With the support of our generous members, donors, and volunteers, we were able to accomplish a tremendous amount in 2019. Please click below to watch a special video ‘thank you’ recorded by DMRF Executive Director Janet Hieshetter which details the many accomplishments that were made possible this year. If you have not yet made your […]
Dystonia is more than a diagnosis. It's a journey.
Non-profit evaluator Charity Navigator has once again awarded the Dystonia Medical Research Foundation (DMRF) with the top 4-star rating. Charity Navigator bases its rating on an organization’s financial health and commitment to accountability and transparency. Thank you for trusting the DMRF with your donations and support. Together, we will find a cure for dystonia. The […]
This article appeared in the Dystonia Dialogue. “In my family, we were all aware that my father had a problem with his hands,” explained Carole Rawson, “and my parents’ generation was one in which, if there was something bad going on, you didn’t talk about it. He was very closed-lipped about it.” Carole’s father went […]
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Current Dystonia Research Investigations
Striatal Neuron Activity Patterns in Dystonia
The causes of dystonia are not clearly understood but abnormal signaling within the striatum, a region of the brain that controls movement, is thought to be involved. It is now possible to record the firing patterns of dozens of neurons simultaneously in the striatum of awake dystonic mice to reveal the abnormal neural code associated with dystonia. Technology known as in vivo microscopy will be used in mice with dystonia to visualize the firing patterns of neurons within the striatum. Mice will be recorded while they are dystonic and after they have been treated with drugs that alleviate the dystonia. By comparing the different firing patterns with and without dystonia, these experiments will reveal the neural code associated with dystonia for the first time. In the short term, these experiments will provide important information that could be useful to guide stimulation parameters for deep brain stimulation in dystonia patients. In the long-term, understanding the neural code of dystonia will provide important information for the development of novel therapeutics that target the abnormal neural code.
Machine Learning Guided Deep Brain Stimulation to Cure Neurological Disease
The DMRF is partnering with Jesse H. Goldberg, MD, PhD of Cornell University on a project to engineer a revolutionary new generation of deep brain stimulation (DBS) devices to treat dystonia and other neurological diseases.
Dystonia results from abnormal brain activity that can be corrected by direct electrical stimulation of dysfunctional brain pathways. In current DBS systems, an implanted medical device delivers continuous stimulation to the brain and adjustments to the stimulation must be made using a remote control device in the hands of a highly trained clinician. A major obstacle to providing patients with maximum benefit from this therapy is knowing where in the brain to stimulate and tailoring stimulation parameters to the unique needs of each patient.
Dr. Goldberg proposes a radically new approach to DBS. He is using artificial intelligence to develop a system in which a computer, interconnected with the brain, figures out exactly how and where to stimulate to restore normal movement.
In this three-year project, Dr. Goldberg will establish the feasibility of this concept in mice. He is collaborating with Mert Sabuncu, PhD in the School of Electrical and Computer Engineering and School of Biomedical Engineering at Cornell University.
Three-Dimensional Network Architecture of Dystonia
Brain imaging techniques have advanced the understanding of metabolic network abnormalities in inherited and sporadic dystonia. It remains elusive, however, whether dystonia-related brain networks can be identified with resting state functional MRI (magnetic resonance imaging) utilizing time-series information. It is also unclear whether such networks relate to underlying anatomical connections. Dr. Vo hypothesizes that dystonia is characterized by distinct functional and structural network topographies in the resting state. To test this hypothesis, she and her team will examine resting state functional MRI and diffusion MRI data in patients with inherited and sporadic dystonia. The proposed work will advance the understanding of brain network architecture in dystonia. The new information will help identify areas within the network space for optimal therapeutic targeting and individually customized treatment.