Neurological Surgery faculty members at UT Southwestern Medical Center in Dallas are leading the way in neuromodulation research. Current trials are exploring novel therapeutic uses for deep brain stimulation as well as brain-computer interface technology that could help patients more easily interact with the world.
Clinical Trials
Deep Brain Stimulation for Depression
Tractography Guided Subcallosal Cingulate Deep Brain Stimulation for Treatment Resistant Depression
Nader Pouratian, M.D., Ph.D., and his team developed a novel method for optimizing targeting of deep brain stimulation for depression. Unlike traditional targeting, this method relies on analyzing and pinpointing brain connections that seem to be critical for improving symptoms of depression. In collaboration with the UT Southwestern Interventional Psychiatry team, led by Kala Bailey, M.D., Dr. Pouratian is conducting a trial of deep brain stimulation for treatment resistant depression using this novel targeting technique. The team believes using this cutting-edge approach to stimulate these key pathways will significantly increase the chance of improvement in patients’ symptoms. The trial has enrolled two patients and aims to enroll up to 12 participants.
Deep Brain Stimulation for Depression
Deep Brain Stimulation (DBS) for Depression Using Directional Current Steering and Individualized Network Targeting
In another innovative trial applying deep brain stimulation to depression, Dr. Pouratian is collaborating with Baylor College of Medicine faculty members Sameer Sheth, M.D., Ph.D., and Wayne Goodman, M.D., to evaluate a different approach. The team aims to use advanced brain mapping techniques to better understand how depression affects the brain and how stimulation affects brain activity. During a 10-day hospitalization, patients have their brain activity recorded continuously as they perform various tasks and undergo different types of stimulation. The goal is to link these two critical sources of knowledge to design more precise and physiologically guided treatments for depression using deep brain stimulation. The trial targets both the subcallosal cingulate region and the ventral capsule/ventral striatum because of the different patterns of brain connections associated with each target. The trial has enrolled six patients so far, with six additional patients still to be enrolled at UT Southwestern.
Related papers:
- Deep Brain Stimulation for Depression Informed by Intracranial Recordings – PubMed (nih.gov)
- Decoding Depression Severity From Intracranial Neural Activity – PubMed (nih.gov)
NIH grant: RePORTER (nih.gov)
Deep Brain Stimulation for Low Back Pain
DBS of the Subgenual Cingulate Cortex (SCC) for the Treatment of Medically Refractory Chronic Low Back Pain (CLBP)
Pain is very complex, and there is increasing evidence that chronic low back pain is associated with structural and functional changes in the brain. On close analysis, the brain areas affected by chronic low back pain significantly overlap with the areas involved in depression – including prefrontal cortices and especially the medial prefrontal cortex. The subcallosal cingulate region, which is also targeted in trials of deep brain stimulation for depression, is highly connected to these brain networks involved in both depression and chronic pain. In this trial, our team, which includes Ausaf Bari, M.D., Ph.D., at the University of California, Los Angeles, is evaluating a different way of treating chronic low back pain using deep brain stimulation. The trial is seeking patients who have exhausted all other pain treatment options, including spinal cord stimulation. To date, two patients out of a total of 12 across the two sites have received implants.
Related paper: Deep Brain Stimulation of the Subgenual Cingulate Cortex for the Treatment of Chronic Low Back Pain – PubMed (nih.gov)
NIH grant: RePORTER (nih.gov)
Deep Brain Stimulation for Schizophrenia
Bradley Lega, M.D., and Dr. Pouratian are working with Carol Tamminga, M.D., of the Department of Psychiatry, to develop a novel application of deep brain stimulation to treat schizophrenia. This protocol, currently seeking regulatory approval, aims to begin enrolling in one year. The goal is to use brain mapping to design custom brain stimulation patterns to guide the placement of chronic brain stimulation devices.
Deep Brain Stimulation for Amelioration of Memory Loss in Mild Cognitive Impairment
Dr. Lega and his team are developing novel brain stimulation approaches to treat memory loss conditions such as mild cognitive impairment. Their strategy has evolved from groundbreaking work performed as part of a team science initiative funded by DARPA. The goal is to use patient-specific brain stimulation parameters to enhance each person’s unique brain wave pattern linked with successful memory. Dr. Lega is testing how these brain waves are affected by the kinds of brain chemical changes that accompany Alzheimer’s disease using pharmacological manipulation. Dr. Lega is seeking funding to expand this work to patients with mild cognitive impairment, in partnership with UT Southwestern colleagues Brendan Kelley, M.D., and C. Munro Cullum, Ph.D. The goal is to use the principles developed within the DARPA paradigm to design patient-specific brain stimulation paradigms, using existing DBS devices.
Brain Computer Interface (BCI)
MindEx: A Novel, Multifocal, Cognitive Brain-Machine Interface System
Srinivas Chivukula, M.D., Ph.D., is working on technology that can allow a person to control a computer or a tablet through their thoughts alone. This cutting-edge technology, known as a brain-computer interface (BCI), transforms neural signals recorded from the user’s brain into control signals for external applications. This technology has the potential to transform the lives of millions worldwide who have paralysis or other disorders, allowing them to communicate, type, or otherwise interact with the world through a virtual ecosystem. Dr. Chivukula’s work is unique in incorporating many types of sensory, cognitive, and motor signals from across a distributed network of brain regions and using advanced algorithms, including artificial intelligence, to decode the user’s intentions from these signals for intuitive and efficient control of external applications.
Related Papers: