Current Biology
Volume 26, Issue 3, 8 February 2016, Pages 371-376
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Selective Activation of the Deep Layers of the Human Primary Visual Cortex by Top-Down Feedback

https://doi.org/10.1016/j.cub.2015.12.038Get rights and content
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Highlights

  • High-field fMRI can resolve neural activity with laminar specificity in humans

  • Top-down and bottom-up signals lead to distinct laminar activation profiles in V1

  • Top-down signals selectively activate deep layers of V1

  • Bottom-up stimulus input activates all layers of V1

Summary

In addition to bottom-up input, the visual cortex receives large amounts of feedback from other cortical areas [1, 2, 3]. One compelling example of feedback activation of early visual neurons in the absence of bottom-up input occurs during the famous Kanizsa illusion, where a triangular shape is perceived, even in regions of the image where there is no bottom-up visual evidence for it. This illusion increases the firing activity of neurons in the primary visual cortex with a receptive field on the illusory contour [4]. Feedback signals are largely segregated from feedforward signals within each cortical area, with feedforward signals arriving in the middle layer, while top-down feedback avoids the middle layers and predominantly targets deep and superficial layers [1, 2, 5, 6]. Therefore, the feedback-mediated activity increase in V1 during the perception of illusory shapes should lead to a specific laminar activity profile that is distinct from the activity elicited by bottom-up stimulation. Here, we used fMRI at high field (7 T) to empirically test this hypothesis, by probing the cortical response to illusory figures in human V1 at different cortical depths [7, 8, 9, 10, 11, 12, 13, 14]. We found that, whereas bottom-up stimulation activated all cortical layers, feedback activity induced by illusory figures led to a selective activation of the deep layers of V1. These results demonstrate the potential for non-invasive recordings of neural activity with laminar specificity in humans and elucidate the role of top-down signals during perceptual processing.

Keywords

perceptual inference
shape perception
predictive coding
laminar fMRI

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