Sensory expectations and prediction error during feedback control in the human brain

Abstract External disturbances to the body are better counteracted when their nature can be predicted in advance. Here, we investigated the neural mechanisms through which probabilistic predictions shape feedback responses using functional magnetic resonance imaging (fMRI) in humans. We show that, prior to a mechanical perturbation applied to a finger, the primary motor (M1) and somatosensory (S1) cortices receive a signal that linearly encodes the expected sensory input. When perturbations reach these areas, expectations are combined with the sensory input through a simple additive mechanism, yielding motor commands that reflect a weighted sum of the two signals. At the same time, M1 and S1 receive a prediction error signal encoding the difference between expectations and actual sensory input. This signal is visible in fMRI data in humans and in the local field potentials in non-human primates, but not in M1 or S1 spiking activity.