Frontiers in neuroscience · 2026
Frequency tagged multifocal pupillary response fields identify age-related macular degeneration and diabetic retinopathy.
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Trinquet Laure, David Thierry, Chavane Frédéric, Lorenceau Jean, Matonti Fréderic
Аннотация
OBJECTIVES: To quickly characterize multifocal Pupillary Response Fields (mPRF) using frequency tagging and to identify pupillary biomarkers of age-related macular degeneration (AMD) and diabetic retinopathy (DR).
METHODS: Participants with AMD (N = 74), DR (N = 56), and healthy controls (HP, N = 62) underwent standard ophthalmologic assessments together with a multifocal Pupillary Frequency Tagging test (mPFT). The mPFT test comprised 9 retinal regions whose luminance were sinusoidally modulated at incommensurate temporal frequencies so as to elicit sustained pupillary oscillations over 45 s of fixation.
ANALYSES: The recorded pupillary traces were corrected for blinks and transient artifacts. Features of pupillary dynamics and eye-movements, - eye instability during fixation, pupil light reflex, and spectral components of pupil oscillations - were compared across groups. Statistical analyses were performed for each feature separately using Student t-tests and Cohen's d. The Area under the Curve (AUC) of the Receiver Operating Characteristics (ROC) was computed for different combinations of the extracted features. Pearson's correlation was used to compare spectral power with other functional measures.
RESULTS: Multifocal Pupillary Response Fields (mPRF) derived from regional spectral power and phase distributions differed significantly between patients and controls, in accordance with the characteristics of each pathology: decreased power for central and paracentral sectors in AMD, diffuse defects in DR. AUCs of ROC performed with relevant features achieved excellent sensitivity (>0.9) and specificity (>0.9) in classifying patients from healthy subjects.
CONCLUSION: Fast, objective, and easily recorded, mPRF assessments evaluate the functional integrity of retino-pupillary circuits, providing spatiotemporal bio-signatures selective for maculopathies and retinopathies.
METHODS: Participants with AMD (N = 74), DR (N = 56), and healthy controls (HP, N = 62) underwent standard ophthalmologic assessments together with a multifocal Pupillary Frequency Tagging test (mPFT). The mPFT test comprised 9 retinal regions whose luminance were sinusoidally modulated at incommensurate temporal frequencies so as to elicit sustained pupillary oscillations over 45 s of fixation.
ANALYSES: The recorded pupillary traces were corrected for blinks and transient artifacts. Features of pupillary dynamics and eye-movements, - eye instability during fixation, pupil light reflex, and spectral components of pupil oscillations - were compared across groups. Statistical analyses were performed for each feature separately using Student t-tests and Cohen's d. The Area under the Curve (AUC) of the Receiver Operating Characteristics (ROC) was computed for different combinations of the extracted features. Pearson's correlation was used to compare spectral power with other functional measures.
RESULTS: Multifocal Pupillary Response Fields (mPRF) derived from regional spectral power and phase distributions differed significantly between patients and controls, in accordance with the characteristics of each pathology: decreased power for central and paracentral sectors in AMD, diffuse defects in DR. AUCs of ROC performed with relevant features achieved excellent sensitivity (>0.9) and specificity (>0.9) in classifying patients from healthy subjects.
CONCLUSION: Fast, objective, and easily recorded, mPRF assessments evaluate the functional integrity of retino-pupillary circuits, providing spatiotemporal bio-signatures selective for maculopathies and retinopathies.