The human brain mechanisms of afterimages: From networks to cortical layers

The human brain mechanisms of afterimages: From networks to cortical layers | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (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];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results The human brain mechanisms of afterimages: From networks to cortical layers View ORCID Profile Sharif I. Kronemer , Burak Akin , Micah Holness , A. Tyler Morgan , Laurentius Huber , Paul A. Taylor , Javier Gonzalez-Castillo , Daniel A. Handwerker , Peter A. Bandettini doi: https://doi.org/10.1101/2025.08.30.673266 Sharif I. Kronemer 1 Section on Functional Imaging Methods, Laboratory of Brain and Cognition (LBC), National Institute of Mental Health (NIMH), National Institutes of Health (NIH) , Bethesda, MD, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Sharif I. Kronemer For correspondence: sharif.kronemer{at}nih.gov Burak Akin 1 Section on Functional Imaging Methods, Laboratory of Brain and Cognition (LBC), National Institute of Mental Health (NIMH), National Institutes of Health (NIH) , Bethesda, MD, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Micah Holness 1 Section on Functional Imaging Methods, Laboratory of Brain and Cognition (LBC), National Institute of Mental Health (NIMH), National Institutes of Health (NIH) , Bethesda, MD, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site A. Tyler Morgan 1 Section on Functional Imaging Methods, Laboratory of Brain and Cognition (LBC), National Institute of Mental Health (NIMH), National Institutes of Health (NIH) , Bethesda, MD, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Laurentius Huber 2 Functional MRI Facility, NIMH , NIH, Bethesda, MD, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Paul A. Taylor 3 Scientific and Statistical Computing Core , NIMH, NIH, Bethesda, MD, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Javier Gonzalez-Castillo 1 Section on Functional Imaging Methods, Laboratory of Brain and Cognition (LBC), National Institute of Mental Health (NIMH), National Institutes of Health (NIH) , Bethesda, MD, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Daniel A. Handwerker 1 Section on Functional Imaging Methods, Laboratory of Brain and Cognition (LBC), National Institute of Mental Health (NIMH), National Institutes of Health (NIH) , Bethesda, MD, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Peter A. Bandettini 1 Section on Functional Imaging Methods, Laboratory of Brain and Cognition (LBC), National Institute of Mental Health (NIMH), National Institutes of Health (NIH) , Bethesda, MD, USA 2 Functional MRI Facility, NIMH , NIH, Bethesda, MD, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract Afterimages are common visual illusions that have long attracted scientific interest, yet their neural mechanisms remain little understood. We used high-spatial-resolution fMRI to investigate human whole brain and cortical layer activity in primary visual cortex (V1) linked with afterimages and perceptually matching animated images – stimuli designed to imitate the appearance of afterimages. Both afterimages and perceptually matched images engaged overlapping, widespread brain activity, particularly in visual sensory regions that follow the contralateral circuitry of the primary visual pathway. However, afterimages elicited weaker fMRI signals across many subcortical and cortical areas compared to images, except in salience network regions, where activity was enhanced for afterimages. Cortical layer-specific analyses in V1 revealed afterimages selectively engaged deep cortical layers, while images activated middle and superficial layers. In addition, we found that baseline eye measures and fMRI signals in arousal and visual networks differed depending on whether afterimages were perceived or not perceived. We argue that these results challenge the prevailing framing on the neurophysiological origins of afterimages as arising from either retinal or central neural processes. As with image perception, typical afterimages emerge by the interaction between retinal activity and central neural processing. Introduction Afterimages – historically known as “visual persistence”, “aftereffects”, or “ocular spectra” – are common visual illusions. Typically, afterimages are induced by a light source that is no longer physically present. For instance, when headlights from a car disappear from view at night or when looking away from an image on a computer screen, an illusory conscious vision may appear with similar visual features (e.g., shape and visual field location) as the original light source that can last for many seconds, even in total darkness or when the eyes are closed. Afterimages are perceived as either the same color (positive afterimages) or a complementary color (negative afterimages) as the inducing image. While afterimages are specific to vision, there are analogous forms of perseverating sensory perception in audition and somatosensation [ 1 , 2 ]. Afterimages have been studied for millennia. Nevertheless, the precise neural mechanisms of afterimages remain little understood. The role of retinal signaling following photoreceptor adaptation or bleaching (e.g., after viewing a bright light) is commonly referenced [ 3 ]. Likewise, Hermann von Helmholtz characterized afterimages as “a photograph on the retina” [ 4 ]. A retinal-based mechanism is supported by the observation that afterimage position in visual space is updated with gaze position [ 4 – 6 ]. Also supporting a retinal contribution are afterimage-linked signals or “after-responses” that are found in retinal afferents and relay cells of the cat and monkey lateral geniculate nucleus (LGN) [ 7 , 8 ]. In addition, even without photoreceptor bleaching, retinal ganglion cells in monkeys have been shown to evoke a post-stimulation rebound, potentially the sourcing signal of afterimages, although this response persists beyond the typical perceived duration of afterimages [ 9 ]. However, retinal-only explanations for afterimages are incomplete. The relative contribution of retinal versus central neural mechanisms in afterimage perception has long been debated and remains unresolved [ 3 ]. Cerebral generation of afterimages without retinal input has also been considered [ 10 ]. Involvement of central neural processes in afterimage perception is supported by behavioral research highlighting that afterimages can be induced by illusory images or when afterimages appear where there was no previous light (e.g., filling-in illusions) [ 11 , 12 ]. There are even reports of afterimages induced by hallucination and visual imagery [ 13 – 17 ]. Interocular grouping (i.e., the perceptual integration of monocular afterimages) [ 18 ], afterimage rivalry [ 19 ], and conditioned afterimages (e.g., afterimages induced by conditioned tones) are also suggestive of central neural mechanisms [ 18 , 20 , 21 ]. Further, the modulation of afterimage perception by eye movements is evidence for post-retinal modulation of afterimages [ 22 ]. Also highlighting the potential involvement of cortical processes in modifying the neural signals underlying afterimages are findings showing afterimage perception is altered by visual illusions (e.g., illusory depth and surface slant) [ 23 , 24 ]. Direct support for the role of cortex in afterimage perception include findings in non-human animals of persistent visual cortical neural activity after the offset of visual stimuli that induce afterimages [ 25 , 26 ]. Also, human cortical evoked potentials have been recorded with electroencephalography during the perception of afterimages, including a link between afterimages and depressed alpha frequency band activity [ 27 – 30 ]. Furthermore, disrupting human occipital cortical electrophysiology with transcranial magnetic stimulation was found to alter afterimages [ 31 ]. Localization of the brain regions associated with afterimages is suggested by the few human fMRI experiments that found afterimage-linked blood-oxygen-level-dependent (BOLD) signal in human primary visual cortex (V1), fusiform gyrus (FG) and area V8 [ 32 – 35 ]. Likewise, a monkey fMRI study found afterimage-linked brain responses throughout visual cortex, including V2, V3, and V4 [ 36 ]. Although, another experiment found that lesioning V4 and MT did not eliminate the perception of afterimages [ 37 ]. These findings support the involvement of the visual cortex in afterimages, indicating that it may contribute to modifying retinal inputs that drive central neural activity observed with afterimages or even generating the afterimage signal itself. Further interpretation is limited because none of the current fMRI studies report findings outside of visual cortex and all were implemented with spatial resolution that do not allow for interpreting meso-scale dynamics, including cortical layer specific activity patterns that can infer the direction of information processing [ 38 ]. Our goal was to advance beyond the limitations of prior neuroimaging studies on afterimages to further elucidate the brain mechanisms of afterimages. To achieve this, here, we conducted the first human whole brain and the first human cortical layer resolution fMRI study of afterimages. In a previous behavioral experiment [ 39 ], we gathered perceptual details (sharpness, contrast, and duration) on afterimages from healthy, adult participants. We used those reports in the current investigation to design animated images that perceptually matched with each participant’s afterimage experience. These tailored images were referred to as “mock afterimages” to emphasize their perceptual similarity to actual afterimages, despite being physically present stimuli. In the current experiment, afterimages and perceptually matched images were administered in a perception task while recording pupillometry and eye tracking, and whole brain fMRI or cortical-layer resolution V1 fMRI. We hypothesized that afterimages and perceptually matched images would evoke similar activity in visual cortex and across association cortices. However, some differences could be present in the perceptual reality monitoring brain network that may distinguish illusory afterimages from real images. Based on previous behavioral findings linking afterimages to sensory-independent perception (e.g., hallucination and imagery) and their sensitivity to top-down effects (e.g., priming), we hypothesized that afterimages would involve V1 layer activity suggestive of feedback neural signaling, whereas images would exhibit a laminar profile characteristic of feedforward signaling. Leveraging the results from this study to elucidate the central neural processing of afterimages is valuable for explaining centuries of behavioral research on afterimage perception and can be broadly informative on the neural mechanisms underlying visual consciousness [ 40 ]. Methods Participants Healthy, adult participants were recruited from the local Bethesda, Maryland, United States of America (USA) community (N = 35; males = 15; mean age = 28.03 years [standard deviation (SD) = 8.73]; mean education = 16.49 years [SD = 1.42]). All participants completed a behavioral and whole brain fMRI study session (see Whole brain fMRI sequence section). In addition, a subset of the participants (N = 13; males = 4; mean age = 31.54 years [SD = 10.41]; mean education = 17.69 years [SD = 2.32]) completed a layer-resolution V1 fMRI study session (see V1 fMRI sequence section). Recruitment was completed in accordance with the National Institute of Mental Health Institutional Review Board, and all participants gave informed consent prior to participation. Inclusion criteria were: (1) between 18 and 65 years old, (2) completion of a healthy physical examination by a nurse practitioner within a year of the study sessions, (3) able to provide informed consent. Exclusion criteria were: (1) current or previous histories of neurologic or psychiatric disorder, (2) low vision (i.e., unable to read small text on a computer screen) that could not be corrected, (3) head injuries (e.g., loss of consciousness for > 30 minutes and three or more concussive injuries). In addition, three participants were excluded from analyses of the whole brain fMRI data set due to behavioral performance (incorrect reporting during the behavioral tasks; two participants) or reporting that they did not see afterimages following the inducer stimulus (one participant; see Afterimage induction section). In the V1 study, one participant was excluded from analyses because they did not complete the study session. Of the remaining participants, exclusions from analyses were made as follows: two participants were excluded due to persistent artifacts in the BOLD and/or vascular space occupancy (VASO) signals, and two participants were excluded because they did not show a V1 BOLD or VASO response for task events, thus preventing defining a V1 region of interest (see V1 region of interest section). In total, 32 participants were included in the whole brain fMRI data analysis, and 8 participants were included in the V1 fMRI data analysis. Additional participant exclusions were made for the supplementary analyses on the eye tracking and pupillometry data and whole brain fMRI data for specific event conditions based on data quality and number of data epochs (see Analysis Methods section). Behavior Afterimage induction Afterimages were induced using a black silhouette image of a human face in frontal view (presentation duration = 4 seconds; visual angle = 4.60 x 8.47 degrees; maximum luminance = ∼4 cd/m 2 ; https://creazilla.com/nodes/2524-face-silhouette ; Figure 1A ; Supplementary Movie 1). See [ 39 ] for full details on the inducer stimulus. All participants indicated that the inducer resulted in negative afterimages that appeared as a white or light gray, blurry version of the face image and was positioned in the same on-screen location as the inducer when maintaining central fixation. Download figure Open in new tab Figure 1. Afterimage and mock afterimage perception task and behavioral results. The afterimage and mock afterimage perception task involved three trial types (C) : (1) inducers without afterimages or mock inducers without mock afterimages ( inducers + mock inducers only trial ; not depicted), (2) inducers with afterimages ( afterimage trial ), and (3) mock inducers with mock afterimages ( mock afterimage trial ). The mock afterimage is an animated, image that is designed to perceptually match with each participant’s afterimage perception. The perceptual match between afterimages and mock afterimages is represented by the yellow highlight in C. Most participants believed that the mock afterimage was illusory (i.e., not a physical stimulus) because the mock afterimage resembled an afterimage ( Table 1 ). (A) In afterimage trials (Supplementary Movie 1), the inducer stimulus appeared (4 seconds [s]) followed by a blank screen (jittered 10-12 s). Participants regularly reported perceiving an afterimage following the inducer, represented by a dotted outline to indicate that while the afterimage is perceived nothing appears on screen. (B) In mock afterimage trials, the mock inducer appeared (4 s; shown as a half gray and white image to represent that the mock inducer flickered between these two shades). Following the disappearance of the mock inducer (post-mock inducer interval jittered 10-12 s), either a mock afterimage appeared (70% of trials; Supplementary Movie 2) or nothing appeared (blank screen; 30% of trials; Supplementary Movie 3). Participants were instructed to report the onset and offset of all afterimages and mock afterimages they perceived. (D) The mean perception rate with standard error of the mean (SEM) for afterimages following the inducer (red) and mock afterimages following the mock inducer when the mock afterimage was present (dark blue) and absent (light blue). Participants regularly perceived afterimages (> 0.75) and mock afterimages (> 0.90), but not when the mock inducer was presented alone (i.e., without a mock afterimage; < 0.10). (E) The mean afterimage and mock afterimage duration and onset latency with SEM. The afterimage and mock afterimage durations and onset latencies were not statistically different. (F) The correlation between the afterimage and mock afterimage durations and onset latencies with a linear regression line and 95% confidence intervals. Statistically significant positive correlations were found for both duration and onset latency (* p < 0.05; *** p < 0.001). The open circles in subplots D, E, and F represent individual participants (N = 32). Behavioral results are evaluated from the whole brain fMRI session. See the Methods section for full details on the mock afterimage, perception task, and behavioral analyses. Afterimage and image perceptual reporting task To access perceptual details on the perceived visual features of afterimages, previous studies have asked participants to report on the subjective appearance of their afterimages [ 41 , 42 ]. Similarly, in a previous study, we developed a perceptual reporting method that asked participants to indicate three perceptual characteristics: (1) sharpness, (2) contrast, and (3) duration ( Supplementary Figure 1A ) [ 39 ]. The perceptual reporting task involved participants using a “controllable image” – a white version of the inducer stimulus – that they manually adjusted in real time with key presses to indicate either the sharpness or contrast and duration (i.e., contrast and duration were simultaneously reported) of their afterimages following the presentation of the inducer (see Afterimage induction section). The controllable image was selected to approximately match the white or light gray appearance of the afterimages. Serving to both train participants and validate the afterimage perceptual reports, participants first matched the controllable image to on-screen images. These images were modified versions of the controllable image, which were systematically varied in sharpness, contrast, and duration to approximate the perceptual range of afterimages along these dimensions, based on pilot testing (see [ 39 ] for full details). When comparing the subjective reports with the image features (e.g., the reported sharpness of the image versus the true image sharpness), it was found that participants were accurate indicating the sharpness, contrast, and duration of the images [ 39 ]. This result validates the perceptual reporting method and supports the reliability of the afterimage reports. Mock afterimage The participants in the current experiment (see Participants section) are a subset of the participants reported in our previous study [ 39 ]. For each participant, we used their reports from [ 39 ] on afterimage sharpness, contrast, and duration to create a personalized “mock afterimage”. The mock afterimage is an on-screen , animated image designed to resemble an illusory afterimage (Supplementary Movie 2). In short, the mock afterimage is a perceptually matched image to each participant’s reported afterimage perception. Individualized mock afterimages were created to capture the variability in afterimage experiences across participants (e.g., some participants described bright, vivid, and prolonged afterimages, while others reported dim, blurry, and brief afterimages [ 39 ]; Supplementary Figure 1C and D ). Importantly, participants were not initially informed that the mock afterimage was an on-screen image. Instead, they were led to believe that these perceptions were also illusory afterimages. A post-task questionnaire was administered to assess whether the afterimage and mock afterimage appeared similar or different, and to evaluate whether they believed the mock afterimage was real or illusory (see Post-task questionnaire section). The mock afterimage was a manipulated version of the controllable image, thereby matching the shape and shade of the afterimage following the inducer (see Afterimage and image perceptual reporting task section). Specifically, the sharpness of each mock afterimage was set to the participant’s mean reported afterimage sharpness ( Supplementary Figure 1C ). The sharpness of the mock afterimage was constant throughout its entire presentation. Since afterimages are often perceived with dynamic brightness or vividness, to match the change in afterimage contrast overtime, the mock afterimage was animated according to how participants reported their afterimage contrast changed during its perception. The contrast overtime and duration of the mock afterimage was calculated by finding the mean duration of the afterimage (see [ 39 ] for details), scaling each reported afterimage by this duration, then resampling the contrast values at 100-millisecond increments, and, finally, calculating the mean opacity at each time point ( Supplementary Figure 1D ). To eliminate rapid, unnatural jumps in contrast, the mock afterimage contrast-by-time array was smoothed (Savitzky-Golay filter: window size = 11 seconds; polynomial order = 1). The mock afterimage served two main functions. First, the mock afterimage helped validate the accuracy of the afterimage perceptual reports (see Afterimage and mock afterimage perceptual matching validation section). Specifically, if participants were unable to distinguish between their afterimages and mock afterimages or did not realize that the mock afterimage was a physical, on-screen stimulus (i.e., believed it to be illusory), this would support that the perceptual reports used to construct the mock afterimage accurately reflected the afterimage perception. Second, the mock afterimage served to compare physiological signals associated with perceiving physical images versus illusory afterimages. As a perceptually matched counterpart to the afterimage, the mock afterimage enabled this contrast by controlling for low-level visual feature differences (e.g., a long-lasting, bright real image versus a short, dull afterimage). By leveraging the mock afterimage, the current study examined images and afterimages that elicited similar conscious experiences yet distinguished by their origins: image perception associated with ongoing visual input and afterimage perception emerging without simultaneous visual stimulation, although retinal activity may still be present. A key difference between the afterimage and mock afterimage is that the afterimage is proceeded by an inducer stimulus. Meanwhile, the mock afterimage can be perceived by its presentation alone. The inducer potentially biases results because it will introduce physiological changes that are systematically present for the afterimage but absent in the mock afterimage condition. This potential confound is especially challenging in fMRI due to hemodynamic delays that result in the mixing of signals associated with closely timed events. To address this challenge, we designed a “mock inducer” stimulus that was paired with the mock afterimage to match the inducer-afterimage pair ( Figure 1B ; Supplementary Movie 2). The mock inducer was identical in size, shape, and presentation duration as the inducer (see Afterimage induction section). However, instead of a static image, the mock inducer flickered at 1 Hz between a light and dark gray shade. These visual characteristics of the mock inducer were tailored to not evoke afterimages, confirmed by pilot testing (data not shown) and the current behavioral results (see Afterimage and mock afterimage perception task Results section; Figure 1D ; Supplementary Figure 2A ). By presenting the mock inducer immediately before the mock afterimage, we approximated the physiological signal interactions between the inducer and afterimage by mimicking this pairing with the mock inducer and mock afterimage. In addition, the mock inducer helped to conceal that the mock afterimage was an on-screen image (i.e., if the mock afterimage appeared alone, it would become apparent that it was a physical stimulus; see Afterimage and mock afterimage perceptual matching validation section). Whole brain analyses compared the fMRI responses associated with inducers and mock inducers to verify that they were not systematically biasing findings attributed to afterimages and mock afterimages (see the Whole brain BOLD signals Results section; Supplementary Figure 6 ). Afterimage and mock afterimage perceptual matching validation To validate that the afterimage and mock afterimage perceptually matched, participants completed a perceptual matching validation task ( Supplementary Figure 1B ). In this task, participants were introduced to the mock inducer (see Mock afterimage section). However, participants were misleadingly instructed that afterimages could appear following the mock inducer. Instead, unbeknownst to the participants, when the mock inducer disappeared, each participant’s unique mock afterimage was presented in a subset of trials. Therefore, it could appear as if the mock inducer was followed by an afterimage. The perceptual matching validation task involved 48 trials. In 16 trials, neither the inducer nor mock inducer appeared (blank trials). For the remaining 32 trials, both the inducer and mock inducer appeared on opposites sides of the screen, while participants centrally fixated. Each trial consisted of four main task phases ( Supplementary Figure 1B ): (1) pre-inducer and mock inducer (6-8 seconds; not shown in Supplementary Figure 1B ), (2) inducer and mock inducer (4 seconds), (3) afterimage and mock afterimage (10-12 seconds), and (4) question phases (self-paced). During the pre-inducer and mock inducer phase , only a central fixation image (a plus sign inside an open circle) appeared and participants were instructed to maintain their gaze on this point. During the inducer and mock inducer phase both the inducer and mock inducer appeared on opposite sides of the screen, the inducer and mock inducer location counterbalanced across trials. During the afterimage and mock afterimage phase , the screen was blank (a solid gray background) on the side of the screen where the inducer appeared. On the side of the screen where the mock inducer appeared, the mock afterimage was presented in 17 out of 32 trials; in the remaining trials, this side of the screen was blank. Finally, during the question phase , participants were asked “Where did you see an afterimage?”. Participants indicated with a keypress whether they perceived an afterimage on (1) the left or (2) right side of the screen, (3) both sides of the screen, or (4) they did not perceive any afterimages on either side of the screen. Notably, at this stage of the experiment, participants were unaware that the mock afterimage was an on-screen stimulus (see Mock afterimage Results section). Thereby, the instruction to report on the location of afterimages was inclusive of both afterimages and mock afterimages, as the participants believed that the mock afterimages were illusory afterimages at this stage of the study. Afterimage and mock afterimage perception task The afterimage and mock afterimage perception task was administered with simultaneous fMRI, eye tracking, and pupillometry (see Whole brain fMRI sequence , V1 fMRI sequence , and Eye tracking and pupillometry sections). This task comprised of ∼10-minute blocks consisting of 28 trials each. Participants completed a total of 5 blocks per fMRI study session (one participant completed only 4 blocks due to reporting discomfort; two participants completed only 121 and 128 trials of the total 140 trials across 5 blocks due to the task presentation software crashing during the experiment). Each task trial consisted of four phases ( Figure 1A and B ): (1) pre-inducer and mock inducer (10-12 seconds), (2) inducer and mock inducer (4 seconds), (3) afterimage and mock afterimage (variable duration of ∼4 seconds), and (4) post-afterimage and mock afterimage phases (10-12 seconds; the post-afterimage and mock afterimage period was inclusive of the afterimage and mock afterimage phase; i.e., the mock afterimage presentation duration was subtracted from the post-mock afterimage duration, so the cumulative duration of the mock afterimage and post-mock afterimage phases was less than or equal to 12 seconds). The pre-inducer and mock inducer phases were identical and consisted of a blank gray screen with a central fixation image (a plus sign inside an open circle) that remained visible throughout all trial phases. During the inducer and mock inducer phases , either the inducer or mock inducer image appeared on either the right or left side of the fixation point. The inducer and mock inducer location was randomly selected on a trial-by-trial basis, while there was an equal number of presentations between the left and right sides of the screen. In the afterimage phase , nothing appeared (a blank screen) following the offset of the inducer ( afterimage trial ; Figure 1A ). In the mock afterimage phase , in ∼70% of trials (10 out of 14 mock inducer trials per block) a mock afterimage appeared in the same on-screen location that the mock inducer was presented, while for ∼30% of trials (4 out of 14 mock inducer trials per block) nothing appeared ( mock afterimage trial ; Figure 1B ). Finally, the post-afterimage and mock afterimage phases were identical and consisted of a blank gray screen with a central fixation image. Whenever participants perceived an afterimage or mock afterimage, they were instructed to immediately indicate its onset and offset using button presses. If nothing appeared following the inducer and mock inducer, participants were instructed to withhold a response. The buttons coding for perceived onset and offset was counterbalanced across participants (condition A: button 1 = onset, button 2 = offset; condition B: button 2 = onset, button 1 = offset). At this stage of the experiment, most participants were unaware that the mock afterimage was an on-screen stimulus. For naïve participants, they were instructed to report the onset and offset of afterimages, which was inclusive of mock afterimages because these participants believed they were also illusory afterimages. For the participants who became aware that the mock afterimage was an on-screen image either during the perceptual matching validation task (see Afterimage and mock afterimage perceptual matching validation section) or the perception task, they were instructed to report on the onset and offset of both afterimages and mock afterimages. Post-task questionnaire After completing the perceptual matching validation and the afterimage and mock afterimage perception tasks (i.e., after exiting the MRI scanner for the whole brain and V1 fMRI study sessions), participants were administered a post-task questionnaire. The questionnaire inquired on whether participants perceived afterimages, whether the afterimages and mock afterimages appeared similar or different, and if they noticed that the mock afterimage was an on-screen image. Also, participants were encouraged to share any notable observations regarding their afterimage and mock afterimage experiences. Eye tracking and pupillometry Eye tracking and pupillometry acquisition Eye measures are known to reflect widespread brain activity and are linked to conscious perception [ 43 , 44 ]. To complement and help interpret the fMRI findings, we acquired and analyzed pupil size, blink, and microsaccade dynamics. Head-fixed, eye tracking and pupillometry were gathered during the whole brain and V1 fMRI study sessions with the EyeLink 1000 Plus system (recorded eye: right eye, except for 5 participants during the whole brain fMRI session where the left eye offered more stable eye tracking; sampling rate = 1000 Hz; MRI compatible, long-range camera; SR Research, Inc.). The tracker camera was mounted inside the MRI bore, positioned behind the participant’s head. The tracker camera was oriented to capture the participant’s eye via a mirror affixed to the MRI head coil (see Whole brain fMRI sequence , V1 fMRI sequence , and Equipment, software, and facility sections) – the same mirror participants used to view the projector screen displaying the task. The eye tracker camera was positioned approximately 64 cm from the participant’s eye. The head coil and foam padding used to stabilize head position helped ensure reliable eye tracking throughout the study. fMRI Whole brain fMRI sequence Whole brain fMRI was acquired on a MAGNETOM 7T Plus MRI (Siemens, Inc., Healthineers, Erlangen, Germany) with a 32-channel head coil (Nova Medical, Inc., Wilmington MA, USA). BOLD imaging was recorded with a 2D-multi-band sequence (voxel size = 1.2 millimeters [mm] isotropic; repetition time [TR] = 1000 milliseconds [ms]; echo time [TE] = 22.00 ms; flip angle = 55 degrees; slices = 80; phase encoding direction = anterior to posterior; multi-band acceleration factor = 4; field of view = 176 mm) [ 45 ]. The volume position and angle were oriented to maximize subcortical, cortical, and cerebellar coverage. This was achieved by running a localizer scan (voxel size = 0.5 mm isotropic; TR = 8.6 ms; TE = 3.69 ms; flip angle = 20 degrees; slices = 1; phase encoding direction = anterior to posterior). The experimenter used the localizer image to adjust the BOLD volume location using the MRI scanner console graphic user interphase. Once the volume location was specified, 3 rd order B0-shimming was completed to optimize B0-field homogeneity within this field of view. Specifically, we reconstructed phase images from a whole-brain gradient echo image. We utilized the standard Siemens algorithm to compute B0 shim values to homogenize phase across the images and repeated this process three times. Next, we manually altered the linear shim voltages to minimize line width and computed scanning frequency. After completing the BOLD recording part of the study that was run concurrently with the perception task (see Afterimage and mock afterimage perception task section), a high-spatial-resolution anatomical T1-weighted whole brain image (magnetization prepared – rapid gradient echo [MP2RAGE] [ 46 ]; voxel size = 0.8 mm isotropic; TR = 4300 ms; TE = 1.99 ms; inversion time (TI) 1 = 840 ms; TI 2 = 2370 ms; flip angle 1 = 5.0 degrees; flip angle 2 = 6.0 degrees; slices = 224; phase encoding direction = anterior to posterior) was acquired to assist in the preprocessing of the fMRI data (see Whole brain fMRI Analysis Methods section). V1 fMRI sequence V1 fMRI was acquired on a MAGNETOM 7T Plus MRI (Siemens, Inc., Healthineers, Erlangen, Germany) with a 32-channel head coil (Nova Medical Inc., Wilmington MA, USA). Simultaneous BOLD and VASO [ 47 ] imaging was recorded with a 3D-EPI readout (voxel size = 0.8 mm isotropic; volume acquisition sampling rate = 1589 ms; pair TR = 3178 ms; TE 1 = 23.50 ms; TI 1 = 1201.3 ms; TI 2 = 2293.9 ms; variable flip angles with reference [last] = 45 degrees; slices = 18; phase encoding direction = anterior to posterior; field of view = 150 mm) [ 48 – 50 ]. 3 rd order B0-shimming was completed to optimize B0-field homogeneity in visual cortex. The slab position and angle were oriented by the experimenter to be centered within and run parallel to each participant’s calcarine sulcus along the mid-sagittal plane ( Figure 5A ). This was achieved by running a brief (∼10 seconds) 2D inversion recovery turbo flash sequence (voxel size = 1.0 x 1.0 x 8.0 mm; TR = 4300 ms; TE = 3.17 ms; TI 1 = 840 ms; TI 2 = 2540 ms; flip angle 1 = 5 degrees; flip angle 2 = 8.0 degrees; slices = 6; phase encoding direction = anterior to posterior). Based on this localizer, the experimenters manually adjusted the position and angle of the fMRI imaging slab using the MRI graphic user interface. After completing the BOLD and VASO recording part of the study that was run concurrently with the perception task (see Afterimage and mock afterimage perception task section), a high-spatial-resolution anatomical T1-weighted whole brain image was acquired (MP2RAGE; see Whole brain fMRI sequence section) to assist in the segmentation, columnification, and layerification of the BOLD and VASO volumes (see V1 fMRI Analysis Methods section). For two participants, an MP2RAGE scan was not acquired during the V1 fMRI session. Instead, their MP2RAGE images acquired during the whole brain fMRI session were used for subsequent V1 fMRI analyses. Equipment, software, and facility The behavioral tasks were run on a behavioral laptop (MacBook Pro; 13-inch; 2560 x 1600 pixels, 2019; Mac OS Catalina v10.15.7; Apple, Inc.) and with PsychoPy (version 2022.2.24; Open Science Tools Ltd [ 51 ]). In the behavioral session, participants viewed the tasks (see Afterimage and image perceptual reporting task and Afterimage and mock afterimage perceptual matching validation sections) on a VIEWPixx monitor (1920 x 1200 pixels; refresh rate = 120 Hz; VPixx Technologies, Inc.) that was mirrored to the behavioral laptop screen. During the MRI sessions, participants laid supine, and a mirror mounted on the head coil positioned above their eyes reflected task images displayed on a screen located behind their head. The viewing distance between the participants and the center of the screen was approximately 64 cm. Task images were projected onto the screen using a rear projector system (PROPixx; refresh rate = 480 Hz; VPixx Technologies, Inc.) connected to the behavioral laptop in the control room. In both the behavioral and fMRI study sessions, the room lighting was made consistent across all participants. Participants responded during the tasks with their right hand (regardless of handedness) using a keyboard (behavioral session: directly connected to the behavioral laptop) and button box (fMRI sessions: 4 Button Inline Fiber Optic Response Pad; Current Designs, Inc.). The button box was connected to the behavioral laptop via an electronic interface (932 Interface & Power Supply; Current Designs, Inc.). During the behavioral sessions, the experimenter sat behind participants to deliver instructions and monitor task performance, eye tracking, and pupillometry recordings. In the fMRI sessions, the experimenters sat in a control room to monitor task performance, fMRI, eye tracking, and pupillometry recordings, and communicated with and monitored the participants via an intercom unit (Siemens, Inc.). Analysis Methods All analyses were completed in Analysis of Functional NeuroImages (AFNI; version 25.1.07; https://afni.nimh.nih.gov ; [ 52 , 53 ]), Anatomical Normalization Tools (ANTs; https://stnava.github.io/ANTs/ ; [ 54 ]), FreeSurfer (version 7.4.1; https://surfer.nmr.mgh.harvard.edu ; [ 55 ]), ITK-SNAP (version 3.8.0; https://www.itksnap.org/pmwiki/pmwiki.php ; [ 56 ]), LayNii toolbox (version 2.9.0; https://github.com/layerfMRI/LAYNII ; [ 57 ]), MATLAB (version R2023b; https://www.mathworks.com/products/matlab.html ; MathWorks, Inc.), and Statistical Parametric Mapping (SPM; version 12; https://www.fil.ion.ucl.ac.uk/spm/ ). Visualizations were made using MATLAB, AFNI, Illustrator (version 2025; Adobe, Inc.), and Surf Ice (version 15.4.1; https://www.nitrc.org/projects/surfice/ ; [ 58 ]). Behavior Afterimage and mock afterimage perception rate was calculated as the number of afterimages and mock afterimages perceived following the inducer and mock inducer, respectively, versus all inducer and mock inducers presentations ( Figure 1D ; Supplementary Figure 2A ). A perceived afterimage and mock afterimage were determined if (1) the participant reported both an onset and offset time, (2) the onset response was earlier than the offset response time, and (3) for the mock inducer trials, a mock afterimage was presented (i.e., not a blank trial). A not perceived afterimage and mock afterimage was determined if the participant did not report an onset and offset time. The duration and onset latency of perceived afterimages and mock afterimages was calculated by taking the difference between the reported onset and offset (duration) and subtracting the time between the offset of the inducer or mock inducer and the reported onset of the afterimage or mock afterimage, respectively (latency; Figure 1E ; Supplementary Figure 2B ). Wilcoxon matched-pairs signed rank tests (two-tailed) evaluated if (1) the duration and (2) onset latency of the afterimage and mock afterimage was statistically different across participants ( Figure 1E ; Supplementary Figure 2B ). Simple linear regression and Pearson correlation tested if there was a significant relationship in the duration and onset latency of the afterimage and mock afterimage across participants ( Figure 1F ; Supplementary Figure 2C ). Finally, duration and onset latency variance were calculated for all perceived afterimages and mock afterimages within participants. Wilcoxon matched-pairs signed rank tests (two-tailed) evaluated if (1) the duration and (2) onset latency variance of the afterimage and mock afterimage was statistically different across participants (Supplementary Figure 3). For all behavioral analyses, the whole brain and V1 fMRI sessions were evaluated separately. Eye tracking and pupillometry Preprocessing Pupil size, blinking, and microsaccade dynamics were evaluated for each of the afterimage and mock afterimage perception task trial conditions. First, pupil size data were preprocessed to remove blinks and artifacts [ 59 ]. Blink events were identified based on criteria such as outlier pupil size values and rapid changes in pupil size. Microsaccade events were identified from the gaze position data based on velocity thresholds [ 60 , 61 ]. The processed data included (1) a preprocessed pupil size, (2) a binary blink (0 = blink absent; 1 = blink present), and (3) a binary microsaccade (0 = microsaccade absent; 1 = microsaccade present) arrays. Epoch extraction Pupil size, blink, and microsaccade epochs were segmented for each participant. Epochs were centered on the inducer and mock inducer onset times. Epochs were categorized according to the perception task trial conditions (see Afterimage and mock afterimage perception task Methods section): (1) inducer without an afterimage, (2) inducer with an afterimage, (3) mock inducer without a mock afterimage, and (4) mock inducer with a mock afterimage. Next, the mean across all epochs within participant, trial condition, and eye measure type was calculated. For participants who completed both the whole brain and V1 fMRI studies, epochs were combined between sessions within participant, trial condition, and eye measure type and then averaged. High frequency components were removed from the participant mean blink and microsaccade epoch timecourses by smoothing (250 ms moving average span). Finally, the participant mean epoch timecourses were baselined to the mean signal among the 1000 ms prior to the inducer and mock inducer onset. Group-level analyses The eye tracking and pupillometry data were not analyzed for two participants who completed the whole brain fMRI study session due to poor eye tracking. Of the remaining 30 participants, group-level epoch timecourses were calculated by first standardizing or z-scoring the pupil size, blink fraction, and microsaccade fraction values across participants and then evaluating the mean and standard error of the mean (SEM) across all participants and within trial condition (Supplementary Figure 4). A minimum of 5 epochs within a trial condition was required for a participant to be included in group-level analyses for that condition. This criterion resulted in the removal of 8 participants from inducers without afterimages condition who nearly always reported an afterimage following the inducer. Wilcoxon matched-pairs signed-rank tests (two-tailed) evaluated differences in the mean pupil size, blink fraction, and microsaccade fraction within three epoch intervals: (1) inducer and mock inducer (0-4 seconds following the inducer and mock inducer onset), (2) afterimage and mock afterimage (6-10 seconds following the inducer and mock inducer onset), and (3) post-afterimage and post-mock afterimage intervals (10-14 seconds following the inducer and mock inducer onset). Three contrasts were analyzed: (1) the inducers with afterimages versus inducers without afterimages, (2) mock inducers with mock afterimages versus mock inducers without mock afterimages, and (3) inducers with afterimages versus mock inducers with mock afterimages (Supplementary Figure 4). Holm-Bonferroni correction was applied across all statistical tests within each eye measure type (3 tested intervals x 3 tested condition contrasts = 9 tests per eye measure) to control for multiple comparisons. Whole brain fMRI Preprocessing The whole head anatomical image (MP2RAGE; see Whole brain fMRI sequence section) was segmented (FreeSurfer) and skull stripped. Using the skull stripped, segmented anatomical image, standard fMRI preprocessing was applied on the BOLD volumes using AFNI’s afni_proc.py [ 62 ], including slice timing correction, head motion estimation, linear affine EPI-anatomical alignment using the lpc+ZZ cost function [ 63 ], nonlinear alignment of the anatomical to template space (volumes were registered to the MNI152_2009_template; [ 64 ]), smoothing (kernel size = 2 mm), whole brain masking, and motion regression (3 rotation and 3 translation). For improved computational efficiency, the BOLD voxel resolution was rescaled from 1.2 mm to 1.5 mm isotropic. Finally, percent change BOLD was calculated for each brain voxel within fMRI runs, which corresponded with the perception task blocks (see Afterimage and mock afterimage perception task section) relative to the mean voxel-wise BOLD responses across all run volumes. The preprocessed data were quality checked to verify that participant motion was relatively low and did not appear correlated with the task and to confirm that the BOLD, anatomical, and template volumes were in alignment [ 65 ]. Epoch extraction BOLD voxel-by-time epochs were segmented. Epochs were centered on the inducer and mock inducer stimulus onset times (see Afterimage and mock afterimage perception task section). Specifically, 25 volumes (25 seconds) before and after the inducer and mock inducer onset TR were extracted. This epoch interval, while exceeding the perception task trial interval (see Afterimage and mock afterimage perception task Methods section), was selected to account for expected hemodynamic delays of BOLD associated with task events. In rare cases, when the epoch duration exceeded the onset or offset of a run, the missing volume values were replaced with “not-a-number”. Since contrasts between task conditions were made on a timepoint-by-timepoint basis, for trials with an afterimage and mock afterimage, a temporal normalization procedure was applied to account for the variable duration and onset latency among afterimages and mock afterimages. Based on the group-level onset latency and duration reports ( Figure 1E ; Supplementary Figure 2B ), all epochs were fit to an onset latency of 2 seconds (2 TRs) and an afterimage and mock afterimage duration of 4 seconds (4 TRs). Epochs were resampled with linear interpolation to match these standard onset latency and duration intervals. For example, an epoch where an afterimage was reported as lasting for 2 seconds was upsampled to 4 seconds (i.e., the addition of two time points was made between the afterimage onset and offset volumes). Meanwhile, if the afterimage duration exceeded the standard duration, downsampling was achieved by averaging volumes adjacent in time. Temporal normalization was not applied on inducer and mock inducer intervals because they had a constant duration (4 seconds; 4 TRs). Finally, all epochs within each trial condition were averaged within participant resulting in a voxel-by-time (TR) per condition BOLD volume. To increase sample size, the inducers without afterimages and mock inducers without mock afterimages epochs were combined and averaged on the epoch-level basis to define the “inducers + mock inducers only” epoch condition. Combining the inducers and mock inducers only epochs was justified following analyses that confirmed inducers and mock inducers evoked similar whole brain BOLD responses (see the Whole brain BOLD signals Results section; Supplementary Figure 6). Whole brain spatiotemporal cluster-based permutation testing Spatiotemporal cluster-based permutation testing (two-tailed; 1000 permutations; baseline interval = 5 seconds pre-inducer and mock inducer onset) was applied on the whole brain BOLD data focusing on the 0-25 seconds post-inducer and mock inducer onset. Full details on the permutation method are available at [ 66 ]. Briefly, the cluster-based permutation analysis builds a null distribution by random permutation of the trial conditions and a cluster-forming statistic based on spatial and temporal adjacency defined as when statistically significant voxels of the same sign are adjacently located in space or time. Spatiotemporal clusters are then identified in the non-permutated data and evaluated against the null distribution to find statistically significant spatiotemporal clusters. The final output of this analysis was the signed, statistically significant voxels at each queried timepoint. To improve computational efficiency, only gray matter voxels were tested and the BOLD volume spatial resolution was downsampled to 3.0 mm isotropic. Three main tests were explored: (1) inducers with afterimages versus inducers + mock inducers only (unilateral and bilateral visual field analyses), (2) mock inducers with mock afterimages versus inducers + mock inducers only (unilateral and bilateral visual field analyses), and (3) inducers with afterimages versus mock inducers with mock afterimages (unilateral visual field analyses only; Figure 2 ; Supplementary Figure 7). In unilateral analyses, epochs corresponding to left versus right visual field inducer or mock inducer presentations were evaluated separately. Independently testing the left and right-sided stimuli presentations was done to assess contralateral and ipsilateral signaling dynamics. In bilateral analyses, epochs corresponding to left and right visual field inducer and mock inducer presentations were evaluated together. Download figure Open in new tab Figure 2. Whole brain volume and surface BOLD activation maps. Statistically significant t -values are highlighted with a black outline, while sub-threshold regions are shown with transparency at time point 14 seconds (s) after the inducer and mock inducer onset (the approximate peak response time for afterimages and mock afterimages) for the following statistical contrasts: (A) inducers with afterimages versus inducers + mock inducers only conditions ( afterimage ), (B) mock inducers with mock afterimages versus inducers + mock inducers only conditions ( mock afterimage ), and (C) inducers with afterimages versus mock inducers with mock afterimages conditions ( afterimage vs mock afterimage ). Brain surface visualization of t -values from statistically significant voxels are shown in (B) , (D) , and (F) for the same contrasts highlighted in the volume activation maps in A, C, and E. See Supplementary Slides 1, 2, and 3 for volume activation maps for additional time points. Anterior cingulate cortex (AC); basal ganglia (BG); extrastriate cortex (EC); fusiform gyrus (FG); inferior frontal gyrus (IFG); inferior parietal lobule (IPL); insula (In); lateral occipital cortex (LOC); left primary motor cortex (L-M1); left primary somatosensory cortex (L-S1); medial frontal gyrus (MFG); midbrain (MB); rostral middle frontal gyrus (RMFG); right primary motor cortex (R-M1); right primary somatosensory cortex (R-S1); precuneus (Pr); primary visual cortex (V1); posterior cingulate cortex (PCC); superior cerebellum (SC); superior frontal gyrus (SFG); supplementary motor area (SMA); superior parietal lobule (SPL). Supplementary analyses were also explored: (1) inducers with afterimages versus inducers without afterimages, (2) mock inducers with mock afterimages versus mock inducers without mock afterimages, (3) inducers without afterimages versus baseline, (4) mock inducers without mock afterimages versus baseline, and (5) inducers without afterimages versus mock inducers without mock afterimages (Supplementary Figure 5 and 6). 14 participants were excluded from the supplementary analysis because of an insufficient number of inducers without afterimages epochs (minimum threshold > 5 epochs) and, for consistency, the same participants were excluded from the mock inducers with and without mock afterimages analyses. Note that only 8 participants were removed by this exclusion criterion in the eye tracking and pupillometry data analysis because in the eye measures analyses epochs were combined within participant between the whole brain and V1 fMRI sessions. Cluster-based permutation analysis results were visualized by plotting the whole brain t -value map with sub-threshold t -value voxels shown with transparency and above threshold voxels highlighted with a black outline ( Figure 2A , C, and E; Supplementary Figure 5-7) [ 67 , 68 ]. Brain surface visualization was made with Surf Ice by projecting voxel values to a cortical surface mesh (BrainMesh_ICBM152; Figure 2B , D, and F; Supplementary Figure 7). Only voxels that were found statistically significant by cluster-based permutation testing were projected to the surface. K-means clustering K-means clustering (evaluated on the 25 seconds following the inducer and mock inducer onset using correlation as the distance measure) was evaluated on a subset of whole brain voxels. Voxels were included in k-means clustering if they showed statistically significant BOLD activity from either the afterimage and mock afterimage condition analyses ( Figure 2A and C ; see Whole brain BOLD cluster-based permutation testing section) at any time within the 19-second period from the afterimage and mock afterimage onset, regardless to whether the BOLD signal change was positive or negative. To correspond with the spatial resolution of the whole brain statistical analyses (see Whole brain spatiotemporal cluster-based permutation testing section), k-means clustering was also applied on the 3.0 mm isotropic downsampled BOLD volumes. All colored areas in Figure 3A and Supplementary Figure 8A and C represent the voxels included in the k-means analysis (i.e., all non-colored areas were excluded from analyses). K-values between 2 and 6 were tested. The results for a k-value of 3 are reported based on visual inspection and cluster silhouette scores (data not shown) that measure cluster quality by comparing the fit of each voxel within its assigned versus unassigned clusters. Download figure Open in new tab Figure 3. Whole brain BOLD spatiotemporal clustering and network timecourses. (A) K-means clusters (k = 3) of the average responses between the inducers with afterimages and mock inducers with mock afterimages conditions ( afterimage + mock afterimage ) for gray matter brain regions that showed statistically significant change in either the inducers with afterimages or mock inducers with mock afterimages conditions. The clusters corresponded with established functional brain networks: (1) salience and sensory (SSN), (2) task positive (TPN), and (3) task negative (TNN) networks. The network labels approximate the functional role of the brain regions grouped within each cluster. Major anatomical regions are labelled and color-coded by network. (B) The mean percent change blood-oxygen-level-dependent (BOLD; %) timecourses with standard error of the mean (SEM) across all voxels within the SSN, TPN, and TNN. (C) The average BOLD response within the SSN, TPN, and TNN networks for the main trial conditions of the perception task ( Figure 1C ): (1) inducers with afterimages ( Af ), (2) mock inducers with mock afterimages ( Mock Af ), and (3) inducers without afterimages and mock inducers without mock afterimages conditions (inducers + mock inducers only; I + Mock I ). Statistically significant intervals are highlighted with a horizontal bar above each timecourse, color-coded by condition. In B and C, the solid gray bars highlight the inducer and mock inducer period, while the solid gray bar with a dotted outline highlights the approximate afterimage and mock afterimage period. Angular gyrus (AG); anterior cingulate cortex (AC); basal ganglia (BG); extrastriate cortex (EC); fusiform gyrus (FG); inferior frontal gyrus (IFG); insula (In); lateral occipital cortex (LOC); left primary motor cortex (L-M1); left primary somatosensory cortex (L-S1); medial frontal gyrus (MFG); right primary motor cortex (R-M1); right primary somatosensory cortex (R-S1); precuneus (Pr); primary visual cortex (V1); posterior cingulate cortex (PCC); inferior parietal lobule (IPL); rostral middle frontal gyrus (RMFG); superior cerebellum (SC); superior frontal gyrus (SFG); supplementary motor area (SMA); superior parietal lobule (SPL); ventral medial prefrontal cortex (VMFC). Clustering was performed on the group-averaged signal from both the inducers with afterimages and mock inducers with mock afterimages conditions (afterimage + mock afterimage; Figure 3 ). For this analysis, signals between conditions were first averaged within participant and then averaged across all participants. This approach allowed for the identification of a common set of brain networks that could be compared across task conditions. The afterimage + mock afterimage analysis was justified after observing similar whole brain results for the inducers with afterimages and mock inducers with mock afterimages conditions (see Whole brain BOLD signals Results section; Figure 2 ), and that separately clustering on the inducers with afterimages and mock inducers with mock afterimages conditions resulted in similar cluster profiles ( Supplementary Figure 8A and B versus C and D ). All voxels grouped into a common cluster were assigned a constant value to visualize the cluster spatial extent ( Figure 3A ; Supplementary Figure 8A and C ). K-means cluster BOLD activity timecourses were evaluated by averaging the percent change BOLD signal across all voxels within each cluster at each time point ( Figure 3B ; Supplementary Figure 8B and D ). In addition, BOLD timecourses were calculated for each task condition – afterimage, mock afterimage, and inducers + mock inducers only ( Figure 1C ) – using each k-means cluster as a network region of interest. This was achieved by averaging the percent change BOLD signal across all voxels within each cluster separately for each task condition ( Figure 3C ). These cluster-based, task condition timecourses were statistically evaluated against a null response across all time points using temporal cluster-based permutation testing (two-tailed; 1000 permutations; [ 69 ]). Regions of interest Regions of interest (ROIs) analyses were performed to evaluate BOLD signal responses overtime across task conditions in task-engaged brain areas. ROIs were selected based on whole brain BOLD analyses and k-means clustering that highlighted sensory, salience, and motor network regions as responsive to afterimages and mock afterimages ( Figure 2 and 3 ; see Whole brain BOLD signals and Whole brain functional networks Results sections). From these areas, 6 representative ROIs were selected: (1) LGN, (2) V1, (3) FG, (4) anterior cingulate cortex (AC), (5) insula (In), and (6) left primary motor cortex (M1) ( Figure 4A ). ROI analyses were conducted on the original, non-downsampled BOLD volumes with a spatial resolution of 1.5 mm isotropic. Download figure Open in new tab Figure 4. Sensory and salience network regions of interest BOLD timecourses. Regions of interest (ROIs) were selected based on their inclusion in the sensory and salience network ( Figure 3A ). (A) Visualizations of the ROIs with MNI coordinates in millimeters (mm), indicating their position in the axial, coronal, and sagittal planes. (B) Lateral geniculate nucleus (LGN), (C) primary visual cortex (V1), (D) fusiform gyrus (FG), (E) anterior cingulate (AC), (F) insula (In), and (G) left primary motor cortex (L-M1) mean blood-oxygen-level-dependent (BOLD) timecourses with standard error of the mean (SEM; thin, dotted line) were calculated across participants (N = 32) for the main trial conditions of the perception task ( Figure 1C ): (1) inducers with afterimages ( Af ), (2) mock inducers with mock afterimages ( Mock Af ), and (3) inducers without afterimages and mock inducers without mock afterimages conditions (inducers + mock inducers only; I + Mock I ). In all BOLD timecourse subplots, the gray bar between 0 and 4 seconds (s) highlights the inducer and mock inducer period. The solid gray bar with a dotted outline between 6 and 10 s highlights the approximate afterimage and mock afterimage period. The LGN voxels were defined based on each participant’s estimated LGN area according to anatomical whole brain segmentation completed during whole brain fMRI preprocessing (see Whole brain fMRI Preprocessing Methods section). To allow for group-level analyses, the participant-level LGN ROIs were normalized to a common template space and LGN voxels were combined across participants to define a group LGN region. For the remaining ROIs, voxels were selected according to the MNI Glasser atlas [ 70 ]. To identify the most task-engaged voxels within the sensory and left M1 ROIs, within-ROI functional localization was performed. This was achieved by running spatiotemporal cluster-based permutation testing (two-tailed; 1000 permutations; test interval = 0-12 seconds) that evaluated left versus right visual field inducers + mock inducers only epochs for the LGN, V1, and FG ROIs. This analysis evaluated contralateral versus ipsilateral activity independent of motor response (i.e., participants did not make a button press for the inducers + mock inducers only condition). The contralateral relationship between visual field and visual sensory regions meant that the left versus right visual field contrast would highlight right hemispheric regions, and vice versa. For the left M1 ROI, a statistical contrast between the afterimage + mock afterimage (averaged between conditions within participants) versus the inducers + mock inducers only condition was evaluated because the latter did not involve button presses, while the former included right-handed responses to indicate the onset and offset of afterimages and mock afterimages. Thereby, this contrast was sensitive to task motor responses. For all ROI functional localization analyses, a voxel was included in the ROI if it met two criteria: (1) it was statistically significant at any time point between 0-12 seconds after the inducer or mock inducer onset, and (2) its average voxel t -value across those significant time points was greater than zero , indicating a tendency toward increased BOLD activity. Voxels that did not meet these criteria were discarded from the functionally localized ROIs. Finally, timecourses were visualized within each ROI by taking the mean percent change BOLD response across all selected ROI voxels and subtracted from the mean signal in the 5 seconds preceding the inducer and mock inducer onset. Each trial condition was evaluated separately and the mean timecourses are shown with standard error of mean calculated across participants ( Figure 4 ). V1 fMRI Analysis of the layer-resolution V1 fMRI data involved several processing stages detailed below. A schematic summary of the analysis pipeline is depicted in Supplementary Figure 9. Preprocessing V1 fMRI data acquisition involved simultaneous collection of BOLD and VASO images using interleaved TRs (see V1 fMRI sequence section). The VASO volumes were initially acquired as unprocessed cerebral blood volume-weighted or “nulled” signals. The final VASO signal was derived from these nulled images during the processing procedure. Each run consisted of 500 volumes, which were sorted into two image sets: 250 BOLD volumes and 250 nulled volumes. The first three volumes of each set were removed to allow magnetization to reach steady state. Based on the remaining 247 volumes within each image set, 3 reference volumes were created: (1) BOLD, (2) nulled, and (3) T1-reference volumes. The BOLD and nulled reference volumes were calculated by averaging the volumes from the first fMRI run. The T1-reference volume was calculated by dividing the nulled reference image by the BOLD reference image, resulting in a T1-weighted contrast image used for registering the functional volumes to anatomical space. The first run was used to generate these reference images because it was least likely to be affected by motion artifacts. Subsequently, the BOLD and nulled volumes were motion corrected with non-linear alignment to their respective reference images (ANTs). To reduce thermal noise, NOise Reduction with DIistribution Corrected (NORDIC) principal component analysis was implemented separately on the motion-corrected nulled and BOLD volumes [ 71 – 73 ]. BOLD and nulled volumes were temporally upsampled from 247 to 494 volumes using linear interpolation. The VASO signal was then calculated by performing a volume-by-volume division of the nulled signals from the BOLD signals [ 49 ]. Finally, BOLD and VASO percent signal change was calculated for each run relative to the mean signal of each voxel across all volumes within a run. Layerification & columnification A critical stage in layer-resolution fMRI analysis involves segmenting gray matter voxels within the ROI into layers and columns – a process known as “layerification” and “columnification”. Importantly, in this context, “layers” and “columns” do not correspond to precise anatomical or functional boundaries in neural tissues such as the 6 histological layers of human cortical gray matter or V1 ocular dominance columns. Rather, layers and columns refer to spatial segmentations of the gray matter that are aligned with these anatomical orientations. When spatial resolution is sufficiently high, these segmentations support inferences of the functional properties that are characteristic of the underlying neural tissue architecture. Layer and column segmentation was performed for each participant, beginning with bias field correction on the whole brain anatomical image (MP2RAGE; SPM). Brain tissue segmentation was then performed (FreeSurfer) and mapped to the cortical surface (AFNI’s Surface Mapping tool; https://afni.nimh.nih.gov/Suma ). The pial, gray, and white matter surfaces were extracted for each hemisphere and combined into a gray matter rim volume ( Supplementary Figure 9B ). Manual corrections were made to address segmentation errors (e.g., inclusion of the sagittal sinus in the gray matter rim or “kissing gyri” where adjacent gyri lack visible cerebral spinal fluid [CSF] separation). These edits were made using a digital pad (Wacom Intuos CTL4100; ITK-SNAP). The corrected gray matter rim was then upsampled using linear interpolation to a high-spatial-resolution grid (0.27 mm isotropic resolution) to refine tissue boundaries and match the resolution of the T1 reference volume. The gray matter rim was next registered to the functional space (BOLD and VASO volumes) using the bias field corrected anatomical image and the T1 reference volume (ANTs). To enhance registration accuracy, a manually drawn occipital cortex mask based on the T1 reference volume was used to constrain the registration. The mask included visual cortex gray and white matter but avoided the upper and lower 2 slices of the acquired volume because of the risk for slab misalignment. Finally, cortical layers and columns were segmented (LayNii toolbox). Cortical layers were defined by parcellating the gray matter rim into 5 equal-volume parcels, with 2 additional layers of equal thickness added just above and below the gray matter boundary (LN2_LAYERS; Supplementary Figure 9C ). This resulted in a 9-layer padded gray matter rim (i.e., the upper and lower layers extended into white matter and CSF) that was used in subsequent layer-level epoch extraction (see below). Cortical columns were defined by parcellating the padded gray matter rim across the entire slab into 5000 approximately equal-volume compartments (LN2_COLUMNS; Supplementary Figure 9D ). Volume-level epoch extraction Perception task event epochs (see Afterimage and mock afterimage perception task Methods section) were segmented across the entire V1 fMRI acquisition volume. First, task event times (e.g., inducer stimulus onset and button presses) were identified for each trial and categorized according to the three main task conditions of interest ( Figure 1C ): afterimage, mock afterimage, and inducers + mock inducers only. Next, events times were affiliated with their nearest TR to account for the interleaved acquisition of BOLD and VASO volumes. Therefore, each event time was separately matched to its nearest BOLD and VASO TR, which could correspond to different volumes in each image series. Epochs were then extracted from the percent change volumes for both BOLD and VASO. Epochs were centered on the nearest TR to the inducer and mock inducer onset and included 20 TRs (∼32 seconds) before and after the center TR to account for hemodynamic delays. Some VASO epochs were observed to include large, artifactual spikes. These epochs were identified by computing the first derivative of the average VASO signal across all voxels within the V1 ROI (see V1 Region of Interest section). Any time point at or after the onset of the inducer or mock inducer where the first derivative value exceeded 5 percent (this threshold selected based on visual inspection), independent to signal direction, was marked as artifactual, and the corresponding epoch was excluded from further analysis. Across participants, no more than 20 percent of VASO epochs were excluded per task condition based on this criterion. No BOLD epochs were removed. Finally, a separate set of BOLD inducers + mock inducers only condition epochs were spatially smoothed (gaussian blur = 2.0 mm full width at half maximum) to assist in V1 ROI functional localization (see V1 Region of Interest section). V1 region of interest The V1 ROI was functionally localized for each participant based on the BOLD responses to the inducers + mock inducers only condition. First, spatially smoothed BOLD epochs without afterimages or mock afterimages were grouped by left versus right visual field presentation location. Smoothed BOLD signals were used to facilitate visual inspection of the V1 activation area ( Supplementary Figure 9E ). Next, all inducers + mock inducers only epochs were averaged separately within the left and right visual field conditions. The peak activation time in contralateral V1 linked to the inducer and mock inducer presentation was determined by visual inspection. At this peak time point, the boundaries of the V1 activation area in the contralateral visual cortex were manually delineated (AFNI). The resulting left and right V1 ROIs were then registered to the gray matter rim (see Layerification & columnification section) by resampling them into the layer and column voxel grid space (0.27 mm isotropic resolution). To ensure an approximately equal representation of cortical layers within the V1 ROIs, voxels were related to the gray matter rim columns. If any manually drawn voxel overlapped with a column, the entire column was included in the ROI. Finally, manual corrections were made to exclude any erroneously included columns from the contralateral hemisphere. The resulting left and right V1 ROIs were used for subsequent layer-dependent analyses (see Supplementary Figure 9F for the combined left and right V1 ROI from a representative participant). Layer-level epoch extraction Epochs were initially segmented from the entire V1 fMRI acquisition volume (see Volume-level epoch extraction section). To enable layer-dependent analysis, these volume-level epochs were resampled into the layer and column grid space (0.27 mm isotropic resolution). Within the V1 ROIs (see V1 regions of interest section), the mean BOLD and VASO signals were calculated separately for each cortical layer at each time point. This was achieved by finding the layer-specific voxels within the contralateral V1 ROI for each visual field condition (i.e., the right hemisphere ROI voxels were analyzed for epochs corresponding to the left visual field stimulus presentation, and the left hemisphere ROI voxels for the right visual field presentation; Supplementary Figure 9G ). The signals from the contralateral voxels were then averaged across all contralateral conditions to provide a bilateral activation profile based on contralateral response dynamics. V1 region of interest BOLD timecourses The mean V1 ROI BOLD timecourses for the inducers with afterimages, mock inducers with mock afterimages, and inducers + mock inducers only conditions were visualized for one representative participant by taking the mean BOLD response across all V1 ROI voxels ( Figure 5B ). The standard error of the mean was calculated across epochs within each condition. Download figure Open in new tab Figure 5. Primary visual cortex layer-dependent VASO activation timecourses and maps. (A) Representative participant sagittal and axial anatomical brain images and fMRI slab highlighting the layer segmentation in primary visual cortex (V1; dark red = superficial cortical layers near cerebrospinal fluid [CSF]; dark blue = deep cortical layers near the cortical white matter [WM]). The dotted line in the sagittal view approximates the position of the coronal image. (B) The mean percent change blood-oxygen-level-dependent (BOLD; %) timecourses with standard error of the mean (SEM) for all voxels in the V1 region of interest for the participant highlighted in A across the main trial conditions of the perception task ( Figure 1C ): (1) inducers with afterimages ( Af ), (2) mock inducers with mock afterimages ( Mock Af ), and (3) inducers without afterimages and mock inducers without mock afterimages conditions (inducers + mock inducers only; I + Mock I ). These timecourses resemble those in V1 from group-level whole brain BOLD analyses ( Figure 4C ). The percent change vascular space occupancy (VASO; %) is shown across V1 cortical layers for (C) inducers with afterimages ( afterimage ), (D) mock inducers with mock afterimages ( mock afterimage ), and (E) inducers with afterimages versus mock inducers with mock afterimages conditions ( afterimage versus mock afterimage ). In B, C, D, and E, the gray bar between 0 and 4 seconds (s) highlights the inducer and mock inducer period. The dotted open bar in C, solid gray bar in D, and solid gray bar with a dotted outline in B and E between 6 and 10 s highlights the approximate afterimage and mock afterimage period. Subplots (F) , (G) , and (H) show the t -values for cortical layer-by-time cluster-based permutation testing on non-normalized data. Subplots (I) , (J) , and (K) show t -values for cortical layer-by-time cluster-based permutation testing on normalized data (z-scored VASO). Statistically significant layer-time clusters are outlined with a solid black line. The percent change VASO signal was analyzed and shown inverted (negative is up) to enhance clarity and coherence with the BOLD signal. V1 spatiotemporal cluster-based permutation testing To statistically assess V1 layer-dependent activity overtime, spatiotemporal cluster-based permutation testing was conducted (two-tailed; 1000 permutations; baseline interval = 16 TRs [∼25 seconds] post-inducer and mock inducer onset) focusing on the 0-20 TRs (∼32 seconds) post-inducer and mock inducer onset. The analysis followed a similar approach to the whole brain cluster-based permutation analyses (see Whole brain spatiotemporal cluster-based permutation testing section), with one key difference: in the layer-dependent analysis, spatial adjacency was defined based on neighboring cortical layers. Analyses were performed across participants using their mean BOLD and VASO signals within each cortical layer of the V1 ROI. For two participants, VASO layer signal timecourses were smoothed to correct for a constant noise pattern observed across voxels and time. To enhance spatial sensitivity in the cluster-based permutation testing, the layer-resolved BOLD and VASO signals were upsampled from 9 to 18 layers using linear interpolation, although comparable results were observed with and without upsampling. For visual interpretability, the sign of the VASO signal was flipped (i.e., multiplied by negative 1), as decreases in VASO signal correspond to increases in BOLD signal. To emphasize signal dynamics across cortical depth and time, the BOLD and VASO data were normalized (z-scored) across layers within each participant. Four main tests were conducted separately for BOLD and VASO signals with both non-normalized and normalized signals: (1) inducers with afterimages versus baseline, (2) mock inducers with mock afterimages versus baseline, (3) inducers with afterimages versus mock inducers with mock afterimages, and (4) inducers + mock inducers only versus baseline ( Figure 5 ; Supplementary Figure 10 and 11). Results Mock afterimage Participants reported the sharpness, contrast, and duration of their afterimages ( Supplementary Figure 1A ) [ 39 ]. These perceptual details were used to create mock afterimages: animated, images designed to appear as each participant’s afterimage. Thus, the mock afterimage served as a perceptual control tailored to each participant. Across participants, the mock afterimages had a mean sharpness of 14.5 pixels (SD = 4.22; 0 = no blurring; 25 = maximum blurring), a mean maximum contrast of 0.20 (SD = 0.055; 0 = no contrast; 1 = full contrast), and a mean duration of 6.13 seconds (SD = 1.51; Supplementary Figure 1C ). Importantly, participants were not told that the mock afterimage was an on-screen stimulus. However, 6 participants (18.75%) reported noticing that the mock afterimage was an on-screen image (e.g., one participant explaining that when they moved their eyes away from fixation, the mock afterimage remained in place on screen, whereas afterimages typically follow gaze position). The remaining participants believed the mock afterimage was an illusory percept until they were debriefed at the end of their final study session. Overall, participants reported that the afterimage and mock afterimage shared similar visual perceptual attributes, although some participants reported differences ( Table 1 ). Also, 5 participants described distortions and transformations in their afterimages, including the appearance of facial expressions, resemblance to familiar faces, and changes in shape ( Table 2 ). View this table: View inline View popup Download powerpoint Table 1. Representative participant reports on perceived similarities and differences between afterimages and their perceptually matched animated images – what are referred to as “mock afterimages”. Each report (x) reflects an individual participant’s response to the post-task questionnaire (see Post-task questionnaire Methods section). View this table: View inline View popup Download powerpoint Table 2. Participant reports on afterimages appearing to distort or transform. Each report (x) reflects an individual participant’s response to the post-task questionnaire (see Post-task questionnaire Methods section). Afterimage and mock afterimage perception task Participants completed a perception task in which they experienced illusory afterimages and perceptually matched images, referred to as mock afterimages (see Afterimage and mock afterimage perception task Methods section). The perception task was administered with simultaneous pupillometry, eye tracking, and fMRI recordings. The following sections detail the results of these measurements in relation to task events, with a particular focus on afterimages and mock afterimages. Behavior During the whole brain fMRI study session, participants reliably reported afterimages following the inducers (mean perception rate = 0.79; SD = 0.25) but rarely reported afterimages after the mock inducers when no mock afterimage was physically presented (mean perception rate = 0.064; SD = 0.11; Figure 1D ). This confirms that the mock inducers alone did not elicit afterimages. However, when mock afterimages were presented following the mock inducers, participants reported perceiving them at a high rate (mean perception rate = 0.95; SD = 0.075). Similar afterimage and mock afterimage perception rates were observed during the V1 fMRI study session (afterimage mean perception rate = 0.83; SD = 0.12; mock afterimage mean perception rate = 0.94; SD = 0.095; mock afterimage mean perception rate following mock inducers without mock afterimages = 0.05; SD = 0.07; Supplementary Figure 2). During the whole brain fMRI study session, the duration of afterimages (mean = 3.66 seconds; SD = 1.25) and mock afterimages (mean = 4.12 seconds; SD = 1.55), and the onset latency of afterimages (mean = 1.64 seconds; SD = 0.74) and mock afterimages (mean = 1.81 seconds; SD = 0.33) were not statistically different ( p > 0.05; Figure 1E ). The approximate same durations and onset latencies were reported during the V1 fMRI study session (afterimage mean duration = 4.23 seconds; SD = 1.52; mock afterimage mean duration = 3.77 seconds; SD = 1.11; afterimage mean onset latency = 1.51 seconds; SD = 0.67; mock afterimage mean onset latency = 1.84 seconds; SD = 0.31; Supplementary Figure 2). Within participant variance of afterimage and mock afterimage duration and onset latency was statistically greater for afterimages versus mock afterimages in both the whole brain and V1 fMRI study sessions, except the onset latency was not significant for the V1 fMRI session (Supplementary Figure 3). In addition, in the whole brain fMRI session, there was a statistically significant correlation across participants for the duration ( r = 0.60; p = 0.0003) and onset latency ( r = 0.41; p = 0.019) between afterimages and mock afterimages, suggesting shared temporal perceptual features within participants ( Figure 1F ). In the V1 fMRI session, a statistically significant correlation was found for duration ( r = 0.62; p = 0.037) but not onset latency ( p > 0.05; Supplementary Figure 2C ). Eye measure responses During the inducer and mock inducer presentation interval (0-4 seconds), pupil size and blink fraction exhibited distinct patterns of change. The mock inducer produced two distinct troughs and peaks in both pupil size and blink fraction, corresponding with its flashing presentation (0-4 seconds; Supplementary Figure 4B and C ). These fluctuations were mirrored by troughs in microsaccade fraction, likely due to an increase in blinking at those times, thereby reducing the number of detectable microsaccades because the eye is partially or completely closed. Notably, eye measures during the mock inducer presentation showed little to no difference between mock inducer trials with and without mock afterimages ( Supplementary Figure 4B ). In contrast, differences were observed during the inducer interval between inducer trials with and without afterimages ( Supplementary Figure 4A ). Specifically, pupil size was larger ( p = 0.0003) and blink fraction was smaller ( p = 0.0004) for inducers that led to an afterimage compared to those that did not. These findings suggest that neurophysiological state during the inducer presentation is related to whether an afterimage is perceived. This result was corroborated by baseline and inducer related BOLD responses (see Whole brain BOLD signals section). During the afterimage and mock afterimage interval, trials with afterimages and mock afterimages exhibited a decrease in blink fraction (inducer trials with versus without afterimages: p = 0.0003; mock inducer trials with versus without mock afterimages: p = 1×10 -6 ; Supplementary Figure 4A and B ). During the post-afterimage interval, inducer trials with afterimages had a smaller pupil size ( p = 0.003), increased blink fraction ( p = 0.0003), and decreased microsaccade fraction ( p = 0.00013) relative to inducer trials without afterimages ( Supplementary Figure 4A ). During the post-mock afterimage interval, mock inducer trials with mock afterimages had an increased blink fraction ( p = 0.001) relative to mock inducer trials without mock afterimages ( Supplementary Figure 4B ). Comparison between the inducers with afterimages and mock inducers with mock afterimages conditions revealed differences across the inducer and mock inducer ( p = 2×10 -9 ), afterimage and mock afterimage ( p = 0.005), and post-afterimage and mock afterimage intervals ( p = 0.0003; Supplementary Figure 4C ). Blink fraction was also different between conditions for the inducer and mock inducer interval ( p = 7×10 -6 ; Supplementary Figure 4C ). Meanwhile, blink and microsaccade fraction were not different between the inducers with afterimages and mock inducers with mock afterimages conditions during the afterimage and mock afterimage and post-afterimage and mock afterimage intervals. Whole brain BOLD signals Whole brain fMRI analyses revealed that afterimages and mock afterimages recruited widespread subcortical and cortical BOLD signal increases, independent of inducer and mock inducer linked responses, including in visual (e.g., LGN, V1, FG and LOC), salience (e.g., AC and In), and motor network regions (e.g., supplementary motor area [SMA], basal ganglia, and left M1; Figure 2A , B, C, and D; Supplementary Slides 1 and 2). There were also increases in visual attention and decision making frontal and parietal regions, including the superior parietal lobule, inferior parietal lobule, superior frontal gyrus, and inferior frontal gyrus. The engagement of these areas could be explained by task demands (e.g., responding to the onset and offset of afterimages and mock afterimages). Supporting this interpretation, these possible task-related regions, including motor areas did not differ between afterimage and mock afterimage conditions ( Figure 2E and F ). When unilateral visual field analyses were performed (i.e., independently analyzing the left versus right visual field stimulus presentation trials), similar areas of activation were observed as in the bilateral analyses (Supplementary Figure 7). However, a key difference was that visual sensory regions (e.g., V1, FG, and LOC) showed contralateral BOLD signal increases relative to the visual field presentation location, while the ipsilateral areas generally exhibited no change or signal decreases. Meanwhile, for both the afterimage and mock afterimage conditions, higher order association, salience, and motor network regions (e.g., left M1) were retinotopically invariant. Contrasting the afterimage and mock afterimage BOLD signals revealed broad decreases for afterimages relative to mock afterimages ( Figure 2E and F ; Supplementary Slides 3). In short, while afterimages and mock afterimages shared similar areas of activation, the magnitude of the signal was significantly reduced for afterimages relative to mock afterimages across many of these overlapping brain networks. These decreases were predominately present in visual and frontal cortices, particularly middle frontal gyrus. However, two notable salience network regions revealed greater BOLD signals for afterimages versus mock afterimages: AC and In. Differences in afterimage and mock afterimage BOLD signals cannot be explained by activity from inducers and mock inducers. This was directly tested by contrasting BOLD responses to inducers and mock inducers. This comparison revealed only small differences at the peak inducer response time (6 seconds post-inducer and mock inducer onset) and the peak afterimage and mock afterimage response time (14 seconds post-inducer and mock inducer onset; Supplementary Figure 6). Whole brain BOLD signals analyses also explored differences between inducer trials with and without afterimages. Notably, during the interval responsive to the period immediately preceding and during the inducer presentation, BOLD decreases were observed, particularly in visual cortex, and BOLD increases in midbrain and thalamus for inducers with afterimages relative to inducers without subsequent afterimages ( Supplementary Figure 5A and B ). Meanwhile, there were little to no differences at the same time points between mock inducer trials with and without mock afterimages ( Supplementary Figure 5C and D ). These findings are linked with the observed differences in pupil size and blink fraction for inducer trials with and without afterimages during the interval responsive to inducer presentation ( Supplementary Figure 4A ; see Eye measure responses section). Whole brain BOLD functional networks Functional clustering on afterimage and mock afterimage BOLD dynamics was performed to organize whole brain activity patterns and summarize signal trends (see K-means clustering Methods section). K-means clustering (k = 3) resulted in clusters that approximately corresponded with established functional brain networks ( Figure 3A ; Supplementary Figure 8A and C ): (1) sensory and salience (SSN), (2) task-positive (TPN), and (3) task-negative (TNN) networks. The network names were assigned based on the known functional roles of the major brain regions grouped within each network. Among other regions, the SSN includes V1, extrastriate cortex, FG, lateral occipital cortex, superior frontal gyrus, AC, and In; the TPN includes the medial frontal gyrus (pre-SMA), basal ganglia, and right superior cerebellum; and the TNN includes the angular gyrus, ventral medial prefrontal cortex, precuneus, and posterior cingulate cortex (PCC) – all areas affiliated with the default mode network. Importantly, these cluster labels are approximations, as some regions do not strictly align with canonical network definitions (e.g., the left M1 was grouped within the SSN, while right M1 was grouped within TNN). The average BOLD timecourses for the SSN, TPN, and TNN further clarified their functional identity based on temporal dynamics relative to task events ( Figure 3B ; Supplementary Figure 8B and D ). The SSN exhibited an early BOLD increase, peaking ∼11 seconds post-inducer and mock inducer onset. The TNN showed an inverse pattern to the SSN, with an initial decrease reaching a nadir at ∼12 seconds, followed by an increase between 15 and 25 seconds. Finally, the TPN had a late BOLD increase, peaking at ∼15 seconds. The SSN response timing suggests that these areas are sensitive to afterimages and the task stimuli (inducer, mock inducer, and mock afterimage). In contrast, the late TPN response suggests sensitivity to the task behavior (i.e., participants indicating the onset and offset of perceived afterimages and mock afterimages). This interpretation is supported by additional analyses that used each network as a ROI to visualize BOLD signal trends across task conditions and within each network. In the SSN, the afterimage, mock afterimage, and inducers + mock inducers only conditions all shared similar onset latencies but diverged in their peak response time: the inducers + mock inducers only condition exhibited an early peak response ∼6 seconds post-inducer and mock inducer onset, while the afterimage and mock afterimage conditions showed later peaks between 10-15 seconds ( Figure 3C ). Also apparent, the response magnitude in the SSN was reduced for afterimages compared to mock afterimages, consistent with the observed whole brain BOLD signal magnitudes ( Figure 2C ). In the TPN, afterimage and mock afterimage conditions showed similar BOLD timecourses, while the inducers + mock inducers only condition did not elicit a significant response ( Figure 3C ). This result aligns with the behavior during the perception task: button presses were made for the afterimage and mock afterimage conditions only, while no response was made for the inducers + mock inducers only trials. These results further highlight that the TPN was specifically responsive to task behavior. In the TNN, all conditions produced a similar pattern of change: a decrease in BOLD signal, reaching a nadir between 10-13 seconds post-inducer and mock inducer onset ( Figure 3C ). The presence of this response for the inducers + mock inducers only condition suggests it is not solely driven by task demands, rather it may reflect network inhibitions or switches [ 74 ]. Notably, a late BOLD signal rebound was observed in the TNN, which was stronger for the afterimage and mock afterimage conditions, potentially reflecting recovery following visual stimulation, afterimage perception, and task-engagement. Sensory and salience network regions of interests Within network analyses focused on the SSN because it was the most responsive brain network to both afterimages and mock afterimages ( Figure 3C ). We selected 6 ROIs clustered within SSN ( Figure 4A ; see Regions of interest section): (1) LGN, (2) V1, (3) FG, (4) AC, (5), AI, and (6) left M1 (L-M1). In L-M1, the BOLD signal showed the expected response: late increases in activity of equal magnitude for afterimages and mock afterimages, with no response for the inducers + mock inducers only condition ( Figure 4G ). There were two distinct phases in the afterimage and mock afterimage L-M1 timecourses, likely corresponding to the two button presses made by participants indicating the onset and offset of perceived afterimages and mock afterimages. The visual sensory ROIs (LGN, V1, and FG; Figure 4B , C, and D) exhibited robust early responses across all conditions, with an onset latency of ∼4 seconds after the inducer or mock inducer onset. However, only the afterimage and mock afterimage conditions showed a second distinct response, while the inducers + mock inducers only condition returned to baseline after an initial peak. In the LGN and V1, this second, afterimage and mock afterimage-linked response appeared as a distinct peak at ∼15-17 seconds. Notably, in V1, the afterimage and mock afterimage peaks were reduced in magnitude compared to the earlier inducer and mock inducer-related peaks. In FG, instead of two peaks, a prolonged, unimodal response was observed, peaking between ∼7-11 seconds. Consistent with the whole brain results ( Figure 2C ), the afterimage response was weaker in all visual sensory ROIs relative to the mock afterimage. In the salience network ROIs (AC and In), all trial conditions revealed increases in BOLD activity. However, the peak time differed: the inducers + mock inducers only condition peaked ∼9-12 seconds post-inducer and mock inducer onset, while the afterimage and mock afterimage conditions peaked between ∼13-15 seconds ( Figure 4E and F ). Furthermore, as observed in the whole brain results, afterimages evoked a stronger BOLD response than the mock afterimages in AC and In. In summary, the ROI BOLD timecourses complement and expand on the whole brain BOLD activation maps by showing the full temporal response profile in areas of known activity. For LGN, V1, and L-M1, bimodal BOLD responses were present, likely reflecting both stimulus processing and task-related motor activity. For FG, AC, and In, unimodal BOLD responses were present, potentially reflecting sustained or integrative processing (e.g., overlapping contributions from both the inducer and mock inducer and afterimage and mock afterimage phases). V1 cortical layer-dependent activity The current results along with previous fMRI studies (e.g., [ 34 ]), support that afterimages activate V1. However, shared activation of V1 does not necessarily imply that afterimages and images share neural information flow. Feedforward and feedback neural signaling are associated with distinct layer-specific activity patterns, detectable using high-spatial-resolution fMRI capable of resolving meso-scale activity [ 49 ]. To investigate neural signaling patterns in V1 for afterimages and mock afterimages, we collected high-spatial-resolution BOLD and VASO fMRI data in V1 while participants completed the perception task ( V1 fMRI sequence Methods sections). First, we confirmed that layer-resolution BOLD signals in V1 produced responses across afterimage, mock afterimage, and inducers + mock inducers only conditions that closely matched the timecourses observed in the whole brain BOLD V1 ROI analysis ( Figure 4C versus Figure 5B ). This replication suggests consistency between the whole brain and V1 data sets. Subsequently, we analyzed event-related, layer-dependent VASO responses in V1. VASO offers higher spatial specificity than BOLD, especially in layer analyses, due to its reduced sensitivity to large vessels positioned along the cortical surface [ 38 ]. Therefore, VASO results are emphasized ( Figure 5 ; Supplementary Figure 11A , C, and E), though layer-dependent BOLD signals are also reported (Supplementary Figure 10; Supplementary Figure 11B , D, and F). Non-normalized and normalized (z-scored) VASO and BOLD signals are presented to highlight both absolute response magnitude and relative trends across layers, respectively. During the inducer and mock inducer period, VASO increases were synchronized across V1 layers, peaking ∼4-6 seconds after onset ( Figure 5C , D, F, and G; Supplementary Figure 11A and C ). A similar pattern was observed in BOLD ( Supplementary Figure 10A , B, D, and E; Supplementary Figure 11B and D ). However, VASO and BOLD showed significantly more activity in the middle layers and middle and superficial layers, respectively, for inducers relative to mock inducers ( Figure 5E and H ; Supplementary Figure 10C and F ). Meanwhile, during the afterimage and mock afterimage period, cortical layer differences were observed in VASO but not in BOLD. Specifically, afterimages elicited greater deep layer VASO activity than mock afterimages ( Figure 5E and H ). The normalized VASO and BOLD signal reinforced these findings, including VASO and BOLD increases in superficial layers for inducers versus mock inducers ( Supplementary Figure 10I ), and VASO increases in deep V1 layers for afterimages versus mock afterimages ( Figure 5K ). Normalized VASO also revealed distinct temporal dynamics: a single superficial-middle layer response for inducers with afterimages, and two temporally separated superficial-middle layer responses for mock inducers with mock afterimages – the first linked to the mock inducer and the second to the mock afterimage ( Figure 5I versus J). These results suggest that while both inducers with afterimages and mock inducers with mock afterimages conditions involve two events, V1 superficial and middle layers were less responsive to afterimages. In fact, normalized VASO responses for afterimages appeared similar to those observed for the inducers + mock inducers only condition that involves a single event ( Figure 5I versus Supplementary Figure 11E ). Finally, a consistent trend observed across all task conditions and in both VASO and BOLD signals was that the V1 layers which were most active early in the response became least active later ( Figure 5 ; Supplementary Figure 10 and 11). This dynamic shift in response across cortical depth and over time underscores the independent signaling of the V1 cortical layers. Discussion The precise neural mechanisms of afterimages are unknown. To advance knowledge on the neurophysiological basis of afterimages, we examined the human whole brain and V1 cortical layer fMRI responses, along with eye measures during afterimage perception and while viewing “mock afterimages” – perceptually matching animated images that were tailored to resemble each participant’s afterimage. Our results are summarized by four main findings: (1) afterimages engaged widespread cortical and subcortical activity, particularly across visual sensory regions ( Figure 2 and 3 ); (2) the magnitude of the afterimage fMRI signal was weaker , especially in visual sensory and lateral frontal regions compared to perceptually matched images ( Figure 2 , 3, and 4); (3) the magnitude of the afterimage fMRI signal was greater in salience network regions (AC and In) compared to perceptually matched images ( Figure 2 and 4 ); and (4) afterimages involved greater activity in deep cortical layers of V1, whereas perceptually matched images showed greater activity in middle and superficial layers, suggesting that afterimage and image perception rely on distinct neural information flow dynamics in V1 ( Figure 5 ). Additional observations include that afterimages maximally activated the contralateral visual cortex relative to the visual field in which the afterimage appeared (Supplementary Figure 7). This pattern of response mirrors those of images and shows that afterimage neural signaling abide by the contralateral circuitry of the primary visual pathway. Furthermore, we show that blinking and microsaccades are similarly responsive for afterimages and perceptually matched images, although this common response may be related to task demands (Supplementary Figure 4). We also found that pupil size and blinking during the inducer presentation interval – the stimulus administered to provoke afterimages – differed between trials when an afterimage was perceived versus not perceived. This finding was linked to decreased fMRI activity predominately in visual cortical regions and increased fMRI activity in arousal network regions (midbrain and thalamus) prior to the afterimage perception interval for trials when afterimages were perceived versus not perceived ( Supplementary Figure 5A and B ). These findings reveal that the preceding central neurophysiological state contributes to whether an afterimage is subsequently perceived. This result relates to previous behavioral findings that attentional and conscious states prior and during afterimage perception influences their conscious experience [ 75 – 77 ]. Further, the influence of neurophysiological state, which can be dynamic on a moment-by-moment basis, may help explain why afterimages are found to be more perceptually heterogenous within and across individuals compared to suprathreshold images, as we report in the current study ( Figure 1 ; Supplementary Figure 1, 2, and 3; also see [ 39 ]). An unexpected outcome from this investigation was that some participants reported that their afterimages would occasionally transform and distort (e.g., appearing as a recognizable face or making facial expressions; Table 2 ). This could be related to top-down effects that alter the appearance of afterimages. In support, previous behavioral research finds that afterimages are sensitive to top-down modification, including by priming and perceptual priors [ 42 , 78 ]. Do afterimage and image perception share brain mechanisms? Afterimages engaged similar brain regions as perceptually matched images, including V1, FG, and LOC. However, our results also indicate that the neural processes underlying afterimages and images differ. A major difference was reduced fMRI signal magnitude for afterimages compared to images across the entire brain, especially in visual network regions ( Figure 2 , 3, and 4). This finding aligns with a previous study reporting better fMRI-based classification performance for images versus afterimages, which may be explained by weaker afterimage signals [ 35 ]. Importantly, the afterimage-linked fMRI signals were weaker, despite the perceptually matched images closely resembling afterimages ( Table 1 ). Notably, many participants were convinced that these images were also illusory afterimages. Another difference was in the pattern of V1 layer activity. Although both afterimages and images activated V1, layer-dependent analyses revealed that afterimages selectively engaged deep layers, whereas images engaged middle and superficial layers of V1 ( Figure 5 ). The middle layer of V1 receives feedforward input, while superficial and deep layers are primarily associated with feedback signaling [ 79 , 80 ]. In addition, distinct neural activity dynamics in superficial versus deep layers of V1 suggest different types of feedback [ 81 , 82 ]. One hypothesis is that superficial layers involve externally generated feedback (e.g., during visual perception), while deep layers involve internally generated feedback (e.g., during visual imagery) [ 83 ]. This framework is supported by findings that visual perceptual illusions engage superficial cortical layers, while visual imagery recruit deep layers [ 84 , 85 ]. Correspondingly, the observed V1 layer activity suggests that afterimages involve internally generated feedback at the earliest stage of visual cortical processing. Thereby, the neural mechanisms of afterimages in V1 may be more similar to visual imagery and other self-generated percepts (e.g., hallucinations and dreams) than sensory visual perception. This conclusion is corroborated by behavioral evidence that the vividness of afterimages and visual imagery are correlated [ 39 , 86 , 87 ]. Also, it has been reported that visual imagery can induce afterimages [ 13 , 16 ]. Finally, the differences observed between afterimages and images, such as in frontal cortical areas, including AC and middle frontal gyrus may reflect perceptual reality monitoring : neural processes that distinguish real from illusory or self-generated conscious experiences (e.g., seeing versus imagining) [ 88 – 90 ]. Accordingly, our findings may partly reflect neural mechanisms that detect signal features that distinguish illusory or internally generated visual percepts from those elicited by physically present images. Are afterimages retinal or central? The neurophysiological origins of afterimages are often framed as arising from either retinal or central neural processes [ 3 ]. This framing posits a false dichotomy. Much like image perception, typical afterimages involve both retinal and central neural mechanisms. Supporting this integrated perspective, the current results revealed widespread subcortical and cortical activity linked with afterimages. These afterimage-linked central neural signals may originate in the retina but undergo post-retinal signal modulation that shapes the afterimage experience. An additional nuance is that there are different categories of afterimages, such as positive and negative afterimages, and less explored afterimage subtypes, including conditioned afterimages or imagery-induced afterimages [ 13 – 16 , 21 ]. Each category of afterimage may involve a unique balance of retinal and central contributions. For example, if imagery-induced afterimages are taken at face value, they exemplify cortically generated afterimages (i.e., afterimages in the absence of any retinal input). Meanwhile, afterimages resulting from retinal photoreceptor bleaching (e.g., after viewing a bright light) may be best characterized by perseverating retinal activity that drives a strong feedforward input to the visual cortical network. Conclusions Afterimages are a long-standing source of scientific interest, yet there are few studies that directly investigate the neural processes involved in afterimage perception. In this experiment, we recorded human whole brain and V1 layer fMRI signals and eye measures linked with afterimages and perceptually matched images. Our results show that afterimage and image perception involve overlapping, widespread brain activity. Yet, the afterimage signals were also distinct from those of images, including reduced signal magnitude across the brain, except in salience network regions where the fMRI signal was stronger for afterimages. We also observed that afterimages selectively engaged deep layers of V1, while images recruited middle and superficial layers, suggesting distinct patterns of neural signaling. These neuroimaging findings help explain behavioral evidence that link afterimages with visual imagery and reveal afterimages are influenced by neurophysiological state and top-down effects. While typical afterimages likely originate from retinal activity, these results introduce compelling evidence for the role of central neural processing in afterimage perception. Code and Data Availability Data and code will be available upon publication. Author Contributions SIK was involved in conceptualization, methodology, software, validation, formal analysis, investigation, data curation, writing – original draft, visualization, supervision, and project administration; BA was involved in software, validation, formal analysis, writing – original draft, and visualization; MH was involved in software, formal analysis, investigation, and writing – review & editing; ATM was involved in conceptualization, methodology, investigation, and writing – review & editing; LH was involved in methodology, software, formal analysis, investigation, and writing – review & editing; PAT was involved in software, formal analysis, writing – review & editing, and visualization; JG-C was involved in software, formal analysis, writing – review & editing, and supervision; DAH was involved in conceptualization, methodology, formal analysis, writing – review & editing, and supervision; PAB was involved in conceptualization, methodology, writing – review & editing, supervision, project administration, and funding acquisition. Supplementary Movie 1. Afterimage trial . An inducer stimulus appears (4 seconds) on the right side of the screen followed by a blank screen ( Figure 1A ). Participants often reported a negative afterimage appearing in the same location that the inducer was presented while maintaining central fixation ( Figure 1D ; Supplementary Figure 2A ). Supplementary Movie 2. Mock afterimage trial . A mock inducer stimulus appears (4 seconds) on the right side of the screen followed by a mock afterimage (∼4 seconds; Figure 1B ). Each participant was shown an individualized mock afterimage that perceptually matched with their afterimage perception following the inducer ( Supplementary Figure 1D ). Supplementary Movie 3. Mock inducer without a mock afterimage trial . A mock inducer stimulus appears (4 seconds) on the right side of the screen followed by a blank screen. Participants often reported that the mock inducer did not produce an afterimage ( Figure 1D ; Supplementary Figure 2A ). Supplementary Slides 1. Afterimage whole brain volume BOLD activation maps . Statistically significant t -values are highlighted with a black outline, while sub-threshold regions are shown with transparency at time point 0 to 25 seconds (s) after the inducer onset for inducers with afterimages versus inducers + mock inducers only conditions. Supplementary Slides 2. Mock afterimage whole brain volume BOLD activation maps . Statistically significant t -values are highlighted with a black outline, while sub-threshold regions are shown with transparency at time point 0 to 25 seconds (s) after the mock inducer onset for mock inducers with mock afterimages versus inducers + mock inducers only conditions. Supplementary Slides 3. Afterimage versus mock afterimage whole brain volume BOLD activation maps . Statistically significant t -values are highlighted with a black outline, while sub-threshold regions are shown with transparency at time point 0 to 25 seconds (s) after the inducer and mock inducer onset for inducers with afterimages versus mock inducers with mock afterimages conditions. Download figure Open in new tab Supplementary Figure 1. Perceptual reporting task, perceptual matching validation task, and mock afterimage parameters. (A) The afterimage and image perceptual reporting task involved participants indicating their perceived sharpness, contrast, and duration of afterimages and images using a controllable image (depicted with a hand icon to represent that participants could manipulate its appearance using key presses). The afterimage is depicted with a dotted outline to highlight that the screen remained blank when afterimages were perceived. For full details on the perceptual reporting task see [ 39 ]. (B) The matching validation task was administered to evaluate the efficacy of perceptual matching between the afterimage and mock afterimage. In a subset of trials, the afterimage and mock afterimage were perceived side-by-side. Subsequently, participants were asked to report where they perceived an afterimage. Participants were not initially informed that the mock afterimage was an on-screen stimulus, thereby the instruction to report seen afterimages was inclusive of both afterimages and mock afterimages. (C) The sharpness, maximum contrast, and duration of the mock afterimages across participants. Each open circle represents individual participants. Larger sharpness values correspond with blurrier perception. (D) The contrast by time trend for each participant’s mock afterimage. When the mock afterimage was presented, it was animated to change its contrast overtime, following these trend lines. Sharpness was kept constant throughout the mock afterimage presentation. See Supplementary Movie 2 for an example mock afterimage. Download figure Open in new tab Supplementary Figure 2. V1 fMRI session behavioral results. (A) The mean perception rate with standard error of the mean (SEM) for afterimages following the inducer (red) and mock afterimages following the mock inducer when the mock afterimage was present (dark blue) and absent (light blue). Participants regularly perceived afterimages (> 0.75) and mock afterimages (> 0.90), but not when the mock inducer was presented alone (i.e., without a mock afterimage; < 0.10). (B) The mean afterimage and mock afterimage duration and onset latency with SEM. The afterimage and mock afterimage durations and onset latencies were not statistically different. (C) The correlation between the afterimage and mock afterimage durations and onset latencies with a linear regression line and 95% confidence intervals. Statistically significant positive correlations were found for duration (* p < 0.05) but not onset latency. The open circles represent individual participants (N = 12). See the Methods section for full details on the behavioral analyses. Download figure Open in new tab Supplementary Figure 3. Within participant variance for reported afterimage and mock afterimage duration and onset latency. Duration variance (seconds [s]) for afterimages (red) and mock afterimages (blue) during (A) the whole brain fMRI and (C) V1 fMRI study sessions. Onset latency variance for afterimages and mock afterimages during (B) the whole brain fMRI and (C) V1 fMRI study sessions. Variance is calculated within participant and across all reported perceived afterimages and mock afterimages. In all subplots, the bar height indicates the mean variance, error bars indicate the standard error of the mean, and the open circles indicate individual participants. Statistically significant differences between afterimage and mock afterimage variances are shown with an asterisk (*). Download figure Open in new tab Supplementary Figure 4. Perception task-evoked pupil size, blink, and microsaccade timecourses. (A) Inducers with afterimages versus inducers without afterimages conditions. (B) Mock inducers with mock afterimages versus mock inducers with mock afterimages conditions. (C) Inducers with afterimages versus mock inducers with mock afterimages conditions. The peaks and troughs during the mock inducer period correspond with the contrast flickering of the mock inducer, designed to suppress afterimages. In all subplots, the gray bar between 0 and 4 seconds (s) highlights the inducer and mock inducer period. The dotted open bar in A, solid gray bar in B, and solid gray bar with a dotted outline in C between 6 and 10 s highlight the approximate afterimage and mock afterimage period. The thicker solid timecourses indicate the mean pupil size in pixels (px), blink fraction (the proportion of epochs with a blink at any given timepoint), and microsaccade fraction (the proportion of epochs with a microsaccade at any given timepoint). The thinner dotted timecourses indicate the standard error of the mean (SEM). Statistically significant differences between the depicted conditions in mean eye measure responses within the inducer and mock inducer (0-4 s), afterimage and mock afterimage (6-10 s), and post-afterimage and post-mock afterimage (10-14 s) intervals are indicated with asterisks (*; see Eye tracking and pupillometry Group-level analysis Analysis Methods section). All values were standardized (z-scored) across participants (see Eye tracking and pupillometry Analysis Methods section). Download figure Open in new tab Supplementary Figure 5. Inducers with versus without afterimages and mock inducers with versus without mock afterimages whole brain volume BOLD activation maps. Statistically significant t -values are highlighted with a black outline and sub-threshold regions are shown with transparency at representative time points (A, C) 0 and (B, D) 6 seconds (s) from the inducer and mock inducer onset. Results are depicted for ( A , B ) a contrast between inducers with afterimages versus inducers without afterimages and ( C , D ) a contrast between mock inducers with mock afterimages versus mock inducers without mock afterimages. Download figure Open in new tab Supplementary Figure 6. Inducers versus mock inducers whole brain volume BOLD activation maps. Statistically significant t -values are highlighted with a black outline, while sub-threshold regions are shown with transparency at representative time points (A, B, C) 6 (near to the peak time in BOLD signal linked to inducers and mock inducers) and (D, E, F) 14 seconds (s; near to the peak time in BOLD signal linked to afterimages and mock afterimages) after the inducer and mock inducer onset. Results are depicted for ( A ) inducers without afterimages, ( B ) mock inducers without mock afterimages, and ( C ) inducers without afterimages versus mock inducers without mock afterimages. Download figure Open in new tab Supplementary Figure 7. Left versus right visual field afterimage and mock afterimage whole brain volume BOLD activation maps. Statistically significant t -values are highlighted with a black outline, while sub-threshold regions are shown with transparency at representative time point 14 seconds (s) after the inducer and mock inducer onset. Results are depicted for (A) left and (B) right visual field inducers with afterimages versus inducers + mock inducers only conditions ( afterimage ), and (C) left and (D) right visual field mock inducers with mock afterimages versus inducers + mock inducers only conditions ( mock afterimage ). Brain surface visualization of t -values from statistically significant voxels are shown in a posterior view to highlight visual cortex responses. Download figure Open in new tab Supplementary Figure 8. Afterimage and mock afterimage whole brain BOLD spatiotemporal clustering and network timecourses. K-means clusters (k = 3) of (A) the inducers with afterimages and (C) mock inducers with mock afterimages responses for gray matter brain regions that showed statistically significant change in either the inducers with afterimages or mock inducers with mock afterimages conditions. The clusters corresponded with established functional brain networks: (1) salience and sensory (SSN), (2) task positive (TPN), and (3) task negative (TNN) networks. The network labels approximate the functional role of the brain regions grouped within each cluster. The mean percent change blood-oxygen-level-dependent (BOLD; %) timecourses with standard error of the mean (SEM) across all voxels within the SSN, TPN, and TNN for (B) the inducers with afterimages and (D) mock inducers with mock afterimages conditions. In B and D, the solid gray bar between 0 and 4 seconds (s) highlights the inducer and mock inducer period, while the solid gray bar with a dotted outline between 6 and 10 s highlights the approximate afterimage and mock afterimage period. Download figure Open in new tab Supplementary Figure 9. Layer resolution BOLD and VASO data processing and analysis summary. (A) Schematic of the layer resolution processing and analysis pipeline. Example images from a representative participant (same participant highlighted in Figure 5A and B ) at different stages of the analysis. (B) Extracted cortical gray matter rim with the white matter (WM) and cerebral spinal fluid (CFS) borders. (C) Segmented layers (n = 9) within the gray matter rim (warmer colors indicate layers nearer to the CSF [superficial surface]; cooler colors indicate layers nearer to the WM [deep surface]). (D) Segmented columns (n = 5000) within the gray matter rim. (E) Percent change blood-oxygen-level-dependent (BOLD; %) activation map at 4 seconds after inducer and mock inducer onset for the inducers + mock inducers only condition. (F) Primary visual cortex (V1) region of interest (ROI) defined according to the activation map and cortical columns. (G) Percent change BOLD and vascular space occupancy (VASO) layer-resolution activity in the V1 ROI (highlighted in red to indicate the final output from the processing and analysis pipeline). See the V1 fMRI sequence and V1 fMRI Methods sections for full details on the layer resolution data acquisition, processing, and analysis. Download figure Open in new tab Supplementary Figure 10. Primary visual cortex layer-dependent BOLD activity. The percent change blood-oxygen-level-dependent (BOLD; %) across cortical layers for ( A ) inducers with afterimages ( afterimage ), ( B ) mock inducers with mock afterimages ( mock afterimage ), and ( C ) inducers with afterimages versus mock inducers with mock afterimages ( afterimage vs mock afterimages ) conditions. In A, B, and C the gray bar between 0-4 seconds (s) indicates the inducer and mock inducer period. The dotted open bar in A, solid gray bar in B, and solid gray bar with a dotted outline in C between 6 and 10 s highlight the approximate afterimage and mock afterimage period. Subplots ( D ), ( E ), and ( F ) show the t -values for cortical layer-by-time cluster-based permutation testing on non-normalized data. Subplots ( G ), ( H ), and ( I ) show t -values for cortical layer-by-time cluster-based permutation testing on normalized data (z-scored BOLD). Statistically significant layer-time clusters are outlined with a solid black line. Cerebrospinal fluid (CSF); white matter (WM). Download figure Open in new tab Supplementary Figure 11. Inducers + mock inducers only condition primary visual cortex layer-dependent VASO and BOLD activity. The percent change ( A ) vascular space occupancy (VASO) and ( B ) blood-oxygen-level-dependent (BOLD; %) shown across cortical layers. In A and B, the gray bar between 0 and 4 seconds (s) highlights the inducer and mock inducer period. T -values from cortical layer-by-time cluster-based permutation testing for ( C ) VASO and ( D ) BOLD and ( E ) normalized VASO and ( D ) normalized BOLD (z-scored). Statistically significant layer-time clusters are outlined with a solid black line. The percent change VASO signal was analyzed and shown inverted (negative is up) to enhance clarity and coherence with the BOLD signal. Cerebrospinal fluid (CSF); white matter (WM). Conflicts of Interest The authors declare no conflicts of interest. Acknowledgements This research was made possible by the support of the National Institute of Mental Health Intramural Research Program (ZIAMH002783, ZICMH002884, ZICMH002888). The study was completed in compliance with the National Institutes of Health Clinical Center protocol ID 93-M-0170 ( ClinicalTrials.gov ID: NCT00001360 ). This work utilized the computational resources of the NIH HPC Biowulf cluster ( https://hpc.nih.gov ). Thank you to Gang Chen, Josh Faskowitz, and Marco Barilari for helpful conversations regarding the analysis of the fMRI data. Thank you to Chung Kan for training and guidance in MRI acquisition. Thank you Rüdiger Stirnberg for sharing the 3D-EPI sequence used in the layer-fMRI VASO experiments. This research was supported by the Intramural Research Program of the National Institutes of Health (NIH). The contributions of the NIH authors were made as part of their official duties as NIH federal employees, are in compliance with agency policy requirements, and are considered Works of the United States Government. However, the findings and conclusions presented in this paper are those of the authors and do not necessarily reflect the views of the NIH or the U.S. Department of Health and Human Services. Funder Information Declared National Institute of Mental Health Intramural Research Program , ZIAMH002783 , ZICMH002884 , ZICMH002888 Footnotes ↵ * Co-senior authors References 1. ↵ Zwicker , E ., “Negative afterimage” in hearing . The Journal of the Acoustical Society of America , 1964 . 36 : p. 2413 – 2415 . OpenUrl CrossRef Web of Science 2. ↵ Singh , U. and R.S. Fearing , Tactile After-Images From Static Contact . 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