Submitted Successfully!
To reward your contribution, here is a gift for you: A free trial for our video production service.
Thank you for your contribution! You can also upload a video entry or images related to this topic.
Version Summary Created by Modification Content Size Created at Operation
1 -- 2430 2023-10-13 05:52:06 |
2 Reference format revised. -1 word(s) 2429 2023-10-15 14:07:50 |

Video Upload Options

We provide professional Video Production Services to translate complex research into visually appealing presentations. Would you like to try it?

Confirm

Are you sure to Delete?
Cite
If you have any further questions, please contact Encyclopedia Editorial Office.
Cheng, Y.; Chen, J.; Li, J.; Li, L.; Hou, G.; Xiao, X. Public Art Design in Urban Landscapes. Encyclopedia. Available online: https://encyclopedia.pub/entry/50240 (accessed on 16 November 2024).
Cheng Y, Chen J, Li J, Li L, Hou G, Xiao X. Public Art Design in Urban Landscapes. Encyclopedia. Available at: https://encyclopedia.pub/entry/50240. Accessed November 16, 2024.
Cheng, Yue, Jiayin Chen, Jiahua Li, Lin Li, Guanhua Hou, Xuan Xiao. "Public Art Design in Urban Landscapes" Encyclopedia, https://encyclopedia.pub/entry/50240 (accessed November 16, 2024).
Cheng, Y., Chen, J., Li, J., Li, L., Hou, G., & Xiao, X. (2023, October 13). Public Art Design in Urban Landscapes. In Encyclopedia. https://encyclopedia.pub/entry/50240
Cheng, Yue, et al. "Public Art Design in Urban Landscapes." Encyclopedia. Web. 13 October, 2023.
Public Art Design in Urban Landscapes
Edit

As urbanization quickens, the role of public art in urban landscape design gains prominence. Nevertheless, how stylistic characteristics of landscape public art affect aesthetic preferences remains insufficiently discussed, particularly with objective assessment methods. The use of event-related potential (ERP) can offer neurophysiological evidence to support research and practice in landscape art design. 

urban landscape design public art aesthetic preferences

1. Public Art in Urban Landscapes

According to the “2022 World Cities Report” published by UN-Habitat [1], the urban population in 2021 accounted for 56% of the global population, a figure projected to rise to 68% by 2050. With the advancement of urbanization, people’s aesthetic demands for urban spaces are increasing daily [2]. Public art, as a new urban norm in the cityscape, has been widely used for embellishing and beautifying urban spaces [3][4][5]. They not only elevate the aesthetic standards of the space but also attract people’s attention to specific locations [6][7]. The unique role of public art in urban aesthetics has transcended mere visual attraction. Not only does it contribute to the improvement of life quality in urban settings, but it also acts as a catalyst in the construction of urban landscapes. Furthermore, meticulously designed public art can metamorphose undeveloped urban areas into dynamic community hubs, thus promoting the regeneration of the city [8][9]. While a growing body of research has investigated the societal [10][11], cultural [12], and economic [13] aspects of public art, gaps still persist in the understanding of its aesthetic mechanisms. To be more specific, the majority of studies depend on subjective methodologies like case analyses [14][15] and surveys [16][17] for measuring the aesthetics of public art. Although these conventional approaches are valuable, they are still inadequate in offering objective and measurable data.

2. Abstract and Figurative Stylistic Features

Public art’s main goal is to meet the aesthetic demands of the general populace while concurrently serving to enhance and beautify spaces [7][8]. Therefore, the aesthetic appreciation and experience of the audience are crucial to the design of art pieces [18]. In the field of art research, how stylistic features such as those described as abstract or figurative influence the public’s aesthetic perception and evaluation has been extensively studied [19][20]. The selection of these styles can profoundly impact the acceptance and interaction level of public art in urban landscapes.
People’s aesthetic appreciation of urban public art falls within the realm of visual cognition, encompassing various stages of information processing. Affect accompanies cognitive processing interactively, thereby leading to corresponding aesthetic judgments and evaluations [21]. As articulated by Leder et al. [22], this includes perception, the gathering of implicit memory, explicit categorization, cognitive mastery, and evaluation. Through top–down cognitive processes, such as personal experiences and emotions, combined with bottom–up visual analyses, like color, lines, textures, and other visual attributes [23][24], temporary models of the visual world are established and validated or updated according to the information provided by sensory stimuli [25][26][27]. The subjective experience of artwork might involve multiple cognitive processes from perception to memory, varying with the abstractness of the art [28][29][30]. Figurative art often depicts true forms of life, such as humans, animals, and objects, displaying accurate proportions, dimensions, and precise details and features [31]. As a result, they frequently serve as commemorative and symbolic representations of events and individuals [32][33]. The specific information and actual events portrayed in figurative art enable viewers to rapidly process visual information, matching it with corresponding knowledge and memory, making it more readily comprehensible [34]. However, the intricate decoration and historical figures in figurative art may sometimes create impressions of elitism and political propaganda, thereby sparking controversy [35][36]. Abstract art, emphasizing elements like form, space, and material, often abandons concrete shapes and appearances, opting instead for simplified shapes, lines, and colors to convey themes and emotions [5][37]. They frequently challenge viewers’ expectations, stimulate their imaginations, and invite them into more proactive and exploratory modes of artistic perception [38]. While some audiences may appreciate the ambiguity and openness of abstract artworks, the uncertainty may make it challenging to effectively link cognition with visual representation during the information processing stage, requiring further elaboration of meaning [39].

3. Aesthetic Emotions, Fluency Theory, and Expertise

Aesthetic preference is defined as the degree of admiration and affection for visual stimuli, or the aesthetic evaluation of such stimuli [40][41], and is closely associated with factors such as aesthetic experience and emotions [42], the level of processing difficulty [43][44], and the expertise of the participants [21][45].
Researchers posit that aesthetic experience is a “perceive–feel–sense” capability, indicating the involvement of cognitive, emotional, and reward-related processes when evaluating artistic creations [24][46]. Leder et al. [22] assert that aesthetic experience initially manifests as a cognitive process, subsequently transforming into an ever-growing emotional state, ultimately culminating in aesthetic sentiment; conversely, Chatterjee and Vartanian [47] contend that aesthetic pleasure is profoundly influenced by the cognitive system. Pleasurable aesthetic emotions often correlate with positive aesthetic experiences [48]. Emotional reactions to art play a vital role in determining aesthetic preferences, as studies have shown that emotions influence the formation of preferences and decision making [49][50]. Additionally, the theory of fluency is an influential perspective, arguing that the ease or fluency of processing an artwork contributes to enhancing its aesthetic allure [44]. From this standpoint, art that is easily processed and understood is more readily favored. Moreover, the personality, training, and expertise of the viewer are also significant. A high degree of openness to experience, or a craving for novel experiences, is associated with a broader aesthetic preference and a more profound appreciation of artistic works. Research has shown that experts and non-experts differ in their aesthetic preferences and experiences, with experts exhibiting a stronger perception of unique artistic features compared to laypeople [21][45][51]. In conclusion, the emotions and expertise people engage in when appreciating and interacting with art affect their ultimate aesthetic preferences. However, these factors are subjective and dynamic, and given the complex information processing mechanisms of the audience’s brain, describing these differences based on experience presents a challenge [18][43]. Therefore, scientifically measuring these disparities is a significant and difficult issue.

4. Aesthetic Research on Urban Public Art

Currently, aesthetic research on public art mainly focuses on areas such as questionnaire surveys [16][17] and case studies [14][15]. For instance, Peruzzi et al. [15] uncovered the presence of stereotypical impressions of female figures and the insufficiency of cultural policies in the Italian urban environment through an analysis of aesthetic and cultural aspects of 34 urban sculptures distributed across Italian territory. Meanwhile, Tang et al. [17] discussed the aesthetic experiences of tourists regarding iconic public art through a survey, finding that related aesthetic factors can serve as an indicator of the public art experience.
While these research methodologies are facile in execution and cost-effective, the data collected suffer from considerable limitations. Questionnaires, though a commonly employed quantitative research tool, are easily influenced by both external and internal factors as people respond to them. Their feelings might not correspond with actual experience, and respondents may deliberately alter their answers instead of offering their initial, unfiltered cerebral reactions [52][53]. Furthermore, numerous other elements such as rewards, time constraints, or peer pressure could lead to a distortion of the respondents’ feelings, thereby possibly preventing the survey results from truly reflecting the respondents’ authentic thoughts [54].

5. Aesthetic Assessment Based on Neuroscience

In recent years, the field of neuroscience has laid the physiological and methodological foundations for the study of aesthetic preferences [55][56], wherein event-related potentials (ERPs) have emerged as a complex, non-invasive method for measuring and mapping the topography of brain activity [57][58]. The experimental principle of ERPs involves recording the potential changes in the brain regions of subjects induced by specific external sensory, cognitive, or active stimuli. Through techniques such as superimposed averaging and time–frequency analysis, these subtle physiological signals are extracted from spontaneous EEG activity. ERPs are highly suited for the gathering of brain data, boasting the advantages of cost-efficient experimental design and an extraordinarily high temporal resolution [59][60]. ERPs encompass three critical metrics: amplitude, latency, and scalp distribution [61]. By determining the mean amplitude of ERP across various time segments, one can study the disparities in different environments. Latency, measured in milliseconds, refers to the time interval between the commencement of a stimulus and the attainment of its peak. Observing the ERP distribution across the entire scalp, we can identify which regions of the brain are activated when a stimulus appears. For instance, the parietal P200 refers to a positive ERP component active in the parietal lobe area of the brain, peaking approximately 200 ms after stimulus onset. Researchers typically select components and brain regions based on different experimental objectives and analyze electrode points within the chosen brain areas to obtain relevant data on ERP components. For example, in Markey et al.’s ERP study on painting semantics, the N300/400 and P600 components related to visual semantics were observed, and the midcentral region (FC1, FC2, C1, Cz, C2, CP1, CPz, CP2) in which these components are active was selected for analysis [62]. These three key factors in ERPs offer insights into human psychological activity [58]. Certain researchers have employed ERPs to explore the neural responses to various stimuli that induce users’ aesthetic preferences [60][63].
The N100 is an ERP component associated with attention, typically reaching its peak within the 100–200 ms following a stimulus. As an exogenous visual element, it is related to the allocation of attentional resources elicited by the stimulus, subsequently influencing the participant’s recognition of visual characteristics [64][65]. Certain studies have revealed that the N100 is sensitive to low-level visual features, and its amplitude is correlated with the physical attributes of the stimulating material [64][66]. In perceptual processing, the participant’s attention and recognition handling may be influenced by physical factors such as shape and material. Notably, a higher N100 amplitude signifies a greater allocation of attentional resources to visual feature recognition [59][67]. Moreover, the aesthetic perception of artworks among different individuals has been demonstrated to have a connection with the N100 component. 
P200 is an ERP component that reaches its peak approximately 200 ms after stimulation, specifically involved in visual aesthetic processing. It is capable of reflecting the allocation of early attentional resources and emotional arousal [68][69]. Aesthetic evaluation encompasses not only attention but also an emotional experience. When exposed to positive or favored stimuli, the P200 amplitude experiences a corresponding increase [67][70][71]. For example, Fudali-Czyż et al. [71] observed that the P200 amplitude elicited when participants viewed beautiful paintings was greater than when viewing less attractive ones. Cao et al. [70] found in their study on mobile phone images that attractive anthropomorphic icons induce larger P200 responses than their non-anthropomorphic counterparts. 
The N200 is an ERP component that reaches its peak within a 200–350 ms time window after stimulation, is closely related to cognitive processes such as automatic stimulus recognition, selective attention, and perception, and is considered an endogenous negative component [72][73]. Moreover, existing research has affirmed that the N200 is associated with aesthetic preferences [74]. Researchers have found that individuals, when confronted with items they dislike or deem to have low aesthetic value, trigger a more substantial N200 response. For instance, Handy et al. [75] observed an increase in N200 amplitude in the central frontal area in response to disliked logos in a commercial symbol study. 

Neural Mechanisms of Aesthetic Perception in Public Art

The visual N100 is closely associated with the early visual processing stage of emotional stimuli and is considered a vital indicator of selection and resource allocation [64][76]. According to previous research, the N100 is related to the activation of early visual areas in the brain triggered by visual stimuli, an activation principally elicited by low-level properties of stimuli such as contours, shapes, and colors [64]. Moreover, the N100 is also connected to the allocation of attention in aesthetic preferences. For instance, Chen et al. [77] discovered that lighter tiles with higher preference scores could induce a larger N100 amplitude compared to darker tiles with lower preference scores. However, differing from the above studies, the statistical results demonstrate that the art’s characteristic types did not induce a main effect on the frontal N100. This finding suggests that during the primary stage of perceptual processing, individuals are unable to differentiate between different feature levels of urban public art. This may be due to the specificity of the experimental material, causing participants to focus solely on low-level attributes during the initial visual stage, without completing the mental reconstruction of APA or FPA, which requires higher-level visual processing. As Bimler et al. [78] found, the aesthetic experience is regarded as a cognitive process where objects are decomposed into lower-level features such as color, brightness, lines, light points, etc., and gradually develop into higher-level processing through the interpretation of artworks, systematically reconstructing them into intricate forms. This process might require individuals to observe for a more extended period to achieve full completion [41]. Furthermore, the statistical results also reveal that experts elicit more N100 components than non-experts, indicating that while appreciating public artworks, the brain’s visual regions of experts are more active, and their professional knowledge prompts them to allocate more attentional resources [45]. This discovery aligns with prior research [45][79].
According to research, the P200 functions as a neural correlate during the initial stages of processing visual aesthetics, associated with the processing of emotional stimuli, reflecting the automatic allocation process in the early stage of emotional stimulus processing [69][80]. It is well recognized that emotions (both positive and negative) constitute one of the essential elements in aesthetic preference, and both positive and negative stimuli can elicit variations in P200 amplitude [81]. According to the results of the study, people’s preference for FPA leads to a greater P200 response. Existing research indicates that a larger P200 response is elicited when individuals are exposed to positive and preferred stimuli [67][70][71].
The N200 component reflects a preferential selection of attention towards stimulus-related attributes, while also revealing differences in emotional stimuli [82][83]. Moreover, compared to stimuli with a high preference, those with a low preference have been found to evoke a greater N200 amplitude [75][77][84]. The ERP results are consistent with the aforementioned studies, demonstrating that participants exhibit a higher N200 amplitude in response to low-preference APA as opposed to FPA with a higher preference. Reber et al. [44] propounded a theory of fluency, suggesting that the aesthetic appeal of a piece of art is determined by the ease or difficulty with which it can be understood or perceived. Due to the often elusive and difficult-to-interpret content of APA [43], people tend to generate a more pronounced negative reaction to low-preference APA. This reflects a negative stimulus-driven selection of attention, and the research findings lend support to Hypothesis 3. In addition, during further analysis, experts elicited a greater N200 response to abstract art, signifying that those trained in the arts exhibit a more precise recognition and categorization of artworks. Their information processing is more profound [85], thereby enhancing their selective attention driven by emotions. In contrast, non-experts are found to be in a state where attentional resources are diffused.

References

  1. UN-Habitat World Cities Report. 2022. Available online: https://unhabitat.org/wcr/ (accessed on 17 August 2023).
  2. Nia, H.A.; Olugbenga, F. A Quest on the Role of Aesthetics in Enhancing Functionality of Urban Planning. Civ. Eng. Archit. 2020, 8, 873–879.
  3. Carrier, D. The Aesthete in Pittsburgh: Public Sculpture in an Ordinary American City. Leonardo 2003, 36, 35–39.
  4. McNally, D. I Am Tower of Hamlets: Enchanted Encounters and the Limit to Art’s Connectivity. Soc. Cult. Geogr. 2019, 20, 198–221.
  5. Webber, M. Monumental Marginalia. Borders of Space and Authority in Contemporary Melbourne. Stud. Hist. Theory Archit. Stud. Istor. Teor. Arhit. 2016, 4, 152.
  6. Guinard, P.; Margier, A. Art as a New Urban Norm: Between Normalization of the City through Art and Normalization of Art through the City in Montreal and Johannesburg. Cities 2018, 77, 13–20.
  7. Jasmi, M.F.; Mohamad, N.H.N. Roles of Public Art in Malaysian Urban Landscape towards Improving Quality of Life: Between Aesthetic and Functional Value. Procedia Soc. Behav. Sci. 2016, 222, 872–880.
  8. Cheung, M.; Smith, N.; Craven, O. The Impacts of Public Art on Cities, Places and People’s Lives. J. Arts Manag. Law Soc. 2022, 52, 37–50.
  9. Matthews, T.; Gadaloff, S. Public Art for Placemaking and Urban Renewal: Insights from Three Regional Australian Cities. Cities 2022, 127, 103747.
  10. Becker, H. Remembering Marikana: Public Art Intervention and the Right to the City in Cape Town. Soc. Dyn. 2018, 44, 455–471.
  11. Kosmala, K.; Beall, T.S. Problematizing Silences in Intangible Heritage: Unsettling Historical Records of Women in Protests. Int. J. Herit. Stud. 2019, 25, 348–364.
  12. Kyi, C.; Tse, N.; Khazam, S. The Potential Role of Citizen Conservation in Re-Shaping Approaches to Murals in an Urban Context. Stud. Conserv. 2016, 61, 98–103.
  13. Gurney, K. Zombie Monument: Public Art and Performing the Present. Cities 2018, 77, 33–38.
  14. Layne, M.K. What Environmental Art Can Teach Us about Wind Farms: Exploring the Boundaries of Cultural Aesthetics in Scottish Landscapes. Landsc. Res. 2018, 43, 248–259.
  15. Peruzzi, G.; Bernardini, V.; Riyahi, Y. Women’s Statues in Italian Cities. A Study of Public Art and Cultural Policies. Int. J. Cult. Policy 2022, 1–18.
  16. Chen, S.; Fu, K.; Yang, B.; Lian, X. Using Light Art Installation in Urban Nightscapes to Raise Public Awareness of Carbon Neutrality. Sci. Commun. 2023, 45, 414–427.
  17. Tang, J.; Yan, L.; Xu, J. Tourists’ Experience of Iconic Public Art in Macau. J. Tour. Cult. Chang. 2021, 19, 79–96.
  18. Durkin, C.; Hartnett, E.; Shohamy, D.; Kandel, E.R. An Objective Evaluation of the Beholder’s Response to Abstract and Figurative Art Based on Construal Level Theory. Proc. Natl. Acad. Sci. USA 2020, 117, 19809–19815.
  19. Lyu, Y.; Lin, C.-L.; Lin, P.-H.; Lin, R. The Cognition of Audience to Artistic Style Transfer. Appl. Sci. 2021, 11, 3290.
  20. Sidhu, D.M.; McDougall, K.H.; Jalava, S.T.; Bodner, G.E. Prediction of Beauty and Liking Ratings for Abstract and Representational Paintings Using Subjective and Objective Measures. PLoS ONE 2018, 13, e0200431.
  21. Bölte, J.; Hösker, T.M.; Hirschfeld, G.; Thielsch, M.T. Electrophysiological Correlates of Aesthetic Processing of Webpages: A Comparison of Experts and Laypersons. PeerJ 2017, 5, e3440.
  22. Leder, H.; Belke, B.; Oeberst, A.; Augustin, D. A Model of Aesthetic Appreciation and Aesthetic Judgments. Br. J. Psychol. 2004, 95, 489–508.
  23. Zhou, B.; Pöppel, E.; Wang, L.; Yang, T.; Zaytseva, Y.; Bao, Y. Seeing without Knowing: Operational Principles along the Early Visual Pathway. PsyCh J. 2016, 5, 145–160.
  24. Cinzia, D.D.; Vittorio, G. Neuroaesthetics: A Review. Curr. Opin. Neurobiol. 2009, 19, 682–687.
  25. Bar, M. The Proactive Brain: Using Analogies and Associations to Generate Predictions. Trends Cogn. Sci. 2007, 11, 280–289.
  26. Taylor, R.P.; Spehar, B.; Van Donkelaar, P.; Hagerhall, C.M. Perceptual and Physiological Responses to Jackson Pollock’s Fractals. Front. Hum. Neurosci. 2011, 5, 60.
  27. Liu, J.; Lughofer, E.; Zeng, X. Toward Model Building for Visual Aesthetic Perception. Comput. Intell. Neurosci. 2017, 2017, 1292801.
  28. Seth, A.K. From Unconscious Inference to the Beholder’s Share: Predictive Perception and Human Experience. Eur. Rev. 2019, 27, 378–410.
  29. Castellotti, S.; Scipioni, L.; Mastandrea, S.; Del Viva, M.M. Pupil Responses to Implied Motion in Figurative and Abstract Paintings. PLoS ONE 2021, 16, e0258490.
  30. Mastandrea, S.; Bartoli, G.; Carrus, G. The Automatic Aesthetic Evaluation of Different Art and Architectural Styles. Psychol. Aesthet. Creat. Arts 2011, 5, 126–134.
  31. Zamorano Perez, P.E. Nineteenth-Century Spanish American Sculpture: The Chilean Case. Arch. Esp. Arte 2011, 84, 25–40.
  32. Frei, C.J. Columbus, Juana and the Politics of the Plaza: Battles over Monuments, Memory and Identity in Buenos Aires. J. Lat. Am. Stud. 2019, 51, 607–638.
  33. Hautamaki, R.; Laine, S. Heritage of the Finnish Civil War Monuments in Tampere. Landsc. Res. 2020, 45, 742–757.
  34. Liu, S.; Zhang, W.; He, X.; Tang, X.; Lai, S.; Dai, Z. The Role of Understanding on Architectural Beauty: Evidence from the Impact of Semantic Description on the Aesthetic Evaluation of Architecture. Psychol. Rep. 2022, 125, 1438–1456.
  35. Liu, Z.; Uyttenhove, P.; Zheng, X. Moving Urban Sculptures towards Sustainability: The Urban Sculpture Planning System in China. Sustainability 2018, 10, 4802.
  36. Livholts, M.B. Immaterial Monuments, Narrative Inequality and Glocal Social Work. Towards Critical Participatory Community Art-Based Practices. Br. J. Soc. Work 2022, 52, 776–795.
  37. Avgerinou, S.; Vayas, I.; Adamakos, K. Stahl in Der Bildhauerei—Tragwerksentwurf der Skulptur “Le Chemin de l’eau” in Paris. Stahlbau 2016, 85, 52–58.
  38. Withagen, R.; Caljouw, S.R. Aldo van Eyck’s Playgrounds: Aesthetics, Affordances, and Creativity. Front. Psychol. 2017, 8, 1130.
  39. Kris, E. Psychoanalytic Explorations in Art; International Universities Press: Madison, CT, USA, 2000; ISBN 978-0-8236-8220-1.
  40. Roberts, M.N. Complexity and Aesthetic Preference for Diverse Visual Stimuli. Ph.D. Thesis, Universitat de les Illes Balears, Palma, Spain, 2007.
  41. Pelowski, M.; Markey, P.S.; Forster, M.; Gerger, G.; Leder, H. Move Me, Astonish Me… Delight My Eyes and Brain: The Vienna Integrated Model of Top-down and Bottom-up Processes in Art Perception (VIMAP) and Corresponding Affective, Evaluative, and Neurophysiological Correlates. Phys. Life Rev. 2017, 21, 80–125.
  42. Van Dongen, N.N.N.; Van Strien, J.W.; Dijkstra, K. Implicit Emotion Regulation in the Context of Viewing Artworks: ERP Evidence in Response to Pleasant and Unpleasant Pictures. Brain Cogn. 2016, 107, 48–54.
  43. Aviv, V. What Does the Brain Tell Us about Abstract Art? Front. Hum. Neurosci. 2014, 8, 85.
  44. Reber, R.; Schwarz, N.; Winkielman, P. Processing Fluency and Aesthetic Pleasure: Is Beauty in the Perceiver’s Processing Experience? Personal. Soc. Psychol. Rev. 2004, 8, 364–382.
  45. Else, J.E.; Ellis, J.; Orme, E. Art Expertise Modulates the Emotional Response to Modern Art, Especially Abstract: An ERP Investigation. Front. Hum. Neurosci. 2015, 9, 525.
  46. Di Dio, C.; Macaluso, E.; Rizzolatti, G. The Golden Beauty: Brain Response to Classical and Renaissance Sculptures. PLoS ONE 2007, 2, e1201.
  47. Chatterjee, A.; Vartanian, O. Neuroaesthetics. Trends Cogn. Sci. 2014, 18, 370–375.
  48. Brown, S.; Gao, X.; Tisdelle, L.; Eickhoff, S.B.; Liotti, M. Naturalizing Aesthetics: Brain Areas for Aesthetic Appraisal across Sensory Modalities. NeuroImage 2011, 58, 250–258.
  49. Silvia, P.J. Cognitive Appraisals and Interest in Visual Art: Exploring an Appraisal Theory of Aesthetic Emotions. Empir. Stud. Arts 2005, 23, 119–133.
  50. Vessel, E.A.; Starr, G.G.; Rubin, N. The Brain on Art: Intense Aesthetic Experience Activates the Default Mode Network. Front. Hum. Neurosci. 2012, 6, 66.
  51. Ghomeshi, M.; Jusan, M.M. Investigating Different Aesthetic Preferences Between Architects and Non-Architects in Residential Façade Designs. Indoor Built Environ. 2013, 22, 952–964.
  52. Aubry, M.; Müller, R.; Hobbs, B.; Blomquist, T. Project Management Offices in Transition. Int. J. Proj. Manag. 2010, 28, 766–778.
  53. Ding, Y.; Guo, F.; Hu, M.; Cao, Y. Using Event Related Potentials to Investigate Visual Aesthetic Perception of Product Appearance. Hum. Factors Ergon. Manuf. Serv. Ind. 2017, 27, 223–232.
  54. Zhang, X. The Influences of Brand Awareness on Consumers’ Cognitive Process: An Event-Related Potentials Study. Front. Neurosci. 2020, 14, 549.
  55. Chatterjee, A. Neuroaesthetics: A Coming of Age Story. J. Cogn. Neurosci. 2011, 23, 53–62.
  56. Nadal, M.; Pearce, M.T. The Copenhagen Neuroaesthetics Conference: Prospects and Pitfalls for an Emerging Field. Brain Cogn. 2011, 76, 172–183.
  57. Handy, T.C. Event-Related Potentials: A Methods Handbook; MIT Press: Cambridge, MA, USA, 2005; ISBN 978-0-262-08333-1.
  58. Luck, S.J. An Introduction to the Event-Related Potential Technique; MIT Press: Cambridge, MA, USA, 2014.
  59. Guo, F.; Jiang, J.-Y.; Tian, X.-H.; Chen, J.-H. Applying Event-Related Potentials to Measure Perceptual Experience toward the Navigation Interface of a Mobile Game for Improving the Design. Symmetry 2019, 11, 710.
  60. Sun, X.; Jin, W. Elderly’s Preferences towards Rehabilitation Robot Appearance Using Electroencephalogram Signal. EURASIP J. Adv. Signal Process. 2021, 2021, 35.
  61. Daliri, M.; Taghizadeh, M.; Niksirat, K. EEG Signature of Object Categorization from Event-Related Potentials. J. Med. Signals Sens. 2013, 3, 37.
  62. Markey, P.S.; Jakesch, M.; Leder, H. Art Looks Different—Semantic and Syntactic Processing of Paintings and Associated Neurophysiological Brain Responses. Brain Cogn. 2019, 134, 58–66.
  63. Liu, Z.; Du, W.; Sun, Z.; Hou, G.; Wang, Z. Neural Processing Differences of Facial Emotions Between Human and Vehicles: Evidence from an Event-Related Potential Study. Front. Psychol. 2022, 13, 876252.
  64. Vogel, E.K.; Luck, S.J. The Visual N1 Component as an Index of a Discrimination Process. Psychophysiology 2000, 37, 190–203.
  65. Lijffijt, M.; Lane, S.D.; Meier, S.L.; Boutros, N.N.; Burroughs, S.; Steinberg, J.L.; Gerard Moeller, F.; Swann, A.C. P50, N100, and P200 Sensory Gating: Relationships with Behavioral Inhibition, Attention, and Working Memory. Psychophysiology 2009, 46, 1059–1068.
  66. Anllo-Vento, L.; Hillyard, S.A. Selective Attention to the Color and Direction of Moving Stimuli: Electrophysiological Correlates of Hierarchical Feature Selection. Percept. Psychophys. 1996, 58, 191–206.
  67. Shi, A.; Huo, F.; Hou, G. Effects of Design Aesthetics on the Perceived Value of a Product. Front. Psychol. 2021, 12, 670800.
  68. Kosonogov, V.; Martinez-Selva, J.M.; Carrillo-Verdejo, E.; Torrente, G.; Carretié, L.; Sanchez-Navarro, J.P. Effects of Social and Affective Content on Exogenous Attention as Revealed by Event-Related Potentials. Cogn. Emot. 2019, 33, 683–695.
  69. Noguchi, Y.; Murota, M. Temporal Dynamics of Neural Activity in an Integration of Visual and Contextual Information in an Esthetic Preference Task. Neuropsychologia 2013, 51, 1077–1084.
  70. Cao, Y.; Zhang, Y.; Ding, Y.; Duffy, V.G.; Zhang, X. Is an Anthropomorphic App Icon More Attractive? Evidence from Neuroergonomomics. Appl. Ergon. 2021, 97, 103545.
  71. Fudali-Czyż, A.; Francuz, P.; Augustynowicz, P. The Effect of Art Expertise on Eye Fixation-Related Potentials During Aesthetic Judgment Task in Focal and Ambient Modes. Front. Psychol. 2018, 9, 1972.
  72. Cela-Conde, C.J.; Agnati, L.; Huston, J.P.; Mora, F.; Nadal, M. The Neural Foundations of Aesthetic Appreciation. Prog. Neurobiol. 2011, 94, 39–48.
  73. Ernst, L.H.; Ehlis, A.-C.; Dresler, T.; Tupak, S.V.; Weidner, A.; Fallgatter, A.J. N1 and N2 ERPs Reflect the Regulation of Automatic Approach Tendencies to Positive Stimuli. Neurosci. Res. 2013, 75, 239–249.
  74. Hajcak, G.; Weinberg, A.; MacNamara, A.; Foti, D. ERPs and the Study of Emotion. In The Oxford Handbook of Event-Related Potential Components; Oxford Library of Psychology; Oxford University Press: New York, NY, USA, 2012; pp. 441–472. ISBN 978-0-19-537414-8.
  75. Handy, T.C.; Smilek, D.; Geiger, L.; Liu, C.; Schooler, J.W. ERP Evidence for Rapid Hedonic Evaluation of Logos. J. Cogn. Neurosci. 2010, 22, 124–138.
  76. Weinberg, A.; Hajcak, G. Beyond Good and Evil: The Time-Course of Neural Activity Elicited by Specific Picture Content. Emotion 2010, 10, 767–782.
  77. Chen, J.; He, B.; Zhu, H.; Wu, J. The Implicit Preference Evaluation for the Ceramic Tiles with Different Visual Features: Evidence from an Event-Related Potential Study. Front. Psychol. 2023, 14, 1139687.
  78. Bimler, D.L.; Snellock, M.; Paramei, G.V. Art Expertise in Construing Meaning of Representational and Abstract Artworks. Acta Psychol. 2019, 192, 11–22.
  79. Luck, S.J. Event-Related Potentials. In APA Handbook of Research Methods in Psychology, Volume 1: Foundations, Planning, Measures, and Psychometrics; APA Handbooks in Psychology®; American Psychological Association: Washington, DC, USA, 2012; pp. 523–546. ISBN 978-1-4338-1004-6.
  80. Tommaso, M.; Pecoraro, C.; Sardaro, M.; Serpino, C.; Lancioni, G.; Livrea, P. Influence of Aesthetic Perception on Visual Event-Related Potentials. Conscious. Cogn. 2008, 17, 933–945.
  81. Correll, J.; Urland, G.R.; Ito, T.A. Event-Related Potentials and the Decision to Shoot: The Role of Threat Perception and Cognitive Control. J. Exp. Soc. Psychol. 2006, 42, 120–128.
  82. Herbert, C.; Kissler, J.; Junghofer, M.; Peyk, P.; Rockstroh, B. Processing of Emotional Adjectives: Evidence from Startle EMG and ERPs. Psychophysiology 2006, 43, 197–206.
  83. Lu, Y.; Jaquess, K.J.; Hatfield, B.D.; Zhou, C.; Li, H. Valence and Arousal of Emotional Stimuli Impact Cognitive-Motor Performance in an Oddball Task. Biol. Psychol. 2017, 125, 105–114.
  84. Telpaz, A.; Webb, R.; Levy, D.J. Using EEG to Predict Consumers’ Future Choices. J. Mark. Res. 2015, 52, 511–529.
  85. Silvia, P.J. Interested Experts, Confused Novices: Art Expertise and the Knowledge Emotions. Empir. Stud. Arts 2013, 31, 107–115.
More
Information
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register : , , , , ,
View Times: 638
Revisions: 2 times (View History)
Update Date: 15 Oct 2023
1000/1000
ScholarVision Creations