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Article

Exploring the Psychophysiological Effects of Viewing Urban Nature through Virtual Reality Using Electroencephalography and Perceived Restorativeness Scale Measures

by
Audrey Seiz
1,
Byoung-Suk Kweon
1,*,
Christopher D. Ellis
1,
Hyuk Oh
2 and
Kyle Pietro
2
1
Department of Plant Science and Landscape Architecture, University of Maryland, College Park, MD 20742, USA
2
Department of Kinesiology, University of Maryland, College Park, MD 20742, USA
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(17), 13090; https://doi.org/10.3390/su151713090
Submission received: 20 July 2023 / Revised: 17 August 2023 / Accepted: 24 August 2023 / Published: 30 August 2023
Browse Figures
Versions Notes

Abstract

:
Researchers have long explored how humans respond psychologically and physiologically to distinct landscapes and natural features. Walking in nature and viewing photographs of natural landscapes have been shown to reduce stress measured through the physiological responses of blood pressure, salivary cortisol concentration, and pulse rate. Exposure to natural landscapes has also been shown to improve feelings of relaxation and positive emotion. Little research, however, has focused on the potential impact of visualization through virtual reality (VR). This study explores how brain frequencies and psychological measures test the restorativeness of a virtual place. Utilizing VR, twenty-one participants observed a virtual, vegetated, vacant site as it exists currently and then again as a reimagined greenspace. The psychological responses were analyzed using the Perceived Restorativeness Scale (PRS), and the psychophysiological responses were analyzed using electroencephalography (EEG) with a specific focus on alpha and beta brain frequencies in the frontal and parietal lobes. Findings indicated that the perceived restorativeness of the designed site increased for two of the three determined factors. Alpha brain frequencies were not significantly different when viewing the vacant versus the designed site; however, beta brain frequencies demonstrated a marginally significant effect of sex with male beta power spectral density decreasing when viewing the designed site and female beta brain frequencies increasing. This research suggests that redesigning a vegetated urban vacant site can positively impact perceived restorativeness and unveils a potential gender effect present in beta brain frequencies.

1. Introduction

1.1. Theoretical Frameworks

Researchers have long been using psychophysiological measures to examine the restorative capacity of nature on human beings. The two main theories underpinning a substantial amount of this research on restoration and nature are ART and SRT. ART and SRT both stem from an evolutionary assumption that, in general, because humans evolved for most of their existence in natural environments, humans are adapted psychologically and physiologically to the natural world rather than to an urban environment [1,2]. Both ART and SRT also consider the element of stress to play a role within the restoration models [2,3]. The mechanism through which restoration is achieved for humans in natural environments, however, establishes the division between these theories.
ART establishes that a natural space has restorative potential because of its impact on human cognition. Utilizing a two-pronged approach to attention established in James [4], ART posits that directed attention requires effort while fascination requires no effort [3]. Directed attention is a finite resource for humans that is crucial for information processing, and over time, the utilization of this resource can cause mental fatigue that impacts elements of human perception, thought, action, and emotion [3]. Since directed attention is limited, ART offers the concept of fascination as a vehicle to lower cognitive effort and rebuild directed attention capacity [5,6]. Fascination can come from a variety of sources including natural environments. Kaplan [3] deemed fascination in natural environments “soft fascination”, which promotes reflection to aid directed attention recovery (p. 172).
In addition to fascination, three other attributes of the environment must be present to establish a restorative experience: being away, extent, and compatibility [1,3]. Being away is described as the feeling of breaking away from routine environments, extent relates to the connectedness of features within an environment at scale to enhance the feeling of being somewhere else, and compatibility references the relatedness of the environment to a human’s goals for using a space [1,3,7]. When these attributes are present, then, a restorative experience in an environment is possible that facilitates recovery from mental fatigue [3].
SRT asserts that a human’s analysis of an environment originally depends on emotion (affect) not cognition [2]. The theory describes a process in which an immediate emotional reaction (like or dislike) to an environment is derived by our initial emotional state prior to a change in the environment as well as generalized visual cues [2,5,8]. This initial emotional reaction causes arousal that then sparks the cognitive processing of the environment that could further alter arousal and emotional response [2]. Arousal and emotional response are proceeded by a behavior or motivation, which is often oriented toward approach or withdrawal from an environment [2]. SRT argues that an environment can provide emotional and physiological restoration after interaction with a stress-inducing stimulus [2,5]. Specifically, viewing a natural environment following a stressful stimulus alters a human’s emotional state to facilitate immediate positive emotional reactions that in turn reduce arousal while still maintaining interest [2,5].

1.2. Study Purpose

The purpose of this study was to investigate how interactions with urban landscapes influence public health and how purposeful design interventions can improve the livability of urban spaces. We explored the environmental impact on human restorativeness through self-reported perceived restorativeness, a psychological metric, and electrical brain activity, a psychophysiological metric.

1.3. Perceived Restorativeness and Environment

The Perceived Restorativeness Scale (PRS) is a predominant metric for analyzing a participant’s self-reported feeling about the restorativeness of an environment with questions targeting the four Attention Restoration Theory (ART) attributes of a restorative experience [9]. Initially devised by Hartig et al. [8], the PRS has been adapted and modified to fully target the attributes of fascination, being away, compatibility, and extent through distinct types of statements [7,8,10,11,12,13]. Although variations of this metric do exist, there are apparent trends between perceived restorativeness and the environment, which warrants further exploration.
Nature in urban environments can impact the perceived restorativeness of a human’s experience. Previous studies have investigated viewing urban settings with and without greenspace and found that urban greenspace was perceived as more restorative than urban areas without greenspace [11,14,15]. Studies utilizing imagery of a series of urban versus natural environments have reported that the natural environments were rated as more restorative when compared to the urban environments [9,13,16]. In addition, when experiencing environments in situ, participants have demonstrated higher perceived restoration for natural settings [11,12,17]. Research comparing a natural space, an urban greenspace, and urban street reported higher perceived restorativeness for the natural setting, urban greenspace, and urban street, in that order; however, human preference plays a vital role in perceived restoration, specifically in urban greenspace environments [18,19].
Little research has explored virtual nature and its impact on perceived restorativeness. Schutte et al. [20] used virtual reality (VR) to display images of an Australian natural landscape and a small town, and the results indicated the virtual natural setting was significantly more restorative than the urban environment. One additional study compared exposure to nature outdoors versus virtual nature, and the study determined that both virtual and outdoor nature statistically increased perceived restorativeness relative to a control environment with no nature present. This indicated that virtual nature could facilitate a restorative experience for humans [21].

1.4. Brain Activity and Environment

Electroencephalography (EEG) measures changes in brain activity that are associated with different brain states [22]. The dominance of different brain frequencies is associated with different brain states. As such, increased delta activity (0.5–4 Hz) is not normally seen in adults during waking, it is, however, present during sleep; theta activity (4–8 Hz) reflects working-memory, cognitive workload, and mental effort [23,24,25]; alpha activity (8–13 Hz) represents a relaxed but wakeful mind; beta activity (13–30 Hz) signifies an alert and attentive mind; and gamma activity (>30 Hz) often indicates a cognitively engaged or hyperactive mind [26]. In addition, the alpha and beta brain frequencies are further categorized. Alpha I (8–10 Hz) is associated with attentional processing and alpha II (10–13 Hz) with cognitive processing, specifically memory [27]. Beta I (13–20 Hz) is oriented toward concentration, anxiety, and performance, whereas beta II (20–30 Hz) relates to stress, anxiety, and arousal [27].

1.4.1. Indoor Immersion

Regarding indoor experimentation examining EEG and the environment, Ulrich [28] was a foundational study exploring the impact of natural versus urban images on brain activity. This study indicated that natural spaces increased a relaxed but awake cognitive state based on an increase in alpha brain frequency [28]. Numerous studies identified unpredictable results associated with alpha and beta power when juxtaposing environments. When compared to a control, alpha power increased in the medial prefrontal cortex [29] and there were high alpha and theta brain frequencies in the central and occipital areas [30]. Elsadek et al. [31] found higher alpha power in frontal and prefrontal electrodes when built environment vs. nature images were compared. Jiang et al. [32] found a marginally significant increase in high and low alpha power when comparing an urban image to a series of natural environments with no significant effects on other brain frequencies (beta, theta, delta, or gamma); however, the location and number of electrodes used to determine the raw EEG data are unclear from the study. Window views of a greenspace versus an urban setting resulted in marginally and significantly higher alpha power in prefrontal and occipital electrodes [33]. Grassini et al. [34] reported an increase in low alpha power when comparing built and natural environments; however, high alpha, beta, theta, and delta all decreased across 64 electrodes. Finally, Wang et al. [35] did not find any difference between alpha or beta brain frequencies when comparing urban bamboo forest settings, yet the number and location of electrodes is unclear.

1.4.2. Virtual Reality

VR has been used as a tool in tandem with a variety of EEG studies, often associated with rehabilitation [36]; however, few studies have used VR to explore environments and EEG. VR is a revolutionary visualization tool because of its ability to put individuals in a new environment, surround individuals with the environment, or promote exploration within the environment [37]. Gao et al. [38] focused on alpha activity and found there was no significant difference in alpha power between environments ranging from zero to greater than 70% tree canopy; however, only one electrode was utilized for the study, and it is unclear where the electrode was positioned on the forehead. Wang et al. [39] found that twenty minutes of exercise viewing virtual nature or viewing virtual abstract art significantly increased alpha power when comparing the pretest to the posttest, indicating that exercise, not environment, led to increased cognitive relaxation. One study exploring the impact of urban greenspace vegetation on the structure and degree of greening provided inconclusive EEG results [40]. Two studies [41,42] focused on built development and design; however, Hu and Roberts [41] did not include the results from the EEG in their report. Rounds et al. [42] examined the theta band and found that contrasting architectural design elements, including twisting buildings, increased the posterior parietal theta power, yet the posterior parietal theta power decreased when buildings contained green facades.

1.4.3. Frontal Alpha Asymmetry

Frontal alpha asymmetry (FAA) in relationship to emotion has been studied for many decades [43]. Several studies and reviews have determined that this normalized FAA has demonstrated association with state and trait emotion as well as approach–withdrawal motivation. Greater left frontal activity, or a positive normalized FAA, indicates approach motivation, while greater right frontal activity, or negative normalized FAA, indicates withdrawal motivation [44,45,46,47]. Although frequently associated with positive emotion, it is noteworthy that approach motivation can be associated with negative emotions, such as anger [48]. This indication of emotion and arousal, through normalized FAA, relates to Stress Reduction Theory (SRT) and a human’s initial emotional response that informs cognition and behavior; however there is minimal research examining FAA and the environment. Olszewska-Guizzo et al. [49] determined no effect of “contemplative” versus “non-contemplative” environment, and two additional studies, Olszewska-Guizzo et al. [50] and Olszewska-Guizzo et al. [51], inappropriately measured frontal alpha asymmetry. Thus, additional study could reveal the connection between the environment and approach–withdrawal motivation through FAA.

1.5. Research Questions and Hypotheses

Based on the literature review, we developed a study designed to fill gaps in the evidence-based research given that there are no comparative studies of an existing site that was redesigned; few studies have examined brain frequencies solely in urban areas; and there is limited research using VR. This comparative study proposed two research questions with associated hypotheses utilizing an existing vacant site that is redesigned with VR to explore the impacts on brain frequencies and feelings of restorativeness. These research questions and hypotheses were derived from the foundational findings of Hartig et al. [7] and Ulrich [28]. The specific research questions and hypotheses are as follows:
Research Question 1. How do the two different stimulus environments impact brain frequencies and perception of restorativeness?
Hypothesis 1a (H1a).
Perceived restorativeness factors will increase when viewing the designed versus vacant site.
Hypothesis 1b (H1b).
Alpha frequency will increase and beta frequency will decrease when viewing the designed versus vacant site in the frontal and parietal lobes.
Research Question 2. Do the two different stimulus environments impact approach–withdrawal motivation?
Hypothesis 2 (H2).
Approach motivation will increase when viewing the designed versus the vacant site.

2. Materials and Methods

We utilized virtual reality (VR) to develop two immersive environments: an existing, urban, green vacant site in the South Clifton Park neighborhood of Baltimore City and that same green vacant site redesigned as a community greenspace. Using these two stimulus environments, we explored environmental impact on human restorativeness through self-reported perceived restorativeness, a psychological metric, and brain frequencies, a psychophysiological metric.

2.1. Within-Subject Experimental Design

An overview of the within-subject experiment study design is provided in Figure 1.
Prior to conducting this experimental study, a series of four vacant site images and four designed site images were captured from the same four eye-level perspectives at the site. Upon entering the study room, participants were given an overview of the study process and had an opportunity to ask questions. Participants were also reminded to limit any head or body movement throughout the data collection process. Participants then reviewed and completed an online consent form followed by a general information questionnaire with information focused on age, sex, and experience in VR.
Next, a 32-channel, including 2 mastoids M1 and M2, ANT Neuro Waveguard™ original EEG cap (ANT Neuro B.v., Hengelo, The Netherlands) was fitted according to the extended 10–20 international system with a ground electrode on AFz. The impedance of the electrodes was kept below 25 kΩ, and thirty EEG channels, excluding two mastoids, were re-referenced using a common average montage. The Oculus Quest 2 VR headset was placed over the EEG cap, and EEG data were continuously recorded at 500 Hz throughout the remainder of the study (Figure 2).
For Data Collection #1, baseline EEG conditions were collected with eyes open and eyes closed, each condition for 1 min. Following the baseline recordings, participants were shown a series of four images from one stimulus environment (vacant or designed). Before viewing an image, participants were asked not to move their head or body. Each image was shown for one minute, and in between each experiment image, a green image displaying the text “Please Wait” was presented.
Once the four experimental images were viewed, the VR headset was removed, and the participants completed a survey about VR side effects and 16 PRS questions [7]. The VR headset was re-fitted, and the participants completed Data Collection #2, which included the same process of acclimation, baseline conditions, and viewing four experimental images in matching image view order from the stimulus environment (vacant or designed) that was not seen in Data Collection #1. The VR headset was again removed, and the participants completed the same survey presented in Data Collection #1.
In this within-subjects design, each participant viewed a total of eight experimental images from two stimulus environments: four vacant site images and four designed site images. An image matrix was created to ensure that there was counterbalance between participants by sex in terms of the two stimulus environments and image view order to reduce the impact of order effects. This means that an equal number of male and female participants viewed the series of vacant site versus design site experimental images first. In addition, for each image, an equal number of male and female participants viewed the image in either the first, second, third, or fourth positions.

2.2. Participant Recruitment

A total of 21 students were recruited from a large Mid-Atlantic university to participate in this study; however, only 20 students’ data were utilized because of inadequate signal acquisition. Among them, 12 were female and 8 were male. Participant age ranged from 18 to 44 with an average age of 25 years old with a standard deviation of 6.6.

2.3. Experimental Images

A model of an existing, urban, green vacant site (0.22 acres) and the site as a redesigned community greenspace were built using Rhinoceros 3D 7 (Robert McNeel and Associates). The models were rendered using Lumion 12 (Act-3D B.v., Sassenheim, The Netherlands), and four images were captured from all sides of the site for the vacant and designed models from the same perspective. The images were exported from Lumion as large-format, stereoscopic, 360-degree panoramas. To create a boundary from the image and discourage participants from looking around in the VR headset, the images were all brought into Adobe Photoshop, and a black border was placed on the left and right sides of each image. Figure 3 exemplifies two-dimensional visualizations of the vacant versus designed site at one of the four perspectives participants viewed as part of the experimental study.

2.4. EEG Data Processing

The EEG data were processed using EEGLAB v2022.1 [52] and MATLAB (R2022b, The MathWorks, Inc.). After referencing and filtering, the power spectral densities were computed for each of the four, 60 second stereoscopic images using Welch’s method [53] utilizing a periodic hamming window of 4 s with 50% overlap and 4096 fast Fourier transform (FFT) points. The power spectra were approximated by applying the trapezoidal rule to each of six EEG frequency bands of interest—broadband alpha (8–13 Hz), alpha I (8–10 Hz), alpha II (10–13 Hz), broadband beta (13–30 Hz), beta I (13–20 Hz), and beta II (20–30 Hz). The alpha and beta frequencies were identified as frequencies of interest because alpha activity is associated with a relaxed but wakeful mind and beta activity is indicative of an alert and attentive mind [26].

2.5. Statistical Analysis

All data were analyzed using IBM SPSS Statistics 29 (IBM). For the PRS data, a Varimax Rotation factor analysis was conducted separately by stimulus environment (vacant and designed) to identify underlying common factors within the 16 PRS questions. The mean of each PRS factor by stimulus environment was determined by averaging the PRS score for each of the PRS questions associated with a factor per participant. Using SPSS Statistics, an outlier analysis identified outliers and extreme outliers within each PRS factor with an extreme outlier identified as being outside the range of 3rd quartile + 3*interquartile range or the 1st quartile—3*interquartile range [54]. Extreme outliers were removed from the analysis, and notably, if an outlier was found in one of the two stimulus conditions, then it was removed from both conditions for consistency. Descriptive statistics were determined for each factor in each stimulus environment. In addition, paired t-tests were performed to determine whether there were statistically significant differences between means by factor in the vacant versus designed stimulus environments.
After processing, the EEG data were aggregated into a mean power spectrum (PS) for each frequency of interest per participant by frontal and parietal areas. Specifically, F3 and F4 as well as F7 and F8 were aggregated for the frontal area, and P3 and P4 as well as P7 and P8 were aggregated for the parietal area. In addition, the normalized FAA was calculated in the midfrontal sites for the electrode pairings F3 and F4 and in the lateral frontal sites for F7 and F8 [43]. An outlier analysis, descriptive statistics, paired t-tests, and a repeated-measures analysis of variance (ANOVA) with sex as a between-subjects factor was completed for each brain frequency of interest in the frontal and parietal areas; however, only alpha was examined in the repeated-measures ANOVA for FAA.

3. Results

3.1. Perceived Restorativeness

3.1.1. Factor Analysis

The factor analysis for the vacant and designed sites identified three factors based on the PRS questions. Question 6 (“There is much to explore and discover here.”) and Question 12 (“I can do things I like here.”) were excluded from the vacant site factor analysis because the factor loading was less than 0.7. The three factors, Being Away/Fascination (six items), Extent (four items), and Compatibility (four items), were found to be highly reliable (α = 0.941; α = 0.915; α = 0.929, respectively). For the designed site factor analysis, Question 2 (“Spending time here gives a good break from my day-to-day routine.”) was excluded because the factor loading was less than 0.7, and Question 10 (“There is a great deal of distraction.”) was excluded because it was the only question within a factor. The three factors, Being Away/Fascination (six items), Extent (three items), and Compatibility (five items), were found to be highly reliable (α = 0.921; α = 0.897; α = 0.920, respectively).

3.1.2. Within-Subject Paired t-Test

The mean score of the factor Being Away/Fascination for the vacant site (M = 3.044, SD = 1.718, wherein M denotes mean and SD denotes standard deviation) was significantly lower than the mean score of the factor Being Away/Fascination for the designed site (M = 5.298, SD = 0.535); t (18) = −6.089, p < 0.001. In addition, the mean score of the factor Compatibility for the vacant site (M = 2.075, SD = 1.537) was significantly lower than the mean score of the factor Compatibility for the designed site (M = 4.560, SD = 1.156); t (19) = −6.019, p < 0.001. The mean score of the factor Extent, however, did not significantly differ between the vacant (M = 4.388, SD= 1.488) and the designed site (M = 4.617, SD = 1.276); t (19) = −6.019, p = 0.151 (Figure 4).

3.2. EEG Data

3.2.1. Pairwise t-Tests

A group of pairwise t-tests were computed to evaluate simple mean differences within the four photorealistic immersive 3D views for each perspective. To detect statistical significance within perspective, α was set at 0.05 and a Bonferroni correction was utilized to correct for multiple comparisons (i.e., α = 0.05 8 ). The result of this preliminary statistical testing was that there were no significant differences within the four stereoscopic images for either perspective. Since there were no significant differences between the four photorealistic immersive 3D views for either perspective, the group means were calculated to compare differences between each stimulus environment without added bias.

3.2.2. Within-Subject Paired t-Test and Repeated-Measures ANOVA

A within-subject paired t-test revealed no significant difference between means of the vacant versus designed spectral powers in the frontal or parietal electrodes. A within-subject repeated-measure ANOVA was also conducted to explore the impact of sex on the EEG spectral powers of participants between the two stimulus environments (Table 1).
For both frontal and parietal electrodes, the alpha powers were not significantly impacted by the stimulus environment or the relationships between the stimulus environment and sex. Regarding the frontal electrodes, the relationship between the stimulus environment and sex, however, had a marginally significant effect on the broadband beta, F (1,17) = 3.265, p = 0.088; beta I, F (1,17) = 3.692, p = 0.072; and beta II, F (1,17) = 3.073, p = 0.098; mean PS for the frontal electrodes F7 and F8. Specifically, the male broadband beta, beta I, and beta II mean PS decreased when viewing the vacant versus the designed site, yet the female broadband beta, beta I, and beta II mean PS increased (Figure 5).
Regarding the parietal electrodes, the relationship between the stimulus environment and sex had a marginally significant effect on the beta, F (1,16) = 3.565, p = 0.077, and beta I, F (1,16) = 4.289, p = 0.055, mean PS for the parietal electrodes P3 and P4. Again, the male broadband beta and beta I mean PS decreased when viewing the vacant versus the designed site; however, the female broadband beta and beta I mean PS increased (Figure 6).
The relationship between the stimulus environment and sex also had a marginally significant effect on the broadband beta, F (1,17) = 3.682, p = 0. 0.072; beta I, F (1,17) = 3.886, p = 0.065; and beta II, F (1,17) = 3.464, p = 0.080; mean PS for the parietal electrodes P7 and P8. Similarly, the male broadband beta, beta I, and beta II mean PS decreased when viewing the vacant versus the designed site, yet the female broadband beta, beta I, and beta II mean PS increased (Figure 7).

3.3. Frontal Alpha Asymmetry

Paired t-Test

There was a marginally significant difference in the PS for FAA in F7 and F8 electrodes for the vacant (M = −0.0310, SD = 0.1962) and designed site (M = −0.0793, SD = 0.1767); t (19) = 1.5268, p = 0.0721. Specifically, the FAA decreased when viewing the vacant versus the designed site: an indication of higher withdrawal motivation toward the designed site. There was no significant difference in the PS for FAA in F3 and F4 electrodes for the vacant (M = 4.388, SD = 1.488) and the designed site (M = 4.617, SD = 1.276); t (19) = −6.019, p = 0.151 (Table 2).

4. Discussion

This study examined the impact of virtual environments on psychophysiological and psychological metrics. More specifically, the study explored differences in alpha and beta brain activities in the frontal and parietal areas derived from EEG as well as perceived restorativeness for 20 participants when viewing an urban, green vacant site versus the site redesigned in virtual reality (VR). The alpha and beta frequency bands were identified as frequencies of interest because of their association with a relaxed but wakeful mind and an alert and attentive mind, respectively.
PRS results are consistent with Schutte et al. [20] demonstrating that an urban, designed greenspace is significantly more restorative than an urban, green vacant site. Specifically, the results demonstrate that this designed greenspace encourages effortless attention, provides a reprieve from a daily routine, and establishes relatedness to the environment as anticipated in H1a. This capacity for a designed greenspace to promote a restorative human experience illuminates the value of high-quality greenspaces in urban settings. This design, however, did not influence the sense of being in a different world, ART’s tenet of Extent. This lack of Extent may simply be explained by the small size of the site (0.22 acres), which did not allow study participants to feel fully engulfed by an alternate space. All the images shown in VR had some element of the urban context visible, which may have grounded the participant in an urban setting regardless of the changes to the environment. Additionally, the PRS survey resulted in three factors with the questions associated with Being Away and Fascination combined into a single factor while the factors Compatibility and Extent remained separate.
It is also noteworthy that this study’s factor groupings were different from the validated PRS four-factor groupings. This result might be the outcome of the following three factors: site scale, site content, and environmental typology. Previous researchers used relatively large urban and natural environments [8,20]; however, this study used a small site (0.22 acres). Unlike large environments, small sites may not be able to afford four different aspects of PRS. Second, the content of the site might affect the factor groupings. No previous studies tested the PRS scale on vacant lots. Vacant lots might be viewed differently than any other urban and natural environments. Finally, previous studies used the PRS scale to compare two different environments (e.g., urban vs. nature). This study compared the before and after of the same environment. This difference might influence different factor groupings. These factors highlight the need for additional refinement of the PRS questions that target each of the four tenets of ART separately.
The EEG alpha powers were not significantly altered by the two stimulus environments, which is counter to H1b. This result is similar to that of several studies exploring outdoor immersion in urban environments [55,56,57]; however, these results were not identified in the limited VR studies of the environment and brain states. One possible explanation for the lack of a significant change in alpha brain frequencies between stimulus environments is the degree of difference between the urban stimulus environments. Neale et al. [58] found no significant differences in alpha brain activity when comparing an urban quiet street versus an urban park and emphasized that both experiences were overall appealing. Similarly, the vacant and designed site both included vegetated areas with no additional sensory experience, such as noise, heat, or smell, so consistent levels of relaxation may have been present in both stimulus environments. This finding indicates that a complete examination of brain dynamics, not solely the alpha frequency band, is necessary to uncover the effects of natural environments on human psychophysiology.
The EEG beta powers also were not significantly altered by the two stimulus environments, which is counter to H1b. However, the beta powers demonstrated a marginally significant effect of sex in both the frontal and parietal areas. In both frontal and parietal electrodes, broadband beta, beta I, and beta II decreased when viewing the vacant versus the designed site for males, indicating a decrease in alert attention, but increased when viewing the vacant versus the designed site for females, indicating an increase in alert attention. This trend is not identified in the brain activity literature exploring environmental variables; however, researchers are beginning to unearth the effects of sex and environment on other aspects of physiological health, including stress [59,60,61]. The explanation for these results is currently unclear, but the results indicate that sex may play a role in our cognitive processing of environments. This finding should be more holistically explored to develop additional evidence for this trend of differential brain activity response to the environment based on sex. Specifically, given the low power of the study, increasing the sample size could help to reinforce the EEG interaction effects presented here.
Finally, there was a marginally significant difference in the mean FAA, specifically in the lateral frontal sites with F7 and F8 pairing, with the FAA decreasing when viewing the designed site. The trend in FAA signifies increased withdrawal motivation in the designed site, which is contradictory to H3 based on previous research on FAA, Stress Reduction Theory (SRT), and its association with approach–withdrawal motivation [1,3,44,45,46,47,48,49,50,51]. In addition, the trend of the approach–withdrawal motivation in stimulus environments was inversely related to feelings of perceived restorativeness. One possible explanation for this trend could be that while self-reported perceived restorativeness improved when viewing the designed images, the perceived restorativeness is not an appropriate indicator of a participant’s approach–withdrawal motivation. An understanding of a participant’s emotional response to an environment, through surveys like the Profile of Mood States (POMS) or Positive Affect Negative Affect Scale (PANAS), could identify underlying emotions that positively correlate with the findings on FAA within this study.
Experimental setting, equipment, and sampling limitations existed as a part of this study. The controlled experimental setting enabled the exploration of a human’s visual sensory experience of their environment; however, when exposed to an environment in-person, there are a variety of additional auditory and olfactory experiences occurring in tandem with the visual experience. This holistic impact of the environment was not measured within this study. Regarding equipment, the EEG cap used provided a user-friendly EEG experience; however, differences in head shape did cause challenges with some of the electrode placement for participants. In addition, visualization technology in virtual reality, although much improved, is still limited in the creation of a photorealistic image. Certain textures, colors, and qualities of the real environment were not successfully captured in virtual reality. In terms of sampling, a limited number of participants, predominantly with a knowledge of landscape architecture, were involved in the study due to time constraints. Additionally, solely one psychological and one psychophysiological metric was investigated during this study.

5. Conclusions

This study analyzed self-reported perceived restorativeness and EEG alpha and beta powers when viewing a virtual, vegetated, vacant site versus the virtual site as a redesigned greenspace. It fills research gaps because there are no comparative studies of an existing site that was redesigned; few studies have examined brain frequencies solely in urban areas; and there is limited research using VR.
This study is a key first step and provides methodology as well as previous research for a wide variety of future studies. Specifically, further research could create multiple design alternatives for the site in virtual reality to explore participant preference and perceived restorativeness through surveys. The percentage and structure of nature within these multiple design alternatives could also be quantified, using the Visible Green Index, identified in Zhu et al. [40], to understand preference in the degree of environmental greening. In addition, future research could utilize a larger sample size of participants to further assess the existing trends presented in this study regarding perceived restorativeness, brain activities, and FAA, potentially including participants living in the community of the actual site. Also, the incorporation of outdoor immersion could examine the influence of a multisensory experimental setting on brain activity. Finally, the inclusion of a survey quantifying emotional response could determine whether there is a predictive emotional response that correlates with the FAA and the approach–withdrawal motivation.
In the context of landscape architecture, this study provides evidence-based research validating the importance of designed, community greenspace in improving a human’s quality of life. Both physical and mental health are positively impacted by exposure to designed greenspaces, and this research, in concert with other studies, can help provide leverage for policy makers and communities to advocate for greenspace equity in their communities. Landscape architects, therefore, fulfill an essential role in the improvement of urban public health. The use of virtual reality has applications in research exploring the impact of designed greenspaces on public health, as demonstrated within this study, providing opportunities to facilitate the design development of greenspaces and presenting a full, immersive representation of a design to community members and clients.

Author Contributions

Conceptualization, A.S., B.-S.K. and C.D.E.; methodology, A.S., B.-S.K., C.D.E. and H.O.; validation, A.S., B.-S.K., H.O. and K.P.; investigation, A.S.; resources, B.-S.K.; data curation, A.S. and K.P.; writing—original draft preparation, A.S.; writing—review and editing, B.-S.K., C.D.E., H.O. and K.P.; visualization, A.S.; supervision, B.-S.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the University of Maryland Teaching and Learning Grant for 2022.

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of the University of Maryland College Park (1929610-3 and 30 August 2022).

Informed Consent Statement

Written informed consent was obtained from the participants to publish this paper.

Data Availability Statement

The data are contained within the article.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Within-subject experimental study design conducted for each participant.
Figure 1. Within-subject experimental study design conducted for each participant.
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Figure 2. Experimental study design conducted for each participant.
Figure 2. Experimental study design conducted for each participant.
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Figure 3. Experimental study visualizations from one site perspective looking southeast: (a) vacant site visualization and (b) designed site visualization.
Figure 3. Experimental study visualizations from one site perspective looking southeast: (a) vacant site visualization and (b) designed site visualization.
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Figure 4. Mean perceived restorativeness scores for each factor by stimulus environment: (a) mean being away/fascination; (b) mean compatibility; and (c) mean extent.
Figure 4. Mean perceived restorativeness scores for each factor by stimulus environment: (a) mean being away/fascination; (b) mean compatibility; and (c) mean extent.
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Figure 5. Graphs of mean PS for frontal electrodes F7 and F8 in the vacant and designed stimulus environments: (a) mean beta; (b) mean beta I; and (c) mean beta II.
Figure 5. Graphs of mean PS for frontal electrodes F7 and F8 in the vacant and designed stimulus environments: (a) mean beta; (b) mean beta I; and (c) mean beta II.
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Figure 6. Graphs of mean PS for parietal electrodes P3 and P4 in the vacant and designed stimulus environments: (a) mean beta; (b) mean beta I.
Figure 6. Graphs of mean PS for parietal electrodes P3 and P4 in the vacant and designed stimulus environments: (a) mean beta; (b) mean beta I.
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Figure 7. Graphs of mean PS for parietal electrodes P7 and P8 in the vacant and designed stimulus environments: (a) mean beta; (b) mean beta I; and (c) mean beta II.
Figure 7. Graphs of mean PS for parietal electrodes P7 and P8 in the vacant and designed stimulus environments: (a) mean beta; (b) mean beta I; and (c) mean beta II.
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Table 1. Results of a paired t-test showing the difference in EEG spectral powers between the two stimulus environments in the frontal and parietal electrodes.
Table 1. Results of a paired t-test showing the difference in EEG spectral powers between the two stimulus environments in the frontal and parietal electrodes.
Frontal
Spectral PowerSourceSSdfMSFSig.
Beta_F7F8Stimulus Environment0.003821610.00382160.3680.552
Stimulus Environment x Sex0.033946610.03394663.2650.088 *
Error (Stimulus Environment)0.1767241170.0103955
Beta I_F7F8Stimulus Environment0.000159210.00015920.3080.586
Stimulus Environment x Sex0.001910410.00191043.6920.072 *
Error (Stimulus Environment)0.0087975170.0005175
Beta II_F7F8Stimulus Environment0.002410810.00241080.3820.545
Stimulus Environment x Sex0.019389410.01938943.0730.098 *
Error (Stimulus Environment)0.1072637170.0063096
Parietal
Spectral PowerSourceSSdfMSFSig.
Beta_P3P4Stimulus Environment0.00001360910.0000136090.6010.449
Stimulus Environment x Sex0.00008071010.0000807103.5650.077 *
Error (Stimulus Environment)0.000362242160.000022640
Beta I_P3P4Stimulus Environment0.00000064110.0000006410.4970.491
Stimulus Environment x Sex0.00000553710.0000055374.2890.055 *
Error (Stimulus Environment)0.000020654160.000001291
Beta_P7P8Stimulus Environment0.00027494910.0002749490.0890.769
Stimulus Environment x Sex0.01140484610.0114048463.6820.072 *
Error (Stimulus Environment)0.052652411170.003097201
Beta I_P7P8Stimulus Environment0.00000600710.0000060070.0380.848
Stimulus Environment x Sex0.00061924710.0006192473.8860.065 *
Error (Stimulus Environment)0.002709286170.000159370
Beta II_P7P8Stimulus Environment0.00019863010.0001986300.1050.750
Stimulus Environment x Sex0.00657825010.0065782503.4640.080 *
Error (Stimulus Environment)0.032280665170.001898863
* p < 0.1.
Table 2. Results of a paired t-test showing the difference in FAA between the two stimulus environments.
Table 2. Results of a paired t-test showing the difference in FAA between the two stimulus environments.
tdtOne-Sided pTwo-Sided p
V_AAsym_F7F8 − D_AAsym_F7F81.5268180.0721 *0.1442
* p < 0.1.
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Seiz, A.; Kweon, B.-S.; Ellis, C.D.; Oh, H.; Pietro, K. Exploring the Psychophysiological Effects of Viewing Urban Nature through Virtual Reality Using Electroencephalography and Perceived Restorativeness Scale Measures. Sustainability 2023, 15, 13090. https://doi.org/10.3390/su151713090

AMA Style

Seiz A, Kweon B-S, Ellis CD, Oh H, Pietro K. Exploring the Psychophysiological Effects of Viewing Urban Nature through Virtual Reality Using Electroencephalography and Perceived Restorativeness Scale Measures. Sustainability. 2023; 15(17):13090. https://doi.org/10.3390/su151713090

Chicago/Turabian Style

Seiz, Audrey, Byoung-Suk Kweon, Christopher D. Ellis, Hyuk Oh, and Kyle Pietro. 2023. "Exploring the Psychophysiological Effects of Viewing Urban Nature through Virtual Reality Using Electroencephalography and Perceived Restorativeness Scale Measures" Sustainability 15, no. 17: 13090. https://doi.org/10.3390/su151713090

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