Guest Talk by Linzhi Tao

The brain’s ability to weight predictions by their precision (i.e., the inverse of variance) is a central mechanism in predictive processing, enabling optimal integration of prior expectations with incoming sensory input. Using 7-Tesla fMRI and Dynamic Causal Modelling (DCM), we investigated how precision shapes the modulatory connectivity among the insula, pulvinar, and primary visual cortex (V1) during a visual cueing task. Our results suggest a dual-route mechanism whereby the insula directly enhances top-down predictions in V1 while indirectly dampening bottom-up sensory input via the pulvinar during high-precision predictions. We further showed that the connectivity strength of these pathways predicted individual differences in behavioural sensitivity to precision. These findings provide empirical evidence for precision modulation in predictive processing and offer new hypotheses into how precision weighting may be disrupted in neuropsychiatric conditions.