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2020 Alzheimer's Association Research Grant (AARG)

A Computational Approach to Predict Early Symptoms of AD

Does an advanced computer science model predict the onset of Alzheimer’s?

Syed Abid Hussaini, Ph.D.
Columbia University Medical Center
New York, NY - United States


The lateral entorhinal cortex (or LEC), is a brain region that functions as a hub for the formation of memories, object recognition and navigation among other tasks. Studies show that the LEC is one of the first brain regions impacted in Alzheimer’s. Researchers have shown that misplacing items and disruption of sensory systems, such as smell may occur early in Alzheimer’s; these are examples of functions that involve the LEC area of the brain. However, the biological mechanisms that make the LEC more vulnerable to these early brain changes in Alzheimer’s remains unclear. 

Dr. Syed Abid Hussaini and colleagues will use two types of genetically engineered Alzheimer’s-like mouse models to study the role of LEC in early brain changes in Alzheimer’s. These models aim to simulate the two hallmark brain changes seen in Alzheimer’s, the buildup of beta-amyloid plaques and clumping of tau in tangles. These changes occur initially in the entorhinal cortex region of the brain. Preliminary work by Dr. Hussaini’s team shows that both these animal models experience cognitive impairments as they get older.

Research Plan

Building on their preliminary results, Dr. Hussaini’s team will use sophisticated ways to measure and analyze changes in the nerve cell activity in the LEC region in the mice. They will evaluate these changes while the animals perform virtual reality tests of memory. Using an advanced computer science technique called machine learning, the researchers will analyze these recordings and predict how abnormalities in nerve cell activity may indicate changes in the functionality of the nerve cells in the LEC. 

Dr. Hussaini believes that changes in nerve cell activity in the LEC may impact the mouse’s ability to recognize objects and odors, which could be associated with brain changes observed in early Alzheimer’s.  


If successful, these results may generate novel approaches to identify the earliest brain changes observed in Alzheimer’s. Families facing Alzheimer’s now and in future will benefit greatly from early detection, allowing for important care and planning. Furthermore, when we have new therapies, we will be in a better position to know who needs treatment at the earliest time point.

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