Examines digital distraction effects on attention in young adults, implying insights into cognitive processing.
A publicly available, BIDS-compliant multimodal dataset is presented for studying the impact of digital information distraction on attentional processing. Thirty-eight young adults underwent fMRI scanning while performing a global-local attention task under three conditions: social notifications, non-social notifications, and a no-distraction baseline. The dataset includes task-based fMRI, high-resolution structural MRI, trial-level behavioral performance data, and a range of psychological questionnaires assessing digital-media tendencies, affective traits, and attentional control-related individual differences. Raw neuroimaging data, event files, and MRIQC-generated quality-control outputs are provided for all participants. This dataset supports diverse analytic approaches for exploring how different digital cues affect attentional allocation. By offering a well-documented and publicly accessible resource, the Data Descriptor promotes reproducible research and facilitates further investigations into the cognitive and neural mechanisms involved in attention within digitally saturated environments.
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Liu et al. (2026) studied this question.
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