Neuroscientists Keep Writing Papers Bluffing Us About Memory Encoding

 " We do not yet have a systematic theory of how information is encoded in the chemical and electrical activity of neurons, how it is fused to determine behavior on short time scales, and how it is used to adapt, refine, and learn behaviors on longer time scales. " -- "BRAIN 2025: A Scientific Vision," document co-authored by many scientists (link). 

If we are to believe in the claim that brains store human memories, we must have a credible account of four things: encoding, neural storage of very old memories, the instantaneous formation of memories, and the instantaneous retrieval of memories. The theory that human memories are stored in the brain fails in regard to each of these things.

There exists no plausible theory as to how a brain could store memories lasting for 50 years, but we know humans can remember many things for that long. The most popular idea of brain memory storage claims that memories are stored in synapses, but the proteins in synapses have an average lifetime of less than two weeks, meaning such a theory falls short by a factor of 1000 when it comes to explaining memories that persist for 50 years. As for memory retrieval, there is no theory explaining how humans could possibly recall instantly things they learned many years ago, and haven't thought about in years. 

You may hear the name of some obscure historical or cultural figure you learned about decades ago, and haven't heard about or thought about since that time. You may then instantly recall something about that person. But if that memory was stored somewhere in your brain, how could you instantly find the exact little location where that memory was? Doing that (for example, instantly finding a memory in storage spot 834,220 out of 1,200,000) would be like instantly finding a needle in a mountain-sized haystack. If a brain had an indexing system, or a coordinate system, or a neuron numbering system, there might be a faint hope for explaining instantaneous memory retrieval; but the brain has no such things. As for the instantaneous formation of memories, there is no theory that can account for it in a brain. The prevailing theory that memories are stored by synapse strengthening (which would involve protein synthesis requiring minutes) fails to account for memories that humans can form instantly.

When we consider the issue of memory encoding, we find a difficulty as great as the difficulties just discussed. Encoding is supposedly some translation that occurs so that a memory can be physically stored in a brain, so that it might last for years. The problem is that human memories include incredibly diverse types of things, and we have no idea how most of these things could be stored as neural states. Consider only a few of the types of things that can be stored in a human memory:

• Memories of daily experiences, such as what you were doing on some day
• Facts you learned in school, such as the fact that Lincoln was shot at Ford's Theater
• Sequences of numbers such as your social security number
• Sequences of words, such as the dialog an actor has to recite in a play
• Sequences of musical notes, such as the notes an opera singer has to sing
• Abstract concepts that you have learned
• Memories of particular non-visual sensations such as sounds, food tastes, smells, pain, and physical pleasure
• Memories of how to do physical things, such as how to ride a bicycle
• Memories of how you felt at emotional moments of your life
• Rules and principles, such as “look both ways before crossing the street”
• Memories of visual information, such as what a particular person's face looks like

How could all of these very different types of information ever be translated into neural states so that a brain could store them?

Our neuroscientists have told us again and again that the brain does such an encoding, but there is no real evidence that any such thing takes place. What we have evidence for is merely evidence that humans remember things. If you are someone who believes that memories are physically stored in brains, then you may claim that memory encoding occurred at such and such a rate whenever you observe people learning something at such and such a rate. But merely observing evidence of learning or memory is not acquiring any actual evidence that encoding has occurred. There remains the possibility that our memories are not stored as neural states, the possibility that our repository of memory is some spiritual or psychic facility that is non-neural and non-biological.

Such a possibility should not seem remote when we consider that there is no workable theory as to how learned knowledge and experiences could be encoded so that they might be stored in a brain. No matter what theory we may create to account for the encoding of learned knowledge and episodic experience so that they can be stored in a brain, such a theory will always end up sounding ridiculous after we examine the theory in detail and consider its requirements and shortcomings. Let's look at some possibilities, and why they fail.

Theory #1: Direct writing of words and images

First, let's consider the simplest theory of encoding we can imagine – that a memory is stored in the brain so that it appears in a neural form pretty much as we see it in our minds. Under this theory, when you memorized some series of words, this would cause a sequence of microscopic little letters to become stored in your brain; and when you experienced some visual experience, this would get stored as some tiny little image in your brain. So, for example, under this theory, if someone memorized the sentence, “There may be green aliens in the center of the galaxy,” then after the person died, some scientist might examine that person's brain with an electron microscope, and actually find some tiny little words in some neurons, words that directly spelled out, “There may be green aliens in the center of the galaxy.” And under this theory, if someone was given a picture of a toy purple pony, and asked to memorize it, then after the person died, a scientist might be able to examine the person's brain under an electron microscope, and the scientist might say, “Aha, I see in his neurons a tiny little image of a toy purple pony.”

This theory may immediately provoke giggles, and it is rather easy to think of some reasons why it does not work. They are these:

1. If memory worked in such a way, we would surely have already discovered such easily-recognizable memory traces. But no such things have been seen, even though a great deal of human neural tissue has been examined at very high magnification. When we look at brain tissue at the highest magnification, we see no tiny little letters or tiny little images of animals, cars, and persons.
2. For a brain to be able to write words that we memorized in this type of direct manner, it would seem that the brain would need some very precise write mechanism, capable of forming the exact characters of the alphabet in brain tissue; but no such brain capability is known to exist.
3. It seems that if such a theory were true, recalling some words would be like reading. But recalling words is almost never like reading, and we don't see in our mind's eye some stream of letters as we recall some words we memorized.
4. For a brain to be able to read words that we memorized in this type of direct manner, it would seem that the brain would need some very precise reading mechanism, capable of reading the exact characters of the alphabet stored in very tiny letters written in brain tissue; but no such thing is known to exist. We don't have tiny little “micro-eyes” in our brains that might allow us to read tiny microscopic letters stored in our brains.
5. Alphabets of modern languages are relatively recent inventions. For example, the English alphabet is not many  thousands of years old. There has no been no change in brain structure for many thousands of years, and we can think of no  reason why brains would have some ability allowing it to write an alphabet that only came into existence centuries or a few thousand years ago, not many thousands of years ago. 

Theory #2: Brain storage of words and images using some unknown non-binary coding or translation protocol

Now, let's consider a different theory of memory encoding – the idea that instead of directly storing words and images (so that we could directly read the words and directly see the images), the brain uses some type of unknown coding or translation protocols. For example, it could conceivably be that words that we learn are somehow translated into proteins or chemicals or electrical states, using some as-of-yet undiscovered translation scheme.

For example, such a scheme might work a little like this:

Item	How the item might be represented
Letter “A”	Some particular neural arrangement of atoms, chemicals or electricity
Letter “B”	Some other neural arrangement of atoms, chemicals or electricity
Letter “C”	Some other neural  arrangement of atoms, chemicals or electricity

Such a scheme might work a little like the Morse code, in which particular letters are translated into some sequence of dots, dashes, or dots and dashes. Some particular arrangement of atoms, chemicals or electricity might work like a dot in the Morse code, and some other particular arrangement of atoms, chemicals or electricity might work like a dash in the Morse code.

Or there could be some higher-level translation system based on particular words rather than letters. For example, we can imagine something like this:

Item	How the item might be represented
Word “sun”	Some particular neural arrangement of atoms, chemicals, proteins or electricity
Word “man”	Some other neural arrangement of atoms, chemicals, proteins or electricity
Word “move”	Some other neural  arrangement of atoms, proteins chemicals or electricity

There is one giant problem with such a theory. All of the languages that we use are fairly recent innovations, having been created in only the last few percent of the time that humans have existed. For example, back in the Roman Empire people used Latin, but the English we use today has only been in use for less than 1200 years. The alphabet used for English is less than 1000 years old, and its alphabetic predecessor (the Latin alphabet) is only a few thousand years old. It is generally acknowledged even by Darwinism enthusiasts that very complex evolutionary innovations cannot arise in only a few centuries of time or a few thousand years. So we could never explain how the brain could naturally possess some elaborate translation system based on such a relatively recent innovation as the English language and the English alphabet.

Scientists strain our credulity whenever they talk about novel functional genes accidentally appearing even over the course of a million years. Think, then, on how much greater a problem there would be in explaining how hundreds of novel functional genes could have appeared in less than 3000 years, to perform some translation operation involving characters and words that have existed for less than 3000 years. To assume such a thing would be to assume evolution working thousands of times faster than the rate we would predict from known mutation rates.

There is also no evidence that any such great burst of genetic novelty has occurred. Although the half-life of DNA is 512 years, we have enough samples of human DNA from ancient Rome and ancient Egypt to know that there has been no big change in the DNA of humans during the past 3000 years. So it seems impossible that there could be any genetic capability (arising in the past few thousand years) that would allow humans to neurally store information using some encoding mechanism specifically tailored to the letters and words of the English language that have existed for less than 3000 years.

Another difficulty with the theory of encoding just mentioned is that if it existed, we would see big differences in the genes of people who spoke different languages. According to such a theory, we would expect that Chinese people would have one group of genes corresponding to proteins or RNA molecules needed to translate Chinese words into neural states, and that English speaking people would have some other quite different set of genes corresponding to proteins or RNA molecules needed to translate English words into neural states (particularly since the Chinese language and alphabet is so different from the English language and alphabet). But there exists no such difference in the genes of Chinese speaking people and English speaking people.

There is also the difficulty that there is no sign in the human genome that any such genes exist for performing such an elaborate operation of encoding human learned knowledge and episodic experience so that it can be stored in neurons or synapses (and there would need to be many hundreds or thousands of types of genes dedicated to performing such a task if it was done).

Theory #3: Binary writing of words and images

Now, let's consider a theory of memory encoding that perhaps the words we memorize and the images we remember are stored in binary format. We know that computers store information in binary format, so when it is suggested that the brain may use a similar format, this may sound reasonable to the average person (although it isn't, a brain being radically different from an electronic computer).

This possibility actually has all of the difficulties of the previous possibility. What goes on when your computer stores words in binary format is the following:

1. First individual letters in the words are converted into decimal numbers (such as 13, 19, and 23) using a particular translation table called the ASCII code.
2. Then, those numbers are converted from decimal to binary using a decimal-to-binary conversion routine.

So if we are to believe that the brain does binary encoding like a computer, we would need to believe that built into the brain on a low level is some type of translation scheme like the one below, a scheme in which letters are translated into decimal numbers.

ASCII table used by a computer to store encoded information

In addition, we would also have to believe that the brain has some kind of capability to translate the numbers in such a system into binary numbers. Alternately, we could believe that the brain has a scheme for directly translating characters into binary, but the overall complexity of such a translation mechanism would be every bit as great as a system in which characters are converted into decimal, and then into binary.

We have the following difficulties involved with such an idea:

1. If memory worked in such a way, we would surely have already discovered such easily-recognizable memory traces. We would have discovered tiny little traces in the brain that resemble binary coding. But no such things have been seen, even though a great deal of neural tissue has been examined at very high magnification.
2. For a brain to be able to write words that were memorized in this type of direct manner, it would seem that the brain would need some very precise write mechanism, capable of writing binary traces; but no such thing is known to exist.
3. For a brain to be able to read words that we memorized in this type of direct manner, it would seem that the brain would need some very precise reading mechanism, capable of reading in binary; but no such thing is known to exist.
4. Since the alphabets of human languages are only a few thousand years old, there would have been no time for the human body to have evolved some complex biological mechanism capable of converting specific alphabetic characters to binary.
5. We can imagine no way in which a brain could achieve the translation effect in which words are translated into binary. As far as we know, there is nothing anything like an ASCII table in your brain, nor is there anything like a facility for translating English letters directly into binary, nor is there anything like a facility for translating English letters into decimal, and then translating decimal numbers into binary. There are no genes in the genome that perform such tasks.

The Scientists Who Keep Falsely Talking About Memory Encoding and Memory Representations in Brains

The simple fact is that there is not the slightest evidence of memory encoding or memory representation in the human brain. So why it that we keep getting scientific papers claiming to have seen memory encoding or memory representation in the human brain? It's pretty much a "they're talking like they had what they need to have but don't have" kind of affair.  Something similar might be going on if some street beggar were to try to attract women by frequently using finance terms. So someone without $20 to his name might speak like this:  "I think that WEALTH MANAGEMENT is very important, and I am slowly BUILDING MY FORTUNE in a way that will give me a HUGE BONANZA OF WEALTH once my INVESTMENT PLANS are actualized."

But how can someone write a paper making frequent references to memory encoding and memory representation in the brain, even though there is no evidence that such things exist?  The visual below shows the general approach typically used. 

A key element is what can be called chance-mining. Chance-mining typically involves grandly trumpeting some little result that might easily be obtained by pure chance.  I can give an example of chance-mining. Suppose you are doing a study trying to prove what we may call "the Abracadabra Hypothesis," which you define as "the hypothesis that saying 'Abracadabra' before flipping a coin will increase the chance of a Heads result." Any test involving a sufficiently large sample size will fail to support this Abracadabra Hypothesis. That's because something called the Law of Large Numbers says that the more random trials you do, the more the result will tend to match the result expected by chance. But it is very easy to get a test result deviating from what is expected by chance, if you use a very small sample.  For example, it is easy to flip ten coins and get 6 or 7 Heads results, even though the expected chance result is 5.

So if you want to do a paper claiming to support the Abracadabra Hypothesis, you can try a test using a small number of coin flips such as only 10 or 20. If that fails, you can file the results in your file drawer, and start a new experiment, also using a small number of coin flips. Probably before long you will have some result you can claim as "statistically significant." Chance-mining like this misleads people, because it creates the impression that there is a causal relation or causal influence when there is none. Saying "Abracadabra" actually has no influence on the result of coin flips. 

Similar chance-mining occurs in quite a few neuroscience papers.  The papers may make quite a few references to neural encoding or neural representation, but they will not be backed up by references to well-designed studies using an adequate sample size.  Typically the paper will present some research that is utterly unreliable for multiple reasons, such as the use of way-too-small study group sizes or unreliable techniques for trying to measure recall in rodents. 

A example of such a paper is the paper here, entitled "Ventral hippocampus neurons encode meal-related memory." The title is unjustified. No robust evidence has been provided of any neural encoding of memory. There are two gigantic flaws in the study:

(1) The study group size is way too small, consisting of only 5 animals. 

(2) No reliable method was used to measure memory performance in rodents. We read that a "foraging-related spatial memory task" apparatus was constructed to test memory in mice. We see a picture of a weird device that the paper does not name. This was not any well-established protocol for testing memory in mice. We fail to have any diagram explaining why such a device would reliably test memory in mice. 

What usually occurs in such papers claiming evidence of "memory encoding" or "memory representation" is that there will be a combination of two main sins, either one of which is to disqualify a paper as good evidence:

(1) Almost always there will be some study group size that is way too-small for any reliable evidence to be honestly claimed 

(2) Usually there will be a reliance on a completely unreliable measurement for estimating fear or recall in rodents, the method of trying to judge "freezing behavior." All papers relying on this method are junk science, for reasons I discuss here. 

What largely goes on in such poorly written science papers is pareidolia.  Pareidolia is what occurs when someone keeps scanning some stream of random data, looking for something he can call a representation. An example is a person who eagerly scans his toast every day, looking for some sign of a representation, and who one day announces he has found the face of Jesus in his toast, or maybe the face of the Virgin Mary, or maybe the face of his dead wife. 

The neuroscientist eagerly scanning brain scan data or brain wave data looking for something he can call a little bit of "representation" or "encoding" is someone who we can no more trust than someone eagerly scanning the clouds every day, looking for something that looks like the shape of an animal. 

An example from 2025 of a pure pareidolia paper is the junk science paper "Movie-watching evokes ripple-like activity within events and at event boundaries." We have scientists looking at EEG readings obtained in ten epilepsy patients while the patients watched movies.  Looking at the ever-changing line squiggles that are EEG readings, the authors claim to have seen "ripples" that they claim occur more often during "event boundaries." The claim that there are such "ripples" in the data is as much see-what-you-want-to-see pareidolia as the claim that there are particular points in movies that are "event boundaries." The supposed identification of these "ripples" occurred not by humans staring at the EEG readings, but by some computer program which is a black box of convoluted spaghetti code. Computer programming is the best friend of the scientist trying to see things that are not really there. You can run some computer program that is supposedly seeking some obscure thing in noisy data; and if the first analysis run fails, you can keep tweaking the code until it reports finding what you were hoping to find. 

Neurons Are Just as Active During Sleep, Contrary to "Brains Make Minds" Claims

Under the assumption that the brain produces thinking, we would expect that neurons would fire much more often when a person is awake than when he was asleep. The reality is a very embarrassing one for "brains make minds" claimants. The reality is that neurons are continually active, firing between about 1 to 200 times per second. This activity continues full-blast during sleep, without any major decrease in the firing rates of neurons. Asking Google "what kind of diurnal variations are there in neural firing rates?" I get an AI overview answer that includes this statement referring to neurons: "the average firing rates of excitatory pyramidal populations (such as in the hippocampus) remain remarkably static and stable across the 24-hour period, independent of sleep states."

The graph below is from the scientific paper here, entitled "Neuronal firing rates diverge during REM and homogenize during non-REM." We see neural firing rates in the hippocampus of rats during short periods of rapid-eye movement (REM) sleep, during long periods of non-rapid-eye-movement (NREM) sleep (shown underneath the blue bars), and during some short periods of being awake (shown underneath the orange bars). The firing rates all look the same.

The same paper gives us this graph showing neuron firing rates in the cortex. We see neural firing rates in the cortex during short periods of rapid-eye movement (REM) sleep (shown underneath the short purple bars), during long periods of non-rapid-eye-movement (NREM) sleep (shown underneath the blue bars), and during some short periods of being awake (shown underneath the orange bars). The firing rates look pretty much the same in sleep and wakefulness. The highest spikes occur not during wakefulness but during REM sleep. 

The graph below (from the paper here) shows no appreciable difference between neural firing rates of awake rats and neural firing rates of asleep rats. The "hz" on the side stands for "hertz," and 1 hertz means I time per second. In both asleep rats and awake rats, neurons firing at an average rate of about 1 time per second, 

Below is a graph from the scientific paper here, entitled "Increased neuronal firing in resting and sleep in areas of the macaque medial prefrontal cortex." We see neural firing rates in a monkey during sleep (the shaded areas) and during an awake state. The neurons are firing more frequently during sleep than during the wake state. 

This data makes no sense under the idea that your brain makes your mind and the idea that your brain stores your memories. Why would the hippocampus (claimed wrongly to be "the memory center" of the brain) keep firing its neurons at the same rate when you are awake (and need to be continually creating memories) as when you are asleep (when you  are not creating important memories, are not receiving sensory inputs and you are not thinking)? Why would the cortex (wrongly claimed to be the "thinking center" of your brain) fire its neurons more often during sleep (when someone is not thinking) than during wakefulness?

The Mystery Is Not Infantile Amnesia, But How Anything Can Be Instantly Learned or Instantly Recalled

 A recent article at the neuroscience site The Transmitter is entitled "Infant Memories: Lost But Not Gone?" The article has quite a few groundless and incorrect claims about memory, which the authors (Paul Frankland, Sheena Josselyn and Nick Turke-Browne) attempt to substantiate by linking mostly to low-quality papers, some of which they co-authored themselves. 

Early on, the authors state, "The advent of activity-dependent engram labeling and optogenetic tools has enabled researchers to directly address the encoding versus retrieval debate." No such thing as engram labeling exists, and claims that scientists have discovered engrams (reputed places of memory storage in a brain) are without any foundation in good science. 

It is interesting that both of the links above are to papers authored by two of the three Transmitter article authors (Frankland and Josselyn). So we have self-citation. The first paper is a paper by Frankland, Josselyn and Kohler entitled "Engrams." We have the claim, "At the largest scale, engrams are thought to be composed of sparse neuronal ensembles, distributed throughout the brain." That sure does not sound like some specific thing discovered in some particular part of the brain. We read this: "Between 1950 — when Lashley published his scientific magnum opus (In Search of the Engram) — and the late 2000s, barely any scientific articles bore the term engram in their title."

Then we read in the paper about experiments done in recent years. The authors of the paper fail to discuss the low quality of these experiments, and how they were guilty of Questionable Research Practices such as the use of way-too-small study groups, and unreliable methods for measuring how well a rodent remembered. In a paragraph entitled "What is the best evidence for engrams?" we have a reference to rodent experiments using "freezing behavior" judgments (really just immobility tracking).  All such studies are examples of junk science, for reasons explained here. Trying to judge a rodent's immobility (and calling that a tracking of "freezing behavior") is a worthless technique for judging whether an animal remembered something. 

The other link in the quote above from the Transmitter article is to a review article by Frankland, Josselyn and Kohler. It is called "The neurobiological foundation of memory retrieval," but fails to explain how any such thing can occur. The article is one of those review articles in which many a low-quality study is treated as if it was good evidence.

Later in the Transmitter article the authors state, "In mice, researchers can tag engrams in infant pups, track their persistence across development and optogenetically reactivate them later in life to recover seemingly lost memories." That is not at all true. The link is to a low-quality paper "Recovery of 'Lost' Infant Memories in Mice" co-authored by Josselyn, Frankland and others. The study group sizes were way below the minimum of 15 or 20 rodents needed for a study like this to be taken seriously. We read, "Separate groups of infant and adult mice were tested either 1 (P17, N = 9; P60, N = 7), 15 (P17, N = 9; P60, N = 12), 30 (P17, N = 10; P60, N = 7), or 90 days (P17, N = 8; P60, N = 10) after training." The "N" refers to how many rodents were used in particular study groups. Averaging about nine rodents per study group, those are all way-too-small study group sizes. And the worthless method of trying to judge "freezing behavior" was used throughout the study. 

Referring to this low-quality paper as if it was something good, the Transmitter article states this:

"Animals that undergo contextual fear conditioning in infancy show no behavioral evidence of remembering when tested in adulthood (that is, they do not freeze when placed back in a context where they were  shocked as pups). However, optogenetic stimulation of the neurons that were active when the pup was first conditioned triggers expression of the memory; the mature animal now freezes."

But using "freezing behavior" judgments is a worthless technique for trying to measure how well a rodent remembered. And it is particularly invalid to apply "optogenetic stimulation" (a type of brain zapping), and to then claim that this shows that a memory was artificially reactivated because an animal exhibited "freezing behavior." It has been realized by neuroscientists that artificial stimulation of many areas of the brain will produce "freezing behavior" regardless of whether any memory is being recalled. 

Imagine you are running along, and suddenly a scientist switches on some weird thing that causes some energy to pour into your brain. This all by itself might cause you to stop, even if it didn't cause you to recall some memory that caused you to stop. What could have been going on in the mice was just a kind of pausing effect caused by a novel stimulus rather than a recalled fear effect. A science paper says that it is possible to induce freezing [i.e. immobility] 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).”

It is not sound to assume that you can judge the degree of immobility of a mouse in a cage, and then assume that the higher levels of immobility are evidence of a mouse “freezing in fear" because it remembers a fear stimulus.  The "freezing behavior" method of trying to judge recall in mice works like this. A mouse will be trained to fear a shock plate that produces an electrical shock. The mouse will later be put in a cage with such a shock plate. Scientists will then attempt to judge immobility of the mouse during some arbitrary time unit that can be either 30 seconds, a minute, two minutes or three minutes. An arbitrary criteria will be used to judge immobility. For example, not moving for most of ten seconds can be counted as immobility during those seconds, or not moving for most of 20 seconds can be counted as immobility during those seconds, or not moving for  most of 30 seconds can be counted as immobility. Or, any movement at all during those seconds can be counted as movement during that time period. This immobility will be called "freezing," even though scientists have no idea whether the mouse was afraid when it was not moving.  The result of trying to track the mouse's immobility is a "freezing percentage" graph that can be produced in any of 100 different ways. With so many possible analysis choices, it will be almost certain that the experimenter will be able to produce a graph purporting to show the desired difference in "freezing behavior." There are no standards in producing these "freezing behavior" charts. 

Neuroscientists follow this bungling method of trying to measure mouse recall because it is a "see whatever you want to see" method providing the researcher with a near-certainty that the desired results can be claimed. Instead of using so deficient a technique, there are other reliable techniques that can be used. A 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 than the easier path.

Or, more simply, a very hungry mouse trained to fear a shock plate can be put in a cage like the one show below, and it can be recorded whether he touched the shock plate while trying to get the reward, or whether the mouse did not go get the food (as it would only do if it remembered that the shock plate produces pain). 

The Transmitter article authors then approvingly cite an appalling set of studies trying to show evidence of memory formation in infants by brain scanning them. Such studies are criticized in my post "The Reckless Foolishness of Brain-Scanning Healthy Babies in Neuroscience Experiments."  Having no value in helping to understand memory, experiments such as these run very serious risks to the infants who are needlessly put in brain scanners. There is both a risk of an accident that might harm or kill the child (a young boy once died in an MRI accident), and also a very serious risk that such brain scanning may increase the child's lifetime risk of developing cancer.  

The authors of the paper are trying in a self-serving manner to get us to believe in a socially constructed triumphal legend that researchers such as themselves have done something to substantiate the idea of an engram, a claim that has no basis in robust and well-designed experimental studies. Contrary to their insinuation that this "engram" concept has blossomed in the past 15 years, a search for references to "engram" using the Google Books Ngram viewer shows little evidence of such a blossoming. 

We may compare this result with a search for a word that seems to have skyrocketed in use since the year 2000, the word "ghosts."

Judging from the graph above, you might conclude that the observational evidence for apparitions is far stronger than the observational evidence for engrams.  

The mystery is not why a 70-year-old fails to remember the first five years of his life. The mysteries are how any human is able to remember anything at all, how people asked questions with specific answers are able to instantly answer correctly by giving information they learned decades ago, and also why old people are able to remember very well what occurred to them 50 or 60 years ago. 

Nothing in the brain bears any resemblance to a device for storing learned information, and nothing in the brain bears any resemblance to a device for retrieving learned information. The brain has no known writing mechanism and no known mechanism for reading learned information. The microscopic examination of brain tissue has never detected the slightest trace of anything a human ever learned, even though the brains of many corpses of recently-deceased people have been studied by scientists, and even though much brain tissue extracted from living people has been microscopically studied. 

Neuroscientists senselessly claim that memories are stored in synapses, but the proteins that make up synapses have average lifetimes 1000 times shorter than the maximum length of time that humans remember things (average lifetimes of only a few weeks). Synapses fail to even transmit data reliably, with each transmission across a synaptic gap occurring with a reliability of only 50% or less. Such signal transmission unreliability should make both a brain storage of memory and a brain retrieval of memory impossible, because signals would have to pass over so very many synapses when either event occurred (there are very many synapses for every neuron). A human can remember the answers to very many thousands of questions instantly, but nothing in a brain can explain such a wonder. Humans construct things that allow the instant retrieval of information, and so we know the type of things that make possible instant information retrieval. Those things are addresses, indexes and sorting. The brain has no addresses, no indexes, and no sorting. The physical architecture of the brain makes sorting within it impossible. Humans can learn things instantly, something that cannot be explained by synapse strengthening which is a slow affair.

Below are some relevant quotes:

• "Synaptic transmission and axonal transfer of nerve impulses are too slow to organize coordinated activity in large areas of the central nervous system. Numerous observations confirm this view [73]. The duration of a synaptic transmission is at least 0.5 ms, thus the transmission across thousands of synapses takes about hundreds or even thousands of milliseconds. The transmission speed of action potentials varies between 0.5 m/s and 120 m/s along an axon. More than 50% of the nerves fibers in the corpus callosum are without myelin, thus their speed is reduced to 0.5 m/s. How can these low velocities (i.e. classical signals) explain the fast processing in the nervous system?" -- The paper "Emission of Mitochondrial Biophotons and their Effect on Electrical Activity of Membrane via Microtubules" by 7 scientists.
• "Neural circuits consist of many noisy, slow components, with individual neurons subject to ion channel noise, axonal propagation delays, and unreliable and slow synaptic transmission." -- Four scientists (link). 
• "Neurons communicate primarily through chemical synapses, and that communication is critical for proper brain function. However, chemical synaptic transmission appears unreliable: for most synapses, when an action potential arrives at an axon terminal, about half the time, no neurotransmitter is released and so no communication happens... Furthermore, when neurotransmitter is released at an individual synaptic release site, the size of the local postsynaptic membrane conductance change is also variable. Given the importance of synapses, the energetic cost of generating action potentials, and the evolutionary timescales over which the brain has been optimized, the high level of synaptic noise seems surprising."  -- Four scientists (link). 
• "The probability of [synaptic] vesicle release [i.e. successful synaptic transmission] is known to be generally low (0.1 to 0.4) from in vitro studies in some vertebrate and invertebrate systems (Stevens, 1994). This unreliability is further compounded by the trial-to-trial variability in the amplitude of the post-synaptic response to a vesicular release." -- Two scientists (link). 
• "The release probability, the average probability that an active zone of a presynaptic terminal releases one or more vesicles following an action potential, is tightly regulated. Measurements in cultured neurons or in slices indicate that this probability can vary greatly between synapses, but on average it is estimated to be as high as 0.5....Existing evidence thus suggests that under physiological conditions in vivo, presynaptic action potentials trigger the release of neurotransmitter much less frequently than what is observed in in vitro preparations." -- A paper by two scientists, suggesting synapses transmit signals with a reliability much less than 50% (link). 
• "On average most synapses respond to only less than half of the presynaptic spikes, and if they respond, the amplitude of the postsynaptic current varies. This high degree of unreliability has been puzzling as it impairs information transmission." -- Four scientists (link).
• "Transmission at individual synaptic contacts on CAI hippocampal pyramidal neurons has been found to be very unreliable, with greater than half of the arriving presynaptic nerve impulses failing to evoke a postsynaptlc response." -- Two scientists (link). 
• "A precise estimate of the in vivo [synaptic] release probability is difficult, but...it can be expected to be closer to 0.1 than to the previous estimates of around 0.5. " -- "The low synaptic release probability in vivo" by J. Gerard G. Borst (link). 
• "The average number of connections between areas in different hemispheres is even smaller, below 1,500 axons. While previous studies have hinted that connectivity between some areas could be sparse [1], the overall sparsity of cortical connections implied by the present study still comes as a surprise. It is as if a traffic system presumed to consist of multilane highways running between most brain areas in fact consists of just a few precarious footpaths." --  The paper "The Highways and Byways of the Brain" by two scientists (link), a paper referring to "the generally very sparse connectivity" of the brain. 
• "The scale of the vast gulf in absolute connectivity between local and long-range connections is startling."--  Paper "An estimation of the absolute number of axons indicates that human cortical areas are sparsely connected" by two scientists (link).
• "Interestingly, signal propagation speeds in various conditions are similar (~0.1 m/s). Neural spikes generated by 4-aminopyridine (4-AP) travel with a longitudinal speed of 0.09/0.03 m/s along the CA3 region (Kiblerand Durand, 2011), whereas in the presence of picrotoxin, synchronous firing events propagate longitudinally at 0.14 /0.04m/s (Miles et al., 1988). High K+-, low Mg2+-, and zero-Ca2+- triggered spikes again exhibit speeds of 0.07-0.1 m/s, 0.1– 0.15m/s, and 0.04 – 0.15 m/s, respectively (Haas and Jefferys, 1984;Quilichini et al., 2002;Liu et al., 2013). In normal tissue, theta oscillations travel with a speed of 0.08 – 0.107 m/s in the hippocampus of living rodent rats (Lubenov and Siapas, 2009),whereas carbachol-induced theta oscillations travels with a speed of 0.119 m/s along the CA1 cell layer and a 0.141 m/s along the CA3 cell layer (Cappaert et al., 2009). Together, it is clear that 0.1m/s is a common propagation speed regardless of experimental models." -- Two scientists telling us that a common speed of brain signal transmission is about 3.6 inches per second (i.e. a tenth of a meter per second), 1000 times slower than the "100 meters per second" commonly given (link). 

Gadgets Tracking Your Brain Waves Continuously Will Probably Not Help You

 The false "brains make minds" dogma has inspired medical predators and quack gadget sellers. One guy has made an enormous fortune luring people into medically unnecessary PET scans that have a significant chance of increasing someone's risk of cancer. 

PET scans involve the injection of radioactive materials into the body. The radioactive materials have a short half-life, and neuroscientists claim the scans are not risky. But there is every reason to suspect that such scans involve very significant risks to people. PET scans involve significant doses of ionizing radiation that increase the chance of cancer. A PET scan typically involves as much radiation as a CT scan, and it is well-known that every CT scan that you have slightly increases your chance of cancer.   A page on the website of the American Cancer Society says this:

"A PET/CT exposes you to about 25 mSv of radiation. This is equal to about 8 years of average background radiation exposure."

How does that translate to an increased cancer risk? Using the calculator at the web site www.xrayrisk.com (which also allows you to calculate the risk of other things such as CT scans), we get the estimate below:

The answer is that 25 mSv of radiation increases your cancer risk by about 1 part in 328. 

The guy I refer to above is someone who lures people into paying huge amounts of money for medically unnecessary and potentially hazardous PET scans, under the false premise that such scans will tell you something you did not know about your mind.  Scanning brains sheds no insight on a person's mind. But a scammer can always dredge up some low-quality Questionable Research Practices study to try and make it look like some tiny thing found here or there in a brain scan has some value in telling you something about your mind. 

A company called ATLAS has recently announced some very expensive brain monitoring product that has similarities to what I mention above, except that in this case no objection can be made about a potential health hazard (the product seems to involve no health risk).  The product is announced in the recent press release here. Strangely, the press release has no picture of what the device looks like when someone is wearing it. Looking around in the company's site, we get this image:

You have to wonder: how could such a device stay in the shown position? Through some adhesive, perhaps? I would have thought that the way to invent a continuous EEG-like device for monitoring brain waves would have been to create something that leveraged the ear-touching parts of eyeglasses. 

But let's ignore this issue, and ask: is there any reason to think that such a device might be worth its very high cost? The device has a price tag of 499 dollars, and also requires a 30 dollar a month subscription. 

The press release fails to mention any benefit in any convincing way. The press release gives us this laughable sales pitch:

"Imagine a world where data from your own mind helps you redefine what truly matters. ATLAS enables you to ask questions to better understand how your mind works: Was I really present for dinner with my family? Who makes me feel more like myself? Do I actually perform better under pressure? Why am I defining a successful run in minutes rather than stress relief? When I'm exhausted, what do I still show up for? ATLAS helps you discover what brings out the best in you everyday and enables you to become more of that person to optimize your life."

This sales pitch is comically bungling. No, wearing some brain wave tracking device will not enable you to ask questions such as the listed questions. You can ask those questions just fine without wearing any such device. And one of the examples of a question is laughable: "Was I really present for dinner with my family?" You don't need some fancy brain wave tracking device to know that.  The last sentence in the quote is pure "hot air." 

What are brain waves? They are waves that show up in EEG readings taken when lots of electrodes are attached to someone's head. A full EEG reading will involve some cap with many different electrodes positioned at different spots on the top of someone's head.  But you can take a kind of "poor man's EEG" by using readings from just one spot in the head. 

A full EEG reading

Can EEG readings be analyzed to determine what a person is thinking or feeling? No, they cannot. Nowadays there is a great deal of pareidolia and junk science involving the analyzing of brain waves, typically occurring in studies guilty of Questionable Research Practices. There is no robust evidence that anything someone is thinking or feeling or remembering can be determined from analyzing brain waves (with a very few exceptions such as fear or rage, which might cause something like panic trembling or facial expressions that might be detectable by analyzing brain waves, because of related body movements that cause brain wave blips). 

The press release has a chief executive officer of the company telling us this bad example of groundless baloney: "ATLAS gives you a map of your own mind, so you can understand what brings out the best in you, change what doesn't, and become who you want to be." There are no are no EEG readings and no brain scans that can ever produce any such thing as a map of your mind. 

A FAQ page of the company offers no specifics that would justify a purchase. We read, "Atlas does not read individual thoughts, decode memories or know the private meaning of what you are thinking." We merely read these dubious claims:

"It can tell whether you're stressed or relaxed, or whether your mind is engaged with the outside world or if you're in your head, reflecting or focusing on deep work. It can also tell when your mind is using a lot of energy and when it is exhausted and in need of some recovery."

EEG readings cannot distinguish between (1) a motionless person with closed eyes who is doing mental work and (2) a motionless person with closed eyes who is resting his mind. But any type of muscle movements can show up in EEG readings, including mere eye movements, strong facial expressions and finger movements.   So EEG readings could probably distinguish between someone "engaged with the outside world" in the sense of reading, looking around, or using a smartphone or computer, and someone who was sitting motionless and reflecting, with his eyes closed or staring into space. But why would you need some fancy device to distinguish between those two things, when you would already know which you were doing?  And also, you don't need some fancy device to tell you when your mind is exhausted. 

A continuous EEG reader might rarely be useful in detecting epilepsy. But only about 1 in 26 people have epilepsy. And epilepsy produces seizures that allow you to detect it without any high-tech device. 

If the company selling this Atlas device wants to make a convincing case for its brain wave reader product, it will have to produce something way better than its laughable press release here. And it will need to put up a FAQ page much more convincing than its current FAQ page.