OSCOFAI at a Glance
Sleep health and circadian regulation may be targets for early intervention to attenuate rates of cognitive decline. However, it is unclear which aspects of sleep, are the most critical in cognitive decline as well as the underlying mechanisms.
OSCOFAI Aims
Aims of the proposed research, which combines state-of-the-art machine learning techniques with clinical characteristics and biomarker discovery tools, are:
- to explore the associations between sleep-wake cycle data and cognitive function cross-sectionally and longitudinally.
- to create a predictive modelling tool of cognitive function using advanced signal processing and machine learning methods, by analysing the objective sleep measurements and other clinical assessment data.
- to investigate the potential mediating mechanisms, by the extensive biomarkers’ characterization, between sleep-wake actigraphy and cognition, using traditional statistical methods as well as machine learning analyses.
OSCOFAI Methodology
The population of the study will be drawn from an on-going, longitudinal study, the ALBION, conducted in older and middle-aged adults. Participants will receive a comprehensive neuropsychological and neurological assessment and diagnoses of dementia and mild cognitive impairment will be set. Also, cerebrospinal fluid and blood samples will be obtained, participants will receive a brain MRI scan and will use a wrist actigraphy, which objectively records sleep parameters.
OSCOFAI Impact
The proposed project will shed light to the connection between sleep parameters and cognitive function and to the underlying pathophysiological mechanisms, providing valuable information for the development of relevant tailored interventions for healthy aging.