A Brain Would Never Know Where to Read or Write a Memory

There was never any observation that forced scientists to start claiming that human memories are stored in brains. Scientists simply started gradually claiming such a thing, and the idea spread to the masses through a process of social contagion. 

There is no robust evidence that memories are stored in brains, but every now-and-then the press claims that some scientists have done something they could only do if memories were stored in brains. Maybe a claim is made that memories were erased from a brain, or maybe a claim is made that memories were implanted in a brain, or maybe a claim is made that memories were transferred from one brain to another.  It will inevitably be true that if you examine the research in detail, you will find that no robust evidence has been produced for any such thing. Such research suffers from the types of flaws discussed here. 

Given that there are many thousands of neuroscientists funded with so many hundreds of millions of dollars of research money, we should expect that exactly such reports would occasionally appear, even if memories are not stored in brains. In considering matters such as these, I like to remember a particular rule:

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

For example, if there were a group of 40,000 researchers who were believers in Bigfoot creatures, and such a group were to each year receive hundreds of millions of dollars in funding for their research, we should then expect to occasionally get superficially persuasive evidence in support of the existence of Bigfoot creatures, even if they don't exist. 

Sometimes an idea may seem fairly believable when it is painted in broad brushstrokes, but we may recognize the idea as being untenable once we start to examine the idea in detail. When a small child loses a tooth, her mother may tell her the story of the Tooth Fairy. “Just place the tooth under your pillow,” says the mother, assuring the child that when she wakes up there will be some cash under her pillow and that the tooth will be gone, because of the action of the Tooth Fairy. The next morning the child will probably be woken up by her mother, who will report finding some cash under the pillow. The story of the Tooth Fairy doesn't seem too unbelievable, unless the child subjects the story to detailed scrutiny. For example, she might ask: how could the Tooth Fairy ever have known that I had lost a tooth? Or she might ask: how could the Tooth Fairy ever have known where I lived, or removed the tooth and placed the money, without waking me up? After such scrutiny the child may realize that the mother probably just removed the tooth and put the money under the pillow when she woke up the child .

Like the story of the Tooth Fairy, the story that memories are stored in brains does not sound very unreasonable if we hear the claim painted in broad brushstrokes. It is when we start to subject this claim to detailed scrutiny that all types of credibility problems arise.

Let us consider two of these credibility problems: that a brain would never exactly where to read a memory, and that a brain would never know exactly where to write a memory.

Problem #1: A Brain Would Never Know Exactly Where to Read a Memory

One of the worst problems associated with the idea that a brain stores memories is what I call the navigation problem. The navigation problem is the problem that if a memory or some particular piece of knowledge was stored in your brain, your brain would never know where exactly to read that exact memory.

Let's consider an example. You are in school, and you come to a test question asking about some particular human, perhaps a scientist or a general or the leader of a country. You then have to recall what you know about that person. Under the theory that our brains store memories, such information would presumably be stored in some exact tiny spot in your brain. But for you to answer the question using the brain to retrieve a memory, your brain would presumably have to know the exact tiny spot where to read that information. How could the brain possibly know where that exact spot was, so that you instantly recall the memory?

I can imagine an extraterrestrial organism for which such a thing would be easy. It might work like this. The organism might have memory addresses, a position location system with numerical identifiers for each of the little storage locations (comparable to post office boxes in a gigantic post office). So when the organism formed a new memory, it might put that memory into some numbered storage location (for example, memory slot #822,235). Also, when the organism formed a new memory, it would always be associating these memory addresses with particular names, facts, and faces. So, for example, if the organism formed a new memory that Jokonto was the ruler of Zunando, then it would always remember a particular number (such as #532,233) that it would associate with the name Jokonto. Then when the organism heard the name Jokonto, it would remember that memory address and read the information from exactly that tiny little spot in its brain (memory slot #532,233 in this example).

But nothing like this can be occurring in the human brain. Particular neurons in the brain are not addressable. There is no position location system that could possibly be used by the brain to identify the exact tiny location of a stored memory. Also, humans do not at all remember any numbers associated with a storage location in the brain. I may learn the fact that George Patton was a skilled general during World War II, but I do not at all learn any “brain location coordinate” or location address that I associate with the name of George Patton, some neural location number that I could use to instantly retrieve the exact location of the information that I had learned about George Patton.

So if a memory or learned information is stored in some exact spot of the brain, how could your brain ever instantly find that exact spot? It seems that it could never do this. The brain would never know the exact spot to read a particular memory.

You do not at all get around this difficulty by suggesting the idea that a memory or a piece of learned information is scattered in multiple locations across the brain. The difficulty is explaining instantaneous recall. If a brain has to search scattered storage locations in the brain, that would not be any easier than finding a single storage location. We would then have the same problem: how is it that those exact locations can instantly be found? Similarly, if  a family is somewhere in New York City, and you don't know their address, you won't be able to find the family very quickly; and it's not going to be any easier if the family is scattered across three different apartments.

You also do not at all get around this difficulty by suggesting the idea that the brain reads all of its information each time a memory is retrieved. For one thing, such an idea does not correspond to human experience. If I hear a name, I recall only what I have learned about that name, and do not at all have some experience of recalling or reading some huge amount of information. Moreover, the idea of the brain reading all of its stored information (rather than one tiny spot) just worsens the problem of explaining how instantaneous recall can occur. Instantaneous recall could never happen if a brain was reading all of a large amount of information stored in it, or even a tenth of such information. 

Problem #2: A Brain Would Never Know Where to Write a Memory

Now let us consider a separate problem regarding the idea that brains store memories: the problem that a brain could apparently never derive an exact suitable specific location at which a new memory should be written.

With certain types of systems, there is no problem about where to write a new piece of information. Consider a diary. A diary typically consists of dated pages. So it's always obvious where you should be writing when you make a diary entry: in the page that has the name of today's date. It is also rather obvious in a student's notebook where new information should be written: at the end of the last place where something was written.

But a brain is not at all like a diary or a notebook. There are no date-marked places to put information acquired on some particular date. And given the organization of the brain, there is nothing like some place corresponding to the first blank page of a notebook. So, if a brain were to be writing some new information acquired on a particular day, how could the brain figure out or derive some appropriate position to write at?

We will not get any insight into this question by considering how a computer stores data. Imagine I open an application, and write some text. I then try to save my information as a particular file. How does the computer figure out where on the computer to store this information? What seems to happen is that the software application uses the computer's operating system to save the file. The operating system is a core set of software routines used for common tasks such as saving files. If we were to delve into the software code of the operating system, we would probably find that the operating system code searches for a random block of free data on the hard drive, a block with enough space to store the data.

For example, suppose I open the “Notepad” application, and type 100 words. When I choose File/Save from the menu, the application calls some software (probably operating system software) that looks for a random position on the disk with enough space to write 100 words. Random selection is very easy for a computer (for example, it's easy for some sofware routine to pick a random number between 1 and 100).

Here is the type of algorithm that an operating system might use to save data at a random free location:

1. Pick a random position on the disk.
   
2. Scan ahead X bytes to make sure that the next X bytes are free space on which nothing is written (where X is the amount of data to write).
   
3. If the next X bytes are free disk space, write the data to be written at the random position.
   
4. If any of the next X bytes are not free disk space, go back to step (1).
   

Can we imagine that something like this goes on in the brain, even though we have no mental experience of any such logic or calculation going on when we form a new memory? It does not seem that something like this could be occurring in the brain. The brain has nothing like the operating system in a computer. A brain cannot secretly be doing logic like the logic above to determine where to write a memory.

We may consider the simple matter of picking a random position in the brain to write a memory. For a conscious agent, it is very easy to pick a random position. But it would seem to be impossible for a brain to pick a random position in itself without any conscious choice being made by a mind.

There are certain physical arrangements that can kind of guarantee a random positioning effect. For example, if I throw a small ball on a large grate covering a hole, such an arrangement will make it likely that the ball will fall through one of the holes in the grate, with the ball going through a random hole. But there seems to be no physical arrangement in the brain by which some random position in it could be selected as the place to write a memory.

One possibility is the possibility of a cursor. In a word processing document, a cursor is blinking position marker indicating the current writing position. We can imagine something similar in a brain. There could be something like a “moveable write unit.” When a memory is stored using the write unit, the write unit could write wherever in the brain it was located. The write unit could move along as it wrote. Under such a system, there would be no need for a brain to be selecting a random position to write at. The brain would simply write at wherever brain position the write cursor was located at.

However, there is no sign of such a cursor or movable write unit in the brain. Other than electricity and chemicals and blood moving around in the brain, there are no moving parts in the brain. Electricity and chemicals are evenly distributed in the brain, and there is no concentration of electricity or chemicals that could be anything like a memory cursor or a moving write unit. The human brain bears no resemblance to a system for storing a particular memory in one specific spot. Similarly, the human body bears no resemblance to a system for storing the nutrients from a meal in only one specific spot of the body. 

A scientist may claim that when some new memory is acquired, that memory is stored in some exact tiny spot of the brain. But such a person could never give a credible answer to the question: why would such a memory have been stored in that exact tiny spot rather than any of a million other tiny locations in the brain?

Faced with such difficulties, someone may throw up his hands and say, "There must be some way by which some particular spot in the brain becomes the current spot where you store what you are learning right now." To this I say: no, there isn't any such thing. The difficulties I mention are only two of a host of prohibitive difficulties involved in the idea of a brain storing a memory. Others discussed at great length here include the lack of any known information reading mechanism in a brain, the lack of any known information writing mechanism in a brain, the complete lack of any credible theory by which conceptual and episodic information could be translated into neural states or synapse states, and the lack of any credible theory of how memories could be stored in a brain for decades given high molecular turnover such as the very rapid protein turnoever in synapses.  The way to overcome such difficulties is to abandon the never-proven claim that memories are stored in brains, and to move to the idea that memory must be a spiritual facility.  

The Seven Sins of “Memory Engram” Experiments

There are some very good reasons for thinking that long-term memories cannot be stored in brains, which include:

• the impossibility of credibly explaining how the instantaneous recall of some obscure and rarely accessed piece of information could occur as a neural effect, in a brain that is without any indexing system and subject to a variety of severe signal slowing effects;
  
• the impossibility of explaining how reliable accurate recall could occur in a brain subject to many types of severe noise effects;
• the short lifetimes of proteins in synapses, the place where scientists most often claim our memories are stored;
• the lack of any credible theory explaining how memories could be translated into neural states;
• the complete failure to ever find any brain cells containing any encoded information in neurons or synapses other than the genetic information in DNA;
• the lack of any known read or write mechanism in a brain.

But scientists occasionally produce research papers trying to persuade us that memories are stored in a brain, in cells that are called "engram cells." In this post, I will discuss why such papers are not good examples of experimental science, and do not provide any real evidence that a memory was stored in a brain. I will discuss seven problems that we often see in such science papers. The "sins" I refer to are merely methodological sins rather than moral sins. 

Sin #1: assuming or acting as if a memory is stored in some exact speck-sized spot of a brain without any adequate basis for such a “shot in the dark” assumption.

Scientists never have a good basis for believing that a particular memory is stored in some exact tiny spot of the brain. But a memory experiment will often involve some assumption that a memory is stored in one exact spot of the brain (such as some exact spot of a cubic millimeter in width). For example, an experimental study may reach some conclusion (based on inadequate evidence) about a memory being stored in some exact tiny spot of the brain, and then attempt to reactivate that memory by electrically or optogenetically stimulating that exact tiny spot.

The type of reasoning that is used to justify such a “shot in the dark” assumption is invariably dubious. For example, an experiment may observe parts of a brain of an animal that is acquiring some memory, and look for some area that is “preferentially activated.” But such a technique is as unreliable as reading tea leaves. When brains are examined during learning activities, brain regions (outside of the visual cortex) do not actually show more than a half of 1% signal variation. There is never any strong signal allowing anyone to be able to say with even a 25% likelihood that some exact tiny part of the brain is where a memory is stored. If a scientist picks some tiny spot of the brain based on “preferential activation” criteria, it is very likely that he has not picked the correct location of a memory, even under the assumption that memories are stored in brains. Series of brains scans do not show that some particular tiny spot of the brain tends to repeatedly activate to a greater degree when some particular memory is recalled. 

Sin #2: Either a lack of a blinding protocol, or no detailed discussion of how an effective technique for blinding was achieved.

Randomization and blinding techniques are a very important scientific technique for avoiding experimenter bias. For example, what is called the “gold standard” in experimental drug studies is a type of study called a double-blind, randomized experiment. In such a study, both the doctors or scientific staff handing out pills and the subjects taking the pills do not know whether the pills are the medicine being tested or a placebo with no effect.

If similar randomization and blinding techniques are not used in a memory experiment, there will be a high chance of experimenter bias. For example, let's suppose a scientist looks for memory behavior effects in two groups of animals, the first being a control group having no stimulus designed to affect memory, and the second group having a stimulus designed to affect memory. If the scientist knows which group is which when analyzing the behavior of the animals, he will be more likely to judge the animal's behavior in a biased way, so that the desired result is recorded.

A memory experiment can be very carefully designed to achieve this blind randomization ideal that minimizes the chance of experimenter bias. But such a thing is usually not done in memory experiments purporting to show evidence of a brain storage of memories. Scientists working for drug trials are very good about carefully designing experiments to meet the ideal of blind randomization, because they know the FDA will review their work very carefully, rejecting the drug for approval if the best experimental techniques were not used. But neuroscientists have no such incentive for experimental rigor.

Even in studies where some mention is made of a blinding protocol, there is very rarely any discussion of how an effective protocol was achieved. When dealing with small groups of animals, it is all too easy for a blinding protocol to be ineffective and worthless. For example, let us suppose there is one group of 10 mice that have something done to their brains, and some other control group that has no such done thing. Both may be subjected to a stimulus, and their “freezing behavior” may be judged. The scientists judging such a thing may be supposedly “blind” to which experimental group is being tested. But if a scientist is able to recognize any physical characteristic of one of the mice, he may actually know which group the mouse belongs to. So it is very easy for a supposed blinding protocol to be ineffective and worthless. What is needed to have confidence in such studies is not a mere mention of a blinding protocol, but a detailed discussion of exactly how an effective blinding protocol was achieved. We almost never get such a thing in memory experiments. The minority of them that refer to a blinding protocol almost never discuss in detail how an effective blinding protocol was achieved, one that really prevented scientists from knowing something that might have biased their judgments. 

For an experiment that judges "freezing behavior" in rodents, an effective blinding protocol would be one in which such freezing was judged by a person who never previously saw the rodents being tested. Such a protocol would guarantee that there would be no recognition of whether the animals were in an experimental group or a control group. But in "memory engram" papers we never read that such a thing was done.  To achieve an effective blinding protocol, it is not enough to use automated software for judging freezing, for such software can achieve biased results if it is run by an experimenter who knows whether or not an animal was in a control group. 

Sin #3: inadequate sample sizes, and a failure to do a sample size calculation to determine how large a sample size to test with.

Under ideal practice, as part of designing an experiment a scientist is supposed to perform what is called a sample size calculation. This is a calculation that is supposed to show how many subjects to use per study group to provide adequate evidence for the hypothesis being tested. Sample size calculations are included in rigorous experiments such as experimental drug trials.

The PLOS paper here reported that only one of the 410 memory-related neuroscience papers it studied had such a calculation. The PLOS paper reported that in order to achieve a moderately convincing statistical power of .80, an experiment typically needs to have 15 animals per group; but only 12% of the experiments had that many animals per group. Referring to statistical power (a measure of how likely a result is to be real and not a false alarm), the PLOS paper states, “no correlation was observed between textual descriptions of results and power.” In plain English, that means that there's a whole lot of BS flying around when scientists describe their memory experiments, and that countless cases of very weak evidence have been described by scientists as if they were strong evidence.

The paper above seems to suggest that 15 animals per study group is needed.  But In her post “Why Most Published Neuroscience Findings Are False,” Kelly Zalocusky PhD calculates (using Ioannidis’s data) that the median effect size of neuroscience studies is about .51. She then states the following, talking about statistical power:

"To get a power of 0.2, with an effect size of 0.51, the sample size needs to be 12 per group. This fits well with my intuition of sample sizes in (behavioral) neuroscience, and might actually be a little generous. To bump our power up to 0.5, we would need an n of 31 per group. A power of 0.8 would require 60 per group."

So the number of animals per study group for a moderately convincing result (one with a statistical power of .80) is more than 15 (according to one source), and something like 60, according to another source.  But the vast majority of "memory engram" papers do not even use 15 animals per study group.

Sin #4: a high occurrence of low statistical significance near the minimum of .05, along with a frequent hiding of such unimpressive results, burying them outside of the main text of a paper rather than placing them in the abstract of the paper.

Another measure of how robust a research finding is the statistical significance reported in the paper. Memory research papers often have marginal statistical significance close to .05.

Nowadays you can publish a science paper claiming a discovery if you are able to report a statistical significance of only .05. But it has been argued by 72 experts that such a standard is way too loose, and that things should be changed so that a discovery can only be claimed if a statistical significance of .005 is reached, which is a level ten times harder to achieve.

It should be noted that it is a big misconception that when you have a result with a statistical significance (or P-value) of .05, this means there is a probability of only .05 that the result was a false alarm and that the null hypothesis is true. This paper calls such an idea “the most pervasive and pernicious of the many misconceptions about the P value.” 

When memory-related scientific papers report unimpressive results having a statistical significance such as only .03, they often make it hard for people to see this unimpressive number. An example is the recent paper “Artificially Enhancing and Suppressing Hippocampus-Mediated Memories.”  Three of the four statistical significance levels reported were only .03, but this was not reported in the summary of the paper, and was buried in hard-to-find places in the text.

Sin #5: using presumptuous or loaded language in the paper, such as referring in the paper to the non-movement of an animal as “freezing” and referring to some supposedly "preferentially activated" cell as an "engram cell." 

Papers claiming to find evidence of memory engrams are often guilty of using presumptuous language that presupposes what they are attempting to prove. For example,  the non-movement of a rodent in an experiment is referred to by the loaded term "freezing," which suggests an animal freezing in fear, even though we have no idea whether the non-movement actually corresponds to fear.  Also, some cell that is guessed to be a site of memory storage (because of some alleged "preferential activation" that is typically no more than a fraction of 1 percent) is referred to repeatedly in the papers as an "engram cell,"  which means a memory-storage cell, even though nothing has been done to establish that the cell actually stores a memory. 

We can imagine a psychology study using similar loaded language.  The study might make hidden camera observations of people waiting at a bus stop.  Whenever the people made unpleasant expressions, such expressions would be labeled in the study as "homicidal thoughts."  The people who had slightly more of these unpleasant expressions would be categorized as "murderers."   The study might say, "We identified two murderers at the bus stop from their increased display of homicidal expressions." Of course, such ridiculously loaded, presumptuous language has no place in a scientific paper.  It is almost as bad for "memory engram" papers to be referring so casually to "engram cells" and "freezing" when neither fear nor memory storage at a specific cell has been demonstrated.  We can only wonder whether the authors of such papers were thinking something like, "If we use the phrase engram cells as much as we can, maybe people will believe we found some evidence for engram cells." 

Sin #6: failing to mention or test alternate explanations for the non-movement of an animal (called “freezing”), explanations that have nothing to do with memory recall.

A large fraction of all "memory engram" papers hinge on judgments that some rodent engaged in increased "freezing behavior,"  perhaps while some imagined "engram cells" were electrically or optogenetically stimulated. A science paper says that it is possible to induce freezing in rodents by stimulating a wide variety of regions. It says, "It is possible to induce freezing by activating a variety of brain areas and projections, including the hippocampus (Liu et al., 2012), lateral, basal and central amygdala (Ciocchi et al., 2010); Johansen et al., 2010; Gore et al., 2015a), periaqueductal gray (Tovote et al., 2016), motor and primary sensory cortices (Kass et al., 2013), prefrontal projections (Rajasethupathy et al., 2015) and retrosplenial cortex (Cowansage et al., 2014).” 

But we are not informed of such a reality in quite a few papers claiming to supply evidence for an engram. In such studies typically a rodent will be trained to fear some stimulus. Then some part of the rodent's brain will be stimulated when the stimulus is not present. If the rodent is nonmoving (described as "freezing") more often than a rodent whose brain is not being stimulated, this is hailed as evidence that the fearful memory is being recalled by stimulating some part of the brain.  But it is no such thing. For we have no idea whether the increased freezing or non-movement is being produced merely by the brain stimulation, without any fear memory, as so often occurs when different parts of the brain are stimulated.

If a scientist thinks that some tiny part of a brain stores a memory, there is an easy way to test whether there is something special about that part of the brain. The scientists could do the "stimulate cells and test fear" kind of test on multiple parts of the brain, only one of which was the area where the scientist thought the memory was stored. The results could then be compared, to see whether stimulating the imagined "engram cells" produced a higher level of freezing than stimulating other random cells in the brain. Such a test is rarely done. 

Sin #7: a dependency on arbitrarily analyzed brain scans or an uncorroborated judgment of "freezing behavior" which is not a reliable way of measuring fear.

A crucial element of a typical "memory engram" science paper is a judgment of what degree of "freezing behavior" a rodent displayed.  The papers typically equate non-movement with fear coming from recall of a painful stimulus. This doesn't make much sense. Many times in my life I saw a house mouse that caused me or someone else to shreik, and I never once saw a mouse freeze. Instead, they seem invariably to flee rather than to freeze. So what sense does it make to assume that the degree of non-movement ("freezing") of a rodent should be interpreted as a measurement of fear?  Moreover, judgments of the degree of "freezing behavior" in mice are too subjective and unreliable. 

Fear causes a sudden increase in heart rate in rodents, so measuring a rodent's heart rate is a simple and reliable way of corroborating a manual judgment that a rodent has engaged in increased "freezing behavior." A scientific study showed that heart rates of rodents dramatically shoot up instantly from 500 beats per minute to 700 beats per minute when the rodent is subjected to the fear-inducing stimuli of an air puff or a platform shaking. But rodent heart rate measurements seem to be never used in "memory engram" experiments. Why are the researchers relying on unreliable judgments of "freezing behavior" rather than a far-more-reliable measurement of heart rate, when determining whether fear is produced by recall? In this sense, it's as if the researchers wanted to follow a technique that would give them the highest chance of getting their papers published, rather than using a technique that would give them the most reliable answer as to whether a mouse is feeling fear. 

Another crucial element of many "memory engram" science papers is analysis of brain scans.  But there are 1001 ways to analyze the data from a particular brain scan.  Such flexibility almost allows a researcher to find whatever "preferential activation" result he is hoping to find.  

Page 68 of this paper discusses how brain scan analysis involves all kinds of arbitrary steps:

"The time series of voxel changes may be motion-corrected, coregistered, transformed to match a prototypical brain, resampled, detrended, normalized, smoothed, trimmed (temporally or spatially)...Furthermore, each of these steps can be done in a number of ways, each with many free parameters that experimenters set, often arbitrarily....The wholebrain analysis is often the first step in defining a region of interest in which the analyses may include exploration of time courses, voxelwise correlations, classification using support vector machines or other machine learning methods, across-subject correlations, and so on. Any one of these analyses requires making crucial decisions that determine the soundness of the conclusions."

The problem is that there is no standard way of doing such things. Each study arbitrarily uses some particular technique, and it is usually true that the results would have been much different if some other brain scan analysis technique had been used. 

Examples of Such Shortcomings

Let us look at a recent paper that claimed evidence for memory engrams. The paper stated, “Several studies have identified engram cells for different memories in many brain regions including the hippocampus (Liu et al., 2012; Ohkawa et al., 2015; Roy et al., 2016), amygdala (Han et al., 2009; Redondo et al., 2014), retrosplenial cortex (Cowansage et al., 2014), and prefrontal cortex (Kitamura et al., 2017).” But the close examination below will show that none of these studies are robust evidence for memory engrams in the brain. 

Let's take a look at some of these studies. The Kitamura study claimed to have “identified engram cells” in the prefrontal cortex is the study “Engrams and circuits crucial for systems consolidation of a memory.”  In Figure 1 (containing multiple graphs), we learn that the number of animals used in different study groups or experimental activities were 10, 10, 8, 10, 10, 12, 8, and 8, for an average of 9.5. In Figure 3 (also containing multiple subgraphs), we have even smaller numbers. The numbers of animals mentioned in that figure are 4, 4, 5, 5, 5, 10, 8, 5, 6, 5 and 5. None of these numbers are anything like what would be needed for a moderately convincing result, which would be a minimum of 15 animals per study group. So the study is very guilty of Sin #3. The study is also guilty of Sin #2, because no detailed description is given of an effective blinding protocol. The study is also guilty of Sin #4, because Figure 3 lists two statistical significance values of “< 0.05” which is the least impressive result you can get published nowadays. Studies reaching a statistical significance of less than 0.01 will always report such a result as “< 0.01” rather than “<0.05.”  The study is also guilty of Sin #7, because it relies on judgments of freezing behavior of rodents, which were not corroborated by something such as heart rate measurements. 

The Liu study claimed to have “identified engram cells” in the hippocampus of the brain is the study “Optogenetic stimulation of a hippocampal engram activates fear memory recall.” We see in Figure 3 that inadequate sample sizes were used. The number of animals listed in that figure (during different parts of the experiments) are 12, 12, 12, 5, and 6, for an average of 9.4. That is not anything like what would be needed for a moderately convincing result, which would be a minimum of 15 animals per study group. So the study is  guilty of Sin #3. The study is also guilty of Sin #7. The experiment relied crucially on judgments of fear produced by manual assessments of freezing behavior, which were not corroborated by any other technique such as heart-rate measurement. The study does not describe in detail any effective blinding protocol, so it is also guilty of Sin #2. The study is also guilty of Sin #6. The study involved stimulating certain cells in the brains of mice, with something called optogenetic stimulation. The authors have assumed that when mice freeze after stimulation, that this is a sign that they are recalling some fear memory stored in the part of the brain being stimulated. What the authors neglect to tell us is that stimulation of quite a few regions of a rodent brain will produce freezing behavior. So there is actually no reason for assuming that a fear memory is being recalled when the stimulation occurs. 

The Ohkawa study claimed to have “ identified engram cells” in the hippocampus of the brain is the study “Artificial Association of Pre-stored Information to Generate a Qualitatively New Memory.” In Figure 3 we learn that the animal study groups had a size of about 10 or 12, and in Figure 4 we learn that the animal study groups used were as small as 6 or 8 animals. So the study is guilty of Sin #3. Because the paper used a “zap their brains and look for freezing” approach, without discussing or testing alternate explanations for freezing behavior having nothing to do with memory, the Ohkawa study is also guilty of Sin #6. Judgment of fear is crucial to the experimental results, and it was done purely by judging "freezing behavior," without measurement of heart rate.  So the study is also guilty of Sin #7. This particular study has a few skimpy phrases which claims to have used a blinding protocol: “Freezing counting experiments were conducted double blind to experimental group.” But no detailed discussion is made of how an effective blinding protocol was achieved, so the study is also guilty of Sin #2.

The Roy study claimed to have “identified engram cells” in the hippocampus of the brain is the study "Memory retrieval by activating engram cells in mouse models of early Alzheimer’s disease."  Looking at Figure 1, we see that the study groups used sometimes consisted of only 3 or 4 animals, which is a joke from any kind of statistical power standpoint. Looking at Figure 3, we see the same type of problem. The text mentions study groups of only "3 mice per group," "4 mice per group," and "9 mice per group,"  and "10 mice per group."   So the study is guilty of Sin #3. Although a blinding protocol is mentioned in the skimpiest language,  no detailed discussion is made of how an effective blinding protocol was achieved, so the study is also guilty of Sin #2.  Some of the results reported have a statistical significance of only "<.05," so the study is guilty of Sin #4. 

The Han study (also available here) claimed to have “identified engram cells” in the amygdala is the study "Selective Erasure of a Fear Memory." In Figure 1 we see a larger-than average sample size was used for two groups (17 and 24), but that a way-too-small sample size of only 4 was used for the corresponding control group. You need a sufficiently high number of animals in all study groups, including the control group, for a reliable result.  The same figure tells us that in another experiment the number of animals in the study group were only 5 or 6, which is way too small. Figure 3 tells us that in other experiments only 8 or 9 mice were used, and Figure 4 tells us that in other experiments only 5 or 6 mice were used. So this paper is guilty of Sin #3. No mention is made in the paper of any blinding protocol, so this paper is guilty of Sin #2. Figure 4 refers to two results with a borderline statistical significance of only "< 0.05," so this paper is also guilty of Sin #4.  The paper relies heavily on judgments of fear in rodents, but these were uncorroborated judgments based on "freezing behavior," without any measure of heart rate to corroborate such judgments. So the paper is also guilty of Sin #7. 

The Redondo study claimed to have “identified engram cells” in the amygdala is the study "Bidirectional switch of the valence associated with a hippocampal contextual memory engram."  We see 5 or 6 results reported with a borderline statistical significance of only "< 0.05," so this paper is  guilty of Sin #4. No detailed description is given of how an effective blinding protocol was achieved, and only the skimpiest mention is made of blinding, so this paper is guilty of Sin #2.  The study used only "freezing behavior" to try to measure fear, without corroborating such a thing by measuring heart rates.  So the paper was guilty of Sin #7.  The study involved stimulating certain cells in the brains of mice, with something called optogenetic stimulation. The authors have assumed that when mice freeze after stimulation, that this is a sign that they are recalling some fear memory stored in the part the brain being stimulated. What the authors neglect to tell us is that stimulation of quite a few regions of a rodent brain will produce freezing behavior. So there is actually no reason for assuming that a fear memory is being recalled when the stimulation occurs.  So the study is also guilty of Sin #6. 

The Cowansage study claimed to have “identified engram cells” in the retrosplinial cortex of the brain is the study "Direct Reactivation of a Coherent Neocortical Memory of Context." Figure 2 tells us that only 12 mice were used for one experiment. Figure 4 tells us that only 3 and 5 animals were used for other experiments. So this paper is guilty of Sin #3. No detailed description is given of how an effective blinding protocol was achieved, and only the skimpiest mention is made of blinding, so this paper is guilty of Sin #2.    It's a paper using the same old "zap rodent brains and look for some freezing behavior" methodology, without explaining why such results can occur for reasons having nothing to do with memory recall. So the study is guilty of Sin #6. Some of the results reported have a statistical significance of only "<.05," so the study is guilty of Sin #4. 

So I have examined each of the papers that were claimed as evidence for memory traces or engrams in the brain. Serious problems have been found in every one of them.  Not a single one of the studies made a detailed description of how an effective blinding protocol was executed. All of the studies were guilty of Sin #7.  Not a single one of the studies makes a claim to have followed some standardized method of brain scan analysis. Whenever there are brain scans we can say that the experiments merely chose one of 101 possible ways to analyze brain scan data. Not a single one of the studies has corroborated "freezing behavior" judgments by measuring heart rates of rodents to determine whether the animals suddenly became afraid. But all of the studies had a depenency on either brain scanning, uncorroborated freezing behavior judgments, or both. The studies all used sample sizes far too low to get a reliable result (although one of them used a decent sample size to get part of its results). 

The papers I have discussed are full of problems, and do not provide robust evidence for any storage of memories in animal brains. There is no robust evidence that memories are stored in the brains of any animal, and no robust evidence that any such thing as an "engram cell" exists. 

The latest press report of a "memory wonder" produced by scientists is a claim that scientists implanted memories in the brains of songbirds. For example, The Scientist magazine has an article entitled, "Researchers Implant Memories in Zebra Finch Brains."  If you read the scientific paper in the journal Science, you will find that one of the crucial study groups used consisted of only seven birds, which is less that half of the fifteen animals per study group that is recommended for a moderately convincing result. The relevant scientific study is hidden behind a paywall of the journal Science.  But by reading the article in The Scientist, we can get enough information to have the strongest suspicion that the headline is an unjustified brag. 

Of course, the scientists didn't actually implant musical notes into the brains of birds.  Nothing of the sort could ever occur, because no one has the slightest idea of how learned or episodic information could ever be represented as neural states. The scientists merely gave little bursts of energy into the brains of some birds. The scientists claimed that the birds who got shorter bursts of energy tended to sing shorter songs. "When these finches grew up, they sang adult courtship songs that corresponded to the duration of light they’d received," the story tells us.  Of course, it would be not very improbable that such a mere "duration similarity" would occur by chance.  

It is very absurd to be describing such a mere "duration similarity" as a memory implant.  It was not at all true that the birds sung some melody that had been artifically implanted in their heads.  The scientists in question have produced zero evidence that memories can be artificially implanted in animals.  From an example like this, we get the impression that our science journalists will uncritically parrot any claim of success in brain experiments with memory, no matter how glaring are the shortcomings of the relevant study. 

There Is No Good Evidence for a Neural Hallmark of Conceptual Learning or Memory Storage

If memories were stored in brains, we would expect that when a person learned something, there would be some type of physical change in the brain that could be observed, although it might be a tiny subtle thing that was hard to identify.  We can call such a thing a neural hallmark of memory. But no neural hallmark of conceptual or episodic memory has ever been observed.  

Let us imagine two different experimental subjects, either animals or humans. Imagine that the brains of both are thoroughly scanned, in an attempt to determine the exact state of their brains.  Then imagine the first subject was immobilized in a black silent room for ten hours, and the second subject experienced an intense learning experience for ten hours.  If memories are stored in brains, it should be possible to detect some change in the brain that the second subject had that the first did not. 

No test like this has ever produced good evidence of a neural hallmark of conceptual learning or knowledge acquisition.  But there have been some experiments similar to that described above, and some have claimed to have found evidence of memory formation in what are called dendritic spine differences. 

Dendritic spines are little bumps that protrude out of dendrites in the brain. We see below a schematic visual depicting 24 dendritic spines:

 Visual cropped from this paper

The idea that long-term memories are stored in dendritic spines is untenable, for two reasons. The first is that it is known that the proteins that make up dendritic spines are very short-lived, having average lifetimes of only a few weeks.  So there is nothing stable inside a dendritic spine. The second reason is that dendritic spines themselves are unstable, and they generally last for much less than two years. 

Synapses often protrude out of bump-like structures on dendrites called dendritic spines. But those spines have lifetimes of less than 2 years.  Dendritic spines last no more than about a month 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 a subgroup of dendritic spines in the cortex of mice brains (the more long-lasting subgroup) 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." A paper on dendritic spines in the neocortex says, "Spines that appear and persist are rare." While a 2009 paper tried to insinuate a link between dendritic spines and memory, its data showed how unstable dendritic spines are.  Speaking of dendritic spines in the cortex, the paper found that "most daily formed spines have an average lifetime of ~1.5 days and a small fraction have an average lifetime of ~1–2 months," and told us that the fraction of dendritic spines lasting for more than a year was less than 1 percent. A 2018 paper has a graph showing a 5-day "survival fraction" of only about 30% for dendritic spines in the cortex.  A 2014 paper found that only 3% of new spines in the cortex persist for more than 22 days. 

In the light of such facts, it is pretty ridiculous to be looking for signs of a physical hallmark of long-term memory by looking at dendritic spines, which typically have lifetimes only a thousandth as long as the maximum length of time that humans can remember things. But nonetheless some scientists have attempted to do such a thing. A few scientists have presented scientific papers showing "before and after" photos of dendritic spines, papers that try to insinuate that some physical hallmark of learning can be seen.  No one should be persuaded by such experiments,  which have glaring methodological flaws. 

Here is what we will read in a typical scientific paper describing such an experiment:

(1) We are told that there were two sets of rodents, one group that did not engage in learning, and another group that did engage in learning. 
(2) We are shown two photos of dendritic spines, microscopic little bumps that protrude from neural components called dendrites.  Each photo will show about ten of these dendritic spine bumps. One photo will be from the learning group, and one from the control group.
(3) Some captions on the photos will suggest that the learning group has more dendritic spines than the control group. 
(4) There will be some graph suggesting the same thing. 

You may realize such papers are very flawed after you consider the question: how did the scientists select these particular dendritic spines out of many millions or billions of dendritic spines in the brain of the animal being studied?  A huge number of dendritic spines appear and disappear every day in the brain of every human and rodent. So it could not at all be true that the scientists scanned the brains of their subjects, and found some special little group of ten or twenty dendritic spines that were the only ones that had changed. 

What has actually happened in such experiments is that the scientists have simply randomly or arbitrarily selected a group of about ten or a hundred dendritic spines out of millions or billions they could have selected.  Perhaps this was done in a truly random way, using some random selection technique, or perhaps the scientists scanned many dendritic spines looking for a set that would show the alleged "memory storage" effect they were trying to show.  It's usually hard to tell from the way the papers are worded how the tiny set of "study spines" was selected.  Usually there will be no explanation of why this tiny set of about 10 or 100 dendritic spines is being photographed or carefully studied, rather than any 10 or 100 others of millions or billions of dendritic spines that could have been chosen.  In one paper we are told that the set of dendritic spines photographed was a "representative sample."  But we have no idea whether such a sample is truly representative, any more than we would know that ten randomly selected New York residents on the street are "representative samples" of New York residents. 

I can give an analogy explaining how bogus and bunk such a methodology is.  Imagine your hypothesis was that your memories are stored in the flowers of Central Park. You might do an experiment with this protocol: (1) you photograph some groups of Central Park flowers the first week of April; (2) you learn a lot on the second week of April; (3) you could go back to Central Park to photograph the same groups of flowers on the third week of April. Looking for a group of flowers that would support your hypothesis, you would probably have little trouble finding a few flowers that had grown nicely during the second week of April. You could then  publish "before and after" photos of such flowers to try to back up your claim that  your memories are being stored in flowers.  This would, of course, be a completely bunk methodology.  You would have no reason for suspecting that your memories were actually stored in the particular group of flowers you had photographed. 

Similarly, the scientists who perform experiments like the one I have described have no reason for believing that any memories acquired during testing are stored in the tiny group of dendritic spines they are showing in their papers.  

There are a few studies suggesting a little bit of a neural hallmark during muscular exertion activities (such as maze training), but such studies may be showing a bit of a kind of "muscle memory" effect that should not be confused with a physical sign of conceptual learning or knowledge acquisition.  My leg muscles also increase if I do enough activities involving walking, but that does not show that memories are stored in my legs.  We know that nerves are connected to muscles, so even if a brain is not storing learned knowledge, we might expect that parts of brains related to muscle activity might bulk up a tiny bit during novel muscle activities.  But if such a "muscle memory" exists, it is not a real memory, for the hallmark of a real memory is that it can be retrieved by a motionless person. 

In 1979 a scientific paper by Huffenlocher reached these conclusions:

1. Synaptic density was constant throughout adult life (age 16 to 72 years), with a density of about 1100 million synapses per cubic millimeter.
2. There was only a slight decrease in old age, with density decreasing to about 900 million synapses per cubic millimeter.
3. “Synaptic density increased during infancy, reaching a maximum at age 1--2 years which was about 50% above the adult mean.”

So according to the paper, the density of synapses sharply decreases as you grow up, in contrast to claims that learning or knowledge acquisition produces synapse strengthening. 

Some have claimed that a hallmark of knowledge acquisition can be found in London taxi drivers. To become a London cab driver, you have to memorize a great deal of geographical information. A study followed London cab drivers for 4 years, taking MRI scans of their brains.

But the study did not find that such cab drivers have bigger brains, or brains more dense with synapses. The study has been misrepresented in some leading press organs. The National Geographic misreported the findings in a post entitled “The Bigger Brains of London Cab Drivers.” Scientific American also inaccurately told us, “Taxi Drivers' Brains Grow to Navigate London's Streets.” 

But when we actually look at a scientific paper stating the results, the paper says no such thing. The study found no notable difference outside of the hippocampus, a tiny region of the brain. Even in that area, the study says “the analysis revealed no difference in the overall volume of the hippocampi between taxi drivers and controls.” The study's unremarkable results are shown in the graph below. 

The anterior part of the left half of the hippocampus was about 25% smaller for taxi drivers (100 versus 80), but the posterior part of the right half of the hippocampus was slightly larger (about 77 versus 67).  Overall, the hippocampus of the taxi drivers was about the same as for the controls who were not taxi drivers, as we can see from the graph above, in which the dark bars have about the same area as the lighter bars. So clearly the paper provides no support for the claim that these London cab drivers had bigger brains, or brains more dense with synapses.

In this case, the carelessness of our major science news media is remarkable. They've created a “London cab drivers have bigger brains” myth that is not accurate.  The supposedly bigger part (an area of about the size of a jelly bean) is only about 1/500 of the size of the brain. Give me any two randomly chosen set of people, and give me the freedom to make comparisons of 500 parts of their brains, and I will probably be able to find some little part that differs in size by 25% or more, purely because of random variations. This is no strong evidence for anything. 

Another scientific study claimed to find evidence that people called pandits who had memorized Sanskrit scriptures had brains different from normal people.  In a Scientific American story, we have a claim which initially sounds (to the casual reader) like evidence that memorization changes the brain. A scientist says, "Numerous regions in the brains of the pandits were dramatically larger than those of controls, with over 10 percent more grey matter across both cerebral hemispheres, and substantial increases in cortical thickness." But when we take a close look at the study, we find no robust evidence for any brain change caused by memorization. 

The study is what is called a whole-brain study. This means that the authors had complete freedom to check hundreds of tiny regions of the brain, looking for any differences between their 20 pandits who memorized scriptures, and a group of 20 controls.  The problem with that is that a scientist may simply find deviations that we would expect to exist by chance in tiny little brain regions, and then cite these as evidence of a brain effect of memorization.   Note that the scientist did not claim that the brains of the pandits who memorized scriptures had 10 percent more grey matter than ordinary people. He merely claimed that in "numerous regions" there was a 10% difference.  If I take 20 random people, scan their brains, and compare them to 20 other random people whose brains I scanned, I will (purely by chance) probably be able to find quite a few little regions in which the first group had more grey matter than the second (as well as quite a few regions in which the first group had less gray matter).  In the paper, we read that these pandits who memorized scriptures "showed less GM [grey matter] than controls in a large cluster (62% of subcortical template GM) encompassing the more anterior portions of the hippocampus bilaterally and bilateral regions of the amygdala, caudate, nucleus accumbens, putamen and, thalamus."  So the study found in some regions of their brains, these pandits who memorized scriptures had less gray matter than ordinary people, and that in other regions of their brains, they had more grey matter.  That is basically what we would expect to find by chance, and provides no good evidence for anything. 

On page 23 a technical paper tells us how many subjects we would need to have when doing this kind of "whole brain" study using brain scanning:

"With a plausible population correlation of 0.5, a 1000-voxel whole-brain analysis would require 83 subjects to achieve 80% power. A sample size of 83 is five times greater than the average used in the studies we surveyed: collecting this much data in an fMRI experiment is an enormous expense that is not attempted by any except a few major collaborative networks."

How many subjects did the whole-brain analysis study of Sanskrit pandits use? Only 21.  Meaning that it used only one-fourth of the subjects needed for a moderately convincing result, using the approach used.  The results are therefore not robust evidence for anything.  See here for a fuller explanation of why the Sanskrit pandits study provides no good evidence of a neural effect of memorization. 

A certain class of studies called environmental enrichment studies compares groups of animals, one raised in an environment that is not stimulating, and another raised in an environment that is stimulating (such as one with toys and exercise wheels for rats).  It is claimed that the animals raised in the "enriched environment" may have slightly denser or larger areas in certain parts of the brain. But we have no idea whether this is caused by simply increased muscular activity rather than anything pertaining to memory. A review of the topic says, "Several studies have even suggested that physical activity is the sole contributor to the neurogenic and neurotropic effects of environmental enrichment." 

As for the claim so often made that "neurons that fire together wire together," a dogma originated by Hebb,  there is no robust evidence for this dogma of neuroscience that synapses that are more often used become stronger than synapses that are not used.  To get good evidence for this claim, a neuroscientist would need two things: (1) some method of measuring how often synapses fire, and (2) some method of measuring how much they are strengthening.  But unlike the situation with a car (which comes up with an odometer that allows you to precisely know how much it is being used), there is no way of monitoring precisely in vivo how often a neuron or synapse is firing; and it is also extraordinarily difficult to tell whether or not a synapse has strengthened during some period of time. So we don't have any adequate way of testing the Hebbian dogmas that synapses are strengthened more strongly when used more often. And since we could never tell whether a synapse strengthening was caused by mere physical activity rather than memory storage, something similar to muscles increasing in size after greater physical activity, a claimed example of synapse strengthening couldn't be cited as a neural hallmark of conceptual learning.  

A small number of studies have claimed to show evidence of synapse strengthening after learning, but fail to do that in a convincing manner. Such studies typically involve tracking a small number of synapses in some animal.  But there are billions of synapses in every mammal, and we have no way of knowing whether the small number of synapses studied had any connection with a learning experience.  We can compare such studies to a study trying to prove that flowers wilt in Central Park when the Yankees lose, by showing us pictures of a few flowers that showed such a wilting.  To prove the idea of synapse strengthening during learning, you would need to compare the total synapse strength of one group of subjects that had learning and a control group of subjects that did not. But we have no method allowing a scientist to measure the total strength of synapses in an organism. 

The 2019 study here is the latest example of an unconvincing study trying to show some evidence of memories being stored in a brain.  There are two big reasons why the study shows nothing of the sort:

(1) The study uses a technique in which animals are trained to fear some stimulus, and are then subjected to a brain "cell reactivation" that can be roughly described as a brain zapping.  The animals supposedly froze more often when this brain zapping happening, and the study interpreted this behavior as evidence of an artificially produced memory recall of a fear memory. But such a technique does nothing to show that a memory is being recalled, because it is well known that there are many parts of a mouse brain that will cause freezing behavior when artificially stimulated.  The freezing behavior is probably a result of the strange stimulus, and not actual evidence of memory recall.  If you were walking along, you would also freeze if someone turned on some brain-zapping chip implanted in your brain. 

(2) The study is using sample sizes so small that there is a very high chance of a false alarm.  The number of animals per study group was only 10 to 12. But 15 animals per study group is the minimum needed for a modestly convincing result, and a neuroscientist has stated that to get a decent statistical power of .5, animal studies should be using at least 31 animals per study group. 

The second problem is one that is epidemic in modern neuroscience.  Neuroscientists are well aware that the sample sizes typically used in neuroscience studies (the number of animals per study group) are so low that there must be a very high chance of false alarms in very many or most of their experimental studies; but they continue year after year producing such unreliable studies.  There is a "publication quota" expectation that provides a strong incentive for such professional malpractice. 

In considering matters such as these, I like to remember a particular rule:

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

We can consider an example of this rule, one involving astrology, the claim that the stars and planets exert a mysterious occult influence on the destiny of humans. Let us imagine that instead of there being merely a handful of poorly funded astrology researchers in the United States, there were instead 10,000 or more very well-funded astrology researchers, with billions of dollars in research grants to use to try to support their belief in astrology, by doing things like crunching statistics in various ways with computers.  It would then occur that we would occasionally read in the press stories presenting superficially persuasive evidence for astrology.  Such evidence probably would not stand up well to very close scrutiny, but it would be sufficient to give some talking points to astrology supporters. 

Similarly, if there was a large community of 10,000 ardent fairy researchers who were funded with billions of dollars, we would probably occasionally see superficially persuasive papers offering evidence for fairies. For example, with such an army of researchers, and so much money to spend, there might be occasional infrared heat signature studies suggesting anomalous little blobs of heat floating about that might be interpreted as fairies.  The researchers would be helped by the research rule that says, "Torture the data sufficiently, and it will confess to almost anything." 

And so it is for the 10,000 or more US neuroscientists funded with billions of dollars of research money (more than 5 billion dollars each year, according to this site).  Such scientists are able to occasionally produce studies providing superficially persuasive evidence for the dogmas the neuroscientists want to believe in, such as the idea that there is a physical hallmark of conceptual learning in the brain. Such evidence does not hold up well to very close scrutiny, but it is at least sufficient to provide some talking points for the neuroscientists.  Such evidence is actually no greater than the evidence we would expect to be produced for an untrue claim, given the "rule of well-funded and highly motivated research communities" cited above.