Biology subjects

Gazzaley, A.

Publications and source records attributed to Gazzaley, A..

10 recordsLinked to original sources

bioRxiv2026

Individualized brain-body signatures of positive emotions revealed by large-scale multimodal neurophysiological recording

Using one of the most comprehensive multimodal biosensing datasets in affective research, densely sampled within individuals, we asked how emotions are instantiated in each person's brain and body. Four participants viewed 168 emotion-evoking videos during 128-channel EEG and 28 autonomic, ocular and facial recordings. Cross-validated elastic-net classifiers distinguished each of 15 positive and neutral emotions from baseline in every participant (mean accuracy 87-97%). We found that no emotion was predicted by a single marker and each reflected a multimodal ensemble of cortical and autonomic activity whose composition was largely person-specific. Yet physiology-derived groupings converged selectively with self-report; Interest-Awe-Amusement-Satisfaction and Entrancement-Aesthetic Appreciation recurred across individuals based on physiology. Across emotion groups, frontal and posterior delta, posterior alpha and electrodermal activity formed a shared backbone, plausibly reflecting affective and sensory engagement, whereas cardiovascular and facial signals varied between people. This framework yields individualized, objective neurophysiological indicators of emotion, potentially aiding personalized diagnosis.

neuroscience↗

bioRxiv2026

Novelty-seeking and directed exploration scale with dissociable social network outcomes and brain systems in older adults

Social isolation and loneliness are major determinants of well-being in older adults. Shrinking social networks and age-related shifts in social behavior and decision-making may increase vulnerability to loneliness. These changes in social decision-making strategies can be conceptualized within an exploration-exploitation tradeoff framework, in which social options with known outcomes are prioritized over uncertain ones. Yet, no study has characterized how complementary decision-making strategies, undirected novelty seeking and goal-directed exploration, relate to social network constructs or are supported by distinct neural systems. These strategies capture distinct forms of decision-making: undirected novelty seeking is driven by the intrinsic salience of novel options independent of expected informational gain, whereas goal-directed exploration involves deliberately sampling uncertain options to reduce uncertainty and optimize future choices. Here, we used fMRI and a novel social bandit reinforcement task to identify dissociable social constructs and brain systems linked to undirected novelty seeking and goal-directed exploration in older adults. Undirected novelty seeking was associated with social network size and with activity of temporoparietal and mid-cingulate brain areas. Goal-directed exploration predicted subjective feelings of social connectedness and was associated with activity of anterior cingulate and prefrontal brain areas. Crucially, choice probabilities from a non-social version of the three-arm bandit task were not associated with social decision-making nor with social constructs. Our findings suggest that, in later life, dissociable social decision-making strategies, when faced with unknown options, rely on distinct neural systems supporting social network size as well as subjective feelings of social connectedness.

neuroscience↗

bioRxiv2026

The React & Rebound Model: Capturing Emotion Regulation Dynamics from Passive Wearable Data

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.

neuroscience↗

bioRxiv2025

High extraversion enhances attentional control through dynamic network reorganization

The extraversion-introversion dimension of personality is hypothesized to differ based on low or high cortical arousal, respectively. Notably, high cortical arousal in introverts is thought to underlie increased distractibility. Here, we assess fMRI while participants meditate (focused attention to their breath) under three levels of auditory distraction: no, low and high. Whereas introverts exhibited worsening attentional focus on their breath with increasing distraction, extraverts retained their ability to focus attention despite distraction. Dynamic functional connectivity analysis indicated that extraverts exhibited less globally efficient and less modular networks, which may prevent distracting stimuli from creating interference. Furthermore, connectivity strengths amongst the default mode, central executive, and salience networks were increased for extraverts and decreased in introverts during high focused attention; potentially indicating distinct cognitive processes that support attentional control. These findings support the hypothesis regarding differing levels of cortical arousal in extraverts and introverts and extend personality theory by linking the extraversion dimension to attentional control and functional connectivity dynamics.

neuroscience↗

bioRxiv2025

"Awe-scillations": EEG spectral and complexity representations of awe

Awe is a positive emotion often accompanied by sensations of vastness and unity, with known benefits for well-being and social behavior. However, its neural underpinnings remain poorly understood. We recorded electroencephalography (EEG) and autonomic physiology in 23 healthy older participants while they watched a nature-based audiovisual film and subjectively rated awe events. Awe was the predominant emotion reported - though other positive emotions (e.g., joy) were also highly rated. Awe events were associated with decreased skin conductance level (SCL), and decreased EEG alpha and theta spectral power - physiological changes associated with low arousal and positively valenced emotional states. Interestingly, awe events exhibited increased Lempel Ziv Complexity (LZC) - indicating heightened neural signal entropy and increased richness of the conscious experience. LZC was also positively associated with the intensity of the awe ratings and negatively associated with SCL. Three additional datasets with separate independent induction methods (video clips and pharmacological induction via N,N-dimethyltryptamine) also showed positive occipital LZC associations with awe - suggesting some generalizability of LZC as a neurophysiological marker of awe. These results suggest that awe evokes neurophysiological states linked to the subjective affective experience. Impact StatementAwe, an emotion of increasing interest, has been studied with fMRI and peripheral physiology - but few studies have used electroencephalography (EEG). In this EEG study, we utilize a movie-watching paradigm to explore potential physiological correlates of awe. The results present EEG-based complexity increases as a potential correlate of awe, though showing limited generalization to independent datasets and limited uniqueness compared to joy, another positive emotion.

neuroscience↗

bioRxiv2024

Long-term effects of psilocybin on dynamic and effectivity connectivity of fronto-striatal-thalamic circuits

Psilocybin has been shown to induce fast and sustained improvements in mental well-being across various populations, yet its long-term mechanisms of action are not fully understood. Initial evidence suggests that longitudinal functional and structural brain changes implicate fronto-striatal-thalamic (FST) circuitry, a broad system involved in goal-directed behavior and motivational states. Here, we apply empirical methods and computational modeling to resting-state fMRI data from a within-subject longitudinal psilocybin trial in psychedelic-naive healthy volunteers. We first show increases in FST dynamic activity four weeks after a full dose of psilocybin. We then proceed to mechanistically account for these increased dynamics, by showing that reduced structural constraints underlie increased FST dynamic activity post psilocybin. Further, we show that these reduced structural constraints come along with increased bottom-up and reduced top-down modulation of FST circuits. While cortical reductions in top-down modulation are linked to regional 5-HT2A receptor availability, increased information outflow via subcortical and limbic regions relate to local D2 receptor availability. Together, these findings show that increased FST flexibility weeks after psilocybin administration is linked to serotonergic-mediated decreases in top-down information flow and dopaminergic-mediated increases in bottom-up information flow. This long-term functional re-organization of FST circuits may represent a common mechanism underling the potential clinical efficacy of psilocybin across various neuropsychiatric disorders including substance abuse, major depression, and anorexia. Significance StatementFronto-striatal-thalamic systems, which underlie motivation and reward, go through profound functional and structural changes following psilocybin administration. We leveraged longitudinal fMRI data from a within-subject psilocybin trial in psychedelic-naive healthy participants to show that psilocybin increases fronto-striatal-thalamic dynamic activity as well as flexibility four weeks after dosing. Computational modeling revealed that this increased flexibility is mechanistically caused by reduced structural constraints on functional dynamics. Further long-term changes included increased bottom-up and reduced top-down information flow mediated by the serotonergic and dopaminergic systems. This long-term functional re-organization of fronto-striatal-thalamic circuits may reflect a common mechanism underlying clinical symptoms improvements across diagnostic groups, such as increased openness, improved well-being, and reductions in anhedonia, apathy, and substance craving.

neuroscience↗

bioRxiv2024

Human brain changes after first psilocybin use

Psychedelics have robust effects on acute brain function and long-term behavior but whether they also cause enduring functional and anatomical brain changes is unknown. In a placebo-controlled, within-subjects, electroencephalography, and magnetic resonance imaging study in 28 healthy, entirely psychedelic-naive participants, anatomical and functional brain changes were detected from one-hour to one-month after a single high-dose (25 mg) of psilocybin. Increases in cognitive flexibility, psychological insight, and well-being were seen at one-month. Diffusion imaging done before and one-month after 25mg psilocybin revealed decreased axial diffusivity bilaterally in prefrontal-subcortical tracts that correlated with decreased brain network modularity over the same time period. Decreased modularity also correlated with improved well-being. Increased cortical signal entropy at 1- and 2-hours post-dosing predicted improved psychological well-being at one-month. Next-day psychological insight mediated the entropy to well-being relationship. All effects were exclusive to 25mg psilocybin; no effects occurred with a 1mg psilocybin placebo dose.

neuroscience↗

bioRxiv2024

Brain substates induced by DMT relate to sympathetic output and meaningfulness of the experience

N,N-Dimethyltryptamine (DMT) is a serotonergic psychedelic, known to rapidly induce short-lasting alterations in conscious experience, characterized by a profound and immersive sense of physical transcendence alongside rich and vivid auditory distortions and visual imagery. Multimodal neuroimaging data paired with dynamic analysis techniques offer a valuable approach for identifying unique signatures of brain activity - and linked autonomic physiology - naturally unfolding during the altered state of consciousness induced by DMT. We leveraged simultaneous fMRI and EKG data acquired in 14 healthy volunteers prior to, during, and after intravenous administration of DMT, and, separately, placebo. fMRI data was preprocessed to derive individual dynamic activity matrices, reflecting the similarity of brain activity in time, and community detection algorithms were applied on these matrices to identify brain activity substates; EKG data was used to derive continuous heart rate. We identified a brain substate occurring immediately after DMT injection, characterized by hippocampal and medial parietal deactivations and increased superior temporal lobe activity under DMT. Deactivations in the hippocampus and medial parietal cortex correlated with alterations in the usual sense of time, space and self-referential processes, reflecting a deconstruction of essential features of ordinary consciousness. Superior lobe activations instead correlated with audio/visual hallucinations and experience of "entities", reflecting the emergence of altered sensory experiences under DMT. Finally, increased heart rate under DMT correlated positively with hippocampus/medial parietal deactivation and the experience of "entities", and negatively with altered self-referential processes. These results suggest a chain of influence linking sympathetic regulation to hippocampal and medial parietal deactivations under DMT, which combined, may contribute to positive mental health outcomes related to self-referential processing following psychedelic administration.

neuroscience↗

bioRxiv2023

The entropic heart: Tracking the psychedelic state via heart rate dynamics

A growing body of work shows that autonomic signals provide a privileged evidence-stream to capture various aspects of subjective and neural states. This work investigates the potential for autonomic markers to track the effects of psychedelics -- potent psychoactive drugs with important scientific and clinical value. For this purpose, we introduce a novel Bayesian framework to estimate the entropy of heart rate dynamics under psychedelics. We also calculate Bayesian estimates of mean heart rate and heart rate variability, and investigate how these measures relate to subjective reports and neural effects. Results on datasets covering four drugs -- lysergic acid diethylamide (LSD), dimethyltryptamine (DMT), psilocybin, and sub-anaesthetic doses of the dissociative agent ketamine -- show consistent increases in mean heart rate, high-frequency heart rate variability, and heart rate entropy during the psychedelic experience. Moreover, these effects have predictive power over various dimensions of the psychedelic experience. Changes in heart rate entropy were found to be correlated with increases in brain entropy, while other autonomic markers were not. Overall, our results show that a cost-efficient autonomic measure has the potential to reveal surprising detail about subjective and brain states, opening up a range of new research avenues to explore in both basic and clinical neuroscience.

physiology↗

bioRxiv2018

Focus on the breath: Brain decoding reveals internal states of attention during meditation

Meditation practices are used to cultivate internally-oriented attention to bodily sensations, which may improve health via cognitive and emotion regulation of bodily signals. However, it remains unclear how meditation impacts internal attention states due to lack of measurement tools that can objectively assess mental states during meditation practice itself, and produce time estimates of internal focus at individual or group levels. To address these measurement gaps, we tested the feasibility of applying multi-voxel pattern analysis (MVPA) to single-subject fMRI data to (1) learn and recognize internal attentional (IA) states relevant for meditation during a directed IA task, and (2) decode or estimate the presence of those IA states during an independent meditation session. Within a mixed sample of experienced meditators and novice controls (N=16), we first used MVPA to develop single-subject brain classifiers for 5 modes of attention during an IA task in which subjects were specifically instructed to engage in one of five states (i.e., meditation-related states: breath attention, mind wandering, and self-referential processing, and control states: attention to feet and sounds). Using standard cross-validation procedures, MVPA classifiers were trained in five of six IA blocks for each subject, and predictive accuracy was tested on the independent sixth block (iterated until all block volumes were tested, N=2160). Across participants, all five IA states were significantly recognized well above chance (>41% vs. 20% chance). At the individual level, IA states were recognized in most participants (87.5%), suggesting that recognition of IA neural patterns may be generalizable for most participants, particularly experienced meditators. Next, for those who showed accurate IA neural patterns, the originally trained classifiers were then applied to a separate meditation run (10-min) to make an inference about the percentage time engaged in each IA state (breath attention, mind wandering, or self-referential processing). Preliminary group-level analyses demonstrated that during meditation practice, participants spent more time attending to breath compared to mind wandering or self-referential processing. This paradigm established the feasibility of using MVPA classifiers to objectively assess mental states during meditation at the participant level, which holds promise for improved measurement of internal attention states cultivated by meditation.

neuroscience↗