Dystonia is a network disorder

Several groups study functional changes in dystonia using neurophysiological approaches studying the entire human or animal brain. William Hutchison at Toronto Western Hospital (Canada) studies tremor, oscillations and synaptic plasticity in dystonia patients undergoing DBS. Intervention by chronic DBS in the globus pallidus internus (GPi) has been found beneficial in treating severe cases of dystonia but the mechanisms underlying the pathophysiology and the DBS treatment are poorly understood. This study seeks to better understand how and why DBS works. The researchers use microelectrode recordings of dystonia patients to investigate cell activity in an area of the brain called the globus pallidus. In addition, they use microstimulation to determine whether there are functional abnormalities in inhibitory processes at neurosurgical target sites. They obtain synaptic plasticity measures and correlate these to the type and severity of dystonia. The goal is to gain insight into the mechanisms of tremor and dystonia. The researchers hope to possibly translate this knowledge to develop new targets for pharmacological intervention.

Synaptic plasticity, a complex feature of the brain, is also studied by Alexandra Nelson at the University of California San Francisco. This study uses a new mouse model of dystonia based on a genetic form of the human disease called paroxysmal kinesigenic dystonia (PKD), to dissect how the connection between cells is altered, putting patients at risk of developing dystonia. They test the movement of PKD model mice versus their healthy siblings, looking for evidence of dystonia. They are also making recordings of the connections between cells in two brain regions believed to contribute to dystonia: the striatum and the cerebellum hoping that this study will form the foundation for a larger research program aimed at understanding the fundamental cellular and circuit changes that cause dystonia, so that new and more effective drugs or brain stimulation approaches can be developed.

Giuseppe Sciamanna at the University of Rome tor Vergata (Italy) explores another aspect of DYT1 dystonia pathophysiology studying alterations of the basal ganglia circuit. By means of electrophysiological, optogenetic, and biochemical approaches, this project investigates in a mouse model of DYT1 dystonia, potential abnormality in neural activity of specific neurons together with alterations of mutual synaptic connection between them. The project characterizes, for the first time, the role of basal ganglia in the pathogenesis of dystonia by investigating how the interaction among distinct basal ganglia nuclei may be altered. This represents a crucial step to understand the cellular basis of dystonic symptoms.

A very innovative approach is taken by Ellen Hess at Emory University to study the brain of dystonic mice. Although the causes of dystonia are not understood, we know that there is abnormal signaling within the striatum, a region of the brain that controls movement. It is now possible to record the firing patterns of dozens of neurons simultaneously in the striatum of awake dystonic mice to show the abnormal pattern (neural code) associated with dystonia. Using a novel technique of in vivo microscopy in mice with dystonia it is possible to visualize the firing patterns of neurons within the striatum. By comparing the different firing patterns with and without dystonia, the neural code associated with dystonia will be revealed for the first time. Understanding this code of dystonia will provide information for the development of novel therapeutics that target the abnormally functioning brain.

Aasef Shaikh at Case Western Reserve University is testing a new, bold hypothesis by studying cervical dystonia patients. Cervical dystonia, the most common form of dystonia, is believed to be caused by abnormal activity in the basal ganglia, a part of the brain that coordinates movement. However, new studies are suggesting that impairments to the cerebellum, the part of the brain that controls coordination, and sense of body position (proprioception) can cause dystonia as well. Dr. Shaikh hypothesizes that these three brain functions—cerebellum, basal ganglia, and proprioception—work together as a ‘unifying network’ to influence the control of head movements. His study focuses on proprioception and the effect that neck vibration. The goal is to define non-invasive, painless, and cost-effective therapies based on a novel, unifying network model detailing the biological mechanisms of cervical dystonia.

A different holistic approach based on brain imaging is undertaken by An Vo at the Feinstein Institute for Medical Research. Brain imaging techniques have advanced the understanding of abnormalities in inherited and sporadic dystonia. It remains elusive, however, whether dystonia-related brain networks can be identified with imaging. 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 ‘maps’.  She examines imaging data in patients with inherited and sporadic dystonia. This work should advance the understanding of brain network architecture in dystonia and help identify areas within the network for optimal therapeutic targeting and individually customized treatment.

Brain imaging is also used by Richard Reilly, Trinity College/the University of Dublin to probe brain networks in cervical dystonia. It is well known that dystonia is a heterogeneous group of neurological movement disorders and the reasons for clinical treatment outcomes for different patients remain unclear. Major issues in understanding dystonia include the variety of subtypes of dystonia and also the lack of biomarkers to identify the condition. Dr. Reilly uses a unique method based on the so-called the temporal discrimination threshold (TDT), the shortest time interval at which an individual detects two sequential stimuli to be asynchronous, has been shown to be a reliable measure of abnormality in cervical dystonia. The TDT has been shown to be abnormal in 97% of patients with cervical dystonia. It is hypothesized that unaffected relatives with abnormal TDTs are non-manifesting gene carriers for cervical dystonia. In this study, Dr. Reilly employs multimodal analysis on a recently acquired neuroimaging data from 16 cervical dystonia patients (all with abnormal TDT values). He will compare their neuroimaging data with 32 sex- and age-matched first degree relatives: 16 with normal TDT values and 16 with abnormal values indicating non-manifesting gene carriers for cervical dystonia. The project aims to advance our understanding of the structural and functional differences in cervical dystonia patients and also relate this information to a biomarker for cervical dystonia.

Unraveling hierarchical network loops in isolated dystonia is the goal of Xin Jin at the Salk Institute for Biological Studies. For the overwhelming majority of dystonia patients, the treatments target only the symptoms, not the (still largely unknown) causes. There is a growing body of evidence pointing to genetic factors, and some theories about how multiple gene abnormalities might combine with each other or with other “environmental” factors. There is also a large body of research characterizing brain abnormalities at a very macroscopic scale. But the intricate networks controlling muscles responsible for posture and movement remain a mystery. In humans, many parts of the brain involved in muscle control are inaccessible, particularly at the level of networks of neurons. Simulations of dystonia in animals, so-called “animal models”, would allow us to investigate and manipulate these microscopic networks. But the postures and movements seen in most animal models usually do not match what we see in patients. One rare exception is a so-called "2-hit" rat model of blepharospasm (BEB). BEB, one of the most common forms of isolated dystonia, is characterized by loss of control of the muscles around the eyes, resulting in increased blinking and involuntary “squinching” of the eyes. In the rodent model of BEB, the first hit is an experimentally-introduced reduction of the neurotransmitter dopamine in a part of the brain called the basal ganglia. The second hit is to remove a gland that produces the tear film which protects the eyeball, thereby producing an experimental dry eye. Only animals receiving both “hits” go on to show the symptoms commonly seen in BEB: increased spontaneous blinking, eyelid spasms, and increased excitability of the blink reflex. But the brain networks responsible for this effect are not known. In this project, Dr. Jin initiates a line of research to predict the onset of individual symptoms, to modify abnormal activity patterns in the brain in order to disrupt symptoms, and to optimize the treatment by applying the so-called “closed-loop” deep brain stimulation. This is the first research to directly interrogate this brain network in dystonia. It is also the first to examine the relationship between brain activity and symptoms. The results should provide unprecedented insights into the viability of this treatment approach. Because much of this brain network is thought to be similarly involved for different types of dystonia, the results of this study will also be relevant for types of dystonia beyond BEB, including cervical and generalized dystonia.

Andrea Kühn at Charite – University Medicine Berlin, uses functional brain connectivity to optimize deep brain stimulation in dystonia (DBS), the most successful treatment option in dystonia. The goal is to use a combination of novel electrophysiological and imaging methods (connectomic analyses) in patients undergoing deep brain stimulation for otherwise intractable dystonia. The results of these studies should optimize DBS in dystonia, e.g. using adaptive stimulation and define an effective DBS network. The hope is to find and establish a method that will make it possible to predict patient-specific clinical short- and long-term outcome based on multimodal full-brain connectivity analyses of presurgical imaging data. Characterizing a network marker may also inform closed-loop DBS for dystonia in the future. The project offers a comprehensive definition of a network target for the treatment of dystonia. As a consequence, which may alter clinical practice in the future.

Not everything is known about DBS and Roy Sillitoe at Baylor College of Medicine uses novel animal models to understand the inner workings of the brain networks that respond to DBS and medications. DBS has become an effective treatment for dystonia. However, it has its limitations, as a large number of patients suffering from dystonia do not respond to the treatment. These problems with treatment efficacy raise a critical question: what are the current dystonia medications and surgical therapies actually targeting in the brain? And of equal importance, what are these treatments failing to target when they do not work as expected? Research in humans and animal models strongly suggest that more regions of the brain are affected in dystonia than currently thought. If this is true, then perhaps the current approaches of treating the disease are insufficient because they do not fully account for all the faulty brain networks. As a first step towards identifying the brain-wide networks that are affected in dystonia, Dr. Sillitoe designed a genetic toolkit in mice that provided a method for generating mouse models of severe motor disease. The toolkit is based on controlling the cerebellum, now considered the hub for all motor functions and a central target in a growing list of brain diseases, including dystonia. This current project uses a combination of new genetic mouse models and imaging to define brain connectivity defects in severely dystonic mice. The ultimate goal of this work is to define the functional connectome of dystonia. The availability of a more complete map of how brain networks are (mis)wired in dystonia will provide alternate healthcare considerations beyond the currently limited options.

A radical approach is taken by Jesse Goldberg at Cornell University who applies machine learning to guide DBS to cure neurological diseases. 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. In this project, Dr. Goldberg proposes a new approach to DBS. He uses 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 project, Dr. Goldberg intends to establish the feasibility of this concept in mice.