How We Got Misinformed About "Grandmother Cells"

Each neuron fires between about 1 and 200 times per second, with the firing rate being unpredictable. So neurons are a noisy, unpredictable signal source; and that kind of source provides opportunities for noise mining and pareidolia, the occasional finding of some desired pattern by people scanning noisy, variable data looking for such a pattern. Similarly, at a restaurant that makes 200 pieces of toast every day using different types of bread, there is an opportunity for noise mining, in which someone checking each piece of toast may eventually claim to see the face of Jesus in a slice of toast. 

Let us look at the history of claims of "grandmother cells." The term refer to some neuron that might allegedly respond only when a person sees some particular type of visual, such as a picture of the person's grandmother. The 2002 article "Genealogy of the 'Grandmother Cell'" by the late Charles G. Gross gives us some background on how the idea of such a cell got started. Gross tells us this:

"The term originated in a parable Jerry Lettvin told in 1967. A similar concept had been systematically developed a few years earlier by Jerzy Konorski who called such cells 'gnostic' units."

So according to Gross, the concept of a "grandmother cell" arose independently of observations, without any empirical warrant.  But then Gross starts telling an unwarranted self-serving tale that evidence was found supportive of such an idea. He claims, "In the early 1970s, my colleagues and I working at M.I.T. in Cambridge, Massachusetts, reported visual neurons in the inferior temporal cortex of the monkey that fired selectively to hands and faces (Gross and others 1969, 1972; Gross 1998a)." Gross is here engaging in self-citation. Let us look at the papers Gross refers to, and see whether they actually gave any evidence to back up such a claim. 

• The 1969 paper "Visual Receptive Fields of Neurons in Inferotemporal Cortex of the Monkey" by Gross and others which you can read here. We have no specific data backing up any claim that anything had been found like a neuron that only responds to some particular image. We merely have this vague statement: "There were several units that responded most strongly to more complicated figures. For example, one unit that responded to dark rectangles responded much more strongly to a cutout of a monkey hand, and the more the stimulus looked like a hand, the more strongly the unit responded to it." The paper gives no data backing up such a claim. 
• The 1972 paper by Gross is the paper "Visual properties of neurons in inferotemporal cortex of the macaque." Only the first page of the paper is publicly available here. That page makes no claim backing up claims of anything like a grandmother cell. 
• The "Gross 1998a" citation is a citation of the book "Brain, Vision, Memory" by Gross, which you can read here.  On page 198 Gross claims that "he did not publish a full account of a face-selective neuron until 1982," which shows that the previous two citations were inappropriate. On the same page Gross misspoke by claiming that "soon thereafter, a flood of papers on such cells appeared." No such flood occurred. He mentions a 1982 paper by Perrett, Rolls and Cann ("Visual Neurones Responsive to Faces in the Monkey Temporal Cortex"), which you can read here. 

Nothing that is in any of these citations supports the claim that anything like a face-selective cell or a hand-selective cell was discovered. If we look at the 1982 paper by Perrett, Rolls and Cann ("Visual Neurones Responsive to Faces in the Monkey Temporal Cortex"), which you can read here, we also find nothing impressive. The paper claims that "Of the 497 cells recorded in the STS region there was a sub-population of at least 48 cells which gave responses to the sight of faces that were two to ten times as large as the responses to other stimuli tested." There is no claim that these cells fired only when other faces were shown, and Figure 3 (cherry-picked as the strongest evidence of a "face responsive cell") shows the cell firing many times when things other than faces were shown. The graphs in the diagram are examples of cherry-picking, showing results from a few cells that seemed to fire the most when the subject was shown faces. 

Some mathematical analysis will show how unimpressive the result discussed above. In the study there were five types of sensory stimuli: faces, gratings/geometric stimuli, complex 3D stimuli, somatosensory stimuli, and auditory stimuli. Let us imagine that we are recording how 497 cells respond when a subject is exposed to one of a small number of categories of stimulus, such as five.  Given a high random variability in how the cells respond, with the firing rates varying randomly between 1 and 200 times per second, and given a relatively small number of trials, and only a small number of types of stimulus (such as only five), we would expect that by chance there would be about 10% of these cells that would fire twice as often or more when a subject is exposed to one of the five types of stimulus. So the reported result that "there was a sub-population of at least 48 cells which gave responses to the sight of faces that were two to ten times as large as the responses to other stimuli tested" is not something unexpected, assuming purely chance results, and no actual "face sensitivity" or "face selectivity" going on in the cells. 

The claim by Gross to have discovered neurons that "fired selectively to faces and hands" was false. Neither he nor anyone else discovered any such thing. All that was going on was noise-mining.  Monkeys were being shown different visual stimuli, including faces and things that were not faces. The firing of hundreds of neurons were recorded, and researchers were drawing attention to the cells that happened to have the highest firing rate when faces were shown. No evidence was being presented of more neuron firing during face observation than we would expect to see from a random set of randomly firing cells that fired with a high variability. 

Later in the 2002 article "Genealogy of the 'Grandmother Cell'" by Charles G. Gross, Gross makes this claim: "Starting 10 years later, these finding were replicated and extended in a number of laboratories (e.g., Perrett and others 1982; Rolls 1984; Yamane and others 1988) and were often viewed as evidence for grandmother cells." The references do not actually refer to any papers providing evidence for grandmother cells. The 1982 Perrett paper is discussed above, and did not find any such evidence, but merely claimed "Of the 497 cells recorded in the STS region there was a sub-population of at least 48 cells which gave responses to the sight of faces that were two to ten times as large as the responses to other stimuli tested."  The Rolls 1984 paper is the paper "Neurons in the cortex of the temporal lobe and in the amygdala of the monkey with responses selective for faces."  It is merely another paper picking out some cells out of hundreds that fired more often when faces were shown, while also firing when things other than faces were shown. 

None of the papers that Gross has cited could intelligently be interpreted as evidence for grandmother cells, so Gross misleads us badly by claiming that such papers "were often viewed as evidence for grandmother cells." Later Gross confesses, "However, most of the reported face-selective cells do not really fit a very strict criteria of grandmother/ gnostic cells in representing a specific percept, that is, a cell narrowly selective for one face and only one face across transformations of size, orientation, and color (Desimone 1991; Gross 1992)." At the end of the paper, Gross deceives us by trying to make it sound like these alleged "face selective" cells may be something like "grandmother cells." But no evidence he has presented or cited has given any evidence for such "grandmother cells." 

The next big development on this topic occurred when scientists started reading the firings of neurons in individual humans. This is something that cannot be done by simply having a person wear an EEG cap on his head. The reading of firings of individual neurons in humans requires the implanting of electrodes into the brain.  Some people with drug-resistant epilepsy have electrodes implanted in their brains so that doctors can figure out where is the best place to do surgery to help cure their epilepsy. Neuroscientists have tried to leverage the implanting of such electrodes, to study the firing of individual neurons in the human brain. 

This has often been a morally objectionable type of activity by neuroscientists. The type of electrodes implanted in a brain to evaluate a patient for epilepsy are called macroelectrodes.  The type of electrodes implanted to record the firing of individual neurons are called microelectrodes. There is never any medical justification for implanting microelectrodes in addition to macroelectrodes. A scientific paper tells us, "Sixty-five years after single units were first recorded in the human brain, there remain no established clinical indications for microelectrode recordings in the presurgical evaluation of patients with epilepsy (Cash and Hochberg, 2015)." In other words, there is no medical justification for implanting microelectrodes in the brains of epilepsy patients. Here is a quote from a scientific paper:

"The effects of penetrating microelectrode implantation on brain tissues according to the literature data...  are as follows:

1. Disruption of the blood–brain barrier (BBB);
2. Tissue deformation;
3. Scarring of the brain tissue around the implant, i.e., gliosis 
4. Chronic inflammation after microelectrode implantation;
5. Neuronal cells loss."

What is going on with attempts to find something like grandmother cells in humans is typically a morally objectionable affair in which very sick people are being put to unnecessary risks for the sake of scientists seeking fame and glory. Such affairs are so morally dubious that we should have a natural tendency to distrust the statements of scientists doing such research, just as we should have a natural tendency to distrust the statements of any person engaged in a reckless or shady activity. 

Similar to claims of a "grandmother cell" are claims of a "Jennifer Aniston neuron" that was activated only when a epileptic subject was shown a picture of Jennifer Aniston. The claim is unfounded, and does not match the data in the original paper. For a discussion of the shady business that went when claims like this were made, see the last seven  paragraphs of my post here. 

At the link here, a vision scientist describes some of what is going in studies like the studies mentioned above:

"Neuroscience, as it is practiced today, is a pseudoscience, largely because it relies on post hoc correlation-fishing....As previously detailed, practitioners simply record some neural activity within a particular time frame; describe some events going on in the lab during the same time frame; then fish around for correlations between the events and the 'data' collected. Correlations, of course, will always be found. Even if, instead of neural recordings and 'stimuli' or 'tasks' we simply used two sets of random numbers, we would find correlations, simply due to chance. What’s more, the bigger the dataset, the more chance correlations we’ll turn out (Calude & Longo (2016)). So this type of exercise will always yield 'results;' and since all we’re called on to do is count and correlate, there’s no way we can fail. Maybe some of our correlations are 'true,' i.e. represent reliable associations; but we have no way of knowing; and in the case of complex systems, it’s extremely unlikely. It’s akin to flipping a coin a number of times, recording the results, and making fancy algorithms linking e.g. the third throw with the sixth, and hundredth, or describing some involved pattern between odd and even throws, etc. The possible constructs, or 'models' we could concoct are endless. But if you repeat the flips, your results will certainly be different, and your algorithms invalid...As Konrad Kording has admitted, practitioners get around the non-replication problem simply by avoiding doing replications.” 

Later in the same scientist's blog, we read this year 2023 comment: "Articles published during the past decade bemoaning the inability of mainstream neuroscience to generate replicable or even reproducible outcomes are too many to count."  In the same post the scientist states this:

"If we weren't living it, it would be hard to imagine how a research culture could have strayed so far from the path of rationality as has the culture of neuroscience. Fundamental problems in theory and method have long been flagged (e.g. Teller, 1984; Jonas & Kording, 2018; Brette, 2019), but critiques have left barely a trace on the hard-beaten track of routine, mainstream practice."

"Thousands of Participants Are Needed for Accurate Results," But Most Brain Scan Studies Don't Even Use Dozens

For many years neuroscientists have been claiming important results about brains and minds, after doing brain imaging experiments using very small sample sizes.  For example, we may read headlines saying that some particular region of the brain is more active during some type of mental event,  and the total number of subjects who had their brains scanned will usually be smaller than 15. A new press release from the University of Minnesota Twin Cities announces results which indicate that such small-sample correlation-seeking brain imaging experiments are utterly unreliable.  The headline of the press release is "Brain studies show thousands of participants are needed for accurate results."

We read this:

"Scientists rely on brain-wide association studies to measure brain structure and function—using MRI brain scans—and link them to complex characteristics such as personality, behavior, cognition, neurological conditions and mental illness. New research published March 16, 2022 in Nature from the University of Minnesota and Washington University School of Medicine in St. Louis...shows that most published brain-wide association studies are performed with too few participants to yield reliable findings."

The abstract of the paper in the science journal Nature can be read here. The paper is entitled, "Reproducible brain-wide association studies require thousands of individuals." 

The press release tells us this:

"The study used publicly available data sets—involving a total of nearly 50,000 participants—to analyze a range of sample sizes and found:

• Brain-wide association studies need thousands of individuals to achieve higher reproducibility. Typical brain-wide association studies enroll just a few dozen people.
• So-called 'underpowered' studies are susceptible to uncovering strong but misleading associations by chance while missing real but weaker associations. 
• Routinely underpowered brain-wide association studies result in a surplus of strong yet irreproducible findings."

The claim that a typical brain scanning experimental study uses "a few dozen" people is probably an overestimate. Brain imaging studies touted in the press seem to typically involve fewer than 15 subjects. 

The press release tells us that the conclusions above are based on some very heavy number crunching using databases that store brain scans of a large number of people, including in many cases data on what they were doing or thinking while being scanned, what kind of mental characteristics or health history the people had, and what kind of genes the people had.  The largest such database was the UK Biobank, which according to page 5 of the document here includes "resting-state functional MRI measures changes in blood oxygenation associated with intrinsic brain activity (i.e., in the absence of an explicit task or sensory stimulus)," as well as "task-functional MRI" which "uses the same measurement technique as resting-state fMRI, while the subject performs a particular task or experiences a sensory stimulus." (The task was mainly something called the Hariri faces/shapes “emotion” task.)  Another large database used was a Human Connectome Project database including "task-evoked fMRI" brain scans of people while they were doing things involving working memory, gambling, language, social cognition, relational processing and emotional processing (as mentioned on page 36 of the document here).  Another large database used was an Adolescent Brain Cognitive Development (ABCD) database that included fMRI scans while subjects performed tasks such as a Monetary Incentive Delay task. a Stop Signal task and an "n-back" or "nBack" task (as described here). 

In the press release we read this:

"To identify problems with brain-wide association studies, the research team began by accessing the three largest neuroimaging data sets: the Adolescent Brain Cognitive Development Study (11,874 participants), the Human Connectome Project (1,200 participants) and the UK Biobank (35,375 participants). Then, they analyzed the data sets for correlations between brain features and a range of demographic, cognitive, mental health and behavioral measures, using subsets of various sizes. Using separate subsets, they attempted to replicate any identified correlations. In total, they ran billions of analyses, supported by the MIDB Informatics Group and the powerful computing resources of the Minnesota Supercomputing Institute. The researchers found that brain-behavior correlations identified using a sample size of 25—the median sample size in published papers—usually failed to replicate in a separate sample.  As the sample size grew into the thousands, correlations became more likely to be reproduced. Robust reproducibility is critical for today’s clinical research. Senior author Nico Dosenbach, MD, PhD, an associate professor of neurology at Washington University, says the findings reflect a systemic, structural problem with studies that are designed to find correlations between two complex things, such as the brain and behavior."

What this study very strongly indicates is that the vast majority of brain imaging studies trying to correlate brains and mental states or mental activity have misled us by producing false alarms. The study indicates that such brain imaging studies have not merely been guilty of some slight shortfall, but have been guilty of a hundred-fold shortfall (the difference between about 20 and "thousands" being a difference of a hundred times).  It's as bad as if someone told you he produced a score of 1000 on his SAT test, but really only produced a score of 10. 

The study described above was led by neuroscientist Scott Marek. An article on the study in the journal Nature says this:

“ 'There’s a lot of investigators who have committed their careers to doing the kind of science that this paper says is basically junk,' says Russell Poldrack, a cognitive neuroscientist at Stanford University in California, who was one of the paper’s peer reviewers. 'It really forces a rethink.' ”

The New Scientist article on the Marek study is behind a paywall, but at least I can show its headline:

For many years we have been scammed and the US federal government has been scammed by neuroscientists doing ridiculously low-powered brain imaging studies looking for correlations between brains and minds.  For many years our experimental neuroscientists doing small-sample brain imaging studies (looking for correlations between brain states and mental states) have been playing a game of "sham, scam, thank you Sam," the Sam being Uncle Sam who provided the dollars for such worthless studies producing only false alarms. This is a racket, but since it is a nice little source of dishonest income and easy work for professors, the racket will probably long continue. 

The US government seems to be incredibly poor at recognizing bad performance by biology authorities.  In the New York Times there was recently an opinion article with the headline "How Millions of Lives Might Have Been Saved from COVID-19." Without naming any names of the bumbling officials guilty of the bungled US response to COVID-19, we get some startling comparisons between competent responses in small countries and incompetent responses in the US. For example, we are told that Taiwan has suffered only 853 COVID-19 deaths, and that "if the United States had suffered a similar death rate, we would have lost about 12,000 people, instead of nearly a million."  Because the US government seems to be extremely poor at recognizing bad performance by biology authorities. we will probably continue to see the "sham, scam, thank you Sam" researchers bilking the government by doing worthless federally-funded small-sample brain imaging studies producing only  false alarms. 

One of the quotes above tells us that correlations reported with a sample size of 25 "usually failed to replicate in a separate sample," but that "as the sample size grew into the thousands, correlations became more likely to be reproduced." Does this mean that strong correlations were found between brains and cognitive activity or cognitive states as long as you used samples of thousands? No. The Nature article on the Marek study tells us this:

"Researchers measure correlation strength using a metric called r, for which a value of 1 means a perfect correlation and 0 none at all. The strongest reliable correlations Marek and Dosenbach’s team found had an r of 0.16, and the median was 0.01."  

So even when data on thousands of subjects was used, no strong or medium correlations were found, and the median correlation was a negligible 0.01.  A medium-strength correlation has an r of about .5, and a strong correlation has an r of about .7.  The results discussed above are consistent with the idea that the brain is not the source of the human mind, and is not the storage place of human memories.  Under such an idea, we would expect there to be no strong correlations between brain states and unemotional mental activity such as calm thinking or calm recall. 

The Biggest Brain Projects Are Still Failing to Support Prevailing Brain Dogmas

In a December 2020 post I examined the failure of the two biggest brain research projects to back up claims commonly made about the brain, such as the claim that the brain produces the mind and the claim that brains store memories. Let us now look at how one of those two biggest brain research programs (the Human Brain Project) is still failing to substantiate such claims. The Human Brain Project is a billion-dollar European research project. 

The page here of the Human Brain Project web site is entitled "Highlights and Achievements," and presumably lists the biggest accomplishments of the Human Brain Project. Let's take a look at the items listed at the top of the page, in the year 2021 section.  The first five items merely discuss technology innovations, not anything involving new findings about the brain.  The sixth item is merely an interview with a professor who talks about no specific research findings of the Human Brain Project, and who says that the project has "become a truly enabling endeavor," which is the kind of vague praise that people give when they don't have much in the way of specific achievements to discuss.  Then we have an item merely talking about how humans have some brain cell types not found in mice.  

The next item is entitled "Controlling brain states with a ray of light." We have a statement of never-substantiated neuroscientist dogma:  "The brain presents different states depending on the communication between billions of neurons, and this network is the basis of all our perceptions, memories, and behaviors."  But the page discussing this ray of light research mentions nothing that sounds important.  We merely hear of some light being sent into a brain, with some transition occurring, although the only transition claimed is an awakening from sleep: "This new chemically-engineered tool allowed to induce and investigate in detail, in a controlled and non-invasive way, the transitions of brain from sleep- to awake-like states using direct illumination." Not very impressive, given that we have already long known of a tool for inducing a transition from sleep to awake-like states: the humble alarm clock.

The next item merely mentions work on some robot.  The item after that has the title "EBRAINS powers brain simulations to give insight into consciousness and its disorders." The page discussing this research mentions no progress in understanding how consciousness occurs. It merely mentions some project reading brain waves during normal consciousness and sleep. We have a quote making it sound as if unconsciousness always involves less complex brain waves:

"We can see that unconsciousness is not simply a matter of a loss of brain activity,” Massimini says. “It’s not necessarily weaker. But it is a lot less complex.” 

This statement is only half-true. Brain waves are less complex for patients under anesthesia. But the most complex brain waves are those seen during grand mal seizures (also called tonic-clonic seizures), and during such seizures people are typically unconscious. An EEG reading during a grand mal seizures resembles a seismograph reading during an earthquake. 

The next item is entitled "HBP-researchers find new approach for Energy-Efficient AI Applications," which obviously involves no progress in cognitive neuroscience.  The item after that merely involves brain surgery, not cognitive neuroscience.  The next item merely is something pertaining to spinal cord surgery. 

We then see an item of little significance, merely something about some new technique for modeling dendrites. The item after that is the claim "A new means of neuronal communication discovered in the human brain." The claim is unjustified, being based solely on a paper failing to prevent robust evidence. 

The paper is the paper "Long-range phase synchronization of high-frequency oscillations in human cortex."  The claim of a synchronization effect is not well established.  The paper looked for correlations after analyzing brain wave readings from fewer than 100 people.  A paper like this would only be credible if (a) it was a pre-registered study that declared before any data was gathered a hypothesis to be tested, how the data would be gathered and how the data would be analyzed, and (b) the paper discussed a thorough blinding protocol that was followed.  But there is no mention of any pre-registration of this study, and the paper never mentions any blinding protocol (failing to use the word "blind" in its text).  

So what was going on? Apparently the authors got some EEG readings, and were then absolutely free to analyze the data in any way they wanted, being free to slice and dice the data until they found something they could call "synchronization."  We should have very little confidence in a study following such a method.  Given a body of data and freedom to analyze it any of 1001 ways, it is all too easy to find "synchronization" that is no real effect. For example, if I can compare the wins and losses of sports teams with the ups and downs of stock markets, options markets and bond markets, I could probably find  a little something I could claim as "synchronization." 

While the Human Brain Project site has bragged that "a new means of neuronal communication" has been discovered, the scientific paper behind this claim does not even sound very confident of such a thing, merely saying that some brain oscillations "may be synchronized between widely distributed brain regions." Also, neuron communication does not mean that neurons make our minds or store our memories. 

The last item on the Human Brain Project's list of 2021 highlights is merely a discussion of some paper claiming similarities in the brains of birds and mammals.  We read a claim that "the brains of birds and mammals look surprisingly similar in their organization." This is not at all true, and bird brains look very different from human brains. 

Judging from the Human Brain Project's list of 2021 highlights, the lavishly funded Human Brain Project is not making any progress in verifying the main dogmas of cognitive neuroscientists, the claim that the brain is the source of the human mind, and the claim that brains store memories.  Similarly, we find no support for such dogmas in a recent article entitled "The Human Brain Project: six achievements of Europe’s largest neuroscience programme."

Here are the six achievments listed:

• "Human brain atlas":  We read about merely fancy descriptions of parts of the brain. 
• "Synapses in the hippocampus:" We read that "researchers have published detailed 3D-maps of around 25,000 synapses – electrical and chemical signals between brain cells – in the human hippocampus." Such a result does not seem so impressive when you consider that the brain is believed to contain trillions of synapses. Also, you don't explain mental phenomena such as understanding and memory by making maps of synapses or maps of neurons. 
• "Robot hands":  Obviously this has nothing to do with verifying the claims of cognitive neuroscientists.
• "A neuro-inspired computer":  The computer described is not anything like a computer having the characteristics of the brain. If you ever built such a computer, it would never work to process data reliably and at high speeds. In digital computers electrical signals travel with 100% reliability, but in the cortex of the brain a signal will only pass across a synapse with a likelihood of 50% or less. Computers have coordinate systems and indexing systems allowing the computer to instantly find the location of some stored data, but brains have no such things. 
• "Virtual epileptic patient":  This has nothing to do with verifying the claims of cognitive neuroscientists.
• "Scientific output":  We merely hear a mention that 1497 papers cite the Human Brain Project. 

In the year 2020 section of the "Highlights and Achievements" page of the Human Brain Project, you won't find anything that substantiates the main dogmas about brains taught by neuroscientists. My December 2020 post here discusses the items in that section (as well as the 2019, 2018 and 2017 sections), and explains why they fail to support claims such as the claim that brain make minds and the claim that brains store memories. 

The Human Brain Project is making no progress in supporting claims such as the claim that brains make minds and the claim that brains store memories because such claims are not correct.  But what about the other big brain project, the US-based BRAIN Initiative? In my December 2020 post I examined the failure of that project (as well as the Human Brain Project) to back up claims commonly made about the brain, such as the claim that the brain produces the mind and the claim that brains store memories.  Were there any big results for the BRAIN Initiative in 2021?

Apparently not, judging from the page here which lists 2021 highlights for the BRAIN Initiative.  There is some discussion of brain mapping that has not yet done anything to back up the main dogmas of neuroscience. We see only two stories relevant to whether brains make minds:

• A story entitled "Neuroprothesis restores words to man with paralysis."
• A story entitled "Reading Minds with Ultrasound: A Less-Invasive Technique to Decode the Brain's Intentions."

The first story discusses some man who had a stroke leading to brain stem damage causing him to lose the power of speech. Electrodes were planted in his head, to look for some correlation between motor cortex brain activity and attempts of the man to say one of 50 different words. A system was developed wherein the man's attempts to speak can be matched to one of the 50 words.  This merely shows that the brain has a role in the muscle movements related to speech.  It does not prove that the ideas for what to say arise from the brain. 

The story about "reading minds with ultrasound" has a title that is misleading clickbait. The corresponding study was merely done with monkeys.  What's going on is some obscure clear-as-mud business involving trying to predict which of two options (left or right) a monkey will take, based on reading brain states a few seconds before the movement. A good rule of thumb for experimental science is to ignore all studies that did not use at least 15 subjects per study group.  The main results for this study involve experiments on only a single monkey. The study (which shows no sign of using a blinding protocol) is not reliable evidence for any ability to read minds with ultrasound. 

It appears that neither the Human Brain Project in Europe nor the BRAIN Initiative in the US is making progress in supporting claims such as the claim that brains make minds and the claim that brains store memories.  Such progress will never be made because the brain is not the source of our mind, and our brains do not store memories. To find reasons justifying these statements, read the other posts on this blog. 

In today's science news, we have the results of a project to test the reproducibility of cancer research.  A paper reports little success in reproducing results.  We hear that a large fraction of scientists simply refused to respond to queries from fellow scientists trying to reproduce the results, which is just what we would expect if a significant fraction of published research was fraudulent or defective. Here is a very worrying quote from the abstract:

"We conducted the Reproducibility Project: Cancer Biology to investigate the replicability of preclinical research in cancer biology....However, the various barriers and challenges we encountered while designing and conducting the experiments meant that we were only able to repeat 50 experiments from 23 papers. Here we report these barriers and challenges. First, many original papers failed to report key descriptive and inferential statistics: the data needed to compute effect sizes and conduct power analyses was publicly accessible for just 4 of 193 experiments. Moreover, despite contacting the authors of the original papers, we were unable to obtain these data for 68% of the experiments. Second, none of the 193 experiments were described in sufficient detail in the original paper to enable us to design protocols to repeat the experiments, so we had to seek clarifications from the original authors. While authors were extremely or very helpful for 41% of experiments, they were minimally helpful for 9% of experiments, and not at all helpful (or did not respond to us) for 32% of experiments."

Can you imagine a more damning statistic about the work quality of today's biological researchers, the fact that "none of the 193 experiments were described in sufficient detail in the original paper to enable us to design protocols to repeat the experiments"?

In a separate paper, the researchers found that "the median effect size in the replications was 85% smaller than the median effect size in the original experiments, and 92% of replication effect sizes were smaller than the original," which suggests a high degree of unreliability in biomedical research.