Investigative Ophthalmology & Visual Science Cover Image for Volume 65, Issue 7
June 2024
Volume 65, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2024
Natural clustering of smooth pursuit biomarkers in a normative population
Author Affiliations & Notes
  • Eric Seemiller
    Air Force Research Laboratory 711th Human Performance Wing, Wright-Patterson AFB, Ohio, United States
  • Jonelle Knapp
    Air Force Research Laboratory 711th Human Performance Wing, Wright-Patterson AFB, Ohio, United States
  • Marc Winterbottom
    Air Force Research Laboratory 711th Human Performance Wing, Wright-Patterson AFB, Ohio, United States
  • Footnotes
    Commercial Relationships   Eric Seemiller None; Jonelle Knapp None; Marc Winterbottom None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2024, Vol.65, 1499. doi:
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      Eric Seemiller, Jonelle Knapp, Marc Winterbottom; Natural clustering of smooth pursuit biomarkers in a normative population. Invest. Ophthalmol. Vis. Sci. 2024;65(7):1499.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : The quantifiable ballistics of smooth pursuit eye movements can vary substantially within a population. The goal of this investigation was to determine if certain subgroups within a normative population naturally cluster according to these dynamic properties.

Methods : Smooth pursuit eye movements were recorded using the neuroFit ONE eye tracking paradigm. This approach uses a radial Rashbass step-ramp stimulus to assess smooth pursuit performance, recording monocular eye position at 120 Hz. The paradigm reports 11 biomarkers relating to the dynamics and accuracy of the eye movement: latency, acceleration, direction asymmetry, direction anisotropy, direction noise, speed tuning, speed noise, baseline speed, smooth pursuit gain, proportion smooth pursuit, and catch-up saccade amplitude. K-means clustering was used to assign group membership based on the proximity of individual participants in the multidimensional space defined by these biomarkers.

Results : Data were collected from 72 typically-sighted participants. A dendrogram analysis on normalized data revealed the likely presence of two distinct populations, whose centroids were separated by 6.8 normalized units. The coordinates of those centroids indicated that the two groups differed greatly on proportion smooth pursuit (d’ = 1.47), acceleration (d’ = 1.43), smooth pursuit gain (d’ = 1.36), and speed noise (d’ = -1.30). Conversely, there was little separation related to baseline speed (d’ = 0.002) or direction anisotropy (d’ = 0.11). These results indicate the populations differ according to the initial acceleration and maintenance of the smooth pursuit vector.

Conclusions : Cluster analysis of smooth pursuit biomarkers in a normative population reveals the potential existence of two subgroups. Those subgroups may be classified as having either high or low initial acceleration and good or poor adherence to the smooth pursuit vector. Furthermore, the discrimination may be independent of other quantitative smooth pursuit biomarkers such as direction anisotropy. The definition of these clusters may be useful when considering smooth pursuit dynamics as a biomarker of brain injury or other neural pathologies.

This abstract was presented at the 2024 ARVO Annual Meeting, held in Seattle, WA, May 5-9, 2024.

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