Neural Mechanisms Determining the Duration of Task-free, Self-paced Visual Perception

Shira Baror, Thomas J. Baumgarten, Biyu J. He

Research output: Contribution to journalArticlepeer-review


Humans spend hours each day spontaneously engaging with visual content, free from specific tasks and at their own pace. Currently, the brain mechanisms determining the duration of self-paced perceptual behavior remain largely unknown. Here, participants viewed naturalistic images under task-free settings and self-paced each image’s viewing duration while undergoing EEG and pupillometry recordings. Across two independent data sets, we observed large inter-and intra-individual variability in viewing duration. However, beyond an image’s presentation order and category, specific image content had no consistent effects on spontaneous viewing duration across participants. Overall, longer viewing durations were associated with sustained enhanced posterior positivity and anterior negativity in the ERPs. Individual-specific variations in the spontaneous viewing duration were consistently correlated with evoked EEG activity amplitudes and pupil size changes. By contrast, presentation order was selectively correlated with baseline alpha power and baseline pupil size. Critically, spontaneous viewing duration was strongly predicted by the temporal stability in neural activity patterns starting as early as 350 msec after image onset, suggesting that early neural stability is a key predictor for sustained perceptual engagement. Interestingly, neither bottom–up nor top–down predictions about image category influenced spontaneous viewing duration. Overall, these results suggest that individual-specific factors can influence perceptual processing at a surprisingly early time point and influence the multifaceted ebb and flow of spontaneous human perceptual behavior in naturalistic settings.

Original languageEnglish
Pages (from-to)756-775
Number of pages20
JournalJournal of Cognitive Neuroscience
Issue number5
StatePublished - 1 May 2024
Externally publishedYes

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© 2024 Massachusetts Institute of Technology.


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