I'm going to watch more towards the 16 minute mark regarding the psychedelic states, I got sucked into the later minutes of the video.
I stopped at about the 30sum minute mark, but when I have more time I'll watch the rest and give my thoughts.
I really do like the approach he's taking with measuring these various wave states in the brain, using markers for the complexities of these wave patterns to build these visual representations in helping to piece together what he's talking about. I think this is a good direction on things.
What I was really enjoying was his section of talk on some of those optical illusions like the 'Adelsons Checkerboard-Shadow Illusion' then following up with that black & white photograph in a separate slide. But really that adelsons illusion is hilarious. It just goes to show that when we expect/assume parts of our perception to be-the-case - well - that illusion demonstrates perfectly (at least with the perception of color) that our perception of things and what we expect are incredibly fickle, and that what we expect of our perception based on what we're seeing - we're easily fooled - in terms of what reality appears as and what we take it to be as we're experiencing it.
Then the example he shown of the 'Motion-Induced-Blindness Test' with having people stare at the middle white dot, while the circling red dot moves around it with the red dot eventually disappearing entirely from your vision (even though it's still technically there). Then after the red dot disappears - they happen to change the color of the dot for the participants ..then they tell the participants that they'd changed the color of the red dot to say blue or purple - then after telling them this - the dot would quickly reappear in it's blue or green color.
That example just goes to show that once your expectations of something are validated (at least with this example) - that would then accelerate your conscious awareness/perception of it.
Then all that leading down into him talking about the Bayseian Brain model and how we've always mainly thought of how we take in sensory input as a Bottom-Up Feed Forward model - with data/sensory input coming in - then it leading into deeper areas of the brain for further articulation and analysis, but.. then you have the whole bit to explain on the Bayseian structure of things and how that also there's not just a Bottom-Up mechanism but also a Top-Down (Bayesian) architecture to how the brain interprets and processes sensory input.
Sensory input coming in in the Bottom-Up format to be processed, but then all the Bayseian connections that show to work themselves outward (from inside the brains architecture to outside) - and how the Bayseian architecture shows the brains intense ability to assume/predict - then consequently giving us this 'best guess' on what the 'outside conscious world/reality' looks like based on the input given.
I liked how he referred to all the incoming sensory input as 'prediction error/s' with after being funneled into the brain, processed within the deeper centers, then working outward through the Bayseian architecture and allowing the brain to give a 'best prediction' on reality - he ended up referring to reality as a 'reasonably stable/controlled hallucination'.
This is no surprise to me. (D. Mckenna said this well before him)
Interested to watch the rest later.
