For the probabilistic graphical model and belief prop perspective, check out Friston et al. (2017) "The graphical brain: Belief propagation and active inference

For the probabilistic graphical model and belief prop perspective, check out Friston et al. (2017) "The graphical brain: Belief propagation and active inference": https://www.mitpressjournals.org/doi/pdf/10.1162/netn_a_00018 https://www.mitpressjournals.org/doi/pdf/10.1162/netn_a_0001... For the neural corollaries of predictive coding, check out Shipp (2016) "Neural Elements for Predictive Coding": https://www.frontiersin.org/articles/10.3389/fpsyg.2016.01792/full https://www.frontiersin.org/articles/10.3389/fpsyg.2016.0179... For a state-of-art CV framework that fits with the free energy principle, check out the Recursive Cortical Network from George et al. (2017) "A generative vision model that trains with high data efficiency and breaks text-based CAPTCHAs ": http://science.sciencemag.org/content/358/6368/eaag2612 http://science.sciencemag.org/content/358/6368/eaag2612