A New Case of Very Large Brain Damage and Normal Mental Function

In this blog I have discussed many cases of normal or near-normal mental function despite massive brain damage. For example, in the post here and the posts here and here you can read about people who had normal function after removal of half of their brain in hemispherectomy operations. At those links you can also read about people who had normal mental function despite losing far more than half of their brain because of disease.  The scientific paper here describes a patient (P.G.) who scored 142 on an IQ test, even though the right hemisphere of the brain had been removed (as well as a patient D.W. who scored 100 on an IQ test after the left hemisphere of the brain had been removed). 

There has just been reported a new case of someone with normal or almost normal mental function despite having massive brain damage. I found the case on the science subreddit of reddit.com (https://www.reddit.com/r/science). The original link goes to a science journal letter to the editor behind a paywall, a letter entitled "A case of extreme hydrocephalus in a 67-year-old man whose professional and social lives were normal." But one of the reddit users has quoted the letter to the editor, so we can see the details of the case by using the link here and pressing the blue "View Entire Discussion" button to see all comments. At that link we read this quotation from the letter to the editor:

"A male patient first consulted when he was 67 for gait disorders related to Parkinson's disease. The cerebral MRI performed on this occasion showed a very large tetra-ventricular hydrocephalus...His education was completed without remarkable difficulty, he obtained a Vocational Training Certificate and worked in an insurance company. He retired after 40 years and 3 months of work. He has always been very active during his professional life without ceasing work for any disease. According to his brothers, he was very curious, interested in history and had an excellent memory. During his first medical visit, the clinical examination showed both pyramidal and extra-pyramidal syndromes. Occipito-frontal circumference (OFC) was 64 cm (+5 SD). Mini-mental state examination (MMSE) was 27/30 (recall was perturbed), Frontal Assessment battery (FAB) was 17/18 (verbal fluidity was slightly impaired). Cerebral MRI showed a massive communicating hydrocephalus (figure 1A) predominating on the frontal lobes (figure 1B). On FLAIR sequences, hypersignals were noted in the periventricular regions. Furthermore, ruptured septa or pseudo-septa were present on both sides predominating on the left ventricle (figure 1 C and D). In the frontal region, the hemispherical wall was very thin (from 3.4 to 3.8 mm) with an overlying cortex totally unfolded (Figure 1 B and D). The corpus callosum was very thin, stretched by ventricular dilation (Figure 1A). ...Both the clinical history as told by his family and macrocephaly suggest that this hydrocephalus developed very early during the life of this patient....Despite this major hydrocephalus, patient’s professional life was normal. There was only a delay of motor acquisitions and language; this delay vanished during his adolescence."

The disease suffered by this man is hydrocephalus, in which there can arise very large fluid-filled cavities in the brain. If you go to the page here showing the letter to the editor (behind a paywall) you can see four thumbnail images showing this man's brain.  We can see gigantic fluid-filled cavities in the man's brain, which appear as dark holes in the images. An image from one angle seems to show about 75% or more of the brain tissue missing (although a view from another angle makes it look more like about 50% of the brain tissue missing). 

We read that the very brain-damaged subject (age 67) had a score of 27 out of 30 on the Mini-Mental State Examination (MMSE), which is a good score that you or me might get (you have to score 24 or lower for a doctor to regard the score as evidence of dementia).  According to the link here, the average MMSE score for people between 65 and 74 is 22.4. The very brain-damaged subject had a score of 17 out of 18 on the Frontal Assessment Battery test (FAB), which is higher than average for persons of his age (according to the link here, the average score for people in their sixties is 16). 

In a similar vein, the paper here describes tests on a person born without a left temporal lobe of the brain. We are told "she performed within normal range on all language assessment tasks" and that she "performed within normal range on both general cognitive assessments."

Once again, we have evidence that people can have normal minds despite the most massive brain damage. Clinging stubbornly to their unwarranted dogma that the brain is the source of the mind, our neuroscientists continue to avoid putting "two and two together" by realizing the implications of such findings of very high brain damage and normal mental function, just as they avoid putting "two and two together" by failing to realize the implications of very common out-of-body experiences in which people report viewing their bodies while floating outside of their bodies. The data from "very heavy brain damage" medical case histories and the data from parapsychology case histories tell us the same thing: that your brain is not the source of your mind. 

Study Group Sizes, Neuroscience and COVID-19

On this blog I have frequently complained about the way-too-small study group sizes used so often in neuroscience studies.  This is one of the biggest reasons for doubting the reliability of very many neuroscience studies. Two other equally great problems are the failure to pre-register a single detailed hypothesis and the methods that will be used to analyze and collect data before starting an experiment (the "fishing expedition" problem), and the failure of so many neuroscience experimental studies to declare and follow a detailed blinding protocol to mimimize experimenter bias.  The "bare minimum" for a halfway-trustworthy experimental study is 15 subjects per study group, but neuroscience experiments often use  fewer than 15 subjects for particular study groups. 

A completely different situation now exists in regard to COVID-19 vaccines. The study group size nowadays for a particular vaccine is the total number of people who have taken that vaccine. By now the study group size for each of the approved COVID-19 vaccines is millions of times greater than the way-too-small study group sizes so often used in neuroscience studies.  It would seem, therefore, that based on study group sizes you should have high confidence in the reliability of COVID-19 vaccines that have already been used by many millions of people. 

I myself have got two doses of a COVID-19 vaccine, as have my wife and daughters.  I recommend that others do the same. It seemed reasonable to take a "wait and see" attitude when relatively few people had been vaccinated, but as more and more millions of people get vaccinated without a problem, it seems the case for getting a vaccine (at least from a study group size standpoint) is getting stronger and stronger. 

Imaging of Dendritic Spines Hint That Brains Are Too Unstable to Store Memories for Decades

Scientists have very fancy equipment for examining brains at very high resolution. But no microscopic examination of a brain has ever proven or even supported the claim that brains store memories.  The most common claim about a brain storage of memories is that memories are stored in synapses. But the paper here confesses, "Very few studies report long-lasting structural changes of synapses induced by behavioral training."

There are two types of ways to examine brain tissue: in vivo or in vitro. An in vitro examination means looking at some tissue that has been removed from an organism, or some tissue in a dead organism. An in vivo examination means examining tissue in a living organism.  When examining human tissue, there are rather severe constrains on what can be seen in vivo. But there are no constraints on in vitro examinations of newly deceased humans, whenever such humans have donated their bodies to medical science.  The brains of quite a few such humans have been minutely examined with the most sophisticated equipment. No one has ever found evidence of a memory stored in a brain. No one has ever read a memory from a dead person. 

There are a number of ways to do in vivo examinations of the brains of living organisms.  One technique is called time-lapse two-photon laser microcopy.  Such technology is not good enough to clearly inspect individual synapses, which are very small. But such microscopy is good enough to show what are called dendritic spines. 

A dendritic spine is a tiny protrusion from one of the dendrites of a neuron. The diagram below shows a neuron in the top half of the diagram. Some dendritic spines are shown in the bottom half of the visual. The bottom half of the visual is a closeup of the red-circled part in the top of the diagram. 

An individual neuron in the brain may have about a thousand such dendritic spines. The total number of dendritic spines in the brain has been estimated at 100 trillion, which is about a thousand times greater than the number of neurons in the brain.  The total number of synapses in the brain has also been estimated at 100 trillion. A large fraction of synapses are connected to dendritic spines. So by studying how long dendritic spines last, we can tell a good deal about how long synapses last. 

It has been hoped that some relation could be drawn between learning and the formation of new dendritic spines.  But scientists try to insinuate a connection between LTP and learning, and a paper says that "Sorra and Harris measuring three-dimensional reconstructed spines from serial section EM pictures, could not find any significant effect of LTP on morphological properties of spines."

No doubt the first scientists who examined dendritic spines were hoping to see some nice regularity and order, perhaps something that might be some kind of coding system by which dendritic spines might store information.  But dendritic spines show no such regularity. Unlike positions in a DNA molecule (which must be one of only four nucleotide base pair types), dendritic spines can be any of many sizes, shapes or lengths. A length of dendrite and its spines (like the length shown in the bottom half of the visual above) seem to bear no resemblance to encoded information.  The vast majority of new dendritic spines do not last longer than a few months.  

Some unconvincing science papers have attempted to suggest a link between learning and dendritic spines.  Here's what goes on in a typical paper of this type:

(1) Some rodent will be given some learning, such as fear conditioning. 

(2) Various dendritic spines will be examined.

(3) Some newly formed dendritic spines will be declared to be "experience dependent," because they appeared while the learning took place. 

It is easy to explain why such papers use an illegitimate methodology. There are very many billions of dendritic spines in the brain, and they come and go rapidly and randomly. So anyone with a good enough microscope could find some stretch of dendritic spines that increased during learning, just as you could find some stretch of dendritic spines that decreased during learning. There is never any good basis for claiming that some stretch of dendritic spines increased because of some particular type of learning.  Similarly, looking around outside I could find some row of leaves that grew bigger when I was studying something, but there would be zero reason for thinking that such an increase was caused by my learning. 

Some studies compare two different sets of subjects, one that was exposed to learning, and another that was not exposed to learning. The studies may report that the subjects exposed to learning had a greater growth of dendritic spines. This is not at all good evidence that dendritic spines have anything to do with learning. We would expect that if dozens of experiments compared sets of dendritic spines undergoing random fluctuations, that some of them would report (purely by chance) that in some of those sets there was a greater growth of dendritic spines. Similarly, if 100 experimenters tracked the pimples of young teenagers with acne both during the first three months of the school year and during summer vacation, some of the experimenters might report greater numbers of new pimples growing during the first three months of the school year, even though there is no causal connection between learning and the number of pimples a teenager may have on his or her skin. 

By examining the tiny protrusions that are dendritic spines, scientists can get some idea of how stable or unstable these dendritic spines are.  If such spines are very unstable, it is a great problem for any theory that memories are stored in synapses.  Unstable dendritic spines would suggest that synapses are unstable, and are unlikely to be a place where memories could be stored for decades.  Even without studying dendritic spines, we have the strongest reason for believing in the instability of synapses: the fact that proteins in synapses have average lifetimes of only a few weeks. 

Dendritic spines last no more than a few months in the hippocampus, and less than two years in the cortex. This study found that dendritic spines in the hippocampus last for only about 30 days. This study found that dendritic spines in the hippocampus have a turnover of about 40% each 4 days. This study found that dendritic spines in the cortex of mice brains have a half-life of only 120 days. The wikipedia article on dendritic spines says, "Spine number is very variable and spines come and go; in a matter of hours, 10-20% of spines can spontaneously appear or disappear on the pyramidal cells of the cerebral cortex." Referring to in vivo observations of dendritic spines in the mouse hippocampus, the paper here says the authors "measured a spine turnover of ~40% within 4 days."  The 2017 paper here ("Long-term in vivo imaging of experience-dependent synaptic plasticity in adult cortex") found the following regarding dendritic spines in the cortex of rodents:

"About 80% of synapses were detectable for a day or longer; about 60% belonged to the stable pool imaged for at least 8 days. Even this stable pool was found to turn over, with only, 50% of spines surviving for 30 days or longer. Assuming stochastic behaviour, we estimate that the mean lifetime of the stable pool would be on the order of 120 days."

We have no good evidence that any dendritic spines survive for more than  a few years. There is an often-cited paper from the year 2000 with the title "Stably maintained dendritic spines are associated with lifelong memories." The title is misleading, like the title of so many scientific papers.  The paper actually found that "a tiny fraction of daily formed new spines (~0.2% of the total spines) could persist for 3–5 months." So the paper found that only 1 in 500 dendritic spines persist for as long as 5 months.  The paper resorts to some dubious math to try to hypothesize that some dendritic spines may last for years. 

More recent papers have made even more clear the high turnover rate of dendritic spines, and have made it seem less likely that any dendritic spines survive for more than a few years.  The 2015 paper 

"Impermanence of dendritic spines in live adult CA1 hippocampus" states the following, describing a 100% turnover of dendritic spines within six weeks:

"Mathematical modeling revealed that the data best matched kinetic models with a single population of spines of mean lifetime ~1–2 weeks. This implies ~100% turnover in ~2–3 times this interval, a near full erasure of the synaptic connectivity pattern."

The paper here states, "It has been shown that in the hippocampus in vivo, within a month the rate of spine turnover approaches 100% (Attardo et al., 2015; Pfeiffer et al., 2018)." The 2020 paper here states, "Only a tiny fraction of new spines (0.04% of total spines) survive the first few weeks in synaptic circuits and are stably maintained later in life."  The author here is telling us that only 1 in 2500 dendritic spines survive more than a few weeks.  Given such an assertion, we should be very skeptical about the author's insinuation that some very tiny fraction of such spines "are stably maintained." No one has ever observed a dendritic spine lasting for years, and the observations that have been made of dendritic spines give us every reason to assume that dendritic spines do not ever last for more than a few years. 

The same studies that show such short lifetimes for dendritic spines show that while they exist, dendritic spines very rarely maintain the same size and shape.  During their short lifetimes, dendritic spines tend to change very much in size and shape.  One paper says that even among a more stable subset of dendritic spines, "The majority of those (~80%) underwent a fluctuation in head size and neck length of more than 10% (~40% even of more than 30%) within 3 to 4 days."

One 2005 paper ("Development of Long-Term Dendritic Spine Stability in Diverse Regions of Cerebral Cortex") claims to have imaged some mouse dendritic spines in a way so that you could compare how badly some spines decayed after an interval of 18 months. The claim is extremely doubtful, because the paper fails to give any description of how so hard a thing to do was accomplished.  Given the lack of a decent description of how this feat was supposedly accomplished, we should regard the claim with high suspicion. What probably occurred is that some piece of dendrite was examined, and later 18 months later the scientists went looking for some other dendrite with a fairly similar appearance. But we can have no confidence that the exact same little stretch of dendrite was found. Because little stretches of dendrites with a few dendritic spines look so similar, it would be very easy for someone to do a "closest appearance" search, and find a little stretch of dendrite that was not the same little stretch of dendrite examined 18 months earlier. We can have no confidence that the two pairs of dendrites shown in Figure 4 of the paper are actually the same little stretch of dendrite in the same organism. From the author's way-too-scanty description of what was going on, we don't even know whether the images are photos from living mice (as opposed to slides of extracted tissue that were photographed 18 months apart).  We also don't know whether the authors went looking for some fairly stable dendritic spines, in a cherry-picking affair, extracting the most stable-looking dendritic spines from some larger pool where very little stability existed.  

We should keep in mind that a typical neuroscientist studying the lifetimes of dendritic spines (a topic also called dendritic spine turnover or dendritic spine remodeling) is someone likely to be trying to show as much stability as he can find. This is because many  neuroscientists eagerly hope (very illogically) that dendritic spines might be something that can help explain the persistence of memory in humans. So when we see some visual showing some dendritic spines persisting over the course of four months, we are probably seeing something that is not common, something that was cherry-picked to show dendritic spines lasting for a relatively long time. Also, neuroscientists are probably overestimating by 50% or more whenever they estimate what fraction of dendritic spines are stable.

The 2022 paper "Stability and dynamics of dendritic spines in macaque

prefrontal cortex" studied  how long  dendritic spines last in a type of monkey. It says, "We found that newly formed spines were more susceptible to elimination, with only 40% persisting over a period of months."  The same study found that "the percentage of elimination for pre-existing spines over 7 days was only 6% on average," which is a rate that would cause complete disappearance of pre-existing dendritic spines within a year. Dealing with a type of monkey, the 2015 paper "In Vivo Two-Photon Imaging of Dendritic Spines in Marmoset Neocortex" tells us that "The loss or gain rate at the 1 d  [one day] interval observed in this study was similar to those in previous studies of layer 5 neurons of the somatosensory cortex of transgenic mice (12% in 3 d [3 days] for both loss and gain; Kim and Nabekura, 2011) and layer 2/3 neurons of ferret V1 by the virus vector method (4% in 1 d [1 day]  for both loss and gain; Yu et al., 2011)."  The reported loss of dendritic spines is a rate that would cause 100% loss within a year. 

Human memories can last a lifetime, but synapses and the dendritic spines they attach to are very unstable "shifting sands" types of things. "Unstable dendritic spines" implies "unstable synapses," which implies that scientists must be wrong when they claim that memories are stored in synapses.  Stable human memories can last for 50 years, so we cannot believe they are stored in things as unstable as synapses and dendritic spines. Studies on the lifetime of the proteins that make up synapses and dendritic spines tell us that such proteins last only a few weeks.  Synapses and dendritic spines are as unstable as fallen maple leaves.  The brain has no place that it could be storing memories that last for decades.

Postscript: The failure of neuroscientists to listen to what dendritic spines are telling us is epitomized by a 2015 review article on dendritic spines, which states, "It is also known that thick spines may persist for a months [sic], while thin spines are very transient, which indicate that perhaps thick spines are more responsible for development and maintenance of long-term memory."  It is as if the writers had forgotten the fact that humans can remember very well  memories that last for 50 years, a length of time a hundred times longer than "months." 

Electron microscope photos of dendritic spines show something that looks nothing like any organized structure capable of storing information. For example:

Dendritic spines seem to pop up out of dendrites as randomly as twigs pop up from the branches of trees. No one has been able to detect any kind of regularity in the appearance of dendritic spines that might be a  scheme for storing encoded information, just as no one has been able to find any such scheme in the twigs on trees. Just as there does not exist in nature any such thing as a twig reader that scans branches trying to extract encoded information from the twigs of branches, there does not exist anything in the brain that might be a dendritic spine reader. 

A 2019 paper documents a 16-day examination of synapses, finding "the dataset contained n = 320 stable synapses, n = 163 eliminated synapses and n = 134 formed synapses."  That's about a 33% disappearance rate over a course of 16 days. The same paper refers to another paper that "reported rates of [dendritic] spine eliminations in the order of 40% over an observation period of 4 days."  A paper studying the lifetimes of dendritic spines in the cortex states, "Under our experimental conditions, most spines that appear survive for at most a few days. Spines that appear and persist are rare." The rare persistence referred to was only a persistence of a few months. 

The 2023 paper here gives the graph below showing the decay rate of the volume of dendritic spines. It is obvious from the graph that they do not last for years, and mostly do not even last for six months. 

Page 278 of the same paper says, "Two-photon imaging in the Gan and Svoboda labs revealed that spines can be stable over extended periods of time in vivo but also display genesis (generation) and elimination (pruning) at a frequency of 1–4% per week." Something vanishing at a rate of 2% per week will be gone within a year. 

Post-postscript: The 2025 paper here states that  "the synaptic turnover rate is as high as 1% per day in the visual cortex." That is a rate of about 100% replacement every four months. If that is the typical rate at which synapses are replaced, synapses cannot be the storage place of memories lasting decades. Quoting an even higher rate of synaptic turnover, the paper here states, "A recent imaging study revealed that the synaptic turnover rate in hippocampal CA1 cells is very high, with an estimated lifetime of 1–2 weeks (Attardo et al., 2015)." 

Experimental Evidence for ESP Is Well-Replicated

While examing the Science subreddit on www.reddit.com (www.reddit.com/r/science) the other day, I noticed there is a new meta-analysis about ESP experiments.  The meta-analysis is an interesting case example of presenting evidence for paranormal phenomena in pretty much the most hard-to-unravel way possible. If he works very hard, and uses some geeky little computer tricks, it is possible for a reader to get to the core data that is compelling evidence for extrasensory perception. But it is almost as if the authors were trying to minimize the chance of readers discovering such core data.  In this post I will discuss that core data in a way that saves you from doing all that hard work. 

The meta-analysis ("Anomalous perception in a Ganzfeld condition - A meta-analysis of more than 40 years investigation" by P. Tressoldi and Lance Storm) discusses ESP experiments using what is called the Ganzfeld protocol.  A ganzfeld experiment is one in which a test for extra-sensory perception is combined with sensory deprivation achieved through methods such as cutting a ping-pong ball in half and taping it over someone's eyes, and having someone wear an earphone transmitting white noise. In these ESP experiments, the expected chance hit rate (matching of a user's selection and a random target) is 25%. Ganzfeld experiments have a long history of scoring a "hit rate" well over the expected chance result of 25%. 

What we want to know upon reading the new meta-analysis is: how high a "hit rate" did the experiments score? Unfortunately, the authors have made it ridiculously hard to discover this key number. The meta-analysis authors mention "hit rates" far about 25% reported by other meta-analysis papers. But nowhere in their paper do they report the "hit rate" found by their meta-analysis. 

Instead, the authors report what statisticians call an "effect size." The concept of an effect size will not be clear to non-scientists or non-mathematicians.  But everyone can understand that if a long series of ESP experiments reports an average "hit rate" far above the expected-by-chance "hit rate" of 25%, then you have powerful experimental evidence for ESP. 

There is a way to get the "hit rate" reported by this meta-analysis, but it requires some geeky tricks that few readers would naturally achieve. If you click the link here provided by the paper, you will find a page with a series of links on the left side. If you click the third link in this series, you will see a table with some experimental results. But you will not see the full set of experimental results used in the meta-analysis.  You will see only 50 rows. There is then a link that says, "This dataset contains more than 50 rows. To see the remaining content please download the original file."  There is a link that allows you to download a spreadsheet file (GZMADatabase1974_2020.xlsx). Part of it is shown below.

What if you don't have a spreadsheet program on your computer? Then you're out of luck, and can't discover the key number of the "hit rate."

There is no excuse for presenting such road blocks to the reader. Web sites since the early 1990's have been perfectly capable of displaying the simple tabular data that is in this spreadsheet, by using the HTML protocol used since the early 1990's, a protocol fully capable of displaying tabular data. There is no reason why such tabular data could not have been fully displayed in the meta-analysis paper, so users would not have to fool around with external links and downloads.  And there's no reason why the paper could not have included a single sentence summarizing the number of trials, number of successful hits, and hit rate. 

But what happens if you are lucky enough to have a spreadsheet program on your computer, and you can download the spreadsheet, and view the experimental data? Then you still won't get the key number of the average "hit rate" reported by the meta-analysis.  For the spreadsheet table doesn't include a line summarizing the results in the table. 

But by using some hard-core geeky tricks, we can remedy this situation. You have to do this (something that would not occur to 1 reader in 100):

• In cell G115 of the spreadsheet, type this: =SUM(G2:G114)
• In cell H115 of the spreadsheet, type this: =SUM(H2:H114)
• In cell K115 of the spreadsheet, type this: =AVERAGE(K2:K114)

Now finally, we get the "bottom line" numbers, shown in the last line of the screen shot below. From 1974 to 2020 there were 113 ESP experiments using the Ganzfeld protocol, which involved a total of 4841 trials and 1520 successful "hits," which was an average success rate of 31.5%, much higher than the rate expected by chance, which is only 25%. 

Why haven't our meta-analysis authors communicated to us this very clear "bottom line" result, which anyone can understand is a result that is extraordinarily unlikely to have occurred by chance? Why have they only informed us of their results using only an "effect size" that few layman understand? It is as if the authors were doing everything they could to obscure the evidence for ESP they have found.  Indeed, the authors have failed to even use any of the terms commonly used for describing ESP experiments. They have not used the words commonly used in the literature, words such as "psi," "ESP," "extrasensory perception," "telepathy," "clairvoyance" or "mind reading." Instead they have merely used the vague term "anomalous perception," as if they were trying to minimize the number of times their meta-analysis would be found by people doing a Google search for information about ESP. 

Although some of the people gathering such evidence are clumsy about clearly communicating their impressive results, the experimental evidence for extrasensory perception is very strong and very well-replicated.  Using the Ganzfeld technique, ESP researchers have achieved a high-level of experimental replication. But the Ganzfeld results are by no means the best evidence for ESP.  The best evidence consists of (1) earlier tests reported by people such as Rhine and Riess, in which some subjects reported results we would never expect any subject to get by chance even if every person in the world was tested for ESP every week (see here, here and here for examples);  (2) two-hundred years of observational reports of clairvoyance, in which some subjects were vastly more successful than any person ever should have been by chance or coincidence (see here, here, here, here, here, here, here and here for examples). 

No one has any neural explanation for how a brain could produce psi effects such as ESP. Evidence for ESP is fatal to the claim that the human mind is merely a product of the brain.  This is why people who maintain that claim have again and again so stubbornly refused to admit the existence of ESP. They almost always take a "head in the sand" approach, simply refusing to examine the evidence on this topic.  Such mindless non-scholarship is a very strong "red flag" suggesting their beliefs about the brain and mind are fundamentally wrong.  Two of the biggest "red flags" you can have suggesting that someone's beliefs are dogma rather than scientifically warranted are (1) a refusal to seriously study a very large body of important observational reports relevant to such beliefs; (2) a frequent tendency to occasionally make untrue statements about factual matters related to your belief claims.  Very many professors following the "brains make minds" dogma frequently display both of these "red flags."  

Postscript: The 1961 book Challenge of Psychical Research by Gardner Murphy discusses some of the experimental evidence for ESP.  Beginning on page 57, the author discusses a series of experiments he did with a student named Van Dam. The student was blindfolded, and put in a sealed cubicle in one room. In another room, someone chose by lot one of the squares in the grid below.

The blindfolded Van Dam was asked in the other room to guess the square chosen. There were 187 trials done on 7 different days. The expected result by chance was only 4 successes. The actual number of successes was 60, a success rate of nearly 30%.  You would not expect a result half as good to ever occur by chance if every person in the world were to be tested. 

The pages preceding page 75 discuss the Pearce-Pratt ESP experiment involving two people in different buildings. We read on page 75 there were 558 successes in 1850 trials, for a success rate of 30%, in a situation where the expected chance result was only 20% or 370 successes. The probability of getting such a result by chance was calculated at less than 1 in 10 to the twenty-second power, less that 1 in ten billion trillion. 

Most Scientists Don't Follow Formal Evidence Standards, Unlike Judges

The www.realclearscience.com site is a typical "science news" site: a strange mixture of hard fact, speculations, often-dubious opinions, spin, clickbait, hype and corporate propaganda, all under the banner of "science."  I noticed an enormous contrast between one of the site's articles appearing yesterday, and another article appearing today.

The link that appeared yesterday was a link to a very give-you-the-wrong-idea article by scientist Adam Frank, one with the swaggering title, "The most important boring idea in the universe."  This idea that Frank says is so important is the claim that "scientific knowledge" rests upon "mutually agreed standards of evidence." 

Frank attempts to persuade us that after arguing for a long time, scientists agreed on "standards of evidence" that they are now faithfully following. He writes the following:

"There were lots of wrong turns in figuring out what counted as meaningful evidence and what was just another way of getting fooled. But over time, people figured out that there were standards for how to set up an experiment, how to collect data from it, and how to interpret that data. These standards now include things like isolating the experimental apparatus from spurious environmental effects, understanding how data collection devices respond to inputs, and accounting for systematic errors in analyzing the data. There are, of course, many more."

The idea that Frank tries to plant is a false one. Scientists never agreed upon some "standard of evidence" that would be used in judging how experiments or observations should be done or whether scientific papers should be published or publicized.  There is no formal written "standard of evidence" used by scientists. Conversely, courts do actually make use of formal written standards of evidence. 

When you go to www.rulesofevidence.org, you will find the Federal Rules of Evidence used in US federal courts.  The page here lists about 68 numbered rules of evidence used in this evidence standard. Here are some examples:

• Rule 404: "Evidence of a person’s character or character trait is not admissible to prove that on a particular occasion the person acted in accordance with the character or trait."  (There are quite a few exceptions listed.) 
• Rule 608: " A witness’s credibility may be attacked or supported by testimony about the witness’s reputation for having a character for truthfulness or untruthfulness, or by testimony in the form of an opinion about that character. But evidence of truthful character is admissible only after the witness’s character for truthfulness has been attacked."
• Rule 610: "Evidence of a witness’s religious beliefs or opinions is not admissible to attack or support the witness’s credibility." 

There are more than 60 other rules in the Federal Rules of Evidence. US Federal Courts have a formal written set of evidence standards. But scientists have no such thing.  The impression that Frank has attempted to insinuate (that scientists operate under formal standards of evidence that they carefully worked out after long debate) is not correct.

There are no formal detailed written evidence standards in any of the main branches of science.  In biology, poorly designed experiments following bad practices are extremely common.  In theoretical biology and physics, it is extremely common for scientists to publish papers based on the flimsiest or wildest of speculations. When we read scientific papers such as those speculating about a multiverse consisting of many unobserved universes, we are obviously reading papers written by authors following no standards of evidence at all. It's pretty much the same for any of the thousands of papers that have been written about never-actually-observed things such as abiogenesis, dark matter, dark energy or primordial cosmic inflation.

In fields such as paleontology, elaborate speculation papers can be based on the flimsiest piece of ancient matter or the tiniest bone fragment; and many papers in that field are not based on specific fossils.  Then there are endless chemistry papers not based on actual physical experiments but on "chemical reactions" merely occuring on paper, a blackboard, or inside a computer program. Countless papers in many fields are based on mere computer simulations or abstruse speculative math rather than physical experiments or observations. 

On the next day after the www.realclearscience.com site published a link to Frank's article, it published a link to an article that very much contradicted his insinuations that scientists are adhering to sound standards of evidence. The link was to an article on www.reason.com entitled "How Much Scientific Research Is Actually Fraudulent?"

Here are some quotes from the article:

"Fraud may be rampant in biomedical research. My 2016 article 'Broken Science' pointed to a variety of factors as explanations for why the results of a huge proportion of scientific studies were apparently generating false-positive results that could not be replicated by other researchers. A false positive in scientific research occurs when there is statistically significant evidence for something that isn't real (e.g., a drug cures an illness when it actually does not). The factors considered included issues like publication bias, and statistical chicanery associated with p-hacking, HARKing, and underpowered studies....A 2015 editorial in The Lancet observed that 'much of the scientific literature, perhaps half, may simply be untrue.' A 2015 British Academy of Medical Sciences report suggested that the false discovery rate in some areas of biomedicine could be as high as 69 percent. In an email exchange with me, Ioannidis estimated that the nonreplication rates in biomedical observational and preclinical studies could be as high as 90 percent....Summarizing their results, an article in Science notes, 'More than half of Dutch scientists regularly engage in questionable research practices, such as hiding flaws in their research design or selectively citing literature. And one in 12 [8 percent] admitted to committing a more serious form of research misconduct within the past 3 years: the fabrication or falsification of research results.' Daniele Fanelli, a research ethicist at the London School of Economics, tells Science that 51 percent of researchers admitting to questionable research practices 'could still be an underestimate.' "

Such comments are consistent with my own frequent examination of neuroscience research papers. When examining such papers, I seem to find that Questionable Research Practices were used most of the time. Almost always, the papers include study group sizes that are less than the reasonable standard of having at least 15 subjects in every study group, meaning there is a high chance of a false alarm. Most of the times, the papers fail to show evidence that any blinding protocol was used. The detailed elucidation and following of a rigorous blinding protocol is an essential for almost any experimental neuroscience study to be regarded as reliable. Few papers follow the standard of pre-registering a hypothesis and methods for data gathering and analysis, leaving the researchers free to follow an approach rather like "torture the data until it confesses" to what the researcher is hoping to find. 

What this means is that the great majority of times you read about some neuroscience research on some science news site, you are reading about an unreliable result that should not be taken as robust evidence of anything. 

Frank mentioned "best practices," trying to insinuate that scientists follow such practices. He fails to tell us about the large fraction of scientists that follow shoddy practices.  Frank attempted to portray scientists as "follow strictly the good rules" guys acting like judges in a court. But it seems that a large fraction of scientists are like cowboys in the Wild West pretty much doing whatever they fancy.  And so many of the gun blasts from such cowboys are just noise. 

When You Read "It Is Widely Believed," Suspect a Dubious Belief Custom

We can classify several different types of scientific truth claims, along with some tips on how to recognize the different types. 

Type of truth claim	How to recognize it
Citation of established fact	Typically occurs with a discussion of the observational facts that proved the claim.
Citation of a claim that is not yet established fact	Typically occurs with phrases such as “scientists believe” or “it is generally believed” or an appeal to a “scientific consensus.” The claim of a “scientific consensus” is often unfounded, and there may be many scientists who do not accept the claim.
Citation of a claim that has little basis in observations, and that there may be good reasons for doubting	Often occurs with a phrase such as “it is widely believed,” or maybe a more confident-sounding phrase like “it is becoming increasingly clear” or “there is growing evidence.”

Claims that memories are stored in synapses fall into the third of these categories. To show that, I may cite some of the many times in which writers or scientists suggested that memories are stored in synapses, and merely used the weak phrase "it is widely believed" as their authority. 

• "It is widely believed that synaptic plasticity mediates learning and memory"  (link). 
• "It is widely believed that synapses in the forebrain undergo structural and functional changes, a phenomenon called synaptic plasticity, that underlies learning and memory processes" (link).
• "It is widely believed that synaptic modifications underlie learning and memory" (link).
• "As with other forms of synaptic plasticity, it is widely believed that it [spike-dependent synaptic plasticity] underlies learning and information storage in the brain" (link).
• "It is widely believed that memories are stored as changes in the number and strength of the connections between brain neurons, called synapses" (link).
• "It is widely believed that modifications to synaptic connections – synaptic plasticity – represent a fundamental mechanism for altering network function, giving rise to phenomena collectively referred to as learning and memory" (link).
• "It is widely believed that encoding and storing memories in the brain requires changes in the number, structure, or function of synapses"  (link).
• "It is widely believed that long-term changes in the strength of synaptic transmission underlie the formation of memories" (link).
• "It is widely believed that the brain's microcircuitry undergoes structural changes when a new behavior is learned" (link).
• "It is widely believed that long-lasting changes in synaptic function provide the cellular basis for learning and memory in both vertebrates and invertebrates (link).
• "It is widely believed that the brain stores memories as distributed changes in the strength of connections ('synaptic transmission') between neurons" (link).
• "It is widely believed that the long-lasting, activity-dependent changes in synaptic strength, including long-term potentiation and long-term depression, could be the molecular and cellular basis of experience-dependent plasticities, such as learning and memory" (link).
• "It is widely believed that a long-lasting change in synaptic function is the cellular basis of learning and memory" (link).
• "It is widely believed that the modification of these synaptic connections is what constitutes the physiological basis of learning" (link).
• "It is widely believed that memory traces can be stored through synaptic conductance modification" (link).
• "It is widely believed that memories are stored in the synaptic strengths and patterns between neurons" (link).
• "It is widely believed that long-term changes in the strength of synaptic connections underlie learning and memory" (link).
• "It is widely believed that long-term synaptic plasticity plays a critical role in the learning, memory and development of the nervous system" (link).
• "It is widely believed that learning is due, at least in part, to long-lasting modifications of the strengths of synapses in the brain" (link).
• "It is widely believed that long-term memories are stored as changes in the strengths of synaptic connections in the brain" (link). 
• "It is widely believed that activity-dependent modification of synapses is the brain's primary mechanism for learning and memory" (link).
• "It is widely believed that synaptic modifications are one of the factors underlying learning and memory" (link).
• "Learning, it is widely believed, is based on changes in the connections between nerve cells" (link).
• "It is widely believed that memories are stored as changes in the number and strength of the connections between brain cells (neurons)" (link).
• "It is widely believed that memories are stored as changes in the strength of synaptic connections between neurons" (link). 
• "It is widely believed that memory formation is based on changes in synapses" (link).

There is no good evidence that any memories are stored in synapses or stored through a strengthening of synapses or stored by a modification of synapse weights, or stored anywhere in the human brain through any means. No one has any understanding or any credible coherent theory of how learned information or episodic memories could ever be stored using synapses or any other part of the brain. We know of the strongest reason for rejecting all of the claims in the bullet list above, which is that the average lifetime of the proteins in synapses is only about two weeks or less.  The proteins in synapses last an average of only about a thousandth of the longest length of time that humans can remember things (50 years or more). Moreover, humans can form permanent new memores instantly, which could never occur if forming such memories required synapse strengthening (something that would take minutes or hours, because it would require the synthesis of new proteins). 

The examples in the bullet list above are simply an example of a speech custom. Scientists and science writers have got in the bad habit of saying something like "it is widely believed that memory formation occurs through changes in synapses." The fact that such a large fraction of the writers repeating this myth use the same language phrasing (including the phrase "it is widely believed") shows that what is going on is mainly people parroting what other people have said, rather than independently reaching intelligent judgments based on facts.  I may note that in not a single one of these cases has any of these writers even claimed a scientific agreement, or even a majority of scientist opinion.  Claiming that something is "widely believed" is to make a claim much weaker than claiming "almost everyone believes" or "most people believe." When people haven't got much of a case, they use phrases like "it is widely believed." 

In general, when you hear or read someone using the phrase "it is widely believed," you should suspect a dubious belief custom or a misguided belief.  For example, if someone says "it is widely believed you can't trust men from that country," he is saying something that means very little. And if someone says, "it is widely believed that the thirteenth day of the month is unlikely," you are probably just hearing an old wives tale.  Because they all use the weak shaky phrase "it is widely believed," every statement in my bullet list above should be treated as a "red flag" indicating a lack of good evidence. 

Neuroscientists Keep Using Misleading Coloring in Brain Visuals

In my July 2018 post "The Brain Shows No Sign of Working Harder During Thinking or Recall," I looked at quite a few brain scan studies looking for neural correlates of thinking or recall, and showed how such studies show no evidence that brains work harder when you are thinking or remembering anything. Below I will discuss some other studies not listed in that post, studies looking for signs of increased activity when a person is engaging in some kind of recall, recognition or heavy thinking. 

• A study published in November 2018 was entitled "BOLD Activity During Correct-Answer Feedback in Cued Recall Predicts Subsequent Retrieval Performance: An fMRI Investigation Using a Partial Trial Design." Some fMRI scans were made of dozens of subjects during a verbal recall task. Figure 4 of the paper shows a graph displaying signal changes of no greater than about .3 percent. This is about 1 part in 1000, no greater than we would expect to see by chance. The results are quite consistent with the claim that memories are not stored in brains.  No significant sign has been found that brains act differently during recall. 
• An August 2020 paper was entitled "Aging alters neural activity at event boundaries in the hippocampus and Posterior Medial network."  Hundreds of subjects were shown a movie and had their brain scanned. Ignoring Figure 1, which doesn't deal with recall, and looking at Figure 2, which does deal with recall, we see that the average signal change was only about 1 part in 1000, and that the greatest reported signal change (in the highest outliers) was only about 1 part in 300. No significant sign has been found that brains act differently during recall. 
• A 2010 study not mentioned in my July 2018 post is the study "Age-related effects on the neural correlates of autobiographical memory retrieval."  The study did brain scans of 14 young and 14 old people during recall of things that had happened in their lives. None of the results reported in the paper's graphs (such as Figure 1) show a percent signal change greater than 1 part in 1000. The results are quite consistent with the claim that memories are not stored in brains.  No significant sign has been found that brains act differently during autobiographical recall. 
• A January 2021 study was entitled "Neural correlates of recursive thinking during interpersonal strategic interactions." Figure 3 of the study shows no percent signal change greater than about 1 part in 300.  The results are consistent with the idea that thinking is not produced by the brain, and no significant sign has been found that brains act differently during thinking. 
• A 2018 study not mentioned in my July 2018 post is the study "Neural correlates of free recall of 'famous events' in a 'hypermnestic' individual as compared to an age- and education-matched reference group."  The study scanned the brains of 11 people while recalling famous events. Figure 3 shows that the percent signal change was no greater than about 1 part in 500. The results are consistent with the claim that memories are not stored in brains.  No significant sign has been found that brains act differently during recall of famous events. 
• A 2015 study not mentioned in my July 2018 post is the study "Amygdala Activity During Autobiographical Memory Recall in Depressed and Vulnerable Individuals: Association With Symptom Severity and Autobiographical Overgenerality."  We are told, "Sixty healthy control subjects, 45 unmedicated currently depressed individuals, 25 unmedicated remitted depressed individuals, and 30 individuals at high familial risk of developing depression underwent functional MRI while recalling autobiographical memories in response to emotionally valenced cue words."  Figure 1 of the paper has a graph showing that the percent signal change was less than .2 percent, less than 1 part in 500. The results are consistent with the claim that memories are not stored in brains.  No significant sign has been found that brains act differently during recall.
• A 2014 study not mentioned in my July 2018 post is the study "Mean signal and response time influences on multivoxel signals of contextual retrieval in the medial temporal lobe." Brain scans were done "while participants retrieved pair, spatial, and temporal source memories." 17 subjects had their brains scanned during such recall.  Figure 3 shows that the percent signal change was less than .1 percent, less than 1 part in 1000. The results are consistent with the claim that memories are not stored in brains.  No significant sign has been found that brains act differently during recall.
• A 2019 study not mentioned in my July 2018 post is the study "Common and Distinct Functional Brain Networks for Intuitive and Deliberate Decision Making." The study is unable to show brain imaging evidence for brains causing thinking, because its graphs (Figures 4, 5  and 6) show no percent signal change greater than 1 part in 300. 

As we can see from examples like the ones above and the more numerous examples ones in my earlier post, brains look the same when you are doing nothing as they do when people are thinking hard, learning and remembering. So how is it that neuroscientists manage to create the impression that particular parts of the brain are more active during particular mental activities? They use two main tricks:

(1) The trick of wrongly using the words "activated" or "activation" when referring to differences in activity that are only about 1 part in 1000, the kind of difference you would expect to occur by chance. Such language is profoundly misleading.  All parts of the brain are active at all times, and there is no appreciable effect of certain brain regions "turning on" during particular mental activities. 

(2) The trick of visuals that depict brain activity differences of only about 1 part in 1000 in bright red, thereby suggesting a very big difference when there is only an extremely slight difference.  You can read here about how such a trick is performed. 

We can imagine a racist using similar coloring tactics to mislead us. Getting data showing negligible temperature differences between races of only 1 part in 1000, the racist might show us a diagram of different races, depicting some particular race with bright red heads, in an attempt to persuade us that the members of that race are "hot-headed" and prone to get angry.  

Eye pupils vary by 500% under different light conditions, and heart rate differs by as much as 300% between resting and heavy exercise. That shows you that eye pupils are really involved in vision, and that hearts are really involved in supplying the body with blood.  The thousand-times weaker variation in brain activity between mind resting and heavy mind activity does nothing to establish claims that brains produce thinking or that brains store memories. 

The tricks and fallacies of those trying to prove that brains make minds are similar to the tricks and fallacies of the people who called themselves phrenologists in the nineteenth century. In that century, a system called phrenology was very popular.  It was all based on the idea that particular mind functions and personality traits were concentrated in particular areas of the brain, and that you could tell something about a person's mind or personality by feeling little bumps on his head. If you click on the link here, you can find many long works attempting to prove this extremely erroneous idea. In fact, following that link will show that in its vast archives of old books www.archive.org has more than 500 books devoted to teaching the bunk that is phrenology. Most of the writers of such books  thought they were teaching the "latest and greatest" neuroscience when they taught phrenology nonsense.   A wiser future age will look back on the main papers of today's self-described "cognitive neuroscientists" the way we look back now on the phrenology volumes of the nineteenth century.