early implementation and short-term signal data for a service-based camp format that should be tested in subsequent controlled studies with follow-up.
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GLP-1 Drugs Linked to Lower Rates of Substance Use Disorders

A study led by researchers at the University of Texas at El Paso (UTEP) has found that people with type 2 diabetes or obesity who were prescribed GLP-1 receptor agonists (GLP-1 RAs) had substantially lower odds of developing alcohol, opioid, nicotine, and cocaine use disorders compared with similar individuals who were not taking the medications. The research, published in the journal Frontiers in Psychiatry, used health data from more than 142,000 patients from the All of Us Research Program and adds to a growing body of evidence indicating that GLP-1 medications may have an influence on dopamine signaling and other neural pathways that drive cravings not just for food but other substances.

“Our findings add to growing evidence that GLP-1 medications may influence more than appetite and blood sugar regulation,” said lead author Tadesse Abegaz, PhD, an assistant professor in the School of Pharmacy, University of Texas at El Paso. “These medications appear to affect brain pathways involved in reward and craving, which could help explain the lower rates of substance use disorders observed in our study.”

Substance use disorders are a significant public health challenge contributing to illness, premature death, and higher healthcare costs. While current treatment methods that combine medications and behavioral therapy can be effective, relapse rates remain high, often exceeding 50% within the first year after treatment, suggesting a need for additional ways to treat this disease.

An emerging candidate for this are GLP-1 receptor agonists such as semaglutide and liraglutide. Developed to treat type 2 diabetes and obesity, these drugs have drawn attention because GLP-1 receptors are found not only in areas involved in metabolic regulation but also in brain regions associated with reward and reinforcement.

“Animal studies have demonstrated that GLP-1 RAs reduce the self-administration of alcohol, opioid, nicotine, and cocaine effects [that] are believed to be mediated through interactions with the mesolimbic dopamine system,” the researchers wrote. Small human studies and observational analyses have also suggested reductions in substance cravings, relapse rates, and alcohol-related hospitalizations among some patients receiving GLP-1 therapies.

The El Paso investigators said they initiated their research to move beyond smaller studies because “the real-world impact of GLP-1 RA on multiple co-occurrence of SUD (substance use disorder) has not been systematically investigated.”

To address this gap, the team conducted a retrospective nested case-control study using data from the NIH’s All of Us Research Program. The study examined individuals with type 2 diabetes or obesity and identified cases involving new diagnoses of alcohol use disorder, opioid use disorder, nicotine use disorder, or cocaine use disorder. These individuals were compared with matched control participants who had diabetes or obesity but no documented history of substance use disorders.

Analyses of these data showed consistent associations across all categories studied. GLP-1 receptor agonist use was associated with a 74% reduction in the odds of alcohol use disorder, a 69% reduction in the odds of opioid use disorder, a 68% reduction in the odds of nicotine use disorder, and a 75% reduction in the odds of cocaine use disorder. The researchers also reported 75% lower odds of any substance use disorder among GLP-1 users compared with non-users.

“Exposure to GLP-1 RAs was consistently associated with significantly reduced odds of SUD cases,” the researchers wrote. “These findings suggest that GLP-1 RAs may exert behavioral-modifying effects that extend beyond glycemic control and weight loss.”

The researchers noted that their research was observational and does not establish cause and effect. “We do not support prescribing these medications for addiction treatment at this time,” said senior author Gabriel Frietze, PhD, an assistant professor of pharmaceutical sciences at UTEP. “Because this was an observational study in a specific clinical population, randomized clinical trials are needed before GLP-1 medications can be recommended for treating addiction.”

The team believes the findings could help guide future approaches to addressing substance use-related health issues by identifying biological pathways that may be targeted therapeutically. The authors noted that mechanisms potentially involved include modulation of dopamine release, suppression of neuroinflammation, and attenuation of stress-related neural circuits.

“Our next goal is to conduct prospective research that follows individuals initiating GLP-1 therapy over time,” Abegaz said. “We aim to evaluate whether changes in the substance use behaviors occur after treatment begins and whether these changes related to improvements in mental health and quality of life. Ultimately, this work will help inform whether GLP-1 medications could become part of future treatment strategies for substance use disorders.”

The post GLP-1 Drugs Linked to Lower Rates of Substance Use Disorders appeared first on Inside Precision Medicine.