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A study involving 218 participants aged 18-88 has looked at the effects of age on the brain activity of participants viewing an edited version of a 1961 Hitchcock TV episode (given that participants viewed the movie while in a MRI machine, the 25 minute episode was condensed to 8 minutes).

While many studies have looked at how age changes brain function, the stimuli used have typically been quite simple. This thriller-type story provides more complex and naturalistic stimuli.

Younger adults' brains responded to the TV program in a very uniform way, while older adults showed much more idiosyncratic responses. The TV program (“Bang! You're dead”) has previously been shown to induce widespread synchronization of brain responses (such movies are, after all, designed to focus attention on specific people and objects; following along with the director is, in a manner of speaking, how we follow the plot). The synchronization seen here among younger adults may reflect the optimal response, attention focused on the most relevant stimulus. (There is much less synchronization when the stimuli are more everyday.)

The increasing asynchronization with age seen here has previously been linked to poorer comprehension and memory. In this study, there was a correlation between synchronization and measures of attentional control, such as fluid intelligence and reaction time variability. There was no correlation between synchronization and crystallized intelligence.

The greatest differences were seen in the brain regions controlling attention (the superior frontal lobe and the intraparietal sulcus) and language processing (the bilateral middle temporal gyrus and left inferior frontal gyrus).

The researchers accordingly suggested that the reason for the variability in brain patterns seen in older adults lies in their poorer attentional control — specifically, their top-down control (ability to focus) rather than bottom-up attentional capture. Attentional capture has previously been shown to be well preserved in old age.

Of course, it's not necessarily bad that a watcher doesn't rigidly follow the director's manipulation! The older adults may be showing more informed and cunning observation than the younger adults. However, previous studies have found that older adults watching a movie tend to vary more in where they draw an event boundary; those showing most variability in this regard were the least able to remember the sequence of events.

The current findings therefore support the idea that older adults may have increasing difficulty in understanding events — somthing which helps explain why some old people have increasing trouble following complex plots.

The findings also add to growing evidence that age affects functional connectivity (how well the brain works together).

It should be noted, however, that it is possible that there could also be cohort effects going on — that is, effects of education and life experience.

There's been a lot of talk in recent years about the importance of mindset in learning, with those who have a “growth mindset” (ie believe that intelligence can be developed) being more academically successful than those who believe that intelligence is a fixed attribute. A new study shows that a 45-minute online intervention can help struggling high school students.

The study involved 1,594 students in 13 U.S. high schools. They were randomly allocated to one of three intervention groups or the control group. The intervention groups either experienced an online program designed to develop a growth mindset, or an online program designed to foster a sense of purpose, or both programs (2 weeks apart). All interventions were expected to improve academic performance, especially in struggling students.

The interventions had no significant benefits for students who were doing okay, but were of significant benefit for those who had an initial GPA of 2 or less, or had failed at least one core subject (this group contained 519 students; a third of the total participants). For this group, each of the interventions was of similar benefit; interestingly, the combined intervention was less beneficial than either single intervention. It's plausibly suggested that this might be because the different messages weren't integrated, and students may have had some trouble in taking on board two separate messages.

Overall, for this group of students, semester grade point averages improved in core academic courses and the rate at which students performed satisfactorily in core courses increased by 6.4%.

GPA average in core subjects (math, English, science, social studies) was calculated at the end of the semester before the interventions, and at the end of the semester after the interventions. Brief questions before and after the interventions assessed the students' beliefs about intelligence, and their sense of meaningfulness about schoolwork.

GPA before intervention was positively associated with a growth mindset and a sense of purpose, explaining why the interventions had no effect on better students. Only the growth mindset intervention led to a more malleable view of intelligence; only the sense-of-purpose intervention led to a change in perception in the value of mundane academic tasks. Note that the combined intervention showed no such effects, suggesting that it had confused rather than enlightened!

In the growth mindset intervention, students read an article describing the brain’s ability to grow and reorganize itself as a consequence of hard work and good strategies. The message that difficulties don't indicate limited ability but rather provide learning opportunities, was reinforced in two writing exercises. The control group read similar materials, but with a focus on functional localization in the brain rather than its malleability.

In the sense-of-purpose interventions, students were asked to write about how they wished the world could be a better place. They read about the reasons why some students worked hard, such as “to make their families proud”; “to be a good example”; “to make a positive impact on the world”. They were then asked to think about their own goals and how school could help them achieve those objectives. The control group completed one of two modules that didn't differ in impact. In one, students described how their lives were different in high school compared to before. The other was much more similar to the intervention, except that the emphasis was on economic self-interest rather than social contribution.

The findings are interesting in showing that you can help poor learners with a simple intervention, but perhaps even more, for their indication that such interventions are best done in a more holistic and contextual way. A more integrated message would hopefully have been more effective, and surely ongoing reinforcement in the classroom would make an even bigger difference.

Because this is such a persistent myth, I thought I should briefly report on this massive study that should hopefully put an end to this myth once and for all (I wish! Myths are not so easily squashed.)

This study used data from 377,000 U.S. high school students, and, agreeing with a previous large study, found that first-borns have a one IQ point advantage over later-born siblings, but while statistically significant, this is a difference of no practical significance.

The analysis also found that first-borns tended to be more extroverted, agreeable and conscientious, and had less anxiety than later-borns, — but those differences were “infinitesimally small”, amounting to a correlation of 0.02 (the correlation between birth order and intelligence was .04).

The study controlled for potentially confounding factors, such as a family's economic status, number of children and the relative age of the siblings at the time of the analysis.

A separate analysis of children with exactly two siblings and living with two parents, enabled the finding that there are indeed specific differences between the oldest and a second child, and between second and third children. But the magnitude of the differences was again “minuscule”.

Perhaps it's not fair to say the myth is trounced. Rather, we can say that, yeah, sure, birth order makes a difference — but the difference is so small as not to be meaningful on an individual level.

Data from 1.1 million young Swedish men (conscription information taken at age 18) has shown that those with poorer cardiovascular fitness were 2.5 times more likely to develop early-onset dementia later in life and 3.5 times more likely to develop mild cognitive impairment, while those with a lower IQ had a 4 times greater risk of early dementia and a threefold greater risk of MCI. A combination of both poor cardiovascular fitness and low IQ entailed a more than 7 times greater risk of early-onset dementia, and more than 8 times greater risk of MCI.

The increased risk remained even when controlled for other risk factors, such as heredity, medical history, and social-economic circumstances.

The development of early-onset dementia was taken from national disease registries. During the study period, a total of 660 men were diagnosed with early-onset dementia.

A further study of this database, taken from 488,484 men, of whom 487 developed early-onset dementia (at a median age of 54), found nine risk factors for early-onset dementia that together accounted for 68% of the attributable risk. These factors were alcohol intoxication, stroke, use of antipsychotics, depression, father's dementia, drug intoxication other than alcohol, low cognitive function at age 18, low stature at age 18, and high blood pressure at age 18.

By using brain scans from 152 Vietnam veterans with a variety of combat-related brain injuries, researchers claim to have mapped the neural basis of general intelligence and emotional intelligence.

There was significant overlap between general intelligence and emotional intelligence, both in behavioral measures and brain activity. Higher scores on general intelligence tests and personality reliably predicted higher performance on measures of emotional intelligence, and many of the same brain regions (in the frontal and parietal cortices) were found to be important to both.

More specifically, impairments in emotional intelligence were associated with selective damage to a network containing the extrastriate body area (involved in perceiving the form of other human bodies), the left posterior superior temporal sulcus (helps interpret body movement in terms of intentions), left temporo-parietal junction (helps work out other person’s mental state), and left orbitofrontal cortex (supports emotional empathy). A number of associated major white matter tracts were also part of the network.

Two of the components of general intelligence were strong contributors to emotional intelligence: verbal comprehension/crystallized intelligence, and processing speed. Verbal impairment was unsurprisingly associated with selective damage to the language network, which showed some overlap with the network underlying emotional intelligence. Similarly, damage to the fronto-parietal network linked to deficits in processing speed also overlapped in places with the emotional intelligence network.

Only one of the ‘big five’ personality traits contributed to the prediction of emotional intelligence — conscientiousness. Impairments in conscientiousness were associated with damage to brain regions widely implicated in social information processing, of which two areas (left orbitofrontal cortex and left temporo-parietal junction) were also involved in impaired emotional intelligence, suggesting where these two attributes might be connected (ability to predict and understand another’s emotions).

It’s interesting (and consistent with the growing emphasis on connectivity rather than the more simplistic focus on specific regions) that emotional intelligence was so affected by damage to white matter tracts. The central role of the orbitofrontal cortex is also intriguing – there’s been growing evidence in recent years of the importance of this region in emotional and social processing, and it’s worth noting that it’s in the right place to integrate sensory and bodily sensation information and pass that onto decision-making systems.

All of this is to say that emotional intelligence depends on social information processing and general intelligence. Traditionally, general intelligence has been thought to be distinct from social and emotional intelligence. But humans are fundamentally social animals, and – contra the message of the Enlightenment, that we have taken so much to heart – it has become increasingly clear that emotions and reason are inextricably entwined. It is not, therefore, all that surprising that general and emotional intelligence might be interdependent. It is more surprising that conscientiousness might be rooted in your degree of social empathy.

It’s also worth noting that ‘emotional intelligence’ is not simply a trendy concept – a pop quiz question regarding whether you ‘have a high EQ’ (or not), but that it can, if impaired, produce very real problems in everyday life.

Emotional intelligence was measured by the Mayer, Salovey, Caruso Emotional Intelligence Test (MSCEIT), general IQ by the Wechsler Adult Intelligence Scale, and personality by the Neuroticism-Extroversion-Openness Inventory.

One of the researchers talks about this study on this YouTube video and on this podcast.

What underlies differences in fluid intelligence? How are smart brains different from those that are merely ‘average’?

Brain imaging studies have pointed to several aspects. One is brain size. Although the history of simplistic comparisons of brain size has been turbulent (you cannot, for example, directly compare brain size without taking into account the size of the body it’s part of), nevertheless, overall brain size does count for something — 6.7% of individual variation in intelligence, it’s estimated. So, something, but not a huge amount.

Activity levels in the prefrontal cortex, research also suggests, account for another 5% of variation in individual intelligence. (Do keep in mind that these figures are not saying that, for example, prefrontal activity explains 5% of intelligence. We are talking about differences between individuals.)

A new study points to a third important factor — one that, indeed, accounts for more than either of these other factors. The strength of the connections from the left prefrontal cortex to other areas is estimated to account for 10% of individual differences in intelligence.

These findings suggest a new perspective on what intelligence is. They suggest that part of intelligence rests on the functioning of the prefrontal cortex and its ability to communicate with the rest of the brain — what researchers are calling ‘global connectivity’. This may reflect cognitive control and, in particular, goal maintenance. The left prefrontal cortex is thought to be involved in (among other things) remembering your goals and any instructions you need for accomplishing those goals.

The study involved 93 adults (average age 23; range 18-40), whose brains were monitored while they were doing nothing and when they were engaged in the cognitively challenging N-back working memory task.

Brain activity patterns revealed three regions within the frontoparietal network that were significantly involved in this task: the left lateral prefrontal cortex, right premotor cortex, and right medial posterior parietal cortex. All three of these regions also showed signs of being global hubs — that is, they were highly connected to other regions across the brain.

Of these, however, only the left lateral prefrontal cortex showed a significant association between its connectivity and individual’s fluid intelligence. This was confirmed by a second independent measure — working memory capacity — which was also correlated with this region’s connectivity, and only this region.

In other words, those with greater connectivity in the left LPFC had greater cognitive control, which is reflected in higher working memory capacity and higher fluid intelligence. There was no correlation between connectivity and crystallized intelligence.

Interestingly, although other global hubs (such as the anterior prefrontal cortex and anterior cingulate cortex) also have strong relationships with intelligence and high levels of global connectivity, they did not show correlations between their levels of connectivity and fluid intelligence. That is, although the activity within these regions may be important for intelligence, their connections to other brain regions are not.

So what’s so important about the connections the LPFC has with the rest of the brain? It appears that, although it connects widely to sensory and motor areas, it is primarily the connections within the frontoparietal control network that are most important — as well as the deactivation of connections with the default network (the network active during rest).

This is not to say that the LPFC is the ‘seat of intelligence’! Research has made it clear that a number of brain regions support intelligence, as do other areas of connectivity. The finding is important because it shows that the left LPFC supports cognitive control and intelligence through a mechanism involving global connectivity and some other as-yet-unknown property. One possibility is that this region is a ‘flexible’ hub — able to shift its connectivity with a number of different brain regions as the task demands.

In other words, what may count is how many different connectivity patterns the left LPFC has in its repertoire, and how good it is at switching to them.

An association between negative connections with the default network and fluid intelligence also adds to evidence for the importance of inhibiting task-irrelevant processing.

All this emphasizes the role of cognitive control in intelligence, and perhaps goes some way to explaining why self-regulation in children is so predictive of later success, apart from the obvious.

A large long-running New Zealand study has found that people who started using cannabis in adolescence and continued to use it for years afterward showed a significant decline in IQ from age 13 to 38. This was true even in those who hadn’t smoked marijuana for some years.

The study has followed a group of 1,037 children born in 1972-73. At age 38, 96% of the 1004 living study members participated in the latest assessment. Around 5% were regularly smoking marijuana more than once a week before age 18 (cannabis use was ascertained in interviews at ages 18, 21, 26, 32, and 38 years, and this group was not more or less likely to have dropped out of the study).

This group showed an average decline in IQ of 8 points on cognitive tests at age 38 compared to scores at age 13. Such a decline was not found in those who began using cannabis after the age of 18. In comparison, those who had never used cannabis showed a slight increase in IQ. The effect was dose-dependent, with those diagnosed as cannabis dependent on three or more occasions showing the greatest decline.

While executive function and processing speed appeared to be the most seriously affected areas, impairment was seen across most cognitive domains and did not appear to be statistically significantly different across them.

The size of the effect is shown by a further measure: informants (nominated by participants as knowing them well) also reported significantly more attention and memory problems among those with persistent cannabis dependence. (Note that a decline of 8 IQ points in a group whose mean is 100 brings it down to 92.)

The researchers ruled out recent cannabis use, persistent dependence on other drugs (tobacco, alcohol, hard drugs), and schizophrenia, as alternative explanations for the effect. The effect also remained after years of education were taken into account.

The finding supports the view that the adolescent brain is vulnerable to the effects of marijuana, and that these effects are long-lasting and significant.

Some numbers for those interested: Of the 874 participants included in the analysis (those who had missed at least 3 interviews in the 25 years were excluded), 242 (28%) never used cannabis, 479 (55%) used it but were never diagnosed as cannabis-dependent, and 153 (17%) were diagnosed on at least one of the interviews as cannabis-dependent. Of these, 80 had been so diagnosed on only one occasion, 35 on two occasions, and 38 on three or more occasions. I note that the proportion of males was significantly higher in the cannabis-dependent groups (39% in never used; 49% in used but never diagnosed; 70%, 63%, 82% respectively for the cannabis-dependent).

Grasp of fractions and long division predicts later math success

One possible approach to improving mathematics achievement comes from a recent study finding that fifth graders' understanding of fractions and division predicted high school students' knowledge of algebra and overall math achievement, even after statistically controlling for parents' education and income and for the children's own age, gender, I.Q., reading comprehension, working memory, and knowledge of whole number addition, subtraction and multiplication.

The study compared two nationally representative data sets, one from the U.S. and one from the United Kingdom. The U.S. set included 599 children who were tested in 1997 as 10-12 year-olds and again in 2002 as 15-17-year-olds. The set from the U.K. included 3,677 children who were tested in 1980 as 10-year-olds and in 1986 as 16-year-olds.

You can watch a short video of Siegler discussing the study and its implications at

Spatial skills improve children’s number sense

More support for the idea that honing spatial skills leads to better mathematical ability comes from a new children’s study.

The study found that first- and second-graders with the strongest spatial skills at the beginning of the school year showed the most improvement in their number line sense over the course of the year. Similarly, in a second experiment, not only were those children with better spatial skills at 5 ½ better on a number-line test at age 6, but this number line knowledge predicted performance on a math estimation task at age 8.

Hasty answers may make boys better at math

A study following 311 children from first to sixth grade has revealed gender differences in their approach to math problems. The study used single-digit addition problems, and focused on the strategy of directly retrieving the answer from long-term memory.

Accurate retrieval in first grade was associated with working memory capacity and intelligence, and predicted a preference for direct retrieval in second grade. However, at later grades the relation reversed, such that preference in one grade predicted accuracy and speed in the next grade.

Unlike girls, boys consistently preferred to use direct retrieval, favoring speed over accuracy. In the first and second grades, this was seen in boys giving more answers in total, and more wrong answers. Girls, on the other hand, were right more often, but responded less often and more slowly. By sixth grade, however, the boys’ practice was paying off, and they were both answering more problems and getting more correct.

In other words, while ability was a factor in early skilled retrieval, the feedback loop of practice and skill leads to practice eventually being more important than ability — and the relative degrees of practice may underlie some of the gender differences in math performance.

The findings also add weight to the view being increasingly expressed, that mistakes are valuable and educational approaches that try to avoid mistakes (e.g., errorless learning) should be dropped.

Infants can’t compare big and small groups

Our brains process large and small numbers of objects using two different mechanisms, seen in the ability to estimate numbers of items at a glance and the ability to visually track small sets of objects. A new study indicates that at age one, infants can’t yet integrate those two processes. Accordingly, while they can choose the larger of two sets of items when both sets are larger or smaller than four, they can’t distinguish between a large (above four) and small (below four) set.

In the study, infants consistently chose two food items over one and eight items over four, but chose randomly when asked to compare two versus four and two versus eight.

The researchers suggest that educational programs that claim to give children an advantage by teaching them arithmetic at an early age are unlikely to be effective for this reason.

Previous research has pointed to a typical decline in our sense of control as we get older. Maintaining a sense of control, however, appears to be a key factor in successful aging. Unsurprisingly, in view of the evidence that self-belief and metacognitive understanding are important for cognitive performance, a stronger sense of control is associated with better cognitive performance. (By metacognitive understanding I mean the knowledge that cognitive performance is malleable, not fixed, and strategies and training are effective in improving cognition.)

In an intriguing new study, 36 older adults (aged 61-87, average age 74) had their cognitive performance and their sense of control assessed every 12 hours for 60 days. Participants were asked questions about whether they felt in control of their lives and whether they felt able to achieve goals they set for themselves.

The reason I say this is intriguing is that it’s generally assumed that a person’s sense of control — how much they feel in control of their lives — is reasonably stable. While, as I said, it can change over the course of a lifetime, until recently we didn’t think that it could fluctuate significantly in the course of a single day — which is what this study found.

Moreover, those who normally reported having a low sense of control performed much better on inductive reasoning tests during periods when they reported feeling a higher sense of control. Similarly, those who normally reported feeling a high sense of control scored higher on memory tests when feeling more in control than usual.

Although we can’t be sure (since this wasn’t directly investigated), the analysis suggests that the improved cognitive functioning stems from the feeling of improved control, not vice versa.

The study builds on an earlier study that found weekly variability in older adults’ locus of control and competency beliefs.

Assessment was carried out in the form of a daily workbook, containing a number of measures, which participants completed twice daily. Each assessment took around 30-45 minutes to complete. The measures included three cognitive tests (14 alternate forms of each of these were used, to minimize test familiarity):

  • Letter series test: 30 items in which the next letter in a series had to be identified. [Inductive reasoning]
  • Number comparison: 48 items in which two number strings were presented beside each other, and participants had to identify where there was any mismatch. [Perceptual speed]
  • Rey Auditory Verbal Learning Task: participants have to study a list of 15 unrelated words for one minute, then on another page recall as many of the words as they could. [Memory]

Sense of control over the previous 12 hours was assessed by 8 questions, to which participants indicated their agreement/disagreement on a 6-point scale. Half the questions related to ‘locus of control’ and half to ‘perceived competence’.

While, unsurprisingly, compliance wasn’t perfect (it’s quite an arduous regime), participants completed on average 115 of 120 workbooks. Of the possible 4,320 results (36 x 120), only 166 were missing.

One of the things that often annoys me is the subsuming of all within-individual variability in cognitive scores into averages. Of course averages are vital, but so is variability, and this too often is glossed over. This study is, of course, all about variability, so I was very pleased to see people’s cognitive variability spelled out.

Most of the variance in locus of control was of course between people (86%), but 14% was within-individual. Similarly, the figures for perceived competence were 88% and 12%. (While locus of control and perceived competence are related, only 26% of the variability in within-person locus of control was associated with competence, meaning that they are largely independent.)

By comparison, within-individual variability was much greater for the cognitive measures: for the letter series (inductive reasoning), 32% was within-individual and 68% between-individual; for the number matching (perceptual speed), 21% was within-individual and 79% between-individual; for the memory test, an astounding 44% was within-individual and 56% between-individual.

Some of this within-individual variability in cognitive performance comes down to practice effects, which were significant for all cognitive measures. For the memory test, time of day was also significant, with performance being better in the morning. For the letter and number series tests, previous performance also had a small effect on perceived competence. For the number matching, increase in competence subsequent to increased performance was greatest for those with lower scores. However, lagged analyses indicated that beliefs preceded performance to a greater extent than performance preceding beliefs.

While it wasn’t an aspect of this study, it should also be noted that a person’s sense of control may well vary according to domain (e.g., cognition, social interaction, health) and context. In this regard, it’s interesting to note the present findings that sense of control affected inductive reasoning for low-control individuals, but memory for high-control individuals, suggesting that the cognitive domain also matters.

Now this small study was a preliminary one and there are several limitations that need to be tightened up in subsequent research, but I think it’s important for three reasons:

  • as a demonstration that cognitive performance is not a fixed attribute;
  • as a demonstration of the various factors that can affect older adults’ cognitive performance;
  • as a demonstration that your beliefs about yourself are a factor in your cognitive performance.

[2794] Neupert SD, Allaire JC. I think I can, I think I can: Examining the within-person coupling of control beliefs and cognition in older adults. Psychology and Aging. 2012 :No Pagination Specified - No Pagination Specified.

This is another demonstration of stereotype threat, which is also a nice demonstration of the contextual nature of intelligence. The study involved 70 volunteers (average age 25; range 18-49), who were put in groups of 5. Participants were given a baseline IQ test, on which they were given no feedback. The group then participated in a group IQ test, in which 92 multi-choice questions were presented on a monitor (both individual and group tests were taken from Cattell’s culture fair intelligence test). Each question appeared to each person at the same time, for a pre-determined time. After each question, they were provided with feedback in the form of their own relative rank within the group, and the rank of one other group member. Ranking was based on performance on the last 10 questions. Two of each group had their brain activity monitored.

Here’s the remarkable thing. If you gather together individuals on the basis of similar baseline IQ, then you can watch their IQ diverge over the course of the group IQ task, with some dropping dramatically (e.g., 17 points from a mean IQ of 126). Moreover, even those little affected still dropped some (8 points from a mean IQ of 126).

Data from the 27 brain scans (one had to be omitted for technical reasons) suggest that everyone was initially hindered by the group setting, but ‘high performers’ (those who ended up scoring above the median) managed to largely recover, while ‘low performers’ (those who ended up scoring below the median) never did.

Personality tests carried out after the group task found no significant personality differences between high and low performers, but gender was a significant variable: 10/13 high performers were male, while 11/14 low performers were female (remember, there was no difference in baseline IQ — this is not a case of men being smarter!).

There were significant differences between the high and low performers in activity in the amygdala and the right lateral prefrontal cortex. Specifically, all participants had an initial increase in amygdala activation and diminished activity in the prefrontal cortex, but by the end of the task, the high-performing group showed decreased amygdala activation and increased prefrontal cortex activation, while the low performers didn’t change. This may reflect the high performers’ greater ability to reduce their anxiety. Activity in the nucleus accumbens was similar in both groups, and consistent with the idea that the students had expectations about the relative ranking they were about to receive.

It should be pointed out that the specific feedback given — the relative ranking — was not a factor. What’s important is that it was being given at all, and the high performers were those who became less anxious as time went on, regardless of their specific ranking.

There are three big lessons here. One is that social pressure significantly depresses talent (meetings make you stupid?), and this seems to be worse when individuals perceive themselves to have a lower social rank. The second is that our ability to regulate our emotions is important, and something we should put more energy into. And the third is that we’ve got to shake ourselves loose from the idea that IQ is something we can measure in isolation. Social context matters.

Benefits of high quality child care persist 30 years later

Back in the 1970s, some 111 infants from low-income families, of whom 98% were African-American, took part in an early childhood education program called the Abecedarian Project. From infancy until they entered kindergarten, the children attended a full-time child care facility that operated year-round. The program provided educational activities designed to support their language, cognitive, social and emotional development.

The latest data from that project, following up the participants at age 30, has found that these people had significantly more years of education than peers who were part of a control group (13.5 years vs 12.3), and were four times more likely to have earned college degrees (23% vs 6%).

They were also significantly more likely to have been consistently employed (75% had worked full time for at least 16 of the previous 24 months, compared to 53% of the control group) and less likely to have used public assistance (only 4% received benefits for at least 10% of the previous seven years, compared to 20% of the control group). However, income-to-needs ratios (income taken into account household size) didn’t vary significantly between the groups (mainly because of the wide variability; on the face of it, the means are very different, but the standard deviation is huge), and neither did criminal involvement (27% vs 28%).

See their website for more about this project.

Evidence that more time at school raises IQ

It would be interesting to see what the IQs of those groups are, particularly given that maternal IQ was around 85 for both treatment and control groups. A recent report analyzed the results of a natural experiment that occurred in Norway when compulsory schooling was increased from seven to nine years in the 1960s, meaning that students couldn’t leave until 16 rather than 14. Because all men eligible for the draft were given an IQ test at age 19, statisticians were able to look back and see what effect the increased schooling had on IQ.

They found that it had a substantial effect, with each additional year raising the average IQ by 3.7 points.

While we can’t be sure how far these results extend to other circumstances, they are clear evidence that it is possible to improve IQ through education.

Why children of higher-income parents start school with an advantage

Of course the driving idea behind improved child-care in the early years is all about the importance of getting off to a good start, and you’d expect that providing such care to children would have a greater long-term effect on IQ than simply extending time at school. Most such interventions have looked at the most deprived strata of society. An overlooked area is that of low to middle income families, who are far from having the risk factors of less fortunate families.

A British study involving 15,000 five-year-olds has found that, at the start of school, children from low to middle income families are five months behind children from higher income families in terms of vocabulary skills and have more behavior problems (they were also 8 months ahead of their lowest income peers in vocabulary).

Low-middle income (LMI) households are defined by the Resolution Foundation (who funded this research) as members of the working-age population in income deciles 2-5 who receive less than one-fifth of their gross household income from means-tested benefits (see their website for more detail on this).

Now the difference in home environment between LMI and higher income households is often not that great — particularly when you consider that it is often a difference rooted in timing. LMI households are more common in this group of families with children under five, because the parents are usually at an early stage of life. So what brings about this measurable difference in language and behavior development?

This is a tricky thing to derive from the data, and the findings must be taken with a grain of salt. And as always, interpretation is even trickier. But with this caveat, let’s see what we have. Let’s look at demographics first.

The first thing is the importance of parental education. Income plus education accounted for some 70-80% of the differences in development, with education more important for language development and income more important for behavior development. Maternal age then accounted for a further 10%. Parents in the higher-income group tended to be older and have better education (e.g., 18% of LMI mothers were under 25 at the child’s birth, compared to 6% of higher-income mothers; 30% of LMI parents had a degree compared to 67% of higher-income parents).

Interestingly, family size was equally important for language development (10%), but much less important for behavior development (in fact this was a little better in larger families). Differences in ethnicity, language, or immigration status accounted for only a small fraction of the vocabulary gap, and none of the behavior gap.

Now for the more interesting but much trickier analysis of environmental variables. The most important factor was home learning environment, accounting for around 20% of the difference. Here the researchers point to higher-income parents providing more stimulation. For example, higher-income parents were more likely to read to their 3-year-olds every day (75% vs 62%; 48% for the lowest-income group), to take them to the library at least once a month (42% vs 35% vs 26%), to take their 5-year-old to a play or concert (86% vs 75% vs 60%), to a museum/gallery (67% vs 48% vs 36%), to a sporting activity at least once a week (76% vs 57% vs 35%). Higher-income parents were also much less likely to allow their 3-year-olds to watch more than 3 hours of TV a day (7% vs 17% vs 25%). (I know the thrust of this research is the comparison between LMI and higher income, but I’ve thrown in the lowest-income figures to help provide context.)

Interestingly, the most important factor for vocabulary learning was being taken to a museum/gallery at age 5 (but remember, these correlations could go either way: it might well be that parents are more likely to take an articulate 5-year-old to such a place), with the second most important factor being reading to 3-year-old every day. These two factors accounted for most of the effects of home environment. For behavior, the most important factor was regular sport, followed by being to a play/concert, and being taken to a museum/gallery. Watching more than 3 hours of TV at age 3 did have a significant effect on both vocabulary and behavior development (a negative effect on vocabulary and a positive effect on behavior), while the same amount of TV at age 5 did not.

Differences in parenting style explained 10% of the vocabulary gap and 14% of the behavior gap, although such differences were generally small. The biggest contributors to the vocabulary gap were mother-child interaction score at age 3 and regular bedtimes at age 3. The biggest contributors to the behavior gap were regular bedtimes at age 5, regular mealtimes at age 3, child smacked at least once a month at age 5 (this factor also had a small but significant negative effect on vocabulary), and child put in timeout at least once a month at age 5.

Maternal well-being accounted for over a quarter of the behavior gap, but only a small proportion of the vocabulary gap (2% — almost all of this relates to social support score at 9 months). Half of the maternal well-being component of the behavior gap was down to psychological distress at age 5 (very much larger than the effect of psychological distress at age 3). Similarly, child and maternal health were important for behavior (18% in total), but not for vocabulary.

Material possessions, on the other hand, accounted for some 9% of the vocabulary gap, but none of the behavior gap. The most important factors here were no internet at home at age 5 (22% of LMIs vs 8% of higher-incomes), and no access to a car at age 3 (5% of LMIs had no car vs 1% of higher incomes).

As I’ve intimated, it’s hard to believe we can disentangle individual variables in the environment in an observational study, but the researchers believe the number of variables in the mix (158) and the different time points (many variables are assessed at two or more points) provided a good base for analysis.

[2676] Campbell FA, Pungello EP, Burchinal M, Kainz K, Pan Y, Wasik BH, Barbarin OA, Sparling JJ, Ramey CT. Adult outcomes as a function of an early childhood educational program: An Abecedarian Project follow-up. Developmental Psychology;Developmental Psychology. 2012 :No Pagination Specified - No Pagination Specified.

[2675] Brinch CN, Galloway TA. Schooling in adolescence raises IQ scores. Proceedings of the National Academy of Sciences [Internet]. 2012 ;109(2):425 - 430. Available from:

Washbrook, E., & Waldfogel, J. (2011). On your marks : Measuring the school readiness of children in low-to-middle income families. Resolution Foundation, December 2011.

The study involved 1,292 children followed from birth, whose cortisol levels were assessed at 7, 15, and 24 months. Three tests related to executive functions were given at age 3. Measures of parenting quality (maternal sensitivity, detachment, intrusiveness, positive regard, negative regard, and animation, during interaction with the child) and household environment (household crowding, safety and noise levels) were assessed during the home visits.

Earlier studies have indicated that a poor environment in and of itself is stressful to children, and is associated with increased cortisol levels. Interestingly, in one Mexican study, preschool children in poor homes participating in a conditional cash transfer scheme showed reduced cortisol levels.

This study found that children in lower-income homes received less positive parenting and had higher levels of cortisol in their first two years than children in slightly better-off homes. Higher levels of cortisol were associated with lower levels of executive function abilities, and to a lesser extent IQ, at 3 years.

African American children were more affected than White children on every measure. Cortisol levels were significantly higher; executive function and IQ significantly lower; ratings of positive parenting significantly lower and ratings of negative parenting significantly higher. Maternal education was significantly lower, poverty greater, homes more crowded and less safe.

The model derived from this data shows executive function negatively predicted by cortisol, while the effect on IQ is marginal. However, both executive function and IQ are predicted by negative parenting, positive parenting, and household risk (although this last variable has a greater effect on IQ than executive function). Neither executive function nor IQ was directly predicted by maternal education, ethnicity, or poverty level. Cortisol level was inversely related to positive parenting, but was not directly related to negative parenting or household risk.

Indirectly (according to this best-fit model), poverty was related to executive function through negative parenting; maternal education was related to executive function through negative parenting and to a lesser extent positive parenting; both poverty and maternal education were related to IQ through positive parenting, negative parenting, and household risk; African American ethnicity was related to executive function through negative parenting and positive parenting, and to IQ through negative parenting, positive parenting, and household risk. Cortisol levels were higher in African American children and this was unrelated to poverty level or maternal education.

Executive function (which includes working memory, inhibitory control, and attention shifting) is vital for self-regulation and central to early academic achievement. A link between cortisol level and executive function has previously been shown in preschool children, as well as adults. The association partly reflects the fact that stress hormone levels affect synaptic plasticity in the prefrontal cortex, where executive functions are carried out. This is not to say that this is the only brain region so affected, but it is an especially sensitive one. Chronic levels of stress alter the stress response systems in ways that impair flexible regulation.

What is important about this study is this association between stress level and cognitive ability at an early age, that the effect of parenting on cortisol is associated with positive aspects rather than negative ones, and that the association between poverty and cognitive ability is mediated by both cortisol and parenting behavior — both positive and negative aspects.

A final word should be made on the subject of the higher cortisol levels in African Americans. Because of the lack of high-income African Americans in the sample (a reflection of the participating communities), it wasn’t possible to directly test whether the effect is accounted for by poverty. So this remains a possibility. It is also possible that there is some genetic difference. But it also might reflect other sources of stress, such as that relating to prejudice and stereotype threat.

Based on mother’s ethnic status, 58% of the families were Caucasian and 42% African American. Two-thirds of the participants had an income-to-need ratio (estimated total household income divided by the 2005 federal poverty threshold adjusted for number of household members) less than 200% of poverty. Just over half of the mothers weren’t married, and most of them (89%) had never been married. The home visits at 7, 15, and 24 months lasted at least an hour, and include a videotaped free play or puzzle completion interaction between mother and child. Cortisol samples were taken prior to an emotion challenge task, and 20 minutes and 40 minutes after peak emotional arousal.

Long-term genetic effects of childhood environment

The long-term effects of getting off to a poor start are deeper than you might believe. A DNA study of forty 45-year-old males in a long-running UK study has found clear differences in gene methylation between those who experienced either very high or very low standards of living as children or adults (methylation of a gene at a significant point in the DNA reduces the activity of the gene). More than twice as many methylation differences were associated with the combined effect of the wealth, housing conditions and occupation of parents (that is, early upbringing) than were associated with the current socio-economic circumstances in adulthood (1252 differences as opposed to 545).

The findings may explain why the health disadvantages known to be associated with low socio-economic position can remain for life, despite later improvement in living conditions. The methylation profiles associated with childhood family living conditions were clustered together in large stretches of DNA, which suggests that a well-defined epigenetic pattern is linked to early socio-economic environment. Adult diseases known to be associated with early life disadvantage include coronary heart disease, type 2 diabetes and respiratory disorders.

[2589] Blair C, Granger DA, Willoughby M, Mills-Koonce R, Cox M, Greenberg MT, Kivlighan KT, Fortunato CK, the Investigators FLP. Salivary Cortisol Mediates Effects of Poverty and Parenting on Executive Functions in Early Childhood. Child Development [Internet]. 2011 :no - no. Available from:

Fernald, L. C., & Gunnar, M. R. (2009). Poverty-alleviation program participation and salivary cortisol in very low-income children. Social Science and Medicine, 68, 2180–2189.

[2590] Borghol N, Suderman M, McArdle W, Racine A, Hallett M, Pembrey M, Hertzman C, Power C, Szyf M. Associations with early-life socio-economic position in adult DNA methylation. International Journal of Epidemiology [Internet]. 2011 . Available from:

IQ has long been considered to be a fixed attribute, stable across our lifetimes. But in recent years, this assumption has come under fire, with evidence of the positive and negative effects education and experiences can have on people’s performance. Now a new (small) study provides a more direct challenge.

In 2004, 33 adolescents (aged 12-16) took IQ tests and had their brains scanned. These tests were repeated four years later. The teenagers varied considerably in their levels of ability (77-135 in 2004; 87-143 in 2008). While the average IQ score remained the same (112; 113), there were significant changes in the two IQ scores for some individuals, with some participants gaining as much as 21 points, and others falling as much as 18 points. Clear change in IQ occurred for a third of the participants, and there was no obvious connection to specific attributes (e.g., low performers didn’t get better while high performers got worse).

These changes in performance correlated with structural changes in the brain. An increase in verbal IQ score correlated with an increase in the density of grey matter in an area of the left motor cortex of the brain that is activated when articulating speech. An increase in non-verbal IQ score correlated with an increase in the density of grey matter in the anterior cerebellum, which is associated with movements of the hand. Changes in verbal IQ and changes in non-verbal IQ were independent.

While I’d really like to see this study repeated with a much larger sample, the findings are entirely consistent with research showing increases in grey matter density in specific brain regions subsequent to specific training. The novel part of this is the correlation with such large changes in IQ.

The findings add to growing evidence that teachers shouldn’t be locked into beliefs about a student’s future academic success on the basis of past performance.

Postscript: I should perhaps clarify that IQ performance at each of these time points was age-normed - this is not a case of children just becoming 'smarter with age'.

Music-based training 'cartoons' improved preschoolers’ verbal IQ

A study in which 48 preschoolers (aged 4-6) participated in computer-based, cognitive training programs that were projected on a classroom wall and featured colorful, animated cartoon characters delivering the lessons, has found that 90% of those who received music-based training significantly improved their scores on a test of verbal intelligence, while those who received visual art-based training did not.

The music-based training involved a combination of motor, perceptual and cognitive tasks, and included training on rhythm, pitch, melody, voice and basic musical concepts. Visual art training emphasized the development of visuo-spatial skills relating to concepts such as shape, color, line, dimension and perspective. Each group received two one-hour training sessions each day in classroom, over four weeks.

Children’s abilities and brain function were tested before the training and five to 20 days after the end of the programs. While there were no significant changes, in the brain or in performance, in the children who participated in the visual art training, nearly all of those who took the music-based training showed large improvements on a measure of vocabulary knowledge, as well as increased accuracy and reaction time. These correlated with changes in brain function.

The findings add to the growing evidence for the benefits of music training for intellectual development, especially in language.

Musical aptitude relates to reading ability through sensitivity to sound patterns

Another new study points to one reason for the correlation between music training and language acquisition. In the study, 42 children (aged 8-13) were tested on their ability to read and recognize words, as well as their auditory working memory (remembering a sequence of numbers and then being able to quote them in reverse), and musical aptitude (both melody and rhythm). Brain activity was also measured.

It turned out that both music aptitude and literacy were related to the brain’s response to acoustic regularities in speech, as well as auditory working memory and attention. Compared to good readers, poor readers had reduced activity in the auditory brainstem to rhythmic rather than random sounds. Responsiveness to acoustic regularities correlated with both reading ability and musical aptitude. Musical ability (largely driven by performance in rhythm) was also related to reading ability, and auditory working memory to both of these.

It was calculated that music skill, through the functions it shares with reading (brainstem responsiveness to auditory regularities and auditory working memory) accounts for 38% of the difference in reading ability between children.

These findings are consistent with previous findings that auditory working memory is an important component of child literacy, and that positive correlations exist between auditory working memory and musical skill.

Basically what this is saying, is that the auditory brainstem (a subcortical region — that is, below the cerebral cortex, where our ‘higher-order’ functions are carried out) is boosting the experience of predictable speech in better readers. This fine-tuning may reflect stronger top-down control in those with better musical ability and reading skills. While there may be some genetic contribution, previous research makes it clear that musicians’ increased sensitivity to sound patterns is at least partly due to training.

In other words, giving young children music training is a good first step to literacy.

The children were rated as good readers if they scored 110 or above on the Test of Word Reading Efficiency, and poor readers if they scored 90 or below. There were 8 good readers and 21 poor readers. Those 13 who scored in the middle were excluded from group analyses. Good and poor readers didn’t differ in age, gender, maternal education, years of musical training, extent of extracurricular activity, or nonverbal IQ. Only 6 of the 42 children had had at least a year of musical training (of which one was a poor reader, three were average, and two were good).

Auditory brainstem responses were gathered to the speech sound /da/, which was either presented with 100% probability, or randomly interspersed with seven other speech sounds. The children heard these sounds through an earpiece in the right ear, while they listened to the soundtrack of a chosen video with the other ear.

[2603] Moreno S, Bialystok E, Barac R, Schellenberg EGlenn, Cepeda NJ, Chau T. Short-Term Music Training Enhances Verbal Intelligence and Executive Function. Psychological Science [Internet]. 2011 ;22(11):1425 - 1433. Available from:

Strait, Dana L, Jane Hornickel, and Nina Kraus. “Subcortical processing of speech regularities underlies reading and music aptitude in children.” Behavioral and brain functions : BBF 7, no. 1 (October 17, 2011): 44.

Full text is available at

There has been a lot of argument over the years concerning the role of genes in intelligence. The debate reflects the emotions involved more than the science. A lot of research has gone on, and it is indubitable that genes play a significant role. Most of the research however has come from studies involving twins and adopted children, so it is indirect evidence of genetic influence.

A new technique has now enabled researchers to directly examine 549,692 single nucleotide polymorphisms (SNPs — places where people have single-letter variations in their DNA) in each of 3511 unrelated people (aged 18-90, but mostly older adults). This analysis had produced an estimate of the size of the genetic contribution to individual differences in intelligence: 40% of the variation in crystallized intelligence and 51% of the variation in fluid intelligence. (See for a discussion of the difference)

The analysis also reveals that there is no ‘smoking gun’. Rather than looking for a handful of genes that govern intelligence, it seems that hundreds if not thousands of genes are involved, each in their own small way. That’s the trouble: each gene makes such a small contribution that no gene can be fingered as critical.

Discussions that involve genetics are always easily misunderstood. It needs to be emphasized that we are talking here about the differences between people. We are not saying that half of your IQ is down to your genes; we are saying that half the difference between you and another person (unrelated but with a similar background and education — study participants came from Scotland, England and Norway — that is, relatively homogenous populations) is due to your genes.

If the comparison was between, for example, a middle-class English person and someone from a poor Indian village, far less of any IQ difference would be due to genes. That is because the effects of environment would be so much greater.

These findings are consistent with the previous research using twins. The most important part of these findings is the confirmation it provides of something that earlier studies have hinted at: no single gene makes a significant contribution to variation in intelligence.

It has been difficult to train individuals in such a way that they improve in general skills rather than the specific ones used in training. However, recently some success has been achieved using what is called an “n-back” task, a task that involves presenting a series of visual and/or auditory cues to a subject and asking the subject to respond if that cue has occurred, to start with, one time back. If the subject scores well, the number of times back is increased each round.

In the latest study, 62 elementary and middle school children completed a month of training on a computer program, five times a week, for 15 minutes at a time. While the active control group trained on a knowledge and vocabulary-based task, the experimental group was given a demanding spatial task in which they were presented with a sequence of images at one of six locations, one at a time, at a rate of 3s. The child had to press one key whenever the current image was at the same location as the one n items back in the series, and another key if it wasn’t. Both tasks employed themed graphics to make the task more appealing and game-like.

How far back the child needed to remember depended on their performance — if they were struggling, n would be decreased; if they were meeting the challenge, n would be increased.

Although the experimental and active control groups showed little difference on abstract reasoning tasks (reflecting fluid intelligence) at the end of the training, when the experimental group was divided into two subgroups on the basis of training gain, the story was different. Those who showed substantial improvement on the training task over the month were significantly better than the others, on the abstract reasoning task. Moreover, this improvement was maintained at follow-up testing three months later.

The key to success seems to be whether or not the games hit the “sweet spot” for the individual — fun and challenging, but not so challenging as to be frustrating. Those who showed the least improvement rated the game as more difficult, while those who improved the most found it challenging but not overwhelming.

You can try this task yourself at

Jaeggi, Susanne M, Martin Buschkuehl, John Jonides, and Priti Shah. “Short- and long-term benefits of cognitive training.” Proceedings of the National Academy of Sciences of the United States of America 2011 (June 13, 2011): 2-7.

[1183] Jaeggi SM, Buschkuehl M, Jonides J, Perrig WJ. From the Cover: Improving fluid intelligence with training on working memory. Proceedings of the National Academy of Sciences [Internet]. 2008 ;105(19):6829 - 6833. Available from:

Once upon a time we made a clear difference between emotion and reason. Now increasing evidence points to the necessity of emotion for good reasoning. It’s clear the two are deeply entangled.

Now a new study has found that those with a higher working memory capacity (associated with greater intelligence) are more likely to automatically apply effective emotional regulation strategies when the need arises.

The study follows on from previous research that found that people with a higher working memory capacity suppressed expressions of both negative and positive emotion better than people with lower WMC, and were also better at evaluating emotional stimuli in an unemotional manner, thereby experiencing less emotion in response to those stimuli.

In the new study, participants were given a test, then given either negative or no feedback. A subsequent test, in which participants were asked to rate their familiarity with a list of people and places (some of which were fake), evaluated whether their emotional reaction to the feedback affected their performance.

This negative feedback was quite personal. For example: "your responses indicate that you have a tendency to be egotistical, placing your own needs ahead of the interests of others"; "if you fail to mature emotionally or change your lifestyle, you may have difficulty maintaining these friendships and are likely to form insecure relations."

The false items in the test were there to check for "over claiming" — a reaction well known to make people feel better about themselves and control their reactions to criticism. Among those who received negative feedback, those with higher levels of WMC were found to over claim the most. The people who over claimed the most also reported, at the end of the study, the least negative emotions.

In other words, those with a high WMC were more likely to automatically use an emotion regulation strategy. Other emotional reappraisal strategies include controlling your facial expression or changing negative situations into positive ones. Strategies such as these are often more helpful than suppressing emotion.

Schmeichel, Brandon J.; Demaree, Heath A. 2010. Working memory capacity and spontaneous emotion regulation: High capacity predicts self-enhancement in response to negative feedback. Emotion, 10(5), 739-744.

Schmeichel, Brandon J.; Volokhov, Rachael N.; Demaree, Heath A. 2008. Working memory capacity and the self-regulation of emotional expression and experience. Journal of Personality and Social Psychology, 95(6), 1526-1540. doi: 10.1037/a0013345

A new perspective on learning comes from a study in which 18 volunteers had to push a series of buttons as fast as possible, developing their skill over three sessions. New analytical techniques were then used to see which regions of the brain were active at the same time. The analysis revealed that those who learned new sequences more quickly in later sessions were those whose brains had displayed more 'flexibility' in the earlier sessions — that is, different areas of the brain linked with different regions at different times.

At this stage, we don’t know how stable an individual’s flexibility is. It may be that individuals vary significantly over the course of time, and if so, this information could be of use in predicting the best time to learn.

But the main point is that the functional modules, the brain networks that are involved in specific tasks, are more fluid than we thought. This finding is in keeping, of course, with the many demonstrations of damage to one region being compensated by new involvement of another region.

[2212] Bassett DS, Wymbs NF, Porter MA, Mucha PJ, Carlson JM, Grafton ST. Dynamic reconfiguration of human brain networks during learning. Proceedings of the National Academy of Sciences [Internet]. 2011 ;108(18):7641 - 7646. Available from:

Whether IQ tests really measure intelligence has long been debated. A new study provides evidence that motivation is also a factor.

Meta-analysis of 46 studies where monetary incentives were used in IQ testing has revealed a large effect of reward on IQ score. The average effect was equivalent to nearly 10 IQ points, with the size of the effect depending on the size of the reward. Rewards greater than $10 produced increases roughly equivalent to 20 IQ points. The effects of incentives were greater for individuals with lower baseline IQ scores.

Follow-up on a previous study of 500 boys (average age 12.5) who were videotaped while undertaking IQ tests in the late 80s also supports the view that motivation plays a part in IQ. The tapes had been evaluated by those trained to detect signs of boredom and each boy had been given a motivational score in this basis. Some 12 years later, half the participants agreed to interviews about their educational and occupational achievements.

As found in other research, IQ score was found to predict various life outcomes, including academic performance in adolescence and criminal convictions, employment, and years of education in early adulthood. However, after taking into account motivational score, the predictiveness of IQ score was significantly reduced.

Differences in motivational score accounted for up to 84% of the difference in years of education (no big surprise there if you think about it), but only 25% of the differences relating to how well they had done in school during their teenage years.

In other words, test motivation can be a confounding factor that has inflated estimates of the predictive validity of IQ, but the fact that academic achievement was less affected by motivation demonstrates that high intelligence (leaving aside the whole thorny issue of what intelligence is) is still required to get a high IQ score.

This is not unexpected — from the beginning of intelligence testing, psychologists have been aware that test-takers vary in how seriously they take the test, and that this will impact on their scores. Nevertheless, the findings are a reminder of this often overlooked fact, and underline the importance of motivation and self-discipline, and the need for educators to take more account of these factors.

A study of 265 New York City minority children has found that those born with higher amounts of the insecticide chlorpyrifos had lower IQ scores at age 7. Those most exposed (top 25%) scored an average 5.3 points lower on the working memory part of the IQ test (WISC-IV), and 2.7 points lower on the full IQ test, compared to those in the lowest quartile.

The children were born prior to the 2001 ban on indoor residential use of the common household pesticide in the US. The babies' umbilical cord blood was used to measure exposure to the insecticide.

Previous research had found that, prior to the ban, chlorpyrifos was detected in all personal and indoor air samples in New York, and 70% of umbilical cord blood collected from babies. The amount of chlorpyrifos in babies' blood was associated with neurodevelopmental problems at age three. The new findings indicate that these problems persist.

While exposure to the organophosphate has measurably declined, agricultural use is still permitted in the U.S.

Similarly, another study, involving 329 7-year-old children in a farming community in California, has found that those with the highest prenatal exposure to the pesticide dialkyl phosphate (DAP) had an average IQ 7 points lower than children whose exposure was in the lowest quintile. Prenatal pesticide exposure was linked to poorer scores for working memory, processing speed, verbal comprehension, and perceptual reasoning, as well as overall IQ.

Prenatal exposure was measured by DAP concentration in the mother’s urine. Urine was also collected from the children at age 6 months and 1, 2, 3½ and 5 years. However, there was no consistent link between children’s postnatal exposure and cognition.

While this was a farming community where pesticide exposure would be expected to be high, the levels were within the range found in the general population.

It’s recommended that people wash fruit and vegetables thoroughly, and limit their use of pesticides at home.

It’s well-established that feelings of encoding fluency are positively correlated with judgments of learning, so it’s been generally believed that people primarily use the simple rule, easily learned = easily remembered (ELER), to work out whether they’re likely to remember something (as discussed in the previous news report). However, new findings indicate that the situation is a little more complicated.

In the first experiment, 75 English-speaking students studied 54 Indonesian-English word pairs. Some of these were very easy, with the English words nearly identical to their Indonesian counterpart (e.g, Polisi-Police); others required more effort but had a connection that helped (e.g, Bagasi-Luggage); others were entirely dissimilar (e.g., Pembalut-Bandage).

Participants were allowed to study each pair for as long as they liked, then asked how confident they were about being able to recall the English word when supplied the Indonesian word on an upcoming test. They were tested at the end of their study period, and also asked to fill in a questionnaire which assessed the extent to which they believed that intelligence is fixed or changeable.

It’s long been known that theories of intelligence have important effects on people's motivation to learn. Those who believe each person possesses a fixed level of intelligence (entity theorists) tend to disengage when something is challenging, believing that they’re not up to the challenge. Those who believe that intelligence is malleable (incremental theorists) keep working, believing that more time and effort will yield better results.

The study found that those who believed intelligence is fixed did indeed follow the ELER heuristic, with their judgment of how well an item was learned nicely matching encoding fluency.

However those who saw intelligence as malleable did not follow the rule, but rather seemed to be following the reverse heuristic: that effortful encoding indicates greater engagement in learning, and thus is a sign that they are more likely to remember. This group therefore tended to be marginally underconfident of easy items, marginally overconfident for medium-level items, and significantly overconfident for difficult items.

However, the entanglement of item difficulty and encoding fluency weakens this finding, and accordingly a second experiment separated these two attributes.

In this experiment, 41 students were presented with two lists of nine words, one list of which was in small font (18-point Arial) and one in large font (48-point Arial). Each word was displayed for four seconds. While font size made no difference to their actual levels of recall, entity theorists were much more confident of recalling the large-size words than the small-size ones. The incremental theorists were not, however, affected by font-size.

It is suggested that the failure to find evidence of a ‘non-fluency heuristic’ in this case may be because participants had no control over learning time, therefore were less able to make relative judgments of encoding effort. Nevertheless, the main finding, that people varied in their use of the fluency heuristic depending on their beliefs about intelligence, was clear in both cases.

[2182] Miele DB, Finn B, Molden DC. Does Easily Learned Mean Easily Remembered?. Psychological Science [Internet]. 2011 ;22(3):320 - 324. Available from:

A study involving 750 sets of twins assessed at about 10 months and 2 years, found that at 10 months, there was no difference in how the children from different socioeconomic backgrounds performed on tests of early cognitive ability. However, by 2 years, children from high socioeconomic background scored significantly higher than those from low socioeconomic backgrounds. Among the 2-year-olds from poorer families, there was little difference between fraternal and identical twins, suggesting that genes were not the reason for the similarity in cognitive ability. However, among 2-year-olds from wealthier families, identical twins showed greater similarities in their cognitive performance than fraternal twins — genes accounted for about half of the variation in cognitive changes.

The findings are consistent with other recent research suggesting that individual differences in cognitive ability among children raised in socioeconomically advantaged homes are primarily due to genes, whereas environmental factors are more influential for children from disadvantaged homes.

An Australian study of 3796 14-year-olds has found that those who had been reported as having suffered abuse or neglect (7.9%) scored the equivalent of some three IQ points lower than those who had not been maltreated, after accounting for a large range of socioeconomic and other factors. Abuse and neglect were independent factors: those who suffered both (and 74% of those who suffered neglect also suffered abuse) were doubly affected.

A number of studies have provided evidence that eating breakfast has an immediate benefit for cognitive performance in children. Now a new study suggests some “good” breakfasts are better than others.

A Japanese study of 290 healthy, well-nourished children, has revealed that those whose breakfast staple was white rice had a significantly larger ratio of gray matter in their brains, and several significantly larger regions, including the left superior temporal gyrus and bilateral caudate. Those who habitually ate white bread had significantly larger regional gray and white matter volumes of several regions, including the orbitofrontal gyri, right precentral gyrus and postcentral gyrus. Overall IQ scores, and scores on the perceptual organization subcomponent in particular, were significantly higher for the rice group.

One possible reason for the difference may be the difference in the glycemic index (GI) of these two substances; foods with a low GI are associated with less blood-glucose fluctuation than are those with a high GI. There is also a difference in fat content, with those eating white bread typically consuming more fat than those eating a rice-based breakfast. High levels of fat have been shown to reduce the expression of BDNF.

Regardless of the reason for the difference, the fact that breakfast staple type affects brain size and cognitive function in healthy children points to the importance of good nutrition during the years of brain development.

Manganese exposure in the workplace is known to have neurotoxic effects, but manganese occurs naturally in soil and sometimes in groundwater. One region where the groundwater contains naturally high levels of manganese is Quebec. A study involving 362 Quebec children, aged 6-13, has measured both the concentrations of metals (manganese, iron, copper, lead, zinc, arsenic, magnesium and calcium) in their tap water, and their cognitive abilities.

Although manganese concentrations were well below current guidelines, the average IQ of those whose tap water was in the upper 20% was 6.2 points below children whose water contained little or no manganese. The association was more marked for Performance IQ than Verbal IQ (Performance IQ reflects perceptual organization and processing speed). The analysis took into account factors such as family income, maternal intelligence, maternal education, and the presence of other metals in the water. No association was found between manganese in their food and IQ.

No surprise to me (I’m hopeless at faces), but a twin study has found that face recognition is heritable, and that it is inherited separately from IQ. The findings provide support for a modular concept of the brain, suggesting that some cognitive abilities, like face recognition, are shaped by specialist genes rather than generalist genes. The study used 102 pairs of identical twins and 71 pairs of fraternal twins aged 7 to 19 from Beijing schools to calculate that 39% of the variance between individuals on a face recognition task is attributable to genetic effects. In an independent sample of 321 students, the researchers found that face recognition ability was not correlated with IQ.

Zhu, Q. et al. 2010. Heritability of the specific cognitive ability of face perception. Current Biology, 20 (2), 137-142.

The ongoing 12-year Connecticut Longitudinal Study, involving a representative sample of 445 schoolchildren, has found that in typical readers, IQ and reading not only track together, but also influence each other over time. But in children with dyslexia, IQ and reading are not linked over time and do not influence one another. Although this difference has been assumed, this is the first direct evidence for it. It should also be noted that the language problem is not confined to reading: those with dyslexia take a long time to retrieve words, so they might not speak or read as fluidly as others.

[550] Ferrer E, Shaywitz BA, Holahan JM, Marchione K, Shaywitz SE. Uncoupling of reading and IQ over time: empirical evidence for a definition of dyslexia. Psychological Science: A Journal of the American Psychological Society / APS [Internet]. 2010 ;21(1):93 - 101. Available from:

A new theory suggests that more intelligent people are more likely than less intelligent people to adopt evolutionarily novel preferences and values, and that these values include liberalism (caring about numerous genetically unrelated strangers they never meet or interact with), atheism, and, in men, monogamy. Data from the National Longitudinal Study of Adolescent Health (Add Health) provide support: Young adults who self-identify as "very liberal" have an average IQ of 106 while those who self-identify as "very conservative" have an average IQ of 95; young adults who self-identify as "not at all religious" have an average IQ of 103, while those who self-identify as "very religious" have an average IQ of 97. The study follows on from a previous study showing that more intelligent individuals were more nocturnal, waking up and staying up later than less intelligent individuals. Being nocturnal is evolutionarily novel for humans.

[184] Kanazawa S. Why Liberals and Atheists Are More Intelligent. Social Psychology Quarterly [Internet]. 2010 ;73(1):33 - 57. Available from:

A study of 80 pairs of middle-income Canadian mothers and their year-old babies has revealed that children of mothers who answered their children's requests for help quickly and accurately; talked about their children's preferences, thoughts, and memories during play; and encouraged successful strategies to help solve difficult problems, performed better at a year and a half and 2 years on tasks that call for executive skills, compared to children whose mothers didn't use these techniques.

A new analysis of data first published in 2002 in a controversial book called IQ and the Wealth of Nations and then expanded in 2006, argues that national differences in IQ are best explained not by differences in national wealth (the original researchers’ explanation), but by the toll of infectious diseases. The idea is that energy used to fight infection is energy taken from brain development in children. Using 2004 data on infectious disease burden from the World Health Organization, and factors that have been linked to national IQ, such as nutrition, literacy, education, gross domestic product, and temperature, the analysis revealed that infectious disease burden was more closely correlated to average IQ than the other variables, alone accounting for 67% of the worldwide variation in intelligence. The researchers also suggest that the Flynn effect (the rise in IQs seen in developed countries during the 20th century) may be caused in part by the decrease in the intensity of infectious diseases as nations develop.

Data from more than 20,000 18-year-old Israeli men has revealed that IQ scores are lower in male adolescents who smoke compared to non-smokers, and in twin brothers who smoke compared to their non-smoking brothers. The average IQ for a non-smoker was about 101, while the smokers' average was about 94, with those who smoked more than a pack a day being lower still, at about 90. 28% of the sample smoked one or more cigarettes a day, 3% identified as ex-smokers, and 68% said they never smoked.

A study involving 136 healthy institutionalized infants (average age 21 months) from six orphanages in Bucharest, Romania, has found that those randomly assigned to a foster care program showed rapid increases in height and weight (but not head circumference), so that by 12 months, all of them were in the normal range for height, 90% were in the normal range for weight, and 94% were in the normal range of weight for height. Caregiving quality (particularly sensitivity and positive regard for the child, including physical affection) positively correlated with catch-up. Children whose height caught up to normal levels also appeared to improve their cognitive abilities. Each incremental increase of one in standardized height scores between baseline and 42 months was associated with an average increase of 12.6 points in verbal IQ.

Older news items (pre-2010) brought over from the old website

Aerobic fitness boosts IQ in teenage boys

Data from the 1.2 million Swedish men born between 1950 and 1976 who enlisted for mandatory military service at the age of 18 has revealed that on every measure of cognitive performance, average test scores increased according to aerobic fitness — but not muscle strength. The link was strongest for logical thinking and verbal comprehension, and the association was restricted to cardiovascular fitness. The results of the study also underline the importance of getting healthier between the ages of 15 and 18 while the brain is still changing — those who improved their cardiovascular health between 15 and 18 showed significantly greater intelligence scores than those who became less healthy over the same time period. Those who were fittest at 18 were also more likely to go to college. Although association doesn’t prove cause, the fact that the association was only with cardiovascular fitness and not strength supports a cardiovascular effect on brain function. Results from over 260,000 full-sibling pairs, over 3,000 sets of twins, and more than 1,400 sets of identical twins, also supports a causal relationship.

[1486] Åberg MAI, Pedersen NL, Torén K, Svartengren M, Bäckstrand B, Johnsson T, Cooper-Kuhn CM, Åberg DN, Nilsson M, Kuhn GH. Cardiovascular fitness is associated with cognition in young adulthood. Proceedings of the National Academy of Sciences [Internet]. 2009 ;106(49):20906 - 20911. Available from:

Confidence as important as IQ in exam success

I’ve talked repeatedly about the effects of self-belief on memory and cognition. One important area in which this is true is that of academic achievement. Evidence indicates that your perceived abilities matter, just as much? more than? your actual abilities. It has been assumed that self perceived abilities, self-confidence if you will, is a product mainly of nurture. Now a new twin study provides evidence that nurture / environment may only provide half the story; the other half may lie in the genes. The study involved 1966 pairs of identical twins and 1877 pairs of fraternal twins. The next step is to tease out which of these genes are related to IQ and which to personality variables.

[1080] Greven CU, Harlaar N, Kovas Y, Chamorro-Premuzic T, Plomin R. More Than Just IQ: School Achievement Is Predicted by Self-Perceived Abilities—But for Genetic Rather Than Environmental Reasons. Psychological Science [Internet]. 2009 ;20(6):753 - 762. Available from:

Children of older fathers perform less well in intelligence tests during infancy

Reanalysis of a dataset of over 33,000 children born between 1959 and 1965 and tested at 8 months, 4 years, and 7 years, has revealed that the older the father, the more likely the child was to have lower scores on the various tests used to measure the ability to think and reason, including concentration, learning, memory, speaking and reading skills. In contrast, the older the mother, the higher the scores of the child in the cognitive tests.

[1447] Saha S, Barnett AG, Foldi C, Burne TH, Eyles DW, Buka SL, McGrath JJ. Advanced Paternal Age Is Associated with Impaired Neurocognitive Outcomes during Infancy and Childhood. PLoS Med [Internet]. 2009 ;6(3):e1000040 - e1000040. Available from:

Full text available at

Brain-training to improve working memory boosts fluid intelligence

General intelligence is often separated into "fluid" and "crystalline" components, of which fluid intelligence is considered more reflective of “pure” intelligence (for more on this, see my article), and largely resistant to training and learning effects. However, in a new study in which participants were given a series of training exercises designed to improve their working memory, fluid intelligence was found to have significantly improved, with the amount of improvement increasing with time spent training. The small study contradicts decades of research showing that improving on one kind of cognitive task does not improve performance on other kinds, so has been regarded with some skepticism by other researchers. More research is definitely needed, but the memory task did differ from previous studies, engaging executive functions such as those that inhibit irrelevant items, monitor performance, manage two tasks simultaneously, and update memory.

[1183] Jaeggi SM, Buschkuehl M, Jonides J, Perrig WJ. From the Cover: Improving fluid intelligence with training on working memory. Proceedings of the National Academy of Sciences [Internet]. 2008 ;105(19):6829 - 6833. Available from:

Effect of schooling on achievement gaps within racial groups

Analysis of data from a national sample (U.S.) of 8,060 students, collected at four points in time, starting in kindergarten and ending in the spring of fifth grade, has found evidence that education has an impact in closing the achievement gap for substantial numbers of children. High-performing groups in reading were found among all races. About 30% of European Americans, 26% of African Americans and 45% of Asian Americans were in high-achieving groups by the spring of fifth grade — these groups included approximately 23% of African American children and 36% of Asian children who caught up with the initial group of high achievers over time. Only around 4% of European American students were in catch-up groups, because a higher percentage of European Americans started kindergarten as high achievers in reading. The situation was different for Hispanic students, however.  By the end of fifth grade, just over 5% of Hispanic children were high achievers in reading, while the remainder tested in the middle range. There were no low achievers and no catch-up groups. A different pattern was found in math. Only 17% of European American students were high-achievers in math by the end of fifth grade, including 13% who started kindergarten at a lower achievement level and caught up over time.  About 18% of Asian Americans were high-achievers at the end of fifth grade (11% catch-up). Only 0.3% of African Americans were high achievers at the end of fifth grade, and 26% were medium-high achievers. But about 16% of Hispanics were high achievers in math. There were no catch-up groups for either the African Americans or the Hispanics. This suggests that current schooling doesn't have as strong an impact on math achievement as it does in reading.

The study was presented in Washington, D.C. at the 2008 annual meeting of the Society for Research on Educational Effectiveness.

Autism non-verbal not unintelligent

New findings suggest that the association of autism with low intelligence is a product of their language difficulties. Testing autistic kids and normal kids on two popular IQ tests — the WISC (which relies heavily on language) and Raven's Progressive Matrices (considered the best test of "fluid intelligence", and a test that doesn't require much language) found that while not a single autistic child scored in the "high intelligence" range of the WISC, a third did on the Raven's. A third of the autistics had WISC scores in the mentally retarded range, but only one in 20 scored that low on the Raven's test. The non-autistic children scored similarly on both tests. The same results occurred when the experiment was run on autistic and normal adults.

[580] Dawson M, Soulières I, Gernsbacher MA, Mottron L. The level and nature of autistic intelligence. Psychological Science: A Journal of the American Psychological Society / APS [Internet]. 2007 ;18(8):657 - 662. Available from:

Being treated as oldest linked to IQ

The question of whether there is an IQ advantage to being the first-born has long been debated. Now analysis of IQ test results of 241,310 Norwegians drafted into the armed forces between 1967 and 1976 has revealed that the average IQ of first-born men was 103.2 while second-born men averaged 101.2 and third-borns, 100.0. However, second-born men whose older sibling died in infancy scored 102.9, and if both older siblings died young, the third-born score rose to 102.6. This suggests the advantage lies in the social rank in the family and not birth order as such.

[589] Kristensen P, Bjerkedal T. Explaining the Relation Between Birth Order and Intelligence. Science [Internet]. 2007 ;316(5832):1717 - 1717. Available from:

Executive function as important as IQ for math success

A study of 141 preschoolers from low-income homes has found that a child whose IQ and executive functioning were both above average was three times more likely to succeed in math than a child who simply had a high IQ. The parts of executive function that appear to be particularly linked to math ability in preschoolers are working memory and inhibitory control. In this context, working memory may be thought of as the ability to keep information or rules in mind while performing mental tasks. Inhibitory control is the ability to halt automatic impulses and focus on the problem at hand. Inhibitory control was also important for reading ability. The finding offers the hope that training to improve executive function will improve academic performance.

[1256] Blair C, Razza RP. Relating Effortful Control, Executive Function, and False Belief Understanding to Emerging Math and Literacy Ability in Kindergarten. Child Development. 2007 ;78(2):647 - 663.

Students who believe intelligence can be developed perform better

Research with 12-year-olds has found that, although all students began the study with equivalent achievement levels in math, over a two year period, those who believed that intelligence was malleable increasingly did better than those who believed their intelligence was fixed. Another study found that, when students showing declines in their math grades were taught that intelligence could be increased, they reversed their decline and showed significantly higher math grades than others who weren’t taught that.

[1123] Blackwell LS, Trzesniewski KH, Dweck CS. Implicit Theories of Intelligence Predict Achievement across an Adolescent Transition: A Longitudinal Study and an Intervention. Child Development. 2007 ;78(1):246 - 263.

Implicit stereotypes and gender identification may affect female math performance

Relatedly, another study has come out showing that women enrolled in an introductory calculus course who possessed strong implicit gender stereotypes, (for example, automatically associating "male" more than "female" with math ability and math professions) and were likely to identify themselves as feminine, performed worse relative to their female counterparts who did not possess such stereotypes and who were less likely to identify with traditionally female characteristics. Strikingly, a majority of the women participating in the study explicitly expressed disagreement with the idea that men have superior math ability, suggesting that even when consciously disavowing stereotypes, female math students are still susceptible to negative perceptions of their ability.

[969] Kiefer AK, Sekaquaptewa D. Implicit stereotypes, gender identification, and math-related outcomes: a prospective study of female college students. Psychological Science: A Journal of the American Psychological Society / APS [Internet]. 2007 ;18(1):13 - 18. Available from:

Reducing the racial achievement gap

And staying with the same theme, a study that came out six months ago, and recently reviewed on the excellent new Scientific American Mind Matters blog, revealed that a single, 15-minute intervention erased almost half the racial achievement gap between African American and white students. The intervention involved writing a brief paragraph about which value, from a list of values, was most important to them and why. The intervention improved subsequent academic performance for some 70% of the African American students, but none of the Caucasians. The study was repeated the following year with the same results. It is thought that the effect of the intervention was to protect against the negative stereotypes regarding the intelligence and academic capabilities of African Americans.

[1082] Cohen GL, Garcia J, Apfel N, Master A. Reducing the Racial Achievement Gap: A Social-Psychological Intervention. Science [Internet]. 2006 ;313(5791):1307 - 1310. Available from:

Fitness and childhood IQ indicators of cognitive ability in old age

Data from the Scottish Mental Survey of 1932 has revealed that physical fitness contributed more than 3% of the differences in cognitive ability in old age. The study involved 460 men and women, who were tested using the same cognitive test at age 79 that they had undergone at age 11. Physical fitness was defined by time to walk six meters, grip strength and lung function. Childhood IQ was also significantly related to lung function at age 79, perhaps because people with higher intelligence might respond more favorably to health messages about staying fit. But physical fitness was more important for cognitive ability in old age than childhood IQ. People in more professional occupations and with more education also had better fitness and higher cognitive test scores at 79.

[770] Deary IJ, Whalley LJ, Batty DG, Starr JM. Physical fitness and lifetime cognitive change. Neurology [Internet]. 2006 ;67(7):1195 - 1200. Available from:

Black-white IQ gap has narrowed

Data now available suggests that Black Americans have gained an average of .18 IQ points a year on White Americans from 1972 to 2002 for a total gain of 5.4 IQ points.

[929] Dickens WT, Flynn JR. Black Americans reduce the racial IQ gap: evidence from standardization samples. Psychological Science: A Journal of the American Psychological Society / APS [Internet]. 2006 ;17(10):913 - 920. Available from:

Does IQ drop with age or does something else impact intelligence?

As people grow older, their IQ scores drop. But is it really that they lose intelligence? A study has found that if college students had to perform under conditions that mimic the perception deficits many older people have, their IQ scores would also take a drop.

[234] Gilmore GC, Spinks RA, Thomas CW. Age effects in coding tasks: componential analysis and test of the sensory deficit hypothesis. Psychology and Aging [Internet]. 2006 ;21(1):7 - 18. Available from:

Smarter kids may live longer

A prospective study that recruited 897 individuals who scored 135 or higher on the Stanford-Binet IQ test in 1922 has found that higher IQs were associated with longevity, with the survival advantage leveling off after a childhood IQ of 163. The association was independent of childhood social position (as measured by father’s occupation). The study confirms earlier research suggesting an association between IQ and mortality, and provides the new finding of where the cut-off point (when high IQ no longer brought additional health benefits) appears — the cutoff of 163 was much higher than expected. Suggested reasons for the association (all of which may well be valid) include: greater tendency to adopt healthy habits and avoid bad ones; increased probability of better jobs; better skills for managing their health and the health-care system.

[690] Martin LT, Kubzansky LD. Childhood Cognitive Performance and Risk of Mortality: A Prospective Cohort Study of Gifted Individuals. Am. J. Epidemiol. [Internet]. 2005 ;162(9):887 - 890. Available from:

Growing up in a chaotic home may impair child's cognitive development

An association between disorganized, noisy and cramped homes and lower childhood intelligence has been observed before, but the reasons for the association have never been clear. Now a study of some 8000 3- and 4-year-old twins has perhaps disentangled the variables, and has found that chaos had an influence on cognitive skills independent of socioeconomic status. The findings also suggest that when the environment is more stressful, intelligence is more likely to be constrained by genes.

[570] Petrill SA, Pike A, Price T, Plomin R. Chaos in the home and socioeconomic status are associated with cognitive development in early childhood: Environmental mediators identified in a genetic design. Intelligence [Internet]. Submitted ;32(5):445 - 460. Available from:

Early music instruction raises child’s IQ

A new study confirms earlier research supporting the benefits of early music instruction. The study involved 144 children, 6 years old at the start of the study. They were given free weekly voice or piano lessons at the Royal Conservatory of Music. Another group of 6-year-olds was given free training in weekly drama classes, while a fourth group received no extra classes during the study period. Before any classes were given, all the children were tested using the full Weschler intelligence test. At the end of the school year (their first school year), the children were retested. All had an IQ increase of at least 4.3 points on average (a consequence of going to school). Children who took drama lessons scored no higher than those who had no extra lessons, but those who took music lessons scored on average 2.7 points higher than the children who did not take music lessons. Those in the drama group did however show substantial improvement in adaptive social behavior.

[1009] Schellenberg EGlenn. Music lessons enhance IQ. Psychological Science: A Journal of the American Psychological Society / APS [Internet]. 2004 ;15(8):511 - 514. Available from:

Knowledge-based IQ test predicts work performance as well as school

A meta-analysis of 127 studies supports the view that the Miller Analogies Test (MAT) — a knowledge-based test used for admissions decisions into U.S. graduate schools as well as in hiring and promotion decisions in the workplace since 1926 — is predictive of performance in both the academic and workplace environments. Specifically, MAT was a valid predictor of seven of the eight measures of graduate student performance, five of the six school-to-work transition performance criteria, and all four of the work performance criteria. MAT is assumed to measure “g”, the oft-debated “general intelligence” factor.

[1109] Kuncel NR, Hezlett SA, Ones DS. Academic Performance, Career Potential, Creativity, and Job Performance: Can One Construct Predict Them All?. Journal of Personality and Social Psychology [Internet]. 2004 ;86(1):148 - 161. Available from:

Support for "general intelligence" factor

Researchers into intelligence and memory have always concentrated on verbal abilities — for the good reason that they are considerably easier to test. New research suggests that strong visuospatial skills and working memory may be at least as good as verbal skills and working memory as indicators of general intelligence. The study, involving 167 subjects, found a clear relationship between being good at complex visuospatial tasks, and being good at tasks involving the so-called “central executive” (which coordinates tasks, sets goals, etc). The study lends support both to the view that intelligence has both discrete components and a general aspect, and that this “general intelligence” may be related to executive functioning.

[1152] Miyake A, Friedman NP, Rettinger DA, Shah P, Hegarty M. How are visuospatial working memory, executive functioning, and spatial abilities related? A latent-variable analysis. Journal of Experimental Psychology. General [Internet]. 2001 ;130(4):621 - 640. Available from: