How to Tell Whether a Neuroscience Research Announcement Is Unjustified

Questionable Research Practices and shoddy methods are extremely abundant in today's neuroscience research.  How is it that you can detect such examples of poor research? I will give here a method. The method mainly involves looking for certain types of defects in scientific papers, but also involves looking for defects in press announcements about such papers. 

Step #1: open up a "defect list" file

You will be using this file to record any defects you find in either the original scientific paper or any of the press announcements that occur about that paper.  You can create such a file by getting a blank piece of paper, opening up a new file using a tool such as Notepad, opening up a file using Google Docs, clicking on the Notes utility on your I-Pad, and so forth. 

Step #2: Look for a claim in the headline of an article or press release announcing the research that is not justified by any claims in the text of the article or the text of the academic press release. 

An article that you read announcing the research may or may not be the academic press announcing the research. If the press article is not the original academic press release, it may have a link to the academic press release.  The academic press release will typically have a link to a newly published scientific paper, and such a link may also be found in some article based on the press release. 

An extremely common defect of press articles about scientific papers is that they very often make boastful headline claims that are not justified by anything claimed or established in the articles underneath such headlines. This often occurs for economic reasons, to create the effect known as clickbait. Clickbait is when online articles have sensational-sounding headlines or interesting-sounding headlines that lure you into going to some web page that has ads. The people running or funding such pages thereby get advertising revenue when such pages are viewed. 

Clickbait is enormously abundant in the world of science journalism. University press releases very often contain headlines never justified by anything mentioned in the story underneath such headlines. Press articles based on such press releases very often contain headlines never justified by anything mentioned in the story underneath such headlines, or never justified by anything stated in the body of the press release such articles were based on.

A simple starting point in detecting unjustified neuroscience research announcements is to simply compare headlines to the text underlying such headlines, and note cases in which the headline is unjustified. Record any such cases in your "Defects list" file, nothing the URL of the corresponding press article or press release.

I will give a very simple example of such a thing. A headline may announce "Scientists Unlock the Secret of Human Memory Retrieval" But the underlying story may refer to research that only dealt with mice. In such a case the unjustified hype is obvious -- the research told us nothing about human memory. 

Step #3: find a copy of the scientific paper that is the basis of the press release or press article. 

Generally the press article or press release will have a link to a scientific paper that is the basis of the research announcement. In the easiest case, you will simply be able to click on that link to get the full text of the paper.  But in many cases when you click on the link, you will go to a page that merely has the abstract of the paper. There may be some "Full Text" link that asks you to pay money. Such a barrier to you reading the paper is called a paywall. I strongly advise against ever paying money merely to research the quality of a neuroscience paper.  Most neuroscience research papers these days are poor quality papers guilty of multiple examples of Questionable Research Practices. 

But if you find yourself blocked by a paywall, there are some things you can do to try to get the paper:

(1) Go to the Google Scholar site (https://scholar.google.com/), and copy the name of the paper into the search bar. See whether the paper shows in the search results, with a link to the full text of the paper.

(2) Go to the biology preprint server (https://www.biorxiv.org/) and copy the name of the paper into the search bar. See whether the paper shows in the search results. If it does, you will typically be able to get the full text of the paper by clicking on the Full Text tab on that site. 

Step #4: examine the title of the paper and read its abstract, looking for a claim in the title that is not matched by any claim in the abstract

It is surprisingly common these days for the titles of neuroscience research papers to make claims that are not justified by any statements made in either the abstract of the paper or the full text of the paper. If you find any discrepancy between the title of the paper and the results announced in the abstract, record such a discrepancy in your "defects list" file.

Step #5: if the paper is an experimental research file, look for evidence of insufficient study group size

Since the use of way-too-small study group sizes is amazingly predominant these days in experimental neuroscience research,  the abstract of every paper should tell how many subjects were used in each of the study groups. But like people who are trying to hide their shortcomings, the abstracts of experimental neuroscience research papers rarely list the study group sizes used. So you will usually need to search the text of the paper for an indication of the study group sizes used.  

Any experimental neuroscience paper using fewer than 15 subjects in any of its study groups should be regarded as a paper that has used a way-too-small study group size. There are actually reasons for thinking that any use of fewer than 25 subjects in any of the study groups is a reason for doubting the quality of the study, particularly if the work involves brain scans of humans.  

Do not stop looking for study group sizes if you see a statement indicating a fairly large study group size such as 50. What very often happens in neuroscience papers is that the paper will announce a fairly large number of subjects (such as stating "50 mice were analyzed"), but will then divide this group up into smaller study groups, so that the smallest study groups used is much smaller than such a fairly large number. Look for any cases of any study group sizes smaller than 15. 

How do you find what study group sizes were used? The easiest way is to search in the text for the phrases "n=" or "n =". It is a custom in neuroscience research papers to list study group sizes using phrases such as "n =8." For example, the text may vaguely refer to "subjects" or "mice" without specifying how many. Then the text of the paper may state the exact number of subjects by using a phrase such as "n = 10." Another way to search for study group sizes is to search for the phrases "mice," "rats," "subjects" or "humans" and look for a number preceding such phrases. 

Whenever any such searches reveal a study group size of less than 15 or 20, you have discovered prima facie evidence of a too-small study group size, and you should record such a defect in your "defects list" file. Rarely you will find a paper that makes no mention of how many experimental subjects were used. The failure to record so vital a fact is itself a defect that you should note in your "defects list" file.

When an experimental neuroscientist is doing his job right, he will use some statistical method to do what is called a power analysis or a sample size calculation or a power size calculation. This involves some mathematical calculation of what sample size was needed to achieve some particular degree of statistical power.  Many science journals require that a paper state whether or not such a calculation was done. Search for the phrase "sample size calculation" or "power size calculation" or "power calculation" to see whether such a calculation was done. You will often read a confession that no such calculation was done.  If you find such a confession, write that down in your "defects list" file.  If you fail to find any mention of such a calculation, that is also a defect that should be noted in your defects list file. 

Step #6: look for a failure to use controls

Almost any experimental neuroscience experiment should be using controls.  In experimental science a control can be a subject that does not have some characteristic or variable or intervention being tested, or a control can be a neutral state that does not match some experience or condition being tested.  For example, if you are testing some medicine, you can give 15 subjects the medicine, and give 15 other subjects some placebo that is not some medicine. Or, if you are testing whether some cognitive activity such as memory recall causes increased activation of some brain region, you might take 15 brain scans while a subject was engaging in memory recall, and 15 brains "control" scans on some other day in which the subject was asked to think of nothing.

It is easy to check whether a scientific study made use of controls. Just do a text search in the paper for the word "control" looking for usage that indicates controls were used. Typically phrases such as "control subjects" or "control state" will be used.  If you fail to find any evidence controls were used, record that failure in your "defects list" file.

Step #7: look for a failure to follow a detailed blinding protocol

In experimental neuroscience a blinding protocol is usually needed for a robust result. A blinding protocol is a procedure that helps to minimize the chance of a biased analysis.  I can give some examples to illustrate the concept. Imagine you brain scan 15 subjects who were asked to recall memories while their brains were scanned, and you also brain scan 15 other subjects who were asked to think of nothing while their brains were being scanned.  Then suppose you give the brain scans to some analyst.  If the analyst knows that the first 15 brain scans were from people who were recalling things, and the second 15 subjects were from people thinking of nothing, and also that the purpose of the test is to look for brain differences in memory recall, such an analyst will be all too likely to "see what his bosses are hoping he sees," and produce a biased result.  The risk of such bias could be avoided by a careful blinding protocol.  Each set of brain scans could be assigned a random number, with someone recording which number matched a person recalling something, and which number corresponded to a person not recalling something.  If there was a stack of 30 folders, each containing one subject's brain scans, the folders could be shuffled so that the analyst could not tell which one came from some one recalling something. It could then be stated in the paper that the person analyzing the brains was "blind to which subjects had engaged in memory recall." 

There is another type of blinding that could occur. Instead of the brain scan analyst being told that half of the subjects were engaging in memory recall, and half were not, the analyst could be told nothing at all about what the people were doing during the scans. This would make it all the more unlikely that the analyst would see some effect that wasn't really there.  Normally in every study there are multiple ways in which blinding should occur. 

A failure to follow blinding protocols is one of the most egregious defects of today's neuroscience research. Most experimental neuroscience studies fail to follow any blinding protocol. The failure can easily be found if you have the full text of the paper. Simply do a text search for the word "blind." If you fail to find meaningful uses of the word "blind" in the text of the paper, thereby indicating a failure to follow a blinding protocol, record that failure in your "defects list" file.

One or two uses of the word "blind" in the text of a paper does not show that an effective blinding protocol was used. It is all too easy for some experimenter to have an ineffective blinding protocol that fails to achieve much of any real blinding. The smaller the study group size, the easier it is for any attempt at blinding to be ineffective.  I will give an example. Suppose a study used only seven rats for an experimental group, and seven rats for a control group.  The seven rats in the experimental group might be given some modification not given to the seven rats in the control group.  After being given foot tags to identify them with random numbers, the fourteen rats might then be given to an analyst asked to test for some difference.  But if the analyst was involved in applying the modification, it might be all too easy for him to recognize which rat had the modification, and which did not.  For example, only the rats given the modification might have some surgical mark showing they had the modification. What this example shows is that to be effective, a blinding protocol must be a detailed, carefully thought-out plan that prevents "sham blinding" in which someone supposedly blind to which subjects were in the control group is not really blind to such a thing.  

If you either fail to see the word "blind" being used in the text of an experimental neuroscience paper, or if you find the word "blind" or "blinding" only being used once or twice "in passing," you should note the result in your "defects list" file. Also note it in your "defects list" file if you fail to find a detailed discussion of a blinding protocol. If a study merely claims that some analysis was done by analysts "blind" to whether the subjects were control subjects, and fails to discuss how a careful detailed plan was followed to prevent "sham" blinding, that also should be recorded in your "defects list" file. 

Step #8: look for convoluted analysis pathways that may have "conjured up" some illusory result

In my post "Convoluted 'Spaghetti Code' Analysis Pathways Help Neuroscientists Conjure Phantasms That Don't Exist," I gave two examples of scientific papers that used ridiculously convoluted analysis pathways.  Don't be impressed when you see such methods, which may seem like gobbledygook or rigmarole.  Such over-complicated methods are typically not signs of good experimental methods, but instead a failure to follow a straightforward technique for analyzing data. What is going on often can be describe as "keep torturing the data until it confesses." 

Besides doing a quick scan looking for byzantine analysis pathways that sound like statistical "monkey business," there are some things you can look for:

(1) Look for the word "iterations" which typically indicates that some data was passed through a programming loop in which the data may have been distorted or contorted or convoluted. 

(2) Look for the phrases "processing" (particularly "data processing," "preprocessing" or "pre-processing" or "post-processing" or "postprocessing"), phrases which indicate that data has been passed through some computer program.  Once data has been passed through a computer program, there are any number of ways in which the data can be contorted, distorted or corrupted.  Often computer programs processing neuroscience data are written by scientists who are not professional computer programmers, and who can often produce unreliable results. If the programming job is given to a professional programmer, the person may be someone who does not understand the data, leading to unreliable results. Programming code used in scientific research is very often poorly written and poorly commented, producing effects that may be known only to the original programming. Very often the result is a "black box" situation in which even the original programmer does not understand what is happening to the data. 

If you find evidence of such dubious-sounding analysis pathways or dubious pre-processing or post-processing of brain scan data or neuroscience data, add some lines to your "defects list" file recording such a finding. 

Step #9: look for fake data in the science paper, which may be described using the word "simulated" or "simulation." 

Neuroscientists often look for things they cannot find but are hoping to find. When they cannot find such things, they often resort to generating simulated data to try to fill in the gap. Whenever you hear the word "simulated" in a neuroscience paper, you should presume that this actually means "fake."  Search for the words "simulated" or "simulation" in a neuroscience paper. Note the resorting to such simulated data in your "defects list" file. Trying to pass off simulated data rather as if it was real-world data is a sleazy trick you should "throw a flag on" when critically analyzing neuroscience papers. 

Step #10: look for p-hacking 

Modern experimental science has the silly rule that a result is treated of worthy of publication if someone found it to have a "statistical significance" of .05 or less.  This rule ends up being a very silly one in many cases in which it is very easy to get such a result when it is merely a false alarm. Very roughly you can think of a statistical significance of .05 as a result you might get by chance once in 20 tries. Given a lack of pre-registration in scientific studies, it is rather easy to get such a result. You can just keep trying something multiple times, calling these trials Experiment 1, Experiment 2, and so forth. When you get a result that you would get by chance once in 20 times, you can then write up that result, and describe only it. 

How do you find evidence of unimpressive results such as this in a scientific paper? Statistical significance is reported using a phrase such as "p < .05" or "p < .01" or "p < .001."  You can search for such phrases. Whenever you find the phrase "p < .05"  it is a sign that an unimpressive result was obtained.  Write down any such occurrence in your "defects list" file. The more examples you find of the phrase "p < .05" the stronger the case you can make that "p-hacking" went on. 

Don't be impressed if you find a stronger statistical significance reported in addition to a marginal statistical significance of "p < .05." What often happens is that the most relevant result will be some marginal borderline result of "p < .05" but other results not very relevant will be reported with a stronger statistical significance such as "p < .01" or "p < .001." This is often done as a kind of window dressing to give you the impression that the paper has more impressive results than it has. The results with higher statistical significance may be irrelevant to the main claim made by the paper. 

Step #11: look for lack of pre-registration 

It has been pointed out many times that when an experimenter fails to state before gathering data a hypothesis to be tested and a detailed research plan for how to gather and analyze data, there will be a much higher chance of some false alarm being reported. A researcher who is free to "make up his method as he goes along" will be free to keep playing around with data analysis pathways until he seems to find something he was hoping to find.  Pre-registration (also called the use of "registered reports") is when a researcher publishes a hypothesis to be tested and a detailed research plan before any data is gathered. It is widely recognized that following such a method greatly reduces the number of false alarms that are reported. 

It is easy to search in a scientific paper for whether pre-registration occurred. Simply search in the text of the paper for the terms "registered report," "pre-registered" or "pre-registration." If no such terms are found, note this in your "defects list" file. 

Step 12: look for unreliable measurements of memory, such as attempts to judge "freezing behavior." 

There are reliable ways to judge whether an animal remembered something, and also unreliable ways. A reliable way to judge whether a a rodent trained to fear some stimulus (such as a shock plate) is to measure heart spikes when the animal is placed near the pain-inducing stimulus.  Heart rates very dramatically spike in rodents when they are afraid. Another reliable way to judge whether a a rodent trained to fear some stimulus such as a shock plate is to use some setup such as the one shown below, in which an animal remembering the fear stimulus will take the harder path towards a reward rather the easier path.

A very unreliable way of measuring rodent recall of a fearful stimulus is to try to judge "freezing behavior," defined simply as immobility. My post here explains why such a technique is very unreliable as a way to judge whether recall or fear occurred.  Attempts to judge so-called "freezing behavior" are massively used in experimental neuroscience involving rodents and memory. This is an example of a dysfunctional research community tradition. If you find that the neuroscience paper you are examining made any use of judgments of "freezing behavior," note that in your "defects list" file.  All neuroscience papers relying on "freezing behavior" judgments are junk science.  

Once you have taken such steps, you have the basis for a critical review of a neuroscience paper.  Very often your "defects list" file will contain multiple examples of Questionable Research Practices, often more than five. Mentioning such defects, you can explain to a reader why some triumphal announcement of neuroscience progress is unjustified. 

Click to see left column more clearly

Click to see left column more clearly

The Content of Apparition Sightings Argues Against the Hallucination Explanation

 Humans often report apparition sightings. Skeptics try to explain such sightings as hallucinations. Let us consider what we would expect under the hallucination hypothesis, and compare that to what is observed in apparition sightings. 

Under the hypothesis that apparition sightings are hallucinations, we would expect all of the following things:

(1) It would be just as common, or perhaps even more common, for people to see apparitions of healthy, living people (with years of additional life)  as apparitions of dead people.

(2) It would be just as common for people to see apparitions of animals as apparitions of humans. 

(3) It would be just as common for people outside of reputed haunted places to see apparitions of historical people or celebrities as apparitions of family members or friends. 

(4) It would be just as common for people to see apparitions of lifeless things as apparitions of humans. 

(5) Almost never (except by the most improbable of coincidences) would two or more people report seeing the same apparition. If an apparition was a hallucination caused by some rare brain state, we would not expect so rare a brain state to appear identically to two people, so that they both reported seeing at the exact same an illusory thing (such as the same deceased person). That would be as improbable as two people sleeping together waking up, and both of them reporting that they just had the same dream (such as a dream of a dinosaur roaming about). 

(6) The people who reported apparitions of the deceased would be mainly mentally ill people.

All of these predictions fail to match reality. Let's look at each one. 

Prediction 1: "It would be just as common, or perhaps even more common, for people to see apparitions of healthy, living people (with years of additional life) as apparitions of dead people." Counting the entire lifespan (which often includes sightings of apparitions at the end of life), it is fairly common for people to report seeing an apparition of someone known to be dead. Also, a large class of apparitions consists of cases in which someone reports seeing an apparition of someone who was later found to have died at about the same time, or later found to have been close to death at about the same time. I give very many examples of such apparitions in the series of 16 posts you can read here (you can read all of them by continuing to press Older Posts when you come to the bottom). But it seems to be rare for someone to report an apparition of a living, healthy person who had years of additional lifespan ahead of him. Such cases seem to be many times  less common that apparitions of someone who previously died or died at about the same time the apparition was seen. 

Prediction 2: "It would be just as common for people to see apparitions of animals as apparitions of humans." For a large fraction of people, pets are almost like family members. But it seems to be very rare for someone to report seeing an apparition of a deceased pet. The topic is discussed in the news article below, published after the Society for Psychical Research had published hundreds of accounts of apparitions of humans: 

We read at the top left a statement that apparitions of animals are very scarce. 

Prediction 3: "It would be just as common for people outside of reputed haunted places to see apparitions of historical people or celebrities as apparitions of family members or friends." In England there are various old castles or old buildings where there are supposedly apparitions of historical figures sometimes seem. Outside of such cases, it seems to be very rare for anyone to see an apparition of a historical figure. 

Under the theory that apparitions are hallucinations, we would expect apparitions of Jesus to be very common in countries where Christianity is predominant. Apparitions of Jesus seem to be very rare for those not being diagnosed with schizophrenia.  The Chronicling America web site allows you to do text searches of American newspapers from 1756 to 1963.  Searching for the phrase "apparition of Jesus" on the Chronicling America web site produces only 11 matches, with only one of the newspaper accounts referring to an apparition of Jesus reported in modern times.  For some reason, searching for the phrase "ghost of Jesus" on this site does not work to find matches of that exact phrase, but instead picks up any page (very many) referring to the Christian Trinity using the older phrasing such as "the Father, the Son and the Holy Ghost."

Abraham Lincoln was the most famous US president between 1820 and 1920, but searching for "apparition of Lincoln" on the Chronicling America web site produces no cases of anyone reporting an apparition of Lincoln. Similarly, searching for "apparition of Napoleon" on that site produces no cases of anyone reporting an apparition of Napoleon, merely a few repetitions of someone loosely using the word "apparition" to merely mean a sighting of Napoleon while they were in the presence of the living Napoleon.  Without using such a term, I did find one account of someone claiming to see an apparition of Napoleon. 

By comparison, searching for the phrase "apparition of her husband" produces 45 results, many of which are accounts of people claiming to see apparitions of husbands; and searching for "ghost of her husband" produces 126 matches. 

For example, in one newspaper account we read this:

"Calling together her friends and neighbors, she told them she had just seen an apparition of her husband, who, for two years had been absent In New York. He appeared to her to be lying

in a hospital with one hand covering his breast, and he told her that he had been gravely wounded. The day after she received a cablegram from America Informing her that her husband was

dying, having been stabbed by an emissary of the Black Hand."

Similarly, searching for "apparition of his wife" produces 11 matches, searching for "ghost of his wife" produces 119 matches,  searching for "apparition of his father" produces 20 matches, searching for "ghost  of his father" produces 119 matches, searching for "apparition of his mother" produces 6 matches, searching for "ghost of his mother" produces 58 matches, searching for "apparition of her mother" produces 7 matches,  searching for "apparition of her father" produces 9 matches, searching for "ghost of her father" produces 47 matches, searching for "apparition of his brother" produces 5 matches, searching for "apparition of his sister" produces 5 matches, searching for "apparition of her sister" produces 11 matches, searching for "apparition of his friend" produces 11 matches, searching for "apparition of her friend" produces 7 matches, searching for "ghost of her friend" produces 4 matches, and searching for "ghost of her friend" produces 47 matches.

Clearly Prediction #3 does not match reality. It is very much more common for people to report seeing apparitions of deceased family members or deceased friends (or family members or friends at about the same time they died) than to see apparitions of historical figures or celebrities. 

Prediction #4: "It would be just as common for people to see apparitions of lifeless things as apparitions of humans."  It seems to be extremely rare for anyone to see an apparition of a lifeless thing. Automobiles have long played a central role in the life of Americans. But a search for the phrase "apparition of an automobile" on the Chronicling America web site produces only two matches, both of which refer only to horses being scared by automobiles, not humans reporting an apparition of an automobile. No one ever reports seeing an apparition of an automobile in their house or back yard. 

Prediction #5: "Almost never (except by the most improbable of coincidences) would two or more people report seeing the same apparition."  This prediction fails. There are hundreds of cases of more than one people reporting the sight of the same apparition. Such cases can be examined by using the link here, and continuing to press Older Posts at the bottom right. Among the posts you can read using that link are these:

When Multiple Witnesses See the Same Apparition

When Two or More See the Same Apparition

When an Apparition Is Seen by Multiple Observers: 17 Cases

When an Apparition Is Seen by Multiple Observers: 17 More Cases

More Apparitions Seen by Multiple Observers
Many an Apparition Is Seen by More Than One
Still More Apparitions Seen by Multiple Observers

When an Apparition Is Seen by Not Just One

Prediction #6: "The people who reported apparitions of the deceased would be mainly mentally ill people." There is no evidence that this is the case. The great majority who report seeing an apparition of the deceased are normal people who never previously hallucinated.  I personally have published many posts describing many hundreds of apparition sightings, and I can almost never recall such a reported sighting coming from someone with signs of psychosis. 

The content of apparition sightings (mainly involving either family members or friends who either died earlier or at about the same time as the apparition was seen) argues strongly against the claim that apparition sightings are mainly hallucinations. Apparition sightings are an extremely important clue about the nature of our minds: one of many clues that our minds are not the products of our brains, and that minds can exist outside of bodies.  There are many other types of clues telling us the same thing, clues discussed in the posts of this blog. 

The ignoring of apparition sightings by today's neuroscientists is an example of people senselessly ignoring a very important clue, rather like a trusting wife ignoring the very important clue of strange panties repeatedly found under her bed, panties she does not recognize as her own. Senselessly, today's scientists profess belief in things humans never have observed (such as dark matter, dark energy and synapse-stored memories), while refusing to believe in things (spirits of the deceased) that very many people have claimed to have directly observed. It's as if their inner rule was a senseless and unscientific  rule of "believe as my peers believe, not in proportion to how many observations there were of something." 

Groundlessly Boasting Mouse Hibernation Study At Least Reveals the Short Lifetimes of Synapses and Dendritic Spines

 The recent paper "Artificial hibernation reveals synaptic engram architecture associated with memory retention" is another neuroscience paper making a groundless boast in its title. The authors did nothing at all to reveal a "synaptic engram architecture associated with memory retention."  But this weird study involving putting mice into a kind of artificial hibernation does at least reveal something that helps to debunk all claims of synaptic memory storage. 

The final version of the paper is behind a paywall. But when I search for the paper on Google Scholar, it gives me a preprint as the corresponding .pdf file. The preprint is by the same authors, and has an almost identical title, a title of "Artificial hibernation uncovers distinct synaptic engram architecture for memory retention." So I can use that preprint to analyze the research that went on here.  My use of "the paper" below refers to the preprint. 

The paper is one that has many untrue or groundless statements that reflect the author's dogmas and "improperly jumping to conclusions" thinking. Any statements that the authors make using the words "engrams" or "representations" are groundless. These days cognitive neuroscientists are misusing those words very abundantly. Being guilty of "see what you are hoping to see" pareidolia, neuroscientists are frequently claiming without any good warrant to have seen "representations" of this or that in the brain. It's a "Jesus in my toast" kind of affair.  Similarly, whenever neuroscientists use the term "engram" these days, they are making groundless claims in which some cells or synapses are called "engrams," despite a lack of any decent evidence that any such thing as memory storage has occurred in such cells. "Engram" is a word referring to a claimed place of memory storage in the brain. 

The paper is guilty of methodological sins. The study group sizes were ridiculous, consisting of way-too-small study group sizes such as only three mice, only four mice, only five mice, and a study group size imprecisely described as "6-10 mice for each group."  No study like this should be taken seriously as experimental evidence unless it used a study group size of at least 15 or 20 animals per study group. The authors have used the worthless "freezing behavior" method of trying to judge memory recall, which means that what they claim about experimentally demonstrating memory retention should not be regarded as very reliable. Read my post here for why such a method is worthless as a technique for measuring whether a rodent recalled anything. 

But we do get something of value from the paper: some observations of how unstable and short-lived are synapses and dendritic spines. These are observations which help to discredit the popular but groundless dogma that memories are stored in synapses of the brain, which tend to protrude from 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. 

Neuroscientists have often speculated that dendritic spines could be some type of memory storage system, although such a speculation is silly. Dendritic spines no more resemble a memory storage system than do the little twigs on the branch of a tree. And while memories can last decades, dendritic spines are very unstable, typically having a lifetime of only weeks or months.  

We read this (the "QIH" refers to a roughly 48-hour period of artificial hibernation produced by the experimenters):

"We also evaluated the similarity of the locations of all dendritic  spines before and after QIH. The similarity in spine locations between Day 1 and 3, with QIH in between, was 0.91 on average, which was not significantly different from the similarity between Day 3 and 7 without QIH (0.88)."

So in a mere two days or four days, the dendritic spines on the mice lost about 9% of their previous appearance. You can extrapolate from that to get a dendritic spine average lifetime of only several weeks, which is consistent with previous observations by others reported here. Because synapses are typically attached to dendritic spines, anything we learn about the short lifetime of dendritic spines is something also telling us about the short lifetime of synapses. 

The paper also tells us something about the lifetime of synapses. It states this, referring to a hibernation period of only two days. 

"In the current study, we used artificial hibernation in mice to induce extreme downscaling of the neuronal activity and dendritic structures in the hippocampus. During this hypothermic and hypometabolic state, hippocampal neurons show a ~70% reduction in firing rate and the elimination of more than 50% of synapses." 

This is a devastating answer for any one believing that memories are stored in synapses. Extrapolating from such a rate of decay, we would guess that synapses have an average lifetime of only a few days or maybe a few weeks. 

It has long been known that synapses are built from proteins that have very short average lifetimes of only a few weeks.   Richard Huganir led a study that was specifically dedicated to trying to find long-lived proteins in synapses. None were found.  The scientific paper found no such thing. Quite to the contrary, the paper found the following:

• Studying thousands of brain proteins, the study found that virtually all proteins in brains are very short-lived, with half-lives of less than a week.
  
• Table 2 of the paper gives specific half-life estimates for the most long-lasting brain proteins, and in this table only 10 out of thousands of brain proteins had half-lives of 10 days or longer.
  
• Of the proteins whose half-life is estimated in Table 2, only one of them has a half-life of longer than 30 days, that protein having a half-life of only 32 days.
  
• A graph in the paper indicates that none of the synapse proteins had a half-life of more than 35 days.
  

Below is a graph from the Huganir paper. It shows that the study found that virtually all proteins in synapses are very short-lived.

Below is another graph from the same paper. It shows that the study found that virtually all proteins in synapses are very short-lived.

Judging from these graphs, none of the proteins found had a half-life of longer than 35 days, and only a few had a half-life of more than 14 days.

The 2025 paper here states this:

"We measured the lifetime of the major excitatory synaptic scaffold protein PSD-95 over a range of spatial scales from brain regions to single synapses. PSD-95–HT lifetimes ranged from 11 to 14 days, depending on the brain region (Fig. 2f,g)."

So if synapses are made from proteins with short lifetimes of only a few days or weeks, we should not be surprised that a researcher would find that about 48 hours would produce a 50% reduction in synapses. Most synapses are attached to dendritic spines. So the previous result about the short lifetime of dendritic spines reinforces the conclusion that synapses have short lifetimes. 

The paper here states, "Experiments indicate in absence of activity average life times ranging from minutes for immature synapses to two months for mature ones with large weights."  The paper suggests that even larger synapses last only two months.  A 2025 paper states that  "the synaptic turnover rate is as high as 1% per day in the visual cortex." Such a rate of turnover is equivalent to a synaptic lifetime of only about a year. Another paper  states that in  hippocampal CA1 cells the synapses have an  estimated lifetime of only 1–2 weeks.

The lifespan of synapses is of very great relevance to whether there is any credibility in the claim that synapses store memories. Old humans can remember very well many things they learned and experienced 50 years ago. But if synapses have short lifetimes, they cannot possibly be a storage place of knowledge humans learned 50 years ago,  and synapses cannot be a storage place of memories humans had 50 years ago.  If synapses have short lifetimes, the synaptic theory of memory is untenable. 

The issue that synapses are made of proteins with short lifetimes has been known for decades. So why on Earth do so many neuroscientists keep claiming that memories are stored in synapses? It's simply that they have no other alternative theory of brain-stored memories that is any better.  Nothing in the brain looks anything like a system for storing, preserving or retrieving learned information or experiences an organism had.  

We know that the body does one type of reading of information: the reading of genetic information from DNA. We understand some of the extremely complex molecular machinery that is involved in such reading. The transcription of DNA requires the RNA Polymerase II protein complex described in my post here. It is a very complex component requiring a special arrangement of more 10,000 amino acids.  Other complex components are required for the reading of DNA, which takes minutes. 

If information were to be stored in synapses or dendritic spines, there would have to be very complex components capable of reading such information. But no trace of any such component can be found. If any such component existed, it would require minutes to read information from synapses and dendritic spines.  Such a hypothetical reality would be utterly incapable of explaining the wonder of instant memory recall. If you ask me, "Who was Abraham Lincoln?" it does not take me minutes to give a detailed answer. I will instantly answer: "The US president during the American Civil War who was assassinated in 1865." 

A search for "DNA reading" on Google Scholar gives ten pages of search results, because DNA reading is a real thing. A search for "synapse reading" on Google Scholar produces only one page of six results. One of these results does not refer to synapse reading; another result is in a foreign language; and the other four results do not refer to a reading of synapses in the human body, but merely refer to something going on in computer  systems in which parts of the system are being inappropriately called "synapses."  We get results so weak because "synapse reading" is not a real thing.  A search for "dendritic spine reading" on Google Scholar gives zero results. 

A Mind Is a Stable Unity, But a Brain Is Not

Having lived in this world for quite a few decades, I am more impressed than ever by the unity and stability of the human mind. I think back on several decades of my life and I recall a great unity of my  self. There have been gradual changes in my opinions slowly caused by things I have learned more and more about, and also things I have experienced. But this has all felt very much a gradual change in a single mind. Never once did I ever feel that I was in some sense a different person than the person I was a day ago or a week ago. 

So it is for the average person. There may be rare mental illnesses that involve something like a split personality, but for almost all of us nothing like that occurs. Human beliefs are remarkably stable, often to the point of stubbornness. The stability and unity of the human mind comes into play when trying to get people to pay attention to a blog site like this one. I have on this site very many arguments and very much evidence contradicting the claim that the brain is the source of the human mind. But there are so many people who refuse to examine such arguments and evidence. It seems that there are so many people in their fifties and sixties and seventies who keep believing decade after decade what they were told in college, and who kind of are saying to themselves, "I've been believing this doctrine for decades, so I'm sure not going to change my mind now."  

Such inertia of belief is a difficulty for someone like myself trying to challenge old dogmas. But at least such inertia helps show the reality of what I am arguing for at this particular moment: that human minds are remarkably stable things, and typically show very great stability and unity over decades. The unity of the human mind is something we take for granted, because it has been such a stable feature of our lives, as stable as the feature of vision or hearing. But with some imagination, we can imagine human life as a very different affair. 

For example, people might flip-flop around in their political views from one month to the next. People might change their views or religion from one month to the next, one month being an atheist, the next month being a Christian, and the next month being a Buddhist. Or people might always be switching the objects of their affection from week to week, like some fickle ever-changing Lothario who switches his beloved four times a month . In that case we would probably never have marriages lasting for decades. Or, whenever people made decisions it might usually be a very zig-zag affair, like illustrated in the diagram below:

Such is not the human reality we observe. In general, human minds are remarkably stable and unified, and the persistence of beliefs, attitudes and emotions over a period of 40 years or 50 years is very common. But in the brain do we have a physical reality matching this unity and stability? We do not.

A person examining brain scans of an adult at different decades in his life might claim to observe stability, with little change. But at the microscopic level, it is an entirely different story. Brains are made mainly of neurons and units called synapses that connect neurons. The proteins that make up neurons and synapses are not at all stable. Instead they have average lifetimes of only a few weeks. 

A scientific paper states, "Recent studies have revealed that most proteins, including synaptic proteins, have half-lives that range between 5 and 7 days (Cohen et al., 2013, Dörrbaum et al., 2018)."  The average lifetime of a protein is about twice its half-life. 

The 2018 paper here is entitled "Brain tissue plasticity: protein synthesis rates of the human brain." It tells us the astonishing fact that proteins in the human brain are replaced at a rate of 3% to 4% per day. We read this:

"Where skeletal muscle tissue has been shown to turnover at a rate of 1–2% per day, here we show that brain tissue turns over much faster at a rate of 3–4% per day. This would imply complete renewal of brain tissue proteins well within 4–5 weeks. From a physiological viewpoint this is astounding, as it provides us with a much greater framework for the capacity of brain tissue to recondition. Moreover, from a philosophical perspective these observations are even more surprising. If rapid protein turnover of brain tissue implies that all organic material is renewed, then all data internalized in that tissue are also prone to renewal. These findings spark (even) more debate on the interpretation and (long-term) storage of data in neural matter, the capacity of humans to consciously or unconsciously process data, and the (organic) basis of our own personality and ego. All of this becomes quite remarkable in light of such rapid protein turnover rates of the human brain." 

A scientific paper states this:

"Experience-dependent behavioral memories can last a lifetime, whereas even a long-lived protein or mRNA molecule has a half-life of around 24 hrs. Thus, the constituent molecules that subserve the maintenance of a memory will have completely turned over, i.e. have been broken down and resynthesized, over the course of about 1 week."

Research on the lifetime of synapse proteins is found in the June 2018 paper “Local and global influences on protein turnover in neurons and glia.” The paper starts out by noting that one earlier 2010 study found that the average half-life of brain proteins was about 9 days, and that a 2013 study found that the average half-life of brain proteins was about 5 days. The study then notes in Figure 3 that the average half-life of a synapse protein is only about 5 days, and that all of the main types of brain proteins (such as nucleus, mitochondrion, etc.) have half-lives of 15 days or less.  The 2018 study here precisely measured the lifetimes of more than 3000 brain proteins from all over the brain, and found not a single one with a lifetime of more than 75 days (figure 2 shows the average protein lifetime was only 11 days). 

The paper here states, "Experiments indicate in absence of activity average life times ranging from minutes for immature synapses to two months for mature ones with large weights."

 A neuron in the brain may be compared to some house held by a remodeling enthusiast who keeps tearing down rooms and replacing them with different rooms. The synapses in the brain may be compared to something even more unstable.  The average width of a synapse (only about 500 nanometers) is about 1000 times less than the average width of a neuron. Given how small synapses are (1000 times less wide than neurons), and given the very rapid turnover rate of synapse proteins (which have average lifetimes of a few weeks or less), it is very unlikely that any particular synapse lasts for years.  

There is another way in which the brain fails to physically qualify as a stable unity. Neurons in the brain are connected by dendrites and synapses, and the connection is not a continuous material connection. Every synapse has a physical gap. Below is a  schematic diagram of a synaptic gap:

The number of these synaptic clefts (also called synaptic gaps) in the brain is enormous. It has been estimated that the human brain has about 90 billion neurons, and about 100 trillion synapses. So there are something like 1000 synapses for every neuron. Each one of these synapses is a break in the physical unity of the brain. 

The brain isn't like a continent. It's more like some huge archipelago, consisting of countless little islands. Synapses are like the gaps between the islands in the visual below. 

Clearly the brain is not a stable unity. There is another reason for thinking that the brain is not a stable unity: the fact that the brain consists of two separate hemispheres:

It is true that there are fibers connecting these hemispheres, but the physical organization of having two hemispheres is another physical reason for thinking that the brain has no great unity. 

There are many humans that exist as stable unified minds even though there is the most dramatic physical disunity in the brain. These are the people who have brains existing as two separate hemispheres that are not connected. 

A normal human brain consists of two halves called hemispheres, which are connected by a set of fibers called the corpus callosum. However, the corpus callosum fails to develop in many people. Such a condition is called agenesis of the corpus callosum. People lacking a corpus callosum have basically two separate brains inside their skull. Does this result in two minds, as we would expect under the theory that the brain makes the mind? No, people lacking a corpus callosum have a single, unified mind.  

Agnesis means a failure of something in a developing child during a mother's pregnancy. The paper here is entitled "Outcomes Associated With Isolated Agenesis of the Corpus Callosum: A Meta-analysis." The paper distinguishes between what it calls "cACC" and "pACC," defining cACC as complete agenesis of the corpus callosum (in other words, the total failure of the corpus callosum to appear) and defining pACC as partial aegnesis of the corpus callosum (partial  failure of the corpus callosum to appear). The paper gives us these statistics, telling us that in only a relatively small minority of cases of a complete congenital absence of the corpus callosum are there cognitive problems:

"In cACC, chromosomal anomalies occurred in 4.81% (95% confidence interval [CI], 2.2–8.4) of the cases. Gross and fine motor control were abnormal in 4.40% (95% CI, 0.6–11.3) and 10.98% (95% CI, 4.1–20.6) of the cases, respectively, whereas 6.80% (95% CI, 1.7–14.9) presented with epilepsy. Abnormal cognitive status occurred in 15.16% (95% CI, 6.9–25.9) of cases. In partial ACC, the rate of chromosomal anomalies was 7.45% (95% CI, 2.0–15.9). Fine motor control was affected in 11.74% (95% CI, 0.9–32.1) of the cases, and 16.11% (95% CI, 2.5–38.2) presented with epilepsy. Cognitive status was affected in 17.25% (95% CI, 3.0–39.7) of cases."

So in only about 16% of the subjects with a complete lack of a corpus callosum was there an abnormal cognitive status. These cACC (complete agenesis of the corpus callosum) people were basically people with two separate brains in their skulls. But most of them apparently had normal unified minds, since the paper says that only 15% of them had an abnormal cognitive status. 

Below is a quote from a book written by a medical doctor:

"Case I. — Dr. Alexander Bruce reports a man of ordinary intelligence and good character, and who, for thirteen years, did the work of a porter with perfect satisfaction, and exhibited no notable peculiarities. Yet in this man the corpus callosum was completely absent (23).

Case II. — Malinverni reports a soldier, aged 30 years, of ordinary intelligence, but with a slight tendency to melancholia, who had complete absence of the corpus callosum (24).

Case III. — Eichler reports a laborer, 43 years of age, married, diligent and capable, a good husband, sober and quiet, and could read and write, yet he had no corpus callosum, and had other important malformations of the brain (25)."

We have three cases of people with no corpus callosum, meaning that they had two separated hemispheres of the brain. But in each case their mind seemed normal. 

Sometimes to prevent seizures, the entire corpus callosum is surgically severed. This is sometimes called a split brain operation. The operation leaves patients with a single unified self. Insinuations to the contrary sometimes made by materialists are an example of severe deception. 

Physician Michael Egnor states the following about Sperry's research:

"The neuroscientist Roger Sperry studied scores of split-brain patients. He found, surprisingly, that in ordinary life the patients showed little effect. Each patient was still one person. The intellect and will – the capacity to have abstract thought and to choose – remained unified. Only by meticulous testing could Sperry find any differences: their perceptions were altered by the surgery. Sensations – elicited by touch or vision – could be presented to one hemisphere of the brain, and not be experienced in the other hemisphere. Speech production is associated with the left hemisphere of the brain; patients could not name an object presented to the right hemisphere (via the left visual field). Yet they could point to the object with their left hand (which is controlled by the right hemisphere). The most remarkable result of Sperry’s Nobel Prize­–winning work was that the person’s intellect and will – what we might call the soul – remained undivided. The brain can be cut in half, but the intellect and will cannot. The intellect and will are metaphysically simple."

The actual facts about split-brain surgery are related here by a surgeon who has performed such an operation. He states this about split-brain patients:

"After the surgery they are unaffected in everyday life, except for the diminished seizures. They are one person after the surgery, as they were before."

The surgeon states: "In a rational scientific community in which evidence and reason held sway, split-brain surgery would be hailed as compelling evidence for dualism and the immateriality of the intellect and will."