Lucidity, science, and acausality illusions Michael E McIntyre University of Cambridge For more on this, websearch ”lucidity principles”

Lucidity, science, andacausality illusions

Michael E McIntyreUniversity of Cambridge

For more on this, websearch ”lucidity principles”


An idea to take seriously (with far-reaching implications):

perception works by model-fitting.




The unconscious brain actively fits an internal modelto the sensory data coming in from the outside world.





If the fit is good enough, the internal model becomesthe perceived reality.




If the fit is good enough, the internal model becomesthe perceived reality.

Example: the “walking lights”:


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What is the perceived reality? A cube rotating? Which way?

And what is a model?




(in the sense used here – a very generalgeneral sense)


Answer: a

partial and approximate representation of reality

(e.g. of a real person really walking, or of a real wire cube really rotating).




Answer: a



NB: Science works the same way.




Answer: a






(e.g Einstein’s Theory of Relativity)


Answer: a




(Implication: science is not about Absolute Truth orAbsolute Proof.)





Answer: a




(Implication: science is not about Absolute Truth orAbsolute Proof.)

(For one thing, we must assume that there’s an outside world…)




Models and model-fitting require mathematics



(e.g. Euclidean geometry).




Implication: we all have unconscious mathematics.





Another way to say it is:

We all have an unconscious power of abstraction








– and what is abstraction? Answer:

the ability to handle many possibilities at once







– and what is abstraction? Answer:

the ability to handle many possibilities at once

(even an infinite number of possibilities).

All this can be seen as a consequence of biological

natural selection



natural selection

along with certain mathematical facts, especially

combinatorial largeness.



natural selection



The unconscious brain must choose the model components to fit to the incoming data from a

combinatorially large number of possibilities.



natural selection



The unconscious brain must choose the model components to fit to the incoming data from a

combinatorially large number of possibilities.

“No organism can afford to be conscious of matterswith which it could deal on unconscious levels.”

– Gregory Bateson



How large is combinatorially large?

Reminder


How large is combinatorially large?

– Lucidity and Science, Part I

1


The unconscious brain is especially interested ininternal models made of patterns that are

as simple as possible

“Platonic” versus “constructivist” – another of our false dichotomies! Again see Lucidity and Science Part II, p. 296.




(Platonic objects – elegance – computational economy)












– what we perceive are perfectly smooth curves – mathematically simple !







(as distinct from what’sactually on the screen!)







(as distinct from what’sactually on the screen!)


A perfectly straight line is another Platonic object












A perfectly straight line is another Platonic object:



There are very many Platonic objects.






There are very many Platonic objects.E.g. an infinitely large number of smooth curves.






There are very many Platonic objects.E.g. an infinitely large number of smooth curves.Here’s another smooth curve – can you see it?






There are very many Platonic objects.E.g. an infinitely large number of smooth curves.Here’s another smooth curve – can you see it? (unconscious

mathematics again – calculusof variations)






“The illusory contour… is constructed,unconsciously. To wonder at its perfection is to glimpse the Platonic” – Part II, p 296

There are very many Platonic objects.E.g. an infinitely large number of smooth curves.Here’s another smooth curve – can you see it?




Contructivism “versus” Platonism:a false dichotomy:

(unconscious mathematics again – calculusof variations)



Model-fitting takes place in spacetime. (The walkinglights demonstrate it, as does any movie.)




We perceive continuous motion despite actual discontinuities.





Musical example: Mozart’s “flowing oil” – a feeling ofcontinuous motion evoked bydiscontinuous sounds (from the K545 piano sonata).





Musical example: Mozart’s “flowing oil” – a feeling ofcontinuous motion evoked bydiscontinuous sounds (from the K545 piano sonata).

The outer indistinct, ragged “contour”reminds us of the playing of a pianist less skilled than Mozart:


Music takes us deeper still.



Natural selection again: auditory scene analysis.



Natural selection again: auditory scene analysis.An implication is that

the harmonic series is another Platonic object,part of the brain’s model-building repertoire:



Natural selection again: auditory scene analysis.An implication is that

the harmonic series is another Platonic object,part of the brain’s model-building repertoire:

Ravel trio: ↑ ↑ ↑ ↑

Indeed, this is evolutionarily ancient. It’s not just ourbrains that make use of the harmonic series:



“And somewhere, out in that blue and green splendour, something was singing: a small voice, high up, starting and ceasing, incredibly sweet. What was it? A little, sweet, wild voice, a music in mid-air. He listened, and his breath caught in his throat.”

– Ursula Le Guin, The Dispossessed



“And somewhere, out in that blue and green splendour, something was singing: a small voice, high up, starting and ceasing, incredibly sweet. What was it? A little, sweet, wild voice, a music in mid-air. He listened, and his breath caught in his throat.”

– Ursula Le Guin, The Dispossessed

Examples: New Zealand tui and kokako:


Tui song recorded inInvercargill, New Zealand):

Recording by Les McPherson

>


actual half speed

Kokako song

Two further points about the “walking lights” example:


1. The model favoured by the unconscious brainisn’t any old linkage: it‘s a particular 3-dimensionallinked structure, with unchanging distancesbetween pairs of links – to good approximation.

(Re “favoured”, see my website’s “On thinking probabilistically”.)

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2. The example illustrates another basic point about our perceptual and cognitiveprocesses: the organic-change principle.

Thanks to natural selection we favour – are perceptually sensitive to – patterns in which

some things change slightly, while others stay the same



User



2. The example illustrates another basic point about our perceptual and cognitiveprocesses: the organic-change principle.

Thanks to natural selection we favour – are perceptually sensitive to – patterns in which

some things change slightly, while others stay the same

(another abstract concept – and it points straight toward the deepest connections between music and mathematics – e.g.“invariance theorems”..)



User


Music consists oforganically-changing sound patterns.

The existence of music – as well as mathematics – isdirect evidence of our

unconscious power of (and interest in) abstraction.


E.g. the way harmony works (websearch “musical hyperspace”):



Powerful, continuous harmonic motion uses organic change – some things changing slightly while others stay the same –where in this case “slightly” can mean either of the twokinds of perceptual proximity, "melodic" or "harmonic“.



Powerful, continuous harmonic motion uses organic change – some things changing slightly while others stay the same –where in this case “slightly” can mean either of the twokinds of perceptual proximity, "melodic" or "harmonic“.

(And powerful chords are made of harmonic-series subsets. Debussy was the firstgreat composer to recognize all this (Peter Platt, Debussy and the Harmonic Series)– in fact Western music has two templates in slight conflict. That conflict is a richartistic resource exploited by musicians with fine-tuning skills.)


One last point:

Hearing music and making sense of it reminds us,again, that

the brain’s unconsciousmodel-fitting takes place in time as well as space


One last point:



(or rather, in this case, musical hyperspace).


One last point:



(or rather, in this case, musical hyperspace).

Therefore,

subjective time can differ from objective(outside-world) time.


Subjective, i.e., perceived, time is an internal-model property.



(So it needn’t obey the usual laws of physics regarding causality.)

Example: acausality illusions

The perceived time of an event can precede the arrivalof sensory data defining the event.






Basic to Western music are events called harmony changes:





Mozart K 545 again:



Basic to Western music are events called harmony changes:



Any composer asked to provide a straightforward orchestral accompaniment wouldput the harmony change at the time of the arrow:

Finally: the central idea or hypothesis that

perception works by model-fitting

deserves to be taken seriously for other reasons too, e.g.,

For more on this, websearch ”lucidity principles” ”V. S. Ramachandran”

● The nature of “self ”: the brain is committee-like, yet has a single internal “self-model” – continuously being fitted to the incoming data (visual, auditory, tactile, and proprioceptive).

● Acausality illusions include the perceived (subjective) times of making decisions (e.g. experiments by Grey Walter and Libet – cf. free-will debate).

(… “perceived times of internal decisions must be later than, and perceived times of outside-world events earlier than… physical events in the nervous system. Only thus can the brain… represent both sets of times in its internal model of the self in its surroundings at the… accuracies needed for survival.” )

(No time for the following slides:)

Mozart K 545:

Not quite Mozart K 545:

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Lucidity, science, and acausality illusions Michael E McIntyre University of Cambridge For more on this, websearch ”lucidity principles”