Cognitive Vergence and Pupillary Responses as Functional Oculomotor Signatures to Differentiate AT(N) Biological
Ricardo Martínez-Flores1,2, Isabel Martín-Sobrino3,4, Neus Falgàs3,4,5
1Institute of Neurosciences, University of Barcelona (UBNeuro), 08035 Barcelona, Spain.
Background:
The AT(N) biological framework classifies Alzheimer's disease (AD) pathology using CSF biomarkers, with the A+T+ profile defining biological AD and the A-T+ profile representing a biologically distinct entity consistent with suspected non-Alzheimer's pathophysiology, such as primary age-related tauopathy. Functional assessment capable of differentiating these profiles non-invasively remains limited. This study investigates whether cognitive vergence and pupillary temporal dynamics during a visual oddball task can distinguish A-T+ from A+T+ biological profiles in individuals with mild cognitive impairment (MCI).
Methods:
Thirty-eight participants with MCI (12 A-T+, 26 A+T+) classified by CSF biomarkers completed a visual oddball task (80% distractors, 20% targets) under continuous eye-tracking. Linear mixed-effects models examined profile × condition interactions on full time series and six trial-level temporal features. Participant-level differentiation was assessed using binomial logistic regression, adjusting for age, sex, and MMSE.
Results:
Both profiles showed comparable overall oculomotor response magnitudes but diverged markedly in temporal organization. Significant profile × condition interactions emerged for cognitive vergence global slope, time to peak, and pupillary time to peak. Logistic regression confirmed that timing features discriminated biological profiles at the participant level, with differentiation reversing direction between distractor and target conditions. A-T+ participants also maintained superior target detection accuracy (89.3% vs. 82.4%, p = 0.001).
Conclusion:
Cognitive Vergence and pupillary temporal dynamics during an oddball task provide condition-dependent functional oculomotor signatures that systematically differentiate AT(N) biological profiles in MCI, suggesting that oculomotor assessment may offer an accessible, non-invasive complement to CSF-based profile characterization.
