1 Looking, liking and locating: an experimental of orienting 2 3 Mariana Babo-Rebelo, Eoin Travers, Patrick Haggard 4 Institute of Cognitive , University College London 5 6 Corresponding author: Mariana Babo-Rebelo ([email protected]) 7 8 9 10 11 12 13 14 Author contributions 15 MBR and PH designed the study. MBR and ET programmed the study. MBR, ET and PH 16 analyzed the data and wrote the paper. 17 18 19

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20 Abstract 21 Memory for object location has been extensively studied, but little is known about the role 22 of subjective evaluation of objects. We investigated how aesthetic could incidentally 23 modulate memory of location. 96 participants (86 tested at science festivals, 10 at the laboratory) 24 visited a virtual museum, not knowing they would later be tested on spatial memory. Afterwards, 25 they reported how much they liked each painting, and located it on the museum map. Participants 26 remembered better the location of paintings that created strong aesthetic , whether 27 positive or negative, suggesting an arousal effect. Liking a painting increased the ability to recall 28 on which wall the painting was hung. Since recalling the wall requires recalling heading direction, 29 this finding suggests positive aesthetic experience enhances first-person spatial representations. 30 Aesthetic experience of stimuli can shape the cognitive map. These results may have implications 31 for museum design. 32 33 34 Statement of significance 35 Remembering a seen object often involves remembering its location. How is this 36 influenced by the experience we have of the object? We investigated the particular case of 37 aesthetic experience in a museum setting. How do we remember the location of paintings we saw? 38 Is this influenced by our aesthetic experience? We here show that we can remember the location 39 of paintings that created a strong aesthetic experience, whether positive or negative, even if we 40 were not paying attention to their spatial locations while visiting the museum. Moreover, liking a 41 painting enhances a first-person representation of space. These results reveal that aesthetic 42 experience is incidentally accompanied by a representation of the surrounding space. Our 43 memory of object locations is thus shaped by our experience of these objects, even when there is 44 no direct link with survival behaviors. The resulting individual shaping of spatial maps may have 45 important implications for museum design. 46 47 Acknowledgments 48 MBR was funded by a Fyssen Foundation post-doctoral grant. ET was funded by a 49 Leverhulme Trust Research Project grant to PH (RPG-2016-378). The authors thank the team who 50 helped with data collection (Antonio Cataldo, Damiano Azzalini, David Wurzer, Davide Bono, 51 Elisabeth Parés-Pujolràs, Gaiqing Kong, Irena Arslanova, Ivan Ezquerra Romano, Karla Matic, 52 Michael Clements), the organizers of the festivals (Tate Modern ‘Moving Humans’ festival: 53 organized by the Institute of Philosophy and funded by the AHRC Science in Culture theme; UCL 54 ‘It’s All Academic Festival’), and Andrej Bicanski, Nathalie George and Aina Puce for helpful 55 discussion.

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56 Introduction 57 58 Perceiving an object in the world is an experience defined in space and time, and 59 stored in memory with this contextual information. Memory for object-location 60 associations has been extensively studied in the spatial cognition literature (Eichenbaum, 61 2017; Epstein et al., 2017; Manns & Eichenbaum, 2009; Postma et al., 2008), but little is 62 known about the interplay between subjective aspects of experience and spatial 63 representation. We here investigated how aesthetic experience of an object affects the 64 representation of that object’s spatial location. 65 Previous studies link affect to spatial memory in animals (Moita et al., 2003; 66 Wystrach et al., 2020) and humans. For example, spatial context of emotional and 67 arousing stimuli, such as emotional words (D’Argembeau & Van der Linden, 2004; 68 MacKay & Ahmetzanov, 2005) or pictures (Mather & Nesmith, 2008; Schmidt et al., 2011), 69 is better recalled than for neutral stimuli. Similar results were obtained in 3D 70 environments, where emotional landmarks improved spatial memory (Balaban et al., 71 2017; Brunyé et al., 2009; Chan et al., 2012, p. 201; Palmiero & Piccardi, 2017; Ruotolo et 72 al., 2019). However, these tasks generally instructed participants to attend to space and 73 considered objects as landmarks. Little is known about incidental spatial encoding during 74 navigation, and how it might be influenced by the experience of objects encountered en 75 route. 76 We tested these questions using an onscreen virtual museum as a setting (Fig. 1a). 77 Museums provide an interesting setting for studying the interplay between experience 78 and spatial representation, because they implicitly impose spatial constraints on aesthetic 79 experience. The gallery space needs to be navigated even if not attended to, and specific 80 aesthetic experiences are clearly linked to the spatial location of the displayed objects. 81 In this , participants visited a museum, either actively leading the visit, 82 or passively following another visitor, with the sole instruction of evaluating the works of 83 art that they saw (i.e., aesthetic attitude, (Leder et al., 2015)). Afterwards, participants 84 were represented with the paintings, reported their liking for them, and recalled their 85 location on the museum map (Fig. 1b). 86 We investigated the cognitive mechanisms linking aesthetic experience of a 87 painting to memory for its location. Drawing on Osgood’s “semantic differential” approach 88 (Snider & Osgood, 1969), we considered two cardinal aspects dominating aesthetic

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89 experience: the participants’ liking for each painting (valence) and the intensity of 90 experience independent of valence (potency). A third aspect of Osgood’s theory, namely 91 the extent to which an object implies agency is less relevant here. We also distinguished 92 two different aspects of the museum’s spatial environment (Fig. 1a), e.g. exhibition rooms 93 (first to fourth) and hanging walls (left, front or right wall relative to the entrance door) 94 (Marchette et al., 2014). We considered that these are associated with two distinct ways 95 of remembering spatial locations. Correctly reporting the room where a painting was 96 displayed involves recalling the ordinal location of the painting within the progressive 97 sequence of the visit, e.g. first room, second room etc. This might correspond to a count- 98 based or travel-based representation of space. Conversely, recalling whether a painting 99 appeared on the left, front or right wall involves accessing first-person perspective 100 heading information relative to the local environment. We therefore looked at how 101 aesthetic experience could explain memory for the room location or wall location of 102 paintings. 103 104

105 106 Fig. 1. Museum setting and paradigm. a, Museum map and view of the environment. The 107 virtual museum was composed of four successive exhibition rooms with 3 paintings, one on the left, 108 one on the front and one on the right wall relative to the entrance door. b, Paradigm. After the visit, 109 participants complete the test, where the 12 paintings and 3 catch are presented. Participants report 110 whether they had previously seen the painting or not. If they respond ‘yes’, they rate their liking of 111 the painting (‘Liking ratings’), and then drag and drop the painting to its location in the museum 112 map (‘Spatial memory task’). 113 114

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115 Method 116 117 Participants 118 134 participants volunteered to take part in this study, in three different contexts: 119 at the laboratory (n=10), at a neuroscience festival at the Tate Modern museum in London 120 (n=87), and at a science festival at University College London (n=37). 34 participants were 121 excluded at the time of testing, due to difficulties with navigation, major distractions 122 during task performance or interference from audience. Four participants were excluded 123 at the memory screening stage, recognizing less than 33% of paintings previously seen. 124 96 participants were included in the main analyses (Supplementary Table; gender: 46 125 males, 45 females, 5 preferred not to answer; age: mean = 35.4, SD = 14.7, min = 9, max = 126 72). We did not set a minimal sample size for this study, as the experiment was designed 127 to be tested with large numbers of participants at public events. The following analyses 128 were performed once the whole dataset had been collected. All procedures were 129 approved by the appropriate local ethics committee for the data collection setting. 130 131 The virtual environment 132 The virtual environment consisted of a museum, composed successively of an 133 entrance room, four exhibition rooms and an exit room. Rooms were separated by doors. 134 We created three types of exhibition rooms, which differed depending on the position of 135 the exit door: the exit door could be on the right wall as one entered the exhibition room, 136 on the wall in front of the entrance door, or there could be two exit doors on the wall in 137 front of the entrance door1. We created 6 different layouts for the museum as a whole 138 (Supplementary Fig. 1), resulting from the concatenation of four of these exhibition rooms 139 in different order. Each exhibition room presented three paintings, one on the left wall, 140 one on the front wall, and one on the right wall relative to the entrance door. We collected 141 a total of 15 abstract paintings. Twelve paintings were presented in each museum, 142 randomized between museums, and in randomized rooms and walls. 143 The virtual environment was implemented with Unity (version 2019.1.10f1, Unity 144 Technologies, CA, USA). The paintings and objects were taken from the asset “Art Gallery 145 Showroom” by 3dfactorio

1 The two doors could lead to the same room or to two different rooms – only for the version used at the Tate Modern festival. 5

146 (https://assetstore.unity.com/packages/3d/environments/art-gallery-showroom- 147 141559#description, paintings free for use extracted from Unsplash.com). Participants 148 navigated using the W, A, S and D keys of the keyboard (to move forward, leftward, 149 backward and rightward respectively) and the mouse to rotate the view (left-right). Doors 150 could open automatically or by pressing the space bar on the keyboard, once the 151 participant was close enough. A first-person perspective and a head bobbing effect during 152 navigation were used to improve immersiveness, and the field-of-view was 60° vertically 153 and 133° horizontally. 154 155 Task and procedure 156 Participants first navigated the virtual museum, on a computer screen. They were 157 given unlimited time to complete the visit. They were instructed to simply view all the 158 paintings and attend to how much they liked each of them. The visit started in the 159 entrance room, where participants could practice the use of the navigation keys. The visit 160 ended once they reached the exit room. Returning to rooms already visited was not 161 possible. 162 Next, participants completed a computerized test where they were successively 163 presented with 15 paintings (the 12 paintings they had viewed in the museum, plus 3 new 164 ‘catch’ paintings) in randomized order. For each painting, they were asked whether they 165 had seen the painting in the museum or not. If they indicated that they recognized the 166 painting, participants reported how much they liked the painting using a VAS scale 167 (labelled “I hated it” on the left, and “I loved it” on the right). They then placed the painting 168 on the museum map, in the location where they remembered seeing it. 169 Two participants could visit the museum simultaneously, one being the leader and 170 the other the follower. The leader controlled navigation, while the follower simply 171 watched the museum visit on a second screen, facing the leader. Both participants then 172 completed the test separately. Participants could talk during the museum visit, but not 173 while completing the test. 174 175 Data analysis 176 To measure aesthetic experience, we considered liking and intensity ratings. 177 Intensity ratings corresponded to squared liking ratings. This operation suppresses 178 signed valence while emphasizing extreme reactions on our scale. We scored spatial

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179 memory performance for each recognized painting, according to two spatial criteria: 180 correct/incorrect choice of room, and correct/incorrect choice of wall (left, front or right 181 relative to the entrance door of the exhibition room). Catch trials were excluded. We fitted 182 logistic mixed effects models to look at which aspects of aesthetic experience could 183 predict room and/or wall memory. We computed one mixed model for each spatial 184 criterion using the following predictors: liking ratings (z-scored across paintings for each 185 participant, to account for inter-individual variability in the use of the liking scale), 186 aesthetic experience intensity (z-scored liking ratings squared), and the participant’s role 187 (leader or follower). Preliminary analyses (see Supplementary Materials) indicated 188 effects of gender, room number, wall number and room type on spatial recall. To control 189 for these effects, we included these variables as covariates. The intercept in these models 190 was allowed to vary between participants as a random effect. We also tested these models 191 with random effects of acquisition context (Tate festival, UCL festival or laboratory) on 192 the intercept, but the corresponding variance being negligible (<1e-7) we excluded this 193 random factor, and simply pooled across testing sites. 194 We performed two additional analyses to further characterize the effects of 195 aesthetic experience intensity and liking. We computed the same model as before but 196 using correct/incorrect exact location as the binary outcome (correct exact location: both 197 room and wall are correct), to test if the effect of intensity predicted memory for the exact 198 location of paintings. To show that the effect of liking on memory for walls is independent 199 from room performance, we computed the same initial model, but including as an 200 additional predictor correct/incorrect room responses. 201 These analyses were conducted in R, using the “glmer” function from the lme4 202 package (Bates et al., 2014) to compute mixed effects models, and the “Anova” function 203 from the car package (Fox & Weisberg, 2019) to derive corresponding statistics (Type II 204 Wald chi-square tests). We report logistic regression weights as our unstandardised effect 205 size estimates, as they correspond to the expected change in log-odds for a one-unit 206 increase in the corresponding predictor value. 207 208

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209 Results 210 211 Overall accuracy for rooms and walls on the spatial memory task 212 For each trial of the spatial memory task, we looked at whether participants placed 213 the painting in the correct room and/or the correct wall. Participants were above chance 214 at recalling the rooms where paintings were presented (Fig. 2a, chance level = 25%, mean 215 correct = 45.04%, SD=21.32, one sample t-test against chance level: t(95)=9.21, p<0.001), 216 with an advantage for the first room of the gallery (Fig. 2b; see Supplementary Materials). 217 They were also above chance at choosing the hanging wall (Fig. 2a, chance level = 33%, 218 mean correct = 57.16%, SD=23.83, t(95)=9.80, p<0.001), the front wall being associated 219 with worse memory performance than the lateral walls (Fig. 2b; see Supplementary 220 Materials). On average, participants reported the exact location of 30.28% of the paintings 221 (Table 1). 222

223 224 Fig. 2. Performance on the spatial memory task. a, Average percentage of correct responses 225 for each spatial criterion: room and wall. Each dot represents a subject. The green diamond 226 represents the average performances across subjects. The dotted lines correspond to chance level for 227 rooms (horizontal) and for walls (vertical). The density plots represent the distribution of 228 performance across subjects, for rooms (right density top plot) and for walls (top density plot). b, 229 Response pattern on the spatial map task, for rooms and walls. The matrix on the left shows, for each 230 room (first to fourth, each row), the average percentage of responses given for each of the four 231 possible rooms (columns). The matrix on the right shows, for each wall (left, front or right, each row), 232 the average percentage of responses given for each of the three possible walls (columns). Diagonals 233 from bottom left to top right represent correct responses. Below chance level values are in blue; 234 above chance level values are in green; chance level values are in white. The museum maps show the 235 scoring for rooms (1 to 4) and for walls (L: left, F: front, R: right, Entr: entrance room). 236

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Room correct Room incorrect 30.28% ± 21.40 26.88% ± 15.95 Wall correct Chance: 8.33% Chance: 25% 14.75% ± 14.69 28.09% ± 20.98 Wall incorrect Chance: 16.67% Chance: 50% 237 238 Table 1. Percentage correct and incorrect responses for rooms and walls (average 239 percentage correct ± SD). Chance level is indicated for each case. 240 241 Aesthetic factors predicting spatial memory 242 We defined two cardinal aspects of aesthetic experience: participants’ liking or 243 disliking of each painting (obtained directly from their VAS subjective ratings), and the 244 intensity of the aesthetic experience, irrespective of its valence (obtained by squaring the 245 VAS ratings). Average liking ratings were variable between participants, as might be 246 expected (Fig. 3a, see Supplementary Materials). We looked at how liking and intensity 247 could predict memory for rooms and for walls. We controlled for inter-individual 248 (gender) and spatial factors (room number, wall number and room type) shown in 249 preliminary analyses to modulate spatial memory (see Supplementary Materials). 250 Memory for rooms was significantly explained by the intensity of the aesthetic 251 experience, but not by liking (Fig. 3b, Intensity: b= 0.19, SE=0.081, X2(1)=5.38, p=0.020; 252 Liking: b=0.098, SE=0.086, X2(1)=1.31, p=0.25). This suggests that intense aesthetic 253 experience led to a better recollection of the room where paintings were presented. In 254 turn, memory for walls was significantly explained by both intensity and by liking (Fig. 3c, 255 Intensity: b=0.30, SE=0.093, X2(1)=10.78, p=0.0010; Liking: b=0.26, SE=0.095, 256 X2(1)=7.44, p=0.0064). More intense and more positive aesthetic experiences improved 257 recollection of the wall where paintings were hung. Whether participants performed the 258 experiment as leaders or followers did not modulate their ability to recall the room, nor 259 the wall where paintings were presented (Fig. 3b-c, Model for rooms, Role: b=-0.15, 260 SE=0.19, X2(1)=0.67, p=0.41; Model for walls, Role: b=0.22, SE=0.24, X2(1)=0.81, p=0.37). 261 More intense aesthetic experience thus led to better spatial memory for both 262 rooms and walls. Correctly recalling both the room and the wall where a painting was 263 hung means correctly recalling the exact location of the painting. We computed an 264 additional mixed model, using the same predictors as before, to confirm that intensity

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265 predicts the ability to report the exact hanging location. We found that indeed intensity 266 significantly explained the ability to recall the exact location where paintings were 267 displayed (Intensity: b=0.23, SE=0.087, X2(1)=6.83, p=0.0090; Liking: b=0.15, SE=0.094, 268 X2(1)=2.50, p=0.11; Role: b=-0.094, SE=0.24, X2(1)=0.15, p=0.70). 269 Liking appeared to significantly explain memory for walls, but not memory for 270 rooms. To further show the effect of liking on memory for walls is independent from 271 memory for rooms, we recomputed the mixed model predicting memory for walls, but 272 including correct/incorrect room responses as an additional predictor. This way, the 273 shared variance between wall and room performance is removed from all the remaining 274 predictors. Liking still significantly predicted memory for walls (Liking: b=0.24, SE=0.095, 275 X2(1)=6.50, p=0.011), thereby showing that positive aesthetic experiences improved 276 memory for walls, independently from memory for rooms. 277

278 279 Fig. 3. Aesthetics and spatial task. a, Distribution of mean liking ratings across participants. 280 Each dot represents the mean liking (not z-scored) for one participant. b, Aesthetic factors and 281 ability to recall the rooms. The left plot shows the confidence intervals for the b estimates for each of

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282 the three main predictors of the model on the ability to recall the room where paintings were 283 displayed: liking, the intensity of the aesthetic experience and the participant’s role. The barplot 284 shows the proportion of correct responses, for all responses collapsed across participants, in 5 285 quantiles along the liking scale, for visualization of the effects. The schematic on the right illustrates 286 the effect of intensity, corresponding to improved performance for extreme ratings. c, Aesthetic 287 factors and ability to recall the wall where a painting was displayed. As panel b, but here b estimates 288 and proportion of correct responses relate to the ability to recall the wall where paintings were 289 displayed. The schematic on the right illustrates the effect of intensity (see panel b) and the effect of 290 liking, which corresponds to improved performance for higher liking ratings. Error bars represent 291 standard error of the mean. **: p<0.01, *: p<0.05. 292 293 294 295 Discussion 296 297 We have investigated whether and how aesthetic experience could modulate 298 spatial memory. Importantly, spatial encoding in our task was incidental: participants 299 were able to recall locations of abstract paintings from a virtual museum, even though 300 their main focus in the task was the art, and not the space. Participants remembered 301 better the exact location of paintings that generated an intense aesthetic experience – 302 either positive or negative. In turn, more positive aesthetic experience led to a better 303 memory of the wall where the painting was displayed, independently from the room 304 where the painting was located. We found no evidence for differential spatial memory for 305 participants who actively led the museum visit as compared to those who simply passively 306 followed another visitor’s itinerary. These results were obtained with an unusual sample 307 of 96 participants, aged 9 to 72, who were mostly volunteers at a public event (n=86). 308 The fact that intense aesthetic experiences were associated with a precise 309 representation of space could be explained by an arousal effect. This is consistent with 310 previous findings showing better memory for arousing events (Cahill & McGaugh, 1998) 311 or stimuli (Bradley et al., 1992), including better spatial memory (Brunyé et al., 2009; 312 Mather & Nesmith, 2008; Schmidt et al., 2011). Our analysis method was able to dissociate 313 this intensity/arousal effect from a liking/valence effect, since liking selectively 314 modulated recollection of the hanging wall. Previous studies have showed differential 315 spatial memory for positive vs negative landmarks (Balaban et al., 2017; Palmiero &

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316 Piccardi, 2017; Ruotolo et al., 2019), and for aversive (Moita et al., 2003) and rewarding 317 (Butler et al., 2019) stimuli in animals, but little is known about specific effects of arousal 318 vs valence on spatial coding. Here, we showed initial behavioral evidence for a 319 dissociation between arousal and valence effects on spatial memory. Furthermore, the 320 association between aesthetic experience and memory for spatial location occurred 321 incidentally, and was not based on the canonically salient stimuli (e.g., snakes or other 322 threatening stimuli) used in some previous studies. This suggests that the affect-space 323 association, which has an obvious ecological importance in the case of highly emotional 324 threatening events, might also extend to aesthetic stimuli, that generate distinctive human 325 experiences without evident link to basic survival behaviors. 326 Separating object location into wall and room information identified two forms of 327 spatial memory code (Epstein et al., 2017; Marchette et al., 2014), corresponding to 328 heading orientation and sequence recall respectively. Aesthetic experience necessarily 329 requires a subjective perspective on a viewed object (Pearce et al., 2016), but here we 330 show that positive aesthetic experiences are associated with a more elaborated heading 331 representation than negative aesthetic experiences. Specifically, the display wall was 332 better recalled for more liked than for less liked paintings, suggesting that liking 333 strengthened first-person memory for location. This effect was independent from the 334 intensity of the experience and also independent from memory for sequence recall. Other 335 studies have also reported associations between emotional memories and first-person 336 perspective (Berntsen & Rubin, 2006; D’Argembeau et al., 2003; Sutin & Robins, 2008), 337 though typically with very different stimuli, and without explicitly involving spatial 338 representations. Whether this effect relates to spatial encoding or recall remains an open 339 question. 340 More generally, these results call for the consideration of aesthetics as a situated 341 experience. The aesthetic experience of an object is not simply a matter of mental 342 representation of the object itself, but has an impact on the representation of space where 343 the object is found. Subjective experience can truly shape the cognitive map. Finally, these 344 results could have important implications for the field of museum design. They indicate 345 that experience of the display space is an implicit and integral part of our experience of 346 objects displayed. Experiencing artworks in a museum is thus a complete experience, 347 which also includes contextual information. Curators and designers surely use implicit 348 knowledge of this psychological fact in creating the layout of exhibitions. However, to our

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349 knowledge, ours is the first scientific study to provide explicit evidence regarding how 350 spatial representation and aesthetic experience may interact. If these findings attain a 351 sufficient level of generality, our work points towards a field of evidence-based exhibition 352 design. 353

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354 References 355 356 Balaban, C. Z., Karimpur, H., Röser, F., & Hamburger, K. (2017). Turn left where you felt

357 unhappy: How affect influences landmark-based wayfinding. Cognitive

358 Processing, 18(2), 135–144. https://doi.org/10.1007/s10339-017-0790-0

359 Bates, D., Maechler, M., Bolker, B., & Walker, S. (2014). Lme4: Linear mixed-effects models

360 using Eigen and S4. R package version 1.1-7.

361 Berntsen, D., & Rubin, D. C. (2006). Emotion and vantage point in autobiographical

362 memory. Cognition & Emotion, 20(8), 1193–1215.

363 https://doi.org/10.1080/02699930500371190

364 Bradley, M. M., Greenwald, M. K., Petry, M. C., & Lang, P. J. (1992). Remembering pictures:

365 Pleasure and arousal in memory. Journal of Experimental : Learning,

366 Memory, and Cognition, 18(2), 379.

367 Brunyé, T. T., Mahoney, C. R., Augustyn, J. S., & Taylor, H. A. (2009). Emotional state and

368 local versus global spatial memory. Acta Psychologica, 130(2), 138–146.

369 https://doi.org/10.1016/j.actpsy.2008.11.002

370 Butler, W. N., Hardcastle, K., & Giocomo, L. M. (2019). Remembered reward locations

371 restructure entorhinal spatial maps. Science, 363(6434), 1447–1452.

372 https://doi.org/10.1126/science.aav5297

373 Cahill, L., & McGaugh, J. L. (1998). Mechanisms of emotional arousal and lasting

374 declarative memory. Trends in , 21(7), 294–299.

375 https://doi.org/10.1016/S0166-2236(97)01214-9

376 Chan, E., Baumann, O., Bellgrove, M. A., & Mattingley, J. B. (2012). From Objects to

377 Landmarks: The Function of Visual Location Information in Spatial Navigation.

378 Frontiers in Psychology, 3. https://doi.org/10.3389/fpsyg.2012.00304

14

379 D’Argembeau, A., Comblain, C., & Van der Linden, M. (2003). Phenomenal characteristics

380 of autobiographical memories for positive, negative, and neutral events. Applied

381 , 17(3), 281–294. https://doi.org/10.1002/acp.856

382 D’Argembeau, A., & Van der Linden, M. (2004). Influence of Affective Meaning on

383 Memory for Contextual Information. Emotion, 4(2), 173–188.

384 https://doi.org/10.1037/1528-3542.4.2.173

385 Eichenbaum, H. (2017). On the Integration of Space, Time, and Memory. Neuron, 95(5),

386 1007–1018. https://doi.org/10.1016/j.neuron.2017.06.036

387 Epstein, R. A., Patai, E. Z., Julian, J. B., & Spiers, H. J. (2017). The cognitive map in humans:

388 Spatial navigation and beyond. Nature Neuroscience, 20(11), 1504–1513.

389 https://doi.org/10.1038/nn.4656

390 Fox, J., & Weisberg, S. (2019). An R Companion to Applied Regression (Third). Sage.

391 https://socialsciences.mcmaster.ca/jfox/Books/Companion/

392 Leder, H., Gerger, G., & Brieber, D. (2015). Aesthetic appreciation: Convergence from

393 experimental aesthetics and physiology. In J. P. Huston, M. Nadal, F. Mora, L. F.

394 Agnati, & C. J. C. Conde (Eds.), Art, Aesthetics, and the Brain (pp. 57–78). Oxford

395 University Press.

396 https://doi.org/10.1093/acprof:oso/9780199670000.003.0004

397 MacKay, D. G., & Ahmetzanov, M. V. (2005). Emotion, Memory, and Attention in the

398 Taboo Stroop Paradigm: An Experimental Analogue of Flashbulb Memories.

399 Psychological Science, 16(1), 25–32. https://doi.org/10.1111/j.0956-

400 7976.2005.00776.x

401 Manns, J. R., & Eichenbaum, H. (2009). A cognitive map for object memory in the

402 hippocampus. Learning & Memory, 16(10), 616–624.

403 https://doi.org/10.1101/lm.1484509

15

404 Marchette, S. A., Vass, L. K., Ryan, J., & Epstein, R. A. (2014). Anchoring the neural

405 compass: Coding of local spatial reference frames in human medial parietal lobe.

406 Nature Neuroscience, 17(11), 1598–1606. https://doi.org/10.1038/nn.3834

407 Mather, M., & Nesmith, K. (2008). Arousal-enhanced location memory for pictures.

408 Journal of Memory and Language, 58(2), 449–464.

409 https://doi.org/10.1016/j.jml.2007.01.004

410 Moita, M. A. P., Rosis, S., Zhou, Y., LeDoux, J. E., & Blair, H. T. (2003). Hippocampal Place

411 Cells Acquire Location-Specific Responses to the Conditioned Stimulus during

412 Auditory Fear Conditioning. Neuron, 37(3), 485–497.

413 https://doi.org/10.1016/S0896-6273(03)00033-3

414 Palmiero, M., & Piccardi, L. (2017). The Role of Emotional Landmarks on Topographical

415 Memory. Frontiers in Psychology, 8, 763.

416 https://doi.org/10.3389/fpsyg.2017.00763

417 Pearce, M. T., Zaidel, D. W., Vartanian, O., Skov, M., Leder, H., Chatterjee, A., & Nadal, M.

418 (2016). Neuroaesthetics: The Cognitive Neuroscience of Aesthetic Experience.

419 Perspectives on Psychological Science, 11(2), 265–279.

420 https://doi.org/10.1177/1745691615621274

421 Postma, A., Kessels, R., & Vanasselen, M. (2008). How the brain remembers and forgets

422 where things are: The neurocognition of object–location memory. Neuroscience &

423 Biobehavioral Reviews, 32(8), 1339–1345.

424 https://doi.org/10.1016/j.neubiorev.2008.05.001

425 Ruotolo, F., Claessen, M. H. G., & van der Ham, I. J. M. (2019). Putting emotions in routes:

426 The influence of emotionally laden landmarks on spatial memory. Psychological

427 Research, 83(5), 1083–1095. https://doi.org/10.1007/s00426-018-1015-6

16

428 Schmidt, K., Patnaik, P., & Kensinger, E. A. (2011). Emotion’s influence on memory for

429 spatial and temporal context. Cognition & Emotion, 25(2), 229–243.

430 https://doi.org/10.1080/02699931.2010.483123

431 Snider, J. G., & Osgood, C. E. (1969). Semantic differential technique; a sourcebook. Aldine

432 Pub. Co.

433 Sutin, A. R., & Robins, R. W. (2008). When the “I” looks at the “Me”: Autobiographical

434 memory, visual perspective, and the self. Consciousness and Cognition, 17(4),

435 1386–1397. https://doi.org/10.1016/j.concog.2008.09.001

436

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438 Supplementary material 439 440 Preliminary analysis I: Inter-individual factors predicting aesthetic experience 441 As a preliminary step of analysis, we tested whether inter-individual factors could 442 contribute to variability in liking and intensity of aesthetic experience. We computed two 443 mixed models (one for liking and one for intensity) using the following predictors: the 444 participant’s role (leader/follower), age (log-transformed) and gender 445 (female/male/prefer not to say). The intercept term was allowed to vary by participant 446 and by painting as a random effect. 447 Females tended to report higher liking ratings (X2(2)=5.72, p=0.057). Gender did 448 not modulate the intensity of experience (X2(2)=3.30, p=0.19). Neither role nor age 449 significantly explained liking (all X2<1.56, p>0.21) or intensity (all X2<0.49, p>0.48). 450 451 Preliminary analysis II: Inter-individual and spatial factors predicting spatial memory 452 We considered two classes of general factors that could potentially account for 453 room and/or wall accuracy on the map task. The first class of general factors was inter- 454 individual variability. We computed a mixed model using the following predictors: the 455 participant’s role (leader/follower), age (log-transformed), gender (female/male/prefer 456 not to say), and the time spent in each exhibition room (z-scored for each participant). 457 Participants and paintings were entered as random effects. Gender predicted the ability 458 to recall the exhibition room (Gender: X2(2)=6.15, p=0.046; all other predictors: X2<0.9, 459 p>0.35). Females recalled the exhibition room better than males. None of these inter- 460 individual factors significantly contributed to memory of walls (all predictors: X2<1.54, 461 p>0.40). 462 The second class of general factors related to spatial organization. The 463 corresponding mixed model contained the following predictors: the room number (first 464 to fourth), the wall (left, front, right), the museum layout (6 instances), and the exhibition 465 room type (3 instances depending on exit door). Participants and paintings were entered 466 as random effects. Memory for rooms was significantly predicted by room number 467 (X2(3)=9.80, p=0.020) and room layout (X2(2)=6.32, p=0.042; all other predictors: X2<3.5, 468 p>0.17), explained by a better memory for the first visited room and a worse memory for 469 the room layout containing a door on the right wall. The wall where paintings were 470 presented significantly modulated memory for walls (X2(2)=10.09, p=0.0064; all other

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471 predictors: X2<4.7, p>0.20), the front wall being associated with worse memory 472 performance. 473 Predictors which significantly explained memory for rooms and/or walls were 474 then also transferred to analyses of aesthetic value. 475 476 477 478 Supplementary table: details of the dataset 479 Tate festival UCL festival Laboratory Total

Total number of participants 87 37 10 134

At the time of testing 21 13 0 34 # Exclusions At memory screening stage 3 1 0 4 # Inclusions 63 23 10 96

# Female Leaders 15 10 7 32 # Female Followers 9 4 0 13 # Male Leaders 21 6 3 30 Gender / Role # Male Followers 15 1 0 16 # Gender no ans. Leaders 2 1 0 3 # Gender no ans. Followers 1 1 0 2

Mean ± SD 34.35 ± 14.52 43.35 ± 14.28 23.50 ± 2.55 35.38 ± 14.71 Age Min, Max 9, 72 21, 69 19, 27 9, 72 Liking (mean ± SD) 54.70 ± 10.21 52.44 ± 11.15 59.85 ± 9.94 54.70 ± 10.50

Rooms, mean ± SD 45.37 ± 22.01 42.87 ± 20.16 47.91 ± 21.12 45.04 ± 21.32 % Correct Walls, mean ± SD 55.64 ± 24.2 58.96 ± 24.99 62.56 ± 19.44 57.16 ± 23.83 480

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481 482 Supplementary Figure 1: museum maps used in the task. 483 Museums a and b were tested at the Tate Modern science festival. Museums c to f 484 were tested at UCL science festival and at the laboratory. 485

486

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