Identifying Brain-Wide Network Disruptions That Underlie Alzheimer's Disease

The main aim of this project is to identify brain-wide changes in neural networks that contribute to Alzheimer’s disease and use these to better inform deep brain stimulation interventions.

Alzheimer’s disease has effects throughout the brain, changing how different regions connect and communicate. These changes in brain-wide networks can vary from person to person, though, calling for ways to individualize therapies that target them.

Ariel Gilad, PhD, and colleagues aim to define important target regions while considering individual features as a first step toward using deep brain stimulation to treat Alzheimer’s disease. This kind of therapy involves the implantation of electrodes in specific brain areas for therapeutic stimulation.
Working with lab models of Alzheimer’s disease, the group will record brain network activity during the completion of cognitive tasks. The researchers plan to follow these patterns throughout each subject’s lifespan to learn more about how individual traits affect these brain networks in Alzheimer’s disease. They will map numerous brain regions simultaneously that have never been analyzed at the same time in these models.

The work will rely on state-of-the-art tools for following brain network activity as lab subjects freely move about and solve cognitive tasks. Many of the regions that Dr. Gilad and his team will monitor have rarely been studied in Alzheimer’s disease.

The ultimate goal of this innovative, expansive study is to identify target brain regions for deep brain stimulation, which, if successful, could lead to individualized treatments for Alzheimer’s disease.

The multi-fiber technique used in this study is currently a state-of-the-art method to capture brain-wide networks in freely moving mice. We are able to simultaneously record from dozens of areas, most of them have seldom been studied in the AD field. Second, studying brain-wide networks at the longitudinal and individual levels requires is highly innovative in the AD field.

We will provide basic understanding to brain-wide network dysfunctions which will unravel the mechanisms underlying AD. Our work may discover network dysfunctions that emerge at a preclinical phase, involving specific areas in certain individuals, and may aid in early detection of AD. From a clinical perspective, we will provide a sub-network of personal areas that may be used in noninvasive brain stimulation for individual AD patients, aiding in the development of an effective treatment for AD.