On Fralin Biomedical Research Institute at Virginia Tech Week: How do we distinguish which symptoms belong to what neurological disease?
Read Montague, Vernon Mountcastle Research Professor and Director of the Center for Human Neuroscience Research, explores this.
Faculty Bio:
Dr. Montague’s research focuses on computational neuroscience: the connection between physical mechanisms present in real neural tissue and the computational functions that these mechanisms embody. His early theoretical work focused on the hypothesis that dopaminergic systems encode a particular kind of computational process, a reward prediction error signal, similar to those used in areas of artificial intelligence like optimal control. The Montague Lab uses theoretical, computational, and experimental approaches to the problems of mental health and its derangement by disease and injury. They recently pioneered new approaches to measure sub-second fluctuations in dopamine and serotonin levels in the striatum of conscious human subjects.
Transcript:
Tremor is one of the most common symptoms of neurological disease. But two conditions that cause tremor — Parkinson’s disease and essential tremor — can look very similar, especially in the early stages. Distinguishing them is a persistent challenge.
We recorded real-time chemical signaling in the brain during surgery, focusing on dopamine and serotonin. Patients played a simple decision-making game involving fair and unfair monetary offers while we measured how their brain chemistry responded to unexpected outcomes.
A computational model revealed clear differences. In essential tremor, dopamine and serotonin worked in opposition: when one increased, the other decreased. In Parkinson’s disease, that reciprocal pattern was disrupted.
The strongest signal separating the two disorders wasn’t dopamine, as many would expect, but serotonin. Its altered dynamics turned out to be the most reliable marker of Parkinson’s disease.
These results suggest that serotonin could serve as a new biomarker for distinguishing Parkinson’s from essential tremor. More broadly, they show how combining behavioral tasks, computational modeling, and real-time neurochemistry can expose hidden disease signatures in the brain.
By identifying these neurochemical fingerprints, we move closer to more accurate diagnoses and, ultimately, more personalized treatments for tremor disorders.
This discovery reflects years of international, cross-disciplinary teamwork between researchers who revisited data collected nearly a decade ago with new analytical tools. By combining engineering, neuroscience, and computational modeling, the team transformed a long-standing puzzle into a clinically meaningful finding.
Read More:
[Virginia Tech] - Scientists reveal brain signaling that sets Parkinson’s disease apart from essential tremor
