Cortical feedback signals generalise across different spatial frequencies of feedforward inputs

Revina, Y., Petro, L. S. and Muckli, L. (2018) Cortical feedback signals generalise across different spatial frequencies of feedforward inputs. NeuroImage, 180(Part A), pp. 280-290. (doi: 10.1016/j.neuroimage.2017.09.047) (PMID:28951158)

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Visual processing in cortex relies on feedback projections contextualising feedforward information flow. Primary visual cortex (V1) has small receptive fields and processes feedforward information at a fine-grained spatial scale, whereas higher visual areas have larger, spatially invariant receptive fields. Therefore, feedback could provide coarse information about the global scene structure or alternatively recover fine-grained structure by targeting small receptive fields in V1. We tested if feedback signals generalise across different spatial frequencies of feedforward inputs, or if they are tuned to the spatial scale of the visual scene. Using a partial occlusion paradigm, functional magnetic resonance imaging (fMRI) and multivoxel pattern analysis (MVPA) we investigated whether feedback to V1 contains coarse or fine-grained information by manipulating the spatial frequency of the scene surround outside an occluded image portion. We show that feedback transmits both coarse and fine-grained information as it carries information about both low (LSF) and high spatial frequencies (HSF). Further, feedback signals containing LSF information are similar to feedback signals containing HSF information, even without a large overlap in spatial frequency bands of the HSF and LSF scenes. Lastly, we found that feedback carries similar information about the spatial frequency band across different scenes. We conclude that cortical feedback signals contain information which generalises across different spatial frequencies of feedforward inputs.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Petro, Dr Lucy and Muckli, Professor Lars and Revina, Miss Yulia
Authors: Revina, Y., Petro, L. S., and Muckli, L.
College/School:College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience
Journal Name:NeuroImage
Published Online:22 September 2017
Copyright Holders:Copyright © 2017 The Authors
First Published:First published in NeuroImage 180(Part A): 280-290
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
593891Brain reading of contextual feedback and predictions - BrainReadFBPredCodeLars MuckliEuropean Research Council (ERC)ERC-2012-Stg-311751INP - CENTRE FOR COGNITIVE NEUROIMAGING
5887510BBSRC Doctoral Training Partnership 2012George BaillieBiotechnology and Biological Sciences Research Council (BBSRC)BB/J013854/1MVLS COLLEGE SENIOR MANAGEMENT