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Ocular Motor Study

The aim of this project is to fully characterise eye movement changes in ME/CFS on two consecutive days, identifying an ocular motor signature that is unique to the disorder.

  • Christopher Armstrong, PhD
  • Joanne Fielding
  • Meaghan Clough
  • Currently recruiting participants for this study.
  • Preliminary trials on ME/CFS patients have already identified highly distinctive ocular motor changes in people with ME/CFS.
  • It appears that a fatigue phenotype will be able to be monitored using ocular motor testing.
  • A larger trial has begun with data collection ongoing and biofluid collection beginning.
STUDY HYPOTHESIS AND DESCRIPTION

Ocular motor (eye movement) assessment can be used in the diagnosis of various neurological diseases. Eye movement requires signaling across a vast, well-defined neural network that incorporates over 50% of the brain. Damage at any point across this extensive network manifests as abnormalities in eye movement. In a given disease/disorder, this manifests in a unique eye movement signature that can be measured using high powered eye-tracking technologies, allowing the quantification of even the subtlest of changes. This is especially relevant for those with ME/CFS as symptoms can often be subtle and prone to fluctuation (i.e. tending to worsen following exertion).

A defined ocular motor signature for ME/CFS would provide the first, objective, quantifiable marker for this disease that can be used to provide diagnostic certainty, provide a sensitive measure of progression or future treatment effect, and to inform the pathophysiological underpinnings of the disease.

The aim of this project, therefore, is to fully characterise eye movement changes in ME/CFS on two consecutive days, identifying an ocular motor signature that is unique to the disorder.

STUDY DESIGN

  1. Identify fatigue signatures in ME/CFS using simple and repetitive ocular motor tasks over time.
  2. Identify cognitive control changes in ME/CFS using validated cognitive ocular motor tasks.
  3. Characterise eye movement changes due to PEM induced by cognitive exertion.
  4. Develop a diagnostic algorithm and task set that incorporates a variety of ocular motor task signatures in ME/CFS using machine learning techniques.
  5. Combine biofluid collections with 2-day ocular motor tests for metabolite and immune marker analysis.

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