David Vaillancourt profile photo

David Vaillancourt

Professor | Chair University of Florida

  • Gainesville FL

David Vaillancourt’s studies how the brain regulates voluntary and involuntary movement with a specific focus on motor disorders.

Contact
University of Florida logo

University of Florida

View more experts managed by University of Florida

Biography

David Vaillancourt’s research focuses on how the brain regulates voluntary and involuntary movement with a specific focus on motor disorders. His research program uses advanced neuroimaging techniques to study the functional and structural changes in the brain of humans and animal models that span Parkinson’s disease, tremor, ataxia and dystonia.

Areas of Expertise

Structural and Functional Imaging in Rodents and Humans
Rehabilitative, Surgical and Pharmacological Interventions for Motor Disorders
Cortical Oscillations that Underlie Voluntary and Involuntary Movement
Neuroscience and the Brain
Progression Markers of Parkinson’s Disease

Media Appearances

Researchers examine how Parkinson’s disease alters brain activity over time

PsyPost  online

2016-08-15

“If you know that in Parkinson’s disease the activity in a specific brain region is decreasing over the course of a year, it opens the door to evaluating a therapeutic to see if it can slow that reduction,” said senior author David Vaillancourt, Ph.D., a professor in the University of Florida’s Department of Applied Physiology and Kinesiology. “It provides a marker for evaluating how treatments alter the chronic changes in brain physiology caused by Parkinson’s.”

View More

Biomarker breakthrough could improve Parkinson’s treatment

UF News  online

2016-08-15

“Our technique does not rely upon the injection of a drug. Not only is it non-invasive, it’s much less expensive,” said David Vaillancourt, Ph.D., a professor in UF’s Department of Applied Physiology and Kinesiology and the study’s senior author.

View More

Artificial Intelligence Tool Seeks to Enhance Parkinson’s Diagnosis

HealthITAnalytics  online

2021-03-22

“This isn’t going to replace the physician’s decision making; it’s just meant to be another tool in their toolkit,” said David Vaillancourt, PhD, professor and chair of the UF College of Health & Human Performance's department of applied physiology and kinesiology. “The goal is that clinical trials will be better because they will focus on specific variants. Patients will be able to know their diagnosis earlier.”

View More

Social

Articles

A New MRI Measure to Early Differentiate Progressive Supranuclear Palsy From De Novo Parkinson's Disease in Clinical Practice: An International Study

Movement Disorders

Andrea Quattrone, et al.

2020-11-05

Enlargement of the third ventricle has been reported in atypical parkinsonism. We investigated whether the measurement of third ventricle width could distinguish Parkinson's disease (PD) from progressive supranuclear palsy (PSP).

View more

Investigating the role of striatal dopamine receptor 2 in motor coordination and balance: Insights into the pathogenesis of DYT1 dystonia

Behavioural Brain Research

Yuning Liu, et al.

2021-01-23

DYT1 or DYT-TOR1A dystonia is early-onset, generalized dystonia. Most DYT1 dystonia patients have a heterozygous trinucleotide GAG deletion in DYT1 or TOR1A gene, with a loss of a glutamic acid residue of the protein torsinA. DYT1 dystonia patients show reduced striatal dopamine D2 receptor (D2R) binding activity. We previously reported reduced striatal D2R proteins and impaired corticostriatal plasticity in Dyt1 ΔGAG heterozygous knock-in (Dyt1 KI) mice.

View more

A Higher Order Manifold-Valued Convolutional Neural Network with Applications to Diffusion MRI Processing

International Conference on Information Processing in Medical Imaging

Jose J. Bouza, et al.

2021-06-14

In this paper, we present a novel generalization of the Volterra Series, which can be viewed as a higher-order convolution, to manifold-valued functions. A special case of the manifold-valued Volterra Series (MVVS) gives us a natural extension of the ordinary convolution to manifold-valued functions that we call, the manifold-valued convolution (MVC). We prove that these generalizations preserve the equivariance properties of the Euclidean Volterra Series and the traditional convolution operator.

View more

Media