Neuroscientists Keep Peddling Explanatory Snake Oil

 In the nineteenth century a widely practiced scam was the sale of snake oil. A snake oil salesman would typically travel around from town to town, typically new towns in the western United States that had a shortage of doctors.  He would often travel in a horse-pulled wagon called a medicine wagon. The snake oil salesman would make all kinds of groundless claims about the medicinal value of his worthless bottles. After a good day's sale, the snake oil salesman would be off to the next town. By keeping on the road, he would avoid the problem of customers demanding their money back because the product failed to work. Below we see a newspaper ad placed by one of the traveling snake oil salesmen:

Notice the sweeping claim in the ad: the claim that the seller could "heal all manner of disease." Typically the person making such a claim would be selling products of little or no medicinal value. 

As the Wild, Wild West of the United States got more and more tame and adequately filled by regular doctors, snake oil treatments fell into disrepute, and the very term "snake oil" became a term synonymous with cons and cheats. But it is easy to imagine how snake oil manufacturers could have caused snake oil to become very prestigious.  All that would have been needed was the establishment of Departments of Snake Oil Medicine in colleges and universities, populated by Professors of Snake Oil Medicine. 

Once some type of claim gets taught by some type of department in colleges and universities, the public starts thinking of the claim as respectable and well-founded. What happens is that a university or college has great prestige, and is regarded as a lofty teacher of truth and a storehouse of knowledge. So when some new claim gets institutionalized by the establishment of a university department or college department, people tend to think such a claim is well-established. If there were hundreds of Departments of Astrology in colleges and universities all over the country, people would tend to think that astrology is well-established, and that consulting your horoscope is a good way to judge your future. 

But how could some Department of Snake Oil Medicine ever produce research that would give some veneer or aura of scientific respectability to the claims of snake oil advocates? That would be relatively easy. A variety of bad research techniques could be employed. It would work rather like this:

(1) When snake oil advocates did studies that showed no medical effectiveness in people using snake oil, such studies would simply be filed away in the file drawers of scientists, and not submitted for publication. 

(2) Snake oil advocates would run very small studies, and by pure chance a certain number of them (maybe 5% or so) would seem to show marginal effectiveness. Such studies would be the ones submitted for publication in journals. 

(3) Noise-mining and cherry-picking could be heavily utilized. The case histories of thousands of snake oil users could be very carefully scanned, to look for cases in which some type of ailment (perhaps an infectious disease such as the flu) seemed to become less troubling at about the same time someone had drunk or applied snake oil. Such cases would be heavily promoted as proof of the wonderful effectiveness of snake oil. 

(4) Bad measurement techniques and poor analysis techniques could be used when evaluating someone's health, allowing a kind of see-what-you-are-hoping-to-see analysis. For example, when studying the effectiveness of snake oil in treating fevers, snake oil advocates might rely on dubious "rate how you feel on a scale of 1 to 10" survey answers, rather than much more reliable thermometer measures of a person's temperature. 

(5) Misleading visuals might be used, such as body maps showing in bright red regions of the body allegedly treatable by snake oil medicine. 

By the use of such techniques and many similar misleading and poor-practice techniques, Professors of Snake Oil Medicine could easily produce papers or articles that seemed to provide superficial evidence for the effectiveness of snake oil treatments, even though the treatments had no effectiveness. And if the Professors of Snake Oil Medicine were to get heavy funding (directly or indirectly) from snake oil manufacturers who made tons of money from selling snake oil, we can imagine that many university and college Departments of Snake Oil Medicine could stay well-funded. Of course, such professors would have a strong financial motive to produce results pleasing to their corporate sponsors. 

 In a previous post I stated the rule below:

The rule of well-funded and highly motivated research communities: almost any large well-funded research community eagerly desiring to prove some particular claim can be expected to  occasionally produce superficially persuasive evidence in support of such a claim, even if the claim is untrue.  

Such a rule would help Professors of Snake Oil Medicine to be able to claim that they were producing some studies in support of their claims. What would also help very much would be if the Professors of Snake Oil Medicine were to succeed in enforcing taboos and if such professors were to succeed in demonizing, slandering and gaslighting all those who presented evidence against the effectiveness of snake oil.  If such professors somehow made it a taboo to do research discrediting the claims of snake oil proponents, that would be a huge element in helping Departments of Snake Oil Medicine to become well-established.

Now, you may think that the imaginary tale I describe above is one too hard to believe. But the truth is that there actually occurred something very much like what I have described above. What happened is that they established in colleges and universities Departments of Neuroscience dedicated to the propagation of the belief that minds are produced by brains, and that brains are the storage place of human memories. Such claims were very much explanatory snake oil. Although countless billions of dollars have been spent trying to prove such claims, they have never been established by robust evidence. To the contrary, research on brains has produced innumerable reasons for rejecting the claim that minds are produced by brains, and that brains are the storage place of human memories. Such reasons are discussed in the posts of this blog site. 

So how is it that our Departments of Neuroscience have stayed in business and had such high influence? How have Professors of Neuroscience got so many people to believe the unbelievable dogmas they teach? This occurred because such professors used techniques just like I described above. Some of the techniques that such professors have used are listed below:

• Quick and dirty" experimental designs
• Way-too-small study group sizes
• Cherry-picked data subsets
• Ignoring two hundred years of well-documented psychical research presenting evidence contrary to neuroscientist dogmas
• Unreliable claims about fear or recall in rodents, produced by bad measurement methods such as "freezing behavior" estimations 
• Citations of poor-quality papers
• "Keep torturing the data until it confesses" tactics
• Constant reiterations of dogmas disproven or discredited by the facts observed by neuroscientists themselves
• Ignoring unusual case histories that conflict with "brains make minds" claims or "brains store memories" claims
• "Lying with colors" fMRI studies containing misleading visuals
• Lack of pre-registration
• Weird programming loop contortions of data, in which investigators senselessly think they have the right to programmatically perform arbitrary convolutions on the original data and still claim their twisted output is "what the brain is telling us"
• Professor pareidolia resembling "Jesus in my toast" claims
• Ignoring physical shortfalls of all brains that contradict or discredit some hypothesis being tested
• Unreliable and convoluted "spaghetti code" analysis
• Lack of detailed blinding protocols
• Ignoring observation failures
• Poor reproducibility
• HARKing 
• Not publishing null results
• P-hacking
• Title or abstract claims not matching results
• Lack of control subjects, or too few of them
• Blending real data and artificial (fake) data, with the fake data called "simulated" as if something "simulated" was better than something fake
• Unwarranted use of cell names and cell nicknames
• Unwarranted assumptions of causal effects, with a massive failure to consider reasonable alternative explanations of causes
• By a constant use of the passive voice rather than the active voice, a failure to document in most scientific papers the most basic facts needed to help police fraud, facts such as exactly who made an observation, the exact date when the observation was made, and where the observation was made. 

Today's professors of neuroscience do not get payments from snake oil manufacturers. But they often receive (directly or indirectly) very big financial benefits from pharmaceutical manufacturers and the manufacturers of biomedical devices, who may fund research or offer lucrative consulting fees for professors making claims that enhance the stock prices of such manufacturers.  

Just as I imagined Professors of Snake Oil Medicine creating some taboo against research challenging the effectiveness of snake oil, with such professors using techniques of gaslighting and slander to marginalize researchers producing such research, professors of neuroscience have used similar techniques to try to create some taboo against research challenging the "brains make minds" dogma. We have two hundred years of published research documenting the reality of spooky mental phenomena that cannot be explained by brains,  things such as ESP, clairvoyance, paranormal phenomena, apparition sightings, out-of-body experiences and near-death experiences. The professors of neuroscience have declared such research topics to be taboo, and have ignored all of the psychical research that defies their "brains make minds" dogma. Such professors have tried to gaslight, slander and marginalize respectable researchers producing such results that defy brains make minds" dogma.

The "smoke and mirrors" world of modern neuroscience resembles the "smoke and mirrors" shenanigans that would have gone on within Departments of Snake Oil Medicine if they had ever been established.  For a look at a recent example of some of this foolishness, read the recent "Mad in America" article here.  We read of a patient who would not give "informed consent" to a treatment risking her life, who was electrically shocked until she relented, with this being hailed as "restoring decision-making capacity," in some twisted mess of neurobabble. 

A recent article in The Atlantic is entitled "Science Is Drowning In AI Slop." We read that soon after the popular ChatGPT AI program was introduced a few years ago, there was a huge spike in submissions to science journals and science preprint servers. We can imagine how that worked:  scientists stuffing their papers with lots of AI-generated paragraphs and AI-generated charts. We read that some researchers who would rarely submit a paper to a journal are now submitting dozens per year. We read that scientists are running machine-learning algorithms on data, claiming to have produced some interesting outcome. The article calls this "a fraud template for AI researchers," noting "as long as the outcome isn't too interesting, few people, if any, will bother to vet it." 

I was for a long time a software developer, and I know how to read programming code. When I look at the programming code used for some of the low-quality "keep torturing the data until it confesses" neuroscience papers that I read, I will often see code that makes me think something along the lines of "no human would ever write junk this unreadable."  My guess is that neuroscientists are sometimes using AI-generated computer code to do black-box "analytics" on brain scan data and EEG data. I suspect that often both the code and the description of the code in the paper is AI-generated, and that often the author or authors do not even understand very well what the code is doing. The obscure output from such a thing is correctly described as AI slop. But a human peer reviewer may be unlikely to catch the nonsense, partially because (according to the article) much of peer review is now done by AI rather than humans. Another article about a popular scientific preprint server states, "Starting in early 2025, he says, the number of 'AI slop' submissions went up exponentially."

We read this, referring to the LLM algorithms used by AI programs:

"Other preprint servers have also seen a rise in poor, AI-generated content, Nosek says—including the generalist preprint service hosted by OSF, which stopped accepting any new submissions in August 2025 'because a majority of submissions were very low quality.'  PsyArXiv, a community-run psychology preprint server within OSF, swapped from moderating submissions after posting to moderating them in advance for the same reason.  Wijers says the new safeguard is needed in part because LLMs will improve, making it harder or impossible for moderators to distinguish fake AI-generated papers from legitimate work."

Evolutionary Psychologist Tooby Kept Teaching Falsehoods About Brain Programs

For twenty years the Edge Foundation seemed to exist mainly to publish an annual survey in which a group of people (mainly scientists) were asked some Annual Question, and wrote their answers at length.  These annual surveys were published in book form between 1998 and 2018, and you can read most of them for free on this page of the Edge Foundation's site.  For years most of the financial contributions that funded the foundation came from Jeffrey Epstein, the disgraced billionaire who committed suicide in jail after being charged with the sex trafficking of minors.  Epstein was convicted of procuring a child for prostitution in 2008, but he continued for quite a few years before and after that conviction to mingle with scientists and high-tech luminaries at exclusive social events such as dinner parties and cocktail parties, as his sex crimes continued.

What we usually got in the yearly books answering the Annual Question were a group of people advancing an Epstein-friendly view of the world, by which I mean any viewpoint which would not trouble Jeffrey too much as he continued his predatory sex crimes (which seemed to have started long before 2008).  Typically humans would be depicted as accidental piles of chemicals rather than souls or bodies that are mysteriously arising marvels of biological organization. It was as if each of the 100+ essays in each book had been carefully chosen to avoid anything that might make Jeffrey Epstein uncomfortable.  Although occupation-wise the authors were a fairly diverse group, the books were a very monochrome affair, with almost no writers deviating from the Official Party Line of modern academia.  One of the worst examples of the Epstein-compatible viewpoints was the following appalling statement by biologist Richard Dawkins for the 2006 Annual Question:

"But doesn't a truly scientific, mechanistic view of the nervous system make nonsense of the very idea of responsibility, whether diminished or not? Any crime, however heinous, is in principle to be blamed on antecedent conditions acting through the accused's physiology, heredity and environment."

During the twenty years in which the Annual Question books were being published, we seemed to have heard scarcely a peep from any professor along the lines of "I don't want to participate in some book series mainly financed by a child-abusing sex criminal."  During the same period, the contributors to the Annual Questions were marketed as some kind of brilliant elite.  

At the Edge.org site we had many a writer teaching the most morally appalling nonsense. At the site one well-known Darwinist biologist in America taught the morally destructive doctrine of determinism, the nonsensical claim that humans lack free will. I can imagine Jeffrey Epstein reading such writing with a smile on his face, thinking that he is not really to blame, no matter how many kids he rapes, on the grounds that his atoms made him do it. 

Now the Edge.org site has apparently run out of funding, and has no more annual survey questions. Its 2018 Annual Question survey was the last of its series of questions.  At the site we have no mention of how it was funded most notably by a man now universally regarded as a notorious sex criminal. There's an About page on the site, which makes no mention of Jeffrey  Epstein. There is a grand bit of hogwash in which the often immoral and often nonsensical writings of those at Edge.org are hailed as some type of sublime wisdom. It's some "the scientists will take over philosophy" rubbish. We read this: "The third culture consists of those scientists and other thinkers in the empirical world who, through their work and expository writing, are taking the place of the traditional intellectual in rendering visible the deeper meanings of our lives, redefining who and what we are. "   But we have scant evidence at Edge.org that the scientists contributing were suited for such a task.  The page boasts that its writers "create their own reality."  But isn't it better for a scientist to study reality as it exists, rather than making up some reality that you invented?

Now as the first article on the front page of Edge.org I see a tribute to the late John Tooby, who the site calls the founder of evolutionary psychology. Evolutionary psychology is a  cesspool of junk science that someone like Jeffrey Epstein probably was a big fan of. The idea behind evolutionary psychology is that you try to explain the human mind and human behavior by claiming that evolution made us act such and such a way so that we would survive better and reproduce more in the state that humans existed before civilization.  

Evolutionary psychology is one of the worst junkyards of unscientific and unfounded speculation in academia. Sitting on their armchairs, evolutionary psychologists spend endless hours making cheesy impossible-to-test speculations such as "you have such and such a mental trait because cavemen needed such and such a trait for such and such a reason," or "people still act in such and such a way because evolution made cavemen act in such and such a way for such and such a reason."

In the document "Conceptual Foundations of Evolutionary Psychology" we get some examples of the falsehoods and nonsense taught by John Tooby. He taught the fictitious idea that the human mind consists of "programs" that govern our behavior. No such programs have ever been discovered. On and on Tooby goes, misspeaking over and over again, claiming programs in the brain. In the 63-page document, he uses the word "program" 193 times. An example of his deceit comes on page 13, when he states, "These causal relations between information and behavior are created by neural circuits in the brain, which function as programs that process information." The claim has no basis in fact. No one has ever discovered the slightest trace of anything like a computer program by examining brain tissue or neural circuits.  Below are some more similar falsehoods told by Tooby:

• Page 17: "The programs that comprise the human brain were sculpted over evolutionary time by the ancestral environments and selection pressures experienced by the hunter-gatherers from whom we are descended (Advances 2 and 4)." The claim is completely fictional. The human brain consists of elements such as neurons, dendrites and synapses. No one has ever found anything like a program in a human brain. Like almost all human cells, neurons contain DNA. But DNA and its genes are not any type of program. A gene merely tells what amino acids make up a protein, and it is false to claim that DNA is any program for behavior. 
• Page 19: "The brain is fantastically complex, packed with programs, most of which are currently unknown to science." No one has ever discovered any type of program in a human brain. 
• Page 20: "When an organism reproduces, genes that cause the development of its design features are introduced into its offspring." Genes do not explain how there occurs the progression from a one-celled zygote (existing just after impregnation) to the vast organization of a human body. Genes merely specify low-level chemical information such as which amino acids make up a protein. Neither DNA nor its genes "cause the development" of a human body or a human mind. Saying genes "cause the development" of a human body is as false as saying that bricks and pipes and wood beams cause the construction of a large apartment building. 
• Page 21: "Genes are the means by which functional design features replicate themselves from parent to offspring. They can be thought of as particles of design."  This was a fiction. Genes do not specify the design of any human body or any organ or any cell or any organelle of any cell. 
• Page 25: "The human neural architecture is a complex functional system, composed of programs whose design was engineered by natural selection to solve specific adaptive problems." No one has ever discovered any type of program in a human brain. Brains consist of neurons, dendrites and synapses, not programs. The phrase "engineered by natural selection" is a doubly deceptive phrase. The mere "survival of the fittest" effect of so-called natural selection is not actually selection, and is not any engineering effect. The bodies of organisms are replete with abundant engineering effects, which are not explained by any unguided chance processes such as so-called natural selection. As the botanist Hugo de Vries stated,  "Natural selection is a sieve. It creates nothing, as is so often assumed; it only sifts." ( "The Mutation Theory. Volume II, page 609. )
• Page 26: "The neural programs that allow humans to acquire and use spoken language are adaptations, specialized by selection for that task (Pinker, 1994; Pinker & Bloom, 1990)."  A brain has no programs. No one understands the origin of language.  It is false to claim that the ability to speak a language is an adaption. 
• Page 34: "Genes are regulatory elements that use environments to construct organisms." Another glaring falsehood. Genes do not construct organisms or any of their organ systems or any of their organs or any of the cells of such organs or any of the organelles of such cells. Genes do not have any specification of such things. 
• Page 36: "Some neural programs were designed by natural selection to take in substantial amounts of environmental input (e.g., the language acquisition device) whereas others were designed to take in less information (e.g., the reflex that causes the eye to blink in response to a looming figure)." Here we have a triple abuse of language befitting a deceiver like Tooby. First there is a false claim that there are neural programs. Then we have a use of the misleading term "natural selection" which does not refer to any actual selection ("selection" being a term meaning a choice by a conscious agent). Then there is a reference to an imagined blind, unconscious effect (so-called "natural selection") which is described as designing things, as if a blind, unconscious effect had planning and imagination abilities. 
• Page 52:  "Again, a superordinate program is needed that coordinates these components, snapping each into the right configuration at the right time. We have proposed that emotions are such programs (Cosmides & Tooby, 2000b; Tooby, 1985; Tooby & Cosmides, 1990a)."  Utter nonsense. Emotions are not programs.  The nonsense in the quote is repeated endlessly by Tooby. 

This 63-page document suggests Tooby was no real scholar of the brain. In the document he makes no mention of synapses, only one mention of the word "neuron," and only one mention of DNA. What Tooby mainly does is just make stuff up, acting like an armchair reasoner too lazy to get up and read up on the things he is pontificating about.  To read 40 quotations by scientists and doctors disputing claims about genes made like the ones Tooby made above, see my post here. Tooby's document has 45 uses of the words "genes," 10 uses of the word "gene," and 91 uses of the word "genetic." But nowhere does it refer to amino acids, suggesting Tooby had no understanding of the correct nature of a gene, which is a list of the amino acids used by a protein. In the document his misstatements about genes are as huge and frequent as his misstatements about brains. 

Showing a complete failure to understand the lack of any real intelligence in computers, Tooby laughably states, "The greater the number of functionally specialized programs (or subroutines) your computer has installed, the more intelligent your computer is." No, actually your computer has no real intelligence, and your computer does not become more intelligent when you download more software. 

What is it that a brain would need to have to be actually running something like a computer program? It would need all of these things:

(1) Something like a CPU and a system capable of transmitting information as reliably as in a computer. The brain has no such things. Synapses do not reliably transmit information, with a signal being transmitted with less than 50% likelihood over each synaptic gap of a chemical synapse. 

(2) Something like an operating system, something like UNIX or Windows or MS-DOS. The brain has no such thing. 

(3) Something like a programming language, required for program to be written. The brain has no such thing. 

(4) Something like application programs, written in such a programming language. The brain has no such thing. 

What are the outputs of computer programs? Effects such as the rearrangement of pixels on a computer screen. Such effects do not resemble the outputs and main aspects of a human mind, which are things like understanding, consciousness, experience, aspirations, beliefs and emotions, things which do not match any outputs of a computer program. Computers and their programs are not conscious, have no real understanding, and do not have mental experiences or beliefs. 

So saying the mind does what it does because the brain has programs is like saying your toaster can fly to the moon because your toaster is a moon rocket. Your toaster has none of the things it would have to have to be able to fly to the moon. 

Tooby's false teachings are shown not just by the fact that brains have none of the programs that Tooby claimed that brains have. The false nature of his teachings is shown by the fact that humans do not behave as if they were under the control of a program or programs. A computer program typically offers a limited set of responses that can occur given some inputs. For example, an "if/else" statement typically divides responses into two possibilities. What is called a "switch" statement can offer a wider variety of possible responses, but it is only a limited set of possible responses; and any one input always produces the same output. Humans, on the other hand, may respond in an unlimited variety of ways, in some particular situation or facing some particular stimulus. And human responses are not predictable, unlike what you typically have in a computer program, where the output is completely predictable from an input. Brains do not store programs, and people do not act in a way suggesting control by some program or set of programs. 

For more on the sordid nature of evolutionary psychology, see the long article "Why Jeffrey Epstein Loved Evolutionary Psychology." 

They Also Mentally Calculated Faster Than a Brain Could Ever Do

The credibility of claims that mathematical calculation comes from brains is inversely proportional to the speed and capacity and reliability at which things can be mentally calculated. There are numerous signal slowing factors in the brain, such as the relatively slow speed of dendrites, and the cumulative effect of synaptic delays in which signals have to travel over relatively slow chemical synapses (by far the most common type of synapse in the brain). As explained in my post here, such physical factors should cause brain signals to move at a typical speed very many times slower than the often cited figure of 100 meters per second: a sluggish "snail's pace" speed of only about a centimeter per second (about half an inch per second).  Ordinary everyday evidence of very fast and accurate math calculation is therefore evidence against claims that unaided human math calculation occurs because of brain activity, particularly because the brain is totally lacking in the things humans add to constructed objects to allow fast recall (things such as sorting and addressing and indexes). Chemical synapses in the brain do not even reliably transmit signals. Scientific papers say that each time a signal is transmitted across a chemical synapse, it is transmitted with a reliability of 50% or less.  (A paper states, "Several recent studies have documented the unreliability of central nervous system synapses: typically, a postsynaptic response is produced less than half of the time when a presynaptic nerve impulse arrives at a synapse." Another scientific paper says, "In the cortex, individual synapses seem to be extremely unreliable: the probability of transmitter release in response to a single action potential can be as low as 0.1 or lower.")  The more evidence we have of very fast and very accurate calculation occurred by humans unaided by any devices,  the stronger is the evidence against the claim that human math calculation occurs from brain activity. 

It is therefore very important to collect and study all cases of exceptional human mathematics performance. The more such cases we find, and the more dramatic such cases are, the stronger is the case against the claim that unaided human math calculation is a neural phenomenon. Or to put it another way, the credibility of claims that math calculation is a brain phenomenon is inversely proportional to the speed and reliability of the best cases of human math  performance.  The more cases that can be found of humans that seem to calculate too quickly and too accurately for a noisy address-free brain to ever do,  the stronger is the case that human thinking is not a neural phenomenon but instead a spiritual or psychic or metaphysical phenomenon.  My previous post "They Mentally Calculated Faster Than a Brain Could Ever Do" described many such cases, as did my post "They Too Mentally Calculated Faster Than a Brain Could Ever Do." Now let us look at some more cases of this type. 

Some cases of exceptional math performance can be found in the book The Great Mental Calculators by Steven B. Smith. Below from page 179 are the results of very hard math calculations by Arthur Griffith (born 1880):

We see above a record of blazing-fast speed in very hard math calculations.  The "extraction of cube root" referred to is solving the problem: what number multiplied by itself three times gives the supplied number?  The "extraction of a square root" referred to is solving the problem: what number multiplied by itself twice times gives the supplied number? 

A long newspaper article on Arthur Griffith can be read here. We read this:

"While engaged in working a series of tests Griffith multiplied 142,857,143 by 465,891,443 and obtained the product 66,555,920,495,127,349, in ten seconds. He multiplied 999,999,999 by 327,841,277, and had completed the writing of the product, 327,841,276,672,188,723, in nine and a half seconds. Other numbers required a longer time, but in no case was the time needed to complete the multiplication more than thirty seconds. Factors of numbers were called out as quickly as the number was submitted. The fifth power of 996, which equals 980,159,361,278,976, was obtained in thirty-seven seconds. Cubes of large numbers were given without hesitation, and in case the number was not a perfect cube the number which is the nearest perfect cube was given at once."

Using the web site here, I verified that the first  multiplication result is correct. The second multiplication result, 327,841,276,672,188,723, is incorrect only in the fifth-to-last digit, all other digits being correct. We can't tell whether it was a calculation error by Griffith, or an error by whoever wrote down his answer or who typeset the newspaper article. 

On page 297 the author says he was asked by Wim Klein to give two five-digit numbers. The author gave 57,825 and 13,489. In 44 seconds Klein multiplied the two numbers together mentally. On the same page we are told Klein extracted the 19th root of a 133-digit number in under two minutes. 

On page 301 we read this about lightning-fast calculations by Maurice Dagbert:

The same page refers to astounding multitasking and number memorization capabilities of Dagbert:

We read on the next page that Dagbert does not write any intermediate results, but simply announces the number calculated. On page 58 of the book Mental Prodigies by Fred Barton, we have the comment below, which may explain some of Dagbert's abilities. It is a description of something like a photographic memory for numbers:

On page 60 of the same book we read about these "instantaneous" mental calculation feats of Dagbert:

On page 63 of the same book we are told that Dagbert would do performances in which he faced away from a blackboard, and audience members would call out 2-digit numbers that were placed in a grid like the one below. Without  ever viewing the blackboard, Dagbert would correctly name all numbers and their positions in the grid, as well as telling the sum of each of the columns. 

On page 306 of The Great Mental Calculators we read of the astonishing calculation ability of Shakuntala Devi:

In the 1952 newspaper story here, we read of rave reviews of Devi's calculation abilities. A reporter attempts to stump her:

"Your reporter, at this point, slyly glanced at a piece of paper he had laboriously prepared, and asked: 'What is the cube root of 3,375 multiplied by the cube root of 117,649 divided by 5?'

'147,' said Shakuntala, stifling a yawn, and adding, almost apologetically: 'I am usually given problems that present difficulties of one sort or another.' ”

 The answer of 147 is correct. You can get the intermediate numbers in this calculation by using the cube root calculator here, but no such tools existed in 1952. 

On page 311 of The Great Mental Calculators, we learn of the astonishing short-term memory of Hans Eberstark, who could memorize 40 digits after hearing them spoken only once:

Raccoons Are Rather Smart With Less Than 3% As Many Neurons as Humans

 A recent article in the Independent is entitled "I studied the brains of raccoons. Here’s what it tells us about human intelligence." We have an article written by a neuroscientist (Kelly Lambert) who correctly describes how smart raccoons are; but her article may lead to wrong ideas about the brains of raccoons. 

Speaking of raccoons, the neuroscientist states, "the species – Procyon lotor – is known for its impressive intelligence, curiosity and problem-solving skills." We have part of the article suggesting that raccoons were so clever that they were not used as research subjects, because the raccoons kept figuring out ways to escape through ventilation ducts in research laboratories.  We read this:

"And the role confusion continues today with glimpses of humanlike behaviors in raccoons as they enter our living spaces. One report described raccoons interacting with playground equipment at a child care center on Canada’s west coast in ways similar to human children, and even breaking into classrooms as if they were auditing the morning lesson....After introducing young raccoons to slinkies, puzzles and blocks, I sat in awe as they interacted with these objects with the focused enthusiasm of preschoolers on a mission....Early behavioral research suggested that raccoons can learn a task, walk away and later return to solve it accurately – as if having mentally rehearsed the solution. In contrast, other species, including dogs and rats, needed to maintain continuous focus. Scientists have speculated that raccoons have mental imagery capabilities similar to humans."

But none of this should be possible, according to "brains make minds" claims -- because raccoons have fewer than 3% of the cerebral cortex neurons that humans have. Humans are believed to have about 86 billion neurons, with about 20 billion of them in the cerebral cortex. But according to a paper co-authored by Lambert, "The raccoon cerebral cortex has an average 438 million neurons." 

Does Lambert tell us in her Independent article that raccoons have less than 3% of the cerebral cortex neurons of humans? She does not. Instead she gives us the following paragraph that seems designed to give us the wrong idea about raccoon brains: 

"Working with neuroscientist Suzana Herculano-Houzel, my laboratory at the University of Richmond has found that raccoons pack an astonishing number of neurons – an amount comparable to primates – into their brains. Scaled up to size, a raccoon brain would contain roughly the same number of neurons as a human brain."

The statement seems designed to give the casual reader the idea that raccoons have neurons numbers similar to humans. They do not. Raccoons have less than 3% of the cerebral cortex neurons of humans. And comparing total neurons in raccoons and humans, we find that the total number of neurons in raccoons (about 2 billion) is less than 3% of the total number of neurons in humans.  The page here gives the total numbers. 

Trying to explain why raccoons with so few neurons can be so smart, Lambert states this: 

"In collaboration with ecologist Sara Benson-Abram’s research team, we also found that raccoons with more sophisticated cognitive abilities had more neural cells in the hippocampus, reinforcing the idea that their learning and memory capacities map onto similar brain systems as those in people. Taxi drivers in London, who frequently use their knowledge of the 25,000 streets in London, also have a larger hippocampal area."

We have no paper reference for these claims, which are not well-founded. The first claim by Lambert is probably referring to the paper here, co-authored by her, Sara Benson-Abram and others. Its study group sizes were way too small for the study to qualify as any decent evidence for the claim that "that raccoons with more sophisticated cognitive abilities had more neural cells in the hippocampus." The study group size corresponding to "raccoons with more sophisticated cognitive abilities" was a study group of only 7 animals. No claim about a greater number of hippocampal neurons should be taken seriously unless that study group was 2 or 3 times larger, consisting of at least 15 or 20 animals. 

There is also no robust evidence that "taxi drivers in London, who frequently use their knowledge of the 25,000 streets in London, also have a larger hippocampal area." Such claims are based on the study  “Navigation-related structural change in the hippocampi of taxi drivers” which found no notable difference outside of the hippocampus, a tiny region of the brain. Even in that area, the study says “the analysis revealed no difference in the overall volume of the hippocampi between taxi drivers and controls.” The study's unremarkable results are shown in the graph below. 

The anterior part of the left half of the hippocampus was about 25% smaller for taxi drivers (100 versus 80), but the posterior part of the right half of the hippocampus was slightly larger (about 77 versus 67). Overall, the hippocampus of the taxi drivers was about the same as for the controls who were not taxi drivers, as we can see from the graph above, in which the dark bars have about the same area as the lighter bars. 

By claiming that "taxi drivers in London, who frequently use their knowledge of the 25,000 streets in London, also have a larger hippocampal area," Lambert is repeating one of the groundless "old wives' tales" of neuroscience, which is something that neuroscientists frequently do. 

Raccoons are not the only species that acts in a very smart way, despite having less than 3% of the neurons of humans.  Ravens show a wealth of high-level cognitive abilities, even though they have only about as many neurons as raccoons -- about 2 billion, which is less than 3% of the number of neurons that humans have. 

Postscript: Speaking of organisms that do mighty mental feats with tiny brains, below is a quote from a scientific paper:

"Who knew that bees with their tiny brains could memorize flowers and also human faces, solve problems of arithmetic, and learn to use tools. Until the last few years it was thought that social insects were governed only by instinct. It was all nothing more than innate behaviors. But recent research tells us something very different. As Princeton Professor Lars Chittka explains, 'Much of the workings of the bee’s mind can be understood only when one considers the natural challenges of the constantly changing market economy in which it must operate. The pressures of operating in this setting are often expressed in terms of physical performance. For example, a bee can carry its own body weight in nectar and or pollen; it may need to visit 1,000 flowers and fly 10 kilometers to fill its honey stomach only once; and 100 such trips may be required to generate a teaspoon of honey. Less appreciated are the mental efforts required along the way: in visiting 1,000 flowers, the bee has to work 1,000 floral ‘puzzle boxes’ whose mechanics can be as complicated as operating a lock and no two flowers species are quite alike in the mechanics that have to learned to gain access.'  Similarly, Monarch butterflies with brains the size of the head of a straight pin somehow in their annual 2,500 mile migration from the U.S. and Canada to the forests of central Mexico where they hibernate, fly day by day from the same tree their parents flew to the next tree their parents stopped for the night. And if that tree falls or is cut down, the next generation will pick a new tree and their progeny will stop there as well. How can they possibly even know which direction to fly, let alone identify one tree from another as they travel?"

Papers Find Massive Image Chicanery or Dubious Doings in Neuroscience Studies

None of the "brains make minds" claims of neuroscientists depend on imagery, there being no photos that do anything to substantiate either the claim that brains make minds or that brains store memories, So someone might claim that the degree of fake or mislabeled images in neuroscience has no relevance to whether brains make minds.  But there is a possible relevance: if there are honesty problems or accuracy problems with many of the images used in neuroscience research, that is another reason for distrusting cognitive neuroscientists; and the less trustworthy cognitive neuroscientists are, the more we should doubt their dogmatic claims. 

A recent article at the Retraction Watch site (https://retractionwatch.com/) has the title "Widespread image reuse, manipulation uncovered in animal studies of brain injury." The "image reuse" being referred to is when some scientific paper has an image that it claims is data from new original research done by its authors, even though the image seems to be the same image published much earlier in some other scientific paper.  

We read this:

"More than 200 papers on ways to prevent brain injury after a stroke contain problematic images, according to an analysis published today in PLOS Biology...René Aquarius and Kim Wever, of the Radboud University Medical Center in the Netherlands, first noticed these patterns in 2023 when they started working on a systematic review of animal studies in the field...Of the 608 studies they analyzed, more than 240, or 40 percent, contained problematic images...At first, the pair tried to check the images manually, but the work was too slow. So they turned to ImageTwin, which cross-checks uploaded images against a database, making the process 'more efficient and accurate,'  Wever said.  The results showed a sprawling network of images that not only appeared in articles on early brain injury, but also showed up labeled under different experiment conditions across studies on Alzheimer’s disease, epilepsy and lung cancer, and other unrelated fields....In total, their analysis found 37 of these papers in research fields other than early brain injury. Overall, 133 of the 608 articles contained an image that also appeared in another publication, a pattern typical of paper mills or image reuse among an author group, Aquarius said...In their new publication, the researchers took a conservative approach to identifying image reuse, so Aquarius called the 40 percent estimate a 'best-case scenario.' "

The Retraction Watch article is based on the scientific paper here, entitled "High prevalence of articles with image-related problems in animal studies of subarachnoid hemorrhage and low rates of correction by publishers." That paper states this:

"Estimates of the prevalence of inappropriate image duplication in (biomedical) research remains uncertain and are dependent of the body of literature that is being investigated. Reports are sparse and cover widely different literature samples. Out of >20,000 articles from 40 scientific journals, 4% contained problematic figures [18], while Danish researchers detected inappropriate image duplication in 19% of preclinical depression publications [19]. Image-related issues were identified in 6.1% of the assessed articles published in Molecular and Cellular Biology [20] and in 16% of articles published in Toxicology Reports [21]. Finally, in a sample of articles published in the journal Bioengineered, >25% contained inappropriate image duplication [22]. A synthesis of the sparse data estimates the combined misconduct rate (including fabrication, falsification, and plagiarism) to be 14%, 1 in 7 research articles [23]. The 40% prevalence observed in our study far exceeds these figures, suggesting an alarming level of integrity issues in the preclinical subarachnoid hemorrhage literature."

Sometimes you have imagery malfeasance that is so common in some particular field that some researcher can use an "everybody does it" kind of defense. An example is what goes on in brain scan visuals that purport to show areas of "superior activation" in the brain. There massively occurs misleading visuals that give the impression that the amount of variation is much greater than it is. Typically the variation will be some very small amount such as 1 part in 200. But you will see visuals that try to make such differences look much greater than 1 part in 200. 

Page 68 of a scientific paper ("More Than Meets the fMRI: The Unethical Apotheosis of Neuroimages" by Eran Shifferman) has a quote talking about the kind of shady business that goes on when these visuals are produced:

"The time series of voxel changes may be motion-corrected, coregistered, transformed to match a prototypical brain, resampled, detrended, normalized, smoothed, trimmed (temporally or spatially), or any subset of these, with only a few constraints on the order in which these are done. Furthermore, each of these steps can be done in a number of ways, each with many free parameters that experimenters set, often arbitrarily. After preprocessing, the main analysis begins. . In a standard analysis sequence, experimenters define temporal regressors based on one or more aspects of the experiment sequence, choose a hemodynamic response function, and compute the regression parameters that connect the BOLD signal to these regressors in each voxel. This is a whole-brain analysis, and it is usually subjected to one of a number of methods to correct for multiple comparisons… the wholebrain analysis is often the first step in defining a region of interest in which the analyses may include exploration of time courses, voxelwise correlations, classification using support vector machines or other machine learning methods, across-subject correlations, and so on. Any one of these analyses requires making crucial decisions that determine the soundness of the conclusions."

After the quote, the paper author says, "This detailed description shows that BOLD-fMRI NIs [neuroimages] represent mathematical constructs rather than physiological reality (Burock 2009)." Page 70 of the same paper states this:

"A ubiquitous statistical error in functional neuroimaging is the non-independence error (aka double dipping): using the same data for selecting the voxels of interest and then using these voxels for the secondary analysis, the one upon which the functional conclusions are based9 . Double dipping violates random sampling because the test statistics are not inherently independent of the selection criteria of the region of interest, thus statistically guaranteeing the outcome of the second analysis and rendering them useless (Kriegeskorte et al. 2009; Vul et al. 2009). Similarly, as mentioned before, statistical tests in neighboring voxels are not independent of one another, because time series in neighboring voxels are intercorrelated (Peterson 2003). Analyses have shown that the non-independence error is widespread in BOLD-fMRI studies (40-50% of published papers) and that the severity of the distortions of the results presented in these papers could not be assessed. This necessitates replications and reanalysis (Kriegeskorte et al. 2009) or the results of these studies “mean almost nothing”, since they are 'using seriously defective research methods and producing a profusion of numbers that should not be believed' (Vul et al. 2009)."

On page 71 we have this complaint about the use of way-too-small study group sizes in brain scan studies:

"Yet another sizeable statistical concern is unfitting sample sizes: most published fMRI studies have sample sizes that would be considered exceedingly small by conventional standards (Yarkoni 2009; Button et al. 2013; Ingre 2013), if they include sample size calculations at all (Guo et al. 2014). It is established that in fMRI studies, small studies (n=16) fail to reliably distinguish small and medium-large effect sizes from random noise as do larger studies (n=100) (Ingre 2013). However, Wager et al. (Wager et al. 2009) report that across 415 fMRI studies reviewed, the average group size was smaller than 12, with some using only 4 subjects."

Page 73 refers to a "localization project," by which the author means attempts to show that particular brain regions activate more strongly when some type of cognitive activity is performed.  We read, "The cumulative effect of these types of data variability is a serious impediment on the localization project, suggesting that there are no macroscopic-level delineations corresponding to cognitive performance, and that they are probably a methodological artifact (Gonzalez-Castillo et al. 2012; Thyreau et al. 2012)."

The author of the scientific paper is apparently suggesting that you cannot actually find any evidence that particular regions of the brain are more active during particular cognitive activities. On page 76 the author refers to those running brain scan studies, saying, "This practice all too often amounts to unethical science, one where the generators of data overlook known shortcomings of their tools of the trade and press forward with producing claims too strong to be supported by exploiting the strong appeal of their meticulously crafted images."

Misleading Claims and a Revealing Omission in NatGeo's List of "Biggest Scientific Breakthroughs of the Past 25 Years"

 The National Geographic Society was founded in 1888, and since that year it has published a magazine. For very many years the Society was guilty of promoting racism. In 2018 the Society itself had an issue confessing how racist its past publications were. A 2018 NPR article stated this:

"Editor in Chief Susan Goldberg asked John Edwin Mason, a professor of African history and the history of photography at the University of Virginia, to dive into the magazine's nearly 130-year archive and report back. What Mason found was a long tradition of racism in the magazine's coverage: in its text, its choice of subjects, and in its famed photography.

'[U]ntil the 1970s National Geographic all but ignored people of color who lived in the United States, rarely acknowledging them beyond laborers or domestic workers,' writes Goldberg in the issue's editor letter, where she discusses Mason's findings. 'Meanwhile it pictured 'natives' elsewhere as exotics, famously and frequently unclothed, happy hunters, noble savages—every type of cliché.' "

An example of the racism that National Geographic Magazine promoted is mentioned here: a photo caption in which a particular type of dark-skinned person is described as being lowest in intelligence. For more than 70 years National Geographic Magazine helped encourage misguided ideas that dark-skinned people are inferior or savages. 

National Geographic may have reformed its racism by 2018. But at the magazine there is still another form of stupidity : the stupidity of blind materialism.  For decades National Geographic (in its website and magazine) has promoted false or dubious claims about human minds, human bodies, human experiences and human origins. 

For years, National Geographic magazine (and its web site and TV channel) have acted as an uncritical echo chamber for prevailing materialist dogma.  This post sites some inaccurate statements on a National Geographic show about the origin of life.  See this post for a look at a National Geographic show that gave an absurdly biased treatment of a type of paranormal experience.  The Cosmos TV series on the National Geographic channel was an often erring mouthpiece for misguided materialist ideas. The National Geographic show "Brain Games" constantly committed the big error of describing any mental human experience as something that is going on in the brain or produced by the brain.  We never hear on National Geographic about the many powerful reasons for doubting claims that human consciousness and thinking are produced by the brain, and for doubting that human memories are stored in the brain.   

A recent National Geographic article is entitled "The Biggest Scientific Breakthroughs of the Last 25 Years -- And a Few to Watch." There are some serious misstatements in the article, and some of the times it boasts about supposed accomplishments that were never actually accomplished. 

The article starts out with a whopper right in in the first listed "breakthrough." The article lists as it first listed breakthrough "The Completion of the Human Genome, and the Advent of Synthetic Life." No actual "synthetic life" has ever been created by scientists. As an example of "synthetic life," the article claims "scientists developed the first synthetic cell in 2010." But we have a link that merely refers us to a paper describing a study that did not actually create any life from scratch. The study merely involved removing genes from a living cell. That is not creating "synthetic life," but merely tinkering with a pre-existing living thing. The paper is entitled "Design and synthesis of a minimal bacterial genome," and can be read here. The paper was promoted with a misleadingly-titled press release entitled "First Minimal Synthetic Bacterial Cell," one prone to create the utterly false impression that a reproducing cell had been produced from scratch. 

What is particularly ironic here is that the false claim that "scientists  developed the first synthetic cell in 2010" tends to create the impression that cells are relatively easy to create from scratch. But the research being referred to told us the exact opposite. After making a long attempt to modify a cell so that it had the smallest possible number of genes and the smallest possible number of types of protein molecules, while still being capable of self-reproduction, the scientists, were still left with a microbe with 475 genes, corresponding to 475 types of proteins. The resulting stripped-down genome still consisted of 530,000 base pairs. The misleadingly-titled press release entitled "First Minimal Synthetic Bacterial Cell" failed to mention this crucial point from the paper. 

Another false claim in the National Geographic article was the claim that the AlphaFold software had solved the protein folding problem. The problem has not at all been solved, and is still one of the biggest unsolved problems in science. 

Protein molecules are three-dimensional structures built from many different amino acid components, usually hundreds or thousands. A fundamental question is: how do protein molecules get their three- dimensional shapes?  This problem is known as the protein folding problem. We might have an answer for this if it happened that each amino acid stored in it three numbers specifying the 3D position that it should go to. We can imagine a setup in which an amino acid would store three different numbers: one representing the X-axis coordinate that the amino acid should exist at, another representing the Y-axis coordinate the amino acid should go to, and a third representing the Z-axis coordinate the amino acid should go to. We can imagine some complicated molecular machinery that would read such numbers, and drag each amino acids to the appropriate X, Y and Z coordinates (a particular point in 3D space) that the amino acid should go to. Under such a system, a 3D protein molecule like the one below might be constructed from a one-dimensional string-like chain of amino acids. 

But that is not at all the way nature works. An amino acid does not store any numbers. An amino acid stores neither 3D coordinate numbers, nor any other type of number. So how do the more than 20,000 types of protein molecules in our bodies get their intricate 3D shapes? That problem is what is called the protein folding problem. 

The AlphaFold software is able to predict the shape of many proteins not by any thermodynamic calculation process  but instead by a frequentist "pattern matching" approach that relies on some vast database of known 3D protein shapes and their corresponding amino acid sequences. In discussions of the protein folding problem, it is very important to not mix up two very different problems:

(1) The protein folding problem, which is the problem of how it is that one-dimensional polypeptide sequences (chains of amino acids) very quickly within organisms fold into a three-dimensional shape needed for the function.

(2) The protein folding prediction problem, which is the problem of what computer techniques can be used to accurately predict the three-dimensional shape of a protein molecule, giving its one-dimensional polypeptide sequence. 

The AlphaFold software has made progress on the second of these problems, not the first.  News reports about the AlphaFold software will often inaccurately describe it as having made progress on the "protein folding problem" (the first of these problems). But such reports should be only reporting that progress has been made on the second of these problems (the protein folding prediction problem). 

Later in the National Geographic article we have the claim that "The Deep Ocean Reveals How Life Might Have Started." The paragraph that follows this claim does nothing to substantiate it, merely talking about other things. We hear nothing substantiating the idea that any breakthrough occurred here. 

The truth is that scientists have made no progress in understanding how life could have originated. No experiment realistically simulating the early Earth has ever produced life. No experiment realistically simulating the early Earth has ever produced any of the protein molecules that are the main building components of the simplest one-celled life. No  experiment realistically simulating the early Earth has ever even produced any of the amino acids that are the building components of the building components of life. 

Later in the National Geographic article we got the claim that there were "possible biosignatures discovered on Mars, Venus and exoplanets." This is listed as one of the greatest scientific breakthroughs of the past 25 years. But there is no robust evidence behind any of the claims. The claim that a biosignature was discovered on Mars is debunked in my post here. The claim that a biosignature was discovered on Venus is debunked in my post here.  The claim that a biosignature was discovered on planet K2-I8 b is debunked in my post here. The article refers to "exoplanets" (planets in other solar systems), but only mentions only one exoplanet, referring to K2-18b. 

There is a revealing omission in the National Geographic article. None of the claimed breakthroughs did anything to substantiate claims that brains make minds or that brains store memories.   It seems that cognitive neuroscientists are getting nowhere in their attempts to prove that brains make minds and that brains store memories. What they are most noticeably producing are low-quality or not-important science studies that serve to increase their "published paper counts," but do nothing to clarify how a mind can arise.