Increased activity in superficial and deep layers of human S1 for prediction error

Sensory processing in humans is thought to rely on a predictive model of the environment. And these predictions are constantly optimized to minimize future sensory prediction errors. However, the neural microcircuits underlying this prediction error model are still poorly understood. Here, we used an index finger prediction task that consists of sequential finger-stroking in high-resolution (0.71mm) BOLD and VASO fMRI at 7T to investigate how the prediction error activity changes across layers in the human primary somatosensory cortex (S1). We found that prediction error activity is stronger in superficial and deep layers rather than the middle layers of S1.