Popular accounts of mind and brain propose that the brain continuously forms predictions about future sensory inputs and combines predictions with inputs to determine what we perceive.1Bar M. Visual objects in context.Nat. Rev. Neurosci. 2004; 5: 617-629https://doi.org/10.1038/nrn1476Crossref PubMed Scopus (1153) Google Scholar,2Yuille A. Kersten D. Vision as Bayesian inference: analysis by synthesis?.Trends Cogn. Sci. 2006; 10: 301-308https://doi.org/10.1016/j.tics.2006.05.002Abstract Full Text Full Text PDF PubMed Scopus (526) Google Scholar,3de Lange F.P. Heilbron M. Kok P. How Do Expectations Shape Perception?.Trends Cogn. Sci. 2018; 22: 764-779https://doi.org/10.1016/j.tics.2018.06.002Abstract Full Text Full Text PDF PubMed Scopus (420) Google Scholar,4Press C. Kok P. Yon D. The Perceptual Prediction Paradox.Trends Cogn. Sci. 2020; 24: 13-24https://doi.org/10.1016/J.TICS.2019.11.003Abstract Full Text Full Text PDF PubMed Google Scholar,5Den Ouden H.E. Kok P. De Lange F.P. How Prediction Errors Shape Perception, Attention, and Motivation.Front. Psychol. 2012; 3: 548https://doi.org/10.3389/fpsyg.2012.00548Crossref PubMed Scopus (260) Google Scholar,6Kaiser D. Quek G.L. Cichy R.M. Peelen M.V. Object Vision in a Structured World.Trends Cogn. Sci. 2019; 23: 672-685https://doi.org/10.1016/j.tics.2019.04.013Abstract Full Text Full Text PDF PubMed Scopus (71) Google Scholar Under "predictive processing" schemes, such integration is supported by the hierarchical organization of the cortex, whereby feedback connections communicate predictions from higher-level deep layers to agranular (superficial and deep) lower-level layers.7Felleman D.J. Van Essen D.C. Distributed Hierarchical Processing in the Primate Cerebral Cortex.Cereb. Cortex. 1991; 1: 1-47https://doi.org/10.1093/cercor/1.1.1-aCrossref PubMed Scopus (8) Google Scholar,8Rockland K.S. Virga A. Terminal arbors of individual "Feedback" axons projecting from area V2 to V1 in the macaque monkey: A study using immunohistochemistry of anterogradely transported Phaseolus vulgaris-leucoagglutinin.J. Comp. Neurol. 1989; 285: 54-72https://doi.org/10.1002/cne.902850106Crossref PubMed Scopus (185) Google Scholar,9van Kerkoerle T. Self M.W. Roelfsema P.R. Layer-specificity in the effects of attention and working memory on activity in primary visual cortex.Nat. Commun. 2017; 8: 13804https://doi.org/10.1038/ncomms13804Crossref PubMed Scopus (111) Google Scholar,10Yu Y. Huber L. Yang J. Jangraw D.C. Handwerker D.A. Molfese P.J. Chen G. Ejima Y. Wu J. Bandettini P.A. Layer-specific activation of sensory input and predictive feedback in the human primary somatosensory cortex.Sci. Adv. 2019; 5eaav9053https://doi.org/10.1126/sciadv.aav9053Crossref Scopus (44) Google Scholar Predictions are compared with input to compute the "prediction error," which is transmitted up the hierarchy from superficial layers of lower cortical regions to the middle layers of higher areas, to update higher-level predictions until errors are reconciled.11Friston K. A theory of cortical responses.Philos. Trans. R. Soc. Lond. B Biol. Sci. 2005; 360: 815-836https://doi.org/10.1098/rstb.2005.1622Crossref PubMed Scopus (2834) Google Scholar,12Bastos A.M. Usrey W.M. Adams R.A. Mangun G.R. Fries P. Friston K.J. Canonical Microcircuits for Predictive Coding.Neuron. 2012; 76: 695-711https://doi.org/10.1016/j.neuron.2012.10.038Abstract Full Text Full Text PDF PubMed Scopus (1390) Google Scholar,13Kanai R. Komura Y. Shipp S. Friston K. Cerebral hierarchies: Predictive processing, precision and the pulvinar.Philos. Trans. R. Soc. Lond. B Biol. Sci. 2015; 370https://doi.org/10.1098/rstb.2014.0169Crossref Scopus (243) Google Scholar,14Rao R.P.N. Ballard D.H. Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects.Nat. Neurosci. 1999; 2: 79-87https://doi.org/10.1038/4580Crossref PubMed Scopus (3210) Google Scholar,15Stephan K.E. Petzschner F.H. Kasper L. Bayer J. Wellstein K.V. Stefanics G. Pruessmann K.P. Heinzle J. Laminar fMRI and computational theories of brain function.NeuroImage. 2019; 197: 699-706https://doi.org/10.1016/j.neuroimage.2017.11.001Crossref PubMed Scopus (37) Google Scholar In the primary visual cortex (V1), predictions have thereby been proposed to influence representations in deep layers while error signals may be computed in superficial layers. Despite the framework's popularity, there is little evidence for these functional distinctions because, to our knowledge, unexpected sensory events have not previously been presented in human laminar paradigms to contrast against expected events. To this end, this 7T fMRI study contrasted V1 responses to expected (75% likely) and unexpected (25%) Gabor orientations. Multivariate decoding analyses revealed an interaction between expectation and layer, such that expected events could be decoded with comparable accuracy across layers, while unexpected events could only be decoded in superficial laminae. Although these results are in line with these accounts that have been popular for decades, such distinctions have not previously been demonstrated in humans. We discuss how both prediction and error processes may operate together to shape our unitary perceptual experiences.
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