individual differences

How action videogames change some people’s brains

May, 2012

A small study has found that ten hours of playing action video games produced significant changes in brainwave activity and improved visual attention for some (but not all) novices.

Following on from research finding that people who regularly play action video games show visual attention related differences in brain activity compared to non-players, a new study has investigated whether such changes could be elicited in 25 volunteers who hadn’t played video games in at least four years. Sixteen of the participants played a first-person shooter game (Medal of Honor: Pacific Assault), while nine played a three-dimensional puzzle game (Ballance). They played the games for a total of 10 hours spread over one- to two-hour sessions.

Selective attention was assessed through an attentional visual field task, carried out prior to and after the training program. Individual learning differences were marked, and because of visible differences in brain activity after training, the action gamers were divided into two groups for analysis — those who performed above the group mean on the second attentional visual field test (7 participants), and those who performed below the mean (9). These latter individuals showed similar brain activity patterns as those in the control (puzzle) group.

In all groups, early-onset brainwaves were little affected by video game playing. This suggests that game-playing has little impact on bottom–up attentional processes, and is in keeping with earlier research showing that players and non-players don’t differ in the extent to which their attention is captured by outside stimuli.

However, later brainwaves — those thought to reflect top–down control of selective attention via increased inhibition of distracters — increased significantly in the group who played the action game and showed above-average improvement on the field test. Another increased wave suggests that the total amount of attention allocated to the task was also greater in that group (i.e., they were concentrating more on the game than the below-average group, and the control group).

The improved ability to select the right targets and ignore other stimuli suggests, too, that these players are also improving their ability to make perceptual decisions.

The next question, of course, is what personal variables underlie the difference between those who benefit more quickly from the games, and those who don’t. And how much more training is necessary for this latter group, and are there some people who won’t achieve these benefits at all, no matter how long they play? Hopefully, future research will be directed to these questions.

Reference: 

[2920] Wu, S., Cheng C K., Feng J., D'Angelo L., Alain C., & Spence I.
(2012).  Playing a First-person Shooter Video Game Induces Neuroplastic Change.
Journal of Cognitive Neuroscience. 24(6), 1286 - 1293.

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Genes, brain size, brain atrophy, and Alzheimer’s risk

May, 2012

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

Reference: 

[2858] Consortium, E N I G M-A(ENIGMA)., & 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(EGG).
(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

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Video game training benefits cognition in some older adults

April, 2012

A study has found that playing a cognitively complex video game improved cognitive performance in some older adults, particularly those with initially poorer cognitive scores.

A number of studies have found evidence that older adults can benefit from cognitive training. However, neural plasticity is thought to decline with age, and because of this, it’s thought that the younger-old, and/or the higher-functioning, may benefit more than the older-old, or the lower-functioning. On the other hand, because their performance may already be as good as it can be, higher-functioning seniors may be less likely to benefit. You can find evidence for both of these views.

In a new study, 19 of 39 older adults (aged 60-77) were given training in a multiplayer online video game called World of Warcraft (the other 20 formed a control group). This game was chosen because it involves multitasking and switching between various cognitive abilities. It was theorized that the demands of the game would improve both spatial orientation and attentional control, and that the multiple tasks might produce more improvement in those with lower initial ability compared to those with higher ability.

WoW participants were given a 2-hour training session, involving a 1-hour lecture and demonstration, and one hour of practice. They were then expected to play the game at home for around 14 hours over the next two weeks. There was no intervention for the control group. All participants were given several cognitive tests at the beginning and end of the two week period: Mental Rotation Test; Stroop Test; Object Perspective Test; Progressive Matrices; Shipley Vocabulary Test; Everyday Cognition Battery; Digit Symbol Substitution Test.

As a group, the WoW group improved significantly more on the Stroop test (a measure of attentional control) compared to the control group. There was no change in the other tests. However, those in the WoW group who had performed more poorly on the Object Perspective Test (measuring spatial orientation) improved significantly. Similarly, on the Mental Rotation Test, ECB, and Progressive Matrices, those who performed more poorly at the beginning tended to improve after two weeks of training. There was no change on the Digit Symbol test.

The finding that only those whose performance was initially poor benefited from cognitive training is consistent with other studies suggesting that training only benefits those who are operating below par. This is not really surprising, but there are a few points that should be made.

First of all, it should be noted that this was a group of relatively high-functioning young-old adults — poorer performance in this case could be (relatively) better performance in another context. What it comes down to is whether you are operating at a level below which you are capable of — and this applies broadly, for example, experiments show that spatial training benefits females but not males (because males tend to already have practiced enough).

Given that, in expertise research, training has an on-going, apparently limitless, effect on performance, it seems likely that the limited benefits shown in this and other studies is because of the extremely limited scope of the training. Fourteen hours is not enough to improve people who are already performing adequately — but that doesn’t mean that they wouldn’t improve with more hours. I have yet to see any interventions with older adults that give them the amount of cognitive training you would expect them to need to achieve some level of mastery.

My third and final point is the specific nature of the improvements. This has also been shown in other studies, and sometimes appears quite arbitrary — for example, one 3-D puzzle game apparently improved mental rotation, while a different 3-D puzzle game had no effect. The point being that we still don’t understand the precise attributes needed to improve different skills (although the researchers advocate the use of a tool called cognitive task analysis for revealing the underlying qualities of an activity) — but we do understand that it is a matter of precise attributes, which is definitely a step in the right direction.

The main thing, then, that you should take away from this is the idea that different activities involve specific cognitive tasks, and these, and only these, will be the ones that benefit from practicing the activities. You therefore need to think about what tasks you want to improve before deciding on the activities to practice.

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Fluctuating sense of control linked to cognitive ability in older adults

April, 2012

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.

Reference: 

[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.

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Scent of rosemary may help cognition

March, 2012

Rosemary is a herb long associated with memory. A small study now provides some support for the association, and for the possible benefits of aromatherapy. And a rat study indicates that your attitude to work might change how stimulants affect you.

A small study involving 20 people has found that those who were exposed to 1,8-cineole, one of the main chemical components of rosemary essential oil, performed better on mental arithmetic tasks. Moreover, there was a dose-dependent relationship — higher blood concentrations of the chemical were associated with greater speed and accuracy.

Participants were given two types of test: serial subtraction and rapid visual information processing. These tests took place in a cubicle smelling of rosemary. Participants sat in the cubicle for either 4, 6, 8, or 10 minutes before taking the tests (this was in order to get a range of blood concentrations). Mood was assessed both before and after, and blood was tested at the end of the session.

While blood levels of the chemical correlated with accuracy and speed on both tasks, the effects were significant only for the mental arithmetic task.

Participants didn’t know that the scent was part of the study, and those who asked about it were told it was left over from a previous study.

There was no clear evidence that the chemical improved attention, but there was a significant association with one aspect of mood, with higher levels of the scent correlating with greater contentment. Contentment was the only aspect of mood that showed such a link.

It’s suggested that this chemical compound may affect learning through its inhibiting effect on acetylcholinesterase (an important enzyme in the development of Alzheimer's disease). Most Alzheimer’s drugs are cholinesterase inhibitors.

While this is very interesting (although obviously a larger study needs to confirm the findings), what I would like to see is the effects on more prolonged mental efforts. It’s also a little baffling to find the effect being limited to only one of these tasks, given that both involve attention and working memory. I would also like to see the rosemary-infused cubicle compared to some other pleasant smell.

Interestingly, a very recent study also suggests the importance of individual differences. A rat study compared the effects of amphetamines and caffeine on cognitive effort. First of all, giving the rats the choice of easy or hard visuospatial discriminations revealed that, as with humans, individuals could be divided into those who tended to choose difficult trials (“workers”) and those who preferred easy ones (“slackers”). (Easy trials took less effort, but earned commensurately smaller reward.)

Amphetamine, it was found, made the slackers worked harder, but made the workers take it easier. Caffeine, too, made the workers slack off, but had no effect on slackers.

The extent to which this applies to humans is of course unknown, but the idea that your attitude to cognitive effort might change how stimulants affect you is an intriguing one. And of course this is a more general reminder that factors, whatever they are, have varying effects on individuals. This is why it’s so important to have a large sample size, and why, as an individual, you can’t automatically assume that something will benefit you, whatever the research says.

But in the case of rosemary oil, I can’t see any downside! Try it out; maybe it will help.

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Group settings hurt expressions of intelligence, especially in women

March, 2012

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.

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Confidence is key to women's spatial skills

March, 2012

A series of experiments has found that confidence fully accounted for women’s poorer performance on a mental rotation task.

One of the few established cognitive differences between men and women lies in spatial ability. But in recent years, this ‘fact’ has been shaken by evidence that training can close the gap between the genders. In this new study, 545 students were given a standard 3D mental rotation task, while at the same time manipulating their confidence levels.

In the first experiment, 70 students were asked to rate their confidence in each answer. They could also choose not to answer. Confidence level was significantly correlated with performance both between and within genders.

On the face of it, these findings could be explained, of course, by the ability of people to be reliable predictors of their own performance. However, the researchers claim that regression analysis shows clearly that when the effect of confidence was taken into account, gender differences were eliminated. Moreover, gender significantly predicted confidence.

But of course this is still just indicative.

In the next experiment, however, the researchers tried to reduce the effect of confidence. One group of 87 students followed the same procedure as in the first experiment (“omission” group), except they were not asked to give confidence ratings. Another group of 87 students was not permitted to miss out any questions (“commission” group). The idea here was that confidence underlay the choice of whether or not to answer a question, so while the first group should perform similarly to those in the first experiment, the second group should be less affected by their confidence level.

This is indeed what was found: men significantly outperformed women in the first condition, but didn’t in the second condition. In other words, it appears that the mere possibility of not answering makes confidence an important factor.

In the third experiment, 148 students replicated the commission condition of the second experiment with the additional benefit of being allowed unlimited time. Half of the students were required to give confidence ratings.

The advantage of unlimited time improved performance overall. More importantly, the results confirmed those produced earlier: confidence ratings produced significant gender differences; there were no gender differences in the absence of such ratings.

In the final experiment, 153 students were required to complete an intentionally difficult line judgment task, which men and women both carried out at near chance levels. They were then randomly informed that their performance had been either above average (‘high confidence’) or below average (‘low confidence’). Having manipulated their confidence, the students were then given the standard mental rotation task (omission version).

As expected (remember this is the omission procedure, where subjects could miss out answers), significant gender differences were found. But there was also a significant difference between the high and low confidence groups. That is, telling people they had performed well (or badly) on the first task affected how well they did on the second. Importantly, women in the high confidence group performed as well as men in the low confidence group.

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How early environment impacts cognitive development

February, 2012

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.

Reference: 

[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.

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How family circumstance impacts learning and memory in children

February, 2012

A large study shows the impact of having multiple family disadvantages on cognitive development. A brain scan study finds childhood maltreatment significantly reduces the size of the hippocampus, while another finds parental care can increase it.

Quarter of British children performing poorly due to family disadvantage

A British study involving over 18,000 very young children (aged 9 months to 5 years) has found that those exposed to two or more “disadvantages” (28% of the children) were significantly more likely to have impaired intellectual development, expressed in a significantly reduced vocabulary and behavioral problems.

These differences were significant at three, and for the most part tended to widen between ages three or five (cognitive development, hyperactivity, peer problems and prosocial behaviors; the gap didn’t change for emotional problems, and narrowed for conduct problems). However, only the narrowing of the conduct problem gap and the widening of the peer problem gap was statistically significant.

Ten disadvantages were identified: living in overcrowded housing; having a teenage mother; having one or more parents with depression, parent with a physical disability; parent with low basic skills; maternal smoking during pregnancy; excessive alcohol intake; financial stress, unemployment; domestic violence..

Around 41% of the children did not face any of these disadvantages, and 30% faced only one of these disadvantages. Of those facing two or more, half of those (14%) only had two, while 7% of the total group experienced three risk factors, and fewer than 2% had five or more.

There was no dominant combination of risks, but parental depression was the most common factor (19%), followed by parental disability (15%). Violence was present in only 4% of families, and both parents unemployed in only 5.5%. While there was some correlation between various risk factors, these correlations were relatively modest for the most part. The highest correlations were between unemployment and disability; violence and depression; unemployment and overcrowding.

There were ethnic differences in rate: at 48%, Bangladeshi children were most likely to be exposed to multiple disadvantages, followed by Pakistani families (34%), other (including mixed) (33%), black African (31%), black Caribbean (29%), white (28%) and Indian (20%).

There were also differences depending on family income. Among those in the lowest income band (below £10,400 pa) — into which 21% of the families fell, the same proportion as is found nationally — nearly half had at least two risk factors, compared to 27% of those in families above this threshold. Moreover, children in families with multiple risk factors plus low income showed the lowest cognitive development (as measured by vocabulary).

Childhood maltreatment reduces size of hippocampus

In this context, it is interesting to note a recent finding that three key areas of the hippocampus were significantly smaller in adults who had experienced maltreatment in childhood. In this study, brain scans were taken of nearly 200 young adults (18-25), of whom 46% reported no childhood adversity and 16% reported three or more forms of maltreatment. Maltreatment was most commonly physical and verbal abuse from parents, but also included corporal punishment, sexual abuse and witnessing domestic violence.

Reduced volume in specific hippocampus regions (dentate gyrus, cornu ammonis, presubiculum and subiculum) was still evident after such confounding factors as a history of depression or PTSD were taken into account. The findings support the theory that early stress affects the development of subregions in the hippocampus.

While mother’s nurturing grows the hippocampus

Supporting this, another study, involving 92 children aged 7 to 10 who had participated in an earlier study of preschool depression, has found that those children who received a lot of nurturing from their parent (generally mother) developed a larger hippocampus than those who didn’t.

‘Nurturing’ was assessed in a videotaped interaction at the time of the preschool study. In this interaction, the parent performed a task while the child waited for her to finish so they could open an attractive gift. How the parent dealt with this common scenario — the degree to which they helped the child through the stress — was evaluated by independent raters.

Brain scans revealed that children who had been nurtured had a significantly larger hippocampus than those whose mothers were not as nurturing, and (this was the surprising bit), this effect was greater among the healthy, non-depressed children. Among this group, those with a nurturing parent had hippocampi which were on average almost 10% larger than those whose parent had not been as nurturing.

Reference: 

First study:
Sabates, R., Dex, S., Sabates, R., & Dex, S. (2012). Multiple risk factors in young children’s development. CLS Cohort Studies Working paper 2012/1.
Full text available at http://www.cls.ioe.ac.uk/news.aspx?itemid=1661&itemTitle=More+than+one+i...

Second study:
[2741] Teicher, M. H., Anderson C. M., & Polcari A.
(2012).  Childhood maltreatment is associated with reduced volume in the hippocampal subfields CA3, dentate gyrus, and subiculum.
Proceedings of the National Academy of Sciences.
Full text available at http://www.pnas.org/content/early/2012/02/07/1115396109.abstract?sid=f73...

Third study:
[2734] Luby, J. L., Barch D. M., Belden A., Gaffrey M. S., Tillman R., Babb C., et al.
(2012).  Maternal support in early childhood predicts larger hippocampal volumes at school age.
Proceedings of the National Academy of Sciences.

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Cognitive training for older adults can also change a personality trait

February, 2012

A program designed to improve reasoning ability in older adults also increased their openness to new experiences.

Openness to experience – being flexible and creative, embracing new ideas and taking on challenging intellectual or cultural pursuits – is one of the ‘Big 5’ personality traits. Unlike the other four, it shows some correlation with cognitive abilities. And, like them, openness to experience does tend to decline with age.

However, while there have been many attempts to improve cognitive function in older adults, to date no one has tried to increase openness to experience. Naturally enough, one might think — it’s a personality trait, and we are not inclined to view personality traits as amenable to ‘training’. However, recently there have been some indications that personality traits can be changed, through cognitive interventions or drug treatments. In this new study, a cognitive training program for older adults also produced increases in their openness to experience.

The study involved 183 older adults (aged 60-94; average age 73), who were randomly assigned to a 16-week training program or a waiting-list control group. The program included training in inductive reasoning, and puzzles that relied in part on inductive reasoning. Most of this activity was carried out at home, but there were two 1-hour classroom sessions: one to introduce the inductive reasoning training, and one to discuss strategies for Sudoku and crosswords.

Participants came to the lab each week to hand in materials and pick up the next set. Initially, they were given crossword and Sudoku puzzles with a wide range of difficulty. Subsequently, puzzle sets were matched to each participant’s skill level (assessed from the previous week’s performance). Over the training period, the puzzles became progressively more difficult, with the steps tailored to each individual.

The inductive reasoning training involved learning to recognize novel patterns and use them to solve problems. In ‘basic series problems’, the problems required inference from a serial pattern of words, letters, or numbers. ‘Everyday serial problems’ included problems such as completing a mail order form and answering questions about a bus schedule. Again, the difficulty of the problems increased steadily over the training period.

Participants were asked to spend at least 10 hours a week on program activities, and according to the daily logs they filled in, they spent an average of 11.4 hours a week. In addition to the hopefully inherent enjoyment of the activities, those who recorded 10 hours were recognized on a bulletin board tally sheet and entered into a raffle for a prize.

Cognitive and personality testing took place 4-5 weeks prior to the program starting, and 4-5 weeks after program end. Two smaller assessments also took place during the program, at week 6 and week 12.

At the end of the program, those who had participated had significantly improved their pattern-recognition and problem-solving skills. This improvement went along with a moderate but significant increase in openness. Analysis suggested that this increase in openness occurred independently of improvement in inductive reasoning.

The benefits were specific to inductive reasoning and openness, with no significant effects on divergent thinking, processing speed, verbal ability, or the other Big 5 traits.

The researchers suggest that the carefully stepped training program was important in leading to increased openness, allowing the building of a growing confidence in their reasoning abilities. Openness to experience contributes to engagement and enjoyment in stimulating activity, and has also been linked to better health and decreased mortality risk. It seems likely, then, that increases in openness can be part of a positive feedback cycle, leading to greater and more sustained engagement in mentally stimulating activities.

The corollary is that decreases in openness may lead to declines in cognitive engagement, and then to poorer cognitive function. Indeed it has been previously suggested that openness to experience plays a role in cognitive aging.

Clearly, more research is needed to tease out how far these findings extend to other activities, and the importance of scaffolding (carefully designing cognitive activities on an individualized basis to support learning), but this work reveals an overlooked aspect to the issue of mental stimulation for preventing age-related cognitive decline.

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