Ready-Made Bodily Sensations

Ready-Made Bodily Sensations | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Ready-Made Bodily Sensations Nicole Ruta, Gemma Schino, Marina Iosifyan, Brendan Wolfe This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6429051/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 18 Aug, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Embodiment plays an important role in art engagement, yet it is unclear how expectations shape bodily sensations, especially when interacting with ready-made art. In this study, we investigated how expectations and the nature of images of everyday objects affect bodily sensations. We tested if bodily sensations changed depending on (1) whether the participants were told that everyday objects were from a Museum, Commercial or Mixed context and (2) the nature of the images, counterbalancing whether they were of ready-made art or not. To measure bodily sensations, we asked participants to self-report their feelings of activity getting stronger (activations) or weaker (deactivations) in their body by clicking on body silhouettes after viewing the images, a methodology called bodily sensation mapping (BSM). We found that bodily activity in the Chest and Upper Limbs areas was influenced by expectations induced by context only. At the same time, Head and Abdomen activations and Chest, Lower and Upper Libs deactivations were solely impacted by the image type. Our innovative approach to BSMs image analysis revealed how both context and image type were influenced by the activity type, contributing and enriching the ongoing debate regarding the uniqueness of art experiences and aesthetic cognition. Biological sciences/Psychology Biological sciences/Psychology/Human behaviour Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Artworks that depict goal-directed actions, expressive facial emotions, and distinctive bodily postures often engage viewers by evoking embodied responses to the actions and emotions and postures represented 1,2 . As modern art evolved, artists began challenging the very notion of what a work of art is by incorporating everyday objects in their work. Ready-mades (or found art) are everyday objects—often created for a specific, functional, non-artistic purpose—that artists deliberately choose to assign to the status of artwork, usually by recontextualising these objects by placing them in a museum or exhibition space 3 . Classic and now iconic examples of ready-mades are Duchamp’s Bicycle Wheel 4 , consisting of a bicycle fork with a front wheel mounted upside-down on a wooden stool, or Picasso’s Bull’s Head 5 , consisting of a bicycle seat and handlebars arranged to resemble a bull’s head. This contemporary art practice bridges artistic engagement with practical associations by exploiting the ability of the objects to evoke a sense of instrumental action rooted in viewers’ everyday interactions with the exhibited items. Ready-mades offer a unique opportunity to study how everyday objects, when presented as art, can evoke different physical responses based on how much they remind us of their original function (or affordance) within an art setting. Embodied cognition offers a useful theoretical framework to better understand our engagement with ready-made art as it highlights the essential role that bodily sensations play in all cognitive processes 6,7 . In philosophy, phenomenologists such as Merleau-Ponty 8 , Dewey 9 and von Hildebrand 10 significantly contributed to theorising the essential role that the body plays in cognition 11 . According to von Hildebrand 10 , knowing an object (e.g., a painting or a sculpture) corresponds to understanding the creative process behind it. This idea later found strong support in scientific research, starting with Gibson’s ecological theory of perception 12 . Gibson conceptualised perception as an active engagement with our environment and was the first to introduce the term affordances, defined as the possible actions associated with or involving a certain object (e.g., a bottle affords drinking) 12 . More recently, Rietveld broadened the concept of affordances beyond physical interactions, to include our cognitive engagement with the world— such as the act of reflecting and imagining Rietveld 13 . Advances in psychology and neuroscience led to the discovery of mirror neurons 14,15 and the development of embodied simulation theory 16 . Research has shown that the mirror neuron system activates not only when we execute movements but also when we observe others performing the same movements 2,17 . Building on these discoveries, embodied simulation theory emphasized that our sensory-motor system is crucial not only for interacting with the world (e.g. moving, reaching, or feeling), but also for understanding others and for the act of imagining. Taken together, embodied and environmentally embedded approaches highlight the need to integrate the neuroscientific study of the brain with rigorous investigations of how the body acts and interacts with the world 18 . In the context of art experience, Freedberg and Gallese 2 suggested that when we engage with a painting or sculpture, our motor system automatically simulates the artist’s gestures by mentally recreating the movements performed to make the brushstrokes or to carve the shape of the sculpture. A canonical example used to illustrate the role of embodiment in art perception is Lucio Fontana’s Concetto Spaziale series, consisting of monochromatic paintings that exhibit vertical cuts through the surface of the canvases. Embodied simulation theory predicts that, when looking at Fontana’s paintings, the viewers will mentally simulate the action of cutting through the canvas, mirroring the motor action the artist performed. Umiltà et al. 19 observed mu-rhythm suppression in response to Lucio Fontana’s canvas but not to graphically modified versions of his paintings. The mu-rhythm suppression is an index of mirror neuron activity—often observed via an electroencephalogram (EEG)—when we move or observe movement 19 . Moreover, sensory-motor engagement impacts the appreciation of artworks. For example, participants that were asked to contract their facial muscles while looking at a painting with a painful expression gave higher artistic beauty ratings compared to participants who were asked to refrain from making any facial movements 20 . Our experience of art seems to be deeply linked to the way the artist engages with the world: by mentally reconstructing the creative process behind an artwork the viewer generates a new, interactive and dynamic experience 21,22 . Collectively, the studies reported so far indicate that artworks are perceived in an embodied manner. One of the key implications of extending embodied simulation theory to art experiences is that perceiving art involves the same simulation mechanisms that shape our everyday interactions with the world. However, the question of whether art experiences are intrinsically different compared to everyday experiences is still an open question in empirical aesthetics 23 and the object of a lively theoretical debate. While some researchers sustain that art is special and intrinsically different from everyday experiences 23–26 , others argue that those differences are mainly due to socio economics contextual factors rather than unique brain activations during art engagement 27 . Consider a broken glass: in a hardware store a broken glass is seen as a dangerous waste, due to the fact that it can no longer afford its original purpose as a reflective surface or functional window. In her solo exhibition at the Tate Modern, Yoko Ono’s A HOLE 28 placed a pane of glass deliberately shot through with a bullet in the middle of the exhibition space, inviting the viewers to ‘go to the other side of the glass and see through the hole’. In the museum context, Ono transforms the glass's functional flaw into a symbol: an opportunity to explore themes of violence, loss, and renewal. This example illustrates how recontextualising an object within a museum setting can not only reshape its perception as art, but can also transform its affordances—and the ways that we embody it. The prior knowledge and expectations that individuals have about art is often referred to as art schema 29,30 . This schema is activated when individuals believe that they are engaging with art (e.g., in a museum), which subsequently influences both their cognitive and emotional processing of the experience (e.g. the way they will engage with broken glass). Prinz 26 proposes that what sets engagement with art apart from interaction with everyday objects is the adoption of an aesthetic stance that encourages the observer to look beyond the object's practical or ordinary function (e.g., a broken reflective surface or window), affording its metaphorical or unexpected meanings (e.g., an embodied symbol of artistic ideas). An object can afford the aesthetic stance either through its perceptual features like form and colour, or through external cues like contextual expectations and the artist’s intentions. Critically, an aesthetic response arises when something about the object, either in its form or context, invites viewers to interpret it beyond its practical function, opening up metaphorical or emotional meanings 26 . Unlike everyday interactions with objects, which involve direct and active engagement, art often invites a stance of inaction and contemplation, captured by the concept of beholding affordances 31 . While the idea of viewing objects beyond their practical functions echoes Kant’s idea of disinterested interest 32 , in the present study we refer to the modern conceptualisation of disinterestedness, which is characterised by a lack of emotional or bodily involvement towards practical ends 23 . In the example of A HOLE 28 , Ono’s recontextualisation of the broken glass in a museum environment shapes our embodied and motor responses to that object by creating opportunities for contemplation (e.g., looking through the hole) rather than physical interaction (e.g., disposing of it as waste). To our knowledge, no empirical study has examined whether bodily sensations associated with everyday objects differ depending on whether they occur in an art context or in everyday life. Bodily Sensation Maps (BSMs) are a recently developed self-reporting tool for bodily topography aimed at assessing bodily feelings 33,34 . BSMs rely on a person’s self-awareness of their bodily changes and aim to capture their embodied and somatic responses to stimuli or events. Bodily Sensation Maps (BSMs) allow individuals to indicate regions on whole-body silhouettes where they experience increased (activations) or decreased (deactivations) sensory activity. Previous studies have used BSMs to identify unique activation patterns across various contexts, populations, and stimuli 35–41 , including responses to narrative texts, images, and artworks 42,43 . Beyond its application in art, BSMs have proven valuable as biomarkers for bodily sensations related to various cognitive, homeostatic, or even illness-related states 44 , confirming their usefulness and versatility as research tools. The present study adopts an embodied cognition perspective to investigate how the embodied experience of everyday objects that afford specific activities (e.g., a bottle affording drinking) is modulated by their depiction as either ready-made artworks or non-art images, and by contextual information. Specifically, we provided three different contexts: in the Museum condition, everyday objects were presented as works of art; in the Commercial condition, the same objects were introduced as items photographed for sale; while in the Mixed condition, both contexts are presented, and participants are asked to guess which objects were artworks and which were products for sale. This contextual manipulation was intended to evoke distinct expectations in participants, prompting them to adopt a Museum, Commercial, or Mixed cognitive stance. In particular, we address the following research questions: (a) Do experimentally-induced expectations (i.e., Museum vs Commercial vs Mixed stances) have an impact on bodily sensations reported when viewing everyday objects? (b) Does the image type (Art vs Not-Art) moderate these bodily sensations? (c) When expectations are mixed (Mixed condition), is it possible to differentiate between Art and Not-Art image types? (d) Are distinct patterns of bodily sensation associated more with experimentally-induced expectations or with the image type? We hypothesise that when Not-Art images of everyday objects are presented in a Commercial context, they will elicit more sensations in body parts linked to their functional use (e.g., a cup will activate the hands and lips) compared to art images. In contrast, in a Museum context, the same Not-Art images will evoke sensations in atypical body regions (e.g., a cup will elicit sensations in the forehead or knees), but these sensations may be weaker or less differentiated than those elicited by Art images. Finally, we expect that, regardless of the experimental context, Art images will activate fewer body parts associated with an object’s typical functionality compared to Not-Art images. Results Developing a new researchers-friendly BSM visualisation tool and analysis approach Leveraging methodologies by Schino et al. 43 , Ruta and Schino 45 , and Nummenmaa et al. 33 , we developed a custom open-access R script to visualise BSMs, offering a user-friendly alternative to existing MATLAB-based methods 33 . Our new R script automates data preprocessing and enhances the visual representation of click density distributions, enabling standardised and reproducible visualisations of activations and deactivations across body areas. Additionally, it includes a loop function that allows custom filtering of BSMs by variables such as participant or stimuli, facilitating flexible and scalable data analysis. Full methodological details—including preprocessing steps, visualisation techniques, and R code—are provided in the Supplementary Information and freely accessible on OSF at https://osf.io/bke9q/?view_only=5d9f2c577d3f417db1abc1486e7cb776. Assessing the Impact of Condition and Image Type across Body Regions at Individual Level To quantify bodily sensations, we computed an Embodiment Score based on self-reported clicks on the BSMs. For each participant, activation and deactivation click frequencies were summarised separately for each image across five body regions: Head, Chest, Abdomen, Upper Limbs, and Lower Limbs. To obtain the final Embodiment Score, we first calculated the difference between activation and deactivation click counts. Taking into consideration that this difference could be either a positive or negative value ranging from –10 to 10, we applied a signed log transformation to normalise the distribution while preserving directional effects: log(1 + |x|) × sign(x) . We fitted a linear mixed-effects model (estimated using ML and BOBYQA optimiser) to assess the effect that Condition (Mixed vs Commercial vs Museum), Image Type (Art vs Not-Art) and Body Part (Head vs Chest vs Abdomen vs Upper Limbs vs Lower Limbs), and the interactions between these factors have on Embodiment Score. The model included participants and image identity as random effects. The model's total explanatory power was weak (conditional 𝑅2 = 0.08), with the fixed effects alone accounting for 6% of the variance (marginal 𝑅2 = 0.06). The model’s intercept, corresponding to Condition = Mixed, Image Type = Not-Art, and Body Part = Head, was at 0.31 (95% CI [0.26, 0.36], t(45017) = 13.12, p < .001). Within this model, Embodiment Scores were significantly lower in the Chest, Abdomen, Upper Limbs and Lower Limbs than they were in the Head region (all 𝑝 < .001), suggesting a general tendency for participants to report stronger bodily sensations in the Head region, regardless of Condition or Image Type (see Table S2 in the Supplementary Information). We also found that Image Type (Art) had a significant and positive effect (β = 0.07, 95% CI [0.02, 0.13], t(45017) = 2.61, p = 0.009; Std. β = 0.09, 95% CI [0.02, 0.16]), indicating that Art images elicited higher Embodiment Scores overall than Non-Art images (MArt = 0.0994; MNot-art = 0.0913), regardless of Condition or Body Part. The effect of Image Type was significantly moderated by Body Part, indicating that bodily sensations differed depending on both the region of the body and whether the image was from the Art or Not-Art subset. Specifically, Art images elicited significantly lower Embodiment Scores than Non-Art images in the Chest, Upper Limbs, and Lower Limbs compared to the Head region (see Figure 1A and Table S2). Post-hoc pairwise comparisons further clarified the interaction between Image Type (Art vs Non-Art) and Body Part, showing that the effect of Image Type varies significantly across body regions. Specifically, for the Head and Abdomen body regions, Not-Art images elicited significantly lower Embodiment Scores compared to Art images (Head [Not-Art vs Art]: estimate = -0.0925, SE = 0.0158, z = −5.87, p < .0001; Abdomen [Not-Art vs Art]: estimate = -0.1169, SE = 0.0158, z = −7.418, p < .0001). On the other hand, for the Chest, Upper Limbs and Lower Limbs regions, we found the opposite pattern of results, with Not-Art images eliciting significantly higher Embodiment Scores than Art images (Chest [Not-Art vs Art]: estimate = 0.0534, SE = 0.0158, z = 3.388, p = 0.0007; Upper Limbs [Not-Art vs Art]: estimate = 0.0556, SE = 0.0158, z = 3.530, p = 0.0004; Lower Limbs [Not-Art vs Art]: estimate = 0.0649, SE = 4.117, z = 4.117, p < .0001). These post-hoc comparisons were based on estimated marginal means averaged across all levels of Condition (Museum, Commercial and Mixed). We found that Condition did not have a significant main effect on Embodiment Scores, nor was this effect moderated by Image Type. This indicates that, overall, experimentally-induced expectations (i.e., Museum, Commercial or Mixed stances) did not significantly alter bodily sensations when participants viewed Art vs Non-Art images of everyday objects. However, Condition significantly interacted with Body Part, specifically when comparing Embodiment Scores in the Head and Lower Limbs regions. Compared to the Head, both the Commercial (β = 0.11, 95% CI [0.04, 0.19], t(45017) = 2.87, p = 0.004; Std. β = 0.14, 95% CI [0.05, 0.24]) and Museum conditions (β = 0.09, 95% CI [0.02, 0.17], t(45017) = 2.42, p = 0.015; Std. beta = 0.12, 95% CI [0.02, 0.22]) were associated with higher Embodiment Scores in the Lower Limbs relative to the Mixed condition (see Figure 1B and Table S2). Post-hoc pairwise comparisons confirmed that this effect was mainly driven by the difference between the Mixed and Museum conditions in the Lower Limbs region (M = –0.07, SE = 0.03, z = –2.67, p = .023, Bonferroni-corrected). These post-hoc comparisons were based on estimated marginal means averaged across both levels of Image Type (Art and Non-Art). There were no other significant effects in the model, confirming there was no significant interaction between Image Type and Condition, nor a three-way interaction with Body Part (see Table S2 in the Supplementary Information). Differences in Embodiment Score according to Image Type and Condition respectively are illustrated in Figure 1, alongside corresponding BSMs. Is It Art or Not Art? In the Mixed condition, we calculated the relative frequencies of participants’ guesses of whether they thought the images were made by professional artists or by people who sell products. When participants viewed images of everyday objects that were not artworks (Image Type: Not-art), they correctly identified them as images made by people selling items online in 71.49% of cases. However, when participants viewed images of ready made artworks (Image Type: Art), they correctly identified them as such in 49.62% of cases. A Pearson’s Chi-squared test with Yates’ continuity correction showed there was a significant association between the Image Type and participant’s guesses (𝜒2 (1, N = 85) = 143.74, p < .000), meaning that participants were significantly more likely to correctly identify Non-Art images as made by people who sell products than Art images as made by professional artists (Figure 2). Together, the findings reported so far show that both contextual framing (Condition) and whether an image depicts a ready-made artwork (Image Type) independently influence region-specific embodied responses (Body Part), but do not interact with each other. Specifically, the Mixed condition was associated with more polarised embodiment patterns between the Head and Lower Limbs, while Art images elicited higher Embodiment Scores than Not Art images in the Head and Abdomen. In the Mixed condition, where instructions did not invite participants to adopt a specific cognitive stance, participants were significantly better at identifying Not Art images than Art images, suggesting greater ambiguity in identifying artistic representations of everyday objects as artworks. Finally, the model revealed substantial variability in random effects associated with image identity, suggesting that embodiment responses may have been influenced by the everyday activities typically associated with the depicted objects (e.g., shirt with dressing, fork with eating). To account for this, we further explored whether different activities moderated BSMs embodiment patterns across Conditions and Image Type. Exploratory Cluster Analysis to Assess the Impact of Specific Activities at Group Level We ran an exploratory analysis to investigate whether the colour patterns of the BSMs constituted clusters. We used the patternize 46 , recolorize 47 and colordistance 48,49 R package to generate a distance matrix of colour similarity for the BSMs across experimental condition and activity. This approach was inspired by the workflow proposed by Weller and the parameters selected by Schino et al. 50 for the processing of BSMs data. Namely, the parameters are: standard red-green-blue (RGB) color space format, k-means clustering binning method, and Earth Mover’s Distance (EMD) as a measure of distance/dissimilarity 51 . The analysis aimed to group images with similar colour palettes, assessing whether the resulting clusters represented the most visually similar BSMs. Descriptive statistics for total number of pixels counted by body region, respectively associated with activations and deactivations colours, alongside Embodiment Score according to Regions of Interest, Condition and Image Type are reported in Table 1. Table 1. Descriptive statistics for three measures across Regions of Interest (Head, Chest, Abdomen, Upper Limbs, and Lower Limbs), experimental Conditions (Mixed, Museum, Commercial), and Image Types (Art, Not Art). The first two measures—Activations (pixel count) and Deactivations (pixel count)—reflect the total number of pixels associated with activation (red) and deactivation (blue) areas in the BSMs, as identified by our custom image-processing code. The third measure, Embodiment Score (log-transformed), was derived from participants’ click responses and reflects the relative intensity of embodied sensations in each region. Activations are shown in shades of red, Deactivations in blue, Embodiment Score in purple, and Regions of Interest in grey. Regions of Interest Head Chest Abdomen Upper Limbs Lower Limbs Condition Image Type Activations (pixel count) Activations (pixel count) Activations (pixel count) Activations (pixel count) Activations (pixel count) Mixed Art 68537 214584 124412 180877 48816 Mixed Not-Art 78417 193070 79605 176383 19387 Museum Art 73038 143357 82397 99211 75781 Museum Not-Art 78908 170167 53196 125969 26243 Commercial Art 75586 127387 78943 158047 60565 Commercial Not-Art 76069 189065 29478 159549 19784 Deactivations (pixel count) Deactivations (pixel count) Deactivations (pixel count) Deactivations (pixel count) Deactivations (pixel count) Mixed Art 6263 56686 64568 234821 290033 Mixed Not-Art 0 52489 110856 223363 303518 Museum Art 4729 112273 93230 179431 266045 Museum Not-Art 7915 89685 138425 197192 294923 Commercial Art 0 89107 98911 221110 293526 Commercial Not-Art 4854 61990 152015 210166 324220 Embodiment Score Embodiment Score Embodiment Score Embodiment Score Embodiment Score Mixed Art 0,38 0,09 0,08 0,15 -0,26 Mixed Not-Art 0,31 0,17 -0,01 0,19 -0,22 Museum Art 0,42 0,12 0,13 0,14 -0,20 Museum Not-Art 0,29 0,15 0,01 0,22 -0,14 Commercial Art 0,36 0,08 0,10 0,15 -0,25 Commercial Not-Art 0,27 0,12 -0,04 0,19 -0,15 Using a colour distance matrix generated with the colordistance R package (see Figure S1), we visualised pairwise similarity between BSM images as a heatmap. Lower distance values—represented by darker blue tones—indicate higher similarity between images, whereas higher distance values—represented by brighter pink tones—indicate lower similarity (or greater dissimilarity). To complement these results, we qualitatively inspected the hierarchical clustering of BSMs (see Figure S2), using the resulting dendrogram to explore potential recurring embodiment patterns and inform our diagnostic approach for the formal statistical analysis. We observed that BSMs corresponding to the same activity in the Museum and Commercial conditions tend to show low colour distances, indicating a high degree of similarity in embodiment patterns across these two contexts. For example, the distance between the BSM generated for the Art image associated with the activity of dressing in Museum and Commercial conditions is very low (EMD ≅ 0.11; see Figure S1). This suggests that, despite the different expectations induced by the two contextual information (Museum vs Commercial), the same activity tends to evoke similar BSMs for Art images associated with the activity of dressing. Similarly, Not-Art images associated with the same activity result in BSMs that cluster close together. However, when comparing Art and Not-Art images depicting objects associated with the same activity, we can observe a different pattern of results. As can be seen in Figure 3, for activities such as ‘watching media’ and ‘walking’ the difference between BSMs varies depending on whether or not the image is Art or Not-Art. In these cases, the Image Type seems to be critical in inducing different patterns of bodily activity. For example, Art images depicting objects associated with ‘walking’ clearly evoked higher deactivations in the Lower Limbs region than Not-Art images did, in line with the results predicted by the models. Similarly, Art images connected to the activities of ‘watching media’ and ‘eating’ generated unique BSMs that were more distinct than those generated by Not-Art images associated with the same activities. Notably, BSMs generated in response to Art images related to activities like ‘reading’ in both the Museum and Commercial conditions consistently appeared distinct from BSMs for other activities. Art images depicting everyday objects associated with the activity of ‘reading’ in both the Museum and Commercial conditions generated BSMs that showed high dissimilarity scores (EMD > 0.35) compared to most other activities, indicating a unique bodily activation pattern for this activity and Image Type. Discussion The present study investigated how experimentally-induced expectations about the artistic status (Condition) of everyday objects influence self-reported embodiment activity, while accounting for whether the images were actually from art institutions or commercial websites (Image Type). When examining the role of experimentally-induced expectations, we found that the difference in Embodiment Scores between the Head and Lower Limbs was significantly smaller in the Commercial and Museum conditions compared to the Mixed condition. Most notably, the Museum condition reported significantly less deactivation in the Lower Limbs than the Mixed condition did. When assessing the role of image type, results showed that Art and Not-Art images had a significant and clear impact on self-reported embodiment activity in different body regions regardless of the everyday object depicted. Specifically, Art images reported significantly more activity in the Head and Abdomen, as well as significantly less activity in Chest, Lower Limbs and Upper Limbs areas than Not-Art images did. Considering that our results did not reveal a significant interaction between contextual information (Mixed vs Museum vs Commercial) and image type (Art vs Not-art) on Embodiment Score, and that participants were not more likely to recognise Art images as professionally produced, our findings suggest that the artistic depiction of everyday objects and viewers’ expectations each play important yet distinct roles in our embodied experience of art encounters. One of the key contributions of the present study is our improved approach to BSMs analysis, which enabled us to unveil and better quantify colour pattern variations across relevant experimental variables. Cluster analysis on BSMs revealed that the nature of the image and the activity associated with the everyday objects depicted in it played a critical role in shaping embodiment patterns. For activities such as ‘watching media’, ‘working’, and ‘sleeping’, which typically involve a seated posture or minimal engagement of the Lower Limbs, participants reported less Lower Limb deactivation when viewing Art images than when viewing Not-Art images. To better understand these findings, we will take a closer look at the images associated with the activity of ‘watching media’. In our dataset, both image types depicted a TV screen—the Art image showed a screen positioned on a tall plinth against a plain white wall, while the Not-Art image showed a flat TV screen on a low cabinet with storage shelves in a modern living-room interior. The BSM embodiment patterns for the ‘watching media’ Art image revealed higher activations at the level of the Lower Limbs than the Not-Art image did. Conversely, the Not-Art image elicited strong activations in the Head area that were absent from the Art image’s BSMs. There are two important insights to draw from these findings. First: the complex and nuanced pattern of results that emerged from the cluster analysis highlights how individual activities (like ‘watching media’) display characteristic activation patterns that are deviations from and sometimes opposite to the global trend. Second: the recurring clustering of BSM according to image type suggests that Art images depicting everyday objects may reduce sensations typically associated with the functional affordances of those objects and may elicit bodily responses distinct from Non-Art images depicting the same objects. As was the case for image type, we found that individual activities also played an important role in shaping BSM embodiment patterns for the different conditions. For example, when analysing an utilitarian activity like ‘eating’, image cluster analysis revealed that Not-Art images showed more activations at the level of the Head (i.e. mouth and throat areas) in the Commercial condition compared to the Museum and Mixed conditions. At the same time, Art images clustered together in a separate location, showing an increased activity both at the level of the Head and Abdomen across all conditions. Taken together these results demonstrate the need to assess BSMs in terms of activation patterns across the whole body to reveal more meaningful, richer and generalisable insights. We can interpret these findings to indicate that images of ready-made artworks have been deliberately created by art professionals to disrupt the typical functional associations the viewer makes with everyday objects, therefore eliciting less functionally driven bodily sensations. Critically, the results showing diversified embodiment patterns for Art and Not-Art images aligns with predictions from embodied simulation theory 52 , which predicts that art can transform or subvert ordinary affordances by eliciting bodily responses that differ from those elicited by more functionally oriented depictions. We can therefore speculate that when engaging with ready-made artworks, we temporarily distance ourselves from everyday tasks, creating more space for our mental simulation processes to engage in less utilitarian affordances and bodily sensations. Overall, our pioneering approach to BSMs contributes to a better understanding of how context-driven expectations and images of ready-made art shape bodily responses. Finally, a key contribution of this study is our decision and effort to make the R code for visualising and analyzing BSMs openly available to the research community. In doing so, we aim to enhance accessibility, transparency, and reproducibility to facilitate cross-study comparisons, and encourage broader adoption of BSM methods across disciplines. The use of the BSMs has represented an interdisciplinary method of investigation, since body mapping was used for the exploration of all art forms by Violet Paget (‘Vernon Lee’) and Clementina Anstruther-Thomson during excursions at museums and galleries 53 . Paget and Anstruther-Thomson claimed that embodied experiences and bodily sensations are the factors that give rise to mental impressions of beauty or feelings of pleasure (not the other way around), echoing the principles of embodied cognition framework. We demonstrate that BSMs serve as more than visually appealing graphics; they are computationally efficient and enable rapid data processing. This enhances our ability to understand, explore, and compare art experiences holistically in both quantitative and qualitative terms. However, when data volume grows, the overplotting that results may lead to overlapping points obscuring underlying relationships. In such cases, the interpretability of results may diminish. Hence, the importance of our preprocessing approach that computes the differences between activations and deactivations to mitigate this effect. An additional limitation of our study is the potential stimulus set effect 54,55 . It is possible that our reliance on a specific set of everyday-object images, although sourced from both art institutions and commercial websites, might restrict the generalisability of our findings, as the limited variability in stimulus types could have influenced participants’ embodiment responses. By revealing how subtle shifts in context and perception shape the way our bodies respond to everyday objects, this study not only advances our understanding of embodied aesthetics, but also lays the groundwork for a more reproducible and interdisciplinary science of felt experience. Methods All studies described in this paper were approved by the University of St Andrews School of Psychology & Neuroscience Ethics Committee (approval code PS16674), in accordance with the University’s Principles of Good Research Conduct (https://www.st-andrews.ac.uk/policy/research-conduct-and-ethics/principles-of-good-research-conduct-policy.pdf) and fully account for ethical issues related to research involving humans. Informed consent was obtained from all participants prior to taking part in the study. Participants All participants were recruited on Prolific (www.prolific.com), a platform for online research. To ensure high quality data, the study had the following selection criteria: Participants had to (1) be fluent in English and (2) have at least an 80% success rate of experiment completion. The study was developed on Qualtrics, an online software for conducting psychological studies (www.qualtrics.com). A total of 277 participants took part in the study. Twelve participants were excluded from the final analysis due to poor data quality (e.g., no clicks reported on body silhouettes) or failure to pass all attention checks, resulting in a final sample of 265 participants ( M age = 40.11, SD = 13.85; 89 women, 172 men, 2 non-binary and 2 preferred not to report their gender). As recommended by Atari, Davani & Dehghani and Nummenmaa and colleagues, studies exploring self-reported bodily sensations should ideally recruit at least 40 participants per group to ensure adequate statistical power 33,35 . Similar studies conducted with the use of BSMs estimated approximately a similar number of participants taking part in the experiments 37,56 . Therefore, we aimed at having at least 40 participants per condition. Participants were randomly assigned to one of the three experimental Conditions: Museum ( n = 92), Commercial ( n = 93), and Mixed ( n = 92). After exclusions, 89, 91, and 85 participants were retained in each group, respectively. Stimuli Selection We aimed to select a set of objects that people frequently associate with daily activities. To this end, we conducted a pilot study, recruiting 40 participants on Prolific ( M age = 42.05, SD = 13.66; 27 women and 13 men) who did not take part in the main study. Participants were asked to describe activities they perform on a daily basis and the objects they associate with these activities (e.g., drinking: cup). Overall, participants mentioned 25 activities and 536 objects (for the full list of activities, objects and their frequencies, please refer to Table 3S in the Supplementary Information). Based on the results, the most frequent activities were: eating, walking, sleeping, working, showering, dressing, watching media, drinking, reading, cleaning and observing. Previous studies 42,43 found that when participants viewed visual art, their BSMs showed increased activation in the head region, a result interpreted as linked to the act of observing. Therefore, we decided to include objects associated with the activity of observation in our stimuli selection to help determine whether head-level activation is linked to contextual information (i.e., whether it is consistently reported across all BSMs regardless of the activity associated with the object depicted in the image or whether it varies according to the expectations shaped by the set of instructions given to the participant). We then selected the objects most commonly associated with specific everyday activities, such as a shirt for dressing and a coffee cup for drinking. For each activity, we selected pairs of images depicting the same object: one sourced from art institution websites (Image Type: Art) and the other from popular commercial sites that sell new and used goods online, such as eBay (Image Type: Not-Art). The final image set consisted of 68 images in total, representing 34 objects, each depicted by both Art and Not-Art image type. We provide the full list of images, including the depicted objects, corresponding activity, image type (Art vs Not-Art) and website source in Table S1 in the Supplementary Information. Experimental Procedure Participants were randomly assigned to one of the three experimental conditions: Museum, Commercial, or Mixed (see Figure 4). Each condition was designed to induce a specific cognitive stance by providing participants with a distinct set of instructions. The instructions were presented at the beginning of the study, with the aim of shaping participants' expectations regarding the images they would see during the course of the experiment (see Table S4 in the Supplementary Information for the original instructions provided in each experimental condition). Immediately after receiving the instructions, the trials began (see Figure 5). Each image was displayed on-screen for 5 seconds, accompanied by the following text: ‘Look at this picture and think carefully about your body sensations while viewing it.’ Each participant saw 34 images in total, with objects counterbalanced by image type (17 Art and 17 Non-Art) and images presented in a random order. The design ensured that each participant saw all 34 objects, and avoided presenting both image types of the same object. Participants were then asked to report their bodily sensations by using two body silhouettes: one for activations (stronger sensations, more energy) and another for deactivations (weaker sensations, less energy). There was no time limit for this task. Participants were informed that they could click up to 10 times and were encouraged to use multiple clicks to emphasise more significant activation or deactivation in a specific body area (see Figure 5). After seeing each image and reporting their bodily sensations, only participants in the Mixed condition were additionally asked to assess who they thought created the image. They could choose between two options: (1) professional artists or (2) people who sell products. Declarations Data availability Considering that some of the stimuli used in ‘Ready-Made Bodily Sensations’ are protected by copyright, we provide the full list of images selected for the study, relevant image information and the related source link in Table S1. The data and analysis code that support the findings of this study are openly available at: https://osf.io/bke9q/?view_only=5d9f2c577d3f417db1abc1486e7cb776 Acknowledgements This work was supported by the Templeton Religion Trust, TRT-2021-10512, awarded to Brendan Wolfe. The authors would like to thank Karlee Bowlby for proofing the manuscript. Author contributions statement N.R. & M.I. conceived the study, N.R., G.S. & M.I. contributed to the experimental design and B.W. secured the funding to support the study. M.I. conducted the pilot study and image selection, while G.S. & N.R. developed the Qualtrics survey. N.R., G.S. & M.I. analysed the data. N.R. & G.S. developed the new open-access R code to visualise BSM (‘BSM Visualisations 2025.R’) and N.R. & M.I. developed the code to identify body regions and count pixels from the BSM images (‘BSM ROI Finder 2025.R’). G.S. exported the BSM images and ran the cluster analysis. NR, GS, & MI contributed to the development of the initial version of the manuscript and BW provided critical feedback and helped shape the final manuscript. Additional information We have no known conflict of interest to disclose. References Chatterjee, A. The neuropsychology of visual artistic production. Neuropsychologia 42 , 1568–1583 (2004). Freedberg, D. & Gallese, V. Motion, emotion and empathy in esthetic experience. Trends in Cognitive Sciences 11 , 197–203 (2007). Breton, A. & Duchamp, M. Le Surréalisme en 1947 . (Pierre à Feu, Maeght Éditeur, Paris, France, 1947). Duchamp, M. Bicycle Wheel . (1913). Picasso, P. Bull’s Head . (1942). Burnett, M. & Gallagher, S. 4E Cognition and the Spectrum of Aesthetic Experience. Jolma JournalArticle_3409 (2020) doi:10.30687/Jolma/2723-9640/2020/02/001. Keijzer, F. A. Representation and Behavior . (MIT Press, Cambridge, Mass., 2001). Merleau-Ponty, M. The World of Perception . (Routledge, London, 1948). Dewey, J. 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The Aesthetic Stance – On the Conditions and Consequences of Becoming a Beholder. in Aesthetics and the Embodied Mind: Beyond Art Theory and the Cartesian Mind-Body Dichotomy (ed. Scarinzi, A.) vol. 73 117–138 (Springer Netherlands, Dordrecht, 2015). Cupchik, G. C. The Evolution of Psychical Distance As an Aesthetic Concept. Culture & Psychology 8 , 155–187 (2002). Menninghaus, W. et al. The Distancing-Embracing model of the enjoyment of negative emotions in art reception. Behav Brain Sci 40 , e347 (2017). Prinz, J. Emotion and Aesthetic Value. in The Aesthetic Mind: Philosophy and Psychology (eds. Schellekens, E. & Goldie, P.) 0 (Oxford University Press, 2011). doi:10.1093/acprof:oso/9780199691517.003.0006. Skov, M. & Nadal, M. A farewell to art: Aesthetics as a topic in psychology and neuroscience. Perspectives on Psychological Science 15 , 630–642 (2020). Ono, Y. A HOLE . (2009). Jacobsen, T. Bridging the Arts and Sciences: A Framework for the Psychology of Aesthetics. 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Body Maps of Moral Concerns. Psychol Sci 31 , 160–169 (2020). Hietanen, J. K., Glerean, E., Hari, R. & Nummenmaa, L. Bodily maps of emotions across child development. Developmental Science 19 , 1111–1118 (2016). Novembre, G., Zanon, M., Morrison, I. & Ambron, E. Bodily sensations in social scenarios: Where in the body? PLoS ONE 14 , e0206270 (2019). Rinne, P., Tavast, M., Glerean, E. & Sams, M. Body maps of loves. Philosophical Psychology 1–23 (2023) doi:10.1080/09515089.2023.2252464. Lee, H.-S., Torregrossa, L. J., Shenoy, S. & Park, S. Embodiment of emotion in schizophrenia in the context of culture. Psychiatry Research Communications 2 , 100072 (2022). Niemi, K. J. et al. Bodily Maps of Symptoms and Emotions in Parkinson’s Disease. Movement Disorders 39 , 1037–1043 (2024). Volynets, S., Glerean, E., Hietanen, J. K., Hari, R. & Nummenmaa, L. Bodily maps of emotions are culturally universal. Emotion 20 , 1127–1136 (2020). Nummenmaa, L. & Hari, R. Bodily feelings and aesthetic experience of art. Cognition and Emotion 37 , 515–528 (2023). Schino, G., Van Klaveren, L.-M., Gallegos González, H. G. & Cox, R. F. A. Applying bodily sensation maps to art-elicited emotions: An explorative study. Psychology of Aesthetics, Creativity, and the Arts 18 , 315–329 (2021). Nummenmaa, L., Hari, R., Hietanen, J. K. & Glerean, E. Maps of subjective feelings. Proc. Natl. Acad. Sci. U.S.A. 115 , 9198–9203 (2018). Ruta, N. & Schino, G. Bodily Sensation Maps to capture valence and arousal of artistic images: developing a new methodology. (2023). van Belleghem, S. patternize: Quantification of Color Pattern Variation. 0.0.5 https://doi.org/10.32614/CRAN.package.patternize (2017). Weller, H. recolorize: Color-Based Image Segmentation. 0.1.0 https://doi.org/10.32614/CRAN.package.recolorize (2021). Weller, H. colordistance: Distance Metrics for Image Color Similarity. (2021). Weller, H. & Westneat, M. Quantitative color profiling of digital images with earth mover’s distance using the R package colordistance. PeerJ 7 , e6398 (2019). Schino, G., van Klaveren, L.-M., van Dorsten, Theisje, Van Heusden, B. & Cox, R. F. A. Art Is in The Body of The Beholder: Examining Emotions in Children and Adolescents’ Art Experiences. (2025). Rubner, Y., Tomasi, C. & Guibas, L. J. The Earth Mover’s Distance as a Metric for Image Retrieval. International Journal of Computer Vision 40 , 99–121 (2000). Gallese, V. Naturalizing Aesthetic Experience: The Role of (Liberated) Embodied Simulation. (2018) doi:10.3167/proj.2018.120207. Lee, V. The Psychology of an Art Writer . (David Zwirner Books, New York, NY, 1903). Temme, J. E. Effects of Mere Exposure, Cognitive Set and Task Expectations on Aesthetic Appreciation. in Advances in Psychology (eds. Crozier, W. R. & Chapman, A. J.) vol. 19 389–410 (North-Holland, 1984). Bilalić, M., McLeod, P. & Gobet, F. The Mechanism of the Einstellung (Set) Effect: A Pervasive Source of Cognitive Bias. Curr Dir Psychol Sci 19 , 111–115 (2010). Torregrossa, L. J. et al. Anomalous Bodily Maps of Emotions in Schizophrenia. Schizophr Bull 45 , 1060–1067 (2019). Additional Declarations No competing interests reported. Supplementary Files ReadyMadeBSMsSupplementaryInfoScientificReportsApril2025.pdf Cite Share Download PDF Status: Published Journal Publication published 18 Aug, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 16 Jun, 2025 Reviews received at journal 14 Jun, 2025 Reviews received at journal 10 Jun, 2025 Reviewers agreed at journal 05 Jun, 2025 Reviewers agreed at journal 30 May, 2025 Reviewers invited by journal 30 May, 2025 Editor assigned by journal 19 May, 2025 Editor invited by journal 23 Apr, 2025 Submission checks completed at journal 23 Apr, 2025 First submitted to journal 11 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6429051","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":464109170,"identity":"caffd085-ee32-4341-a764-8aebde80a238","order_by":0,"name":"Nicole Ruta","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7UlEQVRIiWNgGAWjYLCChAoILYEQOkBAy4MzENXEa2F82EaKFnOJ9GsfEufV1TGwnz14u6LisD0D++EHzDxncGuxnJFTPCNx22EJBp68ZMszZw4nNvCkGTDz3MCtxeDMmWSGxG0HJOwP5JhJNrbdTmBgyGFg5vlASMucOgkG/jdALf9u2wMZBLQcbz/MkNjALMEgAbKl4TZjgwTIFnwOO97DzJBw7LBkg8QbY8uGY/8T2ySeGRycg8f7BofZHzP+qKnjZ+DPMbzZUJNmz8+f/PDBm2O4tTAw8Big8tkYCEYk+wP88qNgFIyCUTAKAN7TT+mvQUdrAAAAAElFTkSuQmCC","orcid":"","institution":"University of St Andrews, St Mary’s College","correspondingAuthor":true,"prefix":"","firstName":"Nicole","middleName":"","lastName":"Ruta","suffix":""},{"id":464109173,"identity":"4794ffa9-6229-483e-aa88-e9fe196c0780","order_by":1,"name":"Gemma Schino","email":"","orcid":"","institution":"University of Groningen","correspondingAuthor":false,"prefix":"","firstName":"Gemma","middleName":"","lastName":"Schino","suffix":""},{"id":464109176,"identity":"7f761988-a971-48bd-83b1-6ed492717385","order_by":2,"name":"Marina Iosifyan","email":"","orcid":"","institution":"University of St Andrews, St Mary’s College","correspondingAuthor":false,"prefix":"","firstName":"Marina","middleName":"","lastName":"Iosifyan","suffix":""},{"id":464109179,"identity":"8d06cb57-ad03-44b1-a160-72ea601922fd","order_by":3,"name":"Brendan Wolfe","email":"","orcid":"","institution":"University of St Andrews, St Mary’s College","correspondingAuthor":false,"prefix":"","firstName":"Brendan","middleName":"","lastName":"Wolfe","suffix":""}],"badges":[],"createdAt":"2025-04-11 14:08:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6429051/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6429051/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-14061-5","type":"published","date":"2025-08-18T16:29:31+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":83816376,"identity":"86a914c5-3ae5-41b2-a0eb-9ba303fb9dc4","added_by":"auto","created_at":"2025-06-03 07:51:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":196200,"visible":true,"origin":"","legend":"\u003cp\u003eBar plots (left) display the estimated Embodiment Score (log-transformed) from the mixed-effects model for each body part, separated by Image Type (A) and Condition (B). Corresponding Bodily Sensation Maps (BSMs) are shown on the right, illustrating average sensation distributions across body silhouettes as a function of Image Type (top row) and Condition (bottom row).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6429051/v1/8e1e9e5f8ad69642b911fde5.png"},{"id":83816373,"identity":"92cd0be8-bdcb-4289-900e-dbac4f200815","added_by":"auto","created_at":"2025-06-03 07:51:05","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":48557,"visible":true,"origin":"","legend":"\u003cp\u003eStacked bar plot showing the percentage of guess response types by Image Type for participants in the Mixed condition only. Responses for Art images are shown in light red; responses for Not Art images are shown in dark red.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6429051/v1/3daa128c2db60bf05013dbbe.png"},{"id":83816375,"identity":"8c5092fc-0ca7-49b4-9d9a-f06cc90de8e7","added_by":"auto","created_at":"2025-06-03 07:51:05","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":167515,"visible":true,"origin":"","legend":"\u003cp\u003eBSMs for the activities ‘Watching Media’ (top) and ‘Walking’ (bottom), shown across Conditions \u003cbr\u003e\n(Mixed, Museum, Commercial) and Image Types (Art \u003cem\u003evs\u003c/em\u003e Not Art).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6429051/v1/ee5d3d84256a4a1034cc33d7.png"},{"id":83816378,"identity":"2041d95f-10e7-47a9-a343-5468252e5f34","added_by":"auto","created_at":"2025-06-03 07:51:05","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":85789,"visible":true,"origin":"","legend":"\u003cp\u003eDiagram showing experimental condition allocation.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6429051/v1/f0e02d8ade0c8bb88781fedf.png"},{"id":83816374,"identity":"529f5e26-3008-44ea-a485-710fe46eaea2","added_by":"auto","created_at":"2025-06-03 07:51:05","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":60608,"visible":true,"origin":"","legend":"\u003cp\u003eDiagram showing trial procedure for each image.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6429051/v1/e21d2ebc6144c0044a2b3ee6.png"},{"id":89847280,"identity":"7bd7cfb7-ed1f-48db-8e85-45b790679f29","added_by":"auto","created_at":"2025-08-25 16:42:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1421587,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6429051/v1/d26f07a9-67b7-476c-aaad-03b599900f80.pdf"},{"id":83816377,"identity":"b2d19acd-373a-46db-9c19-ebc25186fa2d","added_by":"auto","created_at":"2025-06-03 07:51:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1293517,"visible":true,"origin":"","legend":"","description":"","filename":"ReadyMadeBSMsSupplementaryInfoScientificReportsApril2025.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6429051/v1/39183d16aabb10609fddc99f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Ready-Made Bodily Sensations","fulltext":[{"header":"Introduction","content":"\u003cp\u003eArtworks that depict goal-directed actions, expressive facial emotions, and distinctive bodily postures often engage viewers by evoking embodied responses to the actions and emotions and postures represented \u003csup\u003e1,2\u003c/sup\u003e. As modern art evolved, artists began challenging the very notion of what a work of art is by incorporating everyday objects in their work. Ready-mades (or found art) are everyday objects—often created for a specific, functional, non-artistic purpose—that artists deliberately choose to assign to the status of artwork, usually by recontextualising these objects by placing them in a museum or exhibition space \u003csup\u003e3\u003c/sup\u003e. Classic and now iconic examples of ready-mades are Duchamp’s Bicycle Wheel \u003csup\u003e4\u003c/sup\u003e, consisting of a bicycle fork with a front wheel mounted upside-down on a wooden stool, or Picasso’s Bull’s Head \u003csup\u003e5\u003c/sup\u003e, consisting of a bicycle seat and handlebars arranged to resemble a bull’s head. This contemporary art practice bridges artistic engagement with practical associations by exploiting the ability of the objects to evoke a sense of instrumental action rooted in viewers’ everyday interactions with the exhibited items. Ready-mades offer a unique opportunity to study how everyday objects, when presented as art, can evoke different physical responses based on how much they remind us of their original function (or affordance) within an art setting.\u003c/p\u003e\n\u003cp\u003eEmbodied cognition offers a useful theoretical framework to better understand our engagement with ready-made art as it highlights the essential role that bodily sensations play in all cognitive processes \u003csup\u003e6,7\u003c/sup\u003e. In philosophy, phenomenologists such as Merleau-Ponty \u003csup\u003e8\u003c/sup\u003e, Dewey \u003csup\u003e9\u003c/sup\u003e and von Hildebrand \u003csup\u003e10\u003c/sup\u003e significantly contributed to theorising the essential role that the body plays in cognition \u003csup\u003e11\u003c/sup\u003e. According to von Hildebrand \u003csup\u003e10\u003c/sup\u003e, knowing an object (e.g., a painting or a sculpture) corresponds to understanding the creative process behind it. This idea later found strong support in scientific research, starting with Gibson’s ecological theory of perception \u003csup\u003e12\u003c/sup\u003e. Gibson conceptualised perception as an active engagement with our environment and was the first to introduce the term affordances, defined as the possible actions associated with or involving a certain object (e.g., a bottle affords drinking) \u003csup\u003e12\u003c/sup\u003e. More recently, Rietveld broadened the concept of affordances beyond physical interactions, to include our cognitive engagement with the world— such as the act of reflecting and imagining Rietveld \u003csup\u003e13\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAdvances in psychology and neuroscience led to the discovery of mirror neurons \u003csup\u003e14,15\u003c/sup\u003e and the development of embodied simulation theory \u003csup\u003e16\u003c/sup\u003e. Research has shown that the mirror neuron system activates not only when we execute movements but also when we observe others performing the same movements \u003csup\u003e2,17\u003c/sup\u003e. Building on these discoveries, embodied simulation theory emphasized that our sensory-motor system is crucial not only for interacting with the world (e.g. moving, reaching, or feeling), but also for understanding others and for the act of imagining. Taken together, embodied and environmentally embedded approaches highlight the need to integrate the neuroscientific study of the brain with rigorous investigations of how the body acts and interacts with the world \u003csup\u003e18\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIn the context of art experience, Freedberg and Gallese \u003csup\u003e2\u003c/sup\u003e suggested that when we engage with a painting or sculpture, our motor system automatically simulates the artist’s gestures by mentally recreating the movements performed to make the brushstrokes or to carve the shape of the sculpture. A canonical example used to illustrate the role of embodiment in art perception is Lucio Fontana’s Concetto Spaziale series, consisting of monochromatic paintings that exhibit vertical cuts through the surface of the canvases. Embodied simulation theory predicts that, when looking at Fontana’s paintings, the viewers will mentally simulate the action of cutting through the canvas, mirroring the motor action the artist performed. Umiltà et al. \u003csup\u003e19\u003c/sup\u003e observed mu-rhythm suppression in response to Lucio Fontana’s canvas but not to graphically modified versions of his paintings. The mu-rhythm suppression is an index of mirror neuron activity—often observed via an electroencephalogram (EEG)—when we move or observe movement \u003csup\u003e19\u003c/sup\u003e. Moreover, sensory-motor engagement impacts the appreciation of artworks. For example, participants that were asked to contract their facial muscles while looking at a painting with a painful expression gave higher artistic beauty ratings compared to participants who were asked to refrain from making any facial movements \u003csup\u003e20\u003c/sup\u003e. Our experience of art seems to be deeply linked to the way the artist engages with the world: by mentally reconstructing the creative process behind an artwork the viewer generates a new, interactive and dynamic experience \u003csup\u003e21,22\u003c/sup\u003e. Collectively, the studies reported so far indicate that artworks are perceived in an embodied manner.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOne of the key implications of extending embodied simulation theory to art experiences is that perceiving art involves the same simulation mechanisms that shape our everyday interactions with the world. However, the question of whether art experiences are intrinsically different compared to everyday experiences is still an open question in empirical aesthetics \u003csup\u003e23\u003c/sup\u003e and the object of a lively theoretical debate. While some researchers sustain that art is special and intrinsically different from everyday experiences \u003csup\u003e23–26\u003c/sup\u003e, others argue that those differences are mainly due to socio economics contextual factors rather than unique brain activations during art engagement \u003csup\u003e27\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsider a broken glass: in a hardware store a broken glass is seen as a dangerous waste, due to the fact that it can no longer afford its original purpose as a reflective surface or functional window. In her solo exhibition at the Tate Modern, Yoko Ono’s A HOLE \u003csup\u003e28\u003c/sup\u003e placed a pane of glass deliberately shot through with a bullet in the middle of the exhibition space, inviting the viewers to ‘go to the other side of the glass and see through the hole’. In the museum context, Ono transforms the glass's functional flaw into a symbol: an opportunity to explore themes of violence, loss, and renewal. This example illustrates how recontextualising an object within a museum setting can not only reshape its perception as art, but can also transform its affordances—and the ways that we embody it.\u003c/p\u003e\n\u003cp\u003eThe prior knowledge and expectations that individuals have about art is often referred to as art schema \u003csup\u003e29,30\u003c/sup\u003e. This schema is activated when individuals believe that they are engaging with art (e.g., in a museum), which subsequently influences both their cognitive and emotional processing of the experience (e.g. the way they will engage with broken glass). Prinz \u003csup\u003e26\u003c/sup\u003e proposes that what sets engagement with art apart from interaction with everyday objects is the adoption of an aesthetic stance that encourages the observer to look beyond the object's practical or ordinary function (e.g., a broken reflective surface or window), affording its metaphorical or unexpected meanings (e.g., an embodied symbol of artistic ideas). An object can afford the aesthetic stance either through its perceptual features like form and colour, or through external cues like contextual expectations and the artist’s intentions. Critically, an aesthetic response arises when something about the object, either in its form or context, invites viewers to interpret it beyond its practical function, opening up metaphorical or emotional meanings\u003csup\u003e26\u003c/sup\u003e. Unlike everyday interactions with objects, which involve direct and active engagement, art often invites a stance of inaction and contemplation, captured by the concept of beholding affordances \u003csup\u003e31\u003c/sup\u003e. While the idea of viewing objects beyond their practical functions echoes Kant’s idea of disinterested interest \u003csup\u003e32\u003c/sup\u003e, in the present study we refer to the modern conceptualisation of disinterestedness, which is characterised by a lack of emotional or bodily involvement towards practical ends \u003csup\u003e23\u003c/sup\u003e. In the example of A HOLE \u003csup\u003e28\u003c/sup\u003e, Ono’s recontextualisation of the broken glass in a museum environment shapes our embodied and motor responses to that object by creating opportunities for contemplation (e.g., looking through the hole) rather than physical interaction (e.g., disposing of it as waste). To our knowledge, no empirical study has examined whether bodily sensations associated with everyday objects differ depending on whether they occur in an art context or in everyday life.\u003c/p\u003e\n\u003cp\u003eBodily Sensation Maps (BSMs) are a recently developed self-reporting tool for bodily topography aimed at assessing bodily feelings \u003csup\u003e33,34\u003c/sup\u003e. BSMs rely on a person’s self-awareness of their bodily changes and aim to capture their embodied and somatic responses to stimuli or events. Bodily Sensation Maps (BSMs) allow individuals to indicate regions on whole-body silhouettes where they experience increased (activations) or decreased (deactivations) sensory activity. Previous studies have used BSMs to identify unique activation patterns across various contexts, populations, and stimuli \u003csup\u003e35–41\u003c/sup\u003e, including responses to narrative texts, images, and artworks \u003csup\u003e42,43\u003c/sup\u003e. Beyond its application in art, BSMs have proven valuable as biomarkers for bodily sensations related to various cognitive, homeostatic, or even illness-related states \u003csup\u003e44\u003c/sup\u003e, confirming their usefulness and versatility as research tools.\u003c/p\u003e\n\u003cp\u003eThe present study adopts an embodied cognition perspective to investigate how the embodied experience of everyday objects that afford specific activities (e.g., a bottle affording drinking) is modulated by their depiction as either ready-made artworks or non-art images, and by contextual information. Specifically, we provided three different contexts: in the Museum condition, everyday objects were presented as works of art; in the Commercial condition, the same objects were introduced as items photographed for sale; while in the Mixed condition, both contexts are presented, and participants are asked to guess which objects were artworks and which were products for sale. This contextual manipulation was intended to evoke distinct expectations in participants, prompting them to adopt a Museum, Commercial, or Mixed cognitive stance. In particular, we address the following research questions: (a) Do experimentally-induced expectations (i.e., Museum \u003cem\u003evs\u003c/em\u003e Commercial \u003cem\u003evs\u003c/em\u003e Mixed stances) have an impact on bodily sensations reported when viewing everyday objects? (b) Does the image type (Art \u003cem\u003evs\u003c/em\u003e Not-Art) moderate these bodily sensations? (c) When expectations are mixed (Mixed condition), is it possible to differentiate between Art and Not-Art image types? (d) Are distinct patterns of bodily sensation associated more with experimentally-induced expectations or with the image type?\u003c/p\u003e\n\u003cp\u003eWe hypothesise that when Not-Art images of everyday objects are presented in a Commercial context, they will elicit more sensations in body parts linked to their functional use (e.g., a cup will activate the hands and lips) compared to art images. In contrast, in a Museum context, the same Not-Art images will evoke sensations in atypical body regions (e.g., a cup will elicit sensations in the forehead or knees), but these sensations may be weaker or less differentiated than those elicited by Art images. Finally, we expect that, regardless of the experimental context, Art images will activate fewer body parts associated with an object’s typical functionality compared to Not-Art images.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eDeveloping a new researchers-friendly BSM visualisation tool and analysis approach\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLeveraging methodologies by Schino et al. \u003csup\u003e43\u003c/sup\u003e, Ruta and Schino \u003csup\u003e45\u003c/sup\u003e, and Nummenmaa et al. \u003csup\u003e33\u003c/sup\u003e, we developed a custom open-access R script to visualise BSMs, offering a user-friendly alternative to existing MATLAB-based methods \u003csup\u003e33\u003c/sup\u003e. Our new R script automates data preprocessing and enhances the visual representation of click density distributions, enabling standardised and reproducible visualisations of activations and deactivations across body areas. Additionally, it includes a loop function that allows custom filtering of BSMs by variables such as participant or stimuli, facilitating flexible and scalable data analysis. Full methodological details\u0026mdash;including preprocessing steps, visualisation techniques, and R code\u0026mdash;are provided in the Supplementary Information and freely accessible on OSF at https://osf.io/bke9q/?view_only=5d9f2c577d3f417db1abc1486e7cb776.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessing the Impact of Condition and Image Type across Body Regions at Individual Level\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo quantify bodily sensations, we computed an Embodiment Score based on self-reported clicks on the BSMs. For each participant, activation and deactivation click frequencies were summarised separately for each image across five body regions: Head, Chest, Abdomen, Upper Limbs, and Lower Limbs. To obtain the final Embodiment Score, we first calculated the difference between activation and deactivation click counts. Taking into consideration that this difference could be either a positive or negative value ranging from \u0026ndash;10 to 10, we applied a signed log transformation to normalise the distribution while preserving directional effects:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003elog(1 + |x|) \u0026times; sign(x)\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eWe fitted a linear mixed-effects model (estimated using ML and BOBYQA optimiser) to assess the effect that Condition (Mixed \u003cem\u003evs\u0026nbsp;\u003c/em\u003eCommercial \u003cem\u003evs\u003c/em\u003e Museum), Image Type (Art \u003cem\u003evs\u003c/em\u003e Not-Art) and Body Part (Head \u003cem\u003evs\u003c/em\u003e Chest \u003cem\u003evs\u003c/em\u003e Abdomen \u003cem\u003evs\u003c/em\u003e Upper Limbs \u003cem\u003evs\u003c/em\u003e Lower Limbs), and the interactions between these factors have on Embodiment Score. The model included participants and image identity as random effects. The model\u0026apos;s total explanatory power was weak (conditional 𝑅2 = 0.08), with the fixed effects alone accounting for 6% of the variance (marginal 𝑅2 = 0.06). The model\u0026rsquo;s intercept, corresponding to Condition = Mixed, Image Type = Not-Art, and Body Part = Head, was at 0.31 (95% CI [0.26, 0.36], t(45017) = 13.12, p \u0026lt; .001).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWithin this model, Embodiment Scores were significantly lower in the Chest, Abdomen, Upper Limbs and Lower Limbs than they were in the Head region (all 𝑝 \u0026lt; .001), suggesting a general tendency for participants to report stronger bodily sensations in the Head region, regardless of Condition or Image Type (see Table S2 in the Supplementary Information).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe also found that Image Type (Art) had a significant and positive effect (\u0026beta; = 0.07, 95% CI [0.02, 0.13], t(45017) = 2.61, p = 0.009; Std. \u0026beta; = 0.09, 95% CI [0.02, 0.16]), indicating that Art images elicited higher Embodiment Scores overall than Non-Art images (MArt = 0.0994; MNot-art = 0.0913), regardless of Condition or Body Part.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe effect of Image Type was significantly moderated by Body Part, indicating that bodily sensations differed depending on both the region of the body and whether the image was from the Art or Not-Art subset. Specifically, Art images elicited significantly lower Embodiment Scores than Non-Art images in the Chest, Upper Limbs, and Lower Limbs compared to the Head region (see Figure 1A and Table S2). Post-hoc pairwise comparisons further clarified the interaction between Image Type (Art vs Non-Art) and Body Part, showing that the effect of Image Type varies significantly across body regions. Specifically, for the Head and Abdomen body regions, Not-Art images elicited significantly lower Embodiment Scores compared to Art images (Head [Not-Art \u003cem\u003evs\u003c/em\u003e Art]: estimate = -0.0925, SE = 0.0158, z = \u0026minus;5.87, p \u0026lt; .0001; Abdomen [Not-Art \u003cem\u003evs\u003c/em\u003e Art]: estimate = -0.1169, SE = 0.0158, z = \u0026minus;7.418, p \u0026lt; .0001). On the other hand, for the Chest, Upper Limbs and Lower Limbs regions, we found the opposite pattern of results, with Not-Art images eliciting significantly higher Embodiment Scores than Art images (Chest [Not-Art \u003cem\u003evs\u003c/em\u003e Art]: estimate = 0.0534, SE = 0.0158, z = 3.388, p = 0.0007; Upper Limbs [Not-Art vs Art]: estimate = 0.0556, SE = 0.0158, z = 3.530, p = 0.0004; Lower Limbs [Not-Art \u003cem\u003evs\u003c/em\u003e Art]: estimate = 0.0649, SE = 4.117, z = 4.117, p \u0026lt; .0001). These post-hoc comparisons were based on estimated marginal means averaged across all levels of Condition (Museum, Commercial and Mixed).\u003c/p\u003e\n\u003cp\u003eWe found that Condition did not have a significant main effect on Embodiment Scores, nor was this effect moderated by Image Type. This indicates that, overall, experimentally-induced expectations (i.e., Museum, Commercial or Mixed stances) did not significantly alter bodily sensations when participants viewed Art \u003cem\u003evs\u003c/em\u003e Non-Art images of everyday objects. However, Condition significantly interacted with Body Part, specifically when comparing Embodiment Scores in the Head and Lower Limbs regions. Compared to the Head, both the Commercial (\u0026beta; = 0.11, 95% CI [0.04, 0.19], t(45017) = 2.87, \u003cem\u003ep\u003c/em\u003e = 0.004; Std. \u0026beta; = 0.14, 95% CI [0.05, 0.24]) and Museum conditions (\u0026beta; = 0.09, 95% CI [0.02, 0.17], t(45017) = 2.42, p = 0.015; Std. beta = 0.12, 95% CI [0.02, 0.22]) were associated with higher Embodiment Scores in the Lower Limbs relative to the Mixed condition (see Figure 1B and Table S2). Post-hoc pairwise comparisons confirmed that this effect was mainly driven by the difference between the Mixed and Museum conditions in the Lower Limbs region (M = \u0026ndash;0.07, SE = 0.03, z = \u0026ndash;2.67, \u003cem\u003ep\u003c/em\u003e = .023, Bonferroni-corrected). These post-hoc comparisons were based on estimated marginal means averaged across both levels of Image Type (Art and Non-Art).\u003c/p\u003e\n\u003cp\u003eThere were no other significant effects in the model, confirming there was no significant interaction between Image Type and Condition, nor a three-way interaction with Body Part (see Table S2 in the Supplementary Information). Differences in Embodiment Score according to Image Type and Condition respectively are illustrated in Figure 1, alongside corresponding BSMs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eIs It Art or Not Art?\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the Mixed condition, we calculated the relative frequencies of participants\u0026rsquo; guesses of whether they thought the images were made by professional artists or by people who sell products. When participants viewed images of everyday objects that were not artworks (Image Type: Not-art), they correctly identified them as images made by people selling items online in 71.49% of cases. However, when participants viewed images of ready made artworks (Image Type: Art), they correctly identified them as such in 49.62% of cases. A Pearson\u0026rsquo;s Chi-squared test with Yates\u0026rsquo; continuity correction showed there was a significant association between the Image Type and participant\u0026rsquo;s guesses (𝜒2 (1, N = 85) = 143.74, \u003cem\u003ep\u003c/em\u003e \u0026lt; .000), meaning that participants were significantly more likely to correctly identify Non-Art images as made by people who sell products than Art images as made by professional artists (Figure 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTogether, the findings reported so far show that both contextual framing (Condition) and whether an image depicts a ready-made artwork (Image Type) independently influence region-specific embodied responses (Body Part), but do not interact with each other. Specifically, the Mixed condition was associated with more polarised embodiment patterns between the Head and Lower Limbs, while Art images elicited higher Embodiment Scores than Not Art images in the Head and Abdomen. In the Mixed condition, where instructions did not invite participants to adopt a specific cognitive stance, participants were significantly better at identifying Not Art images than Art images, suggesting greater ambiguity in identifying artistic representations of everyday objects as artworks. Finally, the model revealed substantial variability in random effects associated with image identity, suggesting that embodiment responses may have been influenced by the everyday activities typically associated with the depicted objects (e.g., shirt with dressing, fork with eating). To account for this, we further explored whether different activities moderated BSMs embodiment patterns across Conditions and Image Type.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExploratory Cluster Analysis to Assess the Impact of Specific Activities at Group Level\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe ran an exploratory analysis to investigate whether the colour patterns of the BSMs constituted clusters. We used the \u003cem\u003epatternize\u003c/em\u003e\u003csup\u003e46\u003c/sup\u003e, \u003cem\u003erecolorize\u0026nbsp;\u003c/em\u003e\u003csup\u003e47\u003c/sup\u003e and \u003cem\u003ecolordistance\u003c/em\u003e\u003csup\u003e48,49\u003c/sup\u003e R package to generate a distance matrix of colour similarity for the BSMs across experimental condition and activity. This approach was inspired by the workflow proposed by Weller and the parameters selected by Schino et al. \u003csup\u003e50\u003c/sup\u003e for the processing of BSMs data. Namely, the parameters are: standard red-green-blue (RGB) color space format, k-means clustering binning method, and Earth Mover\u0026rsquo;s Distance (EMD) as a measure of distance/dissimilarity \u003csup\u003e51\u003c/sup\u003e. The analysis aimed to group images with similar colour palettes, assessing whether the resulting clusters represented the most visually similar BSMs. Descriptive statistics for total number of pixels counted by body region, respectively associated with activations and deactivations colours, alongside Embodiment Score according to Regions of Interest, Condition and Image Type are reported in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eDescriptive statistics for three measures across Regions of Interest (Head, Chest, Abdomen, Upper Limbs, and Lower Limbs), experimental Conditions (Mixed, Museum, Commercial), and Image Types (Art, Not Art). The first two measures\u0026mdash;Activations (pixel count) and Deactivations (pixel count)\u0026mdash;reflect the total number of pixels associated with activation (red) and deactivation (blue) areas in the BSMs, as identified by our custom image-processing code. The third measure, Embodiment Score (log-transformed), was derived from participants\u0026rsquo; click responses and reflects the relative intensity of embodied sensations in each region. Activations are shown in shades of red, Deactivations in blue, Embodiment Score in purple, and Regions of Interest in grey.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"644\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\" style=\"width: 497px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRegions of Interest\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eHead\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eChest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eAbdomen\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eUpper Limbs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eLower Limbs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCondition\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eImage Type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eActivations (pixel count)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eActivations (pixel count)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eActivations (pixel count)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eActivations (pixel count)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eActivations (pixel count)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003eArt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e68537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e214584\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e124412\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e180877\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e48816\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003eNot-Art\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e78417\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e193070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e79605\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e176383\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e19387\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eMuseum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003eArt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e73038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e143357\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e82397\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e99211\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e75781\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eMuseum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003eNot-Art\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e78908\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e170167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e53196\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e125969\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e26243\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eCommercial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003eArt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e75586\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e127387\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e78943\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e158047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e60565\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eCommercial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003eNot-Art\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e76069\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e189065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e29478\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e159549\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e19784\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDeactivations (pixel count)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDeactivations (pixel count)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDeactivations (pixel count)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDeactivations (pixel count)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDeactivations (pixel count)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003eArt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e6263\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e56686\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e64568\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e234821\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e290033\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003eNot-Art\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e52489\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e110856\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e223363\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e303518\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eMuseum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003eArt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e4729\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e112273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e93230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e179431\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e266045\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eMuseum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003eNot-Art\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e7915\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e89685\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e138425\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e197192\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e294923\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eCommercial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003eArt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e89107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e98911\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e221110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e293526\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eCommercial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003eNot-Art\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e4854\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e61990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e152015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e210166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e324220\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmbodiment Score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmbodiment Score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmbodiment Score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmbodiment Score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmbodiment Score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003eArt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0,38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0,09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0,08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0,15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e-0,26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003eNot-Art\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0,31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0,17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e-0,01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0,19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e-0,22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eMuseum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003eArt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0,42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0,12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0,13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0,14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e-0,20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eMuseum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003eNot-Art\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0,29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0,15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0,01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0,22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e-0,14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eCommercial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003eArt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0,36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0,08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0,10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0,15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e-0,25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eCommercial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 63px;\"\u003e\n \u003cp\u003eNot-Art\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0,27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0,12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e-0,04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0,19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003e-0,15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eUsing a colour distance matrix generated with the \u003cem\u003ecolordistance\u003c/em\u003e R package (see Figure S1), we visualised pairwise similarity between BSM images as a heatmap. Lower distance values\u0026mdash;represented by darker blue tones\u0026mdash;indicate higher similarity between images, whereas higher distance values\u0026mdash;represented by brighter pink tones\u0026mdash;indicate lower similarity (or greater dissimilarity). To complement these results, we qualitatively inspected the hierarchical clustering of BSMs (see Figure S2), using the resulting dendrogram to explore potential recurring embodiment patterns and inform our diagnostic approach for the formal statistical analysis.\u003c/p\u003e\n\u003cp\u003eWe observed that BSMs corresponding to the same activity in the Museum and Commercial conditions tend to show low colour distances, indicating a high degree of similarity in embodiment patterns across these two contexts. For example, the distance between the BSM generated for the Art image associated with the activity of dressing in Museum and Commercial conditions is very low (EMD\u0026nbsp;\u0026cong;\u0026nbsp;0.11; see Figure S1). This suggests that, despite the different expectations induced by the two contextual information (Museum\u0026nbsp;\u003cem\u003evs\u003c/em\u003e Commercial), the same activity tends to evoke similar BSMs for Art images associated with the activity of dressing. Similarly, Not-Art images associated with the same activity result in BSMs that cluster close together.\u003c/p\u003e\n\u003cp\u003eHowever, when comparing Art and Not-Art images depicting objects associated with the same activity, we can observe a different pattern of results. As can be seen in Figure 3, for activities such as \u0026lsquo;watching media\u0026rsquo; and \u0026lsquo;walking\u0026rsquo; the difference between BSMs varies depending on whether or not the image is Art or Not-Art. In these cases, the Image Type seems to be critical in inducing different patterns of bodily activity. For example, Art images depicting objects associated with \u0026lsquo;walking\u0026rsquo; clearly evoked higher deactivations in the Lower Limbs region than Not-Art images did, in line with the results predicted by the models. Similarly, Art images connected to the activities of \u0026lsquo;watching media\u0026rsquo; and \u0026lsquo;eating\u0026rsquo; generated unique BSMs that were more distinct than those generated by Not-Art images associated with the same activities. Notably, BSMs generated in response to Art images related to activities like \u0026lsquo;reading\u0026rsquo; in both the Museum and Commercial conditions consistently appeared distinct from BSMs for other activities. Art images depicting everyday objects associated with the activity of \u0026lsquo;reading\u0026rsquo; in both the Museum and Commercial conditions generated BSMs that showed high dissimilarity scores (EMD \u0026gt; 0.35) compared to most other activities, indicating a unique bodily activation pattern for this activity and Image Type.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study investigated how experimentally-induced expectations about the artistic status (Condition) of everyday objects influence self-reported embodiment activity, while accounting for whether the images were actually from art institutions or commercial websites (Image Type). When examining the role of experimentally-induced expectations, we found that the difference in Embodiment Scores between the Head and Lower Limbs was significantly smaller in the Commercial and Museum conditions compared to the Mixed condition. Most notably, the Museum condition reported significantly less deactivation in the Lower Limbs than the Mixed condition did. When assessing the role of image type, results showed that Art and Not-Art images had a significant and clear impact on self-reported embodiment activity in different body regions regardless of the everyday object depicted. Specifically, Art images reported significantly more activity in the Head and Abdomen, as well as significantly less activity in Chest, Lower Limbs and Upper Limbs areas than Not-Art images did. Considering that our results did not reveal a significant interaction between contextual information (Mixed \u003cem\u003evs\u003c/em\u003e Museum \u003cem\u003evs\u003c/em\u003e Commercial) and image type (Art \u003cem\u003evs\u003c/em\u003e Not-art) on Embodiment Score, and that participants were not more likely to recognise Art images as professionally produced, our findings suggest that the artistic depiction of everyday objects and viewers’ expectations each play important yet distinct roles in our embodied experience of art encounters.\u003c/p\u003e\n\u003cp\u003eOne of the key contributions of the present study is our improved approach to BSMs analysis, which enabled us to unveil and better quantify colour pattern variations across relevant experimental variables. Cluster analysis on BSMs revealed that the nature of the image and the activity associated with the everyday objects depicted in it played a critical role in shaping embodiment patterns. For activities such as ‘watching media’, ‘working’, and ‘sleeping’, which typically involve a seated posture or minimal engagement of the Lower Limbs, participants reported less Lower Limb deactivation when viewing Art images than when viewing Not-Art images. To better understand these findings, we will take a closer look at the images associated with the activity of ‘watching media’. In our dataset, both image types depicted a TV screen—the Art image showed a screen positioned on a tall plinth against a plain white wall, while the Not-Art image showed a flat TV screen on a low cabinet with storage shelves in a modern living-room interior. The BSM embodiment patterns for the ‘watching media’ Art image revealed higher activations at the level of the Lower Limbs than the Not-Art image did. Conversely, the Not-Art image elicited strong activations in the Head area that were absent from the Art image’s BSMs. There are two important insights to draw from these findings. First: the complex and nuanced pattern of results that emerged from the cluster analysis highlights how individual activities (like ‘watching media’) display characteristic activation patterns that are deviations from and sometimes opposite to the global trend. Second: the recurring clustering of BSM according to image type suggests that Art images depicting everyday objects may reduce sensations typically associated with the functional affordances of those objects and may elicit bodily responses distinct from Non-Art images depicting the same objects.\u003c/p\u003e\n\u003cp\u003eAs was the case for image type, we found that individual activities also played an important role in shaping BSM embodiment patterns for the different conditions. For example, when analysing an utilitarian activity like ‘eating’, image cluster analysis revealed that Not-Art images showed more activations at the level of the Head (i.e. mouth and throat areas) in the Commercial condition compared to the Museum and Mixed conditions. At the same time, Art images clustered together in a separate location, showing an increased activity both at the level of the Head and Abdomen across all conditions. Taken together these results demonstrate the need to assess BSMs in terms of activation patterns across the whole body to reveal more meaningful, richer and generalisable insights.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe can interpret these findings to indicate that images of ready-made artworks have been deliberately created by art professionals to disrupt the typical functional associations the viewer makes with everyday objects, therefore eliciting less functionally driven bodily sensations. Critically, the results showing diversified embodiment patterns for Art and Not-Art images aligns with predictions from embodied simulation theory \u003csup\u003e52\u003c/sup\u003e, which predicts that art can transform or subvert ordinary affordances by eliciting bodily responses that differ from those elicited by more functionally oriented depictions. We can therefore speculate that when engaging with ready-made artworks, we temporarily distance ourselves from everyday tasks, creating more space for our mental simulation processes to engage in less utilitarian affordances and bodily sensations. Overall, our pioneering approach to BSMs contributes to a better understanding of how context-driven expectations and images of ready-made art shape bodily responses.\u003c/p\u003e\n\u003cp\u003eFinally, a key contribution of this study is our decision and effort to make the R code for visualising and analyzing BSMs openly available to the research community. In doing so, we aim to enhance accessibility, transparency, and reproducibility to facilitate cross-study comparisons, and encourage broader adoption of BSM methods across disciplines.\u003c/p\u003e\n\u003cp\u003eThe use of the BSMs has represented an interdisciplinary method of investigation, since body mapping was used for the exploration of all art forms by Violet Paget (‘Vernon Lee’) and Clementina Anstruther-Thomson during excursions at museums and galleries \u003csup\u003e53\u003c/sup\u003e. Paget and Anstruther-Thomson claimed that embodied experiences and bodily sensations are the factors that give rise to mental impressions of beauty or feelings of pleasure (not the other way around), echoing the principles of embodied cognition framework. We demonstrate that BSMs serve as more than visually appealing graphics; they are computationally efficient and enable rapid data processing. This enhances our ability to understand, explore, and compare art experiences holistically in both quantitative and qualitative terms. However, when data volume grows, the overplotting that results may lead to overlapping points obscuring underlying relationships. In such cases, the interpretability of results may diminish. Hence, the importance of our preprocessing approach that computes the differences between activations and deactivations to mitigate this effect. An additional limitation of our study is the potential stimulus set effect \u003csup\u003e54,55\u003c/sup\u003e. It is possible that our reliance on a specific set of everyday-object images, although sourced from both art institutions and commercial websites, might restrict the generalisability of our findings, as the limited variability in stimulus types could have influenced participants’ embodiment responses.\u003c/p\u003e\n\u003cp\u003eBy revealing how subtle shifts in context and perception shape the way our bodies respond to everyday objects, this study not only advances our understanding of embodied aesthetics, but also lays the groundwork for a more reproducible and interdisciplinary science of felt experience.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eAll studies described in this paper were approved by the University of St Andrews School of Psychology \u0026amp; Neuroscience Ethics Committee (approval code PS16674), in accordance with the University\u0026rsquo;s Principles of Good Research Conduct (https://www.st-andrews.ac.uk/policy/research-conduct-and-ethics/principles-of-good-research-conduct-policy.pdf) and fully account for ethical issues related to research involving humans. Informed consent was obtained from all participants prior to taking part in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants were recruited on Prolific (www.prolific.com), a platform for online research. To ensure high quality data, the study had the following selection criteria: Participants had to (1) be fluent in English and (2) have at least an 80% success rate of experiment completion. The study was developed on Qualtrics, an online software for conducting psychological studies (www.qualtrics.com).\u003c/p\u003e\n\u003cp\u003eA total of 277 participants took part in the study. Twelve participants were excluded from the final analysis due to poor data quality (e.g., no clicks reported on body silhouettes) or failure to pass all attention checks, resulting in a final sample of 265 participants (\u003cem\u003eM\u003csub\u003eage\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e= 40.11, \u003cem\u003eSD\u003c/em\u003e = 13.85; 89 women, 172 men, 2 non-binary and 2 preferred not to report their gender).\u003c/p\u003e\n\u003cp\u003eAs recommended by Atari, Davani \u0026amp; Dehghani and Nummenmaa and colleagues, studies exploring self-reported bodily sensations should ideally recruit at least 40 participants per group to ensure adequate statistical power \u003csup\u003e33,35\u003c/sup\u003e. Similar studies conducted with the use of BSMs estimated approximately a similar number of participants taking part in the experiments \u003csup\u003e37,56\u003c/sup\u003e. Therefore, we aimed at having at least 40 participants per condition. Participants were randomly assigned to one of the three experimental Conditions: Museum (\u003cem\u003en\u003c/em\u003e = 92), Commercial (\u003cem\u003en\u003c/em\u003e = 93), and Mixed (\u003cem\u003en\u003c/em\u003e = 92). After exclusions, 89, 91, and 85 participants were retained in each group, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStimuli Selection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe aimed to select a set of objects that people frequently associate with daily activities. To this end, we conducted a pilot study, recruiting 40 participants on Prolific (\u003cem\u003eM\u003csub\u003eage\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e= 42.05, \u003cem\u003eSD\u003c/em\u003e = 13.66; 27 women and 13 men) who did not take part in the main study. Participants were asked to describe activities they perform on a daily basis and the objects they associate with these activities (e.g., drinking: cup). Overall, participants mentioned 25 activities and 536 objects (for the full list of activities, objects and their frequencies, please refer to Table 3S in the Supplementary Information). Based on the results, the most frequent activities were: eating, walking, sleeping, working, showering, dressing, watching media, drinking, reading, cleaning and observing. Previous studies \u003csup\u003e42,43\u003c/sup\u003e found that when participants viewed visual art, their BSMs showed increased activation in the head region, a result interpreted as linked to the act of observing. Therefore, we decided to include objects associated with the activity of observation in our stimuli selection to help determine whether head-level activation is linked to contextual information (i.e., whether it is consistently reported across all BSMs regardless of the activity associated with the object depicted in the image or whether it varies according to the expectations shaped by the set of instructions given to the participant).\u003c/p\u003e\n\u003cp\u003eWe then selected the objects most commonly associated with specific everyday activities, such as a shirt for dressing and a coffee cup for drinking. For each activity, we selected pairs of images depicting the same object: one sourced from art institution websites (Image Type: Art) and the other from popular commercial sites that sell new and used goods online, such as eBay (Image Type: Not-Art). The final image set consisted of 68 images in total, representing 34 objects, each depicted by both Art and Not-Art image type. We provide the full list of images, including the depicted objects, corresponding activity, image type (Art \u003cem\u003evs\u003c/em\u003e Not-Art) and website source in Table S1 in the Supplementary Information.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExperimental Procedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants were randomly assigned to one of the three experimental conditions: Museum, Commercial, or Mixed (see Figure 4). Each condition was designed to induce a specific cognitive stance by providing participants with a distinct set of instructions. The instructions were presented at the beginning of the study, with the aim of shaping participants\u0026apos; expectations regarding the images they would see during the course of the experiment (see Table S4 in the Supplementary Information for the original instructions provided in each experimental condition).\u003c/p\u003e\n\u003cp\u003eImmediately after receiving the instructions, the trials began (see Figure 5). Each image was displayed on-screen for 5 seconds, accompanied by the following text: \u0026lsquo;Look at this picture and think carefully about your body sensations while viewing it.\u0026rsquo; Each participant saw 34 images in total, with objects counterbalanced by image type (17 Art and 17 Non-Art) and images presented in a random order. The design ensured that each participant saw all 34 objects, and avoided presenting both image types of the same object.\u003c/p\u003e\n\u003cp\u003eParticipants were then asked to report their bodily sensations by using two body silhouettes: one for activations (stronger sensations, more energy) and another for deactivations (weaker sensations, less energy). There was no time limit for this task. Participants were informed that they could click up to 10 times and were encouraged to use multiple clicks to emphasise more significant activation or deactivation in a specific body area (see Figure 5).\u003c/p\u003e\n\u003cp\u003eAfter seeing each image and reporting their bodily sensations, only participants in the Mixed condition were additionally asked to assess who they thought created the image. They could choose between two options: (1) professional artists or (2) people who sell products.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch1\u003eData availability\u003c/h1\u003e\n\u003cp\u003eConsidering that some of the stimuli used in \u0026lsquo;Ready-Made Bodily Sensations\u0026rsquo; are protected by copyright, we provide the full list of images selected for the study, relevant image information and the related source link in Table S1. The data and analysis code that support the findings of this study are openly available at: https://osf.io/bke9q/?view_only=5d9f2c577d3f417db1abc1486e7cb776\u0026nbsp;\u003c/p\u003e\n\u003ch1\u003eAcknowledgements\u003c/h1\u003e\n\u003cp\u003eThis work was supported by the Templeton Religion Trust, TRT-2021-10512, awarded to Brendan Wolfe. The authors would like to thank Karlee Bowlby for proofing the manuscript.\u003c/p\u003e\n\u003ch1\u003eAuthor contributions statement\u003c/h1\u003e\n\u003cp\u003eN.R. \u0026amp; M.I. conceived the study, N.R., G.S. \u0026amp; M.I. contributed to the experimental design and B.W. secured the funding to support the study. M.I. conducted the pilot study and image selection, while G.S. \u0026amp; N.R. developed the Qualtrics survey. N.R., G.S. \u0026amp; M.I. analysed the data. N.R. \u0026amp; G.S. developed the new open-access R code to visualise BSM (‘BSM Visualisations 2025.R’) and N.R. \u0026amp; M.I. developed the code to identify body regions and count pixels from the BSM images (‘BSM ROI Finder 2025.R’). G.S. exported the BSM images and ran the cluster analysis. NR, GS, \u0026amp; MI contributed to the development of the initial version of the manuscript and BW provided critical feedback and helped shape the final manuscript.\u003c/p\u003e\n\u003ch1\u003eAdditional information\u003c/h1\u003e\n\u003cp\u003eWe have no known conflict of interest to disclose.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChatterjee, A. The neuropsychology of visual artistic production. \u003cem\u003eNeuropsychologia \u003c/em\u003e\u003cstrong\u003e42\u003c/strong\u003e, 1568\u0026ndash;1583 (2004).\u003c/li\u003e\n\u003cli\u003eFreedberg, D. \u0026amp; Gallese, V. Motion, emotion and empathy in esthetic experience. \u003cem\u003eTrends in Cognitive Sciences \u003c/em\u003e\u003cstrong\u003e11\u003c/strong\u003e, 197\u0026ndash;203 (2007).\u003c/li\u003e\n\u003cli\u003eBreton, A. \u0026amp; Duchamp, M. \u003cem\u003eLe Surr\u0026eacute;alisme en 1947\u003c/em\u003e. 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J. \u003cem\u003eet al.\u003c/em\u003e Anomalous Bodily Maps of Emotions in Schizophrenia. \u003cem\u003eSchizophr Bull \u003c/em\u003e\u003cstrong\u003e45\u003c/strong\u003e, 1060\u0026ndash;1067 (2019).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6429051/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6429051/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Embodiment plays an important role in art engagement, yet it is unclear how expectations shape bodily sensations, especially when interacting with ready-made art. In this study, we investigated how expectations and the nature of images of everyday objects affect bodily sensations. We tested if bodily sensations changed depending on (1) whether the participants were told that everyday objects were from a Museum, Commercial or Mixed context and (2) the nature of the images, counterbalancing whether they were of ready-made art or not. To measure bodily sensations, we asked participants to self-report their feelings of activity getting stronger (activations) or weaker (deactivations) in their body by clicking on body silhouettes after viewing the images, a methodology called bodily sensation mapping (BSM). We found that bodily activity in the Chest and Upper Limbs areas was influenced by expectations induced by context only. At the same time, Head and Abdomen activations and Chest, Lower and Upper Libs deactivations were solely impacted by the image type. Our innovative approach to BSMs image analysis revealed how both context and image type were influenced by the activity type, contributing and enriching the ongoing debate regarding the uniqueness of art experiences and aesthetic cognition.","manuscriptTitle":"Ready-Made Bodily Sensations","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-03 07:51:00","doi":"10.21203/rs.3.rs-6429051/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-06-16T10:30:20+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-14T18:25:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-10T13:33:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"224966298373438372253538485217725099191","date":"2025-06-05T09:06:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"102303658013021737128139613212702378656","date":"2025-05-30T10:08:24+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-30T09:50:54+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-19T09:39:35+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-04-23T17:43:34+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-23T04:06:49+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-04-11T14:00:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1d5aaade-9447-4b49-80a1-fcceaffcc0cf","owner":[],"postedDate":"June 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":49281818,"name":"Biological sciences/Psychology"},{"id":49281819,"name":"Biological sciences/Psychology/Human behaviour"}],"tags":[],"updatedAt":"2025-08-25T16:36:06+00:00","versionOfRecord":{"articleIdentity":"rs-6429051","link":"https://doi.org/10.1038/s41598-025-14061-5","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-08-18 16:29:31","publishedOnDateReadable":"August 18th, 2025"},"versionCreatedAt":"2025-06-03 07:51:00","video":"","vorDoi":"10.1038/s41598-025-14061-5","vorDoiUrl":"https://doi.org/10.1038/s41598-025-14061-5","workflowStages":[]},"version":"v1","identity":"rs-6429051","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6429051","identity":"rs-6429051","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}