Why we linger: Memory encoding, rather than visual processing demand, drives fixation timing on natural scenes - evidence from a large-scale MEG dataset | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Why we linger: Memory encoding, rather than visual processing demand, drives fixation timing on natural scenes - evidence from a large-scale MEG dataset Philip Sulewski, Carmen Amme, Martin Hebart, Peter König, Tim Kietzmann This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7029247/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Prior to each of the ~200k daily eye movements, our brain needs to decide how long to remain fixated at the current location while novel information awaits elsewhere. To elucidate this process, here we report on the results of a large-scale scene-viewing experiment [4,080 natural scenes, 5 participants] that combines magnetoencephalography (MEG), eye tracking, and a semantic scene captioning task. Using multivariate analysis techniques of MEG source-space patterns, behavioural analyses and artificial neural network (ANN) modelling, we demonstrate that longer fixations do not arise from prolonged visual processing, but rather relate to downstream memory encoding. First, the temporal variability of ventral stream representational dynamics does not explain variability in fixation duration. Second, fixation durations are anti-correlated with patch complexity, as estimated from task-trained ANN models. Third, fixation durations correlate positively with ANN-predicted patch memorability and caption-inclusion, and co-occur with increased theta-gamma phase-amplitude coupling, particularly in frontal, and hippocampal regions. Biological sciences/Neuroscience/Learning and memory Biological sciences/Neuroscience/Sensorimotor processing/Decision Biological sciences/Neuroscience/Visual system Biological sciences/Neuroscience/Cognitive neuroscience/Attention Biological sciences/Neuroscience/Computational neuroscience active vision fixation timing object recognition memory encoding phase-amplitude coupling MEG eye tracking Full Text Additional Declarations There is NO Competing Interest. Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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