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Norwegian family flynn effects

I have good memories of 1975. I got my first secure job, a Lectureship in Psychology at the Middlesex Hospital Medical School, part of the University of London. It was a glorious summer, followed the next year by an even better and drier one, and I finally finished my PhD. Little did I realise that we had reached peak intelligence, and after that it would be downhill all the way. In my defence, it takes time to notice that a peak has been passed, and all this relates to Norwegian data, but nonetheless, the endullment of Western society was underway, and any subjective concerns I had about the increasing foolishness of the world have now been amply confirmed. 1975 turns out to have been a pivotal year, and a new paper says that the reasons are within the family.

Flynn effect and its reversal are both environmentally caused
Bernt Bratsberg and Ole Rogeberg

http://www.pnas.org/cgi/doi/10.1073/pnas.1718793115

https://sci-hub.tw/https://doi.org/10.1073/pnas.1718793115

Abstract

Population intelligence quotients increased throughout the 20th century—a phenomenon known as the Flynn effect—although recent years have seen a slowdown or reversal of this trend in several countries. To distinguish between the large set of proposed explanations, we categorize hypothesized causal factors by whether they accommodate the existence of within-family Flynn effects. Using administrative register data and cognitive ability scores from military conscription data covering three decades of Norwegian birth cohorts (1962–1991), we show that the observed Flynn effect, its turning point, and subsequent decline can all be fully recovered from within-family variation. The analysis controls for all factors shared by siblings and finds no evidence for prominent causal hypotheses of the decline implicating genes and environmental factors that vary between, but not within, families.

This is an interesting and quite complicated paper, which argues that because the Flynn effect is of equal magnitude in older and younger sons within the same family, then it was probably caused by unknown factors affecting all family members, and cannot have been caused by differences between families. For example, if poor families have more children, and these tend to be dull, then there will be differences between families, not within them.

The method seems to be simple: every year test the intelligence of the first born son and compare it with the intelligence of the second son within that same family, the second son of course being born and being tested some time later. If both sons show the same pattern of rising or falling intelligence, then the Flynn effect, whatever its cause, is due to things which affect all families in the same way. Clean water, good food, home computers, healthy living can boost all family member’s ability levels. Genetic differences would favour some families over others, but that is not detected in this study, so is probably unlikely.

To narrow down the set of hypotheses, we examine the extent to which we can recover observed Flynn effects from within-family variation in large-scale administrative register data covering 30 birth cohorts of Norwegian males. Within-family variation will only recover the full Flynn effect if the underlying causal factors operate within families. Notably, if within-family variation fully recovers both the timing and magnitudes of the increase and decline of cohort ability scores in the data, this effectively disproves hypotheses requiring shifts in the composition of families having children. This set of disproved hypotheses would include dysgenic fertility and compositional change from immigration, the two main explanations proposed for recent negative Flynn effects

A metareview of empirical studies argues that the positive Flynn effect relates to improved education and nutrition, combined with reduced pathogen stress. Turning to the negative Flynn effect, the metareview notes a deceleration of IQ gains in some studies and suggests that these may relate to (i) decreasing returns to environmental inputs (saturation) or (ii) the picking up of effects that cause IQ decreases and may ultimately reverse the Flynn effect, such as dysgenic fertility. Dysgenic fertility is also the favored hypothesis in a recent literature review on reversed Flynn effects, where the authors conclude that dysgenic trends are the simplest explanation for the negative Flynn effect. A negative intelligence–fertility gradient is hypothesized to have been disguised by a positive environmental Flynn effect, revealing itself in data only once the ceiling of the Flynn effect was reached.

So, this paper confirms what was already known, that the secular rise in intelligence test scores has already given way to a fall in those scores (with perhaps a slight rise again?), but attempts to rule out a whole set of possible explanations, saying that there is no need for them. The full effect can be shown to operate within families.Hence the authors’s view of the significance of their findings.

Using administrative register data with information on family relationships and cognitive ability for three decades of Norwegian male birth cohorts, we show that the increase, turning point, and decline of the Flynn effect can be recovered from within-family variation in intelligence scores. This establishes that the large changes in average cohort intelligence reflect environmental factors and not changing composition of parents, which in turn rules out several prominent hypotheses for retrograde Flynn effects.

Now for the detail. These are conscription data for young men. No reason to believe young women would be different. The authors report that the family average tracks the pattern of the first born pretty well. However, as the years went by, lower scoring first borns were unlikely to have had younger brothers who were tested themselves, and this requires a correction factor to be applied. Although the correction for this selection bias is carefully done, it introduces some uncertainty to the estimates, though the authors see this as well within reasonable limits. The authors also argue, in my view convincingly, that the reversal of the Flynn effect is so rapid that it is unlikely to be a dysgenic indicator, since such things happen between successive generation, not within one.

A salvo has been fired against genetic factors being implicated in the apparent drop in intelligence. As a note of caution, it would be good to look at whether this holds true of all components of the intelligence test: numbers, words and shapes. Anyway, the authors say that these data do not allow them to specify what causes the Flynn effect and its reversal, merely to suggest it cannot be genetics.

The strong points of the study are that it is based on conscript age data obtained on almost all Norwegian men from 1962 to 1991, and they restrict themselves to Norwegians with two Norwegian parents, so they will not be cultural or genetic confounders.

They say:

 
• Category: Science • Tags: Flynn Effect, IQ 
Who? Whom? versus "What? When? Why? How?
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Black-white difference Becker survey

The argument from authority is of questionable merit. Yes, some people know far more than others, but how does one establish that? Happily, there are publication and citation metrics available to help us, and a reasonable case can be made that experts exist. That does not preclude the possibility that they are all wrong. One really good study might conceivably show that they had all missed an important point. Although rare, this does happen from time to time, just to make things interesting.

In 1987 Synderman and Rothman reported on a survey of 1020 intelligence experts, data having been collected in 1984. The experts were in agreement (99.3%) that intelligence involved “abstract thinking or reasoning”. As regards the burning question: “what is the source of the black-white difference in IQ?” 45% said both genetics and environment, 15% entirely environmental, 14% did not respond, and 1% said entirely genetic. So, strong environmentalists were far more common than strong geneticists. Looking at the references in that paper shows you that experts at that time were reading SJ Gould and Leon Kamin, and their arguments may have increased the environmentalist tendency.

Who are the intelligence experts now?

Men, mostly. That 83% of them are male could be because of male standard deviation advantage, in that exceptional ability is more likely in males (as is the exceptional lack of it). Even more precisely, it would fit the hypothesis that men are also 3 points ahead of women. They are of middle age, which is what one becomes after reading all the required literature (same pattern as in 1984). However, if 30 year olds bother to do the reading they can quickly contribute to it. 7 people over 70 are still publishing. The experts are well-published; and left-wing. The last point may come as a surprise. They tend towards liberal rather than conservative opinions. They are left of centre by 2 to 1. They are strongly in favour of gay marriage, in favour of more social democratic policies and of immigration. They are less keen on, though not totally opposed to “strong affirmative action”.

They come from middle class backgrounds, as one would expect of the children of better educated and probably brighter parents. They are mostly European, and often Jewish. They studied psychology, have PhDs, and are mostly in universities. Two thirds of them are not religious. 75% regard themselves as Jensenists, meaning that IQ has a general factor and is heritable.

Experts sometimes talk to the media, but have a generally poor opinion of it. As of 2013/2014 they rated two particular bloggers far more highly. They find the public debates about intelligence are mostly (two thirds) based on ideology. They have often hesitated to give their opinions in public. They also think that intelligence research could be abused in political settings. On balance, they think that 51% of the black-white difference in intelligence in the US is caused by environmental factors.

Figure 10 shows the range of opinions:

Black-white difference Becker survey

Environmental hardliners are nearly three times as common as hereditarian hardliners. Since the Snyderman and Rothman study in 1987 there has been a shift towards accepting genetic components. Unfortunately, these judgments are strongly related to political perspectives r = -.49 as will be seen below.

Black-white difference and politics Becker

One assumes that political perspective came first, and provided a powerful interpretative filter. Age did not have much effect, but gender was almost as powerful r = .48 . There were only 10 women and their average estimate was that 77% of the genetic group difference was environmental, compared to the male average estimate of 39%.

So, here we have another projective test. Is the question of group differences all down to opinion, or do facts matter? It seems to be a case of “Who? Whom?” versus “What? When? Why? How?”. From my perspective, the political affiliations come as a partial surprise. It is informative that this group put the genetic contribution at 49% despite the fact that they lean left. I hope this finding about a willingness to countenance (anonymously) a genetic compontent will not feed them to the wolves.

Having heard the details of the expert’s backgrounds, if you judge people by their demographics, then you may find lots to object about, and might even want to expel those with right wing opinions. If you judge people by their arguments, then you might wish to ignore the revealed political bias, and concentrate on the actual arguments and the supportive evidence, to examine the deeper foundations of the debate. I would favour that approach, but would warn you that, if you are not middle aged now, you will be middle to old aged by the time you have done the necessary reading.

Here is the slide deck presenting the results of the survey.

London18DBSurveyV3 (1)

 
• Category: Science • Tags: Heredity, IQ, Race/IQ 
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Al-Mumia_04_ALFILM

I have held off talking about the Press attacks on the London Conference earlier this year. Triggered by journalist and educationalist Toby Young’s appointment to a UK Governmental education committee, rival journalists fired off a salvo of accusations in a “guilt by association” spoiling operation. I was simply collateral damage, accused of keeping bad company with a group of deplorables, whose secret meetings Toby had briefly attended in order to gather material for a talk he was giving at another intelligence conference. I thought it was better that the participants replied on their own accout, since they drew most of the fire, rather than I as the organizer tried to speak for them. Many of the participants have put their names to a joint paper which is soon to be published in a scholarly journal.

However, for some months I have been sitting on a charming essay by one particular participant, Julien Delhez, who has the great merit of being an Egyptologist. What is such a person doing at a conference on intelligence, otherwise infested by psychologists of a psychometric persuasion? Well, our inclusion criteria are pretty simple: people with interesting ideas who are committed to empirical methods. The notion that one could someday measure the intelligence of the Pharaohs seemed intriguing, and Julien’s ideas developed as he attended the conferences. Originally interested in estimating how illnesses may have diminished the ability of the highest status ancient Egyptians, he now wants to incorporate ancient DNA studies to do intelligence estimates.

I think he gives a very good background to the events, explains the conference content and general procedures, and draws attention to the underlying socio-political problems which arise when research even raises the possibility of genetic components in group differences.

https://republicstandard.com/reflections-london-conference-intelligence/

Any comments you make here will be also be looked at by him, so both of us can reply to your remarks.

 
• Category: Science 
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Cambridge undergrads

Newspaper reports are still discussing the story about the numbers of Africans admitted to Oxbridge, but I have not seen any giving the numbers of AAA students available, or any that mention intelligence. I doubt that Admissions Officers read my blog, or indeed that they would survive in post if they were ever caught doing so, but it is perfectly possible that Admissions Officers have friends, and some of those friends might innocently print out this post for them to read when they call round for coffee.

First, let us start with some data on cognitive assessments carried out in schools. They are not face to face Wechsler tests, nor are they the traditional tests on which we have decades of comparative data, but they give us some idea of student capabilities by ethnic group, and that is what we need in order to contribute to this debate. Indeed, looking at the data has a generality beyond the specific case of Oxbridge, and applies to all university entrance matters where ethnicity is an issue. Here are cognitive scores for ethnic groups in Britain, as assessed by the CAT test at school.

pupil background CAT

In the table below I will concentrate mostly on those groups with more than 1000 subjects and not having “other” in their ethnicity description, since one does not know what ethnicities are included. I simplify the three reasoning measures into one simple average and standard deviation (this is crude but quick). I then give the percentage of each ethnic group who are above IQ 130, on the basis of a requirement that students are IQ 130 and above on the assumption that the population has an average IQ 100 and a standard deviation of 15 points. These are all approximations, since the observed standard deviations are narrower than expected, possibly because the tests may not have been offered to some lower ability children, and they may have omitted private schools with higher ability students. I have rounded the means and standard deviation scores up or down with the usual 0.5 break point, which will have further affected some of the calculations.

130+ by ethnicity

As you can see, on these figures Chinese students are the most likely to get to a good university. They would do so at roughly 3 times the rate of white students. White students would be almost 7 times more likely to get to these universities than Black Caribbean students.

Remember also that category of “3 A’s or better” hides a four point scale, ranging from AAA to A*A*A*, so a demanding university can still pick and choose within the students who achieve the minimal entrance level.

Now back to the actual figures of students getting AAA, which is what the universities must deal with. Since only 6600 applicants get a place at Oxbridge, we can assume that if every candidate with at least 3 As applies, then the success rate is 6600/17,146 which is 38%. The final column shows what the actual figures of placement offers should be for Oxbridge. These would be the admissions made on merit only, as judged by scholastic results. There would only be 1 Black Caribbean for every other 277 students.

Oxbridge entry

I do not frequent these establishments, but if you have a pressing interest in using genetic background as an entry criterion, a prospect which does not please me, you may wish to go around counting undergraduates and rate them according to their apparent ethnicities, and compare them with the various calculation shown above. The final point should be very clear: entrance to university cannot be calculated on population numbers alone.

 
• Category: Science • Tags: Academia, IQ 
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Cambridge

It is that time of year when Oxford and Cambridge universities are in the doghouse again, accused of being biased against black students. A politician, Mr David Lammy, has called for special measures to be taken to boost the numbers of Africans at those universities. Calls like this seem to be accepted at face value, but universities are tertiary educators, fed by secondary schools. What does the pipeline deliver them?

Well, to get to a good university you need at least 3 A grades, and for the best colleges preferably 5, all in respectable, that is to say, hard subjects. For example, an A in Maths, and another A in Further Maths reassures good universities that the place they offer a candidate is unlikely to be wasted. If one looks at the average offer extended to Oxbridge candidates it is A*AA (three As, one of them being A starred). That is what they must get in their exams to secure a place, the actual subjects depending on what discipline they wish to read.

Here is the official Department of Education summary of the ethnic success rate in most recent results for 3 A grades.

https://www.ethnicity-facts-figures.service.gov.uk/education-skills-and-training/a-levels/draft-percentage-of-students-achieving-3-a-grades-or-better-at-a-level/latest

3 A grades or better at A level was achieved by 24% of Chinese students, 11% of Mixed students, 11% of White students, 11% of Other ethnic group students, 10% of Asian students and 5% of Black students.

Chinese students were consistently most likely to achieve 3 A grades or better at A level and Traveller of Irish Heritage students and Gypsy/Roma students were least likely to.

The summary is not entirely clear about mixed students. The detailed tables are hard to display, so I have made a simplified version. By the way, two things should be borne in mind when considering the numbers of ethnic students who gain entry to highly selective universities: the percentage of each ethnic group who reach the basal standard, and the actual size of the ethnic group.

3 As or better

Oxford and Cambridge offer roughly 6,600 undergraduate places in total, and roughly five times as many students apply as are accepted. So, 7600 white students who reach the minimal standard do not get admitted to Oxbridge every year. Tough luck.

Every statistic based on ethnicity is influenced by the immigration history of the nation in question. For example, Black British used to mean “from the West Indies”. These are the group who have had most time to get the benefits of life in the United Kingdom, and are almost all British born, using the NHS from conception and the education system throughout. Now the African population is larger than the Caribbean population, a consequence of recent mass migration. Many will have been born abroad.The Indians in the UK are drawn from particular populations, and India is heterogenous as regards ability.

Many people will find the statistics startling. Can it really be the case that only 62 Black Caribbean students achieve 3 A grades? Here is a very rough calculation: assume 594,825 Caribbeans in the UK. Assume that, as for other populations, only 2.33% of that population are of an age to go to university, and that all apply. Assume that the best estimate of Afro-Caribbean intelligence is 90, and that IQ 130 is the minimal Oxbridge entrance requirement. In that case there will be 53 qualified applicants. This estimate is in broad agreement with the observed figure.

The larger (and very probably pre-selected) African ethnic group seems a more promising pool for recruitment, if the requirement is simply that the candidate be of African genetics. The African group is bimodal in terms of occupational level: lots of professional African immigrants, plus lots who are unemployed. They are drawn from a vast population.

The table is also informative about racial admixture. The children of Whites have gained by mixing with Asian genetic groups (actual group unspecified) and lost somewhat when mixing with Black Africans and more so with Black Caribbeans. Interestingly, the White/Black Caribbean mix of 11% and 3% pass rates results in exactly a 7% pass rate for the mixed group.

It seems that British people do not blink when it is proposed that another genetic group should be granted extra privileges. There is no call for White British candidates to be put on the same footing as Chinese and Indian students. I suppose the supposition is that they are brighter or studied harder, probably both.

It might help the public debate about university entry if more people were to look at the official education statistics. The focus of discussion may one day move to secondary schools. Then, after a while, it may move to primary schools and then kindergartens. Since racial differences in ability can be detected at age 3, expect special measures to be required for kindergartens.

 
• Category: Science 
118 cm3
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Sex diffs in brain size Ritchie

Pity the poor blogger’s lot: there are more interesting papers being published every week than any essayist, however diligent, can possibly cope with. And there will be more, as the vast genetic databases give up their secrets. No sooner does one team scoop the others with a savage novelty than their rivals counter-attack with their own surprising findings. If you are curious about mankind, it is the best time to be alive. We are likely to learn more about ourselves in the next few decades than was possible in the last few centuries.

So back we go to an old theme, but with a new twist: how do women’s brains work?

To sort out this mildly contentious issue, Stuart Ritchie, up and coming member of the Edinburgh crew and its international affiliates, has provided intrigued men with a map of women’s brains. Smaller, of course, as many a man has surmised in the midst of an unexpectedly heated domestic discussion, but apparently able to function as well, or almost as well, as the male variety. Let us dig deeper into these mysteries, in the calm and measured way which befits this distinguished audience.

Sex Differences in the Adult Human Brain: Evidence from 5216 UK Biobank Participants
Stuart J Ritchie, Simon R Cox, Xueyi Shen, Michael V Lombardo, Lianne M Reus, Clara Alloza, Mathew A Harris, Helen L Alderson, Stuart Hunter, Emma Neilson, David C M Liewald, Bonnie Auyeung, Heather C Whalley, Stephen M Lawrie ,Catharine R Gale, Mark E Bastin, Andrew M McIntoshIan, J Deary.
Cerebral Cortex, bhy109, https://doi.org/10.1093/cercor/bhy109
Published: 16 May 2018

https://academic.oup.com/cercor/advance-article/doi/10.1093/cercor/bhy109/4996558

The authors say:

Sex differences in the human brain are of interest for many reasons: for example, there are sex differences in the observed prevalence of psychiatric disorders and in some psychological traits that brain differences might help to explain. We report the largest single-sample study of structural and functional sex differences in the human brain (2750 female, 2466 male participants; mean age 61.7 years, range 44–77 years). Males had higher raw volumes, raw surface areas, and white matter fractional anisotropy; females had higher raw cortical thickness and higher white matter tract complexity. There was considerable distributional overlap between the sexes. Subregional differences were not fully attributable to differences in total volume, total surface area, mean cortical thickness, or height. There was generally greater male variance across the raw structural measures. Functional connectome organization showed stronger connectivity for males in unimodal sensorimotor cortices, and stronger connectivity for females in the default mode network. This large-scale study provides a foundation for attempts to understand the causes and consequences of sex differences in adult brain structure and function.

There is much to discuss here, but my attention was drawn by two phrases “considerable distributional overlap” (which in my experience means that one group is pretty different from another) and “generally greater male variance” (which agrees with most of the observations on sex differences indicating that men are leptokurtic (more variable), women more platykurtic (less variable).

Women are more at risk of dementia, depression, schizophrenia and dyslexia. Men are better than women at mental rotation tasks, and are more physically aggressive; women are more interested in people than in things, are more neurotic and more agreeable.

One of the most interesting sex differences is intelligence. Here is their introduction to the topic:

There is more to sex differences than averages: there are physical and psychological traits that tend to be more variable in males than females. The best-studied human phenotype in this context has been cognitive ability: almost universally, studies have found that males show greater variance in this trait (Deary et al. 2007a; Johnson et al. 2008; Lakin 2013; though see Iliescu et al. 2016). This has also been found for academic achievement test results (themselves a potential consequence of cognitive differences, which are known to predict later educational achievement; Deary et al. 2007b; Machin and Pekkarinen 2008; Lehre et al. 2009a, 2009b), other psychological characteristics such as personality (Borkenau et al. 2013), and a range of physical traits such as athletic performance (Olds et al. 2006), and both birth and adult weight (Lehre et al. 2009a). To our knowledge, only two prior studies have explicitly examined sex differences in the variability of brain structure (Wierenga et al. 2017; Lange et al. 1997), and no studies have done so in individuals older than 20 years. Here, we addressed this gap in the literature by testing the “greater male variability” hypothesis in the adult brain.
[]
We tested male–female differences (in mean and variance) in overall and subcortical brain volumes, mapped the magnitude of sex differences across the cortex with multiple measures (volume, surface area, and cortical thickness), and also examined sex differences in white matter microstructure derived from DT-MRI and NODDI. We tested the extent to which these differences were regionally-specific or brain-general, by adjusting them for the total brain size (or other relevant overall measurement; for instance, adjusting volume differences for total brain volume and cortical thickness differences for mean cortical thickness), and examining whether the differences found in the raw analyses were still present. We tested the extent to which these structural differences (in broad, regional, and white matter measures) mediated sex variation in scores on two cognitive tests, one tapping a mixture of fluid and crystallized reasoning skills (skills previously found to be linked to brain volumes; Pietschnig et al. 2015) and one testing processing speed (previously found to be linked to white matter microstructural differences; see Penke et al. 2012). At the functional level, we also examined large-scale organization of functional networks in the brain using resting-state fMRI functional connectivity data and data-driven network-based analyses.

The study compared 2750 females (mean age = 61.12 years, SD = 7.42, range = 44.64–77.12) and 2466 males (mean age = 62.39 years, SD = 7.56, range = 44.23–76.99). These are extremely large samples, two orders of magnitude larger than the early studies in the 1980s, and way larger than many of the studies that the Press report so frequently. Consider them “Foxtrot Oscar” samples.

The first result is startling: male brains are very much bigger, a colossal 1.4 effect size. 92% of men will be above the mean for women. On average men have 117.8 cm3 more brain than women. All this extra brain must be doing something for men, you might surmise, other than just helping them perpetually contemplate the relative advantages of the more complicated positions adopted during sexual intercourse. Perhaps not. Broadly the same effect of male advantage can be found in all the brain region sub-comparisons. Male brains are both larger, and also vary more in size. Greater male variability seems a fact of nature. If there were a direct relationship between brain size and cognitive ability, there would be many, many more bright men than bright women.

 
• Category: Science • Tags: Brain Scans, Gender, Sex Differences 
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Genc Figure_4 fewer connections

The ISIR July 2017 meeting in Montreal seems a long time ago, and that feeling is entirely explicable by it being 10 months since I heard the lecture in question. I was chairing the session, which normally diminishes attention to the actual content, but this talk was the exception. It came up with a counter-intuitive finding, and it has been difficult to avoid talking about it. Brighter brains have fewer connections between neurones. Cool.

It has been a real struggle to keep quiet about this remarkable result, and a relief that the embargo has been lifted today, 14 months after receipt of the paper by the publishers. Publish and be damn delayed. Blogging is the future.

As you will see from the author list, particularly the last author, this is a team which has been working on this topic for decades, (with important results from at least 1988) and has always sought to have reliable measures and large sample sizes before publishing anything. In ISIR 2014, tired of reading neuro-bollocks in the media, I lobbed Rex Jung what I thought might be a tricky question: How reliable are your neuro-imaging measures? He replied that he and Rich Haier had always put their subjects into the scanner twice: once briefly so as to get benchmark reliability measures, and then again for the full session. Jung and Haier also held back from publication until they had large sample sizes, although in early years this meant a long wait, since they were mostly working in the odd free spaces between the high priority medical school clinical use of the sole scanner available. Things have got better in recent years.

Another feature of this duo is that when they were offered an celebratory session at ISIR 2017 they chose to invite their critics to knock hell into them. Several did, and I pursue them every now and then to make their P-FIT theory more specific. So, it is great to be able to report some new and very specific findings.

Diffusion markers of dendritic density and arborization in gray matter predict differences in intelligence. Erhan Genç, Christoph Fraenz, Caroline Schlüter, Patrick Friedrich, Rüdiger Hossiep, Manuel C. Voelkle, Josef M. Ling, Onur Güntürkün & Rex E. Jung

Nature Communications volume 9, Article number: 1905 (2018)
doi:10.1038/s41467-018-04268-8

The first two authors contributed equally. Take a good look at their reference list, which is a roll-call of the top people in the field, and those one should turn to for further comments on this paper and its implications.

Here is the main finding in full screen size, with the relevant explanations.

https://www.nature.com/articles/s41467-018-04268-8/figures/4

Here is the link to the entire paper:

https://www.nature.com/articles/s41467-018-04268-8

Here is the abstract:

Previous research has demonstrated that individuals with higher intelligence are more likely to have larger gray matter volume in brain areas predominantly located in parieto-frontal regions. These findings were usually interpreted to mean that individuals with more cortical brain volume possess more neurons and thus exhibit more computational capacity during reasoning. In addition, neuroimaging studies have shown that intelligent individuals, despite their larger brains, tend to exhibit lower rates of brain activity during reasoning. However, the microstructural architecture underlying both observations remains unclear. By combining advanced multi-shell diffusion tensor imaging with a culture-fair matrix-reasoning test, we found that higher intelligence in healthy individuals is related to lower values of dendritic density and arborization. These results suggest that the neuronal circuitry associated with higher intelligence is organized in a sparse and efficient manner, fostering more directed information processing and less cortical activity during reasoning.

“Intelligence is not a function of how hard the brain works but rather how efficiently it works”.

In terms of method, the team collected 259 participants (138 males) between 18 and 40 years of age (M = 24.31, SD = 4.41) which gives the analysis of results sufficient power. Participants had no history of psychiatric or neurological disorders and matched the standard inclusion criteria for fMRI examinations. Each participant completed the matrix-reasoning test and neuroimaging measurements.
To validate the results obtained from sample of 259 subjects, the team downloaded additional data provided by the Human Connectome Project, namely, the “S500 plus MEG2” release. This set includes 506 participants with data suitable for their analyses. The best papers now give what would formerly have been two papers, for the price of one. The first sample is the sample of discovery, the second the sample of validation. Some things in science are getting better.

The measures themselves are a new variant of diffusion imaging analysis. If you will forgive a simplistic analysis: a pipe full of water will show different measures if measured end-on (where all the water in the pipe vibrates with the imposed resonance) as compared to when measured at right angles to the pipe (where only a small amount of water is available for resonance to be detected). In this way you can deduce which way the dendrites run in the brain.

Currently, the most promising technique for the quantification of neurite morphology is a diffusion MRI technique known as neurite orientation dispersion and density imaging (NODDI). This technique is based on a multi-shell high-angular-resolution diffusion imaging protocol and offers a novel way to analyze diffusion-weighted data with regard to tissue microstructure. It features a three-compartment model distinguishing intra-neurite, extra-neurite, and cerebrospinal fluid (CSF) environments. NODDI is based on a diffusion model that was successfully validated by histological examinations utilizing staining methods in gray and white matter of rats and ferrets. In addition, Zhang, Schneider have shown that NODDI is also capable of estimating diffusion markers of neurite density and orientation dispersion by in vivo measurements in humans. Direct validation of NODDI has recently been performed in a study investigating neurite dispersion as a potential marker of multiple sclerosis pathology in post-mortem spinal cord specimens. The authors reported that neurite density obtained from NODDI significantly matched neurite density, orientation dispersion, and myelin density obtained from histology. Furthermore, the authors also found that NODDI neurite dispersion matched the histological neurite dispersion. This indicates that NODDI metrics are closely reflecting their histological conditions.

The point is that this study confirms previous findings, that “measures of neurite density and arborization show negative relationships to measures of intelligence, implicating neural efficiency, particularly within parieto-frontal brain regions, as suggested by the vast majority of neuroimaging studies of intelligence”.

The study also provides a partial confirmation of the P-FIT theory, in that a majority of the observed associations between brain areas and intelligence conform to the predictions from P-FIT as proposed by Haier and Jung, or as further elaborated by Basten. The score could be called a 4 out of 5 area confirmation.

 
• Category: Science • Tags: Brain Scans, Brighter Brains, Intelligence, IQ 
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world IQ map becker 2018

Mankind’s IQ is 84-88. Becker May 2018 update

The London Conference on Intelligence began, as is now traditional, with an update on the project to produce a public database of the world’s IQ. It is hard to get academics to agree to anything, even when they are under bombardment, but this is one point of common purpose. Not surprisingly, there are many issues surrounding the notion of national IQs. Representativeness looms large. Well-organized countries have lots of data, less well-organized ones far less. Restricting the results to those countries which actually have data is an obvious step. For comparative purposes, one can look at the far less satisfactory approach of estimating missing country data by assuming they are like their nearest neighbours.

As befits a German, Becker has taken a systematic approach. He has now sorted the basics, such as the standard Flynn Effect correction to be applied, and now has to turn to the thorny matter of quality estimations, corrections for sample size, and the integrated representation of different measures of cognitive ability. There are also many new studies to be added. There are still many countries for which we do not have data.

When looking at his presentation slides, a few explanations are required.

DB = David Becker
L&V = Lynn and Vanhanen (authors of the original books on national IQs)
RPM = Raven’s Progressive Matrices (in various forms)
WISC = Wechsler Intelligence Scale for Children
CFT = Culture Fair Test

The last data slide Number 14 shows correlations between country IQs and a number of measures.
This slide is a useful summary of important findings so far.

Becker summary of correlations

Here is the link to his lecture:

https://drive.google.com/open?id=1l32bquDkqhvEkToK9Khs7X0rdD2Ydh5f

Finally, we hope that you will look at the data repository, and tell others it is available for inspection and comment.

http://viewoniq.org/

 
• Category: Science 
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Factfulness

Like many others, I first heard about the work of the late Hans Rosling through his TED lectures, in which his animated bubbles (nations over the decades shown as bubbles proportional to population size, rising or falling against some criterion, such as lifespan) revealed the mostly good news about human progress across the world. The lecture content was not a surprise. For decades the UN, WHO and other institutions had been showing welcome improvements in health and educational attainments in formerly poor countries. Documentaries in the 1980’s and 1990’s had illustrated the living circumstances of people at different levels of income. I can still remember an African man at the lowest living standards proudly showing off his heart-breaking annual material gains: a good shirt, a pair of trousers, and some shoes. The daily battle of the poor to get water, firewood and other necessities was contrasted at the end of the scale with a middle income European, where water came without any problem from taps in the home, the toilets flushed, and electricity and food were always available. It was all the more impactful because the Austrian’s income was low and his flat was modest, but it seemed bathed in luxury when set in global context.

This good message was amplified by many authors. Matt Ridley’s “Rational Optimist” was an excellent example. For centuries having light at home was a cumbersome and expensive business. The Romans had oil lamps with simple wicks. Candles were a great improvement, paraffin lamps with mantles (I grew up with those) an improvement on candles, and then incandescent bulbs were a paradigm shift, making night work possible. Since then the cost of lighting has fallen even further, with LED lighting consuming a fraction of the wattage of the older lamps. A good story of human ingenuity.

Hans Rosling, with whom I shared a Nobel Prize in 1985, follows a noble tradition of clear-headed helpfulness. A doctor specialising in public health, he used research to focus efforts on bringing health to poor (and poorly ) countries. Like all good educators, he begins with a quiz. The revelation of ignorance is the beginning of wisdom. I did pretty well on his questions, but felt I had cheated. From previous publications and some of my reading I knew the global story was a good one, so if in doubt I just went for the most positive outcomes. There are 13 questions, and I claim 9 right. By the way, question 7 is about the number of deaths from natural disasters. Page 5 says the deaths halved over the last 100 years (true) but page 271 says they doubled. Not good to criticize punters for getting questions wrong if the book can’t consistently get the answers right.

What is the book about? The major theme is that the state of the world is far better than people realise. Rosling does not regard himself as an optimist, but a possibilist. He shows that improvements are possible. While giving the figures, Rosling tries to explain why they come as a surprise to so many people, including aid workers, government officials, journalists, documentary film makers, and leaders of global corporations. He does very well on this, showing that we make a number of errors, particularly in using news broadcasts about exceptional events as a fallible benchmark regarding country differences. A lot of the book is about the proper management of data, and all this is good, and informative. He clearly shows that bad things are decreasing, and explains that publicizing these facts is not tantamount to declaring that no further effort is required to make things even better. Crime seems to be going up because we find murder stories more interesting than proper crime statistics. So long as we get an awful crime story once a week we can maintain our subjective feelings about society falling apart. Rosling is also good about the perils of simple extrapolation, and stresses the need to think in curves rather than just straight lines. Many global statistics are S shaped: a slow start when nothing seems to work, then a very rapid improvement, and then a gently rising plateau.

All this is very well, yet it would be wrong not to mention what the book leaves out. The underlying assumption is that all people all over the world are fundamentally the same, and although some countries have persistently rotten governments the people themselves are sensible, and have worked to achieve the great advances that the book records. Rosling puts no stock on the effects of ideology or religion, but believes that the data show that incremental improvements occur everywhere, despite those supposed differences.

There is validity in this argument, but it is far from a full picture. It is good to show that people make their own decisions about family size regardless of religion. I think that the “fundamental-sameness-of-people” argument somewhat elides obvious objections. Why should the good citizens of Africa require the services of a Swedish epidemiologist? Why not use home-grown talent? Rosling gave up his Christmas to hurry to Africa to sort out the Ebola crisis, having noticed the exponential rise of cases which normally denotes an epidemic. Once there he did a bit of work to distinguish between suspected and confirmed cases, showing that there was an understandable fear-driven over-diagnosis, super-imposed on a real epidemic, but that the steps taken so far were having the desired effect of reducing real cases. Good stuff. How come, some five or six decades after liberation from the colonial yoke, that no one on the ground in Africa had done the necessary spade work with the spreadsheets? (If they had, an apology is required from the authors).

David Landes’ conclusion, having studied the economic history of the world to determine how a nation becomes wealthy, can be summarised in one word: innovate. Rosling never mentions innovation. African inventions should be making their impact by now, at the very least challenging Asian and Indian businesses. He does not mention that China and India shot ahead by turning away from full central planning to their own versions of free enterprise. Rosling sees the growing level 2 world mostly as an investment opportunity for Western businesses. Some Africans have higher ambitions, and would like to be welcomed in Europe as wealthy tourists, once their own economies flourish in the globalised world economy. Too early to say when that will happen.

On the predicted African population boom Rosling is confident the UN is right to predict global population in 2100 as 11 billion, and that getting people out of extreme poverty will bring Africa down to the world pattern of less than 2.5 children per woman. However, he accepts that by 2100 there are predicted to be 3 billion more Africans and 1 billion more Asians, for a world picture of 1 billion Americans, 1 billion Europeans, 4 billion Africans, 5 billion Asians. He says that by 2014 60% of wealthy people (level 4) will live outside the West, and that Western domination of the world economy will be over. I feel that, in a mobile world, and given the track record of African governments, an extra 3 billion Africans will present the world with some problems, not least of which will be African migration to Europe.

 
• Category: Economics • Tags: Africa, Development 
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Psychological Comments screen grab youtube

Text is a refined type of talking. It involves an extra level of complexity, since reading and writing require some 7 years for a child to master, what with learning alphabets, reading, writing, and the composition of sentences, paragraphs and proper essays. The payoff from this investment is that written messages are compact, efficient, skippable, and eternal. Good quality ink on proper paper can last 500 years with reasonable care in a library. Every few years I look at the Salisbury Magna Carta, readable on vellum after eight centuries. Reading is a fast way of grasping the essentials of an idea, particularly when the writing has been very carefully considered. Words are tools of meaning.

I favour writing over talking because it is more precise, and easily editable. Ambiguities can be detected and corrected. Writing can be edited, errors quickly corrected.

However, speech is the more usual method of human communication. It seems to require no teaching at all, beyond immersion in the society of other talkers. A functional competence emerges in a few years, one of the wonders of human learning, and although vocabulary keeps increasing with the passing years the average 7 year old can give a good account of daily events, and understand much of the basics of language.

Speech reaches a wider audience, since not everyone reads, and listening is often easier than reading when there are other tasks to be done, or when concentration is fading. Ideally, speech can serve as the gentle introduction to deeper reading, a setting out of wares which might encourage some to take a longer look at a particular subject. This is particularly the case when you want to comment in general terms immediately, knowing that writing things up will take too long, or might even never get written up at all.

So, faced with a week in which many interesting papers had been published or publicize again, here is my attempt to supplement written accounts with some spoken commentary. Let me know what you think of it, and if you find it OK, recommend it to those who you think might listen to it.

Additional Notes

The Piffer equation is explained in my last post, and Piffer has added that the new correlation between his prediction and the observed genetic group means is 0.9

The bird migration paper is here, and turns out to be a 2010 study, recently in the news again:

http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0009617

The paper on free diving and larger spleens is here:

https://www.cell.com/cell/fulltext/S0092-8674(18)30386-6

The iris response aspect is in another study

By the way, the selective change to the iris is contraction to pin hole size for better focus, not expansion for greater light. My error. Easy to edit in text, hard to change on a video.

 
• Category: Science 
James Thompson
About James Thompson

James Thompson has lectured in Psychology at the University of London all his working life. His first publication and conference presentation was a critique of Jensen’s 1969 paper, with Arthur Jensen in the audience. He also taught Arthur how to use an English public telephone. Many topics have taken up his attention since then, but mostly he comments on intelligence research.