Biological Psychology

Wellbeing is commonly defined as the combination of feeling good and functioning well and typically conceptualized as two related but distinct components. Hedonic wellbeing emphasizes pleasure, happiness, and life satisfaction, while eudaimonic wellbeing focuses on meaning, personal growth, flourishing, and the realization of ones potential. The Mental Health Continuum-Short Form was developed as a comprehensive measure of wellbeing and includes three subscales assessing emotional, social, and psychological wellbeing. Although the Mental Health Continuum total score is often interpreted as an indicator of overall wellbeing, the underlying genetic structure of its three subscales and its genetic overlap with other commonly used wellbeing measures remains unclear. Using data from 5,212 individuals from the Netherlands Twin Register (72% female, mean age 36.4), we fitted multivariate twin models to examine the genetic architecture of the Mental Health Continuum and its associations with other wellbeing measures (quality of life, life satisfaction, subjective happiness, and flourishing). Results indicate that, at the genetic level, the Mental Health Continuum is best explained by its three distinct subscales rather than by a latent factor. When considering the Mental Health Continuum together with the other wellbeing measures, we found moderate to high genetic correlations (r = 0.52 - 0.83), indicating substantial overlap in the genetics underlying the wellbeing constructs. However, we did not find evidence for a single common genetic factor underlying all constructs. These findings highlight the multidimensional structure of wellbeing, but the moderate to high genetic correlations across measures suggest that it is important to align the level of measurement (phenotypic vs genetic) with the research question.

Historically, neural variability observed during task was interpreted as "noise," assumed to obscure meaningful signal and thus something to be minimized both analytically by researchers and functionally by the brain. Changes to this signal-to-noise ratio have been proposed as a possible neural mechanism behind the increased reaction-time variability (RTV) in attention deficit hyperactivity disorder (ADHD). However, not all variability is the same - in some cases, variability can have some underlying "statistical structure" that can be beneficial to information processing. The challenge lies in distinguishing meaningful variability from random noise. The edge-of-synchrony critical point, which describes a system poised between synchronous and asynchronous regimes, could be a good theoretical framework to study these different types of neural variability. In this study, we investigate whether changes in criticality and oscillatory dynamics preceded slower behavioral responses during a bimodal continuous performance task in ADHD. We find evidence that, prior to slower responses, neural dynamics shift toward criticality in both ADHD and control groups, suggesting that increase variability in ADHD and during attention lapses are related to structured variability and not necessarily random noise. Notably, these findings run counter predictions based on the proposed model and previous literature on neural noise in this population, challenging predictions of edge-of-synchrony criticality as a unifying account of neural variability and behavioral performance. Furthermore, this effect did not emerge at the between-subject level, underscoring the limitations of relying on between-subject correlations to infer neural mechanisms. Impact StatementOur findings add new perspective to the hypothesis that links neural variability to reaction time variability in adults with and without ADHD. We found that neural dynamics shift towards criticality prior to slow reaction times in adults with and without ADHD, but in ADHD, dynamics lie closer to criticality regardless of response type, suggesting a different "attractor" state.

Voluntary actions are coupled with the respiratory cycle, yet whether this coupling reflects action timing aligning with breathing or breathing adjusting to anticipated action remains unclear. This pre-registered study compared respiration-action coupling across three conditions using a modified Libet clock task. Thirty participants performed key presses under Self-initiated (freely chosen timing), Delayed (predictable timing after one full clock rotation), and Immediate (speeded response to stimulus onset) conditions. Circular uniformity tests revealed significant respiratory phase concentration at key press exclusively in the Self-initiated condition, and time-resolved phase consistency analysis showed that coupling emerged before movement onset only in this condition. These findings suggest that action timing aligns with ongoing breathing rhythms, and that temporal freedom, rather than preparation time or predictability, is critical for this coupling to emerge. Additionally, actions performed during inhalation were followed by shorter and deeper subsequent breaths across all conditions, indicating greater perturbation of ongoing breathing when acting during inhalation. Participants reported a subjective preference for pressing during exhalation, which correlated with individual differences in exhalation bias during self-initiated actions. Body awareness, but not interoceptive awareness or trait anxiety, predicted coupling strength. These results suggest that pre-movement respiration-action coupling reflects an implicit process whereby self-chosen action timing exploits ongoing respiratory states, potentially minimizing action-related respiratory perturbation.

Differences in looking to and processing of audiovisual speech have been theorized to contribute to heterogeneity in language ability in autistic children. Differential audiovisual speech processing has been indexed by event-related potentials (ERPs), specifically via amplitude suppression in response to audiovisual versus auditory-only speech, and linked with vocabulary in school-aged children. This study used an intact-group comparison and concurrent correlational design in infant siblings of autistic children (Sibs-Autism) and non-autistic children (Sibs-NA) to determine whether amplitude suppression is (a) present in infancy, (b) different in Sibs-Autism versus Sibs-NA, and (c) related to looking to audiovisual speech and language abilities. We collected EEG data from 54 infants aged 12-18 months (29 Sibs-Autism; 25 Sibs-NA) while they viewed videos of audiovisual and auditory-only speech, as well as eye tracking and language data. We found significant amplitude differences at the N2 ERP component in response to audiovisual versus auditory-only speech but no significant group differences in ERP amplitudes. Associations between looking to audiovisual speech, amplitude effects, and language were moderated by group, chronological age, and biological sex. Our findings suggest that differential audiovisual speech processing is present in 12-18-month-olds and may explain heterogeneity in looking to audiovisual speech and emerging language ability.

BackgroundPavlovian responding is a core component of behavior and can be measured via Pavlovian-instrumental transfer (PIT), where Pavlovian responses bias instrumental actions. Standard single-lever PIT paradigms, which assess responses using a single-choice option, cannot dissociate the contribution of model-free versus model-based reinforcement learning. While indirect evidence suggests a role for model-free responding in single-lever PIT, the contribution of model-based strategies is unclear. It also remains unknown whether internal cognitive states, such as mind wandering, impair specifically model-based but not model-free PIT, as is theoretically expected. MethodsWe developed a novel, trial-by-trial two-stage PIT paradigm designed to computationally dissociate model-free and model-based Pavlovian responding by leveraging probabilistic state transitions and trial-wise outcome predictions. After each two-stage Pavlovian learning trial, participants performed a single-lever PIT trial as well as a query trial of explicit value judgment. Detailed task instructions were provided to support potential model-based strategies. Computational modeling was used to quantify individual learning strategies. We assessed mind-wandering questionnaires and thought probes. ResultsAnalysis of query and PIT trials revealed trial-by-trial updating of outcome expectations based on probabilistic task structure, consistent with model-based Pavlovian responding. Behavioral responses during PIT were best explained by a computational model-based reinforcement learning model. In contrast, we found little evidence for model-free Pavlovian responding. Higher levels of mind wandering were associated with reduced model-based control but did not impact model-free indices. ConclusionWe introduce a novel single-lever PIT paradigm that enables fine-grained dissociation of model-free versus model-based Pavlovian response systems. Our findings provide evidence that single-lever PIT can operate through model-based mechanisms, challenging the assumption that single-lever PIT is predominantly model-free. Our findings also indicate that internal attentional states selectively modulate model-based PIT. Given the involvement of Pavlovian responding in numerous psychiatric conditions, our paradigm offers new avenues for understanding maladaptive behavior. Author SummaryOur daily actions are often influenced by cues like the smell of food or the sound of phone notifications that signal potential rewards or losses. These Pavlovian cues can shape our instrumental behavior even though their outcomes do not depend on what we do - a process known as Pavlovian-instrumental transfer (PIT). Here we study the computational learning mechanisms that underlie such PIT effects. While it is often assumed that Pavlovian responding follows simple, automatic rules without a cognitive model of cue consequences (i.e., model-free), evidence also shows a role for cognitive anticipations in Pavlovian responding (i.e., model-based). In this study, we extend this evidence by showing that PIT responding can be driven by flexible model-based learning. We designed a task to test whether participants use model-free versus model-based strategies to guide PIT, providing detailed task instructions. Using reinforcement learning models, we found that most participants used model-based learning when forming cue-outcome associations. Importantly, peoples attention mattered: when they were more distracted and doing mind wandering, they relied less on model-based strategies. Our findings suggest that Pavlovian learning is complex, flexible, and influenced by internal mental states, opening new windows to understand decision-making problems in mental health conditions like addiction.

Humans form selective and enduring pair bonds with romantic partners, a principal feature of human sociality. Neuroimaging studies have shown that romantic partners are differentially represented from other individuals in the nucleus accumbens (NAcc) and anterior insula (aINS), and that the specificity of partner representations in the NAcc diminishes as relationships mature. However, it remains unclear whether such differentiation reflects partner-specific coding or mere differences in familiarity with others, and whether these regions play different roles in romantic bonding. To address these questions, we applied multiple regression representational similarity analysis to fMRI data from 51 heterosexual male participants in early romantic relationships. The data were acquired during a social incentive delay task, in which participants anticipated social approval from their female romantic partner, a female friend, or an unfamiliar female individual. This approach allowed us to dissociate partner-specific representations from familiarity-related effects in the NAcc and aINS. We found that both regions exhibited partner-specific representations that could not be explained by familiarity. Consistent with previous findings, partner specificity in the NAcc was negatively associated with relationship duration, indicating that partner-specific coding in this region is established early in romantic relationships and diminishes as relationships progress. Moreover, greater partner specificity in the aINS was associated with more frequent intrusive thoughts about the partner. Together, these findings demonstrate that romantic partners are represented in the NAcc and aINS in a qualitatively distinct manner from other individuals, and that these regions support dissociable aspects of romantic bonding. Key PointsO_LIMultiple regression representational similarity analysis revealed partner-specific representations in the nucleus accumbens and anterior insula that cannot be explained by familiarity. C_LIO_LIIndividuals in longer relationships showed reduced partner specificity in the nucleus accumbens, consistent with prior findings. C_LIO_LIIndividuals exhibiting greater partner specificity in the anterior insula reported more frequent intrusive thoughts about their partner, indicating dissociable psychological functions across regions. C_LI

BackgroundAutonomous sensory meridian response (ASMR) and music-induced frisson are sensory-affective phenomena characterized by tingling, chills, and pronounced emotional responses. Previous research has mainly focused on physiological changes during these experiences, whereas much less is known about whether baseline physiological state is associated with subsequent susceptibility. ObjectiveTo examine whether baseline autonomic flexibility, indexed primarily by heart rate variability (HRV), is associated with later ASMR/frisson responsiveness. Resting EEG measures were included as secondary exploratory markers. MethodsFifteen participants were recruited by convenience sampling; after artifact-based exclusion, 10 participants were included in the analyses. A 5-minute resting baseline EEG and ECG was recorded prior to stimulus presentation. Participants were then exposed to auditory and audiovisual ASMR stimuli, classical music excerpts, and a control stimulus, and reported whether they had experienced ASMR-typical sensations or frisson. Main analyses examined associations between baseline physiological parameters and a combined response-positive outcome. Exploratory analyses included participant-level correlations, comparisons between susceptible and non-susceptible participants, and stimulus-specific effect sizes. ResultsHRV-related measures showed the clearest and most consistent pattern of association with responsiveness. Higher baseline total HRV power was associated with a greater number of response-positive stimuli (r = 0.756, p = 0.011), with similar positive associations for high-frequency HRV (HF; r = 0.672, p = 0.033) and baseline heart rate slope (r = 0.751, p = 0.012). Stimulus-specific analyses likewise showed the most consistent positive baseline effects for total HRV power, with HF and heart rate slope pointing in the same direction. Frontal alpha asymmetry (FAA) was negatively associated with responsiveness ({rho} = -0.862, p = 0.001), but EEG findings overall were less consistent than the HRV-related pattern and are best interpreted as secondary exploratory observations. ConclusionsIn this exploratory pilot sample, baseline HRV, particularly total HRV power, showed the most coherent physiological association with susceptibility to ASMR and music-induced frisson. The findings are consistent with the possibility that these experiences depend not only on stimulus properties, but also on pre-existing physiological state. Given the small sample and exploratory design, the results should be interpreted as hypothesis-generating and require replication in larger confirmatory studies.

Neural oscillations in the delta (0.5-4 Hz) and theta (4-8 Hz) bands play a key role in tracking the temporal structure of speech. According to Temporal Sampling (TS) theory, dyslexia arises from atypical entrainment of these low-frequency oscillations to speech during infancy and childhood, which is particularly disruptive regarding phonological encoding. However, studies of adults with dyslexia have rarely examined both delta and theta cortical tracking under naturalistic listening conditions, and have not measured delta-band cortical tracking. Using EEG, here we focused on delta and theta band cortical tracking continuous natural speech by adults with and without dyslexia, applying a decoding analysis previously used with dyslexic children. Forty-eight English-speaking adults (24 dyslexic, 24 control) listened to a 16-minute continuous spoken narrative while EEG was recorded. Neural decoding of the speech envelope was quantified using backward multivariate Temporal Response Function (mTRF) models applied at two levels: a between-group analysis evaluating group-level differences in neural representation patterns, and a within-participant analysis assessing individual decoding accuracy. Cerebro-acoustic coherence was computed in parallel to provide a complementary measure of neural-speech synchronisation. Additional analyses examined band power, cross-frequency phase-amplitude coupling (PAC), and cross-frequency phase-phase coupling (PPC). Dyslexic adults exhibited less accurate delta- and theta-band decoding in the between-group analysis and reduced theta-band decoding accuracy in the within-participant analysis, alongside reduced coherence in both bands and increased delta-band power, particularly over the right temporal region. No group differences were found for PAC or PPC. HighlightsO_LIAdults with dyslexia showed reduced delta- and theta-band speech decoding C_LIO_LICerebro-acoustic coherence was reduced in delta and theta bands in dyslexia group C_LIO_LIDelta-band power was increased in dyslexia, especially over right temporal region C_LIO_LICross-frequency coupling did not differ between adults with and without dyslexia C_LI

Interpersonal neural synchrony (INS) in mother-child dyads is often interpreted as a neural marker of relational quality and sensitive caregiving, yet findings on its predictors remain heterogeneous. One possible source of this variability is the diversity of interactional paradigms used in hyperscanning research. This study examined how maternal personality, child temperament, and affective states relate to INS across interaction contexts varying in social interactivity. Thirty-three mother-child dyads (n = 20 female children) participated in a functional near-infrared spectroscopy hyperscanning experiment involving passive video co-exposure, a structured cooperative task, and free interaction. Fronto-temporal activity was recorded simultaneously, and INS was computed using wavelet transform coherence. Above-chance levels of INS emerged in inter-brain region combinations primarily involving the mothers left inferior frontal gyrus (IFG) and the childs right IFG (adjusted ps < 0.030, Cohens d range = 0.14-0.31). Maternal neuroticism was the only significant predictor of INS, with higher levels associated with increased synchrony during passive video co-exposure (adjusted p = 0.012) and free interaction (adjusted p = 0.021), but not during the structured game. These findings indicate that maternal dispositional traits shape INS in a context-dependent manner. Notably, the positive association between neuroticism and INS suggests that heightened neural synchrony may reflect over-attunement in more anxious caregivers, rather than optimal coordination. Excessive synchrony may therefore index tightly coupled, over-monitoring interaction dynamics, consistent with models of affiliative vigilance in anxious parenting. Overall, INS may follow a non-linear pattern in which moderate levels are most adaptive, highlighting its flexible, dynamic, and context-sensitive nature.

Excessive self-blaming emotions are commonly observed in anxiety disorders, with qualitatively similar symptomatology reported in subclinical populations. Interpretation of moral information requires assessing the social conceptual information, a process overseen by the superior anterior temporal lobe (sATL). Feelings of self-blame evoke interactions of sATL and socio-affective regions, and previous research shows that subclinical anxiety modulates the organisation of the self-blame circuitry. This study aimed to extend these findings by exploring links of trait-anxiety with (i) self-blaming emotions and associated behaviours in an experimental task, and (ii) self-blame-dependent neural activity and connectivity, as observed during reliving of autobiographical guilt memories. We also explored the role of resting-state fMRI in linking these phenomena. Increased anxiety was linked to stronger self-blaming emotions, and more pronounced self-attacking and hiding. When experiencing negative emotions about themselves (i.e. shame and self-anger), anxious individuals were also less likely to disengage from self-focused thoughts. These behavioural findings were paralleled by enhanced self-blame-related connectivity between the left sATL and bilateral posterior subgenual cingulate cortex. Distinct patterns of activity and connectivity within the ATL-related circuitry were furthermore linked to individual differences in intensity of the self-blaming emotions and approach-avoidance motivation towards the guilt memories. As such, the results of the current study link stronger self-blaming emotions in anxious individuals with specific maladaptive patterns of behaviour. Furthermore, the work provides robust evidence for the important role of ATL-related circuitry in self-blame processing, supporting its broader involvement in social conceptual processing and its alterations in subclinical anxiety.

Brain-computer interfaces (BCIs) have immense potential regarding the provision of therapies for disorders of development, but to date have typically been created for non-linguistic disorders such as ADHD (attention deficit hyperactivity disorder). Here we present a BCI that aims to improve linguistic phonological processing in developmental dyslexia. Phonological deficits are considered a core feature of dyslexia across languages. A non-invasive EEG-BCI relying on auditory inputs and visual feedback was developed to optimise brain patterns related to phonology (speech-sound processing). These patterns were identified using Temporal Sampling (TS) theory, which proposes that phonological difficulties in dyslexia are related to impaired auditory processing of amplitude envelope rise times and low-frequency speech envelope information <10 Hz. These impairments are thought to affect automatic features of speech processing from birth, impairing the development of a phonological system. Adults with and without a diagnosis of developmental dyslexia played the BCI for 16 sessions, and received pre-and post-testing regarding phonological awareness and single word and nonword reading skills. Significant associations between their BCI scores (a measure of BCI learning) and improvements in syllable stress discrimination, nonword reading and amplitude rise time discrimination were found. The data are interpreted with respect to TS theory.

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.

Mind wandering has been linked to a wide range of psychiatric conditions, yet most studies have examined these associations in isolation. Given the substantial comorbidity across the psychopathological spectrum, it remains unclear whether elevated mind wandering reflects a general marker of psychopathology or a more specific attentional-control deficit shared across symptom dimensions. To address this, we adopted a dimensional, transdiagnostic approach in a non-clinical sample (N = 376), simultaneously modeling seven symptom dimensions: ADHD, depression, obsessive-compulsive tendencies, schizotypy, autistic traits, hypomania, and eating disorder symptoms. At the bivariate level, mind wandering correlated positively with all symptom dimensions. However, when the substantial shared variance across dimensions was accounted for in both frequentist and Bayesian multivariate regression models, only ADHD symptoms emerged as a unique predictor ({beta} = 0.53; BF{square}{square} > 1000), with all remaining predictors yielding negligible unique contributions and Bayes factors supporting the null hypothesis. These findings suggest that previously reported associations between mind wandering and diverse psychopathological symptom dimensions largely reflect a shared liability with ADHD-related attentional dysregulation, rather than disorder-specific mechanisms. This positions mind wandering as a marker of attentional dysregulation more closely tied to ADHD symptomatology than to general psychopathological burden.

BackgroundAlcohol use disorder (AUD) is a chronic condition characterized by compulsive drinking and high relapse risk. Craving in early abstinence is a strong predictor of relapse, yet its underlying neurobiological mechanisms remain unclear. Guided by Menons Triple Network Model (TNM) of psychopathology, this study investigates whether altered connectivity between the salience (SN), default mode (DMN), and central executive (CEN) networks --previously implicated in alcohol-related behaviours -- underlies craving during early abstinence. MethodsA final cohort of 27 individuals with AUD recruited from an inpatient alcohol withdrawal program completed resting-state fMRI scans on day 1 of withdrawal and 18 days later. Additionally, 17 healthy controls underwent fMRI at two sessions spaced two weeks apart. Craving was assessed in the AUD group at both timepoints using the obsessive thoughts subscale of the Obsessive Compulsive Drinking Scale (OCDS). Functional connectivity between brain networks was computed by referencing each individuals between-network connectivity to normative models derived from large-scale reference data to generate scores reflecting their deviations from normative values. Proposed analysesPlanned analyses will leverage large-scale lifespan normative models to test associations between patient deviation scores in SN-DMN connectivity and craving during acute withdrawal, along with longitudinal associations during abstinence. Exploratory analyses will assess correlations between craving and connectivity of other network pairs of the TNM. ConclusionsThis report aims to identify functional neurobiological markers of craving during early abstinence in AUD employing normative models. Findings may advance understanding of relapse vulnerability and inform personalized interventions targeting large-scale brain network dysfunctions in AUD. This submission corresponds to Level 3 of the Peer Community In (PCI) Registered Report bias-control taxonomy: data were collected and pre-processed prior to hypothesis formulation, but key variables (subject-level values) have not been observed and no statistical analyses have been performed.

Auditory associative word learning has been shown in infants and proven to be a difficult task in young adults, where learning is only successful under specific conditions. In order to better understand the transition from successful infant auditory associative word learning to the challenging adult learning, we tested 5-6-year-olds and 9-10-year-olds in a sequential associative task to investigate their ability in associating novel pseudowords with environmental sounds. Additionally, we explored short-term episodic recognition memory, language development, sex, and musical training and their effects on behavioral and electrophysiological measures of word learning. EEG data were collected to assess word learning in an initial training phase (consistent vs. inconsistent pairings) and a subsequent testing phase (matching vs. violated pairings) with additional button-press reactions for behavioral learning data. While learning effects were seen in the first half of the training phase in younger children, no early effects of learning were found in older children. Only musically trained 9-10-year-olds indicated word learning in the second half of the training phase. In the testing phase, only non-musically trained 9-10-year-olds revealed trend-level N400-like responses. Short-term memory (auditory-verbal, auditory-nonverbal, and visual-nonverbal) and language development improved with age, but only visual-nonverbal short-term recognition memory was positively correlated with improved auditory associative word learning. Unlike cross-modal visual associative word learning, our results, together with earlier findings in infants and young adults, suggest a difficulty in auditory associative word learning beyond infancy, which is sustained from childhood to young adulthood.

BackgroundEmotion regulation--the ability to respond to and restore equilibrium after emotional perturbations--is central to mental health. Yet objective measurement remains limited to lab-based studies with group-level results, while consumer wearables focus on physical activity-related metrics rather than emotional dynamics. ObjectiveWe aimed to develop computational models that extract personalized, interpretable emotion regulation parameters from continuous heart rate variability (HRV) data collected via consumer wearables during everyday life, and validate these parameters against self-reported anxiety symptoms. MethodsWe analyzed 4 weeks of continuous HRV data from N = 49 healthy adults wearing Samsung Galaxy Active 2 smartwatches. We derived a continuous autonomic balance signal and developed three computational modeling approaches of increasing sophistication: (1) a static sympathetic load metric, (2) an Ornstein-Uhlenbeck (OU) dynamical systems model capturing continuous restoration dynamics, and (3) a discrete-state Markov transition model--the React & Rebound model-- capturing reactivity and rebound dynamics. All models were estimated using joint hierarchical Bayesian models that simultaneously extract subject-specific parameters from HRV time series and estimate their association with Generalized Anxiety Disorder 7-item scale (GAD-7) scores. The validity of extracted parameters was evaluated against anxiety symptom severity. ResultsStatic sympathetic load correlated modestly with GAD-7 (r = 0.39, R2 = 0.16). The OU model captured 69% of variance (R2 = 0.69), and the React & Rebound model captured 60% (R2 = 0.60) with substantially fewer parameters. Both models revealed that anxiety symptom severity is associated with the interaction between activation and restoration parameters--not either alone. Fast rebound appeared protective even for highly reactive individuals, who scored comparably to low-reactivity groups when restoration was rapid (Cohens d = 1.17 between highest- and lowest-risk quadrants). In the OU model, the interaction effect was specific to GAD-7 scores versus PHQ-9 and ISI scores; in the React & Rebound model, the interaction was credible across all three symptom measures. Both models were unchanged after controlling for physical activity ({Delta}R2 < 0.002). ConclusionsComputational models can extract interpretable emotion regulation parameters from naturalistic wearable data. The React & Rebound model yields two personalized parameters--reactivity and rebound--that are strongly associated with anxiety symptoms and define meaningful autonomic profiles. These parameters bridge autonomic dynamics measurable via consumer devices to neural circuit models of emotion regulation, with implications for characterizing individual autonomic profiles via consumer wearables.

Mind{square}body practices like meditation and yoga, which are widely used to support mental health, involve paying attention to internal bodily sensations like the breath. During these practices, individuals often report "interoceptive lapses," moments when attention drifts away from the body. While lapses in attention to the external world have been widely studied, far less is known about physiological and neural signals that temporally predict when attention to internal sensations falters. Interoceptive lapses may share markers with exteroceptive attention lapses--such as reaction time variability and changes in default-mode network (DMN) connectivity--but may also depend on distinct brain systems and breathing physiology. To test these possibilities, we examined behavioral, physiological and neural changes preceding lapses in a convenience sample of 93 adolescents with depressive symptoms. Participants performed a 20-minute breath counting task in the fMRI scanner with simultaneous breath recordings. Lapses were defined as moments when counting errors occurred. The sample was split into a training and validation sample, and machine learning models predicting attentional lapses were tested. The strongest predictors were timing and variability of button responses (AUCs > 0.75). Breathing variability and breathing-behavior coupling showed smaller but generalizable predictive value (AUCs < 0.65). Whole-brain connectivity models also predicted lapses (AUC {approx} 0.65) and incorporated regions within the DMN, dorsal, and ventral attention networks--overlapping with systems implicated in exteroceptive attention-- as well as the somatomotor network. Further, models that included brain connectivity marginally outperformed behavior-only models. Together, these findings suggest that interoceptive lapses reflect both shared mechanisms with exteroceptive attention failures and additional contributions from brain systems involved in bodily representation and sensory pathways. Although generalizability is limited by the clinical sample and absence of an exteroceptive comparison task, these results highlight candidate brain-body markers of interoceptive attention that may inform real-time monitoring during mind-body interventions and improve understanding of interoceptive disturbance in affective disorders.

The identification of objective, dimensional indices of mental health is of central importance in the pursuit of transdiagnostic multi-dimensional frameworks of psychopathology. Altered visual processing occupies a specific domain of interest and motivated the present investigation aimed to quantify the visuocortical impact of affective naturalistic distractor cues on limited capacity attentional resources in obsessive-compulsive disorder (OCD). The current investigation examined the extent to which attentional resources are allocated toward task cues under affective and disorder-relevant distraction in participants with OCD (N = 33) and control participants (N = 31). Steady-state visual evoked potentials (ssVEPs) in response to task-relevant cues were examined using a foreground task where participants detected coherent motion in a flickering random dot kinematogram (RDK) overlaid on naturalistic distractor pictures ranging in emotional content (pleasant, neutral, unpleasant, and OCD-evoking pictures). Amplitude envelopes of ssVEPs in response to the motion stimulus served as an index of visuocortical engagement with task-relevant cues. Data were also fitted to the distraction under competition model (DUC), a computational framework of attention selection. Group differences emerged with stronger visuocortical competition effects (attenuated task engagement) for the OCD group, driven largely by the unpleasant pictures, followed by the OCD-evoking pictures. Furthermore, the DUC model fit well in both groups, demonstrated the dominance of the visuocortical competition observed in response to the unpleasant pictures, and revealed the presence of substantial competition in response to the OCD-evoking pictures in the OCD group.

BackgroundInteroceptive cardiovascular signals, including heart rate (HR) and blood pressure (BP), arise from coordinated sympathetic (SNS) and parasympathetic (PSNS) regulation and contribute to affective and cognitive processes. Although atypical autonomic nervous system (ANS) modulation has been reported in autism spectrum disorder (ASD), the dynamical structure underlying branch-specific coordination remains insufficiently characterized. ObjectiveTo estimate latent ANS regulatory structure in typically developing (TD) and ASD individuals using a computational modeling framework. MethodsA closed-loop computational model integrating cardiovascular, respiratory, and autonomic dynamics was developed. ANS regulation was formalized using three autonomic control modes (coupled reciprocal, coupled nonreciprocal, and uncoupled) and parameterized by the relative activity of SNS and PSNS branches. HR and BP responses to the head-up tilt (HUT) test were simulated, and regulatory surfaces were compared with empirical HR and BP data from TD and ASD groups. Additional simulations under normal respiration, deep respiration, and absence of respiration evaluated mean arterial pressure (MAP) regulation across varying SNS-PSNS activity combinations. ResultsTD individuals exhibited differentiated SNS-PSNS coordination patterns across control modes, whereas ASD individuals showed convergence of relative SNS-PSNS activity. In TD, HR and BP distributions under coupled reciprocal mode were most consistent with expected physiological responses, characterized by high SNS and low PSNS activity during postural challenge. In ASD, empirical data extended toward regions of relatively higher PSNS weighting. Incorporation of deep respiration enhanced MAP reduction during BP recovery, particularly under over-elevated SNS activity. ConclusionThis study provides a mechanistic, state-space characterization of autonomic coordination in TD and ASD populations, enabling inference of latent autonomic regulation from measurable interoceptive phenotypes and identifying respiration as a model-based regulatory lever that augments cardiovascular stabilization.

When participants are engaged with auditory narratives, physiological and neural signals exhibit temporal correlations between subjects. The intersubject correlation (ISC) increases when attention is directed to the stories, suggesting that shared neural and bodily dynamics arise from a similar processing of the narratives. Identifying the factors that drive these common responses is clinically relevant for interpreting EEG ISC exhibited in unresponsive patients. In this study, we investigated whether the ISC of the EEG elicited by auditory narratives is driven by low-level acoustic (envelope, spectrogram) and/or higher-level linguistic information (word onset, word surprisal) in two groups of healthy participants during passive, attentive and distracted listening. We use temporal response functions (TRFs) for acoustic, and linguistic features to assess the contribution of each feature to the ISC, measured using correlated component analysis (CorrCA). TRFs derived for acoustic features explained a larger fraction of variance in the EEG than linguistic features and were the main contributors to the ISC. The attention-related increase in ISC was driven by all features. Importantly, word surprisal had an effect on ISC only during active story engagement, with timing and scalp distribution consistent with language processing. Notably, the linear responses captured by TRFs only explained a small amount of the overall ISC, suggesting that ISC is largely driven by nonlinear responses to the narratives. We propose that the combined use of ISC and TRFs has the potential to provide meaningful markers of language processing in patients with disorders of consciousness, and we suggest practical recommendations for their implementation.