Alzheimer’s disease disrupts brain networks and is marked by shifts in brain rhythms detectable by EEG long before significant cell death. Recognizing these changes is vital for early detection and targeted interventions.

This post presents a new modeling study by our team and collaborators that uncovers the neural mechanisms behind prediction error evaluation and precision weighting in the brain. Using a biophysically grounded Laminar Neural Mass Model (LaNMM), the work offers a plausible implementation of predictive coding principles through cross-frequency coupling across cortical layers.