The Experience Machine

1 - Unboxing The Prediction Machine

Hallucinations, from a predictive processing perspective, are not the same as our usual trippin’ balls perspective. Strong predictions (EG - feeling our phone vibrate when we’re under stress, even if it’s not in our pocket) can create these sensations.

Our brain, as part of it’s normal function, is always creating predictions, and this is what we subjectively experience. We don’t objectively consume sensory input.

Our previous predictions and experiences are always at play, and they’re unavoidable.

We can’t just think ourselves happier, but we do have some flexibility in shaping our interpretation of our sensory input.

The Smart Camera Model of Seeing

Our older models of processing involve a feedforward (top down) model - which assumed our brains took sensory input and gradually got more data out of it. This was unaware of evidence of “downward (and sideways) connectivity.” (Page 9)

Flipping the Flow

Instead of brains being cameras, it appears they may do the opposite, as it’s more energy efficient, maintaining a prediction model. It takes sensory input, checks it against existing miniature models, and generates prediction error signals when it doesn’t line up. Winston’s work in computational neuroscience goes by predictive processing, hierarchical predictive coding, and active inference interchangeably.

Bad Radios and Controlled Hallucinations

Hermann von Hemholtz argued that we generate controlled hallucinations based on previous experiences, conserving energy use in the brain. (The implication here is, this may take part in how we can make predictions about noisy data - like being able to recognize a familiar song mangled by poor FM reception.)

The Frugal Brain

Linear predictive coding is more of a mathematical concept that compresses data by storing only the deltas. (Like in video compression algorithms where frames are compared, and we only need to store the differences.) They suggest our brains work similarly - we just know a lot more.

Human brains seem to benefit from intelligent prediction strategies of just that kind… thanks to the use of multiple “levels of processing.” … simple predictions are nested under less simple, more abstract ones… prediction errors are formed and pushed upward through the system.

Brains reserve bandwidth for prediction errors, as it’s more efficient. Our experiences are hallucinatory.

(This section also talks a bit about prediction hierarchy without explicitly mentioning it.)

The Power of Prediction

A few examples of prediction:

• They show the 12 13 14 ABC image, highlighting that unconscious (masked) biases at work.
• The Hollow-Face illusion which prevents us from seeing the concave representation.
• A Mooney image, ala https://www.behaviouralbydesign.com/post/neuroscience-of-strange-and-beautiful-experiences. Predictions are easily permanently altered.
• Sine Wave Speech - an auditory example, similar to above.
• Think about Brainstorm or Green Needle while watching this. https://www.youtube.com/watch?v=1okD66RmktA - this easily flips between one or the other.
• Suggesting you can hear a familiar song in white noise will often cause you to hallucinate it faintly.
• The Ponzo Illusion
• The dress that I’m tired of hearing about. (But they do offer the explanation that we will often see the dress in a certain color depending on our masked assumptions on lighting.)
• Experientially, if we looked at a tree, and we were not expecting to see a robin at the top of it, we’d likely initially not notice the robin, be surprised when we saw it, and then we’d see it clearly.