A Question About the Cortex https://t.co/kCHzJcfTXK
Category: Science, Physics, and Philosophy of Science
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A Question About the Cortex
A Question About the Cortex https://propertarianism.com/2020/06/02/a-question-about-the-cortex-3/
Source date (UTC): 2020-06-02 00:46:04 UTC
Original post: https://twitter.com/i/web/status/1267618451813793795
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A Question About the Cortex
A QUESTION ABOUT THE CORTEX
—“Does the commensurability of the edge of the cerebral cortex require fractal geometry, like a coastline? Does it have self similarity?”—The Nationalist @Nationalist7346
No.
the outer layer of the cortex is just a couple of mm thick; consists two functions (what,where), using six layers; divided into columns and modules (groups of columns); homogenous in structure but differing in neural density by physical origin of nerves that enter them.
So no it’s not fractal: the average size of a human cortex, if laid out flat would be approximately the size of a dinner napkin, and just as thick. The rest of the neocortex consists entirely of white matter (nerve fibers: axons) which connect everything to everything.
With the hippocampus consolidating and organizing information, and then using rehearsal (replay) to encode episodes of memory, and thalamus controlling attention (what gets thru to the neocortex for computation, and basal ganglia that surrounds both releasing physical actions.
Most of the advanced functions of the brain consist of these three ‘levers’ and the natural increase in reflection created by increasing brain size, from back (senses) to front (permuting, planning, manipulating). So the brain functions as a series of loops (operating system)
That recursively process a moment of information and merge it with the next moment of information in a continuous stream which we can ‘buffer’ with a half life of just a few seconds, and no more than twenty or so. By Comparison of these moments we discern change in state.
When people say the brain isn’t a computer they’re only a tiny bit right. It does operate in binary (on off) and frequency (hertz), and by competition for attention but with unimaginable numbers of connections in unimaginable parallel, in a continuous loop (OS).
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A Question About the Cortex
A QUESTION ABOUT THE CORTEX
—“Does the commensurability of the edge of the cerebral cortex require fractal geometry, like a coastline? Does it have self similarity?”—The Nationalist @Nationalist7346
No.
the outer layer of the cortex is just a couple of mm thick; consists two functions (what,where), using six layers; divided into columns and modules (groups of columns); homogenous in structure but differing in neural density by physical origin of nerves that enter them.
So no it’s not fractal: the average size of a human cortex, if laid out flat would be approximately the size of a dinner napkin, and just as thick. The rest of the neocortex consists entirely of white matter (nerve fibers: axons) which connect everything to everything.
With the hippocampus consolidating and organizing information, and then using rehearsal (replay) to encode episodes of memory, and thalamus controlling attention (what gets thru to the neocortex for computation, and basal ganglia that surrounds both releasing physical actions.
Most of the advanced functions of the brain consist of these three ‘levers’ and the natural increase in reflection created by increasing brain size, from back (senses) to front (permuting, planning, manipulating). So the brain functions as a series of loops (operating system)
That recursively process a moment of information and merge it with the next moment of information in a continuous stream which we can ‘buffer’ with a half life of just a few seconds, and no more than twenty or so. By Comparison of these moments we discern change in state.
When people say the brain isn’t a computer they’re only a tiny bit right. It does operate in binary (on off) and frequency (hertz), and by competition for attention but with unimaginable numbers of connections in unimaginable parallel, in a continuous loop (OS).
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Terminal Velocity of a Cat vs Mouse?
Terminal Velocity of a Cat vs Mouse? https://t.co/Tc0jSXg7s4
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Terminal Velocity of a Cat vs Mouse?
Terminal Velocity of a Cat vs Mouse? https://propertarianism.com/2020/06/02/terminal-velocity-of-a-cat-vs-mouse/
Source date (UTC): 2020-06-02 00:42:44 UTC
Original post: https://twitter.com/i/web/status/1267617611153657858
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Terminal Velocity of a Cat vs Mouse?
QUESTION: One question. What is the difference between the terminal velocity of a cat, and a mouse? ANSWER: A man’s terminal velocity is 210 km/h (130 mph). A cat’s terminal velocity is 100 km/h (60 mph) A mouse’s terminal velocity is ~10km/h (6 mph) OLD STUFF: “Down 1000 foot mine shaft, a mouse walks away (not true), a rat dies (certainly), a man breaks (certainly, very), and a horse splashes.”
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Terminal Velocity of a Cat vs Mouse?
QUESTION: One question. What is the difference between the terminal velocity of a cat, and a mouse? ANSWER: A man’s terminal velocity is 210 km/h (130 mph). A cat’s terminal velocity is 100 km/h (60 mph) A mouse’s terminal velocity is ~10km/h (6 mph) OLD STUFF: “Down 1000 foot mine shaft, a mouse walks away (not true), a rat dies (certainly), a man breaks (certainly, very), and a horse splashes.”
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Comments on Nate Silver’s Book
Doolittle’s Comments On Silver’s Quotes from his Book:
The story data tells us is often the one we’d like to hear, and we usually make sure it has a happy ending.
There are entire disciplines in which predictions have been failing, often at a great cost to society.
Some stone-age strengths have become information-age weaknesses.
We can never make perfectly objective predictions. They will always be tainted by our subjective point of view.
(CD: They will always be tainted by our wants for the world rather than untainted by a description of the world. we live in paradigms of utility.)A belief in the objective truth -and a commitment to pursuing it- is the first prerequisite of making better predictions.
(CD: very few of us seek truth. We all seek utility not truth. For some of us truth and utility are identical. for others it forces them into competition with darwin – and truth is the enemy of false genes as much as false ideas.)Prediction is important because it connects subjective and objective reality.
(CD: prediction is important because it falsifies many subjective realities training us to predict objective realities.)We are undoubtedly living with many delusions that we do not even realize.
(CD: psychology must be the study of cognitive error, bias, wishful thinking and deceit – and the sciences efforts at compensating for them.)We must become more comfortable with probability and uncertainty.
- We must think more carefully about the assumptions and beliefs that we bring to a problem.
- A certain amount of immersion in a topic will provide disproportionally more insight that an executive summary.
- The signal is the truth. The noise is what distracts us from the truth.
- Precise forecasts masquerade as accurate ones.
- If you have reason to think that yesterday’s forecast was wrong, there is no glory in sticking to it.
New ideas are sometimes found in the most granular details of a problem where few others bother to look.
Extrapolation is a very basic method of prediction -usually, much too basic.
(CD: One must never extrapolate a trend – everything in nature equilibrates.)In many cases involving predictions about human activity, the very act of prediction can alter the way that people behave.
The most effective flu prediction might be the one that fails to come to fruition because it motivates people toward more healthful choices.
While simplicity can be a virtue for a model, a model should at least be sophisticatedly simple.
(CD: the quality of a prediction is dependent upon the quality and quantity of information, not the complexity of the model.)We can never achieve perfect objectivity, rationality, or accuracy in our beliefs. Instead, we can strive to be less subjective, less irrational, and less wrong.
(CD: we have spent, because of theology, far too much of our history in via-positiva justification, and are still escaping it. Instead we must focus on via positiva reduction of ignorance, error, bias, wishful thinking, and deceit.)Recently, […] some well-respected statisticians have begun to argue that frequentist statistics should no longer be taught to undergraduates. […] In fact, if what you read what’s been written in the past ten years, it’s hard to find anything that doesn’t advocate a Bayesian approach.
(CD: Bayseian accounting is superior to mathematical averages. when stated in this manner the difference in quality of prediction is rather obvious.)There is strong empirical evidence that there is a benefit in aggregating different forecasts.
(CD: competition between theories produces information not only about one theory but about the minds of man making those theories.)This is another of those Information-age risks: we share so much information that our independence is reduced. (CD: information that is not true (parsimonious)
Perhaps the central finding of behavioral economics is that most of us are overconfident when we make predictions.
(CD: we evolved overconfidence because action for gain is necessary. We confuse the necessity of action for gain with applying it beyond its evolutionary purpose.)In science, progress is possible. In fact, if one believes in Bayes’ theorem, scientific progress is inevitable as predictions are made and as beliefs are tested and refined.
(CD: Whether mathematical Bayes or Philosophical Popper, or Cognitive science’s lesson that our brains operate by massively parallel similarly bayesian means, learning through trial and error no matter how error prone, will produce either progress in knowledge or failure to survive.)The March toward scientific progress is not always straightforward, and some well-regarded (even “consensus”) theories are later proved wrong- but either way science tends to move toward the truth.
(CD: The difference between the fundamental sciences and entrepreneurship, and daily action is that fundamental science is a luxury good, the findings of which may propagate through the polity over time – but daily action in life has no such luxury of time and cost – we must produce returns. This conflict illustrates the problem of our evolutionary demand for action influencing our overconfidence in science, and conversely, our science ignoring time and cost. )Under Bayes’ theorem, no theory is perfect. Rather, it is a work in progress, always subject to further refinement and testing.
(CD: I knew bayes first, Godel second, hayek third, popper fourt, and kuhn fifth. Bayes provides accounting on one end, then popper, then kuhn, and then hayek on the other end. Only during the past twenty years have we understood the brain’s mixture of elementary composition and spatial attribution. Same process, different scales. It’s not just bayesian – it’s the only possible epistemological method and everything else is a legacy failure we call ‘justificationism’.)
-
Comments on Nate Silver’s Book
Doolittle’s Comments On Silver’s Quotes from his Book:
The story data tells us is often the one we’d like to hear, and we usually make sure it has a happy ending.
There are entire disciplines in which predictions have been failing, often at a great cost to society.
Some stone-age strengths have become information-age weaknesses.
We can never make perfectly objective predictions. They will always be tainted by our subjective point of view.
(CD: They will always be tainted by our wants for the world rather than untainted by a description of the world. we live in paradigms of utility.)A belief in the objective truth -and a commitment to pursuing it- is the first prerequisite of making better predictions.
(CD: very few of us seek truth. We all seek utility not truth. For some of us truth and utility are identical. for others it forces them into competition with darwin – and truth is the enemy of false genes as much as false ideas.)Prediction is important because it connects subjective and objective reality.
(CD: prediction is important because it falsifies many subjective realities training us to predict objective realities.)We are undoubtedly living with many delusions that we do not even realize.
(CD: psychology must be the study of cognitive error, bias, wishful thinking and deceit – and the sciences efforts at compensating for them.)We must become more comfortable with probability and uncertainty.
- We must think more carefully about the assumptions and beliefs that we bring to a problem.
- A certain amount of immersion in a topic will provide disproportionally more insight that an executive summary.
- The signal is the truth. The noise is what distracts us from the truth.
- Precise forecasts masquerade as accurate ones.
- If you have reason to think that yesterday’s forecast was wrong, there is no glory in sticking to it.
New ideas are sometimes found in the most granular details of a problem where few others bother to look.
Extrapolation is a very basic method of prediction -usually, much too basic.
(CD: One must never extrapolate a trend – everything in nature equilibrates.)In many cases involving predictions about human activity, the very act of prediction can alter the way that people behave.
The most effective flu prediction might be the one that fails to come to fruition because it motivates people toward more healthful choices.
While simplicity can be a virtue for a model, a model should at least be sophisticatedly simple.
(CD: the quality of a prediction is dependent upon the quality and quantity of information, not the complexity of the model.)We can never achieve perfect objectivity, rationality, or accuracy in our beliefs. Instead, we can strive to be less subjective, less irrational, and less wrong.
(CD: we have spent, because of theology, far too much of our history in via-positiva justification, and are still escaping it. Instead we must focus on via positiva reduction of ignorance, error, bias, wishful thinking, and deceit.)Recently, […] some well-respected statisticians have begun to argue that frequentist statistics should no longer be taught to undergraduates. […] In fact, if what you read what’s been written in the past ten years, it’s hard to find anything that doesn’t advocate a Bayesian approach.
(CD: Bayseian accounting is superior to mathematical averages. when stated in this manner the difference in quality of prediction is rather obvious.)There is strong empirical evidence that there is a benefit in aggregating different forecasts.
(CD: competition between theories produces information not only about one theory but about the minds of man making those theories.)This is another of those Information-age risks: we share so much information that our independence is reduced. (CD: information that is not true (parsimonious)
Perhaps the central finding of behavioral economics is that most of us are overconfident when we make predictions.
(CD: we evolved overconfidence because action for gain is necessary. We confuse the necessity of action for gain with applying it beyond its evolutionary purpose.)In science, progress is possible. In fact, if one believes in Bayes’ theorem, scientific progress is inevitable as predictions are made and as beliefs are tested and refined.
(CD: Whether mathematical Bayes or Philosophical Popper, or Cognitive science’s lesson that our brains operate by massively parallel similarly bayesian means, learning through trial and error no matter how error prone, will produce either progress in knowledge or failure to survive.)The March toward scientific progress is not always straightforward, and some well-regarded (even “consensus”) theories are later proved wrong- but either way science tends to move toward the truth.
(CD: The difference between the fundamental sciences and entrepreneurship, and daily action is that fundamental science is a luxury good, the findings of which may propagate through the polity over time – but daily action in life has no such luxury of time and cost – we must produce returns. This conflict illustrates the problem of our evolutionary demand for action influencing our overconfidence in science, and conversely, our science ignoring time and cost. )Under Bayes’ theorem, no theory is perfect. Rather, it is a work in progress, always subject to further refinement and testing.
(CD: I knew bayes first, Godel second, hayek third, popper fourt, and kuhn fifth. Bayes provides accounting on one end, then popper, then kuhn, and then hayek on the other end. Only during the past twenty years have we understood the brain’s mixture of elementary composition and spatial attribution. Same process, different scales. It’s not just bayesian – it’s the only possible epistemological method and everything else is a legacy failure we call ‘justificationism’.)