Three groups of patients with Alzheimer's disease, bvFTD and svPPA were recruited from the Cognitive Disorders Unit of the Marqués de Valdecilla University Hospital (Santander, Spain). Participants were evaluated with the Global Deterioration Scale (Reisberg et al., 1982) and Mini-Mental State Examination (MMSE) (Folstein et al., 1975) as global measures of disease severity. Only patients in a mild dementia stage (Global Deterioration Scale = 4) were included. All Alzheimer's disease patients displayed the classical amnestic phenotype. Diagnoses were established according to consensus criteria for probable Alzheimer's disease (McKhann et al., 2011), bvFTD (Rascovsky et al., 2011), and svPPA (Gorno-Tempini et al., 2011). In addition to congruent neuropsychological and neuroimaging findings (brain CT and/or MRI), all diagnoses were supported by at least one type of biomarker, amyloid-PET, and/or CSF Alzheimer's disease core biomarkers. Final diagnoses were agreed in multidisciplinary meetings including four neurologists (PSJ, ERR, SLG, and CL) and two neuropsychologists (MGM and AP). To minimize misclassification or heterogeneity due to co-pathology, only those cases with a complete concordance between clinicians' diagnosis and biomarker results were included.

Healthy volunteers were participants from the Valdecilla Study of Memory and Brain Aging, a prospective cohort recruiting community-dwelling non-demented people older than 55 years. The baseline protocol includes a comprehensive neuropsychological assessment, brain MRI and CSF analysis of Alzheimer's disease core biomarkers. Those subjects selected for our study had no cognitive complaints and showed normal results in all baseline evaluations, including normal levels of CSF biomarkers, which allows excluding the influence of preclinical Alzheimer's disease on their oculomotor performance.

These four groups were used as a discovery sample for the description of oculomotor performance, exploring neuropsychological and brain metabolic correlates and training machine learning algorithms. The classification accuracy of these algorithms was subsequently tested in two independent samples, a sample of 15 patients with Alzheimer's disease from our center who did not have a biomarker-supported diagnosis; and a sample of 6 bvFTD patients from an independent center, the Memory Unit of Santa Creu i Sant Pau Hospital (Barcelona, Spain) (Alcolea et al., 2019a; Illán-Gala et al., 2019). Both samples were evaluated with the same eye-tracker and an identical examination protocol as the discovery sample.

The study was approved by both local Ethics Committees and all participants gave their written informed consent according to the Declaration of Helsinki. For those patients who could not give a reliable informed consent due to their degree of cognitive impairment, it was obtained from their accompanying relative.

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