Predicting Patterns in Real-time Cognitive Performance in Neurodegenerative Disease

Spring 2018 RESEARCH INCUBATION AWARDEE

PI: Alice Cronin-Golomb, Professor, Psychological & Brain Sciences

Co-PI: Daniel Fulford, Assistant Professor, Occupational Therapy, SAR; Vijaya Kolachalama, Assistant Professor, Medicine, MED

The challenge

There has been a global rise in life expectancy and a decline in fertility; thus there has been an increasing number of people older than 65 years in the population. This has consequently increased age-related neurodegenerative diseases such as dementia, cerebral vascular disease, and Lewy body disease. Studies have been conducted to explore the risk factors that expose people to such diseases, while only a few companies have been able to reverse the deterioration caused by neurodegenerative diseases successfully.

The Solution

Since most of these diseases are not curable, the identification of the risk factors and pathogenesis that exposes certain people to these diseases is crucial. Some of the risk factors associated with these diseases include genetics, epigenetics, lifestyle, and environmental factors. Predicting the occurrence of such disease before they occur goes a long way in ensuring that the older adults exposed decreases exponentially.

The Process

Of course, the prediction of whether the risk factors apply to all people will require the review of past studies that focused on the predictability of neurodegenerative diseases. Further, studies that dealt with all the risk factors and the measurement of the cognitive performance will be reviewed to sufficiently inform the process of predicting the occurrence of neurodegenerative diseases.