Closed-Loop Attention Restoration Theory for Virtual Reality-Based Attentional Engagement Enhancement

Abstract

Today, as media and technology multitasking becomes pervasive, the majority of young people face a challenge regarding their attentional engagement (that is, how well their attention can be maintained). While various approaches to improve attentional engagement exist, it is difficult to produce an effect in younger people, due to the inadequate attraction of these approaches themselves. Here, we show that a single 30-min engagement with an attention restoration theory (ART)-inspired closed-loop software program (Virtual ART) delivered on a consumer-friendly virtual reality head-mounted display (VR-HMD) could lead to improvements in both general attention level and the depth of engagement in young university students. These improvements were associated with positive changes in both behavioral (response time and response time variability) and key electroencephalography (EEG)-based neural metrics (frontal midline theta inter-trial coherence and parietal event-related potential P3b). All the results were based on the comparison of the standard Virtual ART tasks (control group, n = 15) and closed-loop Virtual ART tasks (treatment group, n = 15). This study provides the first case of EEG evidence of a VR-HMD-based closed-loop ART intervention generating enhanced attentional engagement.

Attention Detection in Virtual Environments Using EEG Signals: A Scoping Review

“…As future direction, we can list the main recommended aspects that surround and must follow attention detection/investigation through EEG-signal: identify attention allocation through N100, N200, P100 and P300 in fronto-central-occipital brain areas (Vogt et al, 2015;Jaquess et al, 2017); P300 in fronto-parietal brain areas (Rohani and Puthusserypady, 2015;Vogt et al, 2015;Yu et al, 2015;Causse et al, 2016;Chen et al, 2016;Lamti et al, 2016;Jaquess et al, 2017;Chung et al, 2018;Li et al, 2020d) and SSVEP component in occipital area (Leite et al, 2018;Chu and D'Zmura, 2019) as we cited in Figure 3; x. Investigate attention by means of brain waves increase, decrease and beta (12-31.25 Hz)/theta (3-8 Hz) ratio in fronto-parietal brain areas, θ (Clemente et al, 2014;Fuentes-García et al, 2019;Lim et al, 2019), in occipital area, θ (Savage et al, 2013), in frontal area, αβθδ (Clemente et al, 2014;Cowley and Ravaja, 2014;Jagannath and Balasubramanian, 2014;Yin and Zhang, 2014;Lee et al, 2015;Hazarika et al, 2018;Lim et al, 2019;Li et al, 2020d) as we cited in Figure 3.…”

“…Investigate attention by means of ERP components to identify attention allocation through N100, N200, P100 and P300 in fronto-central-occipital brain areas ( Vogt et al, 2015 ; Jaquess et al, 2017 ); P300 in fronto-parietal brain areas ( Rohani and Puthusserypady, 2015 ; Vogt et al, 2015 ; Yu et al, 2015 ; Causse et al, 2016 ; Chen et al, 2016 ; Lamti et al, 2016 ; Jaquess et al, 2017 ; Chung et al, 2018 ; Li et al, 2020d ) and SSVEP component in occipital area ( Leite et al, 2018 ; Chu and D’Zmura, 2019 ) as we cited in Figure 3 ;…”

“…the states of concentration and immersion were compared at engrossment level, in the concentration task, a specific point on the screen was required for focus, while in the immersion task the task was to control the entire game. Significant differences in α, θ, and β were identified for the different tasks (Lim et al, 2019); In HMD systems investigations, at total immersion level: to assess the theory of attention restoration (ART) in two different groups, given the variable response time and EEG, θ and parietal P3b metrics (Li et al, 2020d) and when faced with passive auditory stimuli, in the assessment of mismatch negativity (MMN)/P3a (Chung et al, 2018), pointing to highly restorative experience; in six different virtual environments (Gao et al, 2019), identifying improvements in the state of restoration and fatigue relief; (Peterson et al, 2018) analyzed individuals during exposure or not to VR by HMD during beamwalking, as a result, through peaks of EEG amplitude, they found that VR exposure may increase physiological stress during dynamic balance tasks and may impair physical and cognitive performance during balance; in addition to the investigation of feature-based attention (FBA) through SSVEPs (Chu and D'Zmura, 2019), pointing out that these potentials are strongly influenced by flicker stimulus in the peripheral visual field.…”

“…None of the studies cited on ART in a recent review ( Ohly et al, 2016 ) reported neural data related to the attention restoration process. After the aforementioned review article, the authors Chung and Li ( Chung et al, 2018 ; Li et al, 2020d ) present in their work studies exploring ART and EEG neural signals. Both found variations in the evoked potential P3 in exposures to virtual environments with simulation of nature, in 5 and 30 min, respectively, for the cited studies.…”

Exploring the feasibility of mitigating VR-HMD-induced cybersickness using cathodal transcranial direct current stimulation

“…Thus, a multimodal objective measurement can be planned for future study. This is especially pertinent given the progress on AI-based physiological feature learning for VR application [29] and highly-integrated research-grade [30] or commercial [31] VR-biosensing platforms.…”