Psychophysiology

The heartbeat-evoked potential (HEP) reflects the cortical processing of cardiac afferent signals. However, it remains unclear whether trial-level interoceptive prediction errors can be quantified directly from spontaneous resting cardiac fluctuations and whether these model-derived errors are associated with HEP amplitude. Here, we applied a Kalman filter, implemented as a sequential Bayesian estimation procedure, to resting-state EEG and ECG recordings from 21 healthy adults to estimate trial-by-trial signed prediction errors in RR-intervals. Positive prediction errors reflected unexpected cardiac deceleration, whereas negative prediction errors reflected unexpected cardiac acceleration. Cluster-based permutation tests showed that unexpected cardiac acceleration was associated with greater fronto-centro-parietal HEP amplitude than unexpected deceleration in an early post-R-peak window, spanning FC1, CP1, Pz, CP2, Cz, C4 and FC2 from 215 to 250 ms. A Bayesian linear mixed-effects model further indicated a credible negative association between signed prediction error and HEP amplitude after controlling for respiratory phase and preceding RR interval. In a secondary connectivity analysis, unexpected acceleration was associated with stronger Cz-to-frontal beta-band phase synchrony during a later post-R-peak window from 250 to 500 ms. Exploratory individual-difference analyses suggested that neuroticism was negatively correlated with late frontal HEP amplitude during unexpected acceleration, but not during unexpected deceleration or when trials were pooled across conditions. These findings demonstrate that spontaneous cardiac fluctuations can be used to derive trial-level computational estimates of interoceptive prediction error and that these estimates are reflected in early HEP amplitude. They further suggest that the cortical processing of unexpected cardiac acceleration may be related to individual differences in affective personality traits.

The relationship between motor intention and initiation of voluntary movement remains a fundamental topic in neuroscience, originating from the B. Libet seminal framework introduced in 1983. Libets paradigm significantly influenced discussions on intentionality, motor control, and free will. However, methodological critiques continue to challenge its interpretations, specifically the accuracy and validity of the urge to move phenomenon. One understudied factor in this debate is the potential influence of interoceptive signals--particularly cardiac activity--in shaping the experience of motor intention and movement initiation. In our study, we addressed this gap by examining whether cardiac signals modulate participants experience of the urge to move, using behavioural and electrophysiological measures in 34 healthy human participants performing Libets task. Crucially, when participants were asked to report the perceived urge to move, their button press timings were predominantly aligned with the diastolic phase of the cardiac cycle, indicating cardiac modulation of motor intention perception. However, analysing heart evoked potential (HEP) amplitudes as a measure of cardiac input perception, we observed no differences in HEP amplitudes associated with changes in introspective demands during the task in both source and sensor spaces. Our results suggest that implicit perception of cardiac signals biases subjective experience of voluntary action initiation, independent from cortical interoceptive markers. These findings have implications for models of motor preparation, intentionality and the bodily basis of voluntary action, challenging conventional interpretations of motor intention and informing debates on volition and interoception. Significance StatementOur study provides evidence that implicit perception of cardiac signals influences the subjective experience of motor intention--the urge to move in Libets experiment. We demonstrate, for the first time, that when reporting urge to move, participants tended to initiate voluntary movements during the diastolic phase of the cardiac cycle. These findings challenge traditional views on factors affecting motor initiation, suggesting relevance of interoceptive processing. By highlighting the role of cardiac input in experiencing motor intention, our findings impact existing debates on volition, agency and free will, further underscoring the importance of integrating bodily signals into these theoretical frameworks.

Electroencephalography (EEG) has emerged as a key method for investigating the neural mechanisms through which oxytocin influences cognition and behaviour. EEG is cost-effective, has excellent temporal precision, and may elucidate neural correlates of emotional and cognitive processes. EEG studies evaluating oxytocins electrophysiological effects have, however, yielded mixed results, which is likely driven by heterogeneity in EEG measures, study designs, dosages, and samples. To investigate the effect of oxytocin administration on EEG measures, we performed two multilevel random effects meta-analyses: The first meta-analysis synthesized studies investigating the effects of oxytocin administration on different neural correlates of social and cognitive processing; the second meta-analysis synthesized studies evaluating effects of oxytocin administration on exploratory, less task-specific neural activity measures, such as the modulation of microstates. Across both meta-analyses, we synthesized 161 effect sizes from 28 randomised controlled trials with a total of 1361 participants from different population groups. These multilevel meta-analyses yielded small effect sizes of oxytocin administration across different EEG measures reflecting social and cognitive processes (Hedges g = 0.14), and exploratory neural activity (Hedges g = 0.28) with significant heterogeneity estimates (p < 0.01 and p < 0.001, respectively). Moderator analyses revealed that the different EEG measurements of interest (e.g., event-related potentials) and the proportion of female participants were found to significantly moderate the effect of oxytocin on neural EEG activity. Altogether, these meta-analyses present tentative evidence for oxytocin administration modulating a wide range of neural activity. We observed substantial heterogeneity across studies - in terms of study designs, experimental paradigms and EEG measurements, and participant characteristics. More research is warranted to map out the context-specific effects of oxytocin administration on different neural markers, to better understand the neurobiological mechanisms of oxytocin.

BackgroundChronobiology research has historically focused on circadian rhythms; however, longer infradian rhythms are prevalent in human physiology and may have important implications for health and wellbeing. Previous studies have identified widespread infradian rhythms across human physiology, often in the context of hormonal regulation and disease. Despite growing evidence of their ubiquity, the mechanisms, significance, and clinical relevance of these rhythms remain poorly understood, largely due to lack of longitudinal datasets and robust detection methods. The emergence of new wearable technologies enables rich, continuous data capture within individuals, allowing physiological rhythms to be studied at scale. MethodsThis study analyzed a cohort of healthy, young adults (N=623), with up to four years of wearable and questionnaire data collected through the University of Notre Dames (USA) NetHealth project. Participants who recorded at least three months of continuous (>80% adherence) heart rate data were included and significant infradian rhythms were identified using wavelet analysis. Unsupervised non-negative matrix factorization was performed to cluster similar wavelet power spectrum distributions. Individuals heart rate rhythms were compared to known environmental cycles (day-of-week, lunar, seasonal) and considering demographics and social networks. A second, smaller cohort (N=70) with heart rate and menstrual timing were included to analyze the interplay of hormonal regulation on monthly cycles. Multinomial logistic regression, and statistical tests (i.e., one-way ANOVA) were applied to quantify the effects of environmental, behavioral and demographic factors on heart rate rhythms. FindingsSignificant infradian rhythms of heart rate were detected in 69.7% (365/523) of the cohort and 35.9% (188/523) had two or more rhythms. Annual, biannual and 10-week rhythms were the most common. Within the 4-45-day band, individuals clustered into four multiday chronotypes based on dominant periodicities in their wavelet power spectra: weekly ([~]7 days), shorter-monthly ([~]25 days), longer-monthly ([~]35 days), and multi-month (>35 days). Heart rate rhythms were influenced by environmental cycles (day-of-week and seasonality) but were not tightly correlated to external cues. Additionally, heart rate rhythms were synchronized to the menstrual cycle in most menstruating females, although monthly rhythms were also observed in males and menopausal women. InterpretationThe prevalence of infradian, or multiday heart rate rhythms in healthy young people motivates further scientific investigation to understand the mechanisms of these rhythms and their potential association with autonomic function, and risk of disease or disease-specific symptoms. Characterizing physiological rhythms can drive new insights into how multiscale fluctuations modulate disease symptoms across neurological, psychiatric, and broader health conditions.

Emotions are dynamic experiences that unfold over time, yet most affective neuroscience studies have relied on static stimuli and laboratory-based EEG systems. This study examined whether emotional valence and arousal can be reliably decoded using a consumer-grade wearable EEG device in naturalistic contexts. Forty-three participants viewed video clips designed to elicit four core affect categories including high-arousal positive, low-arousal positive, high-arousal negative, and low-arousal negative, while EEG signals were continuously recorded. Multivariate analyses, including classification, multidimensional scaling (MDS), and intersubject correlation (ISC), were employed to assess affective representation and neural synchrony. Behavioral data demonstrated robust classification of both valence and arousal, whereas EEG data yielded consistent above-chance classification of valence but less stable decoding of arousal, particularly in within-participant analyses. MDS revealed that both behavioral and EEG responses were primarily organized along the valence dimension, with weaker separation along arousal. ISC analyses further indicated frequency- and region-specific neural synchrony, with stronger alignment in left and temporal electrodes, though overall ISC values were modest, likely reflecting the brief duration of stimuli. Taken together, these findings suggest that valence is more stably represented in both subjective and neural domains, whereas arousal may require time-resolved or longer-duration approaches for reliable decoding. This work demonstrates the feasibility and limitations of employing wearable EEG for theory-driven affective neuroscience, underscoring its potential for scalable and ecologically valid emotion research beyond laboratory settings.

The heart does not beat like a metronome: varying parasympathetic input to the heart leads to constant heart rate variability. Vagal cardiomotor neuron activity is coupled to the respiratory cycle, leading to Respiratory Sinus Arrhythmia (RSA), a permanent oscillation of heart rate synchronized to respiration. Heart rate also temporarily decelerates in specific conditions such as in freezing due to perceived threat, or anticipation of a salient stimulus. Anticipatory Cardiac Deceleration (ACD) is observed consistently in anticipation of a stimulus in perceptual tasks, but its relationship with perceptual performance is debated. Previous quantifications of ACD neglect ongoing heart rate oscillations due to RSA, which may have led to inconsistencies in the ACD-related analyses across studies. Here, we suggest a novel approach to estimate trial-averaged RSA amplitude and respiratory phase-independent cardiac deceleration simultaneously, and apply it to an EEG-ECG dataset from a visual detection task. While the total ACD was not associated with perception, dissociating RSA-based and non-respiratory cardiac modulations revealed that they show opposing effects on perceptual performance. Additionally, we found that participants with higher ACD amplitudes also displayed larger Visual Awareness Negativity potentials, further supporting a contribution of ACD to visual perception. Impact StatementWe present a novel analysis method to quantify task-related, anticipatory cardiac deceleration which takes tonic heart rate oscillations due to respiratory sinus arrhythmia into account. Our results add to previous research on the relationship between cardiac deceleration and perception by simultaneously characterizing and dissociating respiratory and non-respiratory heart rate modulations during stimulus anticipation.

Mental imagery is known to be accompanied by autonomic responses, traditionally viewed as merely downstream consequences of imagery. Recent theoretical work has challenged this view, proposing that mental imagery requires the integration of cortical sensory representations with ascending interoceptive signals supplied by the autonomic nervous system. These two views make opposite predictions: if autonomic activity is only a consequence of imagery, then the responsiveness of the autonomic nervous system should not predict imagery vividness. If instead autonomic input shapes the generation of mental images, individuals with greater autonomic responsiveness should experience more vivid imagery. The present study tested these competing predictions by examining whether individual differences in cardiac vagal reactivity (indexed by the magnitude of HRV change in response to a paced breathing manipulation) predict self-reported visual imagery vividness. Imagery vividness was assessed using the Vividness of Visual Imagery Questionnaire (VVIQ) at a separate time point from the paced breathing protocol, ensuring that any observed relationship between cardiac vagal capacity cannot reflect autonomic activation driven by imagery itself. The key result was that cardiac vagal reactivity (indexed by RMSSD change normalized by mean R-R interval), significantly predicted higher VVIQ scores (r = .30, p = .031). These findings demonstrate that vividness of mental imagery is not exclusively central in origin but also shaped by the capacity of the autonomic nervous system to enter a high-parasympathetic state. Imagery thus likely involves bidirectional autonomic-cortical interaction, with descending pathways triggering the intention to generate an image and ascending interoceptive signals contributing to its generation.

The gastric-brain axis is a burgeoning field of neuroscience; however, inferences from neuroimaging research are often constrained by the high dimensionality of methodological choices potentially leading to disparate outcomes. This study addresses such concerns by performing a multiverse analysis of gastric-brain coupling in humans. We systematically evaluated 1,728 unique analytic pipelines using electroencephalography (EEG) and electrogastrography (EGG) data to quantify the robustness of observed gastric-brain coupling. Our results reveal that whilst analytic decisions influence the magnitude of observed coupling, at the group level the phenomenon remains relatively robust across the parameter space. High inter-individual variance can, however, be observed. Coupling was observed in the alpha, theta, and beta bands, with the latter two bands showing robust coupling across the largest number of electrodes. Robust coupling across frequency bands was primarily seen in medial electrodes, with some left lateral coupling also observed. Overall, these findings suggest that gastric-brain coupling is likely to be a robust physiological feature in healthy participants, providing a stable foundation for future studies.

In contemporary Cognitive Neuroscience, increasing attention is devoted to brain-body interactions, as an expanding body of literature suggests that processing the external world may not emerge from the brain in isolation but rather from the coordinated contribution of multiple bodily systems. These interactions have been extensively studied in the context of interoception. However, evidence linking them to visual perception remains scarce. To address this gap, the present study examines heart-brain interactions during a visual feature integration task. The task of the participants required shape and color integration of features to identify a target while inhibiting distractor-related information. Cardiac and neural activity were simultaneously recorded, enabling the assessment of the heart rate (HR), heart-evoked potentials (HEP), and, albeit seldom reported previously, heart-evoked oscillations (HEO). Pre-stimulus cardiac-related neural activity differed between correctly and incorrectly integrated features. HEO analysis revealed alpha and low beta band modulations before target onset, which vanished when cardiac time-locking was removed, indicating that they were specifically driven by brain-heart coupling rather than by ongoing brain activity alone. These findings provide the first evidence that HEO dynamics contribute to successful perceptual integration and extend previous work on HEPs from stimulus detection to higher-level perceptual processes. More broadly, they suggest that cardiac signals shape early brain states that bias perception, supporting theoretical frameworks proposing an active role for bodily signals in perceptual processing. HighlightsO_LIPre-stimulus heart-evoked potentials differ between correct and incorrect feature integration. C_LIO_LIHeartbeat-locked alpha and low beta activity increase before correct feature integration C_LIO_LIPre-stimulus oscillatory effects vanish without cardiac activity, revealing HEO contribution. C_LIO_LIBrain-heart coupling biases perceptual outcomes. C_LI

The ERP components P3 and P600 have been proposed to reflect phasic activity of the locus coeruleus norepinephrine (LC/NE) system in response to deviant and task-relevant stimuli across cognitive domains. Yet causal evidence for this link remains limited. Here, we used continuous transcutaneous auricular vagus nerve stimulation (taVNS), a non-invasive method proposed to modulate LC/NE activity, to test whether these components are indeed sensitive to NE manipulation. Forty participants completed both an active visual oddball task and a sentence processing task including both syntactic and semantic violations, while receiving continuous taVNS at the cymba conchae in one session and sham stimulation at the earlobe in another session. We observed robust P3 and P600 effects. Crucially though, taVNS had no effect on P3 or P600 amplitude. The physiological NE markers salivary alpha amylase level and baseline pupil size were also unaffected by the stimulation, suggesting that the taVNS protocol and/or task may not have been sufficient to successfully engage the LC/NE system. Beyond the stimulation, however, exploratory analyses revealed correlations between the syntactic P600 and both the P3 and salivary alpha amylase levels, supporting the idea that the P600 might be related to both the P3 and NE. Overall, our findings do not allow for theoretical implications concerning a potential causal link between the two components and NE but highlight the need for more standardized taVNS protocols.

PurposeWe aimed to develop a non-invasive neural test of language comprehension to use with non-speaking children for whom standard behavioural testing is unreliable (e.g., minimally-verbal autism). Our aims were three-fold. First, we sought to establish the sensitivity of two auditory paradigms to elicit neural responses in individual neurotypical children. Second, we aimed to validate the use of a portable and accessible electroencephalography (EEG) system, by comparing its recordings to those of a research-grade system. Third, in light of substantial inter-individual variability in individuals neural responses, we assessed whether multivariate decoding methods could improve sensitivity. MethodsWe tested the sensitivity of two child-friendly covert N400 paradigms. Thirty-one typically developing children listened to identical spoken words that were either strongly predicted by the preceding context or violated lexical-semantic expectations. Context was given by a cue word (Experiment 1) or sentence frame (Experiment 2) and participants either made an overall judgement on word relatedness or counted lexical-semantic violations. We measured EEG concurrently from a research-grade system, Neuroscans SynAmps2, and an adapted gaming system, Emotivs EPOC+. ResultsWe found substantial inter-individual variability in the timing and topology of N400-like effects. For both paradigms and EEG systems, traditional N400 effects at the expected sensors and time points were statistically significant in around 50% of individuals. Using multivariate analyses, detection rate increased to 88% of individuals for the research-grade system in the sentences paradigm, illustrating the robustness of this method in the face of inter-individual variations in topography. ConclusionsThere was large inter-individual variability in neural responses, suggesting inter-individual variation in either the cognitive response to lexical-semantic violations, and/or the neural substrate of that response. Around half of our neurotypical participants showed the expected N400 effect at the expected location and time point. A low-cost, accessible EEG system provided comparable data for univariate analysis but was not well suited to multivariate decoding. However, multivariate analyses with a research-grade EEG system increased our detection rate to 88% of individuals. This approach provides a strong foundation to establish a neural index of language comprehension in children with limited communication.

Wearable electroencephalography (EEG) and electrocardiography (ECG) devices may offer a non-invasive, user-friendly, and cost-effective approach for assessing well-being (WB) in real-world settings. However, challenges remain in dealing with signal artifacts (such as environmental noise and movements) and identifying robust biomarkers. We evaluated the feasibility of using portable hardware to identify potential EEG and heart-rate variability (HRV) correlates of WB. We collected simultaneous ultrashort (2-minute) EEG and ECG data from 60 individuals in real-world settings using a wrist ECG electrode connected to a 4-channel wearable EEG headset. These data were processed, assessed for signal quality, and analyzed using the open-source EEGLAB BrainBeats plugin to extract several theory-driven metrics as potential correlates of WB. Namely, the individual alpha frequency (IAF), frontal and posterior alpha asymmetry, and signal entropy for EEG. SDNN, the low/high frequency (LF/HF) ratio, the Poincare SD1/SD2 ratio, and signal entropy for HRV. We assessed potential associations between these features and the main WB dimensions (hedonic, eudaimonic, global, physical, and social) implementing a pairwise correlation approach, robust Spearmans correlations, and corrections for multiple comparisons. Only 8 files showed poor signal quality and were excluded from the analysis. Eudaimonic (psychological) WB was positively correlated with SDNN and the LF/HF ratio. EEG posterior alpha asymmetry was positively correlated with Physical WB (i.e., sleep and pain levels). No relationships were found with the other metrics, or between EEG and HRV metrics. These physiological metrics enable a quick, objective assessment of well-being in real-world settings using scalable, user-friendly tools.

The human startle reflex has primarily been characterized by its repeatable, coordinated, and temporally patterned somatomotor responses. In this study, we assessed whether startle-evoked sympathetic nervous system (SNS) responses might also constitute a repeatable, coordinated, and temporally structured output. Using a noninvasive tactile startle stimulus, we simultaneously recorded startle-evoked electrodermal activity, photoplethysmography-derived blood volume indices, heart rate, blood pressure, stroke volume, and cardiac output in healthy participants. Our results demonstrate that startle elicits a reproducible and patterned constellation of SNS responses - a multimodal SNS startle signature - with conserved temporal relationships across effector systems. The SNS startle signature was composed of robust bilateral peripheral responses, including palmar sweating, cutaneous vasoconstriction, and biphasic cutaneous venous-capillary blood volume changes, in addition to more mild central hemodynamic changes. In contrast to previous startle reflex studies, there was no influence of biological sex or cardiac-cycle gating on responses. Lastly, the SNS startle signature exhibited features of a potentially attractive diagnostic, associated with robust responder discrimination and high response reliability across repeated trials. Overall, these findings fill a critical knowledge gap and also suggest the potential utility of this multimodal signature for assessing autonomic dysfunction.

Emotion is key to human communication, inferring emotion in a speakers voice is a cross-cultural and cross-linguistic capability. Electroencephalography (EEG) studies of neural mechanisms supporting emotion perception have reported that early components of the event-related potential (ERP) are modulated by emotion. However, the nature of emotions effect, especially on the P200 component, is disputed. We hypothesised that early acoustic features of emotional utterances might account for ERP modulations previously attributed to emotion. We recorded multi-channel EEG from healthy participants (n = 30) tasked with recognising the emotion of utterances. We used fifty vocalisations in five emotions - anger, happiness, neutral, sadness and pleasure - drawn from the Montreal Affective Voices dataset. We statistically quantified instantaneous associations between ERP amplitudes, emotion categories, and acoustic features, specifically, intensity, pitch, first formant, and second formant. We found that shortly after utterance onset (120-250 ms, i.e., P200, early P300) ERP amplitude for sad vocalisations was less than for other emotional categories. Moreover, ERP amplitude at around 180 ms for happy vocalisation was less than for anger, sadness, and pleasure. Our analysis showed that acoustic intensity explains most of these early-latency effects. We also found that, at longer latency (220-500 ms; late P200, P300) ERP amplitude for neutral vocalisations was less than for other emotional categories. Furthermore, there were also ERP differences between anger and happiness, anger and pleasure, anger and sadness, happiness and pleasure, as well as happiness and sadness in shorter windows during this late period. Acoustic pitch and, to a lesser degree, acoustic intensity explain most of these later effects. We conclude that acoustic features can account for early ERP modulations evoked by emotional utterances. Because previous studies used a variety of stimuli, our result likely resolves previous disputes on emotions effect on P200.

Cortical tracking of speech features is a well-established marker of continuous speech processing, but far less is known about listeners ocular responses to speech rhythm. Ocular responses are central to active sensing models in the auditory domain, where motor recruitment guides temporal speech prediction and attention allocation, potentially shaped by non-rhythmic cues, such as emotions. Here, we ask whether listeners pupil response and eye movements track the acoustic speech signals and to what extent this tracking is modulated by emotion-related top-down factors, including subjective emotion ratings, mood, and trait empathy. In a validation study (N = 100), participants passively listened to two TED talks and intermittently rated segments on valence (negative-positive) and arousal (low-high). This suggested substantial variability in valence and arousal across speech segments in both talks. In the second study (N = 41), participants completed the same task while pupillometry and electrooculography (EOG) were recorded. Mutual information was used to quantify speech tracking in pupil dilation, along with horizontal and vertical eye movements. All ocular signals significantly tracked speech at low frequencies. High-arousal speech was associated with stronger pupil tracking but weaker vertical and horizontal EOG tracking. Negative speech valence was linked to stronger tracking in pupil and vertical eye-movement signals. Interactions between the speech-emotion dimensions, as well as their interactions with listeners mood, further shaped these effects, giving rise to distinct patterns across ocular measures. Taken together, our findings provide evidence that ocular activity dynamically aligns to the temporal structure of natural speech and that this tracking is sensitive to both stimulus-driven and listener-dependent emotional factors.

Heartbeat-evoked responses (HER), as measured by electroencephalography (EEG) or magnetoencephalography (MEG), represent neural activity time-locked to heartbeats and are widely used as a marker of cardiac interoception in the study of brain-body interactions. However, HER studies report largely variable findings, at least partially due to methodological variability. To achieve consensus on HER processing and improve the reproducibility of findings, the field urgently requires a structured summary of the methods employed so far. To this end, we conducted a systematic review of 132 HER studies using non-invasive M/EEG recordings in humans. Our results reveal substantial heterogeneity across most steps of HER analysis, ranging from data acquisition and preprocessing to HER estimation and statistical approaches. The large diversity in the processing choices is accompanied by considerable proportions of unreported methodological information across reviewed studies, reaching up to 80% for key processing steps. In addition, less than 33% of studies had enough statistical power to reliably detect meta-level HER effects, while their reported spatiotemporal locations varied substantially. We provide a comprehensive reporting and quality control checklist to aid in the development of more standardized procedures, highlighting critical steps for robust HER investigations. Additionally, we share the full extracted dataset, including an interactive version, to support other researchers in answering additional specific questions they may have. We hope that these resources will improve the robustness, reproducibility, and transparency of research in the growing HER field.

Defining the brain mechanisms underlying initial emotional evaluation is a key but unexplored clue to understand affective processing. Event-related potentials (ERPs), especially suited for investigating this issue, were recorded in two experiments (n=36 and n=35). We presented emotionally negative (spiders) and neutral (wheels) silhouettes homogenized regarding their visual parameters. In Experiment 1, stimuli appeared at fixation or in the periphery (200 trials per condition and location), the former eliciting a N40 (39 milliseconds) and a P80 (or C1: 80 milliseconds) component, and the latter only a P80. In Experiment 2, stimuli were presented only at fixation (500 trials per condition). Again, a N40 (45 milliseconds) was observed, followed by a P100 (or P1: 105 milliseconds). Analyses revealed significantly greater N40-C1P1 peak-to-peak amplitudes for spiders in both experiments, and ANCOVAs showed that these effects were not explained by C1P1 alone, but that processes underlying N40 significantly contributed. Source analyses pointed to V1 as a N40 focus (more clearly in Experiment 2). Sources for C1P1 included V1 (P80) and V2/LOC (P80 and P100). These results and their timing point to low-order structures (such as visual thalamic nuclei or superior colliculi) or the visual cortex itself, as candidates for initial evaluation structures.

Cognitive reappraisal, the deliberate reinterpretation of emotional events, is widely considered an effective emotion regulation strategy, and modulation of the late positive potential (LPP) during negative affect reduction has become the primary electrophysiological evidence for volitional emotional control. Experimental instructions, however, impose dual-task demands that free viewing does not, confounding reappraisal with cognitive load. By including instructions to increase emotional responses to pictures ("enhance") as well as instructions to decrease ("suppress"), different predictions are generated. If the LPP reflects regulation, then, compared to free viewing, suppress instructions should decrease LPP amplitude, and enhance instructions should increase LPP amplitude. If modulation instead reflects cognitive load, both instructions should reduce the LPP, as both impose an additional cognitive task. In a sample of 107 participants, evaluative ratings confirmed that regulation instructions modulated reported emotional intensity in the expected directions (Enhance > View > Suppress), but that both enhance and suppress instructions reduced LPP amplitude compared to free viewing, with Bayesian model comparisons providing strong evidence against direction-specific regulation and in favor of cognitive load. Whole-scalp multivariate pattern analysis confirmed that no instruction-related neural signal exists at any scalp location or latency within the first second after stimulus onset. These data indicate that LPP modulation following both instruction types reflects dual-task cognitive load rather than volitional emotional control. Significance StatementCognitive reappraisal is considered the gold standard of emotion regulation, and reduced late positive potential (LPP) amplitude during negative emotion suppression is the primary neural evidence that humans can voluntarily control emotional responses. The current data are inconsistent with this regulatory account and instead support a cognitive load interpretation. Whether instructed to enhance or suppress emotional responses, LPP amplitude was reduced in both conditions relative to free viewing, consistent with attentional resource competition rather than directional regulatory control. The same participants reported successfully regulating emotional experience in opposite directions, producing a clear dissociation between neural and behavioral measures. These findings challenge a basic tenet of emotional regulation and raise questions concerning LPP modulation as a biomarker of regulatory capacity.

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.

Skin Conductance Response (SCR) is a phasic change in electric conductivity of the skin, occurring either non-specifically, or in response to a stimulus (event-related, or ER-SCR). It has long been understood that ER-SCR amplitudes are greater when associated with unpleasant or high-arousal stimuli; however, the relationship between emotional valence and arousal to other ER-SCR measures such as ER-SCR latency (interval between stimulus onset and ER-SCR onset) and ER-SCR rise time (interval between ER-SCR onset and peak amplitude) is less well-established. Here, we presented 60 emotive pictures from IAPS and NAPS affective picture systems to a group of 100 young, healthy adults (50 male and 50 female) and recorded their electrodermal activity. We found that higher emotional arousal was associated with greater ER-SCR amplitudes and shorter ER-SCR rise times. Interestingly, while the increase in ER-SCR amplitudes was only observed for a subset of high-arousal stimuli (score 7-9 on a 9 point scale), the effect on ER-SCR rise times was more graded and particularly sensitive to the difference between low (score 1-3) and medium-arousal (score 4-6) categories. Next, we found that while ER-SCR amplitudes were greater in response to unpleasant stimuli (valence score 1-3 on a 9-point scale), none of the ER-SCR measures could distinguish between neutral (score 4-6) and positive stimuli (score 7-9). We suggest that the increase in ER-SCR amplitudes for unpleasant stimuli is primarily driven by the inherent association between unpleasantness and high arousal. In conclusion, we demonstrate that ER-SCR rise time conveys valuable information about emotional arousal and represents a useful complementary measure to ER-SCR amplitude in order to discern between multiple degrees of emotional arousal. Furthermore, this study confirms the cross-cultural validity of the IAPS and NAPS databases in a sample of young adult Czechs.