rough draft on what happens in the brain when you have an insight

Epistemic status: It is better to be wrong than to have no model at all. I recommend the footnotes.[1]

šŸµ

On my current models of theoretical[2] insight-making, it looks something like this:

  1. A gradual build-up and propagation of salience wrt some tiny discrepancy between highly confident specific beliefs

    1. This maybe corresponds to simultaneously-salient neural ensembles whose oscillations are inharmonic[3]

    2. Or in the frame of predictive processing: unresolved prediction-error between successive layers

  2. Immediately followed by a resolution of that discrepancy if the insight is successfwl

    1. This maybe corresponds to the brain having found a combination of salient ensemblesā€”including the originally inharmonic ensemblesā€”whose oscillations are adequately harmonic

    2. Super-speculative but: If the ā€œquestion phaseā€ in step 1 was salient enough, and the compression in step 2 great enough, this causes an insight-frisson[4] and a wave of pleasant sensations across your scalp, spine, and associated sensory areas

This maps to a fragile/ā€‹chaotic high-energy ā€œquestion phaseā€ during which the violation of expectation is maximized (in order to adequately propagate the implications of the original discrepancy), followed by a compressive low-energy ā€œsolution phaseā€ where correctness of expectation is maximized again.

In order to make this work, there are several homeostatic mechanisms which make the brain-state hug the border between phase-transitions as tightly as possible.[5] A corollary of this is that the brain maximizes dynamic correlation length between neurons,[6] which is when they have the greatest ability to influence each other across long distances (aka ā€œcommunicateā€). This is called the ā€œcritical brain hypothesisā€, and it suggests that good thinking is necessarily chaotic in some sense.

Another point is that insight-making is anti-inductive.[7] Theoretical reasoning is a frontier thatā€™s continuously being exploited based on the brainā€™s native Value-of-Information-estimator, which means that the branches with the highest naively-calculated-VoI are also less likely to have any low-hanging fruit left. What this implies is that novel insights are likely to be very narrow targetsā€”which means they could be really hard to hold on to for the brief moment between initial hunch and build-up of salience. Concisely: epistemic frontiers are anti-inductive.

  1. ^

    šŸ¦¶

  2. ^

    I scope my arguments only to ā€œtheoretical processingā€ (i.e. purely introspective stuff like math), and I donā€™t think they apply to ā€œempirical processingā€.

  3. ^

    Harmonic (red) vs inharmonic (blue) waveforms. When a waveform is harmonic, efferent neural ensembles can quickly entrain to it and stay in sync with minimal metabolic cost. Alternatively, in the context of predictive processing, we can say that ā€œtop-down predictionsā€ quickly ā€œlearn to predictā€ bottom-up stimuli.

    Comparing harmonic (top) and inharmonic (bottom) waveforms.
  4. ^

    I basically think musical pleasure (and aesthetic pleasure more generally) maps to 1) the build-up of expectations, 2) the violation of those expectations, and 3) the resolution of those violated expectations. Good art has to constantly balance between breaking and affirming automatic expectations. I think the aesthetic chills associates with insights are caused by the same structure as appogiaturasā€”the one-period delay of an expected tone at the end of a highly predictable sequence.

  5. ^
  6. ^

    I highly recommend this entire YT series!

  7. ^

    I think the term originates from Eliezer, but Q Home has more relevant discussion on itā€”also Iā€™m just a big fan of their chaoticoptimal reasoning style in general. Can recommend! šŸµ