{"paper_id":"258aea75-a317-4217-83af-97f8322fee8e","body_text":"Temporal contrast enhancement generalizes across pain and 1 \nauditory modalities 2 \nShort Title: Temporal contrast in pain and audition 3 \nJakob Poehlmannab*, Tibor M. Szikszayab, Luisa Luebkeab, Waclaw M. Adamczykabc, Kerstin 4 \nLuedtkeab and Malte Wöstmannd 5 \n 6 \na. Institute of Health Sciences, Department of Physiotherapy, Pain and Exercise Research 7 \nLuebeck (P.E.R.L.), University of Lübeck, Lübeck, Germany. 8 \nb. Center of Brain, Behavior and Metabolism (CBBM), University of Lübeck, Lübeck, 9 \nGermany. 10 \nc. Laboratory of Pain Research, Institute of Physiotherapy and Health Sciences, The Jerzy 11 \nKukuczka Academy of Physical Education, Katowice, Poland. 12 \nd. Department of Psychology, University of Lübeck, Lübeck, Germany 13 \n*Corresponding author:  14 \nJakob Poehlmann, University of Luebeck, Ratzeburger Allee 160, 23562 Lübeck, Germany 15 \nTelephone: +49 451 3101 85 48; Fax:  +49 451 3101 1154 , E-mail: jakob.poehlmann@uni-16 \nluebeck.de 17 \nData availability statement: Data are available on reasonable request. 18 \nFunding: Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - 493000854.  19 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n2 \n \nAbstract  20 \nThe h uman brain continuously  processes sensory inputs whose perceptual impact  depends on 21 \nstimulus intensity, salience, and context. Temporal filtering shapes this processing by dynamically 22 \nmodulating neural responses according to stimulus repetition , temporal structure, and predictive 23 \ncontingencies. Higher-order percepts such as pain are likewise a subject to temporal filtering, as 24 \nexemplified by  temporal contrast enhancement (TCE) , a stimulation paradigm eliciting pain 25 \ninhibition. However , g iven the prevalence of filtering mechanisms across sensory domains, it 26 \nremains unclear whether TCE is specific to pain or represents a supramodal filtering mechanism. 27 \nHere, we contrasted behavioral and neurophysiological responses, including 28 \nelectroencephalography and pupillometry, in a TCE paradigm for painful heat versus 29 \nuncomfortable auditory stimulation . We sought to establish whether TCE generalizes across 30 \nmodalities and bases on similar or distinct underlying neurophysiological processes.  Human 31 \nparticipants took part in either a purely behavioral investigation (n = 33) or in a neurophysiological 32 \nand behavioral investigation (n = 29) . Both painful heat and loud sounds  induced TCE effects, 33 \nsuggesting a supramodal temporal filtering mechanism with modality-specific temporal dynamics. 34 \nIncreasing pupil size and decreas ing power of neural alpha oscillations (~10 Hz) with higher 35 \npainful heat indicate bottom-up modulation of the autonomic nervous system and a release of 36 \nneural inhibition, respectively. Critically, expectation of pain – but not loud sound – induced an 37 \nalpha power increase, demonstrating to-down contributions to temporal filtering of pain. However, 38 \nno direct neurophysiological correlate s of subjectively experienced TCE effect s were found. 39 \nFindings suggests that a supramodal  temporal filtering mechanism with modality -specific 40 \nneurophysiological dynamics shapes the processing of aversive stimulation. 41 \nKeywords: Temporal Filtering, Temporal Contrast Enhancement, Offset Analgesia, Auditory 42 \nSystem, Pain, Sensory Processing  43 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n3 \n \nAbbreviations 44 \nANS  Autonomic nervous system 45 \nCT  Constant trial 46 \nEEG  Electroencephalography 47 \neVAS  Electronic visual analogue scale 48 \nFDR  False discovery rate 49 \nfMRI  Functional magnetic resonance imaging 50 \nOT  Offset trial 51 \nTCE   Temporal contrast enhancement  52 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n4 \n \nIntroduction  53 \nHuman environments contain a plethora of sensory inputs. Sensory integration is a complex 54 \nprocess dependent on  stimulus intensity, salience and context  (1). Therefore, diverse filtering 55 \nmechanisms are required to selectively enhance specific aspects of stimuli, evaluate their 56 \nrelevance, and modulate their perceptual processing (2,3). Commonly, these filtering mechanisms 57 \nare divided into spatial  and temporal domains of perceived input , which can be observed  in all 58 \nsensory systems (visual (4,5), auditory (6–8) tactile (9,10)). Well-adapted filtering mechanisms 59 \nhelp us make accurate and reliable judgements in constantly changing sensory environments (11). 60 \nHere, we test the hypothesis that temporal filtering in different modalities share s a common 61 \nperceptual and neurophysiological basis. 62 \nConvergences in temporal filtering have been documented across sensory domains. In the 63 \ncontext of auditory perception, temporal summation  - alternatively referred to as temporal  64 \nintegration (12) or temporal sound summation  (13) -  describes the phenomena of  a perceived 65 \nloudness increase when a tone of constant volume  is presented for a longer duration. Temporal 66 \nfiltering of auditory percepts is of utmost importance, due to its relevance in vocalization and 67 \nspeech recognition (14), as well as in avoiding uncomfortably loud sound . Temporal summation 68 \nlikewise characterizes nociceptive perception (15), where adaptive temporal filtering is vital for 69 \naverting tissue injury and protecting the organism. Additional similarities can be observed in 70 \nfiltering processes resulting in adaptation to perceived stimulus inputs. Such phenomena can be 71 \nobserved in  (acute) pain or auditory adaptation . When an individual is exposed to a constant 72 \nstimulus within the appropriate context and depending on the stimulus parameters, a reduction in 73 \nthe perceived intensity of the stimulus can be observed  (11,16,17). By contrast, when context 74 \nsignals threat, through salience, magnitude, or affective associations, temporal filtering can 75 \namplify perception indicated by pain intensification (17,18) or temporal sound summation (13), 76 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n5 \n \nhighlighting the importance of these  factors. Additional current  evidence indicates temporal 77 \nfiltering processes share similar mechanisms across modalities and sensory systems (19–22). 78 \nHowever, despite their high relevance, the extent to which temporal filtering in auditory and pain 79 \nprocessing is based  on common perceptual and physiological mechanisms is not yet fully 80 \nunderstood.  81 \nTemporal contrast enhancement (TCE), a putative component  of the endogenous pain 82 \nmodulatory system, is conceptualized as a temporal filtering process whose mechanisms remain 83 \nunclear (23–25). Commonly referred to as offset analgesia, is characterized by a disproportionally 84 \nlarge reduction in perceived pain in response to a slight decrease in noxious stimulus intensity(25–85 \n27). A variety of mechanisms distributed along the neuroaxis have been postulated as potential 86 \nmediators of TCE . Several brain imaging studies using functional magnetic resonance imaging 87 \n(fMRI) showed increased activity  of cortical  structures such as the primary (24,25,28) and 88 \nsecondary (28) somatosensory cortex, ventromedial (25) and dorsolateral (23,24) prefrontal cortex 89 \nand subcortical structures such as the putamen and nucleus accumbens (23), insula (24,25) and the 90 \nspinal cord (29) as evidenced by greater blood oxygenation levels during the TCE interval 91 \ncompared to a control condition. Additionally, structures of the brainstem previously linked to 92 \ndescending pain modulation such as the periaqueductal grey and rostro -ventromedial medulla 93 \nshowed increased activity during TCE (25,28,30).  94 \nInterestingly, studies investigating the temporal dynamics of TCE using 95 \nelectroencephalography (EEG) seem to be lacking in the field. General investigations of both tonic 96 \nand phasic pain observed in EEG have been conducted, with the main focus being oscillations in 97 \nthe alpha range ( ~10Hz), showing a prominent pattern of reduced alpha power during tonic and 98 \nphasic painful stimuli (31–33). This might relate to the proposed functional inhibition of situational 99 \nirrelevant information (34–38), which is well-established by alpha power modulation in auditory 100 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n6 \n \nattention research  (39–41). Additional temporally sensitive and objective measures, such as 101 \npupillometry, have been used to characterize neurophysiological correlates of pain and auditory 102 \nprocessing. Changes in pupil diameter are closely related to autonomic nervous system activity 103 \nand have been linked to perceived stimulus intensity and arousal, particularly in response to painful 104 \nstimuli (42,43). In auditory research, pupil dilation has similarly been associated with loudness of 105 \nthe stimuli, salience, and aversiveness (44–46), highlighting its relevance for tracking perceptual 106 \nand attentional processes. 107 \nHere, we hypothesize that the effects of TCE on noxious stimuli may not  reflect pain-108 \nspecific processes but  rather could be indicative of a general temporal filtering mechanism in 109 \nresponse to salient stimuli . To determine whether observed effects in pain -research are modality 110 \nspecific or merely reflect general arousal, prior studies have employed salience-matched control 111 \nstimuli; nevertheless the evidence still remains equivocal and the issue remains unresolved (31,47–112 \n50). We therefore conducted a multimodal experiment to determine whether TCE is specific to 113 \npain. This was achieved  by applying painful heat or uncomfortable auditory stimulation using a 114 \ntypical TCE paradigm. The investigation encompassed behavioral and neurophysiological 115 \nresponses (EEG, pupillometry), with the objective of improving our understanding of temporal 116 \nfiltering mechanisms. 117 \nResults  118 \nA total of 62 healthy volunteers were recruited in this study (behavioral investigation: n = 119 \n33, behavioral + neurophysiological investigation: n = 29). All participants tolerated the selected 120 \nstimulus intensities without difficulty and exhibited no signs of adverse events  (see S1 and S2 121 \nTables for details) . Figure 1 illustrates the study design.  Both investigations used a similar 122 \nexperimental approach to investigate behavioral responses to the TCE paradigm. Thus, the 123 \nfollowing analysis consists of the combined behavioral data of both experiments. An overview of 124 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n7 \n \nstimulation parameters , as well as additional analyses for each individual experiment can be 125 \naccessed in the Materials and Methods Section and the Supporting Information (S3 – S5 Tables). 126 \n 127 \nFigure 1. Study design. Schematic representation of the study design  of both experiments . After preparation, participants 128 \nunderwent a training & familiarization phase to accustom to stimuli and the operation of the electronic visual analogue scale 129 \n(eVAS). In Experiment 1 (top of the figure), stimulus intensities were individually calibrated. The experimental procedure was split 130 \ninto two blocks (1 per modality) consisting of 8 trials with offset (OT) or constant (CT) trials in pseudorandomized sequence . In 131 \neach trial, participants rated their sensory experience using the eVAS . A two-minute pause was conducted after each trial  and a 132 \nfive-minute break was conducted after switching to the other modality . In Experiment 2 (bottom of the figure) fixed stimulus 133 \nintensities were used. The experimental procedure was split into four blocks (2 per modality) consisting of 10 trials with offset (OT) 134 \nor constant (CT) trials in pseudorandomized sequence. Each trial was followed by a two -minute break, and after each modality 135 \nblock participants had a five-minute break. The first two trials of each block were fixed to include an OT and CT (being randomized 136 \nin order) and were used to collect the behavioral response. The remaining 8 trials did not include any eVAS ratings, only collecting 137 \nneurophysiological responses. 138 \nTemporal contrast enhancement is robust in heat-induced pain and 139 \naversive auditory stimulation 140 \nParticipants were either presented with a sine -tone via headphones (1000 Hz) or with a 141 \nthermal heat stimulus on the left forearm using a thermal contact stimulator. Stimulation intensity 142 \nwas either constant across a duration of 35  s (constant trial) or increased in the time interval 143 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n8 \n \nbetween 10 and 20  s ( offset trial; Figure 2). First, we tested whether participants’ ratings of 144 \nexperienced pain (heat) or discomfort (sound) would vary as a function of time interval (T1: 5-10 145 \ns, T2: 15-20 s, T3: 25-30 s), trial type (OT: offset trial, CT: constant trial)  and modality (heat, 146 \nauditory). Given a significant main effect of modality and significant interactions involving 147 \nmodality (see S3 Table for details), separate ANOVAs were conducted for each modality. 148 \n 149 \nFigure 2: Behavioral Temporal Contrast Enhancement (TCE) response in two modalities. Means and standard errors of the 150 \nmean (SEM) for behavioral responses are displayed as obtained by an electronic visual analogue scale (eVAS). Thermal stimulation 151 \n(A) and auditory stimulation (B) both induced significant (*, p < .05) TCE effects in T3 when comparing offset (OT) (darker colors) 152 \nand constant (CT) (lighter colors) trials. The correlation of TCE effects (C) (CT-OT at T3) (green = behavioral experiment, black 153 \n= neurophysiological experiment) between both modalities was not significant. Boxplots of eVAS ratings (D) for each of the fo ur 154 \nconditions split into three relevant time intervals (T1: 5 -10s, T2: 15 -20s, T3: 25 -30s). Significant (p < .05) within -modality 155 \ncomparisons indicated by solid lines, between-modality comparisons indicated by dashed lines.  156 \nANOVAs revealed  interactions of  time interval x trial type  for auditory (F (2, 122) = 157 \n102.39, p < 0.001,  p2 = 0.63) and thermal (F (2, 122) =186.55, p < 0.001,  p2 = 0.75) stimulation. 158 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n9 \n \nComparing trials using false discovery rate (FDR) -corrected post -hoc testing for auditory 159 \nstimulation revealed no difference between OT and CT during T1 (p = 0.71). However, we found 160 \nsignificantly higher discomfort ratings for  OT vs. CT in T 2 (p < 0.0 01) and a reversal of this 161 \ndifference in T3 (p < 0.0 01), indicating that a return to the stimulus intensity of T1 induced a 162 \nsignificant TCE effect in the interval of interest (T3). Similarly, post hoc testing for thermal 163 \nstimulation showed no difference between OT and CT during T1(p = 0.30), but significantly higher 164 \npain ratings for OT vs. CT in T2 (p < 0.0 01) and a reversal of this difference in T3  (p < 0.001). 165 \nThese findings demonstrate that TCE  – a significant and disproportionate reduction in perceived 166 \nintensity following a brief decrease in stimulus intensity  – occurs for both, painful heat and 167 \naversive auditory stimulation. 168 \nHaving established behavioral TCE effects for thermal and auditory stimulation, we next 169 \ntested the association between  the two. Across participants, TCE effects (i.e. the OT - CT 170 \ndifference in T3) were not significantly correlated between auditory and thermal stimulation (r = 171 \n0.15, p = 0.25; BF₁₀ = 0.33), indicating a modest tendency of the results to be in favor of the null 172 \nhypothesis. Additionally, to test temporal filtering within each modality, we calculated dependent-173 \nsamples t-tests comparing T1 and T3 within each trial type. For auditory stimulation, we found 174 \nsignificantly lower discomfort ratings in T 1 compared to T3 despite constant stimulation (CT; t 175 \n(61) = −5.69, p < 0.001, d z = 0.40, M DIFF = −14.32), indicating temporal loudness summation. 176 \nHowever, no difference between T1 and T3 was found for offset trials (OT; t (61) = 0.93, p = 0.36, 177 \ndz = 0.08, MDIFF = 2.46). To the contrary, for thermal stimulation, pain ratings decreased from T1 178 \nto T3 despite constant stimulation (CT, t ( 61) = 5.05, p < 0.001, d z = 0. 45, MDIFF = 14.53), 179 \nindicating temporal adaptation. Furthermore, a pronounced decrease in pain ratings from T1 to T3 180 \nwas observed for offset trials (OT, t (61) = 12.17, p < 0.001, dz = 1.74, MDIFF = 62.57), resulting 181 \nin a strong TCE effect. A visual representation of changes over time using boxplots can be seen in 182 \nFehler! Verweisquelle konnte nicht gefunden werden..  183 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n10 \n \nPupil size reflects perception of pain but not auditory discomfort 184 \nWe next examined the event-related pupil dilation (Figure 3) to determine whether TCE is 185 \naccompanied by modality-dependent autonomic modulation, contrasting auditory versus thermal 186 \nstimulation. Similarly to the behavioral data, the main effect modality and all interaction effects 187 \nincluding modality reached significance (p < 0.001; S6 Table). For auditory stimulation, we found 188 \na significant main effect of ‘time’ (F (2, 56) = 32.67, p < 0.001,  p2 = 0.54). FDR corrected post 189 \nhoc testing revealed significant reduction in the pupil size for T3 vs. T2 (p < 0.001), T3 vs. T1 (p 190 \n< 0.001) but not for T2 vs. T1 (p = 0.74). This indicates a gradual decrease in pupil size during the 191 \ntrial. 192 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n11 \n \n 193 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n12 \n \nFigure 3 Mean pupil response over time. Mean pupil diameter (mm) over time was measured for auditory (A) and thermal (B) 194 \nstimulation. Thermal stimulation induced significant changes (* , p < .05; cluster -based permutation test ) in the pupil diameter 195 \nwhen comparing offset trials (OT, darker colors) with constant trials (CT, lighter colors). No significant clusters could be identified 196 \nfor auditory stimulation, despite visually observable changes to stimulus onset and offset. The timing of the stimulation intensity is 197 \ndisplayed as a solid (OT) and dashed (CT) line at the top of the figure and was similar for both modalities.  Mean pupil diameter 198 \n(mm) for each condition (C) split into three time intervals (T1: 0-5s, T2: 15-20s, T3: 20-25s). Significant (p < .05) between-modality 199 \ncomparisons indicated by dashed lines. 200 \nFor thermal stimulation, there was a significant interaction effect of ‘trial type’ and ‘time’ 201 \n(F (2, 56) = 64.35, p < 0.001,  p2 = 0.70). Comparing trial types at different time intervals , we 202 \nfound significantly enhanced pupil size for OT vs. CT in T2 (p < 0.001) but not in T1 (p = 0.88) 203 \nand T3 (p = 0.08). In addition to these planned statistical analyses, we performed exploratory 204 \ncluster based permutation test (51), comparing OT and CT during the entire trial time course (see 205 \nFigure 3). 206 \nNeural alpha power reflects pain sensation and expectation 207 \nFinally, we tested whether commonalities and differences in behavioral TCE effects for 208 \nthermal versus auditory stimuli were reflected in neural oscillatory EEG responses (Figure 4). For 209 \ndata analysis , we used baseline -corrected time frequency representations of oscillatory power , 210 \naveraged across selected channels and frequencies in the  alpha range ( 7–13 Hz) for the defined 211 \ntime bins of interest (for details, see Materials and methods). A visual representation of the event-212 \nrelated potential can be accessed in the Supporting Information (S8 Fig. and S9 Fig.). 213 \nWe first calculated a combined repeated -measures ANOVA including both modalities  214 \n(painful heat & aversive sound), which can be accessed in the Supporting Information (S7 Table). 215 \nUnlike the pupillometry and behavioral results,  interactions involving modality did not reach 216 \nsignificance (all p > 0.1). For interpretability, we nonetheless conducted two modality -specific 2 217 \n(trial type) x 3 (time interval) ANOVAs.  For auditory stimulation , the analysis revealed a  218 \nsignificant main effect of ‘time’ (F (2, 56) = 9.92, p < 0.001,  p2 = 0.26), while thermal stimulation 219 \ndisplayed a significant interaction effect of ‘trial’ and ‘time’ (F (2, 56) = 5.91, p = 0.005,  p2 = 220 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n13 \n \n0.17). Comparing the different time intervals in auditory simulation with FDR corrected post-hoc 221 \ntests showed a significant difference in alpha power between T1 and T2 (p = 0.033), T2 and T3 (p 222 \n= 0.004), and T3 and T1 (p = 0.004), indicating an overall alpha power increase over time.  The 223 \ninteraction effect in thermal stimulation was driven by  a significant difference between OT and 224 \nCT only for T2 (p = 0.002) but not for T1 (p > 0.05) and T3 (p > 0.05). 225 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n14 \n \n 226 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n15 \n \nFigure 4: Mean alpha power over time for both modalities. Auditory (A) and thermal (B) stimulation-induced mean alpha power 227 \n(7–13 Hz) averaged across centro-occipital electrodes (P7, P3, O1, C3, POz, Pz, CPz, P8, P4, O2, C4) . Topographic maps show 228 \nspatial distributions of alpha power at time points 0, 10, 20 and 30 seconds (color limits: yellow = +2dB, blue = –2dB). Comparing 229 \nalpha oscillat ory power  during Offset (OT) (darker colors) and Constant (CT) (lighter colors) trials using cluster -based 230 \npermutation tests resulted in significant (* , p < .05 ) differences only during thermal stimulation . Mean (alpha) power for each 231 \ncondition (C) split into the three time intervals of interest (T1: 0-5s, T2: 10-15s, T3: 20-25s). Significant (p < .05) within-modality 232 \ncomparisons indicated by solid lines, between-modality comparisons indicated by dashed lines. 233 \nNotably, significant alpha modulation in the  T2 interval  for thermal stimulation  was 234 \nattributable to two distinct underlying mechanisms reflecting the occurrence and expectation of 235 \nthe stimulus (Figure 5). To differentiate these, we performed post-hoc testing to compare a baseline 236 \ninterval during T1 (5–10 s) to the time interval wherein a cluster-based permutation test revealed 237 \na significant difference for OT vs. CT (10.6 - 17.8 s; see Figure 4). First, the increase in thermal 238 \nstimulation intensity induced an alpha power decrease in OT trials, resulting in significantly lower 239 \nalpha power compared to T1  (t (28) = −2.61, p = 0.015, dz = 0.48, MDIFF = −0.40). Second, an 240 \nomission of the expected increase in thermal stimulation intensity induced an alpha power increase 241 \nin CT trials compared to the baseline interval during T1 (t (28) = 3.34, p = 0.002, dz = 0.62, MDIFF 242 \n= 0.49). These findings demonstrate that temporal filtering of pain sensation (but not auditory 243 \ndiscomfort) reflects both stimulus -driven (bottom -up) and expectation -driven (top -down) 244 \nmechanisms. 245 \n 246 \nFigure 5: Topographic distribution of alpha power. Stimulation-induced mean alpha power  (7–13 Hz) averaged across centro-247 \noccipital electrodes (P7, P3, O1, C3, POz, Pz, CPz, P8, P4, O2, C4). Topographic maps show spatial distributions of alpha power 248 \nat the significant time point (11 sec – 17 sec, one topography per second) of a cluster-based permutation test (* p < .05) comparing 249 \noffset (OT) and constant (CT) trials (color limits: yellow = +2dB, blue = –2dB). 250 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n16 \n \nDiscussion 251 \nTemporal filtering operates across sensory modalities, including vision, audition, and pain 252 \nperception (20,21). Here, we aimed to delineate behavioral and (neuro -)physiological substrates 253 \nof temporal filtering and  to assess  its specificity to pain  and unpleasantness . To this end, we 254 \nemployed the phenomenon of temporal contrast enhancement , a  temporal filtering mechanism 255 \nthought to underlie offset analgesia (26). TCE was elicited by pain-inducing heat and aversive 256 \nsounds, indicating a supramodal temporal filtering process with distinct temporal dynamics across 257 \nmodalities. Pupil dilation, indexing autonomic nervous system activation, and alpha -band 258 \noscillations, reflecting cortical inhibition, were both modulated by temporal increases in noxious 259 \nheat but not by auditory stimulation. These findings suggest pain-specific temporal filtering acting 260 \non both the processing of painful input and its temporal expectation. 261 \nModality-specific processes underlie temporal contrast enhancement  262 \nConsistent with prior evidence, we were able to successfully induce TCE using thermal 263 \nstimulation. Noxious heat is known to produce robust TCE effects, indicated by statistically 264 \nsignificant decreases in pain sensation following a short  heat offset (52). To our knowledge, this 265 \nis the  first experiment investigating TCE using non-painful aversive auditory stimuli, 266 \ndemonstrating that TCE reflects a modality -general (i.e., supramodal)  mechanism of afferent 267 \ncontrast filtering rather than a nociception-specific process. In addition to domain-general effects, 268 \nwe observed modality -specific patterns  in subjective ratings , suggesting  intricate processing  269 \ndifferences between modalities during the stimulation paradigm. When comparing different time 270 \nintervals (T1 vs. T3) during constant stimulation, we found pain ratings decreasing over time while 271 \nthe opposite was observed for subjective auditory discomfort ratings . We argue that these results 272 \nrepresent two different temporal filtering mechanisms. First,  adaptation to pain , which is well-273 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n17 \n \nknown to be induced by tonic heat (16,53). Second, temporal sound summation, reflecting neural 274 \nintegration of auditory energy over time (12,13).  275 \nComparing ratings between time windows of interest  for offset trials, we found a typical 276 \ndecrease in perceived pain following heat offset (T3) compared to baseline (T1) . In the auditory 277 \nmodality, however, the same contrast was not significant, suggesting a differently constituted TCE 278 \neffect. Here, TCE was driven by a gradual increase in TSS during constant stimulation, which was 279 \nabsent during offset trials, thereby yielding a comparable overall TCE magnitude. Taken together, 280 \nthese results indicate  temporal pain inhibition but an absence of such an effect for auditory 281 \nstimulation. Importantly, the dissociation of underlying generators of TCE effects for pain and 282 \nauditory stimulation receives further support from the absence of a correlation between TCE 283 \neffects, suggesting  partly independent generators of what appears like a common filtering 284 \nmechanism.  285 \nNeurophysiological signatures of filtering perception of pain and 286 \nauditory discomfort 287 \nAlongside subjective behavioral responses, we collected  objective neuro(physiological) 288 \nmeasures (pupillometry and EEG ) aiming to better understand the differences between the 289 \nobserved TCE effects for auditory vs. thermal stimulation. Thermal stimulation induced significant 290 \ndifferences in pupil size between OT and CT in T2, the interval with the highest stimulus intensity. 291 \nReactive increases in pupil diameter to pain -inducing stimuli may reflect autonomic nervous 292 \nsystem (ANS) activation, specifically sympathetic arousal associated with heightened awareness 293 \nand the fight -or-flight response, as observed in previous studies on pupillary responses to pain  294 \n(43,54–57). Our observed phasic increases in pupil diameter likely reflect bottom-up processes 295 \ninduced by increases in stimulus temperature and are in line with previous research (58). However, 296 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n18 \n \nauditory stimulation did not display such trial  type-specific differences, only eliciting significant 297 \ndecreases of pupil diameter over time. This suggests that auditory discomfort did not elicit sizeable 298 \nmodulation of activity in the ANS. Possible explanations for this difference could be factors such 299 \nas stimulus intensity or salience, with painful stimulation arguably resulting in a higher perceived 300 \nthreat level compared to auditory stimulation , hence inducing far greater changes in pupil 301 \ndiameter. 302 \nConsistent with the pupillary dynamics, time –frequency EEG analyses revealed a similar 303 \nmodality-specific pattern: thermal stimulation elicited a significant alpha power reduction during 304 \noffset trials in T2, which was not observed for auditory stimulation. A reduction of alpha power in 305 \nresponse to painful stimulation is in line with previous reports of alpha decreases accompanying 306 \nincreased pain perception (31,32,59). Moreover, when comparing T1 and T2 in OTs, we observed 307 \na significant alpha desynchronization, reflecting bottom -up processes associated with increased 308 \nstimulus intensity. In contrast, CTs exhibited significant alpha synchronization  (i.e., an alpha 309 \npower increase)  that may reflect top -down processes, possibly induced by  expectation of an 310 \nincrease in painful stimulation.  This agrees  with prior research observing top -down processes 311 \ninfluencing alpha oscillations (60). For auditory stimulation, we hypothesized similar spatial and 312 \ntemporal patterns of oscillatory activity ; however, no significant changes in alpha power were 313 \nobserved for either stimulation pattern. Given the comparable stimulation paradigm employed in 314 \nboth modalities, one could expect that participants would manifest a comparable increase in alpha 315 \npower, driven by the anticipation of a change in stimulus intensity. However, no such effects were 316 \nobserved, which lends further support to the view that the neural modulation and representation of 317 \nauditory discomfort differ from that of painful stimulation. 318 \nInterestingly, we did not observe any neurophysiological changes mirroring the TCE effect 319 \nthat we observed in behavior. Neither pupillometry, nor EEG displayed  any significant 320 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n19 \n \nmodulations by trial type (OT vs. CT) during T3. Based on literature showing a robust link between 321 \ntonic pain and reduced alpha oscillatory power, we hypothesized that the TCE effect would elicit 322 \nmeasurable changes in alpha activity —potentially an alpha increase reflecting the experienced 323 \nrelief - as it has been reported for placebo analgesia (61,62). Contrary, we did not observe any 324 \nrepresentation of the behavioral TCE effects in neural recordings. One plausible explanation could 325 \nbe that  the brain regions responsible for processing or mediating TCE are mainly located 326 \nsubcortically, which would be less accessible to surface EEG. Previous fMRI studies have reported 327 \nchanges to activity in the insula (24,25), structures of the brainstem (25,28), putamen and nucleus 328 \naccumbens (23) or the spinal cord (29). It might thus be that these structures are more relevant to 329 \nthe construction of TCE compared to the more superficially located ones.  Furthermore, one should 330 \nbe cautious expecting identical findings when comparing fMRI to EEG, since both imaging 331 \ntechniques show distinct sensitivities to neural and hemodynamic processes, temporal and spatial 332 \nresolution, and often can display different correlations depending on measured frequencies 333 \n(63,64). Additionally, subjective experiences such as changes in pain perception may not always 334 \nalign with objective indices, which could be the case for TCE. Our pupillometry findings provide 335 \npartial support for this hypothesis, since both modalities displayed temporal filtering as evidenced 336 \nby decreases in pupil diameter over time. However, these temporal patterns did not correspond 337 \nwith the observed patterns in the subjective domain, where only pain decreased over time, but 338 \nauditory discomfort increased. However, to our knowledge, studies investigating TCE employing 339 \nobjective measures besides fMRI are  scarce (65–67) making it difficult to assess the extent to 340 \nwhich subjective and physiological responses to TCE diverge  and whether our findings reflect 341 \nsuch an incongruence.  342 \nWe replicated robust behavioral TCE responses in both investigations using individually 343 \ncalibrated and fixed -stimulus approaches. For the neurophysiological investigation, we adopted 344 \nthe fixed-stimulus approach, as our first study and previous work indicate that it is better suited 345 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n20 \n \nfor assessing neurophysiological outcomes (68,69). However, this approach may have led to a 346 \nlower perceived stimulus intensity, which could have potentially reduced our observed effects, 347 \nespecially in pupillary reactions to auditory stimuli. Regardless, we could not have increased the 348 \nstimulation intensity further since this could have meant potential harm to the participants (70). 349 \nNonetheless, we would attribute the smaller changes in pupil diameter to auditory stimulation, to 350 \nthe underlying aversiveness and threat level that painful stimuli impose on the organism.  In 351 \naddition, modality-specific patterns of temporal dynamics were observed, particularly represented 352 \nin the behavior of participants. An identical stimulation paradigm was employed for all trials, 353 \nenabling direct comparison between modalities and providing a common framework for 354 \ninterpreting differences in temporal filtering dynamics. As demonstrated in previous research, 355 \nTCE has been consistently identified as a highly robust filtering mechanism in pain. TCE effects 356 \ncan be induced with a variety of stimulus intervals, temperature changes and even repeated instead 357 \nof tonic stimuli  (52,71,72). However, future research could benefit from the use of variable 358 \nstimulus sequences to further improve our understanding of these supramodal temporal filtering 359 \ndynamics, driving TCE across modalities. Additionally, future research should aim to characterize 360 \nthe temporal dynamics of TCE in different sensory modalities without compromising spatial 361 \nresolution, ideally incorporating approaches that target subcortical regions potentially underlying 362 \nthe effect. Further exploration of pain -specific paradigms, and of potential shared filtering 363 \nmechanisms across sensory modalities, may provide deeper insight into how such processes shape 364 \nperceptual experience in our multisensory environment. 365 \nConclusion 366 \nIn this study, we probed the specificity of temporal contrast enhancement  to pain. We 367 \nsuccessfully induced TCE using pain-inducing heat but also auditory stimulation, suggesting the 368 \nexistence of  a supramodal temporal filtering mechanism . However, divergences in temporal 369 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n21 \n \nfiltering dynamics indicate that adaptation to pain , but temporal summation of sound underlie 370 \ncontrast enhancement. Modality-specific modulations in pupil size and neural oscillations indicate 371 \nthat painful heat – but not auditory – stimulation increases activity of the ANS and neural 372 \nrepresentation of an occurring, as well as an expected but omitted increase in stimulation intensity. 373 \nThese findings demonstrate the intricate dynamics of temporal filtering mechanisms and their 374 \n(neuro)physiological basis. 375 \nMaterials and methods  376 \nBehavioral investigation of the TCE effect in auditory stimulation 377 \nParticipants 378 \nParticipants (n = 33, 22f; age = 23.7, SD = 6.0) were included if they subjectively reported 379 \nbeing healthy and pain-free on the day of the procedure. Exclusion criteria were chronic pain (> 3 380 \nmonths) within the last two years, diagnosed systemic, neurological, cardiovascular or psychiatric 381 \ndiseases and being with diagnosed hearing loss or tinnitus. All participants were asked not to take 382 \nany painkillers, consume alcohol or undertake any strenuous physical activity 24 hours before 383 \nparticipating in the study. To characterize the study sample age, sex at birth, body mass (kg), 384 \nstature (cm), handedness and general fear of heat pain and fear of loud noises on a numerical rating 385 \nscale from 0 (no fear) to 100 (highest possible fear) were recorded for each participant. To measure 386 \nnoise sensitivity the Weinstein Noise  Sensitivity Scale (WNSS) was used (73). In addition, the 387 \nPain Vigilance and Awareness Questionnaire (PVAQ) was used to measure attention to pain and 388 \nassesses awareness, consciousness, vigilance, and observation of pain (74) and the Pain 389 \nCatastrophizing Scale (PCS) was used to assess the catastrophizing behavior (75). 390 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n22 \n \nThe study was approved by the Ethics Committee of the University of Lübeck (2023-633) 391 \nand conducted in accordance with the Declaration of Helsinki. The methodology was preregistered 392 \non the Open Science Framework (OSF; https://osf.io/643kg).  393 \nEquipment  394 \nAll heat stimuli were applied with a thermal contact stimulator (TCS; André Dufour, 395 \nUniversity of Strasbourg, France). The probe of the TCS has a total stimulation zone of 9 cm2 (five 396 \nequal stimulation zones, each 0.74 x 2.4cm  = 8.88cm2) and was applied to the  left forearm. The 397 \nprobe weighs 440g and the TCS has a temperature range of 0°C to 60°C, adjustable at 0.1°C 398 \nintervals. The maximum temperature rise and fall rate is 100°C/second. For auditory stimulation, 399 \na 1000-Hz sine wave tone sampled at 44.100Hz, generated using Adobe Audition (Adobe Systems 400 \nSoftware, Dublin, Republic of Ireland ), was applied. The sound was presented using over -ear 401 \nheadphones (PXC 550 -II, Sennheiser, Wedemark, Germany) . Probing pain intensity was 402 \nconducted with a Python -based eVAS (76,77). The eVAS was displayed using a  computer and 403 \nranged from 0 \"no sensation\" to 200 \"worst heat pain imaginable\", while a value of 100 represented 404 \nthe “pain threshold” for thermal stimulation . For auditory stimulation, the same eVAS was used 405 \nbut it displayed different anchors, 0 representing “no sound audible”, 200 being “maximum 406 \ndiscomfort imaginable” and 100 representing the “discomfort threshold”. 407 \nFamiliarization and calibration procedure 408 \nBefore attending the main part of the experiment, participants were familiarized to the 409 \nrating procedure and stimulus intensities. For this, they received three different stimulus 410 \nintensities, a high (48°C, 100dB) , low (33°C, 49dB)  and an intermediate (40°C, 82dB) level of 411 \nintensity for thermal and auditory stimulation, respectively. Afterwards, the stimulation intensities 412 \nfor each modality were calibrated, using a staircase procedure (S10 Fig.  in the Supporting 413 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n23 \n \nInformation). Participants were asked to continuously rate their sensory experience using the 414 \neVAS scale. The calibration consisted of ascending stimulation intensities, where each stimulation 415 \nwas applied for ten seconds , followed by ten seconds of either no stimulation (0dB) or baseline 416 \ntemperature (32°C) depending on the applied modality. The stimulation started at either 33°C or 417 \n49dB and increased in 1°C or 3dB steps up until the highest stimulation intensity of 48°C or 100dB 418 \nwas reached. This procedure was repeated for each modality with the modalities being alternated. 419 \nThe stimulation intensities were then derived from the second iteration of each modality by using 420 \nstimulation intensities that produced perceived pain intensities  of 150/200 and 175/200 on the 421 \neVAS. These values were used for the initial stimulation intensity (T1) and increase in stimulation 422 \nintensity (T2) in offset trials (see Experimental paradigm).  Mean heat pain that corresponded to 423 \n150 points on the 0- to 200-point eVAS was 46.4°C (SD 0.8°C) and 47.4°C (SD 0.8°C) for 175/200 424 \npoints respectively. Mean sound stimulation parameters for 150/200 and 175/200 eVAS ratings 425 \nwere 90.8dB (SD 8.0dB) and 95.0dB (SD 7.5dB), respectively. 426 \nExperimental paradigm 427 \nA TCE paradigm with three successive periods (T1-T2-T3) consisting of an OT and a CT 428 \nwas performed (78). CTs were administered for a duration of 35 seconds, during which continuous 429 \nheat or sound stimulation was applied at a calibrated intensity corresponding to 150/200 on the 430 \neVAS. The OTs consisted of an intensity corresponding to 150/200 (T1), followed by ten seconds 431 \nof 175/200 (T2) and then decreased back to the stimulation intensity of T1 for  15 seconds (T3). 432 \nRise and fall rates were kept constant (100°C/s). Each trial was performed four times (4x OT, 4x 433 \nCT) with a break of 2 min in between the trials . The order of trials was pseudorandomized in a 434 \ncounterbalanced manner.  435 \nParticipants continuously rated the experienced pain intensity throughout each trial and 436 \nwere instructed to attend carefully and indicate even very subtle sensations or changes.  This 437 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n24 \n \nprocedure was repeated once for each modality, resulting in a total of 16 trials per participant. All 438 \ntrials were completed for one modality before the other modality was tested . This transition was 439 \npreceded by a 5-min interval of no stimulation to reduce possible carry-over effects. 440 \nStatistical analysis  441 \nSample size calculation was based on the previously described OA effect size (78). With 442 \nan estimated effect size of dz = 0.76 (27), an estimated group size of n = 25 participants for paired 443 \ncomparisons (two-sided t-test, α = 5%) was required to reach statistical power of 95% (G*Power, 444 \nUniversity of Düsseldorf) (79). To preserve planned power, improve precision, and mitigate sex 445 \nimbalance, we prospectively oversampled to n=33 (80). 446 \nStatistical analyses were performed using R Studio (RStudio version 2024.04.11 with R 447 \nversion 4.5.0, R Foundation for Statistical Computing, Vienna, Austria) (81) and MATLAB (The 448 \nMathworks Inc., 2024) (82) Parametric data is presented in means ( x̄ ) with standard deviations 449 \n(SD) and nonparametric data in median (M) with ranges (R) or absolute and relative frequencies. 450 \nThe average eVAS ratings were obtained for each time interval (T1, T2 and T3). The first 5s of 451 \nT1, T2 and T3 and the last 5s of T3  were not considered in our analysis. This is an approach we 452 \nhave chosen before to consider the delay in pain response and extract stable pain ratings (83,84). 453 \nWe calculated a 2x3 repeated measures ANOVA with the factors ‘trial’ (CT, OT) and ‘time’ (T1, 454 \nT2, T3). If there were significant findings, FDR corrected (85,86) t-tests were performed. The level 455 \nof significance was set at p < 0.05. We deviated from our initial analysis plan  (dependent t-tests) 456 \nin the preregistration to achieve more coherence in context of the analysis of the second study. An 457 \nadditional ANOVA analysis including both modalities in a 2 x 2 x 3 ANOVA can be accessed in 458 \nthe Supporting Information (S4 Table). 459 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n25 \n \nNeurophysiological expression of TCE in auditory and thermal 460 \nstimulation 461 \nIn this experiment, we aimed to investigate neural and autonomic nervous system responses 462 \nusing a similar stimulation paradigm and the same modalities as explained above . For this, we 463 \ncollected EEG data, pupillometry data and behavioral ratings. The study was approved by the 464 \nEthics Committee of the University of Lübeck (2023 -633) and conducted in accordance with the 465 \nDeclaration of Helsinki. Again, the methodology was preregistered on the Open Science 466 \nFramework (OSF; https://osf.io/v37mp). 467 \nParticipants 468 \nA total of 29 healthy participants (sex = 19f; age = 24.6, SD = 5.7) were used for analysis. 469 \nIn- and Exclusion criteria were similar for both  experiments. None of the volunteers that 470 \nparticipated in the behaviorally focused experiment were recruited for the second experiment. 471 \nEquipment  472 \nThe same stimulation equipment as in the previous experiment was used for all procedures. 473 \nBehavioral data were collected using an eVAS similar in style and anchors, but the visual 474 \npresentation, data collection and stimulus control was achieved using MATLAB (The Mathworks 475 \nInc., 2024). For visual presentation purposes, the psychophysics toolbox (87) was used. The EEG 476 \nwas recorded at 24 passive scalp electrodes (SMARTING, mBrainTrain, Belgrade, Serbia) at a 477 \nsampling rate of 500 Hz (DC to 250 Hz bandwidth), referenced against electrode FCz. Electrode 478 \nimpedances were kept below 10 kΩ. The amplifier was attached to the EEG cap (Easycap, 479 \nHerrsching, Germany) and the EEG data were transmitted via Bluetooth to a nearby computer, 480 \nwhich recorded the data using the Smarting Streamer (Version 3.4.2). For pupillometry, a Tobii 481 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n26 \n \nX3-120 Eye Tracker (Tobii Technology Inc., Stockholm, Sweden) was used with sampling rate of 482 \n120Hz. Pupillometry data were directly recorded via MATLAB. 483 \nFamiliarization and calibration procedure 484 \nContrary to the first experiment, we did not individually calibrate the stimuli. This 485 \napproach was chosen due to the robust effects seen in the first experiment . Furthermore, the 486 \napplication of constant stimulation intensities ensures uniform stimulus input across all 487 \nparticipants, a feature that assumes greater significance in the context of neurophysiological 488 \ninvestigations (68). We derived stimulus intensities from mean values of the stimulation 489 \nparameters of the behavioral experiment. The initially derived stimulation parameters from the 490 \nfirst experiment  that were used for thermal stimulation led to major pain habituation effects 491 \nresulting in close to zero pain felt by the participants  after a few trials. Due to this, we increased 492 \nthe temperature by 1.5°C (initially 4 6°C and 4 7°C) to reduce these habituation effects . The 493 \nparticipants (n = 11) that received the stimulation protocol prior to this change were excluded from 494 \nthe analysis.  In order to account for the missing practice using the eVAS, the participants 495 \nunderwent a brief familiarization procedure. This procedure comprised five stimuli in ascending 496 \norder, either starting from 44.5°C for thermal stimulation and increasing in 1°C steps or starting 497 \nfrom 80dB and increasing in 5dB steps.  Each stimulus was presented for 10 seconds and then 498 \nfollowed by a 10-second pause (matching the calibration procedure from the first experiment). 499 \nExperimental paradigm 500 \nThe TCE paradigm was the same as the one used for  the behavioral investigation but  501 \nconsisted of fixed stimulation intensities of 47.5°C or 95dB for T1, 48.5°C or 100dB for T2 and 502 \n47.5°C or 95dB for T3, respectively. Each modality was tested twice, and each stimulation block 503 \nconsisted of ten trials . The first two trials per block were designated as an OT or CT, with the 504 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n27 \n \nobjective of collecting behavioral data. Participants were tasked with continuously rating their 505 \nperceived stimulus intensity. For the remaining eight trials, participants were instructed to maintain 506 \ntheir gaze on a fixation cross, focusing on their sensory experience without moving. The order of 507 \ntrials was pseudorandomized to a matching number of trials per block. Each “modality block” was 508 \nfollowed by a  5-min break  and then alternated to the other modality. For an overview of the 509 \nprocedure, consult Figure 1. 510 \nStatistical analysis  511 \nThe determination of sample size was based on the effect sizes derived from  the first 512 \nexperiment. For the auditory modality, an effect size of d z = 0.64  (thermal d z = 1.09) , with 513 \nstatistical thresholds set at alpha = 0.05 and beta = 0.1 (90% power), indicated an estimated sample 514 \nsize of 28 participants . Due to the mentioned changes in temperature (see  Familiarization and 515 \ncalibration procedure) and the exclusion of 11 participants that were previously recorded the final 516 \nsample size for analysis was n = 29. 517 \nStatistical analyses were performed using R Studio (RStudio version 2024.04. 11 with R 518 \nversion 4.5.0, R Foundation for Statistical Computing, Vienna, Austria) (81) and MATLAB (82). 519 \nParametric data is presented in means  (x̄ ) with standard deviations (SD) and nonparametric data 520 \nin median (M) with ranges (R) or absolute and relative frequencies. We calculated a 2x3 repeated-521 \nmeasures ANOVA with the factors ‘trial’ (CT , OT) and ‘time’ (T1, T2, T3). If there were 522 \nsignificant effects, FDR corrected  (85,86) post-hoc t-tests were performed. The level of 523 \nsignificance was set at p < 0.05. An additional ANOVA analysis including both modalities in a 2 524 \nx 2 x 3 ANOVA can be accessed in the Supporting Information ( S5 Table). For behavioral data 525 \nanalysis, the extracted time intervals matched the ones chosen in the first study. For  the analysis 526 \nof EEG and pupillometry data, we shifted the extracted time intervals to right after onset of the 527 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n28 \n \nstimulus, since we did not expect any delay in response compared to the behavioral data, resulting 528 \nin T1 being 0-5s, T2 being 10-15s and T3 being 20-25s. 529 \nEEG preprocessing and analysis 530 \nThe continuous EEG data were high -pass ( 1 Hz) and low -pass filtered ( 100 Hz), re -531 \nreferenced to the average reference across all electrodes, and epoched from –5 to +40s relative to 532 \nthe onset of auditory/thermal stimulation. An independent component analysis (ICA) was used to 533 \nremove components related to eye -blinks, eye-movements and muscle activity . Remaining 534 \nartefactual epochs were removed afterwards by visual inspection. All data analyses were carried 535 \nout in Matlab (R2024b), using custom scripts and the Fieldtrip toolbox (88). Time-frequency 536 \noscillatory power  representations of single -trial EEG data  were obtained using Fast Fourier 537 \nTransform (FFT) with multi-tapering (DPSS, discrete prolate spheroidal sequences) for a moving 538 \ntime window (length: 2s; moving in steps of 0.1s through the trial) for frequencies 1–80Hz in steps 539 \nof 1 Hz with 2Hz spectral smoothing.  540 \nPupillometry preprocessing 541 \nSimilarly to EEG analysis, we used Fieldtrip (88) to conduct the necessary preprocessing 542 \nsteps for the pupillometry data. First, samples reflecting physiologically implausible pupil changes 543 \nwere identified using a velocity -based criterion: data points whose dilation speed exceeded three 544 \nstandard deviations above the mean velocity within each trial were marked as invalid. Next, short 545 \ngaps of missing data (< 500 ms) were interpolated using a cubic spline method to reconstruct brief 546 \nblink-related signal loss, following the recommendations of Sebastiaan Mathôt and Kret and Sjak-547 \nShie (89,90). Longer gaps were left unaltered to avoid introducing artificial signal. Finally, pupil 548 \nsize data from the left and right eye were averaged to obtain a single mean for subsequent analyses. 549 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted December 17, 2025. ; https://doi.org/10.64898/2025.12.16.694610doi: bioRxiv preprint \n\n29 \n \nAcknowledgements 550 \nWe thank Anna M. Hagemann for her contribution and assistance during data collection.  551 \n.CC-BY 4.0 International licenseperpetuity. 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