Notes

Bayesian Brain: Perception as Inference The main idea behind the Bayesian brain is that we use prior knowledge to infer properties that are not explicitly shown by observation.

• Depth can be inferred from prior knowledge/an existing model.

Bayesian Brain: Clinical Explanations

• Autistic people are "bombarded" by external stimuli.
• Schizophrenic people are "bombarded" by internal models. During psychotics episodes, schizophrenic people cannot distinguish between what's reality and what's in their mind.

Free Energy Principle

We care about what we see in the external world. We cannot do variational inference in the "true world", i.e., hidden states. In order to do that, we can use actions, sensations and internal states.

"Animals want to reduce their uncertainty about the world". "If I fell something on my back, I can update my internal model through sensation, but I can also turn around (action) which changes my sensation (from which the connection between sensations and actions). Therefore, I have a dual optimization goal, one is that in my internal model I should change the parameters to fit the best data I have, but I cannot only passively receive sensations and update the model. I can also choose actions that would eventually lead me to have better data and a better model." Actions are part of inference if you have an agent. This branch of research claimed that this would explain everything from cells to brains and minds. There are however a few problems: If I hear something on my back and I want to remove my uncertainty I can just turn around, but I can also do something else. If I am in a dark room there is no Free Energy.

"You want to maximize your surprise temporarily to have a better model that minimizes your surprise overall". From a neuroscientific perspective, such theory is reductionist in saying that all we want to do is minimizing uncertainty.