Quanta Magazine Draws the Wrong Conclusion About Neural Noise and Memories

The online science journalism web site called Quanta Magazine at www.quantamagazine.org is a graphically slick affair, but its articles often are defective, because its writers so often reverently extol or hype or misrepresent dubious studies by scientists, and almost never seem to apply critical judgment when analyzing such questionable work products. Very many times at this site we will read articles on the deepest topics of physics and biology and the human mind, containing dubious or presumptive statements about  the fundamental nature of reality or life or mind or the universe, written by quite youthful-looking writers.  When I look up the biographies of such writers on the site, I sometimes find they lack any stated relevant science education qualifications.  Sometimes the authors have relevant PhD's, but in quite a few cases we have biographies of young adults that may list only a relevant bachelor's degree or maybe not even that.  Many years of independent study on a topic can make up for failing to study that topic very deeply in college, but when I see a youthful-looking face, I tend to doubt that many such years of independent study occurred. 

A recent example of a defective article in Quanta Magazine was an article entitled "New Map of Meaning in the Brain Changes Ideas About Memory."  The article is a credulous treatment of some very dubious neuroscientist studies that are guilty of the same type of  Questionable Research Practices found in a large fraction of all  experimental neuroscience papers these days.  In the article we read repeated claims that some kind of neural representations have been found.  Representation is when one thing represents or stands for another, according to some system of symbols or tokens. All claims of representations in the brain outside of DNA are groundless. We know that the DNA in brain cells (and all other cells) have a form of representation, because certain groups of nucleotide base pairs in DNA stand for or represent particular amino acids, under the representation system known as the genetic code. Other than this, there is no robust evidence of any type of representation anywhere in the human body.  There is zero evidence that there exists any such thing as a "map of meaning in the brain." 

The Quanta article mentioned above refers to this neuroscience paper guilty of the usual Questionable Research Practices so prevalent in the dysfunctional realm that is modern experimental neuroscience. The paper ("A Continuous Semantic Space Describes the Representation of Thousands of Object and Action Categories across the Human Brain") makes this groundless claim: "The brain represents object and action categories within a continuous semantic space." The paper gives no robust evidence for any such representations.  Among the defects of the paper are these:

• Insufficient sample size. The paper describes some brain scanning of a mere five subjects who watched movies.  Fifteen subjects per study group is the minimum for a modestly persuasive experimental result for studies of this type. A sample size calculation (something necessary for any experimental paper of this type to be taken seriously) would have revealed the shortfall, but no such calculation was done.  According to Table 7 of the paper here, a correlation experiment reporting the effect sizes reported by this paper should have used at least 27 subjects. 
• No control group was used, quite the serious defect for a study like this. For each of the brain-scanned subjects watching movies, there should have been an equal number of brain-scanned control subjects who were not watching movies. 
• The study used no blinding protocol (something necessary for any experimental paper of this type to be taken seriously), and neither the word "blind" nor "blinding" appears in the paper. 
• The study was not a pre-registered study registering before data collection an exact hypothesis and exactly how data would be gathered and analyzed, meaning the authors were free to apply any type of analysis they wished after gathering data, and free to improvise how they gathered data,  in a "fishing expedition" type of affair maximizing the chance they would report finding whatever they hoped to find, possibly after slicing and dicing the data until they got the desired result. 

The same defects (the same Questionable Research Practices) are found in another scientific paper referenced by the Quanta Magazine article mentioned above: the paper "A network linking scene perception and spatial memory systems in posterior cerebral cortex," which has the same problems as listed above, except that the study group sizes were 14, 13 and 6 rather than 5.  The same defects (the same Questionable Research Practices) are found in another scientific paper referenced by the Quanta Magazine article mentioned above: the paper "Natural speech reveals the semantic maps that tile human cerebral cortex," which has the same problems as listed above, except that the main study group size was only 7 subjects.  The same defects are found in a paper discussed last month in a misleading Science Daily article entitled "Key brain mechanisms for organizing memories in time." That paper ("Hippocampal ensembles represent sequential relationships among an extended sequence of nonspatial events") used only 5 mice. The paper relied on machine learning, which is being carelessly used by neuroscientists who fail to realize machine learning has an extremely large potential for finding causally irrelevant meaningless correlations.  An expert on computers and software says, "Perhaps the biggest issue with current machine learning trends, however, is our flawed tendency to interpret or describe the patterns captured in models as causative rather than correlations of unknown veracity, accuracy or impact."  A full discussion of how neuroscientists are abusing machine learning will require a separate post. 

There is zero robust evidence for any such things as semantic maps in the human brain, and zero robust evidence for any kind of representations in the brain other than the "nucleotide base pair combinations representing amino acids" representations found in the nucleus of neurons and all other cells. 

In Quanta Magazine what routinely happens is that some article will discuss some shoddy-science research guilty of Questionable Research Practices, and we will see photos showing some scientist involved in the research, with a big proud grin on his or her face.  Were such photos to show facial expressions matching the quality of the research practices involved, we would see people holding their heads in shame. 

A community with very strong ideological motivations, the neuroscientist research community resembles some ideologically-motivated research community dedicated to proving that the ghosts of deceased animals linger in the clouds.  What would happen if such a ghosts-in-the-clouds research community were to follow a very rigorous set of research standards? Conceivably they might get some good evidence in support of their cherished belief that animal ghosts live in the clouds. But what would be the main results if such a community of researchers had bad research practices, and failed to follow rigorous standards? Then what they would mainly produce in their literature are false alarms, such as photos of clouds looking a little like animals.  Similarly, what should we expect to mainly get from a community of neuroscience researchers who are very eager to prove claims that brains produce minds, when such researchers routinely act as if they had almost no experimental research standards, and routinely act as if they were oblivious to sensible rules for producing reliable results?  We should mainly expect to get false alarms. That is mainly what is showing up in the neuroscience articles appearing in Quanta Magazine and other science news sites: mainly false alarms. 

In the 2020 study "Sample size evolution in neuroimaging research: An evaluation of highly-cited studies (1990-2012) and of latest practices (2017-2018) in high-impact journals" by Denes Szucs and John P.A.  Ioannidis we have some facts that illuminate the typically dismal quality of experimental neuroimaging studies.  Analyzing more than 1000 papers, the study found the following:

• that the median reported sample size for neuroimaging imaging studies is a mere 12 (even though, according to section 4.1 of the paper, a sample size more like 33 or 34 is typically needed for a study to be robust);
• that even though "publishers and funders should require pre-study power calculations necessitating the specification of effect sizes,"   almost none of the papers had such pre-study power calculations (in which you calculate the number of subjects needed for a robust effect).

Another defective article on neuroscience recently appearing in Quanta Magazine is an article entitled "Neural Noise Shows the Uncertainty of Our Memories."  The article refers us to the paper "Joint representation of working memory and uncertainty in human cortex."  In that paper we find the same Questionable Research Practices listed above: no blinding protocol, no pre-registration of a hypothesis and techniques to be followed, too small sample sizes (only 11 participants for Experiment 1), and the only control group being a way-too-small group of three subjects.  15 subjects per study group (including controls) are the minimum for a modestly reliable experimental result for studies of this type. 

The Quanta Magazine article suggests the laughable idea that neurons use Bayesian mathematics or probabilistic calculations in recognition or memory.  The young author of the article cites some very relevant problems with the related research, but apparently fails to be alarmed by the giant red flags involved, like someone cheerfully driving along while red lights are flashing on his car dashboard.  The article states this:

"Still, 'one thing to realize is that the actual correlations are very low,' said Paul Bays, a neuroscientist at the University of Cambridge who also studies visual working memory. Compared to the visual cortex, fMRI scans are very coarse-grained: Each data point in a scan represents the activity of thousands, perhaps even millions of neurons. Given the limitations of the technology, it’s notable that the researchers were able to make the kinds of observations in this study at all.  Hsin-Hung Li, a postdoctoral researcher in Curtis’ laboratory at NYU, used a brain scanner to measure the neural activity associated with a working memory, then assessed the research subject’s uncertainty about the memory.  'We are using a very noisy measurement to tease apart a very tiny thing,' said Hsin-Hung Li, a postdoctoral researcher at NYU and first author of the new paper."

What the Quanta Magazine writer should have done is to recognize that these confessions are indications that no reliable evidence has been found, and that what we have is some gossamer-thin false alarm results that are being "teased out" by researchers eager to find some particular result, like some eager ghost-in-the-clouds believer enthusiastically scanning the heavens for faint traces of ghosts in the sky. 

The title of the Quanta Magazine article is inaccurate. Neural noise does not show that human memories are uncertain. There is a great abundance of very severe noise all over the place in the brain. But that does nothing to show that human memories are unreliable.  To the contrary, it is a fact of human experience that humans can memorize with perfect accuracy very long bodies of information.  This is shown every time a stage actor plays the very long role of Hamlet (a role of 1480 lines) without committing an error, and is also shown every time a Wagnerian tenor sings the very long role of Siegfried (a role of 6000+ words) without committing an error.  No such feats should be possible if such persons are retrieving memories stored in brains, given how much noise exists in the brain. 

Brains are extremely noisy. Many neurons fire at unpredictable intervals, just as maple leaves fall from a tree in autumn at unpredictable intervals. A scientific paper tells us, “Neuronal variability (both in and across trials) can exhibit statistical characteristics (such as the mean and variance) that match those of random processes.” Another scientific paper tells us that “Neural activity in the mammalian brain is notoriously variable/noisy over time.” Another paper tells us, "We have confirmed that synaptic transmission at excitatory synapses is generally quite unreliable, with failure rates usually in excess of 0.5 [50%]." A paper tells us that there are two problems in synaptic transmission: (1) the low likelihood of a signal transmitting across a synapse, and (2) a randomness in the strength of the signal that is transmitted if such a signal transmission occurs. As the paper puts it (using more technical language than I just used):

"The probability of vesicle release 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." 

The 2010 paper "The low synaptic release probability in vivo" by Borst is devoted to the topic of what is the chance that a synapse will transmit a signal that it receives. It tells us, "A precise estimate of the in vivo release probability is difficult," but that "it can be expected to be closer to 0.1 than to the previous estimates of around 0.5."  Slide number 20 of the 2019 Power Point presentation here has a graph showing that this release probability is often around 0.1 or 0.2, and the same page mentions 0.3 as a typical release probability. 

Another paper concurs by also saying that there are two problems (unreliable synaptic transmission and a randomness in the signal strength when the transmission occurs):

"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."

It would be almost impossible to overestimate the significance of such facts, which would have the greatest effects all over the place if brains were the storage place of human memories.  Such large levels of neural noise would not just prevent learned information from being accurately stored.  Such neural noise would also prevent learned information from being accurately retrieved.  Imagine if you had a computer so unreliable that each time you saved a file, a particular character (such as a,b,c and so forth) was saved with a likelihood of less than 50%. Imagine the same computer was so unreliable that when it read a stored file, each character would be displayed on your screen with a likelihood of less than 50%.  With such a computer you would never be able to store and retrieve information reliably. We can say the same thing about a brain that has as much noise as the neural noise discussed above.  

But the fact is: despite all this neural noise, many humans are able to memorize with perfect accuracy very large bodies of information.  This is shown not just by Hamlet actors (who perfectly recite 1480 lines in one evening) and Wagnerian tenors who perform similar feats, but also by some Islamic scholars who can recite perfectly every line of their long holy book of more than 6000 lines, and also Christian scholars who were able to perform similar feats of memorization (an example being Tom Meyer who memorized twenty books of the Bible). Akira Haraguchi was able to recite correctly from memory 100,000 digits of pi in 16 hours, in a filmed public exhibition. Many equally astounding cases are discussed here and here, such as the case of a mathematician (Euler) who could recite every line of Homer's Aeneid (a work of 9883 lines). 

There is a correct conclusion to draw from the fact of extremely abundant neural noise. That conclusion is that the brain is not (and cannot possibly be) the storage place of human memories. Such a conclusion is consistent with all well-established facts known about the brain, such as the very short lifetime of proteins in the brain (about 1000 times shorter than the maximum length of time that old people can remember things), the rapid turnover and high instability of dendritic spines, the failure of scientists to ever find the slightest bit of stored memory information when examining neural tissue, the existence of good and sometimes above-average intelligence in some people whose brains had been almost entirely replaced by watery fluid (such as the hydrocephalus patients of John Lorber),  the lack of any indexing system or coordinate system or position notation system in the brain that might help to explain the wonder of instant memory recall, the good persistence of learned memories after surgical removal of half a brain to treat severe seizures,  the ability of many "savant" subjects (such as Kim Peek and Derek Paravicini) with severe brain damage to perform astounding wonders of memory recall, the fact of very vivid and lucid human experience and human memory formation in near-death experiences occurring after the electrical shutdown of the brain following cardiac arrest, and the complete lack of anything in the brain that can credibly explain a neural writing of complex learned information, a neural reading of complex learned information, or a neural instant retrieval of learned information. 

If our neuroscientists were to stop wasting so much time on poorly designed experiments failing to follow good research practices,  and were they to deeply delve into the massive evidence for anomalous mental phenomena utterly beyond any neural explanation (a topic they are extremely negligent in studying),  our neuroscientists might find themselves on a path that might lead to some good alternate non-neural theories to explain the basic wonders of human mental phenomena such as understanding, self-hood and memory. 

Today we have another defective story about memory in Quanta Magazine, one with the untrue headline "Scientists Watch a Memory Form in a Living Brain." The story refers to a study that has  inadequate sample sizes (such as 5 and 11), no blinding protocol, and no pre-registration; but it least it used control groups. Fish were supposedly taught something and then synapses were observed. The result did not even match neuroscientist teachings that memories form from synapse strengthening.  We read this:

"The researchers imaged the pallium before and after the fish learned, and analyzed the changes in synapse strength and location. Contrary to expectation, the synaptic strengths in the pallium remained about the same regardless of whether the fish learned anything.Instead, in the fish that learned, the synapses were pruned from some areas of the pallium — producing an effect 'like cutting a bonsai tree,' Fraser said — and replanted in others."

There is zero justification for using the term "replanted" here. Very probably, what was being observed was simply random fluctuations in synapse numbers, the type of fluctuations that would have occurred even if nothing had been learned, and even if an organism had been sleeping.  Referring to TFC (tail-flick conditioning, a type of learning), the paper tells us that learning made no difference in the total number of synapses  (using L to mean learners, PL to mean partial learners, NL for non-learners): 

"When the total number of synapses before versus after TFC was compared for L, PL, and controls (CS only, US only, and NS) over the entire pallium, no significant difference was found. A modest decrease (∼10%) was found for NL (Fig. 4A; P > 0.05 for L, PL, and controls; P < 0.05 for NL, Wilcoxon test). Additionally, synapse numbers did not differ significantly between L, NL, PL, and control fish at either time point (SI Appendix, Fig. S5; P > 0.05, Kruskal–Wallis test). Thus, our data indicate that TFC learning is not associated with a significant change in the total number of synapses in the pallium."

To their credit, the paper authors make no unwarranted claim in their paper title or abstract. The paper title is "Regional synapse gain and loss accompany memory formation in larval zebrafish."  Yes, synapses are gained and lost when you form a memory -- and also when you don't form a memory.  Synapse gain and loss is continual throughout the brain, regardless of memory formation, largely because synapse proteins last for only about two weeks or shorter, and because individual synapses don't last for longer than one or a few years.  Deplorably, Quanta Magazine has reported this result (doing nothing to show that memories are formed in brains) with the groundless headline "Scientists Watch a Memory Form in a Living Brain." 

"Red Lights Everywhere": Why Brains Must Be Way Too Slow for Instant Recall and Fast Thinking

Claims that brains store memories and produce thinking are not well-established scientific facts, but mere speech customs of neuroscientists who belong to a belief community as dogmatic as the communities of organized religions. Such neuroscientists tend to pay shockingly little attention to the implications of the low-level findings neuroscientists have made about brains.  Replacing its proteins at a rate of about 3% every day, brains are neither stable enough nor fast enough to explain things such as the instant accurate recall of 50-year-old memories.  

People who write about the brain frequently use a trick to make you think that brains are very fast. Such people will tell you that brain signals can travel up to 100 meters per second. But this is the speed when signals pass through the fastest tiny parts of the brain. This is the speed of signals when they travel through what is called a myelinated axon. The mylein sheath around the axon (with a white color) is what makes it so fast. It is interesting that the site here says, "The axons of grey matter are not heavily myelinated, unlike white matter, which contains a high concentration of myelin." Axons without much of a myelin sheath are believed to transmit brain signals about 5 times slower.  According to the diagram here, signals travel across myelinated axons at speeds between about 20 and 120 meters per second (depending on the thickness of the axon), and signals travel between unmyelinated axons between about 5 and 25 meters per second.

But citing a speed of meters per second for the speed of a brain signal is very misleading. It is as misleading as saying that you can drive through New York City very quickly, on the grounds that you can reach a speed of 30 or 40 miles per hour.  Considering only such a maximum speed is misleading, because when you travel through  New York City, you will be slowed down by many red lights.  Similarly, while some microscopic parts of the brain allow a fast transmission of signals, there are very many microscopic parts of the brain which very much slow down brain signals.   You might figuratively put it this way: the brain has billions of red lights all over the place, and each of those spots will slow down the speed of a brain signal.  So while the maximum speed of a brain signal during any millionth of a second may be as high as meters per second, the average speed of a brain signal is much, much slower, something on the order of one centimeter per second or slower. 

The schematic diagram below illustrates the point. We see a diagram of a neuron, one of the billions of cells that make up the brain. Protruding from the main part of the neuron are dendrites. The transmission of signals through dendrites is slow, so next to the dendrites is a snail icon representing how slow such units are. According to neuroscientist Nikolaos C Aggelopoulos, there is an estimate of 0.5 meters per second for the speed of nerve transmission across dendrites (see here for a similar estimate). That is a speed 200 times slower than the nerve transmission speed commonly quoted for myelinated axons.  Such a speed bump seems more important when we consider a quote by UCLA neurophysicist Mayank Mehta: "Dendrites make up more than 90 percent of neural tissue."  Given such a percentage, and such a conduction speed across dendrites, it would seem that the average transmission speed of a brain must be only a very small fraction of the meters-per-second transmission in axons. 

In the diagram above, we see a chain-like unit in the middle. That part is a myelinated axon, which can transmit a brain signal quickly. So I have put a rabbit icon next to that part, to indicate the relatively speedy signal transmission of that part. 

The bottom right part of the diagram shows some axon terminals that have synapses at their ends. Synapses are a serious "speed bump" for signal transmission in a brain. So I have put a snail icon at the bottom right of the diagram to indicate that slowness. 

How much of a "speed bump" are synapses? There are two types of synapses: slow chemical synapses and relatively fast electrical synapses. The parts of the brain allegedly involved in thought and memory have almost entirely chemical synapses. (The sources here and here and here and here and here refer to electrical synapses as "rare."  The neurosurgeon Jeffrey Schweitzer refers here to electrical synapses as "rare."  The paper here tells us on page 401 that electrical synapses -- also called gap junctions -- have only "been described very rarely" in the neocortex of the brain. This paper says that electrical synapses are a "small minority of synapses in the brain.")

We know of a reason why transmission of a nerve signal across chemical synapses should be relatively sluggish. When a nerve signal comes to the head of a chemical synapse, it can no longer travel across the synapse electrically. It must travel by neurotransmitter molecules diffusing across the gap of the synapse. This is much, much slower than what goes on in an axon.

Diffusion across a synaptic gap

There is a scientific term used for the delay caused when a nerve signal travels across a synapse. The delay is called the synaptic delay. According to this 1965 scientific paper, most synaptic delays are about .5 milliseconds, but there are also quite a few as long as 2 to 4 milliseconds. A more recent (and probably more reliable) estimate was made in a 2000 paper studying the prefrontal monkey cortex. That paper says, "the synaptic delay, estimated from the y-axis intercepts of the linear regressions, was 2.29" milliseconds. It is very important to realize that this synaptic delay is not the total delay caused by a nerve signal as it passes across different synapses. The synaptic delay is the delay caused each and every time that the nerve signal passes across a synapse. 

Such a delay may not seem like too much of a speed bump. But consider just how many such "synaptic delays" would have to occur for a brain signal to travel from one region of the brain to another. It has been estimated that the brain contains 100 trillion synapses (a neuron may have thousands of them).  So it would seem that for a neural signal to travel from one part of the brain to another part of the brain that is a distance away only 5% or 10% of the length of the brain, that such a signal would have to endure many thousands of such "synaptic delays" resulting in a cumulative synaptic delay of quite a few seconds of time.

The problem is that we know humans can instantly recall obscure pieces of information, and instantly do complex calculations.  We see this on TV shows such as Jeopardy,  where people again and again give correct answers after a delay of only about 1 second when being presented surprise pieces of very obscure information such as "Works of this Nobel Prize winner include Song of Solomon and Beloved," and "This was the city where King Louis XIV died." It is well known that certain people (some called autistic savants) can do things like instantly tell you the day of the week for any day you select in the century. There are some math calculation prodigies who can actually calculate faster than any person using a hand calculator. It is impossible to account for such speed under the theory that your brain stores your memories and your brain produces your thoughts. 

Here are all the time factors we would need to account for under a theory of neural memory storage:

(1) The time needed to find where a memory was in the brain.  Since the brain has no indexing system, no addressing system, no coordinate system, and no position notation system, we can only assume that this would be a very long time, like the time required to find a needle in a haystack. 

(2) The time needed for an encoded memory stored neurally to be decoded and translated into a thought ending up in your mind.  That would take quite a while. We know that it takes quite a while (many seconds) for the brain to do the only type of decoding known to occur in it, the decoding of genetic information stored in DNA (a type of decoding incomparably simpler than the fantastically complex decoding that would be needed to decode some memory encoded as neural states or synapse states). 

(3) The time needed for signals to travel around in your brain. That would take quite a few seconds, because signals would have to travel across thousands of synapses, each of which would produce a synaptic delay (and also thousands of dendrites that would slow down things). 

In short, there are multiple redundant reasons why you would never be able to recall something instantly if memories were stored in your brain.  The slowness of brain signals also means very rapid thinking cannot be a brain effect. An example of rapid thinking is that when asked in a competition what was 869,463,853 times 73, Neelakantha Bhanu Prakash correctly gave the answer of 63,470,861,269 in only 26 seconds. Similarly, Scott Flansburg added a randomly selected two-digit number (38) to itself 36 times, in only 15 seconds. Such calculations could never occur that quickly if it were performed by a brain with "red lights all over the place."

I'll give an example of a type of question no one would be able to answer in a short time if recall and thinking were the products of the brain. Consider the question: which Broadway composer may remind you of a children's TV show? Many people my age can answer such a question fairly quickly. But think of how much mental activity it involves:

(1) Scanning through your very diverse memories of the names of Broadway composers.

(2) Scanning through your very diverse memories of the names of children's TV shows.

(3) Looking for some kind of fuzzy match (not an exact match) between the two different groups of items. 

The correct answer is: Rodgers, because the great Broadway composer Richard Rodgers has a name sound-matching the name in the once-famous children's TV show "Mr. Roger's Neighborhood." It would take you hours or days to answer such a question if you had to use slow synapses and slow dendrites to solve it, searching through a brain without any indexing system or coordinate system; but many people my age could answer such a question in a few seconds. 

It would be very incorrect to suggest that when humans remember, they always only use some memory acquired at one time.  For example, ask a man to describe the difference between modern living and ancient living, and someone might quickly say something like this:

"We use cars not chariots, and fight with armored divisions not legions. We message with emails not carrier pigeons.  We read using  smartphones not scrolls, and wear trousers not togas. We pray to Jesus not Jupiter. We are paid with direct deposits, not coins."

Such a simple response could easily occur in a few seconds, but if brains store our memories, it would require finding, retrieving, understanding and intelligently using information stored in a dozen different little spots in a brain (a brain without an addressing system or indexing allowing fast retrieval). So it would take a long time, and could never occur instantly. 

A scientific paper suggests that neuroscientists are not paying proper attention to signal delays when calculating the speed of brain signals. It says, "Despite their inevitable physiological significance in living systems, propagation delays are usually overlooked in mathematical models, presumably to avoid further complexity."  That's as silly as calculating the time it would take you to drive through the middle of New York City without taking into account the time spent at traffic lights.  

Focal seizures in the brain propagate at a speed of about 1 millimeter per second. We read the following in one paper about the speed of seizures:

"The spread of activity through cortical circuits has been studied in experiments by means of electrical registrations and optical imaging [1–3], and high-density microelectrode arrays [4]. Experiments show slow propagation of an ictal wavefront and fast spread of discharges behind the front [3] [5]. The ictal wavefront progresses through the cortical area at a pace of < 1 mm/s, which is consistent with propagation speeds measured with electrodes and imaging in brain slice models [1, 2, 6–9] and in vivo (0.6 mm/s in [10] with two-photon microscope and 0.5 mm/s in [11] with widefield imaging in mouse neocortex)."

There is no particular reason for thinking that information-transmitting brain signals in the cortex would travel very many times faster than this low speed of about 1 millimeter per second.  The surface area of the brain is about 2500 square centimeters (about 2,500,000 square millimeters), about the size of a pillow case.  The brain can fit in the skull because of extensive folding, rather like a pillow case folded up to fit inside your coat pocket. If brain signals travel about as fast as seizures, it would take something like 1500 seconds (or 25 minutes) for some thought to travel from the middle of one brain half to the middle of another. 

A 2020 paper was entitled "Kilohertz two-photon fluorescence microscopy imaging of neural activity in vivo." It used some fancy new technology to clock the speed of brain signals in a living mouse, a "latest and greatest" technology that takes thousands of snapshots every second. The paper has only one exact mention of a speed: supplementary Figure 5 of the paper refers to a calcium propagating speed of about 25 microns per second, which is a very slow speed of only about 0.0025 centimeters per second (about .02 millimeters per second). If human brain signals travel at anything like such a speed, the brain must be way, way too slow to be the cause of instant recall and fast problem solving. 

We do not think at anything remotely like the speed of brains. We do not recall at anything remotely like the speed of brains. We think and recall at the speed of souls.

The Two Biggest Brain Projects Have Failed to Bolster the Main Dogmas About Brains

In recent years the two largest brain research projects have been a big US project launched in 2013 called the BRAIN Initiative, and a big European Union project launched in 2013 called the Human Brain Project. In July 2018 I wrote a post describing how the BRAIN Initiative had failed to substantiate claims that the human brain is a storage place for memories and that the human brain is the source of our thinking, consciousness and imagination.  Looking at an article on the BRAIN Initiative's web site recapping what the big project did in 2019, I see no reason for thinking that the situation has changed very much. 

It's rather a bad sign when this "2019 Highlights" article starts off by mentioning some silly experiment in which signs of activity were looked for in the brains of dead pigs a few hours after they died.  After some discussion of some research that merely classified cell types and mapped brain circuits,  there is mention of a study indicating that the human mind can perform well when one half of the brain is removed. But that isn't a discovery of the BRAIN Initiative, and was proven by hemispherectomy operations that occurred long before the BRAIN Initiative started.  Moreover, the finding that he human mind can perform well when one half of the brain is removed is one that is diametrically opposed to the dogmas that the BRAIN Initiative has been trying to prove, claims that the brain is the source of your mind and the storage place of your memories.

Next in the "2019 Highlights" article we have a huge visual of a Science  cover talking about the neurobiology of singing mice, along with a claim that some scientist "measured brain activity in musical mice while they sang duets."  This is not something that should inspire our confidence, since mice can't really sing.  There is no further discussion in the "2019 Highlights" article of anything that  backs up the main dogmatic claims that neuroscientists keep making about brains.  Judging from the article, the BRAIN Initiative is not making very dramatic progress. 

I looked at a News page of the BRAIN Initiative site, to see signs of any recent progress it may have made in trying to prove the things it is trying to prove. I get some links to unimpressive research papers such as this one, "The Anterior Cingulate Cortex Predicts Future States to Mediate Model-Based Action Selection." The paper does not actually provide any good evidence that some brain region is predicting anything, because the study suffered from the usual methodological defects of neuroscience experimental studies.  One of the study groups consisted of only 4 animals, another study group consisted of only 2 animals, and three other study groups consisted of only 8 animals. The chance of a false alarm is too high with such tiny study groups. We should ignore most experimental studies that fail to use at least 15 animals for each study group. Moreover, the study makes no mention of any blinding protocol, something important to have for a reliable experimental study; and the study was also was not a pre-registered study that committed itself to testing a particular hypothesis with a particular methodology.  With so many shortcomings in the study, the BRAIN Initiative should not have had a headline of "Brain Region Implicated in Predicting the Consequences of Actions" to describe this study, since the study did not provide robust evidence of such a thing.

Looking back through all the articles listed on the News page, and going back all the way to July 2019, I can find no sign of any research that substantiates in any robust way any of the dogmas that the BRAIN Initiative has been trying to prove, such as the very dubious claim that the "brain records, processes, uses, stores, and retrieves vast quantities of information." While we know that humans can acquire memories and retrieve memories, and we know that brain cells (like all cells) store genetic information, there is no robust evidence that the brain stores or retrieves memory information, and no credible detailed theory of how any neural storage or instant retrieval of human episodic memory information could occur. The proteins in synapses and brain tissue are so short-lived (having an average lifetime of less than two weeks) that the brain cannot be a place where memories could be stored for 50 years or more. 

On one page of the BRAIN Initiative site, we have a long discussion of some year 2020 symposium featuring speakers funded by the BRAIN Initiative, something called the 6th Annual BRAIN Initiative Investigators Meeting.  There is lots of talk about neuroscience research, but nothing substantially supporting claims that brains produce thinking and store memories. I find no use of the words "thought," "thinking," "consciousness", "imagination," "cognition," "reasoning" or "mind." Here are the only references to memory in the long symposium recap:

"Dr. Nanthia Suthana explained how stimulating and recording deep brain activity could help us understand the neurophysiology of hypervigilance and emotional memory in patients with post-traumatic stress disorder....Dr. Kareem Zhangloul explained the relationship between cortical spiking sequences and memory retrieval in humans."

There's no link to any work by these two, and no one has actually established any relationship between brain spiking sequences and memory retrieval. Searching for a paper by Kareem Zhangloul I find a paper that makes these not very exciting claims:

"Bursts of spikes organized into sequences during memory formation. These sequences were replayed during successful memory retrieval. The extent of sequence replay during correct recall was related to the extent to which cortical spiking activity was coupled with ripples in the medial temporal lobe."

Given the fact that the brain is a constant source of electrical activity, with most of its billions of neurons firing more than once per second, we should expect to be able to find by chance some sequences of spikes that occurred both during memory formation and memory retrieval, regardless of whether memories are stored in brains.  So such research does not qualify as evidence that memories are retrieved from brains. The type of pareidolia going on in such analysis is rather like what would be going on if you had random fluctuation seismograph readings from hundreds of worldwide sites, and found (upon diligent searching) similar patterns during several different Sunday games when the Pittsburgh Steelers played football. 

The BRAIN Initiative page here is entitled "Key Moments in Brain Research." The subtitle is "Explore major milestones in the history of the field, including those stemming from BRAIN-related research programs."  But while there's lots of discussion of about administrative milestones and funding milestones, there's no mention of any research accomplishments of the BRAIN Initiative other than a mention of a classification of brain cell types. There is a mention of a Nobel prize, but that was for research done before the BRAIN Initiative started.   

Like the BRAIN Initiative, the EU's Human Brain Project has announced goals of proving conventional dogmas about the brain. At the page here we read that "the HBP is conducting a coordinated series of experiments to identify the neuronal mechanisms behind episodic memory, and validate them by computational models and robotic systems."  This is an assertion of the unproven dogma that episodic memory can be explained by brain processes; and it is a strange statement, given how silly it is to think that such a dogma could be validated by doing computer models or research into robots.  One of the main tabs of the Human Brain Project has the silly title of "Silicon Brains." No such things exist; brains are brains, and computers are computers. The brain bears no resemblance to a digital computer, and has none of the seven things that a computer uses to store and retrieve information.  Another page of the Human Brain Project has a title of "Understanding Cognition," but makes no mention of any study or experiment backing up the claim that cognition is produced by brains. 

The page here on the Human Brain Project site is entitled "Highlights and Achievements."  But while the page refers to many different scientific studies between 2017 and 2020, it provides no good evidence that the Human Brain Project has done anything to substantiate claims that the brain stores memories or that the brain produces consciousness, selfhood, thinking, creativity or imagination.  Below are some of the studies mentioned.

• There is a link to a page entitled "Dendrite Activity May Boost Brain Processing Power." But the page confesses, "Neurologically speaking, the physiology that makes the human brain so particularly special and capable remains poorly understood," which makes it sound as if neuroscientists have no factual claims backing up their dogmas about the brain. 
• There is a link to a page entitled "The Way of Making Memories." But the page does not discuss any substantial progress in understanding memory, but merely mentions some hardly-worth-mentioning paper entitled, "Regulation of adenylyl cyclase 5 in striatal neurons confers the ability to detect coincident neuromodulatory signals." 
• There is a link to a page entitled "Brains of smarter people have bigger and faster neurons." The page merely refers to a scientific study that fails to establish such a claim. The study only provided data on brain characteristics and IQ for about 25 subjects, and merely found weak correlations such as r= .37 and r= .46 and r = .51.  The site here says, "The relationship between two variables is generally considered strong when their r value is larger than 0.7." Having such a small study group and such not-very-strong correlations, the study does not justify the claim that brains of smarter people have bigger and faster neurons. It is very easy to get by chance a not-very-strong correlation such as .5 between two unrelated things such as hair length and intelligence, from a check of only a small number of subjects (the likelihood of getting a correlation between unrelated things decreases as the number of subjects rises). The study was not a pre-registered study, so we have no idea whether the authors were checking 50 different things, and reporting on a few cases where a not-very-strong correlation was found by chance variation.  To have confidence in a study like this (which could so easily go wrong through subjective analysis), the study would have to have a detailed discussion  of how a full-fledged blinding protocol was followed. Instead there is merely a one sentence mention of some half measures to produce a blinding effect. The study lists six patients who scored above 100 in IQ tests just before surgery for brain tumors, which in not what we would expect if brains were producing human intelligence. 
• There is a link to a page entitled "How brain cells work together to remember and imagine places." But the page does not discuss any evidence for a brain storage of memories or a brain explanation for imagination. It merely discusses a "computational model."
• There is a link to a page entitled, "Individual Brain Charting: A high-resolution brain map of cognitive functions." But the title is misleading, because it merely discusses some brain scans taken when 12 people were doing particular things.  The page has the typical misleading language about such scans, saying, "The images obtained make it possible to specify which regions of the brain are activated during a given task." All regions of the brain are active at all times, and brain scans merely show tiny variations such as half of one percent from one region to another, which could easily be chance fluctuations. It is misleading to say that a region showing less than 1% greater activity are "activated during a different task." 
• There is a link to a page entitled, "A First Principles Approach to Memory Recall." But we get no evidence that neuroscientists understand memory recall, something that has never been credibly explained as a brain process. On the page a neuroscientist states this:

“In Neuroscience, there is nothing you can really predict. We do not know how things really work, and the brain is so complex. Both these things mean you cannot make quantitative predictions."

This creates no impression at all that neuroscientists have facts that prove the dogmas they keep spouting about the brain. 

We should not be impressed by occasional studies that may create some superficial impression that the main assumptions of neuroscientists are correct. Given a huge army of experimental neuroscientists funded each year with so many millions of dollars, it is inevitable that now and then a few weak signals might come forth suggesting some reality behind their assumptions, no matter how wrong they are. Similarly, if you recruit some huge army of people who believe that some clouds are the ghosts of dead animals, and you fund such people with many millions of research money each year, you might occasionally get photos of clouds that might make you think, "Wow, that really looks like the ghost of a dead animal."

The Human Brain Project and the BRAIN Initiative continue to get very many millions of dollars of funding every year. But the web site of the BRAIN Initiative and the web site of the Human Brain Project very much suggest that these lavishly funded projects are failing to substantiate the dogmatic claims about the brain that they are attempting to prove.  Such a failure should surprise no one, because these dogmatic claims (such as the claim that brains store memories and the claims that brains produce minds) are implausible, and are contradicted by many neuroscience facts that have already been established, such as:

• the very short lifetime of brain proteins, only a thousandth of the longest length of time that humans can reliably remember things (60 years);
• the lack of any indexing system or position notation system in a brain that might make possible instant memory recall;
• the failure to discover any proteins or brain mechanisms capable of translating human learned knowledge or episodic memories into synapse states or neuron states;
•  the ability of minds to function and remember very well when half of brains are removed;
• the ability of minds to function very well during near-death experiences occuring during cardiac arrest when brains are shut down;
• the very high levels of noise (and very low levels of synaptic signal transmission reliability) in brains, which should preclude a brain from being able to achieve accurate recall of any detailed memory information; 
• the lack of any mechanism in the brain for reading or writing memories, and the lack of anything analagous to the read/write head of a computer hard disk;
• the slow speed at which brain signals travel across dendrites and synapses, which should prevent any instant recall of memories;
• the failure to find any permanent encoded information in brains other than the genetic DNA information in all cells.

The physical reality of your brain

The paper here discusses some big Chinese multi-year brain project. There is no mention of any research strategy that offers any real hope of backing up standard dogmas about the brain.  In a section entitled "Neural Circuit Mechansims of Cognition," which tries to sell the groundless idea that cognition might be understood through the study of neural circuits, the author states, "Optimists among us may expect within the next two decades the completion of mesoscopic mapping of neural circuits and their activity patterns, and perhaps even the underlying logic and mechanisms, of cognitive processes in animal models such as Drosophila, zebrafish, and rodents."  Clearly our neuroscientists have no understanding of how neural circuits can explain human cognition. Such scientists merely have the hope that two decades of additional study of neural circuits might throw some light on cognition in animals like rats.  There is no reason to suspect that studying the exact way electricity moves around in the brain (the study of neural circuits) will ever explain human mental phenomena such as thought, memory, insight, self-hood and imagination. 

Exhibit B Suggesting Scientists Don't Know How a Brain Could Retrieve a Memory

In a 2019 post “Exhibit A Suggesting Scientists Don't Know How a Brain Could Retrieve a Memory,” I took a close look at 68 “expert answers” given on one page of an “expert answers” site, a page with the topic of "how are memories retrieved in the brain?" I argued  that none of the experts had a coherent and convincing answer to the question “how are memories retrieved in the brain?” I maintain that answering such a question convincingly will always be impossible, because human memories are not stored in brains, and nothing in the human brain bears any resemblance to either  a device for retrieving factual information learned during human experience or a device for storing memories for years. In particular, there is not any thing in the human brain that can explain how a human brain can instantly retrieve detailed information learned long ago about about some obscure person, place or event. Since the brain lacks any addressing system, any indexing system, and any position notation system, it should be absolutely impossible for a brain to instantly recall obscure information, such as we see happening on the long-running television quiz show Jeopardy. For example, if someone asks you (for the first time ever in your life) to name three Russian composers, and you instantly answer “Tchaikovsky, Borodin, and Rimsky-Korsakov,” you are doing something absolutely inexplicable in terms of brain activity.

Now I will give a kind of “Exhibit B” suggesting that scientists don't know how a brain could retrieve a memory: a 2019 paper entitled “The neurobiological foundation of memory retrieval.” When we get beyond the hype and unwarranted braggadocio of this paper, we find that it fails to convincingly portray any such foundation at all.

A great deal of the paper is involved with trying to persuade us that experimental studies have made great progress in identifying memory storage sites (called engrams). The authors state, “In the last decade, enormous progress has been made in identifying and manipulating engrams in rodents.” This statement is not at all correct. A few scattered studies have claimed to identify and manipulate such alleged engrams, but such studies have failed to provide any convincing evidence that such engrams really exist. The studies typically suffer from several of the following methodological 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.

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

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

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.

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."

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.

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.

I fully discuss all of these methodological problems in my post “The Seven Sins of Memory Engram Experiments,” and I give very many examples of how the papers cited as evidence for engrams in rodents are guilty of such procedural sins. So when the authors of the paper “The neurobiological foundation of memory retrieval” assert that "enormous progress has been made in identifying and manipulating engrams in rodents,” they do not speak correctly at all. There still exists no robust well-replicated evidence that any such thing as an engram (a neural site of stored learned information) exists in any animal. 

The authors present a lengthy, credulous and uncritical review of weak neuroscience studies that have attempted to find evidence for memory engrams (neural storage sites for memories). Their review repeatedly fails to subject such studies to an appropriate level of scrutiny. The authors  trumpet weak and poorly replicated studies as evidence for the memory engrams that they  want to believe in. We hear no mention of the very many problems in such studies, such as the fact that they typically use unreliable bias-prone techniques for judging the degree of fear in rodents (subjective judgments about "freezing behavior") rather than reliable objective techniques such as heart-rate measurement (the heart rate of a rat dramatically surges when the rat is afraid). 

In the section entitled “Retrieval as neuronal reinstatement,” we have the main part of the authors' ideas about how memory retrieval might work in a brain. Get beyond the dense layers of jargon, digressions and circumlocutions, and we find very little of substance. Their basic idea is that “natural retrieval cues reactivate neural ensembles active at encoding.” “Encoding” is a jargon term used by neuroscientists to describe some process that allegedly occurs when learned information is translated into neural states or synapse states. Despite the fact that the term “encoding” has been constantly used in scientific papers, we have neither any good evidence that such encoding occurs (in the sense of knowledge being translated into neural or synapse states), nor any coherent theory as to how it possibly could occur (there being an ocean of difficulties in the idea that human experience or conceptual knowledge could ever be translated into neural states). We merely have evidence that human beings remember things.

Neuroscientists so often use the term “encoding” that one way to interpret the word is to simply use it as a synonym for learning or memory acquisition. So using that interpretation, we can regard “natural retrieval cues reactivate neural ensembles active at encoding” as simply meaning “when you recall something, your brain reactivates some part of the brain that you used in learning the thing or experiencing the thing recalled.”

When we consider how a brain works, and the fact that all parts of it are constantly active, we can realize that such an explanation for memory retrieval is vacuous or untenable. All neurons in the human brain are constantly firing. Each neuron fires multiple times per minute. So we cannot at all explain a memory recollection as being a case where some tiny part of the brain was “activated,” as if that tiny part was the only part active. All neurons are constantly active.

Brain scanning studies contradict the claim that some little part of the brain (where some memory might be stored) is activated to a higher degree during memory recall.  Excluding the visual cortex that may be to used to kind of visually enhance some memory that was retrieved, such studies show that when humans recall things, there is no brain area that has even a 1% greater activation than any other brain area. Here are some specific numbers from particular studies:

• This brain scan study was entitled “Working Memory Retrieval: Contributions of the Left Prefrontal Cortex, the Left Posterior Parietal Cortex, and the Hippocampus.” Figure 4 and Figure 5 of the study shows that none of the memory retrievals produced more than a .3 percent signal change, so they all involved signal changes of less than 1 part in 333.
• In this study, brain scans were done during recognition activities, looking for signs of increased brain activity in the hippocampus, a region of the brain often described as some center of brain memory involvement. But the percent signal change is never more than .2 percent, that is, never more than 1 part in 500.
• The paper here is entitled, “Functional-anatomic correlates of remembering and knowing.” It shows a graph showing a percent signal change in the brain during memory retrieval that is no greater than .3 percent, less than 1 part in 300.
• The paper here is entitled “The neural correlates of specific versus general autobiographical memory construction and elaboration.” It shows various graphs showing a percent signal change in the brain during memory retrieval that is no greater than .07 percent, less than 1 part in 1000.
• The paper here is entitled “Neural correlates of true memory, false memory, and deception." It shows various graphs showing a percent signal change during memory retrieval that is no greater than .4 percent, 1 part in 250.
• This paper did a review of 12 other brain scanning studies pertaining to the neural correlates of recollection. Figure 3 of the paper shows an average signal change for different parts of the brain of only about .4 percent, 1 part in 250.
• This paper was entitled “Neural correlates of emotional memories: a review of evidence from brain imaging studies.” We learn from Figure 2 that none of the percent signal changes were greater than .4 percent,  1 part in 250.
• This study was entitled “Sex Differences in the Neural Correlates of Specific and General Autobiographical Memory.” Figure 2 shows that none of the differences in brain activity (for men or women) involved a percent signal change of more than .3 percent or 1 part in 333.

So it simply is not true that when you recall something, there is some substantially greater activation of some region of your brain where the memory is stored.  The claim that "natural retrieval cues reactivate neural ensembles active at encoding" basically means merely "your brain uses the information that it stored somewhere," but such an idea doesn't explain how a human brain supposedly storing very many thousands or millions of learned items of information could ever instantly find just the right neurons to use to cause you to instantly recall just the right piece of information when you are asked a specific question such as "What jobs did Ulysses Grant have?" 

There are many seemingly insurmountable problems that would have to be tackled by any theory of neural memory retrieval. The first is what I call the navigation problem. This is the problem that if a memory were to be stored on some exact tiny spot on the brain, it would seem that there would be no way for a brain to instantly find just that little spot. For that to occur would be like someone instantly finding a needle in a mountain-sized haystack, or like someone instantly finding just the right book in a vast library in which books were shelved in random positions. Neurons are not addressable, and have no neuron numbers or neuron addresses. So, for example, we cannot imagine that the brain instantly finds your memory image of Marilyn Monroe (when you hear her name) because the brain knows that such information is stored at neural location #239355235.  There are no such "neural addresses" in the brain. 

Then there is also the fact that the brain seems to have nothing like a read mechanism by which some small group of neurons are given special attention. The hard disk of a computer has a read/write head, but there's nothing like that in the brain. 

Then there is the fact that if memory information were encoded into neural states, the brain would have to decode that encoded information; but such a decoding would seem to require time that would prevent instantaneous recall. When cells do vastly simpler decoding involved in decoding DNA information, it takes cells many seconds or minutes. We would expect that any decoding of encoded information stored in a brain would take many seconds or minutes, preventing any such thing as instantaneous recall of rarely-remembered data items. In addition, we have not the slightest idea of how human learned information (with so many diverse forms) could either be translated or encoded into neural states, or decoded back into thoughts once such translated or encoded knowledge was decoded.  There exist hundreds of genes for the relatively simple job of decoding the genetic information in DNA. If human learned information and experiences (with so many diverse forms) were to be translated into neural or synapse states, so that learned information could be stored in a brain, there would need to be many hundreds or thousands of genes and proteins devoted to so complex a task. But no such genes and proteins seem to exist, and no one has proven that any gene or protein is dedicated to the task of memory encoding or decoding. 

None of these problems are addressed by the paper "The neurobiological foundation of memory retrieval."  The authors simply ignore the whole speed problem of explaining instant memory recall.  Their paper makes no mention of such a thing, and doesn't use words such as "speed" or "quick" or "fast" or "instant" or "instantaneous."  The authors also ignore the issue of how a brain could decode (during memory retrieval) encoded information stored in a brain. Their paper does not use the words "decode," "decoding" or "translate."  The paper merely refers in passing to some research they claim has "potentially interesting translational implications," but give no details to clarify such a claim.  Nor does the paper have any discussion of some theory of a read mechanism that could be used to read memories from brains. Searching for the word "read" in the paper produces no relevant sentences. 

Any real theory of a neural retrieval of memories would have to also be a theory of the storage and encoding of such memories. There can be no understanding of how some memories could be read from neurons or synapses or decoded unless you had an understanding of how such memories were stored and encoded in neurons or synapses.  But the paper "The neurobiological foundation of memory retrieval" gives no theory of how a brain could store learned information. The paper does make quite a few uses of the word "encoding," but simply uses that as a synonym for "learning" or "memory acquisition" without doing anything to explain how learned information could be translated into neural states. 

So the paper claiming to elucidate a "neurobiological foundation of memory retrieval" fails to discuss in any substantive way any of the main things that would need to be explained by an actual theory or understanding of how a brain could retrieve a memory: (1) how a brain could instantly find just the right tiny engram where a memory was stored in it; (2) how a brain could read information stored in it; (3) how a brain could perform the miracle of instantly decoding such learned information that had been encoded in neural states or synapse states, acting 1000 times faster than cells do when they decode DNA information; (4) what miracle of translation would have allowed information so diverse to ever have been encoded as neural states or synapse states in the first place. The paper is additional evidence that our scientists have no actual understanding of how a brain could instantly retrieve a memory. There does not exist any such thing as a "neurobiological foundation of memory retrieval." Humans and animals remember things, but neither scanning their brains during memory activity nor rat experiments provide any insight as to how instantaneous recall of specific learned items (or any recall at all of such items) can occur. 

The lack of any real understanding on this matter is almost admitted by the paper in question, which states at its end, "Our understanding of the neurobiological underpinnings of retrieval remains rudimentary." That is not how it would be in the year 2020 (70 years after the discovery of DNA) if human brains actually performed memory retrieval.  In a brain that stored and retrieved memories, there would have been signs of its memory storage and retrieval mechanism discoverable around 1950; and around the same time we discovered the readable microscopic encoded information in DNA, around 1950, we would have discovered readable encoded memory information in brains (something which still has not been found).  Instead of finding any evidence for proteins dedicated to encoding memories,  which would have to exist in massive numbers if a brain stored memories, what was found was that the proteins in synapses (the alleged storage place of memories) have lifetimes 1000 times shorter than the maximum age of human memories.