Towards real-world neuroscience using mobile EEG and augmented reality.

Area of Science:

• Neuroscience
• Cognitive Science
• Human-Computer Interaction

Background:

• Traditional cognitive studies often isolate participants from real-world environments.
• This limits understanding of neurocognitive processes in naturalistic settings.
• Mobile EEG (mEEG) and augmented reality (AR) offer potential solutions for ecological research.

Purpose of the Study:

• To investigate neurocognitive processes in real-world environments using a combined mEEG and AR approach.
• To maintain experimental control over perception within naturalistic settings.
• To validate the mEEG-AR paradigm using a known cognitive effect.

Main Methods:

• Participants underwent three electroencephalography (EEG) tasks involving viewing upright and inverted faces.
• Tasks included a lab-based computer setup, viewing real face images while walking, and viewing virtual faces via AR while walking.
• Data analyzed using epoch-based and generalized linear model (GLM)-based approaches.

Main Results:

• Greater low-frequency EEG activity was observed for inverted compared to upright faces across all tasks.
• This finding demonstrates the extraction of cognitively relevant signals using mEEG and AR.
• Both epoch-aligned and continuous EEG analyses confirmed the results.

Conclusions:

• The combined mEEG and AR approach is effective for studying neurocognitive processes in real-world environments.
• This methodology allows for experimental control within naturalistic settings.
• This research opens new avenues for ecological cognitive neuroscience.