Cognitive Vergence and Pupillary Responses as Functional Oculomotor Signatures to Differentiate AT(N) Biological Profiles

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.

Authors

Institutions

Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-04-15
DOI
https://doi.org/10.64898/2026.04.14.718456
Primary Topic
Dementia and Cognitive Impairment Research
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Cognitive Vergence and Pupillary Responses as Functional Oculomotor Signatures to Differentiate AT(N) Biological Profiles

Neus Falgàs, Ricardo Martinez-Flores, Hans Supèr, Carlos Cristi‐Montero et al.
bioRxiv (Cold Spring Harbor Laboratory)
Dementia and Cognitive Impairment Research
article

Cognitive Vergence and Pupillary Responses as Functional Oculomotor Signatures to Differentiate AT(N) Biological Profiles

Neus Falgàs, Ricardo Martinez-Flores, Hans Supèr, Carlos Cristi‐Montero, Isabel Martín-Sobrino, Marc Suárez-Calvet, Oriol Grau-Rivera, Agustín Ibáñez
article en

Abstract

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.

bioRxiv (Cold Spring Harbor Laboratory)
Institució Catalana de Recerca i Estudis Avançats (ES), Pontificia Universidad Católica de Valparaíso (CL), Trinity College Dublin (IE), Adolfo Ibáñez University (CL), Instituto de Salud Carlos III (ES), Istanbul Medipol University (TR), University of San Andrés (AR), Biomedical Research Networking Center on Neurodegenerative Diseases (ES), Pasqual Maragall Foundation (ES), Hospital Clínic de Barcelona (ES), Pontificial Catholic University of Valparaiso (CL), Barcelonaβeta Brain Research Center (ES), Hospital Del Mar (ES), Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (ES), Universitat de Barcelona (ES)
Alzheimer's Association, Wellcome Trust, EU Joint Programme – Neurodegenerative Disease Research, Agenția Națională pentru Cercetare și Dezvoltare, European Commission, Agencia Nacional de Investigación y Desarrollo, National Institutes of Health, Instituto de Salud Carlos III, Fogarty International Center, Fondo de Fomento al Desarrollo Científico y Tecnológico, Fondo de Financiamiento de Centros de Investigación en Áreas Prioritarias, H2020 Marie Skłodowska-Curie Actions, CHIST-ERA
Reduced inequalities
Openalex Percentile: Top 19%
Dementia and Cognitive Impairment Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.