Fine-scale computations for adaptive processing in the human brain
- University of Cambridge, United Kingdom
- Maastricht University, Netherlands
Abstract
Adapting to the environment statistics by reducing brain responses to repetitive sensory information is key for efficient information processing. Yet, the fine-scale computations that support this adaptive processing in the human brain remain largely unknown. Here, we capitalize on the sub-millimetre resolution of ultra-high field imaging to examine fMRI signals across cortical depth and discern competing hypotheses about the brain mechanisms (feedforward vs. feedback) that mediate adaptive processing. We demonstrate layer-specific suppressive processing within visual cortex, as indicated by stronger BOLD decrease in superficial and middle than deeper layers for gratings that were repeatedly presented at the same orientation. Further, we show altered functional connectivity for adaptation: enhanced feedforward connectivity from V1 to higher visual areas, short-range feedback connectivity between V1 and V2 and long-range feedback occipito-parietal connectivity. Our findings provide evidence for a circuit of local recurrent and feedback interactions that mediate rapid brain plasticity for adaptive information processing.
Data availability
Source data have been provided for Figures 3, 4, and 5. Data can also be found on the Cambridge Data repository
Article and author information
Author details
Vasilis M Karlaftis
Funding
Biotechnology and Biological Sciences Research Council (H012508)
- Zoe Kourtzi
Biotechnology and Biological Sciences Research Council (BB/P021255/1)
- Zoe Kourtzi
Wellcome Trust (205067/Z/16/Z)
- Zoe Kourtzi
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: Participants gave written informed consent. The study was approved by the local Ethical Committee of the Faculty of Psychology and Neuroscience at Maastricht University and the University of Cambridge Ethics Committee (ethics number PRE2018.003).
Copyright
© 2020, Zamboni et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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