Layer-Resolved Connective Fields from Ultrafast fMRI Decode Feedforward and Feedback Information Flow during Spontaneous Activity

Layer-Resolved Connective Fields from Ultrafast fMRI Decode Feedforward and Feedback Information Flow during Spontaneous Activity | 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 Layer-Resolved Connective Fields from Ultrafast fMRI Decode Feedforward and Feedback Information Flow during Spontaneous Activity Noam Shemesh, Joana Carvalho, Francisca Fernandes, Mafalda Valente, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6136435/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 May, 2026 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Deciphering the directionality of information flow in cortical circuits is essential for understanding brain dynamics, learning, and neuroplasticity after injury. However, current non-invasive methods cannot distinguish feedforward (FF) from feedback (FB) signals across entire networks, including deep brain regions. Here, we present a novel approach – UltraFast Layer-Resolved Encoding (uFLARE) – that develops ultrahigh spatiotemporal resolution fMRI and a Layer-based Connective Field (lCF) model to disentangle FF from FB signaling. Our findings reveal that lCF size, an indicator of information integration, differentiates FF and FB activity through distinct layer-specific connectivity patterns during spontaneous activity, challenging the notion that FF signals are solely stimulus-driven. FF connectivity follows an inverted U-shape, peaking in layer IV, while FB exhibits a U-shaped pattern, with peaks in layers I and VI. These profiles generalize across sensory pathways (visual, somatosensory, and motor) and reveal injury-induced network reorganization, such as LGN bypassing V1 to provide direct FF input to higher visual areas. Biological sciences/Biological techniques/Imaging/Functional magnetic resonance imaging Biological sciences/Neuroscience/Computational neuroscience/Network models Biological sciences/Biological techniques/Imaging/Magnetic resonance imaging Biological sciences/Neuroscience/Visual system/Pattern vision Full Text Additional Declarations Yes there is potential Competing Interest. NS serves on the scientific advisory board of Bruker Biospon Cite Share Download PDF Status: Published Journal Publication published 04 May, 2026 Read the published version in Nature Communications → 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. 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