Identifying Early Signs of Cognitive Deficits Using a Novel Eye-Tracking Protocol: Distinctions between Subjective Concerns and Healthy Controls.

The dataset consists of behavioural and cognitive performance measures collected as part of a longitudinal study investigating visual recognition memory and related neurocognitive variables in older adults. Data were acquired at two time points approximately 12 months apart (Time 1 and Time 2). Participants were categorised into two groups based on self-reported cognitive status: Healthy Control (HC) and Subjective Cognitive Concern (SCC). All behavioural data were obtained under controlled laboratory conditions using standardized procedures.Eye-tracking–based Visual Paired Comparison (VPC) performance was assessed at both time points using a structured viewing paradigm that presents familiar and novel stimuli following either a 20-second or 2-minute delay interval. For each delay condition, the percentage of viewing time directed toward the novel stimulus was computed as the primary outcome measure. Eye-tracking data were processed using built-in software algorithms that automatically identify fixations and calculate fixation duration percentages. Cognitive performance was also measured via standardized tests, including the Montreal Cognitive Assessment (MoCA), following established administration and scoring guidelines.The dataset contains 47 participants, each represented by a unique numerical identifier. Tabular data are provided in CSV format. Each row corresponds to a single participant, and columns represent:Group (1 = HC, 2 = SCC)Timepoint (1 or 2)VPC_20sec (percentage of fixation on the novel stimulus at the 20-second delay)VPC_2min (percentage of fixation at the 2-minute delay)MoCA scoreAll percentage-based variables are expressed as continuous numerical values. Cognitive test scores follow the standard scoring ranges defined by the respective instruments. Missing values are present in a small number of entries where participants did not complete a given measure at one of the time points. Missingness is non-systematic and primarily due to participant withdrawal or technical issues during eye-tracking acquisition (e.g., loss of calibration). No imputation has been applied; missing values are coded as blank cells in the CSV files.Internal consistency checks were performed to identify outliers, unexpected score ranges, and anomalous values. No measurement errors beyond expected human performance variability were detected. Eye-tracking error ranges align with typical commercial infrared-based systems, which maintain sub-degree spatial accuracy; however, as only percentage fixation measures are reported, hardware error is not directly expressed in the tabular data.The dataset is stored in comma-separated value (CSV) format, ensuring broad compatibility across statistical and data-analysis platforms such as R, Python, MATLAB, SPSS, and Excel.