Unboxing the Experience Machine
- The number of neuronal connections carrying signals backward in this way is estimated to exceed the number carry signals forward by a very substantial margin.
- The brain, at 2% of human body weight is estimated to account for around 20% of total bodily energy consumption.
- The bulk of what the brain does is learn and maintain a kind of model of body and world - a model that can then be used, moment by moment, to try to predict the sensory signal. These predictions help structure everything we see, hear, touch, and feel.
- As a brain encounters new sensory information its job is to determine if there is anything in that incoming signal that looks like important "news" - unpredicted sensory information that matters to whatever it is that we are trying to see or do.
- Hermann von Helmholtz - "given everything I know, how must the world be for me to be receiving the pattern of signals currently present?" This is the question that perceptual systems are built to resolve.
- If the signal is poor, the brain chruns out "good hallucinations" by filling in and fleshing out the missing signal according to what it expects to hear.
- The "top-down" flow of information
- "Controlled hallucination" - When inner guessing completely rules the roost, we are just hallucinating, full stop. But when it is appropriately sensitive to sensory stimulations - via prediction error signals - the guessing is controlled, and the world becomes known to the mind.
- Linear predictive coding (Cluade Shannon) - The trick is trading intelligence and foreknowledge against the costs of encoding and transmitting all the information. Transmit only whatever turns out to be different from the predicted patterns. Wherever there is detectable regularity of any kind, prediction (and hence this form of data compression) becomes possible.
- However complex or high-level the predictions, it is prediction errors that must then carry the news, signaling differences from the expected and thereby keeping us in touch with a changing and sometimes surprising world.
- In the predictive processing architecture of the brain, it is thought that different neuronal populations specialize in different things, so that each "higher" level can use its own specialized knowledge and resources to try to predict the states of the level immediately below it.
