With age, skills related to cognitive function are affected, resulting in decreased speed of processing, working memory capacity, inhibitory function and long-term memory. With dementia, these skills are further impacted. Atypical decreases in function do not necessarily manifest in all aspects of cognitive function simultaneously, but specific aspects can decline years prior to the diagnosis of dementias, such as Alzheimer’s disease (AD). Ideally, we would want to identify these declines before the disease fully manifests in all aspects, as this is key for early diagnosis of amnesic Mild Cognitive Impairment (aMCI), the preceding stage of AD. However, identifying these early declines require large studies covering decades of potential neurodegeneration. A complementary approach is to identify atypical age-related changes in cognitive function in healthy aging. This approach derived from healthy aging (with expected small changes) could potentially be applied to aMCI and AD populations (with expected larger changes) to identify inflection points of cognitive function worsening.
Electrophysiology (EEG or “brainwave recording”) is a well-established clinical biomarker with a strong literature linking it to screening, detection and tracking of MCI, AD, and other dementias, as well as age-related changes. However, most current studies on cognition in aging suffer from lack of personalised measures, or lack of data across days, months, years to identify changes over time. Therefore, in this project a new measurement of typical and atypical cognition in aging was developed, which capitalised on repeated assessments accompanied with EEG recordings, collected by Cumulus Neuroscience, Ltd.
Cumulus Neuroscience has developed a medical-device certified system of wearable EEG paired with engaging tablet-based tasks, and a supporting cloud infrastructure to securely collect and extract insights from the resulting data, yielding neurocognitive markers that are sensitive even to the subtle effects of healthy aging. Cumulus has designed gamified versions of gold-standard neuro-psychological tests that can be used in conjunction with wireless EEG. With its high participant-adherence, high system usability and high data quality, the Cumulus’ platform is suitable for identifying predictive models of cognitive (dys-) function on a large scale.
This project aimed to identify a personalised predictive model of cognitive function in older adults using a home-based EEG system and advanced machine learning methods. This required the development and identification of data selection approaches suitable for dry-EEG data to achieve data of good quality; the identification of models that model practice effects from repeated measurements; the identification of an EEG-base model of cognitive function in older adults; and the identification of a predictive EEG-based model of cognitive function in older adults three years later.
