News Topic intelligence

About these topic collections

I’ve been reporting on memory research for over ten years and these topic pages are simply collections of all the news items I have made on a particular topic. They do not pretend to be in any way exhaustive! I cover far too many areas within memory to come anywhere approaching that. What I aim to do is provide breadth, rather than depth. Outside my own area of cognitive psychology, it is difficult to know how much weight to give to any study (I urge you to read my blog post on what constitutes scientific evidence). That (among other reasons) is why my approach in my news reporting is based predominantly on replication and consistency. It's about the aggregate. So here is the aggregate of those reports I have at one point considered of sufficient interest to discuss. If you know of any research you would like to add to the collection, feel free to write about it in a comment (please provide a reference).

Factors that influence and are influenced by intelligence

Latest news

Nice review in Scientific American of some of the research showing that the active use of a wide array of effective learning strategies is more important for academic achievement than ‘ability’.

... The researchers related their findings to The Matthew Effect: those with high intrinsic motivation and effective learning strategies will tend to increase their ability, while those without those characteristics will tend to decrease their ability. Over time, the gap between those with higher ability and those with lower ability will widen. Which is all the more reason why we ought to set up the right conditions for active engagement for everyone, and teach people the proper strategies for success. ...

Read the full article

I'm a great believer in the wide-ranging, and widely-underestimated, effects of context - on all manner of things. I'm also a fan of the view that intelligence - so widely regarded as a fixed attribute - is also partly influenced by context. So I was pleased to see an article by Stephen Ceci - intelligence guru - discussing the role of context in cognitive development, and the implications of that for education.

Stephen Ceci at This View of Life:

When it comes to mental ability, many of our human talents were shaped by evolutionary forces that arose under the demanding conditions of life on the African savannah 35,000 to 50,000 years ago. Evolutionary psychologists have linked many of our current attributes to these earlier environmental challenges faced by our predecessors (Kanazawa, 2005). This much is noncontroversial. What is less agreed upon, however, is the extent to which present-day cognition is under the control of local conditions—that is, the specific physical, motivational, and psychological conditions under which humans attempt to solve problems. The argument I am making is that it is logically unsafe to claim that our successful performance on cognitive tasks today reflects our evolutionary preparation because the flip side is that our unsuccessful performance reflects our lack of evolutionary preparation—which may be wrong. In fact, a great deal of developmental research demonstrates that even when evolution has prepared us to undertake certain cognitive operations, successful performance depends on local conditions.


Educational implications. The goal of education is not to drum facts and concepts into children, but to create awareness of how these facts and concepts can be generalized to situations that differ from the ones used to teach them. Thus, the key is transferring knowledge from the contexts used to teach it to ones encountered outside of school. And yet, a great deal of empirical research has documented that young and old, high IQ and low IQ, schooled and unschooled, all fail to transfer learning to new contexts that differ from the context in which they were originally taught (e.g., Ceci, 1996; Leshowitz, 1989). The research described here suggests that context is a constituent of cognition, not something adjunctive or peripheral to it. This view of cognition-in-context has several implications for education.

View of Life article

A study shows that IQ and conscientiousness significantly predict emotional intelligence, and identifies shared brain areas that underlie this interdependence.

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.

Brain imaging points to the importance of cognitive control, mediated by the connectivity of one particular brain region, for fluid intelligence.

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 small study has found that, in older adults, their sense of control fluctuates over the course of a day, and this affects their cognitive abilities.

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, S. D., & Allaire J. C. (2012).  I think I can, I think I can: Examining the within-person coupling of control beliefs and cognition in older adults. Psychology and Aging. No Pagination Specified - No Pagination Specified.

Follow-up on an early child-care program for low-income children finds long-term benefits for education and employment. A large study pinpoints the advantages children from higher-income families have over those from low-middle families. Norway shows how extending compulsory education is linked to higher IQ.

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, F. A., Pungello E. P., Burchinal M., Kainz K., Pan Y., Wasik B. H., et al. (2012).  Adult outcomes as a function of an early childhood educational program: An Abecedarian Project follow-up. Developmental Psychology;Developmental Psychology. No Pagination Specified - No Pagination Specified.

[2675] Brinch, C. N., & Galloway T. A. (2012).  Schooling in adolescence raises IQ scores. Proceedings of the National Academy of Sciences. 109(2), 425 - 430.

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

Stress in the lives of young children from low-income homes negatively affects their executive function and IQ, and these associations are mediated through parenting behavior and household risk.

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 D. A., Willoughby M., Mills-Koonce R., Cox M., Greenberg M. T., et al. (2011).  Salivary Cortisol Mediates Effects of Poverty and Parenting on Executive Functions in Early Childhood. Child Development. no - no.

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., et al. (2011).  Associations with early-life socio-economic position in adult DNA methylation. International Journal of Epidemiology.

A small study of adolescents shows marked variability in IQ over a four-year period for many of them. This variability correlated with specific changes in the brain.

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'.

A month-long music-based program produced dramatic improvement in preschoolers’ language skills. Another study helps explain why music training helps language skills.

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 E. Glenn, Cepeda N. J., & Chau T. (2011).  Short-Term Music Training Enhances Verbal Intelligence and Executive Function. Psychological Science. 22(11), 1425 - 1433.

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. http://www.ncbi.nlm.nih.gov/pubmed/22005291.

Full text is available at http://www.behavioralandbrainfunctions.com/content/pdf/1744-9081-7-44.pd...

Games that use the n-back task, designed to challenge working memory, may improve fluid intelligence, but only if the games are at the right level of difficulty for the individual.

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 http://brainworkshop.sourceforge.net/.

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. http://www.ncbi.nlm.nih.gov/pubmed/21670271.

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

A new study confirms earlier indications that those with a high working memory capacity are better able to regulate their emotions.

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

New analytic techniques reveal that functional brain networks are more fluid than we thought.

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, D. S., Wymbs N. F., Porter M. A., Mucha P. J., Carlson J. M., & Grafton S. T. (2011).  Dynamic reconfiguration of human brain networks during learning. Proceedings of the National Academy of Sciences. 108(18), 7641 - 7646.

A new review pointing to the impact of motivation on IQ score reminds us that this factor is significant, particularly for predicting accomplishments other than academic achievement.

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.

[2220] Duckworth, A. L., Quinn P. D., Lynam D. R., Loeber R., & Stouthamer-Loeber M. (2011).  Role of test motivation in intelligence testing. Proceedings of the National Academy of Sciences.

Two longitudinal studies, one rural and one urban, have reported an association between prenatal pesticide exposure and significantly lower IQ at age 7.

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.

Two experiments indicate that judgment about how well something is learned is based on encoding fluency only for people who believe intelligence is a fixed attribute.

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, D. B., Finn B., & Molden D. C. (2011).  Does Easily Learned Mean Easily Remembered?. Psychological Science. 22(3), 320 - 324.

A large study has found significantly lower IQ in teenagers who have suffered abuse and/or neglect.

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 Japanese study finds higher IQ among children who habitually eat white rice for breakfast, compared to those who eat white bread.

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.

The two measures of working memory capacity appear to be fully independent, and only one of them is related to intelligence.

The number of items a person can hold in short-term memory is strongly correlated with their IQ. But short-term memory has been recently found to vary along another dimension as well: some people remember (‘see’) the items in short-term memory more clearly and precisely than other people. This discovery has lead to the hypothesis that both of these factors should be considered when measuring working memory capacity. But do both these aspects correlate with fluid intelligence?

A new study presented 79 students with screen displays fleetingly showing either four or eight items. After a one-second blank screen, one item was returned and the subject asked whether that object had been in a particular location previously. Their ability to detect large and small changes in the items provided an estimate of how many items the individual could hold in working memory, and how clearly they remembered them. These measures were compared with individuals’ performance on standard measures of fluid intelligence.

Analysis of data found that these two measures of working memory — number and clarity —are completely independent of each other, and that it was the number factor only that correlated with intelligence.

This is not to say that clarity is unimportant! Only that it is not related to intelligence.

The ‘safe’ levels of manganese in water may need to be revisited after a study finds school-age children with high levels of manganese in their tap water have significantly lower IQs.

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.

A long-running study confirms that, as theorized, in typical readers, IQ and reading track together and influence each other, but neither of these things is true for children with dyslexia.

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 B. A., Holahan J. M., Marchione K., & Shaywitz S. E. (2010).  Uncoupling of reading and IQ over time: empirical evidence for a definition of dyslexia. Psychological Science: A Journal of the American Psychological Society / APS. 21(1), 93 - 101.

Findings from a survey of adolescents provides support for a theory that more intelligent people are more likely to adopt evolutionarily novel preferences and values, and that these values include liberalism, atheism, and, in men, monogamy.

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. (2010).  Why Liberals and Atheists Are More Intelligent. Social Psychology Quarterly. 73(1), 33 - 57.

A study of 80 pairs of middle-income Canadian mothers and their year-old babies has revealed conversational strategies that are associated with better executive skills among toddlers.

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.

Analysis of global data shows that differences in national IQs are most strongly predicted by the country's infectious disease burden.

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.

[1619] Eppig, C., Fincher C. L., & Thornhill R. (2010).  Parasite prevalence and the worldwide distribution of cognitive ability. Proceedings of the Royal Society B: Biological Sciences.

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 lower still in those who smoked more than a pack a day.

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 healthy institutionalized infants from six Romanian orphanages has found that those randomly assigned to a foster care program showed rapid increases in height and weight, and that this was associated with better caregiving quality and significantly improved verbal IQ.

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, M. A. I., Pedersen N. L., Torén K., Svartengren M., Bäckstrand B., Johnsson T., et al. (2009).  Cardiovascular fitness is associated with cognition in young adulthood. Proceedings of the National Academy of Sciences. 106(49), 20906 - 20911.

http://www.physorg.com/news179415275.html
http://www.telegraph.co.uk/science/science-news/6692474/Physical-health-leads-to-mental-health.html

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, C. U., Harlaar N., Kovas Y., Chamorro-Premuzic T., & Plomin R. (2009).  More Than Just IQ: School Achievement Is Predicted by Self-Perceived Abilities—But for Genetic Rather Than Environmental Reasons. Psychological Science. 20(6), 753 - 762.

http://www.newscientist.com/article/dn17187-confidence-as-important-as-iq-in-exam-success.html

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 A. G., Foldi C., Burne T. H., Eyles D. W., Buka S. L., et al. (2009).  Advanced Paternal Age Is Associated with Impaired Neurocognitive Outcomes during Infancy and Childhood. PLoS Med. 6(3), e1000040 - e1000040.

Full text available at http://medicine.plosjournals.org/perlserv/?request=get-document&doi=10.1371/journal.pmed.1000040

http://www.eurekalert.org/pub_releases/2009-03/plos-coo030309.php

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, S. M., Buschkuehl M., Jonides J., & Perrig W. J. (2008).  From the Cover: Improving fluid intelligence with training on working memory. Proceedings of the National Academy of Sciences. 105(19), 6829 - 6833.

http://www.physorg.com/news128699895.html
http://www.sciam.com/article.cfm?id=study-shows-brain-power-can-be-bolstered

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.

http://www.physorg.com/news123859991.html

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 M. A., & Mottron L. (2007).  The level and nature of autistic intelligence. Psychological Science: A Journal of the American Psychological Society / APS. 18(8), 657 - 662.

http://www.physorg.com/news105376203.html
http://www.eurekalert.org/pub_releases/2007-08/afps-tmo080307.php

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. (2007).  Explaining the Relation Between Birth Order and Intelligence. Science. 316(5832), 1717 - 1717.

http://www.nature.com/news/2007/070618/full/070618-14.html

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 R. P. (2007).  Relating Effortful Control, Executive Function, and False Belief Understanding to Emerging Math and Literacy Ability in Kindergarten. Child Development. 78(2), 647 - 663.

http://www.sciam.com/article.cfm?articleID=90377FAE-E7F2-99DF-3A1204FC5F2BF0F7

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, L. S., Trzesniewski K. H., & Dweck C. S. (2007).  Implicit Theories of Intelligence Predict Achievement across an Adolescent Transition: A Longitudinal Study and an Intervention. Child Development. 78(1), 246 - 263.

http://www.eurekalert.org/pub_releases/2007-02/sfri-swb013107.php

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, A. K., & Sekaquaptewa D. (2007).  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. 18(1), 13 - 18.

http://www.eurekalert.org/pub_releases/2007-01/afps-isa012407.php

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, G. L., Garcia J., Apfel N., & Master A. (2006).  Reducing the Racial Achievement Gap: A Social-Psychological Intervention. Science. 313(5791), 1307 - 1310.

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, I. J., Whalley L. J., Batty D. G., & Starr J. M. (2006).  Physical fitness and lifetime cognitive change. Neurology. 67(7), 1195 - 1200.

http://www.eurekalert.org/pub_releases/2006-10/aaon-fac100306.php

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, W. T., & Flynn J. R. (2006).  Black Americans reduce the racial IQ gap: evidence from standardization samples. Psychological Science: A Journal of the American Psychological Society / APS. 17(10), 913 - 920.

http://www.eurekalert.org/pub_releases/2006-09/afps-big091206.php

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, G. C., Spinks R. A., & Thomas C. W. (2006).  Age effects in coding tasks: componential analysis and test of the sensory deficit hypothesis. Psychology and Aging. 21(1), 7 - 18.

http://www.eurekalert.org/pub_releases/2006-05/cwru-did050106.php

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, L. T., & Kubzansky L. D. (2005).  Childhood Cognitive Performance and Risk of Mortality: A Prospective Cohort Study of Gifted Individuals. Am. J. Epidemiol.. 162(9), 887 - 890.

http://health.yahoo.com/news/126478

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, S. A., Pike A., Price T., & Plomin R. (Submitted).  Chaos in the home and socioeconomic status are associated with cognitive development in early childhood: Environmental mediators identified in a genetic design. Intelligence. 32(5), 445 - 460.

http://www.newscientist.com/news/news.jsp?id=ns99996323

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, E. Glenn (2004).  Music lessons enhance IQ. Psychological Science: A Journal of the American Psychological Society / APS. 15(8), 511 - 514.

http://www.sciencentral.com/articles/view.htm3?article_id=218392326

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, N. R., Hezlett S. A., & Ones D. S. (2004).  Academic Performance, Career Potential, Creativity, and Job Performance: Can One Construct Predict Them All?. Journal of Personality and Social Psychology. 86(1), 148 - 161.

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 N. P., Rettinger D. A., Shah P., & Hegarty M. (2001).  How are visuospatial working memory, executive functioning, and spatial abilities related? A latent-variable analysis. Journal of Experimental Psychology. General. 130(4), 621 - 640.

http://www.eurekalert.org/pub_releases/2001-12/apa-npo121001.php

Genetic basis of intelligence

Latest news

A round-up of genetic news. Several genes are linked to smaller brain size and faster brain atrophy in middle- & old age. The main Alzheimer's gene is implicated in leaky blood vessels, and shown to interact with brain size, white matter lesions, and dementia risk. Some evidence suggests early-onset Alzheimer's is not so dissimilar to late-onset Alzheimer's.

Genetic analysis of 9,232 older adults (average age 67; range 56-84) has implicated four genes in how fast your hippocampus shrinks with age (rs7294919 at 12q24, rs17178006 at 12q14, rs6741949 at 2q24, rs7852872 at 9p33). The first of these (implicated in cell death) showed a particularly strong link to a reduced hippocampus volume — with average consequence being a hippocampus of the same size as that of a person 4-5 years older.

Faster atrophy in this crucial brain region would increase people’s risk of Alzheimer’s and cognitive decline, by reducing their cognitive reserve. Reduced hippocampal volume is also associated with schizophrenia, major depression, and some forms of epilepsy.

In addition to cell death, the genes linked to this faster atrophy are involved in oxidative stress, ubiquitination, diabetes, embryonic development and neuronal migration.

A younger cohort, of 7,794 normal and cognitively compromised people with an average age of 40, showed that these suspect gene variants were also linked to smaller hippocampus volume in this age group. A third cohort, comprised of 1,563 primarily older people, showed a significant association between the ASTN2 variant (linked to neuronal migration) and faster memory loss.

In another analysis, researchers looked at intracranial volume and brain volume in 8,175 elderly. While they found no genetic associations for brain volume (although there was one suggestive association), they did discover that intracranial volume (the space occupied by the fully developed brain within the skull — this remains unchanged with age, reflecting brain size at full maturity) was significantly associated with two gene variants (at loci rs4273712, on chromosome 6q22, and rs9915547, on 17q21). These associations were replicated in a different sample of 1,752 older adults. One of these genes is already known to play a unique evolutionary role in human development.

A meta-analysis of seven genome-wide association studies, involving 10,768 infants (average age 14.5 months), found two loci robustly associated with head circumference in infancy (rs7980687 on chromosome 12q24 and rs1042725 on chromosome 12q15). These loci have previously been associated with adult height, but these effects on infant head circumference were largely independent of height. A third variant (rs11655470 on chromosome 17q21 — note that this is the same chromosome implicated in the study of older adults) showed suggestive evidence of association with head circumference; this chromosome has also been implicated in Parkinson's disease and other neurodegenerative diseases.

Previous research has found an association between head size in infancy and later development of Alzheimer’s. It has been thought that this may have to do with cognitive reserve.

Interestingly, the analyses also revealed that a variant in a gene called HMGA2 (rs10784502 on 12q14.3) affected intelligence as well as brain size.

Why ‘Alzheimer’s gene’ increases Alzheimer’s risk

Investigation into the so-called ‘Alzheimer’s gene’ ApoE4 (those who carry two copies of this variant have roughly eight to 10 times the risk of getting Alzheimer’s disease) has found that ApoE4 causes an increase in cyclophilin A, which in turn causes a breakdown of the cells lining the blood vessels. Blood vessels become leaky, making it more likely that toxic substances will leak into the brain.

The study found that mice carrying the ApoE4 gene had five times as much cyclophilin A as normal, in cells crucial to maintaining the integrity of the blood-brain barrier. Blocking the action of cyclophilin A brought blood flow back to normal and reduced the leakage of toxic substances by 80%.

The finding is in keeping with the idea that vascular problems are at the heart of Alzheimer’s disease — although it should not be assumed from that, that other problems (such as amyloid-beta plaques and tau tangles) are not also important. However, one thing that does seem clear now is that there is not one single pathway to Alzheimer’s. This research suggests a possible treatment approach for those carrying this risky gene variant.

Note also that this gene variant is not only associated with Alzheimer’s risk, but also Down’s syndrome dementia, poor outcome following TBI, and age-related cognitive decline.

On which note, I’d like to point out recent findings from the long-running Nurses' Health Study, involving 16,514 older women (70-81), that suggest that effects of postmenopausal hormone therapy for cognition may depend on apolipoprotein E (APOE) status, with the fastest rate of decline being observed among HT users who carried the APOe4 variant (in general HT was associated with poorer cognitive performance).

It’s also interesting to note another recent finding: that intracranial volume modifies the effect of apoE4 and white matter lesions on dementia risk. The study, involving 104 demented and 135 nondemented 85-year-olds, found that smaller intracranial volume increased the risk of dementia, Alzheimer's disease, and vascular dementia in participants with white matter lesions. However, white matter lesions were not associated with increased dementia risk in those with the largest intracranial volume. But intracranial volume did not modify dementia risk in those with the apoE4 gene.

More genes involved in Alzheimer’s

More genome-wide association studies of Alzheimer's disease have now identified variants in BIN1, CLU, CR1 and PICALM genes that increase Alzheimer’s risk, although it is not yet known how these gene variants affect risk (the present study ruled out effects on the two biomarkers, amyloid-beta 42 and phosphorylated tau).

Same genes linked to early- and late-onset Alzheimer's

Traditionally, we’ve made a distinction between early-onset Alzheimer's disease, which is thought to be inherited, and the more common late-onset Alzheimer’s. New findings, however, suggest we should re-think that distinction. While the genetic case for early-onset might seem to be stronger, sporadic (non-familial) cases do occur, and familial cases occur with late-onset.

New DNA sequencing techniques applied to the APP (amyloid precursor protein) gene, and the PSEN1 and PSEN2 (presenilin) genes (the three genes linked to early-onset Alzheimer's) has found that rare variants in these genes are more common in families where four or more members were affected with late-onset Alzheimer’s, compared to normal individuals. Additionally, mutations in the MAPT (microtubule associated protein tau) gene and GRN (progranulin) gene (both linked to frontotemporal dementia) were also found in some Alzheimer's patients, suggesting they had been incorrectly diagnosed as having Alzheimer's disease when they instead had frontotemporal dementia.

Of the 439 patients in which at least four individuals per family had been diagnosed with Alzheimer's disease, rare variants in the 3 Alzheimer's-related genes were found in 60 (13.7%) of them. While not all of these variants are known to be pathogenic, the frequency of mutations in these genes is significantly higher than it is in the general population.

The researchers estimate that about 5% of those with late-onset Alzheimer's disease have changes in these genes. They suggest that, at least in some cases, the same causes may underlie both early- and late-onset disease. The difference being that those that develop it later have more protective factors.

Another gene identified in early-onset Alzheimer's

A study of the genes from 130 families suffering from early-onset Alzheimer's disease has found that 116 had mutations on genes already known to be involved (APP, PSEN1, PSEN2 — see below for some older reports on these genes), while five of the other 14 families all showed mutations on a new gene: SORL1.

I say ‘new gene’ because it hasn’t been implicated in early-onset Alzheimer’s before. However, it has been implicated in the more common late-onset Alzheimer’s, and last year a study reported that the gene was associated with differences in hippocampal volume in young, healthy adults.

The finding, then, provides more support for the idea that some cases of early-onset and late-onset Alzheimer’s have the same causes.

The SORL1 gene codes for a protein involved in the production of the beta-amyloid peptide, and the mutations seen in this study appear to cause an under-expression of SORL1, resulting in an increase in the production of the beta-amyloid peptide. Such mutations were not found in the 1500 ethnicity-matched controls.

 

Older news reports on these other early-onset genes (brought over from the old website):

New genetic cause of Alzheimer's disease

Amyloid protein originates when it is cut by enzymes from a larger precursor protein. In very rare cases, mutations appear in the amyloid precursor protein (APP), causing it to change shape and be cut differently. The amyloid protein that is formed now has different characteristics, causing it to begin to stick together and precipitate as amyloid plaques. A genetic study of Alzheimer's patients younger than 70 has found genetic variations in the promoter that increases the gene expression and thus the formation of the amyloid precursor protein. The higher the expression (up to 150% as in Down syndrome), the younger the patient (starting between 50 and 60 years of age). Thus, the amount of amyloid precursor protein is a genetic risk factor for Alzheimer's disease.

Theuns, J. et al. 2006. Promoter Mutations That Increase Amyloid Precursor-Protein Expression Are Associated with Alzheimer Disease. American Journal of Human Genetics, 78, 936-946.

http://www.eurekalert.org/pub_releases/2006-04/vfii-rda041906.php

Evidence that Alzheimer's protein switches on genes

Amyloid b-protein precursor (APP) is snipped apart by enzymes to produce three protein fragments. Two fragments remain outside the cell and one stays inside. When APP is produced in excessive quantities, one of the cleaved segments that remains outside the cell, called the amyloid b-peptides, clumps together to form amyloid plaques that kill brain cells and may lead to the development of Alzheimer’s disease. New research indicates that the short "tail" segment of APP that is trapped inside the cell might also contribute to Alzheimer’s disease, through a process called transcriptional activation - switching on genes within the cell. Researchers speculate that creation of amyloid plaque is a byproduct of a misregulation in normal APP processing.

[2866] Cao, X., & Südhof T. C. (2001).  A Transcriptively Active Complex of APP with Fe65 and Histone Acetyltransferase Tip60. Science. 293(5527), 115 - 120.

http://www.eurekalert.org/pub_releases/2001-07/aaft-eta070201.php

Inactivation of Alzheimer's genes in mice causes dementia and brain degeneration

Mutations in two related genes known as presenilins are the major cause of early onset, inherited forms of Alzheimer's disease, but how these mutations cause the disease has not been clear. Since presenilins are involved in the production of amyloid peptides (the major components of amyloid plaques), it was thought that such mutations might cause Alzheimer’s by increasing brain levels of amyloid peptides. Accordingly, much effort has gone into identifying compounds that could block presenilin function. Now, however, genetic engineering in mice has revealed that deletion of these genes causes memory loss and gradual death of nerve cells in the mouse brain, demonstrating that the protein products of these genes are essential for normal learning, memory and nerve cell survival.

Saura, C.A., Choi, S-Y., Beglopoulos, V., Malkani, S., Zhang, D., Shankaranarayana Rao, B.S., Chattarji, S., Kelleher, R.J.III, Kandel, E.R., Duff, K., Kirkwood, A. & Shen, J. 2004. Loss of Presenilin Function Causes Impairments of Memory and Synaptic Plasticity Followed by Age-Dependent Neurodegeneration. Neuron, 42 (1), 23-36.

http://www.eurekalert.org/pub_releases/2004-04/cp-ioa032904.php

[2858] Consortium, E. N. I. G. M. - A.(E. N. I. G. M. A.), & Cohorts Heart Aging Research Genomic Epidemiology(charge) (2012).  Common variants at 12q14 and 12q24 are associated with hippocampal volume. Nature Genetics. 44(5), 545 - 551.

[2909] Taal, R. H., Pourcain B. S., Thiering E., Das S., Mook-Kanamori D. O., Warrington N. M., et al. (2012).  Common variants at 12q15 and 12q24 are associated with infant head circumference. Nature Genetics. 44(5), 532 - 538.

[2859] Cohorts Heart Aging Research Genomic Epidemiology,(charge), & Consortium E. G. G.(E. G. G.) (2012).  Common variants at 6q22 and 17q21 are associated with intracranial volume. Nature Genetics. 44(5), 539 - 544.

[2907] Stein, J. L., Medland S. E., Vasquez A. A., Hibar D. P., Senstad R. E., Winkler A. M., et al. (2012).  Identification of common variants associated with human hippocampal and intracranial volumes. Nature Genetics. 44(5), 552 - 561.

[2925] Bell, R. D., Winkler E. A., Singh I., Sagare A. P., Deane R., Wu Z., et al. (2012).  Apolipoprotein E controls cerebrovascular integrity via cyclophilin A. Nature.

Kang, J. H., & Grodstein F. (2012).  Postmenopausal hormone therapy, timing of initiation, APOE and cognitive decline. Neurobiology of Aging. 33(7), 1129 - 1137.

Skoog, I., Olesen P. J., Blennow K., Palmertz B., Johnson S. C., & Bigler E. D. (2012).  Head size may modify the impact of white matter lesions on dementia. Neurobiology of Aging. 33(7), 1186 - 1193.

[2728] Cruchaga, C., Chakraverty S., Mayo K., Vallania F. L. M., Mitra R. D., Faber K., et al. (2012).  Rare Variants in APP, PSEN1 and PSEN2 Increase Risk for AD in Late-Onset Alzheimer's Disease Families. PLoS ONE. 7(2), e31039 - e31039.

Full text available at http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0031039

[2897] Pottier, C., Hannequin D., Coutant S., Rovelet-Lecrux A., Wallon D., Rousseau S., et al. (2012).  High frequency of potentially pathogenic SORL1 mutations in autosomal dominant early-onset Alzheimer disease. Molecular Psychiatry.

McCarthy, J. J., Saith S., Linnertz C., Burke J. R., Hulette C. M., Welsh-Bohmer K. A., et al. (2012).  The Alzheimer's associated 5′ region of the SORL1 gene cis regulates SORL1 transcripts expression. Neurobiology of Aging. 33(7), 1485.e1-1485.e8 - 1485.e1-1485.e8

A large-scale genome-wide analysis has confirmed that half the differences in intelligence between people of similar background can be attributed to genetic differences — but it’s an accumulation of hundreds of tiny differences.

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 http://www.memory-key.com/memory/individual/wm-intelligence 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.

A large study of very young twins confirms evidence that environment affects cognitive ability far more for those from poor homes, compared to those from better-off homes.

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.

Providing support for a modular concept of the brain, a twin study has found that face recognition is heritable, and that it is inherited separately from 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.

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

Genes more important for IQ as children get older

Data from six studies carried out in the US, the UK, Australia and the Netherlands, involving a total of 11,000 pairs of twins, has revealed that genes become more important for intelligence as we get older. The researchers calculated that genes accounted for some 41% of the variation in intelligence in 9 year olds, rising to 55% in 12 year olds, and 66% in 17 year olds. It was suggested that as they get older, children get better at controlling (or perhaps are allowed to have more control over) their environment, which they do in a way that accentuates their ‘natural’ abilities — bright children feed their abilities; less bright children choose activities and friends that are less challenging.

Haworth, C.M.A. et al. 2009. The heritability of general cognitive ability increases linearly from childhood to young adulthood. Molecular Psychiatry, advance online publication 2 June 2009; doi: 10.1038/mp.2009.55

http://www.newscientist.com/article/mg20327174.600-genes-drive-iq-more-as-kids-get-older.html

A gene that influences intelligence

A study involving more than 2000 people from 200 families has found a link between the gene CHRM2, that activates multiple signaling pathways in the brain involved in learning, memory and other higher brain functions, and performance IQ. Researchers found that several variations within the CHRM2 gene (which is on chromosome 7) could be correlated with slight differences in performance IQ scores, which measure a person's visual-motor coordination, logical and sequential reasoning, spatial perception and abstract problem solving skills, and when people had more than one positive variation in the gene, the improvements in performance IQ were cumulative. Intelligence is a complex attribute that results from a combination of many genetic and environmental factors, so don’t interpret this finding to mean we’ve found a gene for intelligence.

[1173] Edenberg, H., Porjesz B., Begleiter H., Hesselbrock V., Goate A., Bierut L., et al. (2007).  Association of CHRM2 with IQ: Converging Evidence for a Gene Influencing Intelligence. Behavior Genetics. 37(2), 265 - 272.

http://www.eurekalert.org/pub_releases/2007-02/wuso-gag022607.php

Common gene version optimizes thinking but carries a risk

On the same subject, another study has found that the most common version of DARPP-32, a gene that shapes and controls a circuit between the striatum and prefrontal cortex, optimizes information filtering by the prefrontal cortex, thus improving working memory capacity and executive control (and thus, intelligence). However, the same version was also more prevalent among people who developed schizophrenia, suggesting that a beneficial gene variant may translate into a disadvantage if the prefrontal cortex is impaired. In other words, one of the things that make humans more intelligent as a species may also make us more vulnerable to schizophrenia.

[864] Kolachana, B., Kleinman J. E., Weinberger D. R., Meyer-Lindenberg A., Straub R. E., Lipska B. K., et al. (2007).  Genetic evidence implicating DARPP-32 in human frontostriatal structure, function, and cognition. Journal of Clinical Investigation. 117(3), 672 - 682.

http://www.sciencedaily.com/releases/2007/02/070208230059.htm
http://www.eurekalert.org/pub_releases/2007-02/niom-cgv020707.php

Closing in on the genes involved in human intelligence

A genetic study claims to have identified two regions of the human genome that appear to explain variation in IQ. Previous research has suggested that between 40% and 80% of variation in human intelligence (as measured by IQ tests) can be attributed to genetic factors, but research has so far failed to identify these genes. The new study has identified specific locations on Chromosomes 2 and 6 as being highly influential in determining IQ, using data from 634 sibling pairs. The region on Chromosome 2 that shows significant links to performance IQ overlaps a region associated with autism. The region on Chromosome 6 that showed strong links with both full-scale and verbal IQ marginally overlapped a region implicated in reading disability and dyslexia.

[382] Posthuma, D., Luciano M., Geus E., Wright M., Slagboom P., Montgomery G., et al. (2005).  A Genomewide Scan for Intelligence Identifies Quantitative Trait Loci on 2q and 6p. The American Journal of Human Genetics. 77(2), 318 - 326.

Brain regions involved in intelligence

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A very large online study helps decide between the idea of intelligence as a single factor (‘g’) versus having multiple domains.

An online study open to anyone, that ended up involving over 100,000 people of all ages from around the world, put participants through 12 cognitive tests, as well as questioning them about their background and lifestyle habits. This, together with a small brain-scan data set, provided an immense data set to investigate the long-running issue: is there such a thing as ‘g’ — i.e. is intelligence accounted for by just a single general factor; is it supported by just one brain network? — or are there multiple systems involved?

Brain scans of 16 healthy young adults who underwent the 12 cognitive tests revealed two main brain networks, with all the tasks that needed to be actively maintained in working memory (e.g., Spatial Working Memory, Digit Span, Visuospatial Working Memory) loading heavily on one, and tasks in which information had to transformed according to logical rules (e.g., Deductive Reasoning, Grammatical Reasoning, Spatial Rotation, Color-Word Remapping) loading heavily on the other.

The first of these networks involved the insula/frontal operculum, the superior frontal sulcus, and the ventral part of the anterior cingulate cortex/pre-supplementary motor area. The second involved the inferior frontal sulcus, inferior parietal cortex, and the dorsal part of the ACC/pre-SMA.

Just a reminder of individual differences, however — when analyzed by individual, this pattern was observed in 13 of the 16 participants (who are not a very heterogeneous bunch — I strongly suspect they are college students).

Still, it seems reasonable to conclude, as the researchers do, that at least two functional networks are involved in ‘intelligence’, with all 12 cognitive tasks using both networks but to highly variable extents.

Behavioral data from some 60,000 participants in the internet study who completed all tasks and questionnaires revealed that there was no positive correlation between performance on the working memory tasks and the reasoning tasks. In other words, these two factors are largely independent.

Analysis of this data revealed three, rather than two, broad components to overall cognitive performance: working memory; reasoning; and verbal processing. Re-analysis of the imaging data in search of the substrate underlying this verbal component revealed that the left inferior frontal gyrus and temporal lobes were significantly more active on tasks that loaded on the verbal component.

These three components could also be distinguished when looking at other factors. For example, while age was the most significant predictor of cognitive performance, its effect on the verbal component was much later and milder than it was for the other two components. Level of education was more important for the verbal component than the other two, while the playing of computer games had an effect on working memory and reasoning but not verbal. Chronic anxiety affected working memory but not reasoning or verbal. Smoking affected working memory more than the others. Unsurprisingly, geographical location affected verbal more than the other two components.

A further test, involving 35 healthy young adults, compared performance on the 12 tasks and score on the Cattell Culture Fair test (a classic pen and paper IQ test). The working memory component correlated most with the Cattell score, followed by the reasoning component, with the Verbal component (unsurprisingly, given that this is designed to be a ‘culture-fair’ test) showing the smallest correlation.

All of this is to say that this is decided evidence that what is generally considered ‘intelligence’ is based on the functioning of multiple brain networks rather than a single ‘g’, and that these networks are largely independent. Thus, the need to focus on and maintain task-relevant information maps onto one particular brain network, and is one strand. Another network specializes in transforming information, regardless of source or type. These, it would seem, are the main processes involved in fluid intelligence, while the Verbal component most likely reflects crystallized intelligence. There are also likely to be other networks which are not perhaps typically included in ‘general intelligence’, but are nevertheless critical for task performance (the researchers suggest the ability to adapt plans based on outcomes might be one such function).

The obvious corollary of all this is that similar IQ scores can reflect different abilities for these strands — e.g., even if your working memory capacity is not brilliant, you can develop your reasoning and verbal abilities. All this is consistent with the growing evidence that, although fundamental WMC might be fixed (and I use the word ‘fundamental’ deliberately, because WMC can be measured in a number of different ways, and I do think you can, at the least, effectively increase your WMC), intelligence (because some of its components are trainable) is not.

If you want to participate in this research, a new version of the tests is available at http://www.cambridgebrainsciences.com/theIQchallenge

[3214] Hampshire, A., Highfield R. R., Parkin B. L., & Owen A. M. (2012).  Fractionating Human Intelligence. Neuron. 76(6), 1225 - 1237.

A new study of older adults indicates atrophy of the cerebellum is an important factor in cognitive decline for men, but not women.

Shrinking of the frontal lobe has been associated with age-related cognitive decline for some time. But other brain regions support the work of the frontal lobe. One in particular is the cerebellum. A study involving 228 participants in the Aberdeen Longitudinal Study of Cognitive Ageing (mean age 68.7) has revealed that there is a significant relationship between grey matter volume in the cerebellum and general intelligence in men, but not women.

Additionally, a number of other brain regions showed an association between gray matter and intelligence, in particular Brodmann Area 47, the anterior cingulate, and the superior temporal gyrus. Atrophy in the anterior cingulate has been implicated as an early marker of Alzheimer’s, as has the superior temporal gyrus.

The gender difference was not completely unexpected — previous research has indicated that the cerebellum shrinks proportionally more with age in men than women. More surprising was the fact that there was no significant association between white memory volume and general intelligence. This contrasts with the finding of a study involving older adults aged 79-80. It is speculated that this association may not develop until greater brain atrophy has occurred.

It is also interesting that the study found no significant relationship between frontal lobe volume and general intelligence — although the effect of cerebellar volume is assumed to occur via its role in supporting the frontal lobe.

The cerebellum is thought to play a vital role in three relevant areas: speed of information processing; variability of information processing; development of automaticity through practice.

Data from brain-lesion patients supports the idea that general intelligence depends on the brain's ability to integrate several different kinds of processing, and resides in a distributed network.

Using a large data set of 241 brain-lesion patients, researchers have mapped the location of each patient's lesion and correlated that with each patient's IQ score to produce a map of the brain regions that influence intelligence. Consistent with other recent findings, and with the theory that general intelligence depends on the brain's ability to integrate several different kinds of processing, they found general intelligence was determined by a distributed network in the frontal and parietal cortex, critically including white matter association tracts and frontopolar cortex. They suggest that general intelligence draws on connections between regions that integrate verbal, visuospatial, working memory, and executive processes.

[173] Gläscher, J., Rudrauf D., Colom R., Paul L. K., Tranel D., Damasio H., et al. (2010).  Distributed neural system for general intelligence revealed by lesion mapping. Proceedings of the National Academy of Sciences. 107(10), 4705 - 4709.

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

Damaged brains show regions involved in intelligence

Comparison of brain scans of 241 patients with differing degrees of cognitive impairment from events such as strokes, tumor resection, and traumatic brain injury, has correlated the location of brain injuries with scores on each of the four indices in the Wechsler Adult Intelligence Scale (WAIS), the most widely used intelligence test in the world. It was found that lesions in the left frontal cortex were associated with lower scores on the verbal comprehension index; lesions in the left frontal and parietal cortex were associated with lower scores on the working memory index; and lesions in the right parietal cortex were associated with lower scores on the perceptual organization index. A surprisingly large amount of overlap in the brain regions responsible for verbal comprehension and working memory may suggest that these two measures of cognitive ability may actually represent the same type of intelligence.

[1179] Gläscher, J., Tranel D., Paul L. K., Rudrauf D., Rorden C., Hornaday A., et al. (2009).  Lesion Mapping of Cognitive Abilities Linked to Intelligence. Neuron. 61(5), 681 - 691.

http://www.eurekalert.org/pub_releases/2009-03/ciot-cnm031009.php

When it comes to intelligence, size matters

The NIH MRI Study of Normal Brain Development now contains data from more than 500 children and adolescents from newborns to 18-year-olds, who had brain scans multiple times over a period of years as well as various cognitive tests. A sample of 216 healthy 6 to 18 year old brains from the dataset reveal that there is a positive link between cortical thickness and cognitive ability in many areas of the frontal, parietal, temporal and occipital lobes. The regions with the greatest relationship were the 'multi-modal association' areas, where information converges from various regions of the brain for processing. The finding supports a distributed model of intelligence.

[874] Karama, S., Ad-Dab'bagh Y., Haier R. J., Deary I. J., Lyttelton O. C., Lepage C., et al. (Submitted).  Positive association between cognitive ability and cortical thickness in a representative US sample of healthy 6 to 18 year-olds. Intelligence. 37(2), 145 - 155.

http://www.physorg.com/news157210821.html

Processing speed component of intelligence is largely inherited

A new kind of scanner used on the brains of 23 sets of identical twins and 23 sets of fraternal twins has revealed that myelin quality is under strong genetic control in the frontal, parietal, and left occipital lobes, and that myelin quality (in the cingulum, optic radiations, superior fronto-occipital fasciculus, internal capsule, callosal isthmus, and corona radiata) was correlated with intelligence scores. Myelin governs the speed with which signals can travel along the axons of neurons, that is, how fast we can process information. The researchers are now working on finding the genes that may influence myelin growth.

[1310] de Zubicaray, G. I., Wright M. J., Srivastava A., Balov N., Thompson P. M., Chiang M. - C., et al. (2009).  Genetics of Brain Fiber Architecture and Intellectual Performance. J. Neurosci.. 29(7), 2212 - 2224.

http://www.physorg.com/news156519927.html

Intelligence and rhythmic accuracy go hand in hand

And in another perspective on the nature of intelligence, a new study has demonstrated a correlation between general intelligence and the ability to tap out a simple regular rhythm. The correlation between high intelligence and a good ability to keep time, was also linked to a high volume of white matter in the parts of the frontal lobes involved in problem solving, planning and managing time. The finding suggests that the long-established correlation of general intelligence with the mean and variability of reaction time in elementary cognitive tasks, as well as with performance on temporal judgment and discrimination tasks, is a bottom-up connection, stemming from connectivity in the prefrontal regions.

[665] Ullen, F., Forsman L., Blom O., Karabanov A., & Madison G. (2008).  Intelligence and Variability in a Simple Timing Task Share Neural Substrates in the Prefrontal White Matter. J. Neurosci.. 28(16), 4238 - 4243.

http://www.physorg.com/news127561553.html
http://www.eurekalert.org/pub_releases/2008-04/ki-iar041608.php

Brain network related to intelligence identified

A review of 37 imaging studies may have finally answered an age-old question: where is intelligence. Following on from recent evidence suggesting that intelligence is related to how well information travels throughout the brain, the researchers believe they have identified the stations along the routes intelligent information processing takes. These stations primarily involve areas in the frontal and the parietal lobes, many of which are involved in attention and memory, and more complex functions such as language. Basically, the researchers theorize that your level of intelligence is a function of how well these areas communicate with each other. It’s particularly interesting to note that these various imaging studies had remarkably consistent results despite the different definitions of intelligence used in them.

[1015] Jung, R. E., & Haier R. J. (2007).  The Parieto-Frontal Integration Theory (P-FIT) of Intelligence: Converging Neuroimaging Evidence. Behavioral and Brain Sciences. 30(02), 135 - 154.

http://www.physorg.com/news108722746.html
http://www.eurekalert.org/pub_releases/2007-09/uoc--bnr091007.php
http://www.livescience.com/health/070911_intel_network.html

Intelligence based on the volume of gray matter in certain brain regions

Confirming earlier suggestions, the most comprehensive structural brain-scan study of intelligence to date supports an association between general intelligence and the volume of gray matter tissue in certain regions of the brain. Because these regions are located throughout the brain, a single "intelligence center" is unlikely. It is likely that a person's mental strengths and weaknesses depend in large part on the individual pattern of gray matter across his or her brain. Although gray matter amounts are vital to intelligence levels, only about 6% of the brain’s gray matter appears related to IQ — intelligence seems related to an efficient use of relatively few structures. The structures that are important for intelligence are the same ones implicated in memory, attention and language. There are also age differences: in middle age, more of the frontal and parietal lobes are related to IQ; less frontal and more temporal areas are related to IQ in the younger adults. Previous research has shown the regional distribution of gray matter in humans is highly heritable. The findings also challenge the recent view that intelligence may be a reflection of more subtle characteristics of the brain, such as the speed at which nerve impulses travel in the brain, or the number of neuronal connections present. It may of course be that all of these are factors.

[715] Haier, R. J., Jung R. E., Yeo R. A., Head K., & Alkire M. T. (2004).  Structural brain variation and general intelligence. NeuroImage. 23(1), 425 - 433.

http://www.sciencedaily.com/releases/2004/07/040720090419.htm
http://www.eurekalert.org/pub_releases/2004-07/uoc--hid071904.php

Gender differences

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Persistent marijuana use beginning before age 18 (but not after) is associated with a significant drop in IQ in a large, long-running study.

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).

  • Fifth grade students' understanding of fractions and division predicted high school students' knowledge of algebra and overall math achievement.
  • School entrants’ spatial skills predicted later number sense and estimation skills.
  • Gender differences in math performance may rest in part on differences in retrieval practice.
  • ‘Math’ training for infants may be futile, given new findings that they’re unable to integrate two mechanisms for number estimation.

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 http://youtu.be/7YSj0mmjwBM.

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.

Comparing performance on an IQ test when it is given under normal conditions and when it is given in a group situation reveals that IQ drops in a group setting, and for some (mostly women) it drops dramatically.

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.

A new study of older adults indicates atrophy of the cerebellum is an important factor in cognitive decline for men, but not women.

Shrinking of the frontal lobe has been associated with age-related cognitive decline for some time. But other brain regions support the work of the frontal lobe. One in particular is the cerebellum. A study involving 228 participants in the Aberdeen Longitudinal Study of Cognitive Ageing (mean age 68.7) has revealed that there is a significant relationship between grey matter volume in the cerebellum and general intelligence in men, but not women.

Additionally, a number of other brain regions showed an association between gray matter and intelligence, in particular Brodmann Area 47, the anterior cingulate, and the superior temporal gyrus. Atrophy in the anterior cingulate has been implicated as an early marker of Alzheimer’s, as has the superior temporal gyrus.

The gender difference was not completely unexpected — previous research has indicated that the cerebellum shrinks proportionally more with age in men than women. More surprising was the fact that there was no significant association between white memory volume and general intelligence. This contrasts with the finding of a study involving older adults aged 79-80. It is speculated that this association may not develop until greater brain atrophy has occurred.

It is also interesting that the study found no significant relationship between frontal lobe volume and general intelligence — although the effect of cerebellar volume is assumed to occur via its role in supporting the frontal lobe.

The cerebellum is thought to play a vital role in three relevant areas: speed of information processing; variability of information processing; development of automaticity through practice.

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

Brain size does matter, but differently for men and women

A study involving the intelligence testing of 100 neurologically normal, terminally ill volunteers, who agreed that their brains be measured after death, found that a bigger brain size is correlated with higher intelligence in certain areas, but there are differences between women and men. Verbal intelligence was clearly correlated with brain size, accounting for 36% of the verbal IQ score, for women and right-handed men — but not for left-handed men. Spatial intelligence was also correlated with brain size in women, but much less strongly, while it was not related at all to brain size in men. It may be that the size or structure of specific brain regions is related to spatial intelligence in men. Brain size decreased with age in men over the age span of 25 to 80 years, suggesting that the well-documented decline in visuospatial intelligence with age is related, at least in right-handed men, to the decrease in cerebral volume with age. However age hardly affected brain size in women.

[1029] Witelson, S. F., Beresh H., & Kigar D. L. (2006).  Intelligence and brain size in 100 postmortem brains: sex, lateralization and age factors. Brain: A Journal of Neurology. 129(Pt 2), 386 - 398.

http://www.sciencedaily.com/releases/2005/12/051223123116.htm

Correlation between brain volume and intelligence

An analysis of 26 previous international studies involving brain volume and intelligence has found that, on average, intelligence (as measured by standardized intelligence tests) increases with increasing brain volume. The correlation was higher for females than males, and for adults compared to children.

[925] McDaniel, M. A. (Submitted).  Big-brained people are smarter: A meta-analysis of the relationship between in vivo brain volume and intelligence. Intelligence. 33(4), 337 - 346.

A copy of the study is available at http://www.vcu.edu/uns/Releases/2005/june/McDaniel-Big%20Brain.pdf

http://www.eurekalert.org/pub_releases/2005-06/vcu-vss061705.php
http://www.vcu.edu/uns/Releases/2005/june/061705.html

IQ-related brain areas may differ in men and women

An imaging study of 48 men and women between 18 and 84 years old found that, although men and women performed equally on the IQ tests, the brain structures involved in intelligence appeared distinct. Compared with women, men had more than six times the amount of intelligence-related gray matter, while women had about nine times more white matter involved in intelligence than men did. Women also had a large proportion of their IQ-related brain matter (86% of white and 84% of gray) concentrated in the frontal lobes, while men had 90% of their IQ-related gray matter distributed equally between the frontal lobes and the parietal lobes, and 82% of their IQ-related white matter in the temporal lobes. The implications of all this are not clear, but it is worth noting that the volume of gray matter can increase with learning, and is thus a product of environment as well as genes. The findings also demonstrate that no single neuroanatomical structure determines general intelligence and that different types of brain designs are capable of producing equivalent intellectual performance.

[938] Haier, R. J., Jung R. E., Yeo R. A., Head K., & Alkire M. T. (2005).  The neuroanatomy of general intelligence: sex matters. NeuroImage. 25(1), 320 - 327.

http://www.eurekalert.org/pub_releases/2005-01/uoc--iim012005.php
http://www.sciencedaily.com/releases/2005/01/050121100142.htm

Evolution of intelligence

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More support for the theory that bigger brains were a response to living in social groups comes from a wide-ranging comparison of 511 mammalian species, but a comparison of wasp brains over time points to the importance of parasitism.

A comparison of the brain and body size of over 500 species of living and fossilised mammals has found that the brains of monkeys grew the most over 60 million years, followed by horses, dolphins, camels and dogs. Those with relatively bigger brains tend to live in stable social groups. The brains of more solitary mammals, such as cats, deer and rhino, grew much more slowly during the same period.

On the other hand, a new study comparing wasp brains over time has revealed that the mushroom bodies (neural clusters responsible for processing and remembering smells and sights) of parasitic wasps are consistently larger and more complex than those of nonparasitic wasps, which represent the very oldest form of wasp.

Previously, findings that social insects tend to have larger mushroom bodies than solitary ones have lead researchers to believe that the transition from solitary to social living was behind the larger brain regions. These new findings suggest that it is parasitism (which evolved 90 million years before social insects appear) that is behind the growth in size. That may be because well-developed mushroom bodies help parasitic wasps better locate hosts for their larvae.

Of course, this doesn’t rule out the possibility that sociality lead to another boost in size and complexity, and indeed the researchers suggest that these neurological developments may have been a crucial precursor for central place foraging. This behavior is widespread in this group of insects (the Aculeata), requires extensive spatial learning, and may have contributed to the various developments of social behavior. A comparison of the brains of social worker bees and those of parasitic wasps would be helpful.

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

Individual primates display variation in general intelligence

Research into cognition of non-human animals has been concerned almost entirely with the abilities of the species, not with individual variation within a species. Now a study of 22 cotton-top tamarins has revealed that these monkeys, like humans, also display substantial individual variation on tests of broad cognitive ability, although the degree of variation does seem significantly smaller than it is among humans (individual variability accounted for some 20% of the monkey’s performance, while it accounts for some 40-60% of human’s performance on IQ tasks). It may be that greater variability has been an important factor in human brain evolution.

[781] Banerjee, K., Chabris C. F., Johnson V. E., Lee J. J., Tsao F., & Hauser M. D. (2009).  General Intelligence in Another Primate: Individual Differences across Cognitive Task Performance in a New World Monkey (Saguinus oedipus). PLoS ONE. 4(6), e5883 - e5883.

Full text available at http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0005883 

http://www.eurekalert.org/pub_releases/2009-06/hu-ipd061209.php

Bigger is smarter: brain size predicts intelligence in different species

Animals with larger body sizes generally have larger brains, and it has generally been assumed that larger animals require larger nervous systems to coordinate their larger bodies. Consequently, comparison of brain size across different animal species, as an indirect measurement of intelligence, have controlled for body size. New research however suggests that, although some correction is probably needed, completely controlling for body size is almost certainly a mistake. Both overall brain size and overall neocortex size proved to be good predictors of intelligence in different primate species.

[998] Deaner, R. O., Isler K., Burkart J., & van Schaik C. (2007).  Overall Brain Size, and Not Encephalization Quotient, Best Predicts Cognitive Ability across Non-Human Primates. Brain, Behavior and Evolution. 70(2), 115 - 124.

http://www.sciencedaily.com/releases/2007/05/070518172103.htm

Size of brain areas does matter — but bigger isn't necessarily better

In a fascinating mouse study that overturns our simplistic notion that, when it comes to the brain, bigger is better, researchers have found that there is an optimal size for regions within the brain. The study found that if areas of the cortex involved in body sensations and motor control are either smaller or larger than normal, mice couldn’t run an obstacle course, keep from falling off a rotating rod, or perform other tactile and motor behaviors that require balance and coordination as well as mice with normal-sized areas could. It now seems that the best size in one that is best tuned to the context of the neural system within which that area functions — which is not really so surprising when you consider that every brain region acts as part of a network, in conjunction with other regions. This study builds upon a previous discovery by the same researchers, that a gene controls how the cortex in mice is divided during embryonic development into its functionally specialized areas. Different levels of the protein expressed by this gene changes the size of the sensorimotor areas of the cortex. It is known that significant variability in cortical area size exists in humans, and this may explain at least in part variability in human performance.

[334] Leingärtner, A., Thuret S., Kroll T. T., Chou S. - J., Leasure L. J., Gage F. H., et al. (2007).  Cortical area size dictates performance at modality-specific behaviors. Proceedings of the National Academy of Sciences. 104(10), 4153 - 4158.

Full text is available at http://tinyurl.com/2tpyhe

http://www.physorg.com/news92051236.html

Bigger brains associated with domain-general intelligence

Analysis of hundreds of studies testing the cognitive abilities of non-human primates provides support for a general intelligence, and confirms that the great apes are more intelligent than monkeys and prosimians. Individual studies have always been criticized for not clearly ensuring that one species wasn’t out-performing another simply because the particular testing situation was more suited to them. However, by looking at so many varied tests, the researchers have overcome this criticism. Although there were a few cases where one species performed better than another one in one task and reversed places in a different task, overall, some species truly outperformed others. The smartest species were clearly the great apes — orangutans, chimpanzees, and gorillas. Moreover, there was no evidence that any species performed especially well within a particular paradigm, contradicting the theory that species differences in intelligence only exist for narrow, specialized skills. Instead, the results argue that some species possess a broad, domain-general type of intelligence that allows them to succeed in a variety of situations.

Deaner, R.O., van Schaik, C.P. & Johnson, V. 2006. Do some taxa have better domain-general cognition than others? A meta-analysis of nonhuman primate studies. Evolutionary Psychology, 4, 149-196.

Full-text available at http://human-nature.com/ep/downloads/ep04149196.pdf

http://www.sciencedaily.com/releases/2006/08/060801231359.htm

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