Abstract
The past few years have seen new research methods confirming more confidently that glia have a key information processing role in the brain, specifically in relation to learning capability. However, many details Tof glia’s role remain unknown, including a gap between cellular and behavioural level findings. Based on \(Ca^{2+}\) wave mechanics in astrocytes, we derive a theoretical capability of astrocytes to encode cognitive representations as probability distributions over synapses. The process is analogous to MCMC Bayesian inference that samples a neural network configuration from a prior in the astrocyte and then uses its performance to update to a posterior distribution. The proposed model explains recent behavioural results where obstructing astrocytes leads to deficiencies in learning new knowledge without affecting ability to recall existing knowledge. The model is also a novel Bayesian brain theory which uniquely addresses the cellular and synaptic levels.