Biology subjects

Coll, M.-P.

Publications and source records attributed to Coll, M.-P..

8 recordsLinked to original sources

bioRxiv2026

A comprehensive physiological dataset of pain and aversive modalities for pain biomarkers research

While progress has been made in identifying pain biomarkers using neuroimaging, the development of reliable EEG-based biomarkers remains challenging, limited by small sample sizes and the lack of adequate control conditions. We present a comprehensive dataset from 125 pain-free adults, comprising electroencephalogram (EEG) recordings, and behavioural, sociodemographic, and psychological data. Galvanic skin response and electrocardiogram data were also recorded in a subset of participants (n = 76). Participants received two sustained painful stimulations (thermal, chemical) and two sustained aversive non-painful stimulations (auditory, taste), each delivered twice (with and without continuous intensity ratings). Data are provided in Brain Imaging Data Structure format, where all physiological, stimulus-related, and behavioural data are synchronized within the EEG data files for easy access and analysis. Technical validation confirmed data integrity, with spectral and physiological analyses showing responses associated with stimulus intensity and subjective pain/unpleasantness levels. By providing multimodal physiological data across painful and non-painful aversive conditions, this initiative represents a valuable resource for developing or validating biomarkers and exploring the multidimensional nature of pain perception.

neuroscience↗

bioRxiv2026

Distinct EEG microstate signatures across different pain types

Pain is associated with dynamic brain reorganization. Electroencephalographic microstates can characterize transient large-scale brain states, yet findings across pain studies are inconsistent. Two features may contribute: conditions have been studied in isolation, and analytical pipelines vary widely. We applied a harmonized analysis pipeline across three pain conditions: capsaicininduced pain, assessed within participants against a pain-free baseline, and non-chronic and chronic back pain, each compared with matched controls. Using a five-minute resting-state electroencephalographic recordings we examined microstate topography, temporal expression and transition probabilities, and directly compared pain related differences across pain states. We identified five microstates (A-E), corresponding to auditory, visual, salience, and attentional networks. Capsaicin pain showed increased expression of microstate C and reduced expression of microstates A, D and E. Transitions were redistributed towards microstate C, indicating a shift toward salience-related processing at the expense of sensory and attentional dynamics. In clinical back pain, effects were smaller and diverged by pain type: non-chronic back pain showed lower microstate C occurrence, opposite in direction to the capsaicin effect, whereas chronic back pain showed lower microstate D global explained variance, suggesting salience and attentional differences in clinical pain. Direct comparisons showed weaker pain-related increases in microstate C expression in both clinical back pain groups than capsaicin pain, with additional differences involving microstates A, D and E. These findings argue against a unitary EEG microstate signature of pain and instead reveal pain-type-specific patterns of large-scale brain dynamics, with microstate C providing the clearest distinction between experimental and clinical pain.

neuroscience↗

bioRxiv2025

Expectations and uncertainty shape pain perception during learning

Pain perception is modulated by expectations and learning processes, but the influence of uncertainty in this relationship is not well established. We aimed to examine the relationship between uncertainty, pain learning and perception using hierarchical Bayesian modeling. In an aversive learning task, fifty participants learned contingencies between auditory cues and painful stimulations under changing levels of uncertainty to create periods of stability and volatility. Model-free analysis of our data suggested unexpected trials resulted in reduced accuracy and greater response times. In unexpected trials, high pain perception was reduced, while low pain perception was increased, in line with documented effects of expectations on pain perception. Computational model fitting revealed participants learning was best described by a two-level hierarchical gaussian filter model, suggesting participants adapted their beliefs at multiple levels during the task. Uncertainty influenced pain perception in opposite patterns for high and low pain stimulations: high pain perception was greater under high levels of uncertainty, while there was a non-significant trend for low pain perception to be reduced. Analyses of individual differences suggested depressive symptoms were associated with a reduced learning rate throughout the task. These results shed light on processes involved in pain learning in changing environments. They also suggest a possible relationship between learning alterations and psychological traits commonly found in chronic pain, such as depressive symptoms. PerspectiveThis article explores the influence of varying levels of uncertainty on pain perception and learning. Findings reveal that uncertainty modulates pain perception differently depending on pain intensity and that pain learning is influenced by psychological traits. These results contribute to our understanding of pain modulation in dynamic environments.

neuroscience↗

bioRxiv2023

Facial expression is a distinctive behavioural marker of pain processing in the brain

Pain is a private experience observable through various verbal and non-verbal behavioural manifestations, each of which may relate to different pain-related functions. Despite the importance of understanding the cerebral mechanisms underlying those manifestations, there is currently limited knowledge on the neural correlates of the facial expression of pain. In this functional magnetic resonance imaging (fMRI) study, noxious heat stimulation was applied in healthy volunteers and we tested if previously published brain signatures of pain were sensitive to pain expression. We then applied a multivariate pattern analysis to the fMRI data to predict the facial expression of pain. Results revealed the inability of previously developed pain neurosignatures to predict the facial expression of pain. We thus propose a Facial Expression of Pain Signature (FEPS) conveying distinctive information about the brain response to nociceptive stimulations with minimal or no overlap with other pain-relevant brain signatures associated with nociception, pain ratings, thermal pain aversiveness, or pain valuation. The FEPS may provide a distinctive functional characterization of the distributed cerebral response to nociceptive pain associated with the socio-communicative role of non-verbal pain expression. This underscores the complexity of pain phenomenology by reinforcing the view that neurosignatures conceived as biomarkers must be interpreted in relation to the specific pain manifestation(s) predicted and their underlying function(s). Future studies should explore other pain-relevant manifestations and assess the specificity of the FEPS against simulated pain expressions and other types of aversive or emotional states.

neuroscience↗

bioRxiv2023

Pain reflects the informational value of nociceptive inputs.

Pain perception and its modulation are fundamental to human learning and adaptive behavior. This study investigated the hypothesis that pain perception is tied to pains learning function. Thirty-one participants performed a threat conditioning task where certain cues were associated with a possibility of receiving a painful electric shock. The cues that signalled potential pain or safety were regularly changed, requiring participants to continually establish new associations. Using computational models, we quantified participants pain expectations and prediction errors throughout the task and assessed their relationship with pain perception and electrophysiological responses. Our findings suggest that subjective pain perception increases with prediction error, that is when pain was unexpected. Prediction errors were also related to physiological nociceptive responses, including the amplitude of the nociceptive flexion reflex and EEG markers of cortical nociceptive processing (N2-P2 evoked potential and gamma-band power). Additionally, higher pain expectations were related to increased late event-related potential responses and alpha/beta decreases in amplitude during cue presentation. These results further strengthen the idea of a crucial link between pain and learning and suggest that understanding the influence of learning mechanisms in pain modulation could help us understand when and why pain perception is modulated in health and disease.

neuroscience↗

bioRxiv2022

Neural representations of vicarious rewards are linked to interoception and prosocial behaviour

Every day we constantly observe other people receiving rewards. Theoretical accounts posit that vicarious reward processing might be linked to peoples sensitivity to internal body states (interoception) and facilitates a tendency to act prosocially. However, the neural processes underlying the links between vicarious reward processing, interoception and prosocial behaviour are poorly understood. Previous research has linked vicarious reward processing to the anterior cingulate gyrus (ACCg) and the anterior insula (AI). Can we predict someones propensity to be prosocial or to be aware of interoceptive signals from variability in how the ACCg and AI process rewards? Here, participants monitored rewards being delivered to themselves or a stranger during functional magnetic resonance imaging. Later, they performed a task measuring their willingness to exert effort to obtain rewards for others, and a task measuring their propensity to be aware and use interoceptive signals. Using multivariate similarity analysis, we show that peoples willingness to be prosocial is predicted by greater similarity between self and other representations in the ACCg. Moreover, greater dissimilarity in self-other representations in the AI is linked to interoceptive propensity. These findings highlight that vicarious reward is linked to bodily signals in AI, and foster prosocial tendencies through the ACCg.

neuroscience↗

bioRxiv2021

Egocentric Biases are Determined by the Precision of Self-related Predictions.

According to predictive processing theories, emotional inference involves simultaneously minimising discrepancies between predictions and sensory data relating to both ones own and others states, achievable by altering either ones own state (empathy) or perception of anothers state (egocentric bias) so they are more congruent. We tested a key hypothesis of these accounts, that predictions are weighted in inference according to their precision (inverse variance). If correct, more precise self-related predictions should bias perception of anothers emotional expression to a greater extent than less precise predictions. We manipulated predictions about upcoming own-pain (low or high magnitude) using cues that afforded either precise (a narrow range of possible magnitudes) or imprecise (a wide range) predictions. Participants judged pained facial expressions presented concurrently with own-pain to be more intense when own-pain was greater, and precise cues increased this biasing effect. Implications of conceptualising interpersonal influence in terms of predictive processing are discussed.

neuroscience↗

bioRxiv2018

Selective Reporting, Analytical Flexibility and Multiple Comparisons in ERP Research: The case of Pain Empathy

Empathy has received considerable attention from the field of cognitive and social neuroscience. A significant portion of these studies used the event-related potential (ERP) technique to study the mechanisms of empathy for pain in others in different conditions and clinical populations. These show that specific ERP components measured during the observation of pain in others are modulated by several factors and altered in clinical populations. However, issues present in this literature such as analytical flexibility and lack of type 1 error control raise doubts regarding the validity and reliability of these conclusions. The current study compiled the results and methodological characteristics of 40 studies using ERP to study empathy of pain in others. The results of the meta-analysis suggest that the centro-parietal P3 and late positive potential component are sensitive to the observation of pain in others, while the early N1 and N2 components are not reliably associated with vicarious pain observation. The review of the methodological characteristics shows that the presence of selective reporting, analytical flexibility and lack of type 1 error control compromise the interpretation of these results. The implication of these results for the study of empathy and potential solutions to improve future investigations are discussed.

neuroscience↗