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. 2024 Jan 8:17:1286854.
doi: 10.3389/fnins.2023.1286854. eCollection 2023.

Towards ubiquitous and nonintrusive measurements of brain function in the real world: assessing blink-related oscillations during simulated flight using portable low-cost EEG

Affiliations

Towards ubiquitous and nonintrusive measurements of brain function in the real world: assessing blink-related oscillations during simulated flight using portable low-cost EEG

Alexia Ziccardi et al. Front Neurosci. .

Abstract

Blink-related oscillations (BRO) are newly discovered neurophysiological phenomena associated with spontaneous blinking and represent cascading neural mechanisms including visual sensory, episodic memory, and information processing responses. These phenomena have been shown to be present at rest and during tasks and are modulated by cognitive load, creating the possibility for brain function assessments that can be integrated seamlessly into real-world settings. Prior works have largely examined the BRO phenomenon within controlled laboratory environments using magnetoencephalography and high-density electroencephalography (EEG) that are ill-suited for real-world deployment. Investigating BROs using low-density EEG within complex environments reflective of the real-world would further our understanding of how BRO responses can be utilized in real-world settings. We evaluated whether the BRO response could be captured in a high-fidelity flight simulation environment using a portable, low-density wireless EEG system. The effects of age and task demands on BRO responses were also examined. EEG data from 30 licensed pilots (age 43.37 +/- 17.86, 2 females) were collected during simulated flights at two cognitive workload levels. Comparisons of signal amplitudes were undertaken to confirm the presence of BRO responses and mixed model ANOVAs quantified the effects of workload and age group on BRO amplitudes. Significant increases in neural activity were observed post-blink compared to the baseline period (p < 0.05), confirming the presence of BRO responses. In line with prior studies, results showed BRO time-domain responses from the delta band (0.5-4 Hz) consisting of an early negative peak followed by a positive peak post-blink in temporal and parietal electrodes. Additionally, task workload and age-related effects were also found, with observations of the enhancement of BRO amplitudes with older age and attenuation of BRO responses in high workloads (p < 0.05). These findings demonstrate that it is possible to capture BRO responses within simulated flight environments using portable, low-cost, easy-to-use EEG systems. Furthermore, biological and task salience were reflected in these BRO responses. The successful detection and demonstration of both task-and age-related modulation of BRO responses in this study open the possibility of assessing human brain function across the lifespan with BRO responses in complex and realistic environments.

Keywords: aviation; blink-related oscillations (BRO); cognitive state; electroencephalography (EEG); flight simulation; mental workload; neuroergonomics; real world.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Cessna 172 simulator cockpit controls and visual displays.
Figure 2
Figure 2
Segmented workload conditions.
Figure 3
Figure 3
Artifact denoising procedure.
Figure 4
Figure 4
Sample participant’s segmented trials before (left) and after (right) artifact removal.
Figure 5
Figure 5
Ratio of amplitude variance between the 0 point and baseline point before (left) and after (right) cleaning.
Figure 6
Figure 6
Key time frames of interest from the T8 electrode.
Figure 7
Figure 7
C1-C2 components baseline comparisons for the P7 electrode.
Figure 8
Figure 8
C1-C2 components baseline comparisons for the P8 electrode.
Figure 9
Figure 9
C1-C2 components baseline comparisons for the T7 electrode.
Figure 10
Figure 10
C1-C2 components baseline comparisons for the T8 electrode.
Figure 11
Figure 11
BRO C2 component: workload and age effects.
Figure 12
Figure 12
P8 electrode-BRO for age and workload. Waveforms smoothed using a frequency filter of 7 Hz and individual files removed where any of the waveform amplitude values exceeded 5 μV.
Figure 13
Figure 13
BRO C1 component workload and age effects (T8).
Figure 14
Figure 14
BRO C2 component workload and age effects (T8).
Figure 15
Figure 15
T8 electrode-BROs for age and workload. Waveforms smoothed using a frequency filter of 7 Hz and individual files removed where any of the waveform amplitude values exceeded 5 μV.

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