More than meets the eye: neural correlates of consciousness in the sound-induced flash illusion

More than meets the eye: neural correlates of consciousness in the sound-induced flash illusion | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article More than meets the eye: neural correlates of consciousness in the sound-induced flash illusion Theresa Rieger, Josefine Feuerstein, Niko A. Busch, Thomas Straube, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7535859/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract The visual awareness negativity (VAN) has been identified as a potential neuronal correlate of consciousness (NCC). The VAN is typically found when comparing experimental trials in which a stimulus was perceived with trials in which the same stimulus was not perceived. However, if the VAN represents a reliable NCC, it should also be observed under conditions in which participants report conscious perception despite the absence of a corresponding visual stimulus, i.e., a visual illusion. Our event-related potential (ERP) study ( N = 47) aimed to investigate this question by using a suited stimulation design, the sound-induced flash illusion (SIFI), for which a visual stimulus is presented once together with two short beeps, leading - on about half the trials - to the illusory perception of a second flash, with graded levels of reported awareness of these trials. When comparing illusory with non-illusory trials, we found an enhanced negativity over posterior electrodes between 250 and 300 ms. Frequency analyses additionally revealed lower pre-stimulus alpha power in illusion trials, aligning with prior work linking alpha dynamics to perceptual variability. Our findings suggest that even illusory perceptions enhance negative potentials over posterior regions during the VAN interval, supporting the interpretation of the VAN as a NCC. Biological sciences/Neuroscience Biological sciences/Psychology Social science/Psychology NCC EEG/ERP visual awareness consciousness VAN illusions Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction The neural correlates of consciousness (NCC) refer to the basal neural mechanisms that, in combination, are sufficient "for any one specific conscious experience" 1 . In recent years, substantial advances in consciousness research have been achieved, e.g., through studies utilizing electroencephalography (EEG), which suggest potential NCC candidates 2 – 4 . EEG studies on the neural correlates of visual consciousness typically make a “hit vs. miss” comparison, i.e., the comparison of trials in which a stimulus was reported as seen, with trials in which the same stimulus was reported as unseen. Based on this approach, an enhanced negative event-related potential (ERP) emerging approximately 100–300 ms after stimulus onset has been identified; this negativity, known as the Visual Awareness Negativity (VAN), is most prominent over occipital and posterior temporal scalp sites 5 – 9 . The VAN is claimed to be the earliest and most reliable marker of visual consciousness (for review see 3 ) and is in accordance with consciousness theories, which posit a central role of early sensory areas in generating conscious perception of a stimulus 4 , 10 , 11 . Previous research shows that a negative deflection is not only measurable in visual perception but also in other sensory modalities. In this framework, the VAN is part of a family of components of perceptual awareness negativities (PAN 2 , 12 ) with an equivalent in the somatosensory modality (somatosensory awareness negativity, SAN 13 , 14 ) and the auditory modality (auditory awareness negativity, AAN 15 – 18 ). Yet, the role of the VAN as a direct marker of consciousness remains debated. Conscious access has been associated either with both VAN and subsequent late positive components 19 or with later positive components alone 20 – 24 . In this framework, the VAN may reflect early, pre-conscious processing, potentially indexing preparatory or unconscious perceptual activity rather than awareness itself 25 , 26 . If VAN-like negativities also occur without external input such as during illusory perception. This would challenge its interpretation as purely pre-conscious and support its role in conscious awareness. Illusory percepts thus offer a strong test case for disentangling stimulus-driven activity from awareness-related neural markers. We examine the question whether the VAN is exclusive to comparisons between seen and missed veridical stimuli, or whether it can also emerge when contrasting illusory percepts with correctly perceived stimulus absence. To our knowledge, only few studies have directly examined early ERPs elicited by consciously perceived but physically absent stimuli. In the auditory domain, studies have either elicited illusions with Pavlovian conditioning 27 or relied on spontaneous auditory illusions occurring in noise 28 . In both studies negative deflections were more pronounced for illusory percepts, consistent with the AAN 27 , 28 . One study also observed a late positivity for illusory percepts, however interpreted as centro-parietal positivity (CPP), suggesting a decision-related or higher-order cognitive process 28 . For the visual modality, several studies have examined illusory flashes, triggered by the simultaneous presentation of stimuli in other modalities. With auditory trigger stimuli, this phenomenon is called the Sound-Induced Flash Illusion (SIFI 29 , 30 , see 31 for a Touch-Induced Flash Illusion, TIFI. The SIFI occurs when a single visual flash is accompanied by two auditory beeps, leading participants to perceive a second, non-existent flash 29 , 32 . The SIFI not only produces a comparably high rate of illusory perceptions in stimulus-absent trials (around 50% 33 ) but also enables precise estimation of the perceptual onset, as the illusory second flash coincides subjectively with the onset of the second beep. This inference of the illusory percept's onset allows for investigating ERPs associated with visual illusions. The SIFI is widely used to study multisensory integration (for review see 34 , 35 ) but few studies have compared ERPs between illusion and non-illusion trials 36 or between participants with low versus high illusion rates. These studies have yielded heterogeneous findings. Notably, they have not specifically addressed the VAN but followed a predominantly exploratory approach. A positive deflection peaked at 120 ms over occipital sites, was localized to extrastriate visual cortex and covaried across participants with susceptibility to the sound-induced flash illusion, whereas on a trial-by-trial basis illusion perception was associated with enhanced negative deflections peaking at 110 ms (auditory cortex) and 130 ms (superior temporal gyrus 36 ). In a follow-up study, a fronto-central negativity at 130–160 ms distinguished illusion from no-illusion trials and was localized to superior temporal gyrus; the earlier 120 ms occipito-temporal positivity was replicated as a cross modal interaction effect 37 . A later negativity peaking at 270 ms with a centroparietal maximum appeared in cross modal interaction difference waves for both illusory and veridical second flash conditions 36 . Additionally, an event-related difference at 265–280 ms, source-localized to cingulate cortex, differentiated illusion from non-illusion trials 38 . In a TIFI paradigm, an occipital difference between 140–185 ms distinguished illusion from no-illusion trials 31 , indicating VAN-like spatial and temporal properties. Beyond evoked potentials, oscillatory dynamics, particularly in the alpha band, are central to shaping perceptual outcomes, modulating excitability and perceptual thresholds (for comprehensive review see 38 – 44 ). Alpha activity has also been linked to illusory perception. In auditory paradigms like speech-in-noise tasks, illusion trials are associated with reduced alpha power over temporal regions, reflecting heightened cortical excitability 45 . However, this is not consistent across paradigms: Faramarzi et al. 28 found no pre-stimulus alpha differences between illusory and non-illusory auditory trials. In SIFI and TIFI paradigms, alpha-band dynamics show consistent correlations with illusion susceptibility. Lower individual alpha frequency 46 , 47 , reduced pre-stimulus alpha power 48 , and specific alpha phase alignments 31 have each been associated with a higher likelihood of illusion perception (for review see 49 ). To assess subjective illusion perception, it is essential to provide participants with a means of reporting their conscious experience. The Perceptual Awareness Scale (PAS) offers a sensitive and theoretically grounded approach for capturing gradations in illusion perception. It distinguishes between varying levels of conscious access and has been shown to align well with both behavioral and electrophysiological measures 50 – 53 . Notably, there is an ongoing debate as to whether consciousness unfolds gradually 50 , 52 – 57 , or appears in an all-or-none manner 58 , 59 . This ongoing controversy underscores the relevance of nuanced tools like PAS for mapping the structure of conscious experience. The current study employed an adapted SIFI paradigm to reliably elicit illusory percepts in approximately 50% of trials. Leveraging a large sample size and fine-grained subjective reports, this study aims to determine whether VAN-like negativities can also be observed for consciously perceived illusory stimuli, i.e., in the absence of physical visual input, and whether these correlate with graded levels or dichotomous states of reported consciousness. In addition, the study tests whether pre-stimulus alpha-band activity, specifically its power, predicts the likelihood of illusion perception. 2. Materials and Methods Participants Sixty right-handed volunteers between 18 and 30 years old (female = 49; male = 10; divers = 1) were recruited at the University of Muenster to participate in the EEG experiment. An a-priori sample size calculation was on one hand not feasible due to expected inter-individual variability in illusion susceptibility and on the other hand incompatible with the planned cluster-based permutation (CBP 60 ) analysis. Anticipating relatively small effect sizes and accounting for an estimated dropout rate of 10% and expected data loss (e.g., due to artifact rejection and behavioral exclusion), we selected the largest practicable sample size available, resulting in the above mentioned recruited sample of N = 60. All participants had normal or corrected-to-normal vision and no history of psychiatric or neurological diseases. Participants provided written informed consent and received monetary compensation of 12 euros per hour. One participant was excluded because their behavioral data indicated that they were unable to distinguish between one or two flashes presented without auditory stimuli ( d’ = 0.35). Furthermore, 12 subjects were excluded because they did not provide enough trials to obtain reliable ERPs (see section EEG data analysis). This resulted in the final number of N = 47 participants (female = 38; male = 8; divers = 1: M = 23.13 years, SD = 2.39 years) who were included in the main statistical analysis. The study was approved by and conducted following the guidelines of the ethics committee of the local medical association (Ärztekammer Westfalen-Lippe; 2019-049-f-S). Apparatus The experiment was run with Matlab (R2021a, Mathworks Inc., Natick, MA; http://www.mathworks . com) and the Psychophysics toolbox 61 , 62 . Stimuli were displayed on an LCD monitor (Iiyama G-Master GB2488HSU; 1920 × 1080 pixels, 60 Hz) on a black background (0.35 cd/m 2 ) in a dimly lit room. Participants were seated at a viewing distance of ≈ 60 cm in front of the computer. A chin rest was used to prevent head movements during the experiment. Auditory stimuli were presented via two loudspeakers, positioned to the left and right of the monitor. Stimuli and presentation Our EEG study was based on the SIFI paradigm to induce an illusion and then analyze its neural correlates. Therefore, we used two types of stimuli: Auditory (A) stimuli consisted of 1000 Hz sinusoidal beeps, lasting 10 ms, at 80 dB SPL (measured at mid chinrest position, horizontally centered and approximately at mid-head height). Simultaneously, visual (V) stimuli were presented as white flashes, appearing as discs with a 1° visual diameter and a luminance of 330 cd/m². Each flash was presented for 17 ms (Figure 1 c). As peripheral presentation of visual stimuli increases the likelihood of successfully eliciting illusions compared to centrally presented triggers 29 , 33 , the discs were positioned either in the lower visual field (LVF) or in the upper visual field (UVF; Figure 1 b) in a random order, at an eccentricity of 6° from the central fixation. Experimental design and statistical analysis Procedure Participants were instructed beforehand, emphasizing that their responses should reflect their personal, initial visual impressions and spontaneous decisions, rather than deliberating on what might be considered "right" or "wrong." The main experiment lasted approximately 1 hour and consisted of 960 trials in total, divided into 12 blocks, each containing 80 trials. Every block was separated by breaks to relax the eyes and to get informed about how many trials they had already completed out of the total number. By pressing a key, they were able to proceed with the experiment on their own terms. Four different stimulus combinations were randomly presented (Fig. 1 a) each occurring 240 times (120 UVF, 120 LVF). The combinations included unimodal visual stimuli appearing singly (V1) or in pairs (V1V2) and bimodal combinations: A1V1_A2V2 and A1V1_A2 (= illusion condition, see definition-below). The stimulus onset asynchrony (SOA) was set at 83 ms. Each trial started with a fixation cross (randomized duration between 1-1.5 s), followed by one of the above-described stimulus combinations. Participants were asked to watch the cross permanently. After each trial, the subjects were prompted to report the visibility of the second flash with a 600 ms delay after the stimulus offset (in order to minimize motor-related activity during the analysis of ERPs). For the reports, we used the perceptual awareness scale to measure the subjective perception as sensitively as possible 63 , 64 . In pilot experiments, we asked three observers to verbalize their percept on each trial. This procedure led to an adapted 4-leveled scale, closely resembling the scale labels 63 , 64 . The participants were instructed to use the PAS by pressing the keys 1 to 4 on a standard keyboard with the following adapted labels: 1 = " no experience of a second flash ", 2 = “ vague experience of a second flash ”, 3 = “ almost clear experience of a second flash ”, 4 = “ clear experience of a second flash ”. Prior to the main experiment, 32-trial practice sessions were conducted to familiarize participants with the possible perceptual outcomes and the corresponding PAS levels. Behavioral Data Analysis To obtain a measure of the individual ability to discriminate the presentation of one and two flashes (i.e. conditions V1 and V1V2), we dichotomized the PAS responses, relabeling PAS = 1 as “no (second flash)” and PAS > 1 as “yes (second flash)”. Based on the relative proportions of hits (p(“yes” | V1V2)) and correct rejections, (p(“no” | V1)), we calculated the signal detection theory-based index d' 65,66 . To quantify the effect of auditory stimulation on the frequency of illusory perception of a second flash, we calculated the difference between the relative frequencies p(“yes” | V1) and p(“yes” | A1V1_A2). EEG recording and preprocessing Electrophysiological data were collected using a 64-channel BioSemi active electrode system (BioSemi B.V., Amsterdam, Netherlands). Electrodes were positioned according to the extended international 10–20 system as implemented in the BioSemi 64-channel cap. The BioSemi EEG system replaces traditional ground and reference electrodes with a CMS/DRL feedback loop, using two additional electrodes. Vertical eye movements (VEOG) were recorded with electrodes placed above and below the left eye, while horizontal eye movements (HEOG) were captured with electrodes at the outer canthi of both eyes. Electrical potentials were recorded, maintaining electrode offsets below 20 µV. EEG data preprocessing was performed using Brain Electrical Source Analysis (BESA) Research 6.0 (BESA GmbH, Gräfeling, Germany). Offline data were re-referenced to an average reference and filtered with a 0.01 Hz high-pass zero-phase filter (12 dB/oct) and a 40 Hz low-pass zero-phase filter (24 dB/oct). A 50 Hz notch filter was applied to remove line noise. Channels with extreme noise were identified by eye inspection and subsequently interpolated (number of interpolated channels ≤ 13; M = 4.74, SD = 5.66). Eye movements were corrected with BESA's automatic eye-artifact correction method 67 . Additional artifacts were removed using BESA's semi-automatic, principal component analysis (PCA) based artifact topography algorithm, with manual selection of artifacts. Trials exhibiting muscle artifacts, electrode jumps, or amplitudes exceeding a 100 µV threshold were rejected following visual inspection. The main analysis focused on the comparison of trials with and without illusions (henceforth called 'seen' and 'unseen', referring to the second flash) in the critical condition, i.e., A1V1_A2. The proportion of illusion trials can vary across subjects 47 , 68 , 69 . Thus, in our experiment some subjects may provide unreliable ERPs for either the seen or unseen condition if they are based on a low number of trials. While including only subjects with a high number of trials optimizes the reliability of individual ERPs, it reduces the overall sample size and, thus, the reliability of the grand average ERP. To optimize this trade-off, we chose a data-driven, hypothesis-independent approach and systematically evaluated the signal-to-noise ratio (SNR) of the critical condition, i.e., averaged across seen and unseen trials, for a range of minimum trial numbers (between 10 and 100 in steps of 5). To be included in the final sample, the number of seen and the number of unseen trials in the critical condition had to match or exceed this number. For each minimum trial count, we calculated the root mean square (RMS) of the averaged EEG signal. SNR was derived as the ratio of RMS signal during the critical time window (0–300 ms) to the baseline period (-200-0 ms). The highest SNR was observed at 30 trials, leading to the exclusion of the above-mentioned 12 participants. The average number of analyzed trials in the final sample in the critical conditions was mean unseen = 120.96 ( SD = 46.53) and mean seen = 106.89 ( SD = 45.51). Illusory percepts were also expected to occur without auditory stimulation, i.e., in the V1 condition. These illusions were expected to be less frequent, as the participants’ expectation of a second flash was not influenced by the auditory stimulus but by the perceived probability of the appearance of a second flash. To validate possible VAN effects observed in the critical condition, we performed a comparison for seen vs unseen second flash also in the V1 condition. We applied the same SNR-optimization approach also for this comparison, which led to the exclusion of 26 participants. The average number of trials analyzed in the final for the control condition was mean unseen = 148.09 (SD = 41.34) and mean seen = 80.12 (SD = 38.21). EEG data analysis Intervals and electrodes of interest were defined based on previous studies to optimize the detection of electrodes maximally responsive to the VAN. We considered all posterior and occipital electrodes, as supported by prior research (e.g. 7,8,70,71 ), which indicates that these regions show heightened negativity linked to early conscious visual processing. Prior studies (for review see 3 , 5 , 72 , 73 ) suggest that the typical VAN time window falls somewhere between 100–300 ms. In our study, we focused on VAN effects following the second (illusory) flash, occurring 80 ms after the first flash onset. Consequently, we expected the VAN response to appear around 180–380 ms post the initial flash onset in the critical condition (A1V1_A2). Within the defined interval and electrodes of interest, we employed a CBP 60 . CBP tests were performed by computing a paired-sample t-test at each channel and sample of interest. The cluster mass was calculated by summing all t-values with alpha < .05 (one-sided negative) neighboring in time and space (the minimum number of channels to form a cluster was 2). The number of permutations was N = 5000 and the significance threshold for testing the null hypothesis was alpha < .05. The interval of interest extended from 180 to 380 ms and the channels of interest included P1, P3, P5, P7, P9, PO7, PO3, O1, Iz, Oz, POz, Pz, P2, P4, P6, P8, P10, PO8, PO4, and O2. Secondary analyses and visualization of ERPs were conducted using electrodes identified as significant, i.e., all channels with at least one significant sample. Additionally, we explored whether the VAN followed a gradual or dichotomous pattern across the four levels of the PAS scale, using the cluster average, i.e., the mean value of the significant sensors and samples described by the cluster as a measure of the VAN amplitude. We then compared Linear Mixed-Effects Models (LME) with single-trial VAN amplitudes as the dependent variable (DV). All analyses were conducted in R, utilizing the lme4 package 74 for model building and the readr package for data handling and preprocessing. Only trials from the critical experimental condition were retained for analysis. The DV was centered and scaled to facilitate the interpretation of model parameters. To evaluate gradual effects, perceptual awareness was decomposed into orthogonal polynomial contrasts, capturing linear, quadratic, and cubic trends 53 . A baseline model was constructed with only a random intercept for participants to account for individual differences in VAN amplitude. Subsequent models incorporated predictors reflecting either gradual changes in perceptual awareness or dichotomous perceptual outcomes. To test for a dichotomous pattern of awareness, a fixed effects model was specified using a categorical predictor that indexed trials as either illusion or no-illusion, despite identical physical stimulation. This model included a fixed effect for the dichotomous predictor and a random intercept for participant ID. Fixed effects models were selected because models with random slopes failed to converge. Likelihood ratio tests were used to compare model fits, allowing us to assess whether variability in VAN amplitude was better accounted for by gradual or dichotomous patterns of perceptual awareness. Spectral analysis Power spectra were computed using a Fast Fourier Transform of single-trial raw data in the 500 ms pre-stimulus time window. Power was tested for differences between illusion and no-illusion trials in the alpha frequency range (8 to 12 Hz), averaged across three channels, which showed the strongest overall alpha power (PO3, POz, PO4). 3. Results Behavioral data Distribution of awareness ratings PAS Ratings for all experimental conditions are shown in Fig. 2 . In 20.98% ( SD = 0.154) of trials in the V1 condition, participants reported perceiving a second flash (PAS > 1) despite its physical absence, which allowed us to use this condition as a control comparison. A one-way repeated-measures ANOVA revealed a significant main effect of condition on the relative frequency of PAS1 responses, F(3, 184) = 315.059, p < .001, η² = .855, indicating that the frequency of perceiving only one flash varied substantially across conditions. As shown in Table 1 , PAS1 responses (i.e., “no second flash perceived” ) were most frequent in the unimodal visual condition (V1) and least frequent in the multisensory congruent condition (A1V1_A2V2). Table 1 Relative frequency of PAS1 responses per condition Condition Mean (M) SD V1 0.7902 0.1539 V1_V2 0.0571 0.0711 A1V1_A2 0.0274 0.0306 A1V1_A2V2 0.4733 0.1979 Pairwise comparisons (Table 2) confirmed statistically significant differences between all conditions (p < .001). Notably, the comparison between the two bimodal conditions (illusion vs. veridical: A1V1_V2 vs. A1V1_A2V2) revealed a significant difference, t(46) = 4.58, p < .001, d = 0.59. Table 2. Pairwise comparisons of PAS1 frequencies between conditions Comparison t(59) p-value Mean Difference Cohen’s d V1 vs. V1_V2 34.9619 < .001 0.7331 5.0997 V1 vs. A1V1_A2V2 34.6793 < .001 0.7628 5.0585 V1 vs. A1V1_A2 7.1170 < .001 0.3168 1.0381 V1_V2 vs. A1V1_A2V2 3.6954 < .001 0.0297 0.5390 V1_V2 vs. A1V1_A2 -12.3706 < .001 -0.4162 -1.8044 A1V1_A2V2 vs. A1V1_A2 -14.4465 < .001 -0.4459 -2.1072 Electroencephalography data As noted above, a sample of n = 33 remained after applying the criterion of a minimal number of 30 seen and 30 unseen trials for this control comparison. The main analysis is based on comparisons between seen and unseen trials in the critical condition (A1V1_A2). Figure 3 (left) shows the corresponding ERPs and the differential topography. A control analysis is presented for the comparisons between seen and unseen trials in the V1 condition. Corresponding ERPs and topographies are depicted in Fig. 3 (right). ERPs to the four experimental conditions without post-hoc sorting into seen and unseen trials are presented in the Supplementary Material. Visual Awareness Negativity - Seen vs. unseen comparison For the critical condition (A1V1_A2), we observed a significant cluster in the interval and channels of interest (cluster mass = -167.765, p = 0.016). Descriptively, the cluster extended from approximately 250 to 305 ms, as shown in Fig. 3 , which depicts the ERPs averaged across all significant electrodes (P1, Pz, P2, PO3, POz, PO4, and O2). Since CBP tests do not precisely establish the latency and location of effects 75 , the spatiotemporal extents of clusters are provided only for descriptive purposes. On the right side in Fig. 3 , we also provide results for the control condition (V1) for the comparison of trials with and without the illusory perception of a second flash. In both conditions, the VAN can be shown in the expected time window. The topographies in Fig. 3 a visualize the spatiotemporal dynamics of the VAN within the significant time window of 250–305 ms where seen stimuli exhibit greater negativity compared to unseen stimuli. The significant cluster of electrodes is marked in green for the critical condition. The topographies for both conditions show a negativity predominantly localized over posterior-central sites. We tested whether VAN in the critical condition was affected by upper or lower presentation using a Bayesian paired t-test, to determine whether presentation location influenced VAN amplitudes. The results confirmed that there was moderate evidence for the null hypothesis (BF01 = 4.9453) i.e., for no VAN differences between the upper and lower hemifield. Gradual vs. dichotomous correlates Both linear mixed-effects model treating PAS as a gradual or a dichotomous (see vs unseen) predictor of VAN amplitude significantly outperformed the null model, (χ²(1) = 6.94, p = .008 for the graded and χ²(1) = 5.52, p = .019, for the binary model. However, PAS showed only a marginally better fit than detection (AIC: − 17356 vs. − 17355; BIC: − 17327 vs. − 17326), which does not indicate a meaningful statistical difference in overall model fit. Thus, while both Fig. 4 and statistical results suggest at least descriptively a gradual component in the VAN response, our data allow no firm conclusions. Exploratory analysis of pre-stimulus alpha power Alpha-band power in the pre-stimulus interval was stronger preceding trials without illusions compared to trials with illusion (t(46) = 2.32; p = .025; two tailed; Fig. 5 ). 4. Discussion We analyzed whether the VAN could serve as a NCC even in the absence of direct sensory stimulation. We used the SIFI paradigm to examine whether the VAN would be elicited when participants perceived an illusory second flash compared to non-illusory conditions and found a negativity between 250–300 ms, aligning with established VAN characteristics(e.g. 7,26,70,76 ). Our findings foster the robustness of the VAN as a correlate of subjective visual experience even in illusory perception contexts, supporting the notion that the VAN may reflect conscious perception itself, even when no physical visual input is present. Our results contrast with accounts that question the VAN’s role in conscious perception and instead link awareness more consistently to later ERP components 20 – 24 and with views that interpret the VAN as reflecting early, pre-conscious processing 25 , 26 . Conversely, other work associates conscious access with both the VAN and a subsequent late positivity 19 . Our findings provide a counterpoint to a purely pre-conscious interpretation: because a VAN-like negative deflection is present during the conscious perception of physically absent stimuli, its generation cannot be reduced to stimulus-driven input alone and may index processes tied to conscious awareness. Our results are consistent with EEG and MEG studies indicating that illusory and veridical perception can share key neural signatures—especially in oscillatory dynamics and ERP profiles 27 , 28 , 31 , 36 – 38 , 77 . Most EEG studies on the SIFI address multisensory integration rather than the neural determinants of perceptual awareness. However, a few studies have directly contrasted illusion and no-illusion perception. A fronto-central negativity around 130–160 ms has been shown to distinguish illusion from no-illusion trials, although without the posterior distribution typical of the VAN 37 . An event-related difference at 265–280 ms, source-localized to cingulate cortex, has also been linked to illusion perception, but this effect differs from ours in both timing and scalp topography 38 . In a touch-induced illusion, an occipital difference 140–185 ms distinguished illusion from no-illusion trials 31 and was thus spatially and temporally similar to our effect. Two previous studies, which induced auditory illusions, reported also negativities as correlates of illusory perception. An ERP interpretable as the auditory-awareness negativity was identified in a study which relied on spontaneous auditory illusions occurring in noise and contrasted trials with and without reported perception, allowing for a direct comparison of perceived versus unperceived auditory events 28 . Furthermore, in a study which used a design with associative learning between cues and auditory stimuli, an AAN was observed over temporal and parietal electrodes between 200–300 ms, closely paralleling the visual VAN in timing and distribution 27 . We focused our ERP analysis on posterior scalp sites, encompassing occipital, parieto-occipital, and lateral temporal electrodes (see 3 , 7 ). Within this a-priori space, we detected a robust negative deflection that temporally matches the VAN but peaks over mid-parietal electrodes (P1, Pz, P2, PO3, POz, PO4, O2). Studies show that the VAN amplitude and scalp distribution can shift with stimulus complexity 51 , 70 , 78 , perceptual visibility (for review see 79 ), task relevance (e.g. 80 ) and experimental context 7 , 53 , 80 , 81 . Hence, our findings contribute to the growing evidence that VAN (topography) does not seem to be a fixed phenotype but can be modulated by experimental context. In addition to ERPs, we examined oscillatory dynamics, particularly alpha-band activity. Other than in an auditory illusion study which found no pre-stimulus alpha differences between illusion and no-illusion trials 28 , our results are in line with studies showing that lower individual alpha frequency 46 , 47 , reduced pre-stimulus alpha power 48 , and specific pre-stimulus alpha phase alignments 31 increase susceptibility to illusion perception in the SIFI and TIFI paradigms (for review see 49 ). While these studies interpret alpha primarily within the framework of temporal precision for multisensory integration, we suggest that alpha frequency may also index the cortical conditions underlying the access of perceptual content to conscious perception, modulating whether internally or externally driven signals gain perceptual access. For a comprehensive account of the neural marker, the correspondence with participants’ subjective reports is critical. The behavioral data from the V1, V1_V2 and A1V1_A2V2 conditions provide benchmarks, validating participants’ reports across varying sensory contexts. There is reason to consider the PAS ratings in our study as a meaningful reflection of subjective experience. The V1_V2 and A1V1_A2V2 conditions exhibit progressively higher PAS responses where additional sensory information enhances perceptual clarity. In the critical condition, illusions were observed on 50% of trials, congruent with the literature (for review see 33 ). Overall, the resulting distribution of ratings confirms our previous expectations and in addition to the consistent pattern across conditions, this supports the reliability of the behavioral data in our study. However, we also found that in 24% of V1 trials (where only one flash was presented without any auditory input) participants reported perceiving a second flash, despite the absence of a corresponding stimulus. These illusion in our study design can be interpreted within a predictive coding framework, which suggests that strong perceptual priors (shaped, for instance, by repeated exposure) can give rise to illusory percepts in the absence of external input 82 , 83 . In our paradigm, one- and two-flash trials were deliberately made difficult to distinguish, introducing residual uncertainty into the system. Under such conditions, the brain integrates prior knowledge with incoming sensory data to minimize prediction error, especially in regions lacking strong afferent stimulation. When predictions closely match incoming input, residual errors can become negligible, allowing early cortical activity to resemble that of veridical perception, even when the stimulus is absent 84 , 85 . The frequent occurrence of two-flash trials likely strengthened participants’ prior expectation that a second flash would follow the first. This learned association may have contributed to the emergence of double-flash percepts, even when only one flash without auditory input was presented. Illusions in the unimodal V1 condition occurred less frequently than in the multisensory SIFI condition, where the auditory beep further reinforced the “two-flash” prior. Yet this convergence of real and illusory perception has its limits. Participants seem to be able to reliably distinguish between true and illusory percepts 86 . Research on mental imagery demonstrates that while vivid mental images share substantial overlap with veridical perception, they can still be differentiated both behaviorally and in neural activation patterns (for review see 87 ). A question that stays vacant is whether conscious perception unfolds gradually or appears in an all-or-none manner. When plotting ERPs for the four PAS categories in the critical condition, visual inspection suggested a gradual pattern of consciousness. Yet, the data seem to lack statistical power to support a statistical difference between the gradual and the dichotomous model. Descriptively, the gradual model shows a slightly better fit, which is in line with several studies 49 , 51 – 56 (but see 57 , 58 ) and supports the importance of suited measurement of graded experience 88 . We acknowledge several limitations. As outlined above, our goal to gain additional information about the graded vs. dichotomous nature of illusory awareness from the four levels of the PAS could not be reached despite a large number of trials and participants. While the PAS model demonstrated a descriptive advantage over the binary detection model in predicting VAN amplitude, the lack of a statistically significant difference prevents any conclusions and future studies with more power are needed. Furthermore, we used a specific experimental design to induce illusory percepts. It would be helpful to include different designs in future studies in order to provide data if results can be generalized across designs. Conclusion Our findings demonstrate that VAN-like negativities can emerge in response to subjectively perceived visual stimuli, even in the absence of external stimulation. This challenges interpretations of the VAN as purely stimulus-driven and strengthens its candidacy as a neural correlate of visual awareness and illustrate how studies on visual illusions can inform the research on NCC. Declarations Acknowledgments We thank Lisann Lübbers for assistance with data collection and the Open Access Publication Fund of the University of Münster for support. This research received no specific external funding. Especially we thank all study participants. Author contributions These authors contributed equally: Theresa Rieger, Josefine Feuerstein T.R.: Conceptualization, Piloting, Methodology, Investigation, Data Curation, Software, Formal analysis, Visualization, Writing – original draft, Writing – review and editing, Project administration. J.F.: Conceptualization, Piloting, Methodology, Investigation, Data Curation, Software, Formal analysis, Visualization, Writing – original draft, Writing – review and editing, Project administration. N.A.B.: Methodology, Data Curation, Software, Formal analysis, Writing – review and editing. T.S.: Conceptualization, Methodology, Supervision, Writing – Review & Editing. M.B.: Conceptualization, Methodology, Software, Formal analysis, Supervision, Visualization, Writing – original draft, Writing – review and editing, Project administration. Corresponding author Correspondence to [email protected] Data availability statement The datasets analysed during the current study are available from the corresponding author on reasonable request. Competing interests The author(s) declare no competing interests. Funding declaration statement No funding required. Additional information Supplementary Information The online version contains supplementary material available at: References Crick, F. & Koch, C. A framework for consciousness. Nat. Neurosci. 6 , 119–126 (2003). Dembski, C., Koch, C. & Pitts, M. Physiological Correlates of Sensory Consciousness: Evidence for a Perceptual Awareness Negativity. Preprint at (2021). https://doi.org/10.31234/osf.io/ma36g Förster, J., Koivisto, M. & Revonsuo, A. ERP and MEG correlates of visual consciousness: The second decade. Conscious. Cogn. 80 , 102917 (2020). Koch, C., Massimini, M., Boly, M. & Tononi, G. Neural correlates of consciousness: progress and problems. Nat. Rev. Neurosci. 17 , 307–321 (2016). Dellert, T. et al. Dissociating the Neural Correlates of Consciousness and Task Relevance in Face Perception Using Simultaneous EEG-fMRI. J. Neurosci. 41 , 7864–7875 (2021). Koivisto, M. & Grassini, S. Neural processing around 200 ms after stimulus-onset correlates with subjective visual awareness. Neuropsychologia 84 , 235–243 (2016). Koivisto, M. & Revonsuo, A. Event-related brain potential correlates of visual awareness. Neurosci. Biobehav Rev. 34 , 922–934 (2010). Pitts, M. A., Metzler, S. & Hillyard, S. A. Isolating neural correlates of conscious perception from neural correlates of reporting one’s perception. Front Psychol 5 , (2014). Schlossmacher, I., Dellert, T., Pitts, M., Bruchmann, M. & Straube, T. Differential Effects of Awareness and Task Relevance on Early and Late ERPs in a No-Report Visual Oddball Paradigm. J. Neurosci. 40 , 2906–2913 (2020). Lamme, V. A. F. Visual Functions Generating Conscious Seeing. Front. Psychol. 11 , 83 (2020). Lamme, V. A. F. & Roelfsema, P. R. The distinct modes of vision offered by feedforward and recurrent processing. Trends Neurosci. 23 , 571–579 (2000). Dembski, C., Koch, C. & Pitts, M. Perceptual awareness negativity: a physiological correlate of sensory consciousness. Trends Cogn. Sci. 25 , 660–670 (2021). Auksztulewicz, R. & Blankenburg, F. Subjective Rating of Weak Tactile Stimuli Is Parametrically Encoded in Event-Related Potentials. J. Neurosci. 33 , 11878–11887 (2013). Schröder, P., Nierhaus, T. & Blankenburg, F. Dissociating Perceptual Awareness and Postperceptual Processing: The P300 Is Not a Reliable Marker of Somatosensory Target Detection. J. Neurosci. 41 , 4686–4696 (2021). Eklund, R., Gerdfeldter, B. & Wiens, S. Effects of a Manual Response Requirement on Early and Late Correlates of Auditory Awareness. Front. Psychol. 10 , 2083 (2019). Eklund, R., Gerdfeldter, B. & Wiens, S. Is auditory awareness negativity confounded by performance? Conscious. Cogn. 83 , 102954 (2020). Eklund, R. & Wiens, S. Auditory awareness negativity is an electrophysiological correlate of awareness in an auditory threshold task. Conscious. Cogn. 71 , 70–78 (2019). Schlossmacher, I., Dellert, T., Bruchmann, M. & Straube, T. Dissociating neural correlates of consciousness and task relevance during auditory processing. NeuroImage 228 , 117712 (2021). Ye, M., Lyu, Y., Sclodnick, B. & Sun, H. J. The P3 Reflects Awareness and Can Be Modulated by Confidence. Front. Neurosci. 13 , 510 (2019). Babiloni, C., Vecchio, F., Miriello, M., Romani, G. L. & Rossini, P. M. Visuo-spatial Consciousness and Parieto-occipital Areas: A High-resolution EEG Study. Cereb. Cortex . 16 , 37–46 (2006). Dehaene, S. & Changeux, J. P. Experimental and Theoretical Approaches to Conscious Processing. Neuron 70 , 200–227 (2011). Lamy, D., Salti, M. & Bar-Haim, Y. Neural Correlates of Subjective Awareness and Unconscious Processing: An ERP Study. J. Cogn. Neurosci. 21 , 1435–1446 (2009). Salti, M., Bar-Haim, Y. & Lamy, D. The P3 component of the ERP reflects conscious perception, not confidence. Conscious. Cogn. 21 , 961–968 (2012). Sergent, C., Baillet, S. & Dehaene, S. Timing of the brain events underlying access to consciousness during the attentional blink. Nat. Neurosci. 8 , 1391–1400 (2005). Aru, J., Bachmann, T., Singer, W. & Melloni, L. Distilling the neural correlates of consciousness. Neurosci. Biobehav Rev. 36 , 737–746 (2012). Railo, H., Koivisto, M. & Revonsuo, A. Tracking the processes behind conscious perception: A review of event-related potential correlates of visual consciousness. Conscious. Cogn. 20 , 972–983 (2011). Filimonov, D., Lenkkeri, S., Koivisto, M. & Revonsuo, A. Event-related potential correlates of consciousness in simple auditory hallucinations. NeuroImage 310 , 121168 (2025). Faramarzi, M. et al. Similar EEG Activity Patterns During Experimentally-Induced Auditory Illusions and Veridical Perceptions. Front. Neurosci. 15 , 602437 (2021). Shams, L., Kamitani, Y. & Shimojo, S. Visual illusion induced by sound. Cogn. Brain Res. 14 , 147–152 (2002). Shams, L., Ma, W. J. & Beierholm, U. Sound-induced flash illusion as an optimal percept. NeuroReport 16 , 1923–1927 (2005). van Erp, J. B. F., Philippi, T. G., de Winkel, K. N. & Werkhoven, P. Pre- and post-stimulus EEG patterns associated with the touch-induced illusory flash. Neurosci. Lett. 562 , 79–84 (2014). Shams, L., Kamitani, Y. & Shimojo, S. What you see is what you hear. Nature 408 , 788–788 (2000). Keil, J. Double Flash Illusions: Current Findings and Future Directions. Front. Neurosci. 14 , 298 (2020). Hirst, R. J., McGovern, D. P., Setti, A., Shams, L. & Newell, F. N. What you see is what you hear: Twenty years of research using the Sound-Induced Flash Illusion. Neurosci. Biobehav Rev. 118 , 759–774 (2020). Huang, J., Wang, E., Lu, K., Wang, A. & Zhang, M. Long-term training reduces the responses to the sound-induced flash illusion. Atten. Percept. Psychophys . 84 , 529–539 (2022). Mishra, J., Martinez, A., Sejnowski, T. J. & Hillyard, S. A. Early cross-modal interactions in auditory and visual cortex underlie a sound-induced visual illusion. J. Neurosci. Off J. Soc. Neurosci. 27 , 4120–4131 (2007). Mishra, J., Martínez, A. & Hillyard, S. A. Effect of Attention on Early Cortical Processes Associated with the Sound-induced Extra Flash Illusion. J. Cogn. Neurosci. 22 , 1714–1729 (2010). Keil, J., Müller, N., Hartmann, T. & Weisz, N. Prestimulus Beta Power and Phase Synchrony Influence the Sound-Induced Flash Illusion. Cereb. Cortex . 24 , 1278–1288 (2014). Balestrieri, E. & Busch, N. A. Spontaneous Alpha-Band Oscillations Bias Subjective Contrast Perception. J. Neurosci. 42 , 5058–5069 (2022). Busch, N. A., Dubois, J. & VanRullen, R. The Phase of Ongoing EEG Oscillations Predicts Visual Perception. J. Neurosci. 29 , 7869–7876 (2009). Chaumon, M. & Busch, N. A. Prestimulus Neural Oscillations Inhibit Visual Perception via Modulation of Response Gain. J. Cogn. Neurosci. 26 , 2514–2529 (2014). Iemi, L., Chaumon, M., Crouzet, S. M. & Busch, N. A. Spontaneous Neural Oscillations Bias Perception by Modulating Baseline Excitability. J. Neurosci. 37 , 807–819 (2017). Iemi, L. & Busch, N. A. Moment-to-Moment Fluctuations in Neuronal Excitability Bias Subjective Perception Rather than Strategic Decision-Making. eneuro 5, ENEURO.0430-17.2018 (2018). van Dijk, H., Schoffelen, J. M., Oostenveld, R. & Jensen, O. Prestimulus Oscillatory Activity in the Alpha Band Predicts Visual Discrimination Ability. J. Neurosci. 28 , 1816–1823 (2008). Schepers, E., Bodar, L., van Os, J. & Lousberg, R. Cortical processes of speech illusions in the general population. BMC Neurosci. 17 , 65 (2016). Cecere, R., Rees, G. & Romei, V. Individual Differences in Alpha Frequency Drive Crossmodal Illusory Perception. Curr. Biol. 25 , 231–235 (2015). Keil, J. & Senkowski, D. Individual Alpha Frequency Relates to the Sound-Induced Flash Illusion. Multisensory Res. 30 , 565–578 (2017). Kvamme, T. L., Sarmanlu, M., Bailey, C. & Overgaard, M. Neurofeedback Modulation of the Sound-induced Flash Illusion Using Parietal Cortex Alpha Oscillations Reveals Dependency on Prior Multisensory Congruency. Neuroscience 482 , 1–17 (2022). Keil, J. & Senkowski, D. Neural Oscillations Orchestrate Multisensory Processing. Neuroscientist 24 , 609–626 (2018). Jimenez, M., Hinojosa, J. A. & Montoro, P. R. Visual awareness and the levels of processing hypothesis: A critical review. Conscious. Cogn. 85 , 103022 (2020). Jimenez, M. et al. The Level of Processing Modulates Visual Awareness: Evidence from Behavioral and Electrophysiological Measures. J. Cogn. Neurosci. 33 , 1295–1310 (2021). Overgaard, M., Rote, J., Mouridsen, K. & Ramsøy, T. Z. Is conscious perception gradual or dichotomous? A comparison of report methodologies during a visual task. Conscious. Cogn. 15 , 700–708 (2006). Roth-Paysen, M. L., Bröcker, A., Bruchmann, M. & Straube, T. Early and late electrophysiological correlates of gradual perceptual awareness in- and outside the Attentional Blink window. NeuroImage 263 , 119652 (2022). Cohen, M., Keefe, J. & Brady, T. Perceptual awareness occurs along a graded continuum: Evidence from psychophysical scaling. J. Vis. 23 , 5178 (2023). Eiserbeck, A., Enge, A., Rabovsky, M. & Rahman, R. A. Graded Visual Consciousness During the Attentional Blink. Preprint at (2021). https://doi.org/10.1101/2021.01.15.426792 Karabay, A. et al. Two faces of perceptual awareness during the attentional blink: Gradual and discrete. J. Exp. Psychol. Gen. 151 , 1520–1541 (2022). Nieuwenhuis, S. & de Kleijn, R. Consciousness of targets during the attentional blink: a gradual or all-or-none dimension? Atten. Percept. Psychophys . 73 , 364–373 (2011). Sekar, K., Findley, W. M. & Llinás, R. R. Evidence for an all-or-none perceptual response: single-trial analyses of magnetoencephalography signals indicate an abrupt transition between visual perception and its absence. Neuroscience 206 , 167–182 (2012). Sergent, C. & Dehaene, S. Is Consciousness a Gradual Phenomenon? Evidence for an All-or-None Bifurcation During the Attentional Blink. Psychol. Sci. 15 , 720–728 (2004). Maris, E. & Oostenveld, R. Nonparametric statistical testing of EEG- and MEG-data. J. Neurosci. Methods . 164 , 177–190 (2007). Brainard, D. H. The Psychophysics Toolbox. Spat Vis 433–436 (1997). Kleiner, M., Brainard, D. H. & Pelli, D. What’s new in Psychtoolbox-3? (2007). Overgaard, M. & Sandberg, K. Kinds of access: different methods for report reveal different kinds of metacognitive access. Philos. Trans. R Soc. B Biol. Sci. 367 , 1287–1296 (2012). Overgaard, M. & Sandberg, K. The Perceptual Awareness Scale—recent controversies and debates. Neurosci. Conscious. niab044 (2021). (2021). Green, D. M. & Swets, J. A. Signal Detection Theory and Psychophysics (Wiley, 1966). Hautus, M. J., Macmillan, N. A. & Creelman, C. D. Detection Theory: A User’s Guide (Routledge, 2021). 10.4324/9781003203636 Ille, N., Berg, P. & Scherg, M. Artifact Correction of the Ongoing EEG Using Spatial Filters Based on Artifact and Brain Signal Topographies. J. Clin. Neurophysiol. 19 , 113–124 (2002). Balz, J. et al. GABA concentration in superior temporal sulcus predicts gamma power and perception in the sound-induced flash illusion. NeuroImage 125 , 724–730 (2016). Ebbinghaus. Ebbinghaus, H. The principles of psychology. Veit, Leipzig, 437. (1902). (1902). Jimenez, M., Grassini, S., Montoro, P. R., Luna, D. & Koivisto, M. Neural correlates of visual awareness at stimulus low vs. high-levels of processing. Neuropsychologia 121 , 144–152 (2018). Mazzi, C., Mazzeo, G. & Savazzi, S. Late Positivity Does Not Meet the Criteria to be Considered a Proper Neural Correlate of Perceptual Awareness. Front. Syst. Neurosci. 14 , 36 (2020). Pitts, M. A., Martínez, A. & Hillyard, S. A. Visual Processing of Contour Patterns under Conditions of Inattentional Blindness. J. Cogn. Neurosci. 24 , 287–303 (2012). Shafto, J. P. & Pitts, M. A. Neural Signatures of Conscious Face Perception in an Inattentional Blindness Paradigm. J. Neurosci. 35 , 10940–10948 (2015). Bates, D. et al. Package ‘lme4’. convergence 2 (2015). Sassenhagen, J. & Draschkow, D. Cluster-based permutation tests of MEG/EEG data do not establish significance of effect latency or location. Psychophysiology 56 , e13335 (2019). Eklund, R. & Wiens, S. Visual awareness negativity is an early neural correlate of awareness: A preregistered study with two Gabor sizes. Cogn. Affect. Behav. Neurosci. 18 , 176–188 (2018). Powers, A. R., Mathys, C. & Corlett, P. R. Pavlovian conditioning–induced hallucinations result from overweighting of perceptual priors. Science 357 , 596–600 (2017). Derda, M. et al. The role of levels of processing in disentangling the ERP signatures of conscious visual processing. Conscious. Cogn. 73 , 102767 (2019). Koivisto, M. & Revonsuo, A. The role of selective attention in visual awareness of stimulus features: Electrophysiological studies. Cogn. Affect. Behav. Neurosci. 8 , 195–210 (2008). Doradzińska, Ł. & Bola, M. Early Electrophysiological Correlates of Perceptual Consciousness Are Affected by Both Exogenous and Endogenous Attention. J. Cogn. Neurosci. 36 , 1297–1324 (2024). Hense, A., Peters, A., Bruchmann, M., Dellert, T. & Straube, T. Electrophysiological correlates of sustained conscious perception. Sci. Rep. 14 , 10593 (2024). De Ridder, D., Vanneste, S. & Freeman, W. The Bayesian brain: Phantom percepts resolve sensory uncertainty. Neurosci. Biobehav Rev. 44 , 4–15 (2014). Knill, D. C. & Pouget, A. The Bayesian brain: the role of uncertainty in neural coding and computation. Trends Neurosci. 27 , 712–719 (2004). Chennu, S. et al. Silent Expectations: Dynamic Causal Modeling of Cortical Prediction and Attention to Sounds That Weren’t. J. Neurosci. 36 , 8305–8316 (2016). Wacongne, C. et al. Evidence for a hierarchy of predictions and prediction errors in human cortex. Proc. Natl. Acad. Sci. 108, 20754–20759 (2011). van Erp, J. B. F., Philippi, T. G. & Werkhoven, P. Observers can reliably identify illusory flashes in the illusory flash paradigm. Exp. Brain Res. 226 , 73–79 (2013). Dijkstra, N., Bosch, S. E. & van Gerven, M. A. J. Shared Neural Mechanisms of Visual Perception and Imagery. Trends Cogn. Sci. 23 , 423–434 (2019). Overgaard, M. & Sandberg, K. The Perceptual Awareness Scale—recent controversies and debates. Neurosci. Conscious. niab044 (2021). (2021). Additional Declarations No competing interests reported. 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02:48:34","extension":"jpeg","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":213868,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7535859/v1/282047f49aebcdfa8637089a.jpeg"},{"id":91931914,"identity":"6e1cd939-36a4-4394-9b07-d0f7ec3dc9d9","added_by":"auto","created_at":"2025-09-23 02:32:34","extension":"jpeg","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":24094,"visible":true,"origin":"","legend":"","description":"","filename":"groupimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7535859/v1/3e9ff5460c5cf6723eeb155c.jpeg"},{"id":91931927,"identity":"142e05fc-4304-4602-b9ef-84b6073973a6","added_by":"auto","created_at":"2025-09-23 02:32:34","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1933,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7535859/v1/d8b022f0c48793e84c254597.png"},{"id":91934525,"identity":"8cd752e2-ca1f-4599-b866-09af57006c1c","added_by":"auto","created_at":"2025-09-23 02:40:34","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":23319,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7535859/v1/28b0024d25e50699d0f1594d.png"},{"id":91931915,"identity":"68848107-4dd0-4fa8-a43d-f1078320808b","added_by":"auto","created_at":"2025-09-23 02:32:34","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":55833,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7535859/v1/29cefea46a8322188af22976.png"},{"id":91931919,"identity":"9ab7c1c7-9e4e-4d35-b33a-935cf7f0eba0","added_by":"auto","created_at":"2025-09-23 02:32:34","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":122438,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7535859/v1/c608e122a603d34ff4b6c557.png"},{"id":91934529,"identity":"f1de7894-5ff0-48d6-8c3e-5354240ebcaf","added_by":"auto","created_at":"2025-09-23 02:40:34","extension":"png","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":74701,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7535859/v1/b538cdaee44523a4df877e04.png"},{"id":91936401,"identity":"83c5a3cb-01ae-4eb2-ba88-9345b55c530e","added_by":"auto","created_at":"2025-09-23 02:48:34","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":44659,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7535859/v1/d0e54a37a8baeb9877fa2b70.png"},{"id":91931929,"identity":"de7ead31-c944-4cd3-8fcf-8586884a575d","added_by":"auto","created_at":"2025-09-23 02:32:34","extension":"png","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":9490,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinegroupimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7535859/v1/a87425b626f20d5cd0fe7d37.png"},{"id":91931932,"identity":"059b175b-ec47-4ccf-8fb2-ac25db489ad9","added_by":"auto","created_at":"2025-09-23 02:32:34","extension":"xml","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":165416,"visible":true,"origin":"","legend":"","description":"","filename":"37245f6149024e5e9f492e70ebfc81b41structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7535859/v1/21ad61ef98e001f7f82a3e18.xml"},{"id":91931933,"identity":"2f9e1744-2215-4d69-887c-41e8a6a84c70","added_by":"auto","created_at":"2025-09-23 02:32:34","extension":"html","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":181387,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7535859/v1/85fa082b90d163716a4ca140.html"},{"id":91934520,"identity":"9e6c4661-be6e-4166-ae6a-8cfee4688c6c","added_by":"auto","created_at":"2025-09-23 02:40:34","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":105134,"visible":true,"origin":"","legend":"\u003cp\u003eStimulus Configuration and Experimental Design\u003cstrong\u003e(a) \u003c/strong\u003eTrial sequence and stimulus parameters.\u003cstrong\u003e \u003c/strong\u003eFour randomly presented combinations of auditory (A) and visual (V) stimuli, 1= fist, 2 = second stimulus. \u003cstrong\u003e(b)\u003c/strong\u003e Stimulus onset asynchrony (SOA) and temporal configuration. The speaker icon indicates a 10 ms auditory stimulus; the white disk´s duration was 17 ms. Both sensory stimuli had the same onset. The SOA between first and second stimulus presentation is 83 ms.\u003cstrong\u003e (c)\u003c/strong\u003e Overview of the experimental design. The spatial configuration of the visual stimulus is presented. A white disk(s) were positioned either above (upper visual field, UVF) or below (lower visual filed LVF) the fixation cross. Figure 1a-c is not to scale.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7535859/v1/d794241adea836fa27680332.png"},{"id":91931907,"identity":"2c3dad4f-a8f8-4854-b4ca-ca480d53ff96","added_by":"auto","created_at":"2025-09-23 02:32:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":53710,"visible":true,"origin":"","legend":"\u003cp\u003ePAS Ratings and response probabilities for all conditions. Higher PAS ratings indicate clearer perception of the second stimulus. V = Visual stimulus; A = Auditory stimulus; 1 = first stimulus; 2 = second stimulus; PAS = Perceptual Awareness Scale (1 = no perception of the second stimulus, 2 = vague perception, 3 = almost clear perception, 4 = clear perception).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7535859/v1/112caa64853d4e1292785b0c.png"},{"id":91934530,"identity":"9fc2441c-9bee-4657-ba8f-3b0204c05b83","added_by":"auto","created_at":"2025-09-23 02:40:34","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":192286,"visible":true,"origin":"","legend":"\u003cp\u003eTopography and ERPs for the seen vs. unseen difference in the critical and control condition \u003cstrong\u003ea) \u003c/strong\u003eTopographic maps for the critical condition (A1V2, left) and control condition (V1, right) illustrate the spatiotemporal expression of VAN between 250 to 305 ms for seen versus unseen stimuli over bilateral occipito-temporal sites, with significant clusters (in green) indicating greater negativity for seen stimuli.\u003cstrong\u003e b)\u003c/strong\u003e Electrophysiological results in the critical condition A1V1_A2 and control condition V1: ERPs for seen (PAS \u0026gt;1, blue) and unseen (PAS =1, red) trials. \u003cstrong\u003ec)\u003c/strong\u003e Difference waves visualize the difference between seen - unseen trials. The shaded area around these difference ERPs indicates the 95% bootstrap confidence interval. Error bar plots present the average amplitude at selected sensors and intervals of interest, with a 95% confidence interval. Dashed line marks the second stimulus´ onset.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7535859/v1/5651f0a2e00518077de915ee.png"},{"id":91934524,"identity":"43d078dd-0bfe-470e-beda-3c3f06bb6828","added_by":"auto","created_at":"2025-09-23 02:40:34","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":208282,"visible":true,"origin":"","legend":"\u003cp\u003ePAS Levels in the Critical Condition (\u003cem\u003eN\u003c/em\u003e = 38). ERPs for four PAS categories from PAS1 to PAS 4 (1 = no perception of the second stimulus, 2 = vague perception, 3 = almost clear perception, 4 = clear perception) in the critical condition A1V1_A2. The left panel depicts the ERP with color-coded PAS levels red: PAS 1, light green: PAS 2, dark green: PAS 3, blue: PAS 4, while the right panel shows mean amplitudes with error bars for each PAS level over the 250–305 ms time window.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7535859/v1/3021e3467e1f6d4049b4fe57.png"},{"id":91934526,"identity":"9b7d4023-d392-46e4-b310-ad5a6b89e9ae","added_by":"auto","created_at":"2025-09-23 02:40:34","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":84015,"visible":true,"origin":"","legend":"\u003cp\u003eSpectral analysis of pre-stimulus alpha power. a) Mean alpha-band power is plotted separately for illusion (seen) and no-illusion (unseen) trials. b) Topography of the difference (seen – unseen) in alpha power (8-12 Hz).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7535859/v1/017ac41fc6d49a8cafa73fcb.png"},{"id":97179886,"identity":"b9a7f98a-7671-44d3-b2d3-2b49bc572e43","added_by":"auto","created_at":"2025-12-01 16:17:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1564941,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7535859/v1/a8dcafeb-9165-4c3d-bc46-102561bf022d.pdf"},{"id":91936399,"identity":"1e60a7a4-d0d2-408f-82b8-950ed5fc477f","added_by":"auto","created_at":"2025-09-23 02:48:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":444650,"visible":true,"origin":"","legend":"","description":"","filename":"M144Supplement.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7535859/v1/5b419c7cab7083da3def682b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"More than meets the eye: neural correlates of consciousness in the sound-induced flash illusion","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe neural correlates of consciousness (NCC) refer to the basal neural mechanisms that, in combination, are sufficient \"for any one specific conscious experience\"\u003csup\u003e1\u003c/sup\u003e. In recent years, substantial advances in consciousness research have been achieved, e.g., through studies utilizing electroencephalography (EEG), which suggest potential NCC candidates\u003csup\u003e\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. EEG studies on the neural correlates of visual consciousness typically make a \u0026ldquo;hit vs. miss\u0026rdquo; comparison, i.e., the comparison of trials in which a stimulus was reported as seen, with trials in which the same stimulus was reported as unseen. Based on this approach, an enhanced negative event-related potential (ERP) emerging approximately 100\u0026ndash;300 ms after stimulus onset has been identified; this negativity, known as the Visual Awareness Negativity (VAN), is most prominent over occipital and posterior temporal scalp sites\u003csup\u003e\u003cspan additionalcitationids=\"CR6 CR7 CR8\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. The VAN is claimed to be the earliest and most reliable marker of visual consciousness (for review see\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e) and is in accordance with consciousness theories, which posit a central role of early sensory areas in generating conscious perception of a stimulus\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Previous research shows that a negative deflection is not only measurable in visual perception but also in other sensory modalities. In this framework, the VAN is part of a family of components of perceptual awareness negativities (PAN\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e) with an equivalent in the somatosensory modality (somatosensory awareness negativity, SAN\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e) and the auditory modality (auditory awareness negativity, AAN\u003csup\u003e\u003cspan additionalcitationids=\"CR16 CR17\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e).\u003c/p\u003e\u003cp\u003eYet, the role of the VAN as a direct marker of consciousness remains debated. Conscious access has been associated either with both VAN and subsequent late positive components\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e or with later positive components alone\u003csup\u003e\u003cspan additionalcitationids=\"CR21 CR22 CR23\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. In this framework, the VAN may reflect early, pre-conscious processing, potentially indexing preparatory or unconscious perceptual activity rather than awareness itself\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. If VAN-like negativities also occur without external input such as during illusory perception. This would challenge its interpretation as purely pre-conscious and support its role in conscious awareness. Illusory percepts thus offer a strong test case for disentangling stimulus-driven activity from awareness-related neural markers.\u003c/p\u003e\u003cp\u003eWe examine the question whether the VAN is exclusive to comparisons between seen and missed veridical stimuli, or whether it can also emerge when contrasting illusory percepts with correctly perceived stimulus absence. To our knowledge, only few studies have directly examined early ERPs elicited by consciously perceived but physically absent stimuli. In the auditory domain, studies have either elicited illusions with Pavlovian conditioning\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e or relied on spontaneous auditory illusions occurring in noise\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. In both studies negative deflections were more pronounced for illusory percepts, consistent with the AAN\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. One study also observed a late positivity for illusory percepts, however interpreted as centro-parietal positivity (CPP), suggesting a decision-related or higher-order cognitive process\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. For the visual modality, several studies have examined illusory flashes, triggered by the simultaneous presentation of stimuli in other modalities. With auditory trigger stimuli, this phenomenon is called the Sound-Induced Flash Illusion (SIFI\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003c/sup\u003e see\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e for a Touch-Induced Flash Illusion, TIFI. The SIFI occurs when a single visual flash is accompanied by two auditory beeps, leading participants to perceive a second, non-existent flash\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. The SIFI not only produces a comparably high rate of illusory perceptions in stimulus-absent trials (around 50%\u003csup\u003e33\u003c/sup\u003e) but also enables precise estimation of the perceptual onset, as the illusory second flash coincides subjectively with the onset of the second beep. This inference of the illusory percept's onset allows for investigating ERPs associated with visual illusions. The SIFI is widely used to study multisensory integration (for review see\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e) but few studies have compared ERPs between illusion and non-illusion trials \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e or between participants with low versus high illusion rates. These studies have yielded heterogeneous findings. Notably, they have not specifically addressed the VAN but followed a predominantly exploratory approach. A positive deflection peaked at 120 ms over occipital sites, was localized to extrastriate visual cortex and covaried across participants with susceptibility to the sound-induced flash illusion, whereas on a trial-by-trial basis illusion perception was associated with enhanced negative deflections peaking at 110 ms (auditory cortex) and 130 ms (superior temporal gyrus\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e). In a follow-up study, a fronto-central negativity at 130\u0026ndash;160 ms distinguished illusion from no-illusion trials and was localized to superior temporal gyrus; the earlier 120 ms occipito-temporal positivity was replicated as a cross modal interaction effect\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. A later negativity peaking at 270 ms with a centroparietal maximum appeared in cross modal interaction difference waves for both illusory and veridical second flash conditions\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Additionally, an event-related difference at 265\u0026ndash;280 ms, source-localized to cingulate cortex, differentiated illusion from non-illusion trials\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. In a TIFI paradigm, an occipital difference between 140\u0026ndash;185 ms distinguished illusion from no-illusion trials\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, indicating VAN-like spatial and temporal properties.\u003c/p\u003e\u003cp\u003eBeyond evoked potentials, oscillatory dynamics, particularly in the alpha band, are central to shaping perceptual outcomes, modulating excitability and perceptual thresholds (for comprehensive review see\u003csup\u003e\u003cspan additionalcitationids=\"CR39 CR40 CR41 CR42 CR43\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e). Alpha activity has also been linked to illusory perception. In auditory paradigms like speech-in-noise tasks, illusion trials are associated with reduced alpha power over temporal regions, reflecting heightened cortical excitability\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. However, this is not consistent across paradigms: Faramarzi et al.\u003csup\u003e28\u003c/sup\u003e found no pre-stimulus alpha differences between illusory and non-illusory auditory trials. In SIFI and TIFI paradigms, alpha-band dynamics show consistent correlations with illusion susceptibility. Lower individual alpha frequency\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e, reduced pre-stimulus alpha power\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e, and specific alpha phase alignments\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e have each been associated with a higher likelihood of illusion perception (for review see\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e).\u003c/p\u003e\u003cp\u003eTo assess subjective illusion perception, it is essential to provide participants with a means of reporting their conscious experience. The Perceptual Awareness Scale (PAS) offers a sensitive and theoretically grounded approach for capturing gradations in illusion perception. It distinguishes between varying levels of conscious access and has been shown to align well with both behavioral and electrophysiological measures\u003csup\u003e\u003cspan additionalcitationids=\"CR51 CR52\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. Notably, there is an ongoing debate as to whether consciousness unfolds gradually\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan additionalcitationids=\"CR53 CR54 CR55 CR56\" citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e, or appears in an all-or-none manner\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e,\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e. This ongoing controversy underscores the relevance of nuanced tools like PAS for mapping the structure of conscious experience.\u003c/p\u003e\u003cp\u003eThe current study employed an adapted SIFI paradigm to reliably elicit illusory percepts in approximately 50% of trials. Leveraging a large sample size and fine-grained subjective reports, this study aims to determine whether VAN-like negativities can also be observed for consciously perceived illusory stimuli, i.e., in the absence of physical visual input, and whether these correlate with graded levels or dichotomous states of reported consciousness. In addition, the study tests whether pre-stimulus alpha-band activity, specifically its power, predicts the likelihood of illusion perception.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003e\u003cem\u003eParticipants\u003c/em\u003e\u003c/p\u003e\u003cp\u003eSixty right-handed volunteers between 18 and 30 years old (female\u0026thinsp;=\u0026thinsp;49; male\u0026thinsp;=\u0026thinsp;10; divers\u0026thinsp;=\u0026thinsp;1) were recruited at the University of Muenster to participate in the EEG experiment. An a-priori sample size calculation was on one hand not feasible due to expected inter-individual variability in illusion susceptibility and on the other hand incompatible with the planned cluster-based permutation (CBP\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e) analysis. Anticipating relatively small effect sizes and accounting for an estimated dropout rate of 10% and expected data loss (e.g., due to artifact rejection and behavioral exclusion), we selected the largest practicable sample size available, resulting in the above mentioned recruited sample of \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;60. All participants had normal or corrected-to-normal vision and no history of psychiatric or neurological diseases. Participants provided written informed consent and received monetary compensation of 12 euros per hour. One participant was excluded because their behavioral data indicated that they were unable to distinguish between one or two flashes presented without auditory stimuli (\u003cem\u003ed\u0026rsquo;\u003c/em\u003e = 0.35). Furthermore, 12 subjects were excluded because they did not provide enough trials to obtain reliable ERPs (see section EEG data analysis). This resulted in the final number of \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;47 participants (female\u0026thinsp;=\u0026thinsp;38; male\u0026thinsp;=\u0026thinsp;8; divers\u0026thinsp;=\u0026thinsp;1: \u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;23.13 years, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.39 years) who were included in the main statistical analysis. The study was approved by and conducted following the guidelines of the ethics committee of the local medical association (\u0026Auml;rztekammer Westfalen-Lippe; 2019-049-f-S).\u003c/p\u003e\u003cp\u003e\u003cem\u003eApparatus\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe experiment was run with Matlab (R2021a, Mathworks Inc., Natick, MA; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.mathworks\u003c/span\u003e\u003cspan address=\"http://www.mathworks\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. com) and the Psychophysics toolbox\u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e,\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. Stimuli were displayed on an LCD monitor (Iiyama G-Master GB2488HSU; 1920 \u0026times; 1080 pixels, 60 Hz) on a black background (0.35 cd/m\u003csup\u003e2\u003c/sup\u003e) in a dimly lit room. Participants were seated at a viewing distance of \u0026asymp;\u0026thinsp;60 cm in front of the computer. A chin rest was used to prevent head movements during the experiment. Auditory stimuli were presented via two loudspeakers, positioned to the left and right of the monitor.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStimuli and presentation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOur EEG study was based on the SIFI paradigm to induce an illusion and then analyze its neural correlates. Therefore, we used two types of stimuli: Auditory (A) stimuli consisted of 1000 Hz sinusoidal beeps, lasting 10 ms, at 80 dB SPL (measured at mid chinrest position, horizontally centered and approximately at mid-head height). Simultaneously, visual (V) stimuli were presented as white flashes, appearing as discs with a 1\u0026deg; visual diameter and a luminance of 330 cd/m\u0026sup2;. Each flash was presented for 17 ms (Figure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). As peripheral presentation of visual stimuli increases the likelihood of successfully eliciting illusions compared to centrally presented triggers\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, the discs were positioned either in the lower visual field (LVF) or in the upper visual field (UVF; Figure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb) in a random order, at an eccentricity of 6\u0026deg; from the central fixation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eExperimental design and statistical analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eProcedure\u003c/b\u003e\u003c/p\u003e\u003cp\u003e Participants were instructed beforehand, emphasizing that their responses should reflect their personal, initial visual impressions and spontaneous decisions, rather than deliberating on what might be considered \"right\" or \"wrong.\" The main experiment lasted approximately 1 hour and consisted of 960 trials in total, divided into 12 blocks, each containing 80 trials. Every block was separated by breaks to relax the eyes and to get informed about how many trials they had already completed out of the total number. By pressing a key, they were able to proceed with the experiment on their own terms. Four different stimulus combinations were randomly presented (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea) each occurring 240 times (120 UVF, 120 LVF). The combinations included unimodal visual stimuli appearing singly (V1) or in pairs (V1V2) and bimodal combinations: A1V1_A2V2 and A1V1_A2 (=\u0026thinsp;illusion condition, see definition-below). The stimulus onset asynchrony (SOA) was set at 83 ms. Each trial started with a fixation cross (randomized duration between 1-1.5 s), followed by one of the above-described stimulus combinations. Participants were asked to watch the cross permanently. After each trial, the subjects were prompted to report the visibility of the second flash with a 600 ms delay after the stimulus offset (in order to minimize motor-related activity during the analysis of ERPs).\u003c/p\u003e\u003cp\u003eFor the reports, we used the perceptual awareness scale to measure the subjective perception as sensitively as possible\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e,\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e. In pilot experiments, we asked three observers to verbalize their percept on each trial. This procedure led to an adapted 4-leveled scale, closely resembling the scale labels\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e,\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e. The participants were instructed to use the PAS by pressing the keys 1 to 4 on a standard keyboard with the following adapted labels: 1 = \"\u003cem\u003eno experience of a second flash\u003c/em\u003e\", 2 = \u0026ldquo;\u003cem\u003evague experience of a second flash\u003c/em\u003e\u0026rdquo;, 3 = \u0026ldquo;\u003cem\u003ealmost clear experience of a second flash\u003c/em\u003e\u0026rdquo;, 4 = \u0026ldquo;\u003cem\u003eclear experience of a second flash\u003c/em\u003e\u0026rdquo;. Prior to the main experiment, 32-trial practice sessions were conducted to familiarize participants with the possible perceptual outcomes and the corresponding PAS levels.\u003c/p\u003e\u003cp\u003e\u003cb\u003eBehavioral Data Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo obtain a measure of the individual ability to discriminate the presentation of one and two flashes (i.e. conditions V1 and V1V2), we dichotomized the PAS responses, relabeling PAS\u0026thinsp;=\u0026thinsp;1 as \u0026ldquo;no (second flash)\u0026rdquo; and PAS\u0026thinsp;\u0026gt;\u0026thinsp;1 as \u0026ldquo;yes (second flash)\u0026rdquo;. Based on the relative proportions of hits (p(\u0026ldquo;yes\u0026rdquo; | V1V2)) and correct rejections, (p(\u0026ldquo;no\u0026rdquo; | V1)), we calculated the signal detection theory-based index d' \u003csup\u003e65,66\u003c/sup\u003e. To quantify the effect of auditory stimulation on the frequency of illusory perception of a second flash, we calculated the difference between the relative frequencies p(\u0026ldquo;yes\u0026rdquo; | V1) and p(\u0026ldquo;yes\u0026rdquo; | A1V1_A2).\u003c/p\u003e\u003cp\u003e\u003cb\u003eEEG recording and preprocessing\u003c/b\u003e\u003c/p\u003e\u003cp\u003eElectrophysiological data were collected using a 64-channel BioSemi active electrode system (BioSemi B.V., Amsterdam, Netherlands). Electrodes were positioned according to the extended international 10\u0026ndash;20 system as implemented in the BioSemi 64-channel cap. The BioSemi EEG system replaces traditional ground and reference electrodes with a CMS/DRL feedback loop, using two additional electrodes. Vertical eye movements (VEOG) were recorded with electrodes placed above and below the left eye, while horizontal eye movements (HEOG) were captured with electrodes at the outer canthi of both eyes. Electrical potentials were recorded, maintaining electrode offsets below 20 \u0026micro;V.\u003c/p\u003e\u003cp\u003eEEG data preprocessing was performed using Brain Electrical Source Analysis (BESA) Research 6.0 (BESA GmbH, Gr\u0026auml;feling, Germany). Offline data were re-referenced to an average reference and filtered with a 0.01 Hz high-pass zero-phase filter (12 dB/oct) and a 40 Hz low-pass zero-phase filter (24 dB/oct). A 50 Hz notch filter was applied to remove line noise. Channels with extreme noise were identified by eye inspection and subsequently interpolated (number of interpolated channels\u0026thinsp;\u0026le;\u0026thinsp;13; \u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.74, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.66). Eye movements were corrected with BESA's automatic eye-artifact correction method\u003csup\u003e\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u003c/sup\u003e. Additional artifacts were removed using BESA's semi-automatic, principal component analysis (PCA) based artifact topography algorithm, with manual selection of artifacts. Trials exhibiting muscle artifacts, electrode jumps, or amplitudes exceeding a 100 \u0026micro;V threshold were rejected following visual inspection.\u003c/p\u003e\u003cp\u003eThe main analysis focused on the comparison of trials with and without illusions (henceforth called 'seen' and 'unseen', referring to the second flash) in the critical condition, i.e., A1V1_A2. The proportion of illusion trials can vary across subjects\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e,\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e,\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e. Thus, in our experiment some subjects may provide unreliable ERPs for either the seen or unseen condition if they are based on a low number of trials. While including only subjects with a high number of trials optimizes the reliability of individual ERPs, it reduces the overall sample size and, thus, the reliability of the grand average ERP. To optimize this trade-off, we chose a data-driven, hypothesis-independent approach and systematically evaluated the signal-to-noise ratio (SNR) of the critical condition, i.e., averaged across seen and unseen trials, for a range of minimum trial numbers (between 10 and 100 in steps of 5). To be included in the final sample, the number of seen and the number of unseen trials in the critical condition had to match or exceed this number. For each minimum trial count, we calculated the root mean square (RMS) of the averaged EEG signal. SNR was derived as the ratio of RMS signal during the critical time window (0\u0026ndash;300 ms) to the baseline period (-200-0 ms). The highest SNR was observed at 30 trials, leading to the exclusion of the above-mentioned 12 participants. The average number of analyzed trials in the final sample in the critical conditions was mean\u003csub\u003eunseen\u003c/sub\u003e = 120.96 (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;46.53) and mean\u003csub\u003eseen\u003c/sub\u003e = 106.89 (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;45.51).\u003c/p\u003e\u003cp\u003eIllusory percepts were also expected to occur without auditory stimulation, i.e., in the V1 condition. These illusions were expected to be less frequent, as the participants\u0026rsquo; expectation of a second flash was not influenced by the auditory stimulus but by the perceived probability of the appearance of a second flash. To validate possible VAN effects observed in the critical condition, we performed a comparison for seen vs unseen second flash also in the V1 condition. We applied the same SNR-optimization approach also for this comparison, which led to the exclusion of 26 participants. The average number of trials analyzed in the final for the control condition was mean\u003csub\u003eunseen\u003c/sub\u003e = 148.09 (SD\u0026thinsp;=\u0026thinsp;41.34) and mean\u003csub\u003eseen\u003c/sub\u003e = 80.12 (SD\u0026thinsp;=\u0026thinsp;38.21).\u003c/p\u003e\u003cp\u003e\u003cb\u003eEEG data analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIntervals and electrodes of interest were defined based on previous studies to optimize the detection of electrodes maximally responsive to the VAN. We considered all posterior and occipital electrodes, as supported by prior research (e.g.\u003csup\u003e7,8,70,71\u003c/sup\u003e), which indicates that these regions show heightened negativity linked to early conscious visual processing. Prior studies (for review see\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e,\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e) suggest that the typical VAN time window falls somewhere between 100\u0026ndash;300 ms. In our study, we focused on VAN effects following the second (illusory) flash, occurring 80 ms after the first flash onset. Consequently, we expected the VAN response to appear around 180\u0026ndash;380 ms post the initial flash onset in the critical condition (A1V1_A2). Within the defined interval and electrodes of interest, we employed a CBP\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. CBP tests were performed by computing a paired-sample t-test at each channel and sample of interest. The cluster mass was calculated by summing all t-values with alpha\u0026thinsp;\u0026lt;\u0026thinsp;.05 (one-sided negative) neighboring in time and space (the minimum number of channels to form a cluster was 2). The number of permutations was \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5000 and the significance threshold for testing the null hypothesis was alpha\u0026thinsp;\u0026lt;\u0026thinsp;.05. The interval of interest extended from 180 to 380 ms and the channels of interest included P1, P3, P5, P7, P9, PO7, PO3, O1, Iz, Oz, POz, Pz, P2, P4, P6, P8, P10, PO8, PO4, and O2. Secondary analyses and visualization of ERPs were conducted using electrodes identified as significant, i.e., all channels with at least one significant sample. Additionally, we explored whether the VAN followed a gradual or dichotomous pattern across the four levels of the PAS scale, using the cluster average, i.e., the mean value of the significant sensors and samples described by the cluster as a measure of the VAN amplitude. We then compared Linear Mixed-Effects Models (LME) with single-trial VAN amplitudes as the dependent variable (DV). All analyses were conducted in R, utilizing the lme4 package\u003csup\u003e\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u003c/sup\u003e for model building and the readr package for data handling and preprocessing. Only trials from the critical experimental condition were retained for analysis. The DV was centered and scaled to facilitate the interpretation of model parameters. To evaluate gradual effects, perceptual awareness was decomposed into orthogonal polynomial contrasts, capturing linear, quadratic, and cubic trends\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. A baseline model was constructed with only a random intercept for participants to account for individual differences in VAN amplitude. Subsequent models incorporated predictors reflecting either gradual changes in perceptual awareness or dichotomous perceptual outcomes. To test for a dichotomous pattern of awareness, a fixed effects model was specified using a categorical predictor that indexed trials as either illusion or no-illusion, despite identical physical stimulation. This model included a fixed effect for the dichotomous predictor and a random intercept for participant ID. Fixed effects models were selected because models with random slopes failed to converge. Likelihood ratio tests were used to compare model fits, allowing us to assess whether variability in VAN amplitude was better accounted for by gradual or dichotomous patterns of perceptual awareness.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSpectral analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePower spectra were computed using a Fast Fourier Transform of single-trial raw data in the 500 ms pre-stimulus time window. Power was tested for differences between illusion and no-illusion trials in the alpha frequency range (8 to 12 Hz), averaged across three channels, which showed the strongest overall alpha power (PO3, POz, PO4).\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003eBehavioral data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDistribution of awareness ratings\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePAS Ratings for all experimental conditions are shown in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. In 20.98% (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.154) of trials in the V1 condition, participants reported perceiving a second flash (PAS\u0026thinsp;\u0026gt;\u0026thinsp;1) despite its physical absence, which allowed us to use this condition as a control comparison. A one-way repeated-measures ANOVA revealed a significant main effect of condition on the relative frequency of PAS1 responses, F(3, 184)\u0026thinsp;=\u0026thinsp;315.059, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, \u0026eta;\u0026sup2; = .855, indicating that the frequency of perceiving only one flash varied substantially across conditions. As shown in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, PAS1 responses (i.e.,\u0026nbsp;\u003cem\u003e\u0026ldquo;no second flash perceived\u0026rdquo;\u003c/em\u003e) were most frequent in the unimodal visual condition (V1) and least frequent in the multisensory congruent condition (A1V1_A2V2).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRelative frequency of PAS1 responses per condition\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCondition\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean (M)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eV1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7902\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1539\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eV1_V2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0711\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eA1V1_A2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0274\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0306\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eA1V1_A2V2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4733\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1979\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003ePairwise comparisons (Table 2) confirmed statistically significant differences between all conditions (p \u0026lt; .001). Notably, the comparison between the two bimodal conditions (illusion vs. veridical: A1V1_V2 vs. A1V1_A2V2) revealed a significant difference, t(46) = 4.58, p \u0026lt; .001, d = 0.59.\u003c/p\u003e\n\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003ePairwise comparisons of PAS1 frequencies between conditions\u003c/div\u003e\n\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n\u003ctable id=\"Taba\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eComparison\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003et(59)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean Difference\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCohen\u0026rsquo;s d\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eV1 vs. V1_V2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34.9619\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7331\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.0997\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eV1 vs. A1V1_A2V2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34.6793\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7628\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.0585\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eV1 vs. A1V1_A2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.1170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.0381\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eV1_V2 vs. A1V1_A2V2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.6954\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.5390\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eV1_V2 vs. A1V1_A2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-12.3706\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.4162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.8044\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eA1V1_A2V2 vs. A1V1_A2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-14.4465\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.4459\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.1072\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eElectroencephalography data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs noted above, a sample of \u003cem\u003en\u0026thinsp;=\u003c/em\u003e\u0026thinsp;33 remained after applying the criterion of a minimal number of 30 seen and 30 unseen trials for this control comparison. The main analysis is based on comparisons between seen and unseen trials in the critical condition (A1V1_A2). Figure \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e (left) shows the corresponding ERPs and the differential topography. A control analysis is presented for the comparisons between seen and unseen trials in the V1 condition. Corresponding ERPs and topographies are depicted in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e (right). ERPs to the four experimental conditions without post-hoc sorting into seen and unseen trials are presented in the Supplementary Material.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVisual Awareness Negativity - Seen vs. unseen comparison\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor the critical condition (A1V1_A2), we observed a significant cluster in the interval and channels of interest (cluster mass = -167.765, p\u0026thinsp;=\u0026thinsp;0.016). Descriptively, the cluster extended from approximately 250 to 305 ms, as shown in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, which depicts the ERPs averaged across all significant electrodes (P1, Pz, P2, PO3, POz, PO4, and O2). Since CBP tests do not precisely establish the latency and location of effects\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e, the spatiotemporal extents of clusters are provided only for descriptive purposes. On the right side in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, we also provide results for the control condition (V1) for the comparison of trials with and without the illusory perception of a second flash. In both conditions, the VAN can be shown in the expected time window.\u003c/p\u003e\n\u003cp\u003eThe topographies in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea visualize the spatiotemporal dynamics of the VAN within the significant time window of 250\u0026ndash;305 ms where seen stimuli exhibit greater negativity compared to unseen stimuli. The significant cluster of electrodes is marked in green for the critical condition. The topographies for both conditions show a negativity predominantly localized over posterior-central sites. We tested whether VAN in the critical condition was affected by upper or lower presentation using a Bayesian paired t-test, to determine whether presentation location influenced VAN amplitudes. The results confirmed that there was moderate evidence for the null hypothesis (BF01\u0026thinsp;=\u0026thinsp;4.9453) i.e., for no VAN differences between the upper and lower hemifield.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGradual vs. dichotomous correlates\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBoth linear mixed-effects model treating PAS as a gradual or a dichotomous (see vs unseen) predictor of VAN amplitude significantly outperformed the null model, (\u0026chi;\u0026sup2;(1)\u0026thinsp;=\u0026thinsp;6.94, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.008 for the graded and \u0026chi;\u0026sup2;(1)\u0026thinsp;=\u0026thinsp;5.52, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.019, for the binary model. However, PAS showed only a marginally better fit than detection (AIC: \u0026minus;\u0026thinsp;17356 vs. \u0026minus;\u0026thinsp;17355; BIC: \u0026minus;\u0026thinsp;17327 vs. \u0026minus;\u0026thinsp;17326), which does not indicate a meaningful statistical difference in overall model fit. Thus, while both Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e and statistical results suggest at least descriptively a gradual component in the VAN response, our data allow no firm conclusions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExploratory analysis of pre-stimulus alpha power\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAlpha-band power in the pre-stimulus interval was stronger preceding trials without illusions compared to trials with illusion (t(46)\u0026thinsp;=\u0026thinsp;2.32; p\u0026thinsp;=\u0026thinsp;.025; two tailed; Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eWe analyzed whether the VAN could serve as a NCC even in the absence of direct sensory stimulation. We used the SIFI paradigm to examine whether the VAN would be elicited when participants perceived an illusory second flash compared to non-illusory conditions and found a negativity between 250\u0026ndash;300 ms, aligning with established VAN characteristics(e.g.\u003csup\u003e7,26,70,76\u003c/sup\u003e). Our findings foster the robustness of the VAN as a correlate of subjective visual experience even in illusory perception contexts, supporting the notion that the VAN may reflect conscious perception itself, even when no physical visual input is present.\u003c/p\u003e\u003cp\u003eOur results contrast with accounts that question the VAN\u0026rsquo;s role in conscious perception and instead link awareness more consistently to later ERP components\u003csup\u003e\u003cspan additionalcitationids=\"CR21 CR22 CR23\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e and with views that interpret the VAN as reflecting early, pre-conscious processing\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Conversely, other work associates conscious access with both the VAN and a subsequent late positivity\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Our findings provide a counterpoint to a purely pre-conscious interpretation: because a VAN-like negative deflection is present during the conscious perception of physically absent stimuli, its generation cannot be reduced to stimulus-driven input alone and may index processes tied to conscious awareness.\u003c/p\u003e\u003cp\u003eOur results are consistent with EEG and MEG studies indicating that illusory and veridical perception can share key neural signatures\u0026mdash;especially in oscillatory dynamics and ERP profiles\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u003c/sup\u003e. Most EEG studies on the SIFI address multisensory integration rather than the neural determinants of perceptual awareness. However, a few studies have directly contrasted illusion and no-illusion perception. A fronto-central negativity around 130\u0026ndash;160 ms has been shown to distinguish illusion from no-illusion trials, although without the posterior distribution typical of the VAN\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. An event-related difference at 265\u0026ndash;280 ms, source-localized to cingulate cortex, has also been linked to illusion perception, but this effect differs from ours in both timing and scalp topography\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. In a touch-induced illusion, an occipital difference 140\u0026ndash;185 ms distinguished illusion from no-illusion trials\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e and was thus spatially and temporally similar to our effect. Two previous studies, which induced auditory illusions, reported also negativities as correlates of illusory perception. An ERP interpretable as the auditory-awareness negativity was identified in a study which relied on spontaneous auditory illusions occurring in noise and contrasted trials with and without reported perception, allowing for a direct comparison of perceived versus unperceived auditory events\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Furthermore, in a study which used a design with associative learning between cues and auditory stimuli, an AAN was observed over temporal and parietal electrodes between 200\u0026ndash;300 ms, closely paralleling the visual VAN in timing and distribution\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. We focused our ERP analysis on posterior scalp sites, encompassing occipital, parieto-occipital, and lateral temporal electrodes (see\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e). Within this a-priori space, we detected a robust negative deflection that temporally matches the VAN but peaks over mid-parietal electrodes (P1, Pz, P2, PO3, POz, PO4, O2). Studies show that the VAN amplitude and scalp distribution can shift with stimulus complexity\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e,\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e,\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e\u003c/sup\u003e, perceptual visibility (for review see\u003csup\u003e\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u003c/sup\u003e), task relevance (e.g.\u003csup\u003e80\u003c/sup\u003e) and experimental context\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e,\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e. Hence, our findings contribute to the growing evidence that VAN (topography) does not seem to be a fixed phenotype but can be modulated by experimental context.\u003c/p\u003e\u003cp\u003eIn addition to ERPs, we examined oscillatory dynamics, particularly alpha-band activity. Other than in an auditory illusion study which found no pre-stimulus alpha differences between illusion and no-illusion trials\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e, our results are in line with studies showing that lower individual alpha frequency\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e, reduced pre-stimulus alpha power\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e, and specific pre-stimulus alpha phase alignments\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e increase susceptibility to illusion perception in the SIFI and TIFI paradigms (for review see\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e). While these studies interpret alpha primarily within the framework of temporal precision for multisensory integration, we suggest that alpha frequency may also index the cortical conditions underlying the access of perceptual content to conscious perception, modulating whether internally or externally driven signals gain perceptual access.\u003c/p\u003e\u003cp\u003eFor a comprehensive account of the neural marker, the correspondence with participants\u0026rsquo; subjective reports is critical. The behavioral data from the V1, V1_V2 and A1V1_A2V2 conditions provide benchmarks, validating participants\u0026rsquo; reports across varying sensory contexts. There is reason to consider the PAS ratings in our study as a meaningful reflection of subjective experience. The V1_V2 and A1V1_A2V2 conditions exhibit progressively higher PAS responses where additional sensory information enhances perceptual clarity. In the critical condition, illusions were observed on 50% of trials, congruent with the literature (for review see\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e). Overall, the resulting distribution of ratings confirms our previous expectations and in addition to the consistent pattern across conditions, this supports the reliability of the behavioral data in our study. However, we also found that in 24% of V1 trials (where only one flash was presented without any auditory input) participants reported perceiving a second flash, despite the absence of a corresponding stimulus. These illusion in our study design can be interpreted within a predictive coding framework, which suggests that strong perceptual priors (shaped, for instance, by repeated exposure) can give rise to illusory percepts in the absence of external input\u003csup\u003e\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e,\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e\u003c/sup\u003e. In our paradigm, one- and two-flash trials were deliberately made difficult to distinguish, introducing residual uncertainty into the system. Under such conditions, the brain integrates prior knowledge with incoming sensory data to minimize prediction error, especially in regions lacking strong afferent stimulation. When predictions closely match incoming input, residual errors can become negligible, allowing early cortical activity to resemble that of veridical perception, even when the stimulus is absent\u003csup\u003e\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e,\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e\u003c/sup\u003e. The frequent occurrence of two-flash trials likely strengthened participants\u0026rsquo; prior expectation that a second flash would follow the first. This learned association may have contributed to the emergence of double-flash percepts, even when only one flash without auditory input was presented. Illusions in the unimodal V1 condition occurred less frequently than in the multisensory SIFI condition, where the auditory beep further reinforced the \u0026ldquo;two-flash\u0026rdquo; prior. Yet this convergence of real and illusory perception has its limits. Participants seem to be able to reliably distinguish between true and illusory percepts\u003csup\u003e\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e\u003c/sup\u003e. Research on mental imagery demonstrates that while vivid mental images share substantial overlap with veridical perception, they can still be differentiated both behaviorally and in neural activation patterns (for review see\u003csup\u003e\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e\u003c/sup\u003e).\u003c/p\u003e\u003cp\u003eA question that stays vacant is whether conscious perception unfolds gradually or appears in an all-or-none manner. When plotting ERPs for the four PAS categories in the critical condition, visual inspection suggested a gradual pattern of consciousness. Yet, the data seem to lack statistical power to support a statistical difference between the gradual and the dichotomous model. Descriptively, the gradual model shows a slightly better fit, which is in line with several studies\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e,\u003cspan additionalcitationids=\"CR52 CR53 CR54 CR55\" citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e (but see\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e,\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e) and supports the importance of suited measurement of graded experience\u003csup\u003e\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eWe acknowledge several limitations. As outlined above, our goal to gain additional information about the graded vs. dichotomous nature of illusory awareness from the four levels of the PAS could not be reached despite a large number of trials and participants. While the PAS model demonstrated a descriptive advantage over the binary detection model in predicting VAN amplitude, the lack of a statistically significant difference prevents any conclusions and future studies with more power are needed. Furthermore, we used a specific experimental design to induce illusory percepts. It would be helpful to include different designs in future studies in order to provide data if results can be generalized across designs.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur findings demonstrate that VAN-like negativities can emerge in response to subjectively perceived visual stimuli, even in the absence of external stimulation. This challenges interpretations of the VAN as purely stimulus-driven and strengthens its candidacy as a neural correlate of visual awareness and illustrate how studies on visual illusions can inform the research on NCC.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003cbr\u003e\u0026nbsp;\u003c/strong\u003eWe thank Lisann Lübbers for assistance with data collection and the Open Access Publication Fund of the University of Münster for support. This research received no specific external funding. Especially we thank all study participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThese authors contributed equally: Theresa Rieger, Josefine Feuerstein\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eT.R.:\u0026nbsp;\u003c/strong\u003eConceptualization, Piloting, Methodology, Investigation, Data Curation, Software, Formal analysis, Visualization, Writing – original draft, Writing – review and editing, Project administration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eJ.F.:\u0026nbsp;\u003c/strong\u003eConceptualization, Piloting, Methodology, Investigation, Data Curation, Software, Formal analysis, Visualization, Writing – original draft, Writing – review and editing, Project administration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eN.A.B.:\u003c/strong\u003e Methodology, Data Curation, Software, Formal analysis, Writing – review and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eT.S.:\u003c/strong\u003e Conceptualization, Methodology, Supervision, Writing – Review \u0026amp; Editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eM.B.:\u003c/strong\u003e Conceptualization, Methodology, Software, Formal analysis, Supervision, Visualization, Writing – original draft, Writing – review and editing, Project administration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to [email protected]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author(s) declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding declaration statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdditional information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSupplementary Information The online version contains supplementary material available at:\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCrick, F. \u0026amp; Koch, C. A framework for consciousness. \u003cem\u003eNat. Neurosci.\u003c/em\u003e \u003cb\u003e6\u003c/b\u003e, 119\u0026ndash;126 (2003).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDembski, C., Koch, C. \u0026amp; Pitts, M. Physiological Correlates of Sensory Consciousness: Evidence for a Perceptual Awareness Negativity. Preprint at (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.31234/osf.io/ma36g\u003c/span\u003e\u003cspan address=\"10.31234/osf.io/ma36g\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eF\u0026ouml;rster, J., Koivisto, M. \u0026amp; Revonsuo, A. ERP and MEG correlates of visual consciousness: The second decade. \u003cem\u003eConscious. Cogn.\u003c/em\u003e \u003cb\u003e80\u003c/b\u003e, 102917 (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKoch, C., Massimini, M., Boly, M. \u0026amp; Tononi, G. Neural correlates of consciousness: progress and problems. \u003cem\u003eNat. Rev. Neurosci.\u003c/em\u003e \u003cb\u003e17\u003c/b\u003e, 307\u0026ndash;321 (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDellert, T. et al. Dissociating the Neural Correlates of Consciousness and Task Relevance in Face Perception Using Simultaneous EEG-fMRI. \u003cem\u003eJ. Neurosci.\u003c/em\u003e \u003cb\u003e41\u003c/b\u003e, 7864\u0026ndash;7875 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKoivisto, M. \u0026amp; Grassini, S. Neural processing around 200 ms after stimulus-onset correlates with subjective visual awareness. \u003cem\u003eNeuropsychologia\u003c/em\u003e \u003cb\u003e84\u003c/b\u003e, 235\u0026ndash;243 (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKoivisto, M. \u0026amp; Revonsuo, A. Event-related brain potential correlates of visual awareness. \u003cem\u003eNeurosci. Biobehav Rev.\u003c/em\u003e \u003cb\u003e34\u003c/b\u003e, 922\u0026ndash;934 (2010).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePitts, M. A., Metzler, S. \u0026amp; Hillyard, S. A. Isolating neural correlates of conscious perception from neural correlates of reporting one\u0026rsquo;s perception. \u003cem\u003eFront Psychol\u003c/em\u003e \u003cb\u003e5\u003c/b\u003e, (2014).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchlossmacher, I., Dellert, T., Pitts, M., Bruchmann, M. \u0026amp; Straube, T. Differential Effects of Awareness and Task Relevance on Early and Late ERPs in a No-Report Visual Oddball Paradigm. \u003cem\u003eJ. Neurosci.\u003c/em\u003e \u003cb\u003e40\u003c/b\u003e, 2906\u0026ndash;2913 (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLamme, V. A. F. Visual Functions Generating Conscious Seeing. \u003cem\u003eFront. Psychol.\u003c/em\u003e \u003cb\u003e11\u003c/b\u003e, 83 (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLamme, V. A. F. \u0026amp; Roelfsema, P. R. The distinct modes of vision offered by feedforward and recurrent processing. \u003cem\u003eTrends Neurosci.\u003c/em\u003e \u003cb\u003e23\u003c/b\u003e, 571\u0026ndash;579 (2000).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDembski, C., Koch, C. \u0026amp; Pitts, M. Perceptual awareness negativity: a physiological correlate of sensory consciousness. \u003cem\u003eTrends Cogn. Sci.\u003c/em\u003e \u003cb\u003e25\u003c/b\u003e, 660\u0026ndash;670 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAuksztulewicz, R. \u0026amp; Blankenburg, F. Subjective Rating of Weak Tactile Stimuli Is Parametrically Encoded in Event-Related Potentials. \u003cem\u003eJ. Neurosci.\u003c/em\u003e \u003cb\u003e33\u003c/b\u003e, 11878\u0026ndash;11887 (2013).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchr\u0026ouml;der, P., Nierhaus, T. \u0026amp; Blankenburg, F. Dissociating Perceptual Awareness and Postperceptual Processing: The P300 Is Not a Reliable Marker of Somatosensory Target Detection. \u003cem\u003eJ. Neurosci.\u003c/em\u003e \u003cb\u003e41\u003c/b\u003e, 4686\u0026ndash;4696 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEklund, R., Gerdfeldter, B. \u0026amp; Wiens, S. Effects of a Manual Response Requirement on Early and Late Correlates of Auditory Awareness. \u003cem\u003eFront. Psychol.\u003c/em\u003e \u003cb\u003e10\u003c/b\u003e, 2083 (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEklund, R., Gerdfeldter, B. \u0026amp; Wiens, S. Is auditory awareness negativity confounded by performance? \u003cem\u003eConscious. Cogn.\u003c/em\u003e \u003cb\u003e83\u003c/b\u003e, 102954 (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEklund, R. \u0026amp; Wiens, S. Auditory awareness negativity is an electrophysiological correlate of awareness in an auditory threshold task. \u003cem\u003eConscious. Cogn.\u003c/em\u003e \u003cb\u003e71\u003c/b\u003e, 70\u0026ndash;78 (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchlossmacher, I., Dellert, T., Bruchmann, M. \u0026amp; Straube, T. Dissociating neural correlates of consciousness and task relevance during auditory processing. \u003cem\u003eNeuroImage\u003c/em\u003e \u003cb\u003e228\u003c/b\u003e, 117712 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYe, M., Lyu, Y., Sclodnick, B. \u0026amp; Sun, H. J. The P3 Reflects Awareness and Can Be Modulated by Confidence. \u003cem\u003eFront. Neurosci.\u003c/em\u003e \u003cb\u003e13\u003c/b\u003e, 510 (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBabiloni, C., Vecchio, F., Miriello, M., Romani, G. L. \u0026amp; Rossini, P. M. Visuo-spatial Consciousness and Parieto-occipital Areas: A High-resolution EEG Study. \u003cem\u003eCereb. Cortex\u003c/em\u003e. \u003cb\u003e16\u003c/b\u003e, 37\u0026ndash;46 (2006).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDehaene, S. \u0026amp; Changeux, J. P. Experimental and Theoretical Approaches to Conscious Processing. \u003cem\u003eNeuron\u003c/em\u003e \u003cb\u003e70\u003c/b\u003e, 200\u0026ndash;227 (2011).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLamy, D., Salti, M. \u0026amp; Bar-Haim, Y. Neural Correlates of Subjective Awareness and Unconscious Processing: An ERP Study. \u003cem\u003eJ. Cogn. Neurosci.\u003c/em\u003e \u003cb\u003e21\u003c/b\u003e, 1435\u0026ndash;1446 (2009).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSalti, M., Bar-Haim, Y. \u0026amp; Lamy, D. The P3 component of the ERP reflects conscious perception, not confidence. \u003cem\u003eConscious. Cogn.\u003c/em\u003e \u003cb\u003e21\u003c/b\u003e, 961\u0026ndash;968 (2012).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSergent, C., Baillet, S. \u0026amp; Dehaene, S. Timing of the brain events underlying access to consciousness during the attentional blink. \u003cem\u003eNat. Neurosci.\u003c/em\u003e \u003cb\u003e8\u003c/b\u003e, 1391\u0026ndash;1400 (2005).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAru, J., Bachmann, T., Singer, W. \u0026amp; Melloni, L. Distilling the neural correlates of consciousness. \u003cem\u003eNeurosci. Biobehav Rev.\u003c/em\u003e \u003cb\u003e36\u003c/b\u003e, 737\u0026ndash;746 (2012).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRailo, H., Koivisto, M. \u0026amp; Revonsuo, A. Tracking the processes behind conscious perception: A review of event-related potential correlates of visual consciousness. \u003cem\u003eConscious. Cogn.\u003c/em\u003e \u003cb\u003e20\u003c/b\u003e, 972\u0026ndash;983 (2011).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFilimonov, D., Lenkkeri, S., Koivisto, M. \u0026amp; Revonsuo, A. Event-related potential correlates of consciousness in simple auditory hallucinations. \u003cem\u003eNeuroImage\u003c/em\u003e \u003cb\u003e310\u003c/b\u003e, 121168 (2025).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFaramarzi, M. et al. Similar EEG Activity Patterns During Experimentally-Induced Auditory Illusions and Veridical Perceptions. \u003cem\u003eFront. Neurosci.\u003c/em\u003e \u003cb\u003e15\u003c/b\u003e, 602437 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShams, L., Kamitani, Y. \u0026amp; Shimojo, S. Visual illusion induced by sound. \u003cem\u003eCogn. Brain Res.\u003c/em\u003e \u003cb\u003e14\u003c/b\u003e, 147\u0026ndash;152 (2002).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShams, L., Ma, W. J. \u0026amp; Beierholm, U. Sound-induced flash illusion as an optimal percept. \u003cem\u003eNeuroReport\u003c/em\u003e \u003cb\u003e16\u003c/b\u003e, 1923\u0026ndash;1927 (2005).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003evan Erp, J. B. F., Philippi, T. G., de Winkel, K. N. \u0026amp; Werkhoven, P. Pre- and post-stimulus EEG patterns associated with the touch-induced illusory flash. \u003cem\u003eNeurosci. Lett.\u003c/em\u003e \u003cb\u003e562\u003c/b\u003e, 79\u0026ndash;84 (2014).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShams, L., Kamitani, Y. \u0026amp; Shimojo, S. What you see is what you hear. \u003cem\u003eNature\u003c/em\u003e \u003cb\u003e408\u003c/b\u003e, 788\u0026ndash;788 (2000).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKeil, J. Double Flash Illusions: Current Findings and Future Directions. \u003cem\u003eFront. Neurosci.\u003c/em\u003e \u003cb\u003e14\u003c/b\u003e, 298 (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHirst, R. J., McGovern, D. P., Setti, A., Shams, L. \u0026amp; Newell, F. N. What you see is what you hear: Twenty years of research using the Sound-Induced Flash Illusion. \u003cem\u003eNeurosci. Biobehav Rev.\u003c/em\u003e \u003cb\u003e118\u003c/b\u003e, 759\u0026ndash;774 (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHuang, J., Wang, E., Lu, K., Wang, A. \u0026amp; Zhang, M. Long-term training reduces the responses to the sound-induced flash illusion. \u003cem\u003eAtten. Percept. Psychophys\u003c/em\u003e. \u003cb\u003e84\u003c/b\u003e, 529\u0026ndash;539 (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMishra, J., Martinez, A., Sejnowski, T. J. \u0026amp; Hillyard, S. A. Early cross-modal interactions in auditory and visual cortex underlie a sound-induced visual illusion. \u003cem\u003eJ. Neurosci. Off J. Soc. Neurosci.\u003c/em\u003e \u003cb\u003e27\u003c/b\u003e, 4120\u0026ndash;4131 (2007).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMishra, J., Mart\u0026iacute;nez, A. \u0026amp; Hillyard, S. A. Effect of Attention on Early Cortical Processes Associated with the Sound-induced Extra Flash Illusion. \u003cem\u003eJ. Cogn. Neurosci.\u003c/em\u003e \u003cb\u003e22\u003c/b\u003e, 1714\u0026ndash;1729 (2010).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKeil, J., M\u0026uuml;ller, N., Hartmann, T. \u0026amp; Weisz, N. Prestimulus Beta Power and Phase Synchrony Influence the Sound-Induced Flash Illusion. \u003cem\u003eCereb. Cortex\u003c/em\u003e. \u003cb\u003e24\u003c/b\u003e, 1278\u0026ndash;1288 (2014).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBalestrieri, E. \u0026amp; Busch, N. A. Spontaneous Alpha-Band Oscillations Bias Subjective Contrast Perception. \u003cem\u003eJ. Neurosci.\u003c/em\u003e \u003cb\u003e42\u003c/b\u003e, 5058\u0026ndash;5069 (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBusch, N. A., Dubois, J. \u0026amp; VanRullen, R. The Phase of Ongoing EEG Oscillations Predicts Visual Perception. \u003cem\u003eJ. Neurosci.\u003c/em\u003e \u003cb\u003e29\u003c/b\u003e, 7869\u0026ndash;7876 (2009).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChaumon, M. \u0026amp; Busch, N. A. Prestimulus Neural Oscillations Inhibit Visual Perception via Modulation of Response Gain. \u003cem\u003eJ. Cogn. Neurosci.\u003c/em\u003e \u003cb\u003e26\u003c/b\u003e, 2514\u0026ndash;2529 (2014).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIemi, L., Chaumon, M., Crouzet, S. M. \u0026amp; Busch, N. A. Spontaneous Neural Oscillations Bias Perception by Modulating Baseline Excitability. \u003cem\u003eJ. Neurosci.\u003c/em\u003e \u003cb\u003e37\u003c/b\u003e, 807\u0026ndash;819 (2017).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIemi, L. \u0026amp; Busch, N. A. Moment-to-Moment Fluctuations in Neuronal Excitability Bias Subjective Perception Rather than Strategic Decision-Making. \u003cem\u003eeneuro\u003c/em\u003e 5, ENEURO.0430-17.2018 (2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003evan Dijk, H., Schoffelen, J. M., Oostenveld, R. \u0026amp; Jensen, O. Prestimulus Oscillatory Activity in the Alpha Band Predicts Visual Discrimination Ability. \u003cem\u003eJ. Neurosci.\u003c/em\u003e \u003cb\u003e28\u003c/b\u003e, 1816\u0026ndash;1823 (2008).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchepers, E., Bodar, L., van Os, J. \u0026amp; Lousberg, R. Cortical processes of speech illusions in the general population. \u003cem\u003eBMC Neurosci.\u003c/em\u003e \u003cb\u003e17\u003c/b\u003e, 65 (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCecere, R., Rees, G. \u0026amp; Romei, V. Individual Differences in Alpha Frequency Drive Crossmodal Illusory Perception. \u003cem\u003eCurr. Biol.\u003c/em\u003e \u003cb\u003e25\u003c/b\u003e, 231\u0026ndash;235 (2015).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKeil, J. \u0026amp; Senkowski, D. Individual Alpha Frequency Relates to the Sound-Induced Flash Illusion. \u003cem\u003eMultisensory Res.\u003c/em\u003e \u003cb\u003e30\u003c/b\u003e, 565\u0026ndash;578 (2017).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKvamme, T. L., Sarmanlu, M., Bailey, C. \u0026amp; Overgaard, M. Neurofeedback Modulation of the Sound-induced Flash Illusion Using Parietal Cortex Alpha Oscillations Reveals Dependency on Prior Multisensory Congruency. \u003cem\u003eNeuroscience\u003c/em\u003e \u003cb\u003e482\u003c/b\u003e, 1\u0026ndash;17 (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKeil, J. \u0026amp; Senkowski, D. Neural Oscillations Orchestrate Multisensory Processing. \u003cem\u003eNeuroscientist\u003c/em\u003e \u003cb\u003e24\u003c/b\u003e, 609\u0026ndash;626 (2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJimenez, M., Hinojosa, J. A. \u0026amp; Montoro, P. R. Visual awareness and the levels of processing hypothesis: A critical review. \u003cem\u003eConscious. Cogn.\u003c/em\u003e \u003cb\u003e85\u003c/b\u003e, 103022 (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJimenez, M. et al. The Level of Processing Modulates Visual Awareness: Evidence from Behavioral and Electrophysiological Measures. \u003cem\u003eJ. Cogn. Neurosci.\u003c/em\u003e \u003cb\u003e33\u003c/b\u003e, 1295\u0026ndash;1310 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOvergaard, M., Rote, J., Mouridsen, K. \u0026amp; Rams\u0026oslash;y, T. Z. Is conscious perception gradual or dichotomous? A comparison of report methodologies during a visual task. \u003cem\u003eConscious. Cogn.\u003c/em\u003e \u003cb\u003e15\u003c/b\u003e, 700\u0026ndash;708 (2006).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRoth-Paysen, M. L., Br\u0026ouml;cker, A., Bruchmann, M. \u0026amp; Straube, T. Early and late electrophysiological correlates of gradual perceptual awareness in- and outside the Attentional Blink window. \u003cem\u003eNeuroImage\u003c/em\u003e \u003cb\u003e263\u003c/b\u003e, 119652 (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCohen, M., Keefe, J. \u0026amp; Brady, T. Perceptual awareness occurs along a graded continuum: Evidence from psychophysical scaling. \u003cem\u003eJ. Vis.\u003c/em\u003e \u003cb\u003e23\u003c/b\u003e, 5178 (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEiserbeck, A., Enge, A., Rabovsky, M. \u0026amp; Rahman, R. A. Graded Visual Consciousness During the Attentional Blink. Preprint at (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1101/2021.01.15.426792\u003c/span\u003e\u003cspan address=\"10.1101/2021.01.15.426792\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKarabay, A. et al. Two faces of perceptual awareness during the attentional blink: Gradual and discrete. \u003cem\u003eJ. Exp. Psychol. Gen.\u003c/em\u003e \u003cb\u003e151\u003c/b\u003e, 1520\u0026ndash;1541 (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNieuwenhuis, S. \u0026amp; de Kleijn, R. Consciousness of targets during the attentional blink: a gradual or all-or-none dimension? \u003cem\u003eAtten. Percept. Psychophys\u003c/em\u003e. \u003cb\u003e73\u003c/b\u003e, 364\u0026ndash;373 (2011).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSekar, K., Findley, W. M. \u0026amp; Llin\u0026aacute;s, R. R. Evidence for an all-or-none perceptual response: single-trial analyses of magnetoencephalography signals indicate an abrupt transition between visual perception and its absence. \u003cem\u003eNeuroscience\u003c/em\u003e \u003cb\u003e206\u003c/b\u003e, 167\u0026ndash;182 (2012).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSergent, C. \u0026amp; Dehaene, S. Is Consciousness a Gradual Phenomenon? Evidence for an All-or-None Bifurcation During the Attentional Blink. \u003cem\u003ePsychol. Sci.\u003c/em\u003e \u003cb\u003e15\u003c/b\u003e, 720\u0026ndash;728 (2004).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMaris, E. \u0026amp; Oostenveld, R. Nonparametric statistical testing of EEG- and MEG-data. \u003cem\u003eJ. Neurosci. Methods\u003c/em\u003e. \u003cb\u003e164\u003c/b\u003e, 177\u0026ndash;190 (2007).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBrainard, D. H. The Psychophysics Toolbox. \u003cem\u003eSpat Vis\u003c/em\u003e 433\u0026ndash;436 (1997).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKleiner, M., Brainard, D. H. \u0026amp; Pelli, D. What\u0026rsquo;s new in Psychtoolbox-3? (2007).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOvergaard, M. \u0026amp; Sandberg, K. Kinds of access: different methods for report reveal different kinds of metacognitive access. \u003cem\u003ePhilos. Trans. R Soc. B Biol. Sci.\u003c/em\u003e \u003cb\u003e367\u003c/b\u003e, 1287\u0026ndash;1296 (2012).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOvergaard, M. \u0026amp; Sandberg, K. The Perceptual Awareness Scale\u0026mdash;recent controversies and debates. \u003cem\u003eNeurosci. Conscious.\u003c/em\u003e niab044 (2021). (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGreen, D. M. \u0026amp; Swets, J. A. \u003cem\u003eSignal Detection Theory and Psychophysics\u003c/em\u003e (Wiley, 1966).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHautus, M. J., Macmillan, N. A. \u0026amp; Creelman, C. D. \u003cem\u003eDetection Theory: A User\u0026rsquo;s Guide\u003c/em\u003e (Routledge, 2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4324/9781003203636\u003c/span\u003e\u003cspan address=\"10.4324/9781003203636\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIlle, N., Berg, P. \u0026amp; Scherg, M. Artifact Correction of the Ongoing EEG Using Spatial Filters Based on Artifact and Brain Signal Topographies. \u003cem\u003eJ. Clin. Neurophysiol.\u003c/em\u003e \u003cb\u003e19\u003c/b\u003e, 113\u0026ndash;124 (2002).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBalz, J. et al. GABA concentration in superior temporal sulcus predicts gamma power and perception in the sound-induced flash illusion. \u003cem\u003eNeuroImage\u003c/em\u003e \u003cb\u003e125\u003c/b\u003e, 724\u0026ndash;730 (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEbbinghaus. Ebbinghaus, H. The principles of psychology. Veit, Leipzig, 437. (1902). (1902).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJimenez, M., Grassini, S., Montoro, P. R., Luna, D. \u0026amp; Koivisto, M. Neural correlates of visual awareness at stimulus low vs. high-levels of processing. \u003cem\u003eNeuropsychologia\u003c/em\u003e \u003cb\u003e121\u003c/b\u003e, 144\u0026ndash;152 (2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMazzi, C., Mazzeo, G. \u0026amp; Savazzi, S. Late Positivity Does Not Meet the Criteria to be Considered a Proper Neural Correlate of Perceptual Awareness. \u003cem\u003eFront. Syst. Neurosci.\u003c/em\u003e \u003cb\u003e14\u003c/b\u003e, 36 (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePitts, M. A., Mart\u0026iacute;nez, A. \u0026amp; Hillyard, S. A. Visual Processing of Contour Patterns under Conditions of Inattentional Blindness. \u003cem\u003eJ. Cogn. Neurosci.\u003c/em\u003e \u003cb\u003e24\u003c/b\u003e, 287\u0026ndash;303 (2012).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShafto, J. P. \u0026amp; Pitts, M. A. Neural Signatures of Conscious Face Perception in an Inattentional Blindness Paradigm. \u003cem\u003eJ. Neurosci.\u003c/em\u003e \u003cb\u003e35\u003c/b\u003e, 10940\u0026ndash;10948 (2015).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBates, D. et al. Package \u0026lsquo;lme4\u0026rsquo;. \u003cem\u003econvergence\u003c/em\u003e 2 (2015).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSassenhagen, J. \u0026amp; Draschkow, D. Cluster-based permutation tests of MEG/EEG data do not establish significance of effect latency or location. \u003cem\u003ePsychophysiology\u003c/em\u003e \u003cb\u003e56\u003c/b\u003e, e13335 (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEklund, R. \u0026amp; Wiens, S. Visual awareness negativity is an early neural correlate of awareness: A preregistered study with two Gabor sizes. \u003cem\u003eCogn. Affect. Behav. Neurosci.\u003c/em\u003e \u003cb\u003e18\u003c/b\u003e, 176\u0026ndash;188 (2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePowers, A. R., Mathys, C. \u0026amp; Corlett, P. R. Pavlovian conditioning\u0026ndash;induced hallucinations result from overweighting of perceptual priors. \u003cem\u003eScience\u003c/em\u003e \u003cb\u003e357\u003c/b\u003e, 596\u0026ndash;600 (2017).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDerda, M. et al. The role of levels of processing in disentangling the ERP signatures of conscious visual processing. \u003cem\u003eConscious. Cogn.\u003c/em\u003e \u003cb\u003e73\u003c/b\u003e, 102767 (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKoivisto, M. \u0026amp; Revonsuo, A. The role of selective attention in visual awareness of stimulus features: Electrophysiological studies. \u003cem\u003eCogn. Affect. Behav. Neurosci.\u003c/em\u003e \u003cb\u003e8\u003c/b\u003e, 195\u0026ndash;210 (2008).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDoradzińska, Ł. \u0026amp; Bola, M. Early Electrophysiological Correlates of Perceptual Consciousness Are Affected by Both Exogenous and Endogenous Attention. \u003cem\u003eJ. Cogn. Neurosci.\u003c/em\u003e \u003cb\u003e36\u003c/b\u003e, 1297\u0026ndash;1324 (2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHense, A., Peters, A., Bruchmann, M., Dellert, T. \u0026amp; Straube, T. Electrophysiological correlates of sustained conscious perception. \u003cem\u003eSci. Rep.\u003c/em\u003e \u003cb\u003e14\u003c/b\u003e, 10593 (2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDe Ridder, D., Vanneste, S. \u0026amp; Freeman, W. The Bayesian brain: Phantom percepts resolve sensory uncertainty. \u003cem\u003eNeurosci. Biobehav Rev.\u003c/em\u003e \u003cb\u003e44\u003c/b\u003e, 4\u0026ndash;15 (2014).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKnill, D. C. \u0026amp; Pouget, A. The Bayesian brain: the role of uncertainty in neural coding and computation. \u003cem\u003eTrends Neurosci.\u003c/em\u003e \u003cb\u003e27\u003c/b\u003e, 712\u0026ndash;719 (2004).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChennu, S. et al. Silent Expectations: Dynamic Causal Modeling of Cortical Prediction and Attention to Sounds That Weren\u0026rsquo;t. \u003cem\u003eJ. Neurosci.\u003c/em\u003e \u003cb\u003e36\u003c/b\u003e, 8305\u0026ndash;8316 (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWacongne, C. et al. Evidence for a hierarchy of predictions and prediction errors in human cortex. \u003cem\u003eProc. Natl. Acad. Sci.\u003c/em\u003e 108, 20754\u0026ndash;20759 (2011).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003evan Erp, J. B. F., Philippi, T. G. \u0026amp; Werkhoven, P. Observers can reliably identify illusory flashes in the illusory flash paradigm. \u003cem\u003eExp. Brain Res.\u003c/em\u003e \u003cb\u003e226\u003c/b\u003e, 73\u0026ndash;79 (2013).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDijkstra, N., Bosch, S. E. \u0026amp; van Gerven, M. A. J. Shared Neural Mechanisms of Visual Perception and Imagery. \u003cem\u003eTrends Cogn. Sci.\u003c/em\u003e \u003cb\u003e23\u003c/b\u003e, 423\u0026ndash;434 (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOvergaard, M. \u0026amp; Sandberg, K. The Perceptual Awareness Scale\u0026mdash;recent controversies and debates. \u003cem\u003eNeurosci. Conscious.\u003c/em\u003e niab044 (2021). (2021).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"NCC, EEG/ERP, visual awareness, consciousness, VAN, illusions","lastPublishedDoi":"10.21203/rs.3.rs-7535859/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7535859/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe visual awareness negativity (VAN) has been identified as a potential neuronal correlate of consciousness (NCC). The VAN is typically found when comparing experimental trials in which a stimulus was perceived with trials in which the same stimulus was not perceived. However, if the VAN represents a reliable NCC, it should also be observed under conditions in which participants report conscious perception despite the absence of a corresponding visual stimulus, i.e., a visual illusion. Our event-related potential (ERP) study (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;47) aimed to investigate this question by using a suited stimulation design, the sound-induced flash illusion (SIFI), for which a visual stimulus is presented once together with two short beeps, leading - on about half the trials - to the illusory perception of a second flash, with graded levels of reported awareness of these trials. When comparing illusory with non-illusory trials, we found an enhanced negativity over posterior electrodes between 250 and 300 ms. Frequency analyses additionally revealed lower pre-stimulus alpha power in illusion trials, aligning with prior work linking alpha dynamics to perceptual variability. Our findings suggest that even illusory perceptions enhance negative potentials over posterior regions during the VAN interval, supporting the interpretation of the VAN as a NCC.\u003c/p\u003e","manuscriptTitle":"More than meets the eye: neural correlates of consciousness in the sound-induced flash illusion","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-23 02:32:29","doi":"10.21203/rs.3.rs-7535859/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-29T18:15:17+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-29T14:19:03+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-14T15:12:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"32228779088695676204473025081944618671","date":"2025-09-14T07:54:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"66799129524341862052646670614127469659","date":"2025-09-12T15:37:51+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-12T13:18:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-12T12:45:27+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-12T11:30:48+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-10T14:01:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-09-10T13:57:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0d45c89f-f4be-414f-9eea-8e6035cab49e","owner":[],"postedDate":"September 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":54884818,"name":"Biological sciences/Neuroscience"},{"id":54884819,"name":"Biological sciences/Psychology"},{"id":54884820,"name":"Social science/Psychology"}],"tags":[],"updatedAt":"2025-12-01T16:16:38+00:00","versionOfRecord":{"articleIdentity":"rs-7535859","link":"https://doi.org/10.1038/s41598-025-28068-5","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-11-28 15:57:27","publishedOnDateReadable":"November 28th, 2025"},"versionCreatedAt":"2025-09-23 02:32:29","video":"","vorDoi":"10.1038/s41598-025-28068-5","vorDoiUrl":"https://doi.org/10.1038/s41598-025-28068-5","workflowStages":[]},"version":"v1","identity":"rs-7535859","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7535859","identity":"rs-7535859","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}