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Mahfoud, D.

Publications and source records attributed to Mahfoud, D..

2 recordsLinked to original sources

Pre-task light exposure primes higher-order cognition and preserves mood

Light is a fundamental regulator of human physiology and behaviour. Whether prior light exposure shapes subsequent higher-order cognition and mood beyond the period of exposure remains unknown. We tested this in a within-subject, randomised crossover experiment in which 24 healthy young adult males completed a multimodal cognitive battery following 2x15 min of full-spectrum light (FL; median 1,029 melanopic equivalent daylight illuminance [mEDI]) or standard indoor light (SL; median 234 mEDI), with all testing conducted under identical dim illumination. FL improved Digit-Symbol Substitution Test accuracy and promoted digit-directed gaze reallocation, consistent with more efficient associative encoding. On the Balloon Analogue Risk Task, FL reduced reward-seeking behaviour and suppressed backward-referencing gaze transitions linking current and prior-trial reward information. Mood declined following SL but remained stable after FL. Sustained attention, vigilance, and subjective sleepiness were unaffected. Our findings identify pre-task FL exposure as a selective primer of higher-order cognition and mood, independent of alertness.

neuroscience↗

Human-Perception-Aligned Machine Learning for Indoor-Outdoor Classification

Daylight is vital for eye, brain, and overall health, yet misperceptions of what constitutes true outdoor daylight exposure can lead to poor behavioural choices and weaken public health recommendations. We developed InNOut, a perception-aligned machine learning model trained on 73,879 minutes of multispectral light data to classify environments as indoor or outdoor, and benchmarked against public (n = 383) and expert (n = 17) judgments across 183 scenes. InNOut achieved excellent performance (AUC = 0.92 [95% CI, 0.92-0.93], sensitivity 73.9%, specificity 94.5%), closely aligning with expert (83.5%) and public (80.8%) judgments. Clear outdoor and indoor scenes were reliably classified, whereas ambiguous settings (e.g., windowed rooms, vehicles) were often judged indoor by participants but outdoor by the model, consistent with their spectral light profiles. InNOut bridges perception and measurement, offering a scalable means to map light environments and inform digital interventions in medicine and public health.

physiology↗