There is solid neurophysiological evidence indicating that abnormal brain rhythms during sleep and noradrenergic dysfunction are core components of cognitive decline and AD onset, and their related pathophysiology. Crucially, irregularities in these neurophysiological mechanisms appear to occur in an asymptomatic and pre-symptomatic stage, but their potential to identify susceptibility for triggering neurodegeneration has yet to be established.~Thus, the possibility to identify such risk biomarkers in humans will require the acquisition of large-scale data related direct or indirect measurements of these physiological signatures. A possible key source to obtain such large-scale data related to sleep and noradrenergic function is the assessment of electroencephalographic recordings through non-obtrusive, low-cost, and reliable wearable sensors, alongside the use of advanced neuro-computational algorithms that link brain function and behavioral outcomes of LC function via pupilometry measurements.
Data collection based on this study will allow us to collect neurophysiological and cognitive data collected from in-ear EEG recordings of the Autosomal dominant alzheimer's disease population in Colombia