Psychophysiology

The P300 event-related potential is one of the most studied electrophysiological markers of cognition, yet trial-to-trial variability within conditions has traditionally been treated as measurement error.The vP300 framework proposes that P300 variability, quantified by the coefficient of variation (CV), may reflect locus coeruleus-norepinephrine (LC-NE) mode dynamics. A computational simulation (N = 80) tested three hypotheses. Empirical P3 oddball data from the ERP CORE dataset (N = 39) provided partial validation. Mean amplitude and CV were orthogonal in simulation (r = -0.14, n.s.) and moderately correlated in empirical data (r = -0.418, p = .008), with 82.5% of CV variance independent of mean amplitude. CV significantly predicted cognitive flexibility (r = -0.319, p = .004) while mean amplitude did not (r = .010, p = .928). Trial- to-trial P300 variability carries information orthogonal to traditional mean amplitude, supporting a potential revision of how variability is treated in ERP research.

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.

Intelligence or general cognitive ability (GCA) is fundamental to human behavior and cognition. It impacts important life outcomes like educational success and even health and longevity have been related to differences in GCA. Understanding the biological basis of such individual variations presents a crucial goal of neuroscience. The mismatch negativity (MMN) is an event-related brain potential that can be measured when--within a series of frequent standard stimuli, rare deviants are presented--and is suggested to reflect conscious (active) or unconscious (passive) detection processes of the brain. Importantly, variations in MMN amplitude and latency have been linked to differences in GCA. Yet findings vary considerably. This preregistered meta-analysis provides a comprehensive and structured overview of the current state of research. Following the study selection process in accordance with the PRISMA guidelines, and the rating of study design quality with the Study Design and Implementation Assessment Device for Individual Difference Research (DIAD-ID), the association between GCA and MMN amplitude and latency was examined in 695 healthy adults across 13 included studies. The estimated across-sample associations between MMN and GCA were small, but significant (MMN amplitude-GCA: r = -0.08, MMN latency-GCA: r = -0.13; p < 0.05) and moderators were identified. Between-sample heterogeneity was moderate, with no evidence of publication bias. Our findings suggest that higher cognitive ability is associated with slightly stronger and faster MMN responses. However, the low estimated across-sample effect sizes and the small number of included studies also highlight the need for more research.

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.

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.

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.

The olfactory and intranasal trigeminal systems interact closely, influencing chemosensory perception, yet the mechanisms underlying their interaction remain poorly understood and have been studied mainly in young adults. We aimed to characterize olfactory-trigeminal interactions in aging by comparing electrophysiological and behavioral responses under ipsilateral and contralateral olfactory-trigeminal co-stimulation, to determine the relative contributions of peripheral and central mechanisms. Using chemosensory event-related potentials and a localization task, 44 healthy older adults (66.3 {+/-} 4.6 years; 29 women) were tested under four conditions: pure trigeminal (carbon dioxide; CO2), pure olfactory (2-phenylethanol; PEA), ipsilateral co-stimulation (PEA+CO2 in the same nostril), and contralateral co-stimulation (PEA+CO2 in opposite nostrils). Ipsilateral, but not contralateral olfactory-trigeminal co-stimulation, improved trigeminal localization performance and induced larger late positive component amplitudes. Together, these findings suggest that olfactory-trigeminal interactions are driven primarily by peripheral rather than central mechanisms. This study also provides normative CSERP data for healthy older adults.

Creative performance fluctuates from moment to moment, suggesting that it depends partly on transient internal states present before creative thinking begins. Although such fluctuations have been identified in central neural activity, it remains unclear whether they are also reflected in autonomic physiology. We examined whether cardiac and electrodermal activity during a brief pre-trial resting period was associated with subsequent creative performance. Photoplethysmography, electrocardiography, and electrodermal activity were recorded while 28 participants completed the Alternative Uses Test and Fusion Innovation Test, assessing divergent and convergent creative thinking, respectively. Data from 27 participants was included in the analyses. Heart rate, heart rate variability, tonic skin conductance level, and phasic skin conductance activity were extracted from observation windows ranging from 11 to 30 s within a 30-s pre-trial rest period. Trial-level creativity was evaluated using GPT-based ratings of novelty, feasibility, and goal attainment. Linear mixed-effects models showed that higher pre-trial tonic skin conductance level was consistently associated with better subsequent creative performance across tasks, with overall model fit peaking at a 21-s observation window. Permutation-based feature-importance analysis provided convergent support for the contribution of tonic skin conductance, whereas the cardiac and phasic electrodermal indicators showed no reliable independent associations. However, the model explained only a small proportion of behavioral variance. These findings suggest that tonic sympathetic arousal reflects a momentary physiological state associated with creativity potential, while autonomic signals alone remain insufficient for accurate individual-level prediction.

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.

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.

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.

The vagus nerve plays a critical role in balancing the bodys physiological functions, including the cardiovascular system. Measures of heart rate (HR) and its variability (HRV) may provide non-invasive proxies of vagal activity in humans, but transcutaneous auricular vagus nerve stimulation (taVNS) has produced mixed effects so far--limited by a lack of studies stimulating the right branch. Here, we used a randomized cross-over design to study the effects of taVNS on HR and HRV. To estimate how the side of the stimulation (left vs. right ear) affects cardiovascular function, we recorded an electrocardiogram in four sessions per person (factors: Stimulation x Side). To evaluate potential interactions with physiological states, we investigated three phases per session: baseline, during stimulation (taVNS vs. sham), and after consuming a milkshake ([~]400 kcal) with concurrent stimulation. First, we found moderate evidence against an effect of taVNS on HR (BF10=0.21). Second, taVNS decreased HRV (multivariate p =.004) independent of physiological state with strong evidence for RMSSD (BF10=15.11) and HF-HRV (BF10=11.80). Third, taVNS-induced changes were comparable across sides and more strongly correlated (vs. sham), indicating similar cardiovascular effects independent of the stimulation side. We conclude that taVNS reduces HRV without altering HR, contradicting the common assumption that increased HRV indexes a heightened vagal tone. Instead, our results support a putative role of vagal afferent activation in arousal. Crucially, modulatory effects on the cardiovascular system can be safely elicited by taVNS on both sides, opening new options for treatment. Graphical AbstractCreated with BioRender.com O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=129 SRC="FIGDIR/small/542695v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@1b6a615org.highwire.dtl.DTLVardef@51bcf7org.highwire.dtl.DTLVardef@4d047forg.highwire.dtl.DTLVardef@626251_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundIncreasing efforts toward prevention of stress-related mental disorders have created a need for unobtrusive real-life monitoring of stress-related symptoms. Wearable devices have emerged as a possible solution to aid in this process, but their use in real-life stress detection has not been systematically investigated. MethodsUsing ecological momentary assessments (EMA) combined with wearable biosensors for ecological physiological assessments (EPA), we investigated the impact of an ecological stressor (i.e., an exam week) on physiological arousal and affect. With this paradigm we investigated whether we could use wearable devices to detect stress states using machine learning models. ResultsDuring stressful high-stake exam (versus control) weeks, participants reported increased negative affect and decreased positive affect. Intriguingly, physiological arousal was decreased on average during the exam week. Time-resolved analyses revealed peaks in physiological arousal associated with both self-reported stress and self-reported positive affect, while the overall decrease in physiological arousal was mediated by lower positive affect during the stress period. We then used machine learning to show that a combination of EMA and physiology yields optimal identification of stress states. ConclusionsOur findings highlight the potential of wearable biosensors in stress-related mental-health monitoring, but critically show that psychological context is essential for interpreting physiological arousal detected using these devices.

The error-related negativity (ERN) and correct-related negativity (CRN) are event-related potentials (ERPs) that reflect performance monitoring following error and correct responses, respectively. Prior work demonstrates the ERN is sensitive to the motivational significance of errors, which increases under social observation. However, most studies testing how social observation impacts performance monitoring rely on trial-averaged ERPs, potentially obscuring meaningful fluctuations in ERN/CRN over time. Here, we had participants complete a Flanker task twice (social observation vs. alone) and employed mixed-effects modeling of single-trial ERPs to test if social observation impacts ERN/CRN trajectories over short (within blocks) or long (between blocks) timescales. We found that social observation selectively influenced ERN/CRN trajectories over short timescales: for blocks performed under social observation (but not alone), ERN magnitudes increased across trials and CRN magnitudes decreased. At longer timescales, ERN/CRN significantly decreased across all blocks, regardless of social observation and consistent with a vigilance decrement. To our knowledge, this is the first demonstration that social observation influences performance monitoring trajectories over short timescales. Results highlight the importance of analyzing ERN/CRN trajectories over relatively short timescales to fully characterize the impact of social observation on performance monitoring dynamics. These findings lay the groundwork for future investigation into whether social observation interacts with individual differences in motivation/affect to differentially impact performance monitoring dynamics.

Growing evidence indicates that brain continuously interacts with other physiological systems through neural and non-neural pathways. The brain-heart and brain-gut axes play a central role in homeostasis, allostasis and behaviour, but also in cognitive aspects including emotion and decision-making. Disruptions in these axes have been linked to a wide range of cardiovascular, neurological, and psychiatric disorders. Despite this evidence, triadic crosstalk between the brain, heart, and gut remains largely unexplored. Brain activity, cardiac autonomic fluctuations, and gastric rhythms all exhibit slow temporal components in resting state, suggesting that brain-heart-gut electrophysiological interactions may occur over timescales from the infra-slow (0.01-0.1 Hz) physiological range. Using non-invasive electrophysiological recordings from 28 healthy participants at rest, we extracted time-varying power dynamics describing the activity of the three organs: brain alpha power, cardiac sympathetic and parasympathetic indices, and the power of the gastric rhythm. Statistical associations among these organs were quantified using the maximal information coefficient across the extended temporal delay range. Physiological interactions were confirmed using surrogate-based testing, which allowed us to construct the network topology of interactions between the three organs. Our findings show that triadic brain-heart-gut interactions form a multi-directional network at infra-slow timescales, shaping resting state activity. This study offers one of the first insights into the physiology of brain-heart-gut interplay, providing a methodological baseline for the development of more comprehensive biomarkers based on network dynamics capable of linking pathological conditions to dysregulation across multiple organ systems. Abstract figure legend O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=90 SRC="FIGDIR/small/718683v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@6600d1org.highwire.dtl.DTLVardef@bfd404org.highwire.dtl.DTLVardef@1f85612org.highwire.dtl.DTLVardef@dac616_HPS_FORMAT_FIGEXP M_FIG C_FIG Simultaneous resting-state electroencephalographic (EEG), electrocardiographic (ECG), and electrogastrographic (EGG) recordings were processed to extract time-resolved physiological markers for each organ: EEG alpha-band power for the brain, cardiac sympathetic and parasympathetic indices (CSI, CPI) for the heart, and EGG power for the gastrointestinal tract. Coupling between time series was then quantified, and statistical significance was assessed using a surrogate-based method. Significant couplings were subsequently integrated to construct a large-scale network representation, summarizing the strength, temporal delays, and directionality of the predominant electrophysiological interactions among the three organs. Key points summaryO_LIFirst in-human, non-invasive investigation of parallel brain-heart-gut electrophysiological interactions in awake, healthy individuals. C_LIO_LIWe analysed simultaneous electroencephalographic (EEG), electrocardiographic (ECG) and electrogastrographic (EGG) recordings and quantified strength and temporal scale of the derived time-series associations, to construct a large-scale network of interactions. C_LIO_LIWe found that brain-heart-gut interactions extend into the infra-slow (0.01 - 0.1 Hz) range, indicating that spontaneous fluctuations in the electrophysiological activity of one organ at rest are typically followed by corresponding changes in the other two. C_LIO_LIWe found a consistent brain-heart-gut network topology across participants, with multidirectional interactions and bodily dynamics converging toward midline central-posterior brain regions. C_LIO_LIThese findings provide one of the first endeavours in understanding the physiology of brain-heart-gut interactions, and a methodology with strong biomarker development potential. C_LI