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 Ca2+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.
CITATION STYLE
Dimkovski, M., & An, A. (2016). Computational role of astrocytes in bayesian inference and probability distribution encoding. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9919 LNAI, pp. 24–33). Springer Verlag. https://doi.org/10.1007/978-3-319-47103-7_3
Mendeley helps you to discover research relevant for your work.