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"Learning to optimize perceptual decisions through suppressive interactions in the human brain" - Frangou et al. 2019

We are pleased to announce the publication of a collaboration paper in Nature Communications.  The paper: "Learning to optimize perceptual decisions through suppressive interactions in the human brain" is available online here.

 

Data collection for the paper was performed on the 7T MRI scanner at the Oxford Centre for Functional MRI of the Brain, as a collaboration with the Adaptive Brain Lab at Cambridge University, led by Professor Zoe Kourtzi.  The paper tests whether suppressive processing in decision-related and visual areas facilitate perceptual judgements during training.

 

Congratualtions to the authors: Poly Frangou, Uzay Emir, Vasilis Karlaftis, Caroline Nettekoven, Emily Hinson, Stephanie Larcome, Holly Bridge, Charlotte Stagg and Zoe Kourtzi.

 

Abstract

Translating noisy sensory signals to perceptual decisions is critical for successful interactions in complex environments. Learning is known to improve perceptual judgments by filtering external noise and task-irrelevant information. Yet, little is known about the brain mechanisms that mediate learning-dependent suppression. Here, we employ ultra-high field magnetic resonance spectroscopy of GABA to test whether suppressive processing in decision-related and visual areas facilitates perceptual judgments during training. We demonstrate that parietal GABA relates to suppression of task-irrelevant information, while learning-dependent changes in visual GABA relate to enhanced performance in target detection and feature discrimination tasks. Combining GABA measurements with functional brain connectivity demonstrates that training on a target detection task involves local connectivity and disinhibition of visual cortex, while training on a feature discrimination task involves inter-cortical interactions that relate to suppressive visual processing. Our findings provide evidence that learning optimizes perceptual decisions through suppressive interactions in decision-related networks.