UK Biobank Study of Thousands of Brains Finds Negligible Correlation Between Brain Size and Intelligence

I previously described a study published in the January 2021 volume of the journal Cerebral Cortex, one entitled "Is There a Correlation Between the Number of Brain Cells and IQ?" The authors (Nicharatch Songthawornpong, Thomas W Teasdale, Mikkel V Olesen, and Bente Pakkenberg) examined 50 brains of Danish males who had died for reasons other than brain disease. It was possible to reliably estimate the IQ of these Danish males because they all had taken a military mental performance test that very highly correlates with IQ, and is essentially an intelligence test. 

The paper very clearly states its results:

""In our sample of 50 male brains, IQ scores did not correlate significantly with the total number of neurons (Fig. 1A), oligodendrocytes (Fig. 1B), astrocytes (Fig. 1C) or microglia (Fig. 1D) in the neocortex, nor with the cortical volume (Fig. 2A), surface area (Fig. 2B) and thickness (Fig. 2C). This also applied to estimates of the four separate lobes (frontal-, temporal-, parietal-, and occipital cortices; see Supplementary Material). Neither did IQ score correlate significantly with the volumes of white matter (Fig. 2D), central gray matter (Fig. 2E) or lateral ventricles (Fig. 2F), nor with the brain weight (Fig. 3A), or body height (Fig. 3B). All of these correlation coefficients were less than 0.2."

What this means is that the authors found:

• It is not at all true that the more brain cells you have, the more likely you are to be smart.
• It is not at all true that the more gray matter in your brain, the more likely you are to be smart.
• It is not at all true that the more white matter in your brain, the more likely you are to be smart.
• It is not all true that the heavier your brain, the more likely you are to be smart.

Although such results do not by themselves show that your brain is not the source of your mind, such results are quite compatible with the hypothesis that your brain is not the source of your mind. But the message coming from the study is not as loud as it might be, given the rather small sample size of only 50 brains.  Much larger studies have been done using scans of thousands of brains. 

The brain scans were done as part of the UK Biobank project. In that project about 29,000 subjects had their brains scanned, and about 7,000 of them also performed four cognitive tests. The study "Structural brain imaging correlates of general intelligence in UK Biobank" (which you can read here) analyzed performance on such tests, and estimated a general intelligence (which it called g) for each of several  thousand people taking the tests, all of whom had their brains scanned. The study then estimated what the correlation was between things such as intelligence and brain volume. The study found a correlation of only .276 between brain volume and intelligence, and a correlation of only .281 between gray matter volume and intelligence. 

How high a correlation is that? In the scientific paper entitled, “A guide to appropriate use of Correlation coefficient in medical research,” we have a Table 1 which has the heading of "Rule of Thumb for Interpreting the Size of a Correlation Coefficient." Here is that table:

Size of Correlation	Interpretation
.90 to 1.00 (−.90 to −1.00)	Very high positive (negative) correlation
.70 to .90 (−.70 to −.90)	High positive (negative) correlation
.50 to .70 (−.50 to −.70)	Moderate positive (negative) correlation
.30 to .50 (−.30 to −.50)	Low positive (negative) correlation
.00 to .30 (.00 to −.30)	negligible correlation

So by finding a correlation of only .276 between brain volume and intelligence, the study with a very big sample size of about 15,000 subjects has found only a negligible correlation between brain size and intelligence. And by finding a correlation of only .281 between gray matter volume and intelligence, the study with a very big sample size of about 15,000 subjects has found only a negligible correlation between gray matter volume and intelligence.

We have a result here quite compatible with the idea that your brain is not the source of your mind. Similarly, the 2019 study discussed here studied the brains of 324 people by brain scanning, and found that neither knowledge nor intelligence had any clear relation to brain parameters. 

The authors of the study "Structural brain imaging correlates of general intelligence in UK Biobank" (which you can read here) seem to have made some arbitrary choices about how to analyze the data they had. In the total UK Biobank data there were more than 10,000 subjects who had their brains scanned and who also did a Verbal Numerical Reasoning test. But the study authors chose to use only about 7000 of those subjects, only those who had taken four cognitive tests.  They also made the arbitrary decision to use only Part B of a Trail Making Test (a type of cognitive test) rather than the full data gathered (including a Part A and Part B). We can assume that the authors were trying to do an analysis that would show as high a correlation between brain volume and intelligence as they could get; but they have still only reported a negligible correction of .276.  A different analysis of the same UK Biobank would have shown an even lower correlation between brain size and intelligence.  This is proven by the quote below in the paper:

"Using an earlier data release (Ritchie et al., 2018), we previously estimated the correlation between brain size and one of those tests, 'Fluid Intelligence' (which we refer to as Verbal-Numerical Reasoning) to be r = 0.177. We found that the correlation did not differ by sex. Another study using an earlier release of UK Biobank imaging data examined the association between Verbal-Numerical Reasoning and brain size, reporting a correlation of r = 0.19 (N = 13,608; Nave, Jung, Linnér, Kable, & Koellinger, 2019)."

The second paper referred to is "Are Bigger Brains Smarter? Evidence From a Large-Scale Preregistered Study" which you can read here.  The authors of that paper falsely described the negligible correlation they found between brain volume and fluid intelligence, describing the negligible correlation they found of only .19 as "robust." As the table above tells us, all correlations of less than .30 are properly described as "negligible."

Different types of cognitive tests are usually measurements of things more than just intelligence, because the scores in the test scores can be influenced by things  such as manual dexterity, visual perception and a tendency of an unmotivated mind to wander. The type of very low correlations reported above can be easily accounted for under the idea that your brain is not the source of your mind, by supposing that slight differences in things such as manual dexterity and visual perception are showing up in the test scores. 

Postscript: The study "Meta-analysis of associations between human brain volume and

intelligence differences: How strong are they and what do they

mean?" is a meta-analysis of research studying brain size and intelligence. A Psychology Today article describes the meta-analysis:

"The largest and most recent meta-analysis (a study of studies) on the topic was led by Martin Voracek of the University of Vienna in 2015. Voracek and colleagues found that, although there is evidence for a relationship between overall brain volume and various intelligence measures, the strength of the relationship is very weak.

Encompassing 148 samples totaling more than 8,000 individuals in total, the Voracek study found that about 6 percent of the variance in intelligence performance can be attributed to differences in brain volume. This means that a very 'intelligent' person (by one metric or another) can attribute only a tiny fraction of their smarts to having a big brain, while a highly 'unintelligent' person can assign their brain size the same very small degree of blame.

However, even these weak relationships may be illusory. Showing that there is a positive relationship between brain size and smarts is an inherently headline-grabbing finding. Researchers who believe in such a relationship are more likely to undertake these kinds of studies, more likely to analyze their data in a way that generates the desired outcome, and more likely to be able to publish their positive results. Biases like these, which have riled the psychological sciences in recent years, make me doubt that any meaningful relationship exists between brain size and intelligence."

Below is interesting data from Table 1 of the paper here. We have data on six elderly female subjects called "super-agers." The MMSE number is the score on the Mini-Mental State Examination, a test of cognitive ability including short-term recall and also long-term semantic memory.  The maximum score on the test is 30. Notice the lack of correlation between brain weight and IQ, and the lack of correlation between brain weight and the MMSE score. The  MMSE scores for the 1st and 2nd subjects are identical, with the 2nd subject being very slightly smarter, even though the second subject has a brain weight 25% smaller. That same 2nd subject has an IQ of 135 -- in the 99th percentile for humans -- despite her  brain being far below the average female brain size of about 1200 grams. The 4th subject has a brain much smaller than the fifth subject, but has the same perfect MMSE score, and an IQ score 10% higher. These results are consistent with the idea that your brain is not the source of your mind, and not the explanation of your memory powers. 

NAME	AGE	MMSE (MAX=30)	IQ	BRAIN WEIGHT (GRAMS)
SA1	87	29	133	1240
SA2	90	29	135	990
SA3	99	25	112	1020
SA4	87	30	119	1090
SA5	81	30	107	1269
SA6	90	29	111	1100

A similar table with data for 50 subjects can be found in the year 2021 paper "Is there a correlation between the number of brain cells and IQ?" We read this summary of the results:

"In our sample of 50 male brains, IQ scores did not correlate significantly with the total number of neurons (Fig. 1A), oligodendrocytes (Fig. 1B), astrocytes (Fig. 1C) or microglia (Fig. 1D) in the neocortex, nor with the cortical volume (Fig. 2A), surface area (Fig. 2B) and thickness (Fig. 2C). This also applied to estimates of the four separate lobes (frontal-, temporal-, parietal-, and occipital cortices; see Supplementary Material). Neither did IQ score correlate significantly with the volumes of white matter (Fig. 2D), central gray matter (Fig. 2E) or lateral ventricles (Fig. 2F), nor with the brain weight (Fig. 3A), or body height (Fig. 3B). All of these correlation coefficients were less than 0.2." 

Can we imagine a more complete research failure of the "brains make minds" hypothesis?

It is interesting how scientists trying to promote "brains make minds" dogma make false citations of the main study discussed above, "Structural brain imaging correlates of general intelligence in UK Biobank" (which you can read here)  For example, the 2025 study "Neurite density but not myelination of specific fiber tracts links polygenic scores to general intelligence" 

 falsely states, "It is a well-established finding that bigger brains are associated with higher levels of intelligence," giving a citation to the paper "Structural brain imaging correlates of general intelligence in UK Biobank."  Far from "well establishing" such an association, that study found a correlation of only .276 between brain volume and intelligence, and a correlation of only .281 between gray matter volume and intelligence.  As discussed above, this is only a negligible correlation. 

Postscript: In a 1907 book we read this:

"In the Journal of the Biometrical Society, June, 1905, Prof. Karl Pearson, F.R.S., and Dr. Raymond Pearl give the results of an analysis of 2,100 adult male and 1,034 adult female brain weights, belonging to five races — Swedish, Bavarian, Hessian, Bohemian and English — with the conclusion that ' There is no evidence that brain weight is sensibly correlated with intellectual ability.' "

"Brains Make Minds" Models All Flunk a Large Brain Scan Study

There recently appeared a study attempting to measure how well different neuroscientist theories about intelligence performed when trying to predict intelligence from brain scans. The theories were all just minor variations of the idea that intelligence is purely a product of the brain. All of the neuroscience theories tested flunked this test very badly. But the press release announcing the study failed to mention this big flop, and merely gave us a headline announcing that one of the theories performed better than the others.  

The study was entitled "Investigating cognitive neuroscience theories of human intelligence: A connectome-based predictive modeling approach." The study used a surprisingly high number of subjects, about 300. In this respect the study was very different from the great majority of experimental neuroscience studies using brain scanning, which routinely use way too-small study group sizes. Nowadays experimental neuroscience studies mostly display an appalling failure to follow sensible standards. There is no standard being used for the minimum number of subjects that must be used. The great majority of published experimental neuroscience studies are junk science studies that use way too-small study group sizes, typically fewer than 15 subjects per study group. The results reported in such studies are mainly noise and false alarms. Do not ever make the very large mistake of assuming that an experimental neuroscience study must have been good science if it passed peer review and got published in a major science journal. Nowadays peer reviewers are letting all kinds of junk studies and poorly designed research get published in leading neuroscience journals.  The peer reviewers of neuroscience journals are typically scientists who themselves wrote papers using Questionable Research Practices such as a lack of a blinding protocol, unreliable techniques for measuring animal fear, and way-too-small study group sizes.  Such peer reviewers are reluctant to exclude papers for committing the same sins that were committed in the papers authored by the peer reviewers themselves. It's kind of like a situation in which tax cheaters who cheat on their taxes every year are in charge of auditing tax returns by other people. 

In the study "Investigating cognitive neuroscience theories of human intelligence: A connectome-based predictive modeling approach" about 300 subjects were given a large variety of cognitive tests. The same subjects had their brains scanned. From features detected in brains, a group of neuroscience theories were used to make predictions about how well the subjects should have performed in intelligence tests. Graphs were created showing how well these predictions matched reality. 

The neuroscience theories tested against reality included the following:

(1) A "lateral PFC" theory assuming that intelligence mainly comes from the prefrontal cortex.

(2) A "Parieto-Frontal Integration" theory that "proposes that connectivity of a distributed frontoparietal network accounts for intelligence by enabling the integration of knowledge between frontal and parietal areas to support hypothesis generation and problem solving."

(3) A "Multiple Demand" theory that "incorporates more recent advances in understanding the network architecture of general intelligence by appealing to an even broader network of frontoparietal and cinguloopercular regions." 

(4) A "Process Demand" theory that "provides a novel framework centered on the idea that general intelligence reflects the engagement of multiple cognitive processes represented by the overlap (or shared connections) among brain networks." 

(5) A "Network Neuroscience" theory that proposes that intelligence "emerges from individual differences in the network topology and dynamics of the human connectome." 

The paper has some graphs showing how well these theories predicted intelligence.  We get two main types of graphs: scatter plot graphs and  correlation graphs shown as bar graphs. 

Before discussing the results, I must give a little primer on scatter plot graphs involving correlation. A scatter plot shows data items for which two numbers have been collected. For example, if you kept track of how much ice cream was sold on a store, while recording the temperature of each day, you could make a nice scatter plot comparing sales on the different days, and the temperature on each day; and you would see a nice correlation between hot weather and ice cream sales.  When there is a strong correlation, a scatter plot will look something like the graph below, showing a very clear correlation:

Graph 1: A scatter plot showing high correlation

When there is very little or no correlation, a scatter plot will look something like the graph below, with the points scattered all over the graph, with the points showing no very clear line:

                     Graph 2: A scatter plot showing little or no correlation

The study "Investigating cognitive neuroscience theories of human intelligence: A connectome-based predictive modeling approach" has some scatter plots showing how well the various "brains make minds" models performed. The scatter plots all look like Graph 2 above, and show the models flunking the test by performing very poorly at predicting intelligence. 

Figure 4 of the paper shows the scatter plot below, where we see a failure of the "lateral PFC" model to perform impressively, without any clear trend line:

A bar graph next to this graph shows us that the predictive performance is dismal, with the performance seeming to be worst than what we would expect from mere guessing. Figure 5 of the paper looks like the scatter plot shown above, and shows very bad predictive performance of the "Parieto-Frontal Integration" theory, with no clear trend line. Figure 6 of the paper  looks like the scatter plot shown above, and shows very bad predictive performance of the "Multiple Demand" theory, with no clear trend line. 

Discussing the "Process Overlap" theory, the paper tells us that "we find evidence that whole-brain functional edges do a relatively poor job at predicting g [intelligence] compared with other connectivity profiles, with the best-performing model (Figure 7a) generating predictions of r = .11."  The r is a measurement of correlation, which can vary from r = 0 (no correlation) to r = 1 (perfect correlation). A correlation of only .11 is a negligible correlation. As a general rule of thumb, there is no good evidence of a causal relation unless you find some r value greater than .3, and the evidence for a relation is weak unless the r value is .5 or greater.

Finally the paper comes to displaying the performance of the theory that supposedly produces "the most robust predictions of general intelligence" of the theories: the "Network Neuroscience" theory. Unfortunately, the performance of this "best of the lot" winner is dismal. Figure 11 of the paper gives us this scatter plot showing the performance of this "Network Neuroscience" theory:

Again, we see a scatter plot failing to show any clear trend line. The bar graph included with this scatter plot further clarifies how badly the "Network Neuroscience" theory performs. In that bar graph we see that with most versions of the theory, the correlation level is actually less than 0, with a negative correlation.  That equals worst results than you would get from random guessing or throwing a dice.

The end of the "Investigating cognitive neuroscience theories of human intelligence: A connectome-based predictive modeling approach" fails to accurately characterize these extremely poor results from all of the models. We read multiple times a totally unjustified use of the phrase "reliable predictions of g [intelligence]" that does not match any of the graphs shown. The paper should have had a conclusion section mentioning the abysmal predictive failure of all of the models tested. Instead the paper ends with some unjustified language contradicting the data it displays. It's as if the authors failed to study their own graphs, or failed to accurately describe them.  This is what happens very frequently in today's neuroscience literature: authors making claims (particularly in paper titles and paper abstracts) that do not match the data they have collected.  The very marginal and very weak association between cognitive scores and brains shown by a small subset of the data can easily be explained by factors having nothing to do with intelligence, because brain differences can cause things such as differences in perceptual ability, differences in muscle speed, and differences in manual dexterity, all of which can affect IQ test scores. 

The press release of the study gives us this headline: "Study: Network neuroscience theory best predictor of intelligence."  An accurate headline would have been this: "Models Assuming Brain-Based Intelligence All Flunk a Large Brain Scan Test." The reported results are quite consistent with the idea that your brain does not make your mind.  The press release basically does a cover-up job, by failing to mention the very bad predictive performance of all of the theories. 

We hear quotes from a neuroscientist who fails to mention the very bad failure of all of the "brains make minds" theories when predicting intelligence from brain scans.  Instead the neuroscientist gives us a little empty hand-waving by trying to explain problem-solving by mentioning "connections." A connection of brain cells does nothing to explain problem solving or intelligence. We know of countless highly-connected things that are utterly mindless, like the atoms in a crystal lattice.  The paper I have discussed suggests there is no robust correlation between brain connections and intelligence.  

The result should come as no surprise, as it matches a previous study of brain connectivity.  The study was announced on the Science Daily web site with this headline: "MRI scans of the brains of 130 mammals, including humans, indicate equal connectivity."

We read the following:

"Researchers at Tel Aviv University, led by Prof. Yaniv Assaf of the School of Neurobiology, Biochemistry and Biophysics and the Sagol School of Neuroscience and Prof. Yossi Yovel of the School of Zoology, the Sagol School of Neuroscience, and the Steinhardt Museum of Natural History, conducted a first-of-its-kind study designed to investigate brain connectivity in 130 mammalian species. The intriguing results, contradicting widespread conjectures, revealed that brain connectivity levels are equal in all mammals, including humans." 

Recent Study Finds No Correlation Between Number of Brain Cells and IQ

Our science news are hopelessly biased towards propagating prevailing beliefs about the mind and brain. It seems that whenever there are published scientific studies that seem to support prevailing dogmas about the brain, we will see many press stories talking about such studies, no matter how insufficient their sample sizes may or no matter how dubious their methodology may be, and even if the stories were only done with mice rather than humans. But if we have a study providing results conflicting with prevailing dogmas about the brain, it will usually not be covered by the science news sites even if the study had a good sample size and used humans. And so despite reading several science news websites every day, I read no mention in them of a recent study finding the important result that there is no correlation between the number of brain cells and intelligence. 

The study published in the January 2021 volume of the journal Cerebral Cortex was entitled "Is There a Correlation Between the Number of Brain Cells and IQ?" The authors (Nicharatch Songthawornpong, Thomas W Teasdale, Mikkel V Olesen, and Bente Pakkenberg) examined 50 brains of Danish males who had died for reasons other than brain disease. It was possible to reliably estimate the IQ of these Danish males because they all had taken a military mental performance test that very highly correlates with IQ, and is essentially an intelligence test. 

The paper very clearly states its results:

"In our sample of 50 male brains, IQ scores did not correlate significantly with the total number of neurons (Fig. 1A), oligodendrocytes (Fig. 1B), astrocytes (Fig. 1C) or microglia (Fig. 1D) in the neocortex, nor with the cortical volume (Fig. 2A), surface area (Fig. 2B) and thickness (Fig. 2C). This also applied to estimates of the four separate lobes (frontal-, temporal-, parietal-, and occipital cortices; see Supplementary Material). Neither did IQ score correlate significantly with the volumes of white matter (Fig. 2D), central gray matter (Fig. 2E) or lateral ventricles (Fig. 2F), nor with the brain weight (Fig. 3A), or body height (Fig. 3B). All of these correlation coefficients were less than 0.2."

What this means is that the authors found:

• It is not at all true that the more brain cells you have, the more likely you are to be smart.
• It is not at all true that the more gray matter in your brain, the more likely you are to be smart.
• It is not at all true that the more white matter in your brain, the more likely you are to be smart.
• It is not all true that the heavier your brain, the more likely you are to be smart.

Although such results do not by themselves show that your brain is not the source of your mind, such results are quite compatible with the hypothesis that your brain is not the source of your mind. In Figure 1A of the paper, we see that 3 of the 7 or 8 subjects with the lowest number of neuron cells had above average intelligence.  The correlation between the number of neuron cells and intelligence was actually a very slight negative correlation, although not statistically significant. 

The results of this study should come as no surprise to anyone who has studied the posts on this site, such as my post here discussing how removal of half of the brain (to stop very epileptic seizures) has little effect on intellect or memory. The results of this study should also come as no surprise to anyone familiar two items  mentioned by the study's authors: that "the rather large difference in neocortical neuron number between men and women (16% higher in men, Pakkenberg and Gundersen 1997) does not match with the minor gender difference in IQ (Halpern and LaMay 2000) and that highly demented female Alzheimer’s disease patients have normal neocortical neuron numbers (Regeur et al. 1994, Pelvig et al. 2003)."

The 2019 study discussed here studied the brains of 324 people by brain scanning, and found no good evidence for any relation between brain parameters or knowledge and intelligence.