Carney Institute (CI): Tell us a bit about yourself.
Darcy Diesburg (DD): I attended the University of Tulsa where I studied psychology. In my junior year, I started doing research at the Laureate Institute for Brain Research in Tulsa. The lab I was working in was using functional magnetic resonance imaging to investigate how mental health disorders like depression, anxiety and post-traumatic stress disorder (PTSD) affect the brain and how the brain changes from pre- to post-treatment for those disorders. That was how I ended up finding out that neuroscience was something you could pursue as a career. I went on to pursue a Ph.D. at University of Iowa's psychology program, specifically in their behavioral and cognitive neuroscience track where I studied inhibitory control processes in humans.
Inhibitory control is a set of abilities that allow us to exert control over what we call prepotent thoughts or actions. These are thoughts or actions that may already be ongoing or particularly invigorated but that we can suppress if we become aware that we need to very quickly cancel them or shift course. For example, if you are cleaning up your kitchen after you've been cooking and you begin to reach for a hot pan that's on a back burner on the stove, you can cancel that reaching motion and withhold that reach to avoid burning yourself. It's been proposed that issues within these circuits are involved in behaviors like addiction or binge eating or compulsive types of behaviors and, if we expand beyond motor actions, to rumination or intrusive thoughts.
We studied these inhibitory control abilities using a variety of cognitive neuroscience methods including scalp EEG, which are caps of electrodes that record brainwaves, and transcranial magnetic stimulation, or TMS, which involves delivering single pulses of magnetic stimulation to the motor cortex. These TMS pulses get the motor neurons to fire, elicit a pulse in a muscle, and we can use that pulse to understand how excitable the motor system is at a given point in time and thereby understand whether inhibitory control processes are affecting motor output.
Towards the end of my Ph.D I began thinking about what I wanted to do as a next step and I was interested in continuing my work in inhibitory control processes. We had been studying particular brain wave signatures that were associated with the deployment of inhibitory control during successful action stopping. We had some what we call macro-scale signatures that you could observe either in intracranial recordings or on the scalp and I was really interested in finding ways to more deeply probe the generating mechanisms that produced these brain waves and the computations that they reflected. One of the people who was doing cutting-edge work in this was (Carney Institute professor) Stephanie Jones, who has a biophysical model that allows us to go from macro-scale, scalp level signature down to predicted cortical mechanisms at the cellular and cell-network level that might be producing these signatures. She was also working on a particular signature called transient beta, which was something I was working on in the context of action stopping.
CI: Tell us more about transient beta.
DD: Transient beta is a signature that occurs within a specific frequency range of brain signals from 15 to 29 hertz. In this range, there are short increases or what some people call bursts of beta activity that only last about 100 to 150 milliseconds. Throughout circuits in the brain that support movement and support movement cancellation, we see that beta is a signature that's associated with movement. When we perform a movement, there is a reduction in beta in these circuits. But, when we are at rest or when we're able to cancel a movement, beta activity is high. In the case of action stopping, it seems that whenever we can successfully cancel an action, we observe shortly before action cancellation increases in these short beta bursts in the motor cortex and frontocentrally in the brain.
Dr. Jones has been studying the role that these transient events play in sensory detection. For example, if you give someone a tap on the finger, at what threshold does it need to be for that tap to be detected? What they were finding is, when you give a tap on the finger with a force very close to detection threshold, that tap is a lot less likely to be detected when a beta event preceded it in the sensory cortex then when not. They were finding that beta events in this context seem to be inhibitory to incoming perceptual information, and some of the work I was involved in in graduate school was indicating in the action stopping context that they are inhibitory with regards to motor output.
CI: Could a stimulator be placed in the brain or delivered to the brain that could impact signatures like beta that influence behavior?
DD: That is something that does exist in the context of Parkinson's disease. In Parkinson's disease, we find that just at rest, these same beta events that we observe are abnormal. They're much bigger and they're much longer than they are in healthy brains. This observation led to the creation of adaptive deep brain stimulation, which is a deep brain stimulator (DBS) that is able to sense amplitude of certain frequency ranges in the subthalamic nucleus and only turn on when it begins to detect a signal that is larger than it should be. This adaptive DBS has been found to be very effective in treating certain symptoms of Parkinson's disease that have to do with slowness and freezing of movement.
If we can begin to expand out from Parkinson's disease outside the beta range as well - if we have certain high amplitude transients occurring in a particular frequency band - these might be, if not targets for stimulation treatment or invasive treatment, biomarkers of issues in the brain.
CI: We commonly talk about biomarkers in Alzheimer's disease research but less so in this context. Tell us more about that.
DD: There are a lot of opportunities to leverage something like a biophysical model to help us bridge electrophysiological signatures like beta with their cellular underpinnings to help us understand how high-level brain wave signatures might relate to things like cellular mechanisms and pathology.
I'm working with Professor Jones and with Dr. Linda Carpenter at Butler Hospital on some of the questions that were addressed in the Brainstorm challenge, but now formalized as the project I'm pursuing as part of the training program in computational psychiatry. We’re investigating how transient events in different frequency bands might be predictive of treatment response to repetitive TMS for depression. Jones and her group have found that in resting state EEG from individuals being treated for PTSD, characteristics like the frequency or duration of beta events can help predict with some degree of confidence whether or not an individual will respond to TMS therapy. So, there's some indication that these events may also give us some hints for predicting the efficacy of these types of treatments for other psychiatric conditions.
I'm also very interested in continuing to think about how we can use biophysical models to continue to explore the mechanisms that underlie inhibitory control. One initiative I'm very excited about is Carney’s Advancing Research Careers program, which is helping me think about the next step in my research and professional career, and what additional skills I want to acquire before starting my own lab.
CI: What inspires you? What gives you the motivation to spend the long nights in the lab or at the computer?
DD: I find myself inspired by the scientific process and how we are trying to answer questions that no one else has asked or been able to answer. At Brown, we’re surrounded by scientists who are working on the cutting edge of their field. We get to work closely with them and see them present those “big questions” and the answers that they've been able to find. That feels inspiring.