European Journal of Neuroscience

Obesity and metabolic dysfunction are among the strongest risk factors for poor brain and mental health, yet the neural mechanisms linking metabolism, brain, and behaviour remains poorly understood. Here, we provide the first evidence for two distinct large-scale brain network configurations--one associated with metabolic health and another with obesity-- identified using resting-state fMRI data and metabolic phenotypes from a large community cohort (N = 564). While obesity was linked to enhanced coupling between subcortical reward and higher-order cortical networks, metabolic health was characterized by functional integration among default mode, salience, and frontoparietal control regions (metabolic health functional connectivity; MHFC). The MHFC network mediated the relationship between eating restraint and metabolic health, independent on individuals body weight and metabolic status, and it was replicated with data from a different time point. Longitudinal analysis showed that change of MHFC strength predicted metabolic indicators over time, suggesting a role for this network as a potential marker of metabolic resilience. These findings reveal a neurobiological pathway through which executive and interoceptive regulatory systems contribute to metabolic health, offering new insights into the brain mechanisms linking eating behaviour, metabolism, and brain function.

Background and AimFibromyalgia is an idiopathic chronic widespread pain syndrome affecting 2-4% of the general population globally. Besides widespread fibromyalgia pain, morning stiffness, associated neurologic as well as sleep problems are also reported. Disease is more prevalent in females of middle-age group with low socioeconomic status, thus deteriorating overall productivity and psychosocial health. There is no permanent cure of the disease. This study aimed to explore, validate and assess the effect of four weeks of supervised yogic intervention on pain status, quality of life, sleep, cortical excitability, flexibility and range of motion in fibromyalgia patients, as compared to standard therapy. MethodCase-control study, interventional study and assessor-blined randomized controlled trial, conducted in 120 fibromyalgia patients (60 yoga group: 60 waitlisted controls) and 60 age-matched healthy controls. Pain was assessed subjectively, using questionnaires and objectively, using quantitative sensory testing and ELISA. Sleep and quality of life were assessed using common and disease specific decsiptors. Flexibility and range of motion was assessed using sit and reach box, lateral goniometry and modified Schobers test. Transcranial magnetic stimulation on M1 was used to assess corticomotor excitability of participants. Study parameters were assessed at baseline and after four weeks of the intervention. ResultsA significantly poor sleep, flexibility and quality of life was reported in the fibromyalgia patients due to excruciating pain (VAS = 6.92{+/-}0.12); corticomotor function was also abnormal in the patients, which were restored after four weeks of yogic intervention. On subjective and objective assessment of pain, we found significant relief and improvement in pain status in the yoga group as compared to the waitlisted controls. Fibromyalgia impact, sleep, quality of life and flexibility were also found solely better in fibromyalgia patients undergoing yogic interventions. Cortical parameters, specifically RMT, MEPs and MEP recruitment curves showed a significant improvement in yoga group as compared to waitlisted controls. ConclusionFour weeks of regular and supervised yogic intervention may ameliorate pain, improve flexibility and range of motion and changes cortical plasticity in the Indian cohort of fibromyalgia patients, as compared to standard therapy. Yoga-based interventions can also improve overall quality of life and sleep impairmentsby reducing catastrophization and fibromyalgia impact.

Substance use disorder (SUD) recovery typically requires transformative change and prioritizing long-term healthy goals. Unfortunately, successful recovery is threatened by relapse rates that often exceed 50% in the first year. We previously reported on an experiential virtual reality (VR) SUD recovery intervention using personalized future self-avatars that produced emotional engagement and positive behavioral change, ie, stronger connection with the future self and future rewards and reduced craving. Here, we used fMRI to identify brain engagement to a future self experience with divergent futures. Twenty adults (14 male, 33 years old) in early SUD recovery (<1 year) interacted with age-progressed versions of themselves in two different VR future realities: an SUD Future Self and a Recovery Future Self. Vivid lifelike visual and audio animation was augmented with a personalized narrative concerning future drug use and recovery. MRI immediately followed. Participants viewed videos of their future selves in the virtual environment and were directed to contemplate what they were seeing. Viewing and contemplating the future selves elicited activation in midline default mode regions (posterior cingulate and ventromedial prefrontal cortices), visual regions including the occipital and fusiform face areas, and left middle frontal gyrus. The Recovery Future Self produced significant left occipital face area activation compared with the SUD Future Self. Midline default mode activation correlated with VR-induced increases in delayed reward preference, and also with greater trait perseverance. Using digital selves as therapeutic agents reveals an entirely novel set of possible interventions and opens exciting new frontiers in behavior change methodology. Future studies targeting decision-making and future behavior could be informed by evaluating increased midline default mode engagement, with uniquely self-focused mechanisms signaled by executive network and face area coactivation. New hope for treatment-resistant mental health conditions is offered by the nearly limitless range of therapeutic experiences enabled by immersive digital therapeutics. Plain Language SummaryHigh relapse rates in early recovery remains a serious challenge. To promote better outcomes, our team recently developed a virtual reality experience where people interacted with future versions of themselves. We used magnetic resonance imaging (MRI) to understand how the brain activated to this experience, and what brain responses were linked to positive outcomes. We worked with 20 adults in early recovery. Each person used virtual reality to interact with two different future selves: one who had returned to substance use, and one who had stayed in recovery. These digital future selves looked and sounded like the participants and were paired with a personalized story about future drug use and recovery. Right after the virtual reality session, participants brains were scanned while they watched videos of these future selves and were asked to think about what they were seeing. When people viewed and reflected on their future selves, brain areas involved in self-reflection and imagining the future became more active, along with regions that process faces. The future selves triggered brain activation in "self-focused" brain networks and in face-processing regions. Activity in key "self-focused" brain regions was linked to choosing larger, delayed rewards over smaller, immediate ones, and to lower impulsivity. These findings suggest that lifelike digital versions of peoples future selves engage brain systems that support thinking ahead, persistence, and valuing long-term outcomes. This creates a promising new avenue for immersive digital therapeutic experiences to encourage lasting behavior change in early recovery from substance use disorder.

Diabetes Mellitus (DM) is a metabolic disorder characterized by hyperglycemia, with type 1 characterized as an autoimmune destruction of pancreatic beta cells and type 2 characterized by insulin resistance with progressive beta cell dysfunction. This study applied an existing binary classification algorithm (ALTARN) to accurately predict DM. ALTARN, as a tabular attention residual neural network, uses residual connection to find complex patterns present in tabular columns. We achieved an average training accuracy of 75.22%. Furthermore, a robust set of validation metrics was obtained via five-fold stratified cross-validation, yielding an average accuracy of 74.61%, an average precision of 72.36%, a mean recall of 79.69%, and a mean F1 score of 75.83%.

Schizophrenia is a severe neuropsychiatric disorder characterized by positive and negative symptoms and cognitive impairments. The present study aimed to investigate the potential interference of ambient noise on the performance of executive function (EF) tasks in individuals with schizophrenia. The sample consisted of 40 participants, divided equally into two groups: a group of individuals with schizophrenia (SchG) and a healthy control group without neuropsychiatric disorders (HC). All participants did three EF assessment instruments: Trail Making Test, Corsi Block Test, and Maze Test. The experimental design included a test-retest procedure with order counterbalancing: half of the sample began the assessment in the noise condition and the other half in the no-noise condition, to control for order and learning effects. The results indicate that ambient noise has a negative impact on the cognitive performance of individuals with schizophrenia. Specifically, the SchG group performed significantly worse on the Maze Test in the noise condition compared to the no-noise condition. These findings contribute to the understanding of the interactions between sensory and cognitive processes underlying the symptoms of schizophrenia. In addition to their theoretical potential, the results have practical implications, as they support the development of intervention strategies and ambiental adaptations that can improve the functionality and quality of life of people with the disorder.

Schizophrenia is a serious mental disorder characterized by enhanced sensory-perceptual alterations. We investigated face identity recognition in people with schizophrenia with the Facial Identity Recognition Structured Task (FIRST) develop at our laboratory. This was created with natural interference features (beard, makeup and mask). This task consists in six block-trails of six images for identity recognition. Forty three adult volunteers divided into two groups: a Health Control (HC) and a group of hospitalized patients with Schizophrenia (SchG) participated in the study. We measured the total number of correct answers as well as the average reaction time for each block. We observed significant losses in recognition of identity faces with interferences such as make up, beard and facial-mask.

Youth alcohol use is a significant global health concern. Despite the widespread nature of alcohol use-related problems, the longitudinal effects of alcohol on brain structure in youth remain unclear. This review aimed to systematically synthesise the findings from the longitudinal structural magnetic resonance imaging (sMRI) literature on how alcohol use is associated with changes in brain structure in youth. Following PRISMA guidelines, five databases were searched, and studies of youth alcohol use that measured brain structure using sMRI at more than one time-point were included. A label-based meta-analysis (i.e., ratio of number of significant effects for a specific brain region to total number of analyses for that brain region) approach was employed to synthesise the findings. Sixteen studies were included. There was preliminary evidence that youth alcohol use is associated with reduced cortical volume (particularly in temporal regions) and attenuated increases in white matter volume over time. The role of pre-existing structural differences, and other moderating factors remains unclear due to limited research. Future longitudinal studies are needed to clarify the clinical significance of neurodevelopmental changes associated with youth alcohol use. Significance statementThis systematic review synthesises evidence from 16 longitudinal neuroimaging studies on youth alcohol use and brain structure. Preliminary findings suggest adolescent drinking may be associated with reduced grey and white matter volume over time, with heavier consumption amplifying these effects. While methodological limitations prevent definitive conclusions, these potential neurodevelopmental disruptions during a critical brain maturation window could influence cognitive and behavioural outcomes. The review highlights the need for rigorous future research to further clarify the impact of alcohol on developmental brain trajectories, which could support targeted prevention approaches for adolescent brain health.

There is a predicted increase in older adults presenting with mild to severe cognitive impairment. Screening tools with high sensitivity are the first frontier in identifying a cognitive pathology; however, to ensure that they are measuring the intended concept or criterion, thorough psychometric procedures should be followed. In this study, convergent criterion validity of Riga Cognitive Screening Task was measured, using cortical thickness of regions of interest as the criterion. 106 older adults (Mage = 70.49, SD =8.08, 35.8% male) with varying levels of cognitive functioning were involved in the study. All participants underwent cognitive assessment with the screening task and a 3T MRI. Cortical thickness of selected temporal and parietal regions was used as a brain measure. Behavioural Partial Least Squares Correlation was conducted and one latent variable was extracted. The results confirmed that Riga Cognitive Screening Task shows good criterion validity, suggesting successful use for screening.

As the global burden of addiction intensifies, the neurobiological commonalities and distinctions between substance use disorders (SUDs) and behavioral addictions (BAs) remain poorly characterized. This coordinate-based meta-analysis of 59 fMRI articles (n = 2,951) mapped the neural signatures of visual cue-reactivity across the addictive disorders. Our results revealed a universal core network shared by SUDs and BAs centered in the bilateral opercular inferior frontal gyrus, suggesting a shared disruption in inhibitory control. Distinctively, SUDs exhibited a stronger recruitment of a subcortical salience pathway, with greater involvement of the left thalamus ventral anterior nucleus than BAs, potentially reflecting pharmacologically amplified bottom-up salience attribution. Notably, recovery-related patterns diverged in the left medial superior frontal gyrus. Alcohol use disorder was associated with neural restoration, whereas heroin use disorder showed neural decompensation. These neural signatures establish a rigorous neurobiological basis for differentiating substance and behavioral phenotypes, supporting tailored circuit-based precision treatments.

Autoimmune demyelinating central nervous system (CNS) disorders encompass a wide array of clinical entities ranging from the organ specific Multiple Sclerosis (MS) to systemic autoimmune diseases (SADs) such as Systemic Lupus Erythematosus (SLE) and Sjogrens syndrome (SS). Despite international research efforts, distinction of these entities at clinical, imaging and laboratory level remains challenging, with almost 20% of patients being misdiag-nosed with MS, out of which more than 50% carry the misdiagnosis for at least 3 years, while 5% are misdiagnosed for 20 years or more. This work aims to identify early biomarkers that can discriminate MS from other clinical entities that are MS mimickers. For this reason, we have meticulously curated a unique biobank with serum, DNA, RNA, and cerebrospinal fluid (CSF) samples from 396 treatment-naive patients who presented with a demyelinating episode and for which we have recorded over 300 clinical, serological, and imaging parameters. These patients have undergone follow up at 6 months and 12 months from their first demyelinating episodes and have been categorised as follows: MS, SAD with CNS involvement, and demyelination with autoimmune features (DAF). A hybrid model for semi-supervised tabular classification is proposed that integrates a graph attention network with dynamic graph learning via Random Forest proximity and k-NN graphs with tabular prior-data fitted network for direct classification. The model also performed feature selection, self-supervised contrastive learning, self-training and data augmentation.

BackgroundPrediction of response to antipsychotic medications remains elusive, and a biomarker assisting in treatment selection would drastically improve prognosis. The 40 Hz auditory steady state response (ASSR) is an EEG biomarker, mirroring the GABA-glutamate signaling and the excitation/inhibition balance, consistently been reported to be impaired in schizophrenia, on, with inconsistent evidence of an association with specific symptoms. MethodsN=69 schizophrenia inpatients with an acute psychotic episode underwent an EEG recording to assess event related spectral perturbation (ERSP), intertrial phase coherence (ITC) and phase amplitude coupling (PAC) during the ASSR task, aimed to assess their relationship with response to antipsychotics and with positive, negative, disorganized, excited and depressive symptoms. Moreover, patients were compared with controls (N=36), to delineate schizophrenia acute phase ASSR dynamics. ResultsResponders to treatment showed a decreased 40 Hz ERSP in both the early (0-0.2s post-stimulus; P=0.0013; d=-0.936) and late (0-2-1.2s post-stimulus; P=0.0022; d=-0.932) time windows compared to non-responders. Using logistic regression and bootstrap optimism correction, ERSP classified the two groups with 70% accuracy. Responders but not non-responders showed a reduced ERSP compared to controls (P=0.0211; d=-0.558). Patients had reduced early ITPC (P=0.0001; d=-1.015) vs controls. responders compared to non-responders had increased PAC in the early (P=0.0215; d00.65) and in patients vs controls, in both the early (P=0.0002; d=0.57) and the late (P=0.0006; d=0.74) windows. No association emerged between ASSR metrics and symptoms severity. ConclusionsASSR is a candidate biomarker for antipsychotic treatment personalization. Only responders to treatment presented a significant gamma-band impairment, in line with previous literature on stabilized outpatients, but not non-responders, indicating that a distinct neurobiology could exist.

BackgroundTheta-band oscillation is integral to fronto-parietal connectivity in the executive control network and its top-down regulation on subcortical areas. External frontoparietal synchronization using theta-frequency transcranial alternating current (tACS) is a technology to potentially engage this network. In this pre-registered, triple-blind, sham-controlled trial (NCT03907644), we tested this intervention targeting the right frontoparietal network in people with opioid use disorder (OUD) to measure network engagement and behavioral outcomes. MethodSixty male participants with OUD were randomized to receive 20 minutes of active or sham 6 Hz tACS (HD electrodes over F4 and P4). Structural, resting-state, task-based fMRI drug cue reactivity, and repeated cue-induced craving assessments were collected immediately before and after stimulation. Pre-registered outcome measures were analyzed using timexgroup interaction models to examine (1) modulation of drug cue-related brain activity, (2) changes in craving, (3) alterations in functional connectivity, and (4) relationship between electric field, neural responses, and craving behavior. Results(1) A significant Time x Group interaction revealed decreased post-stimulation opioid cue-related activity in the active group relative to sham, involving key nodes in reward processing (ventral striatum, amygdala and ventral tegmental area) (FWE corrected =0.05) (2) subjective craving did not differ significantly between groups (3) Group by time generalized psychophysiological interaction analyses showed increased right frontoparietal network engagement ({beta}=2.63, p=0.0308) following stimulation, and increased top-down inhibitory regulation of frontoparietal network on right ventral striatum ({beta}=1.99, p=0.037) and left medial amygdala ({beta}=1.97, p=0.039) (4) Electric field strength in the right frontal/parietal node predicted frontoparietal network engagement in the active group (r=0.43, p=0.02). ConclusionTogether, these findings demonstrate that theta-band frontoparietal tACS can modulate activity and task-dependent coupling within cortical-subcortical circuits in OUD, supporting network-targeted neuromodulation as a potential intervention for addiction. Significance StatementAddiction is linked to imbalances in cortico-subcortical brain circuits that control reward processing and craving. This study tested whether a non-invasive brain stimulation method-- theta-band transcranial alternating current stimulation (tACS)--can rebalance these circuits in people with opioid use disorder. Using advanced brain imaging, we found that tACS strengthened communication within frontoparietal brain regions involved in self-control while reducing their connections with reward and emotion centers. These brain changes were linked to reduced craving responses to drug cues. Our results demonstrate that dual-site, network-targeted tACS modulates neural activity and task-dependent engagement of brain circuits during drug cue reactivity in addiction, supporting its potential as a novel therapeutic approach.

BackgroundSedentarism is prevalent and associated with poorer mental and physical health. Whether everyday physical activity (PA) maps onto computational decision strategies and brain structure/function in non-elderly adults remains unclear. MethodsSeventy-one healthy adults (39 women; 18-45 years) completed the Multi-Source Interference Task (MSIT) during fMRI. PA was quantified with the short IPAQ and participants were classified as Active or Sedentary. Behavior (RT, accuracy) was analyzed with frequentist models and a hierarchical Bayesian drift-diffusion model (DDM) estimating drift rate (v), boundary separation (), and non-decision time ({tau}). First-level fMRI modeled congruent/incongruent trials; group-level analyses used FLAME1 with cluster-wise FWE correction (z>3.1, p <.05). Structural MRI was processed with FreeSurfer 7.4.1 (cortical thickness, hippocampal subfields); surface-based GLMs tested group and DDM effects. ResultsActive participants responded faster overall; incongruent accuracy showed a speed- accuracy trade-off (accuracy increased with slower RTs), with a significant RT x group interaction. In the DDM, boundary separation () was higher in sedentary individuals (greater caution), whereas drift rate (v) differed by sex (males > females). Structurally, the active group showed larger left hippocampal subfields and thicker cortex in posterior temporal & anterior cingulate regions that are negatively related to . Functionally, boundary-related BOLD modulation encompassed fusiform, posterior cingulate, superior temporal cortex, and SMA; Active > Sedentary contrasts highlighted left occipital and inferior parietal lobe. ConclusionsEveryday PA aligns with lower decision thresholds, select structural advantages, and more efficient task-engaged networks, suggesting PA fosters adaptive, resource-efficient cognitive control. These mechanistic links support PA-based strategies to mitigate risks of sedentarism.

Task-based functional magnetic resonance imaging (fMRI) examines how the brain dynamically responds to cognitive and perceptual demands, offering complementary insight beyond traditional activation-based analyses in schizophrenia. Prior task-based fMRI studies have identified reduced functional connectivity within auditory and associated cortical areas. In this study, we investigated task-evoked functional connectivity and brain state dynamics in 25 healthy controls, 23 patients with schizophrenia experiencing auditory verbal hallucinations (AVH+), and 23 patients without hallucinations (AVH-). Participants completed multiple auditory paradigms, including word lists, sentence lists, and reverse speech. The most robust connectivity differences emerged during the word list task, where cluster-level analyses revealed distinct network interaction patterns differentiating controls, AVH+, and AVH-patients. Energy landscape modeling further demonstrated altered stability and organization of brain states in both patient groups, with the largest deviations observed in AVH+ individuals. These alterations point to dysregulated neural dynamics linked to hallucination vulnerability. Overall, the results show that task-based fMRI sensitively captures disruptions in functional connectivity and brain state stability relevant to auditory hallucinations, underscoring its value for characterizing network-level mechanisms underlying perceptual disturbances in schizophrenia.

Attention Deficit Hyperactivity Disorder (ADHD) affects 5-7% of children worldwide, yet diagnosis continues to rely on clinical-behavioral assessments. The theta/beta ratio (TBR) derived from electroencephalography (EEG) has long been proposed as a complementary neurobiological marker of ADHD, based on reports of elevated TBR in affected children. However, accumulating evidence has raised concerns about the robustness and generalisability of these findings, pointing to a strong sensitivity to methodological choices. Here, we used multiverse analyses to systematically quantify how researcher degrees of freedom shape conclusions about associations between TBR and ADHD. Across two large, independent datasets (Healthy Brain Network: N=1,499; validation sample: N=381), we evaluated 576 of theoretically plausible analytical specifications, varying recording conditions, reference scheme, frequency band definitions, treatment of aperiodic (1/f) activity, regions of interest, sample inclusion criteria and covariate specifications. Across the multiverse, we found that group differences in TBR were highly contingent on analytical choices, with no evidence for robust main effects of diagnosis, indicating no reliable differences between healthy controls, ADHD-inattentive, and ADHD-combined subtypes. Instead, significant effects emerged primarily as interactions with age and individual alpha frequency (IAF), particularly when TBR was derived from aperiodic-uncorrected power or from the aperiodic signal itself. These findings suggest that previously reported TBR effects are driven largely by variations in the 1/f-slope and IAF rather than reflecting genuine differences in oscillatory activity. These interaction patterns replicated across both independent samples and were observed using both categorical and dimensional definitions of ADHD. Together, these findings indicate that previously reported TBR effects are largely driven by variability in aperiodic activity and IAF rather than stable differences in oscillatory theta-beta dynamics. Our results challenge the interpretation of TBR as a reliable standalone biomarker for ADHD and underscore the importance of multiverse approaches for evaluating candidate neurobiological markers in heterogeneous clinical populations.

Background and HypothesisSchizophrenia is a disease characterized by various symptoms and has severe lifelong impacts on patients and their families. Despite various hypotheses and associated studies, the key mechanism in schizophrenia is not fully elucidated. In the present study, we focused on adropin, a peptide regulating energy metabolism, antioxidation, and neuroprotection. Study DesignIn both the group of healthy volunteers (HV) and the group of patients with some schizophrenia spectrum and other psychotic disorders (SZ), we evaluated adropin along with other variables such as anthropological factors, psychological well-being indicators, and laboratory test results. Study ResultsThe adropin levels in SZ were not significantly different from those in HV. Correlation analysis indicated five significant correlations beyond various natural correlations arising from fundamental proportional relationships and multifaceted psychological well-being indicators: (1) adropin versus right handgrip strength in the SZ group ({tau} = -0.82, P = 0.066); (2) adropin versus selenium in the total group ({tau} = 0.44, P = 0.053); (3) ferritin versus perceived stress in the total group ({tau} = -0.44, P = 0.053); (4) right versus left handgrip strength in the total group ({tau} = 0.70, P = 0.001) and in the SZ group ({tau} = 0.82, P = 0.075); and (5) selenium versus state anxiety in the total group ({tau} = 0.44, P = 0.053) and the SZ group ({tau} = 0.84, P = 0.066). ConclusionsThe present study provides a foundation for future studies and sheds light on the role of adropin in schizophrenia.

BackgroundPropofol exposure can produce heterogenous neural responses, from the expected suppression to transient paradoxical excitation. EEG measures of signal complexity and entropy have emerged as reliable markers of consciousness, but different types of complexity and entropy measures are often conflated. We used Type I and II complexity measures on the Complexity-Entropy Causal Plane (CECP) to characterize divergent neural trajectories during propofol-induced loss of consciousness. We hypothesized that paradoxical excitation is reflected in both Type I and Type II complexity; that divergent trajectories on the CECP separate paradoxical excitation from suppression; and that baseline EEG complexity is associated with susceptibility to propofol. MethodsWe analyzed EEG data from two independent cohorts of healthy adults receiving propofol: the Chennu dataset (n = 20), which included resting-state baseline, mild, and moderate sedation, followed by a recovery period; and the RecCognition dataset (n = 8), which used escalating infusions from baseline to deep sedation. For each participant and sedation level, we extracted Lempel-Ziv Complexity (LZC; Type I) and Statistical Complexity (SC; Type II) and projected them onto the CECP. Pearson correlations related baseline SC to changes in SC during moderate sedation; behavioral responsiveness; effect-site propofol concentration; and time-to-loss-of-consciousness. ResultsAt moderate sedation, participants who remained responsive showed paradoxical increases in LZC and decreases in SC, whereas unresponsive participants exhibited the opposite pattern. Baseline SC correlated negatively with both the change in SC (r = -0.88) and behavioural responsiveness, indicating that intrinsic brain dynamics influence individual susceptibility to sedation. CECP trajectories revealed a reproducible inflection point demarcating paradoxical excitation from suppression. ConclusionsMapping EEG trajectories on the CECP bridges anesthetic state transitions with underlying neural dynamics. Baseline neural complexity indexes individual sensitivity to propofol, determining whether brain dynamics transiently enter excitation or direct suppression.

BackgroundEarly low-level alcohol use predicts subsequent alcohol use and problems. Impulsivity and poor inhibitory control also predict later problematic alcohol use. However, few studies prospectively examine early sipping in combination with modeling impulsivity and inhibitory control change over time as predictors of adolescent alcohol use. MethodsData Release 6.0 from the Adolescent Brain Cognitive Development (ABCD) Study was used (n=11,866; 48% Female). A series of linear mixed-effect models examined trajectories of non-religious sipping at baseline (ages 9-10) and self-reported impulsivity (UPPS-P) and task-based inhibitory control (Flanker task) over time as predictors of past year drinks and problematic alcohol use by ages 15-16. Predictors were run as separate models and a full model with all predictors together. Models were nested within the participant and study site. Interactions with age (to measure change over time from Baseline to Year 6) were included. Corrections for multiple comparisons were employed. ResultsIn individual models, four impulsivity interactions were significant: (1) negative urgency*age ({beta}=.04, FDR-p<.001), (2) positive urgency*age ({beta}=.04, FDR-p<.001), (3) lack of planning*age ({beta}=.04, FDR-p<.001), and (4) sensation seeking*age ({beta}=.04, FDR-p<.001), suggesting that as age increases, the relationship between impulsivity and alcohol use strengthens. Sipping*age ({beta}=.02, FDR-p<.001) interactions also predicted standard drinks. Regarding problematic use, there was a significant interaction in the full model: negative urgency*age ({beta}=-.07, p=.05), indicating that this relationship is more pronounced at earlier ages. ConclusionsTrait impulsivity and sipping in late childhood relate to future alcohol use, and the relationship strengthens with age. Our results found a negative interaction between negative urgency and age on problematic use, potentially indicating negative urgency as a phenotype of vulnerability to experiencing alcohol related problems at younger ages. Findings indicate the importance of understanding facets of impulsivity in the context of adolescent alcohol use for prevention and intervention efforts.

BackgroundSpeech cortical mapping (SCM) conducted with widely available functional MRI (fMRI) can yield divergent results compared to the more commonly used navigated TMS (nTMS). The impact of specific fMRI task paradigms and preprocessing choices on reaching similarity with nTMS has not been explored before. ObjectiveTo test how the fMRI experimental task and spatial smoothing of the data compare with nTMS-based results, to subsequently increase the reliability of object naming fMRI for SCM. MethodsThirteen healthy, right-handed Finnish speakers underwent an nTMS-based SCM experiment in which the left hemisphere was stimulated while the subjects overtly named common visually presented stimuli. Standard as well as magnetoencephalography-informed picture-to-TMS intervals were applied. The same participants completed fMRI with overt naming, silent naming, and observation tasks on the same stimuli, analyzed with 0-, 3-, and 6-mm spatial smoothing. nTMS-based error and non-error sites were converted to volumetric density maps, and error-specific maps were derived by subtracting non-error from error density. Spatial similarity between binarized fMRI maps and nTMS maps was quantified using Jaccard index. Within-session fMRI reliability was estimated with voxel- and subjectwise concordance correlation coefficients across two separate runs conducted on the same day. ResultsSimilarity between fMRI and nTMS maps was overall low but depended significantly on data smoothing. Within subjects, mean error-specific Jaccard index was 0.036, with most individuals showing maximal similarity at 6 mm of smoothing. The fMRI task resulting in highest similarity with the nTMS map varied across participants, but at the group level, silent naming with 6-mm smoothing yielded the best correspondence. In general, within-session fMRI reliability increased with greater smoothing. ConclusionThe amount of applied fMRI data smoothing shapes the agreement of fMRI and nTMS maps during SCM. Silent naming fMRI combined with 6-mm data smoothing yielded the highest overlap with nTMS maps, yet the effect of the experimental task was statistically non-significant and the absolute similarity of the maps remained low. These results underline the different views to brain functions provided by direct perturbation of neural functions vs. blood-oxygenation based fMRI, and offer practical guidance when combining fMRI with nTMS in noninvasive speech cortical mapping. HighlightsO_LICorrespondence of fMRI and TMS speech cortical mapping results varied across individuals C_LIO_LIConcordance between the methods was generally low and depended on the fMRI data smoothing C_LIO_LISilent naming task in fMRI, combined with 6-mm data smoothing, yielded highest similarity to nTMS C_LIO_LIWithin-session fMRI reliability increased with greater smoothing C_LI

Despite decades of clinical implementation of medications for opioid use disorder (OUD), overdose mortality rates remain high, underscoring a critical gap in treatments that target brain mechanisms driving addiction. Mindfulness-Oriented Recovery Enhancement (MORE) has demonstrated efficacy in reducing opioid use and craving, hypothetically by restructuring the salience of drug and natural rewards. Yet, to date, MOREs neurobiological mechanisms remain unclear. In this first functional magnetic resonance imaging (fMRI) randomized controlled trial (RCT) of MORE for OUD (NCT04112186), we tested whether compared with an active psychoeducational supportive therapy (PST) control group, MORE rebalanced neural responses to drug and natural reward cues in inpatients with OUD receiving standard of care including medications. Compared with PST, eight weeks of MORE significantly reduced drug-biased activity in the dorsolateral prefrontal cortex (dlPFC) and posterior regions of the default mode network including the precuneus during downregulation of responses to drug cues relative to upregulation of responses to natural reward cues (even when controlling for passive cue viewing). The shift from drug to natural reward responses in the lateral and ventromedial PFC was associated with lower cue-induced craving exclusively in the MORE group. MORE also reduced medial PFC synchronization to naturalistic drug-related movie scenes and significantly extended abstinence duration at follow-up ([~]4 months post-treatment) relative to PST. Together, this neuroimaging RCT demonstrates that MORE normalizes function in PFC nodes of the reward, salience, and control systems, positioning MORE as a biologically-grounded adjunct to pharmacotherapy for OUD.