Latest Research News
A randomized clinical trial involving 103 teenage athletes who sustained concussions while playing sports found that those who underwent a supervised, aerobic exercise program took significantly less time to recover compared to those who instead engaged in mild stretching.
Those in the exercise program took on average 13 days to recover, while those in the control group, who performed placebo-like stretching exercises (that would not substantially elevate heart rate), took 17 days. In addition, only two patients in the exercise program took longer than four weeks to recover, compared to seven patients in the control group.
The treatment began within the first week of a concussion in adolescents, after a few days of rest. Each exercise program was individually tailored, on the basis of their performance on the Buffalo Concussion Treadmill Test, and each participant was given a heart rate monitor to ensure they didn’t exceed the given threshold. The assigned exercise took about 20 minutes each day.
The exercise “dose” was evaluated weekly, and increased as the patient’s condition improved.
Patients were also told to avoid contact sports, gym class, or team practice, and excessive use of electronic devices, since that can also aggravate symptoms.
Adolescents typically take the longest to recover from concussion.
The findings directly contradict the conventional approach to concussion, which often consists of nearly total rest, eliminating most physical and mental activities, including schoolwork.
The American Academy of Pediatric now supports children and teens engaging in light physical activity and returning to school as they recover. It also now advises against complete removal of electronic devices, such as television, computers and smartphones, following a concussion.
"We've learned that keeping kids in dark rooms and eliminating all cognitive and physical activity actually worsened a lot of kids' symptoms rather than improving them."
While young athletes should stop playing immediately after a concussion is suspected, light physical activity, such as brisk walking, can be incorporated as they are recovering. Similarly, academic workloads may need to be lessened after brain injury; however, such students shouldn't need to miss prolonged periods of school or disengage in learning.
However, the authors note that each concussion is unique, and specific recommendations should be tailored for the individual case.
Halstead ME, Walter KD, Moffatt K, and the American Academy of Pediatric’s Council on Sports Medicine and Fitness. Sports-Related Concussion in Children and Adolescents. Pediatrics. Published online Nov. 12, 2018. https://www.childrensomaha.org/wp-content/uploads/2018/11/Sport-Related-Concussion.pdf
A study involving 845 secondary school students has revealed that each hour per day spent watching TV, using the internet or playing computer games at average age 14.5 years was associated with poorer GCSE grades at age 16. Additionally, each hour of daily homework and reading was linked to significantly better grades. Surprisingly, however, the amount of physical activity had no effect on academic performance.
Median screen time was four hours a day, of which around half was spent watching TV; median sedentary non-screen time (reading/homework) was 1.5 hours.
Each hour per day of time spent in front of the TV or computer in Year 10 was associated with 9.3 fewer GCSE points in Year 11 — the equivalent to two grades in one subject or one grade in each of two subjects. Two hours was therefore associated with 18 fewer points at GCSE, and the median of four hours, with a worrying 36 fewer points.
The burning question: are some screens better than others? Comparison of the different screen activities revealed that TV viewing was the most detrimental to grades.
More positively, each hour of daily homework and reading was associated with an average 23.1 more GCSE points. This was a U-shaped function, however, with pupils doing over four hours of reading or homework a day performing less well than their peers. But the number of pupils in this category was relatively low (only 52 pupils) and may include students who were struggling at school.
The benefits from spending time on homework or reading were not simply a consequence of spending less time staring at a screen; screen time and time spent reading or doing homework were independently associated with academic performance.
Do note that, although some homework was doubtless done on the computer, this was not counted as screen time for the purposes of this study.
The finding of no significant association between moderate to vigorous physical activity and academic performance is more surprising, given the evidence for the benefits of exercise and physical fitness for cognition. The median was 39 minutes of moderate to vigorous physical activity a day, with a quarter of the students getting less than 20 minutes a day, and a quarter getting more than 65 minutes.
The data used was from the ROOTS study, a large longitudinal study assessing health and wellbeing during adolescence. Objective levels of activity and time spent sitting were assessed through a combination of heart rate and movement sensing. Screen time, time spent doing homework, and reading for pleasure, relied on self-report. Medians were used rather than means, because of the degree of skew in the data.
We've seen a number of studies showing the value of music training for children's development of language skills. A new study has investigated what happens if the training doesn't begin until high school.
The study involved 40 Chicago-area high school students who were followed from their beginning at high school until their senior year. Nearly half the students had enrolled in band classes, which involved two to three hours a week of instrumental group music instruction in school. The rest had enrolled in junior Reserve Officers' Training Corps (ROTC), which emphasized fitness exercises during a comparable period.
The music group showed more rapid maturation in the brain's response to sound, and demonstrated prolonged heightened brain sensitivity to sound details. While all students improved in language skills tied to sound-structure awareness, the improvement was greater for those in music classes.
The finding is encouraging in that it shows that adolescent brains are still receptive to music training.
It's also encouraging in involving students from low-income areas. Children from families of lower socioeconomic status have been found to process sound less efficiently, in part because of noisier environments and also due to linguistic deprivation. A previous small study by the same researchers looked at the benefits of a free community music program for a group of disadvantaged students (the Harmony Project). In this small study, students more engaged in the program (as assessed by attendance and participation) showed greater improvement after two years, in how their brains processed speech and in their reading scores. Those who learned to play instruments also showed greater improvement than those who participated in music appreciation classes.
There's been a lot of talk in recent years about the importance of mindset in learning, with those who have a “growth mindset” (ie believe that intelligence can be developed) being more academically successful than those who believe that intelligence is a fixed attribute. A new study shows that a 45-minute online intervention can help struggling high school students.
The study involved 1,594 students in 13 U.S. high schools. They were randomly allocated to one of three intervention groups or the control group. The intervention groups either experienced an online program designed to develop a growth mindset, or an online program designed to foster a sense of purpose, or both programs (2 weeks apart). All interventions were expected to improve academic performance, especially in struggling students.
The interventions had no significant benefits for students who were doing okay, but were of significant benefit for those who had an initial GPA of 2 or less, or had failed at least one core subject (this group contained 519 students; a third of the total participants). For this group, each of the interventions was of similar benefit; interestingly, the combined intervention was less beneficial than either single intervention. It's plausibly suggested that this might be because the different messages weren't integrated, and students may have had some trouble in taking on board two separate messages.
Overall, for this group of students, semester grade point averages improved in core academic courses and the rate at which students performed satisfactorily in core courses increased by 6.4%.
GPA average in core subjects (math, English, science, social studies) was calculated at the end of the semester before the interventions, and at the end of the semester after the interventions. Brief questions before and after the interventions assessed the students' beliefs about intelligence, and their sense of meaningfulness about schoolwork.
GPA before intervention was positively associated with a growth mindset and a sense of purpose, explaining why the interventions had no effect on better students. Only the growth mindset intervention led to a more malleable view of intelligence; only the sense-of-purpose intervention led to a change in perception in the value of mundane academic tasks. Note that the combined intervention showed no such effects, suggesting that it had confused rather than enlightened!
In the growth mindset intervention, students read an article describing the brain’s ability to grow and reorganize itself as a consequence of hard work and good strategies. The message that difficulties don't indicate limited ability but rather provide learning opportunities, was reinforced in two writing exercises. The control group read similar materials, but with a focus on functional localization in the brain rather than its malleability.
In the sense-of-purpose interventions, students were asked to write about how they wished the world could be a better place. They read about the reasons why some students worked hard, such as “to make their families proud”; “to be a good example”; “to make a positive impact on the world”. They were then asked to think about their own goals and how school could help them achieve those objectives. The control group completed one of two modules that didn't differ in impact. In one, students described how their lives were different in high school compared to before. The other was much more similar to the intervention, except that the emphasis was on economic self-interest rather than social contribution.
The findings are interesting in showing that you can help poor learners with a simple intervention, but perhaps even more, for their indication that such interventions are best done in a more holistic and contextual way. A more integrated message would hopefully have been more effective, and surely ongoing reinforcement in the classroom would make an even bigger difference.
Two studies indicate that young people carrying the “Alzheimer’s gene” (ApoE4) do not have the pathological changes found later in life. The first study, involving 1412 adolescents, found no differences in hippocampal volume or asymmetry as a function of gene status. The second study, involving 173 young adults (average age, 28 ± 7.6 years), found no difference in plasma concentrations of amyloid-beta peptides.
A study involving 187 children and adolescents with multiple sclerosis, plus 44 who experienced their first neurologic episode (clinically isolated syndrome) indicative of MS, has found that 35% of those with MS and 18% of those with clinically isolated syndrome were cognitively impaired. Cognitive assessment was done using a battery of 11 tests. The most common areas of impairment were fine motor coordination, visual-motor integration, and speeded information processing.
I’ve talked before about how even mild head injuries can have serious consequences, and in recent years we’ve seen growing awareness of the long-term dangers of sports’ concussions (especially for young people). This has been followed by a number of initiatives to help protect athletes. However, while encouraging, they may still be under-estimating the problem. Two recent studies, involving high school athletes who had experienced concussions, point to quite subtle impairment lasting for longer than expected.
In one study, 20 concussed adolescents were tested on their attention and executive function within 72 hours post injury, and then again at one week, two weeks, one month, and two months post injury. Compared with matched controls, they had a significantly greater switch cost on the Task-Switching Test and a significantly greater reaction time for the Attentional Network Test conflict effect component, with this lasting up to two months after injury.
The results suggest that longer recovery periods than the standard 7-10 days may be warranted, given that the slower reaction times (although only a matter of milliseconds) might make further injury more likely.
In another study, 54 adolescent athletes who had been concussed but who reported being symptom-free and had returned to baseline neurocognitive-test levels, were given, further testing. This revealed that over a quarter of them (27.7%) showed cognitive impairment following moderate physical exertion (15 to 25 minutes on a treadmill, elliptical, or stationary bicycle). These athletes scored significantly lower on verbal and visual memory, although processing speed and reaction was not affected (suggesting that tests focusing mainly on these latter abilities are insufficient).
The group affected did not differ from the rest in terms of symptoms or concussion history.
The findings suggest that computerized neurocognitive testing following moderate exertion should be part of the standard procedure when making return-to-play decisions.
I’ve spoken before about the effects of motivation on test performance. This is displayed in a fascinating study by researchers at the Educational Testing Service, who gave one of their widely-used tests (the ETS Proficiency Profile, short form, plus essay) to 757 students from three institutions: a research university, a master's institution and a community college. Here’s the good bit: students were randomly assigned to groups, each given a different consent form. In the control condition, students were told: “Your answers on the tests and the survey will be used only for research purposes and will not be disclosed to anyone except the research team.” In the “Institutional” condition, the rider was added: “However, your test scores will be averaged with all other students taking the test at your college.” While in the “Personal” condition, they were told instead: “However, your test scores may be released to faculty in your college or to potential employers to evaluate your academic ability.”
No prizes for guessing which of these was more motivating!
Students in the “personal” group performed significantly and consistently better than those in the control group at all three institutions. On the multi-choice part of the test, the personal group performed on average .41 of the standard deviation higher than the control group, and the institutional group performed on average .26 SD higher than the controls. The largest difference was .68 SD. On the essay, the largest effect size was .59 SD. (The reason for the results being reported this way is because the focus of the study was on the use of such tests to assess and compare learning gains by colleges.)
The effect is perhaps less dramatic at the individual level, with the average sophomore score on the multichoice test being 460, compared to 458 and 455, for personal, institutional, and control groups, respectively. Interestingly, this effect was greater at the senior level: 469 vs 466 vs 460. For the essay question, however, the effect was larger: 4.55 vs 4.35 vs 4.21 (sophomore); 4.75 vs 4.37 vs 4.37 (senior). (Note that these scores have been adjusted by college admission scores).
Students also reported on motivation level, and this was found to be a significant predictor of test performance, after controlling for SAT or placement scores.
Student participants had received at least one year of college, or (for community colleges) taken at least three courses.
The findings confirm recently expressed concern that students don’t put their best efforts into low-stakes tests, and that, when such tests are used to make judgments about institutional performance (how much value they add), they may well be significantly misleading, if different institutions are providing different levels of motivation.
On a personal level, of course, the findings may be taken as further confirmation of the importance of non-academic factors in academic achievement. Something looked at more directly in the next study.
Motivation, study habits—not IQ—determine growth in math achievement
Data from a large German longitudinal study assessing math ability in adolescents found that, although intelligence was strongly linked to students' math achievement, this was only in the initial development of competence. The significant predictors of growth in math achievement, however, were motivation and study skills.
Specifically (and excitingly for me, since it supports some of my recurring themes!), at the end of Grade 5, perceived control was a significant positive predictor for growth, and surface learning strategies were a significant negative predictor. ‘Perceived control’ reflects the student’s belief that their grades are under their control, that their efforts matter. ‘Surface learning strategies’ reflect the use of rote memorization/rehearsal strategies rather than ones that encourage understanding. (This is not to say, of course, that these strategies don’t have their place — but they need to be used appropriately).
At the end of Grade 7, however, a slightly different pattern emerged, with intrinsic motivation and deep learning strategies the significant positive predictors of growth, while perceived control and surface learning strategies were no longer significant.
In other words, while intelligence didn’t predict growth at either point, the particular motivational and strategy variables that affected growth were different at different points in time, reflecting, presumably, developmental changes and/or changes in academic demands.
Note that this is not to say that intelligence doesn’t affect math achievement! It is, indeed, a strong predictor — but through its effect on getting the student off to a good start (lifting the starting point) rather than having an ongoing benefit.
There was, sadly but unfortunately consistent with other research, an overall decline in motivation from grade 5 to 7. There was also a smaller decline in strategy use (any strategy! — presumably reflecting the declining motivation).
It’s also worth noting that (also sadly but unsurprisingly) the difference between school types increased over time, with those in the higher track schools making more progress than those in the lowest track.
The last point I want to emphasize is that extrinsic motivation only affected initial levels, not growth. The idea that extrinsic motivation (e.g., wanting good grades) is of only short-term benefit, while intrinsic motivation (e.g., being interested in the subject) is far more durable, is one I have made before, and one that all parents and teachers should pay attention to.
The study involved 3,520 students, following them from grades 5 to 10. The math achievement test was given at the end of each grade, while intelligence and self-reported motivation and strategy use were assessed at the end of grades 5 and 7. Intelligence was assessed using the nonverbal reasoning subtest of Thorndike’s Cognitive Abilities Test (German version). The 42 schools in the study were spread among the three school types: lower-track (Hauptschule), intermediate-track (Realschule), and higher-track (Gymnasium). These school types differ in entrance standards and academic demands.
Chronic use of alcohol and marijuana during youth has been associated with poorer neural and cognitive function, which appears to continue into adulthood. A new study looking specifically at white-matter changes provides more support for the idea that adolescent brains may be at particular risk from the damage that substance abuse can bring.
The brain-imaging study compared 41 adolescents (aged 16-20) with extensive marijuana- and alcohol-use histories by mid-adolescence with 51 adolescents with no such history. The study found that substance users showed poorer white matter integrity in seven tracts (right and left superior longitudinal fasciculus, right posterior thalamic radiations, right prefrontal thalamic fibers, right superior temporal gyrus white matter, right inferior longitudinal fasciculus, left posterior corona radiata).
Two brain scans were taken, at baseline and at 18 months. Substance use interviews were given every six months.
More alcohol use during the interval was associated with worse integrity in both the right and left superior longitudinal fasciculi, above and beyond baseline values in these bundles. Marijuana use didn’t predict change over time. Those who had a history of more risk-taking behaviors showed poorer integrity of the right prefrontal thalamic fibers.
The findings add to previous research showing white matter problems in youth with substance-use histories. The study points to alcohol use during adolescence being particularly problematic. It also suggests that youth who engage in risk-taking behaviors may tend to have poorly developed fronto-thalamic tracts.
All of this is particularly worrying because it is thought that maturation of the brain during adolescence is the foundation for self-control, suggesting that substance abuse during this period may have long-lasting effects on the individual’s ability to plan, organize, and self-regulate.
Problems with myelin — demyelination (seen most dramatically in MS, but also in other forms of neurodegeneration, including normal aging and depression); failure to develop sufficient myelin (in children and adolescents) — are increasingly being implicated in a wide range of disorders. A new animal study adds to that evidence by showing that social isolation brings about both depression and loss of myelin.
In the study, adult mice were isolated for eight weeks (which is of course longer for a mouse than it is to us) to induce a depressive-like state. They were then introduced to a mouse they hadn’t seen before. Although typically very social animals, those who had been socially isolated didn’t show any interest in interacting with the new mouse — a common pattern in human behavior as well.
Analysis of their brains revealed significantly lower levels of gene transcription for oligodendrocyte cells (the components of myelin) in the prefrontal cortex. This appeared to be caused by a lower production of heterochromatin (tightly packed DNA) in the cell nuclei, producing less mature oligodendrocytes.
Interestingly, even short periods of isolation were sufficient to produce changes in chromatin and myelin, although behavior wasn’t affected.
Happily, however, regardless of length of isolation, myelin production went back to normal after a period of social integration.
The findings add to the evidence that environmental factors can have significant effects on brain development and function, and support the idea that socializing is good for the brain.
There have been a number of studies in the past few years showing how poverty affects brain development and function. One of these showed specifically that children of high and low socioeconomic status showed differences in brain wave patterns associated with an auditory selective attention task. This was thought to indicate that the groups were using different mechanisms to carry out the task, with the lower SES children employing extra resources to attend to irrelevant information.
In a follow-up study, 28 young adolescents (12-14 years) from two schools in neighborhoods of different socioeconomic status answered questions about their emotional and motivational state at various points during the day, and provided saliva samples to enable monitoring of cortisol levels. At one point in the afternoon, they also had their brainwaves monitored while they carried out an auditory selective attention task (hearing different sounds played simultaneously into both ears, they were required to press a button as fast as possible when they heard one particular sound).
While performance on the task was the same for both groups, there were, once again, differences in the brain wave patterns. Higher SES children exhibited far larger theta waves in the frontal lobes in response to sounds they attended to than to compared to those they should have ignored, while lower SES children showed much larger theta waves to the unattended sounds than for the attended sounds.
While the lower SES children had higher cortisol levels throughout the school day, like the higher SES children, they showed little change around the task, suggesting neither group was particularly stressed by the task. Both groups also showed similar levels of boredom and motivation.
What the findings suggest is that lower SES children have to exert more cognitive control to avoid attending to irrelevant stimuli than higher SES children — perhaps because they live in more threatening environments.
Full text available at http://www.frontiersin.org/human_neuroscience/10.3389/fnhum.2012.00306/a...
Adding to the growing evidence for the long-term cognitive benefits of childhood music training, a new study has found that even a few years of music training in childhood has long-lasting benefits for auditory discrimination.
The study involved 45 adults (aged 18-31), of whom 15 had no music training, 15 had one to five years of training, and 15 had six to eleven years. Participants were presented with different complex sounds ranging in pitch while brainstem activity was monitored.
Brainstem response to the sounds was significantly stronger in those with any sort of music training, compared to those who had never had any music training. This was a categorical difference — years of training didn’t make a difference (although some minimal length may be required — only one person had only one year of training). However, recency of training did make a difference to brainstem response, and it does seem that some fading might occur over long periods of time.
This difference in brainstem response means that those with music training are better at recognizing the fundamental frequency (lowest frequency sound). This explains why music training may help protect older adults from hearing difficulties — the ability to discriminate fundamental frequencies is crucial for understanding speech, and for processing sound in noisy environments.
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).
Full text available at http://infam.antville.org/static/infam/files/pnas.pdf
In contradiction of some other recent research, a large new study has found that offering students rewards just before standardized testing can improve test performance dramatically. One important factor in this finding might be the immediate pay-off — students received their rewards right after the test. Another might be in the participants, who were attending low-performing schools.
The study involved 7,000 students in Chicago public schools and school districts in south-suburban Chicago Heights. Older students were given financial rewards, while younger students were offered non-financial rewards such as trophies.
Students took relatively short, standardized diagnostic tests three times a year to determine their grasp of mathematics and English skills. Unusually for this type of research, the students were not told ahead of time of the rewards — the idea was not to see how reward improved study habits, but to assess its direct impact on test performance.
Consistent with other behavioral economics research, the prospect of losing a reward was more motivating than the possibility of receiving a reward — those given money or a trophy to look at while they were tested performed better.
The most important finding was that the rewards only ‘worked’ if they were going to be given immediately after the test. If students were told instead that they would be given the reward sometime later, test performance did not improve.
Follow-up tests showed no negative impact of removing the rewards in successive tests.
Age and type of reward mattered. Elementary school students (who were given nonfinancial rewards) responded more to incentives than high-school students. Younger students have been found to be more responsive to non-monetary rewards than older students. Among high school students, the amount of money involved mattered.
It’s important to note that the students tested had low initial motivation to do well. I would speculate that the timing issue is so critical for these students because distant rewards are meaningless to them. Successful students tend to be more motivated by the prospect of distant rewards (e.g., a good college, a good job).
The finding does demonstrate that a significant factor in a student’s poor performance on tests may simply come from not caring to try.
I’ve mentioned before that, for some few people, exercise doesn’t seem to have a benefit, and the benefits of exercise for fighting age-related cognitive decline may not apply to those carrying the Alzheimer’s gene.
New research suggests there is another gene variant that may impact on exercise’s effects. The new study follows on from earlier research that found that physical exercise during adolescence had more durable effects on object memory and BDNF levels than exercise during adulthood. In this study, 54 healthy but sedentary young adults (aged 18-36) were given an object recognition test before participating in either (a) a 4-week exercise program, with exercise on the final test day, (b) a 4-week exercise program, without exercise on the final test day, (c) a single bout of exercise on the final test day, or (d) remaining sedentary between test days.
Exercise both improved object recognition memory and reduced perceived stress — but only in one group: those who exercised for 4 weeks including the final day of testing. In other words, both regular exercise and recent exercise was needed to produce a memory benefit.
But there is one more factor — and this is where it gets really interesting — the benefit in this group didn’t happen for every member of the group. Only those carrying a specific genotype benefited from regular and recent exercise. This genotype has to do with the brain protein BDNF, which is involved in neurogenesis and synaptic plasticity, and which is increased by exercise. The BDNF gene comes in two flavors: Val and Met. Previous research has linked the less common Met variant to poorer memory and greater age-related cognitive decline.
In other words, it seems that the Met allele affects how much BDNF is released as a result of exercise, and this in turn affects cognitive benefits.
The object recognition test involved participants seeing a series of 50 images (previously selected as being highly recognizable and nameable), followed by a 15 minute filler task, before seeing 100 images (the previous 50 and 50 new images) and indicating which had been seen previously. The filler task involved surveys for state anxiety, perceived stress, and mood. On the first (pre-program) visit, a survey for trait anxiety was also completed.
Of the 54 participants, 31 carried two copies of the Val allele, and 23 had at least one Met allele (19 Val/Met; 4 Met/Met). The population frequency for carrying at least one Met allele is 50% for Asians, 30% in Caucasians, and 4% in African-Americans.
Although exercise decreased stress and increased positive mood, the cognitive benefits of exercise were not associated with mood or anxiety. Neither was genotype associated with mood or anxiety. However, some studies have found an association between depression and the Met variant, and this study is of course quite small.
A final note: this study is part of research looking at the benefits of exercise for children with ADHD. The findings suggest that genotyping would enable us to predict whether an individual — a child with ADHD or an older adult at risk of cognitive decline or impairment — would benefit from this treatment strategy.
A three-year study involving 3,034 Singaporean children and adolescents (aged 8-17) has found that those who spent more time playing video games subsequently had more attention problems, even when earlier attention problems, sex, age, race, and socioeconomic status were statistically controlled. Those who were more impulsive or had more attention problems subsequently spent more time playing video games, even when initial video game playing was statistically controlled. These findings suggest that the cause-effect relationship between video game playing and attention problems/impulsiveness goes both ways.
While the particular content may have an effect on attention problems and impulsiveness (violent games appeared to be an additional, independent, factor in attention problems), it was the total time spent that was more important.
Participants completed questionnaires about their video game playing habits annually for three years running. They also completed questionnaires aimed to measure attention and impulsiveness (the Current ADHD Symptoms Scale Self-Report, and the Barratt Impulsiveness Scale-11, respectively). Regarding attention, the children answered questions such as how often they "fail to give close attention to details or make careless mistakes" in their work or "blurt out answers before questions have been completed." For the impulsivity test, they selected points they felt described themselves, such as "I often make things worse because I act without thinking" or "I concentrate easily."
How does this finding relate to other evidence showing that playing video games can improve visual attention for rapid and accurate recognition of information from the environment? The answer lies in the different nature of attention — the attention needed for visual search differs in important ways from the attention necessary for sustained concentration in contexts that are often effortful and/or boring.
The example of many attention-challenged individuals makes this more understandable. Many parents of children with ADHD find that the only thing their child can concentrate on for a lengthy period is video games. The answer to that riddle is the rapidly changing nature of video games, and the way they are designed to grab the attention, with flashing lights and loud noises and moving images etc. The young person is not, therefore, improving their ability to focus in a way that is helpful for the school environment, or indeed for everyday life.
Unfortunately, this study suggests that it is precisely those people who are most in need of such ‘external supports’ for attention (‘grabbing’ stimuli such as lights and sounds and movement) — that is, those individuals who are least able to control their own attention — who are most likely to spend a lot of time playing such games. The games then weaken their attentional control even more, and so the cycle continues.
So this research answers the question ADHD parents tend to have: should I encourage my child to play video games a lot (given that it’s the only thing that holds their attention) or not? The answer, unfortunately, would seem to be: not. However, all is not lost. There are computer ‘games’ that are designed to help those with ADHD learn to concentrate in a way that is more useful (see the Topic collection on ADHD for more on this).
The American Academy of Pediatrics recommends one hour per day of total media screen time (including TV, DVDs, video games, Internet, iPad, etc.) for children in elementary school, and two hours for children in secondary school.
Gentile, D.A., Swing, E.L., Lim, C.G. & Khoo, A. 2012. Video game playing, attention problems, and impulsiveness: Evidence of bidirectional causality. Psychology of Popular Media Culture, Vol 1(1), Jan 2012, 62-70. doi: 10.1037/a0026969
Full text available at http://www.apa.org/pubs/journals/releases/ppm-1-1-62.pdf
A review of 10 observational and four intervention studies as said to provide strong evidence for a positive relationship between physical activity and academic performance in young people (6-18). While only three of the four intervention studies and three of the 10 observational studies found a positive correlation, that included the two studies (one intervention and one observational) that researchers described as “high-quality”.
An important feature of the high-quality studies was that they used objective measures of physical activity, rather than students' or teachers' reports. More high-quality studies are clearly needed. Note that the quality score of the 14 studies ranged from 22%! to 75%.
Interestingly, a recent media report (NOT, I hasten to add, a peer-reviewed study appearing in an academic journal) spoke of data from public schools in Lincoln, Nebraska, which apparently has a district-wide physical-fitness test, which found that those were passed the fitness test were significantly more likely to also pass state reading and math tests.
Specifically, data from the last two years apparently shows that 80% of the students who passed the fitness test either met or exceeded state standards in math, compared to 66% of those who didn't pass the fitness test, and 84% of those who passed the fitness test met or exceeded state standards in reading, compared to 71% of those who failed the fitness test.
Another recent study looks at a different aspect of this association between physical exercise and academic performance.
The Italian study involved138 normally-developing children aged 8-11, whose attention was tested before and after three different types of class: a normal academic class; a PE class focused on cardiovascular endurance and involving continuous aerobic circuit training followed by a shuttle run exercise; a PE class combining both physical and mental activity by involving novel use of basketballs in varying mini-games that were designed to develop coordination and movement-based problem-solving. These two types of physical activity offered the same exercise intensity, but very different skill demands.
The attention test was a short (5-minute) paper-and-pencil task in which the children had to mark each occurrence of “d” with double quotation marks either above or below in 14 lines of randomly mixed p and d letters with one to four single and/or double quotation marks either over and/or under each letter.
Processing speed increased 9% after mental exercise (normal academic class) and 10% after physical exercise. These were both significantly better than the increase of 4% found after the combined physical and mental exertion.
Similarly, scores on the test improved 13% after the academic class, 10% after the standard physical exercise, and only 2% after the class combining physical and mental exertion.
Now it’s important to note is that this is of course an investigation of the immediate arousal benefits of exercise, rather than an investigation of the long-term benefits of being fit, which is a completely different question.
But the findings do bear on the use of PE classes in the school setting, and the different effects that different types of exercise might have.
First of all, there’s the somewhat surprising finding that attention was at least as great, if not better, after an academic class than the PE class. It would not have been surprising if attention had flagged. It seems likely that what we are seeing here is a reflection of being in the right head-space — that is, the advantage of continuing with the same sort of activity.
But the main finding is the, also somewhat unexpected, relative drop in attention after the PE class that combined mental and physical exertion.
It seems plausible that the reason for this lies in the cognitive demands of the novel activity, which is, I think, the main message we should take away from this study, rather than any comparison between physical and mental activity. However, it would not be surprising if novel activities that combine physical and mental skills tend to be more demanding than skills that are “purely” (few things are truly pure I know) one or the other.
Of course, it shouldn’t be overlooked that attention wasn’t hampered by any of these activities!
First study: http://blogs.edweek.org/edweek/schooled_in_sports/2012/01/strong_evidenc...
Second study: http://blogs.edweek.org/edweek/schooled_in_sports/2011/11/students_fitne...
Third study: http://news.yahoo.com/exercise-might-boost-kids-academic-ability-1602081...
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.
Washbrook, E., & Waldfogel, J. (2011). On your marks : Measuring the school readiness of children in low-to-middle income families. Resolution Foundation, December 2011.
Is there, or is there not, a gender gap in mathematics performance? And if there is, is it biological or cultural?
Although the presence of a gender gap in the U.S. tends to be regarded as an obvious truth, evidence is rather more equivocal. One meta-analysis of studies published between 1990 and 2007, for example, found no gender differences in mean performance and nearly equal variability within each gender. Another meta-analysis, using 30 years of SAT and ACT scores, found a very large 13:1 ratio of middle school boys to girls at the highest levels of performance in the early 1980s, which declined to around 4:1 by 1991, where it has remained. A large longitudinal study found that males were doing better in math, across all socioeconomic classes, by the 3rd grade, with the ratio of boys to girls in the top 5% rising to 3:1 by 5th grade.
Regardless of the extent of any gender differences in the U.S., the more fundamental question is whether such differences are biological or cultural. The historical changes mentioned above certainly point to a large cultural component. Happily, because so many more countries now participate in the Trends in International Mathematics and Science Study (TIMSS) and the Programme in International Student Assessment (PISA), much better data is now available to answer this question. In 2007, for example, 4th graders from 38 countries and 8th graders from 52 countries participated in TIMSS. In 2009, 65 countries participated in PISA.
So what does all this new data reveal about the gender gap? Overall, there was no significant gender gap in the 2003 and 2007 TIMSS, with the exception of the 2007 8th graders, where girls outperformed boys.
There were, of course, significant gender gaps on a country basis. Researchers looked at several theories for what might underlie these.
Contradicting one theory, gender gaps did not correlate reliably with gender equity. In fact, both boys and girls tended to do better in math when raised in countries where females have better equality. The primary contributor to this appears to be women’s income and rates of participation in the work force. This is in keeping with the idea that maternal education and employment opportunities have benefits for their children’s learning regardless of gender.
The researchers also looked at the more specific hypothesis put forward by Steven Levitt, that gender inequity doesn’t hurt girls' math performance in Muslim countries, where most students attend single-sex schools. This theory was not borne out by the evidence. There was no consistent link between school type and math performance across countries.
However, math performance in the 29 wealthier countries could be predicted to a very high degree by three factors: economic participation and opportunity; GDP per capita; membership of one of three clusters — Middle Eastern (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia); East Asian (Hong Kong, Japan, South Korea, Singapore, Taiwan); rest (Russia, Hungary, Czech Republic, England, Canada, US, Australia, Sweden, Norway, Scotland, Cyprus, Italy, Malta, Israel, Spain, Lithuania, Malaysia, Slovenia, Dubai). The Middle Eastern cluster scored lowest (note the exception of Dubai), and the East Asian the highest. While there are many cultural factors differentiating these clusters, it’s interesting to note that countries’ average performance tended to be higher when students attribute less importance to mastering math.
The investigators also looked at the male variability hypothesis — the idea that males are more variable in their performance, and their predominance at the top is balanced by their predominance at the bottom. The study found however that greater male variation in math achievement varies widely across countries, and is not found at all in some countries.
In sum, the cross-country variability in performance in regard to gender indicates that the most likely cause of any differences lies in country-specific social factors. These could include perception of abilities as fixed vs malleable, attitude toward math, gender beliefs.
A popular theory of women’s underachievement in math concerns stereotype threat (first proposed by Spencer, Steele, and Quinn in a 1999 paper). I have reported on this on several occasions. However, a recent review of this research claims that many of the studies were flawed in their methodology and statistical analysis.
Of the 141 studies that cited the original article and related to mathematics, only 23 met the criteria needed (in the reviewers’ opinion) to replicate the original study:
- Both genders tested
- Math test used
- Subjects recruited regardless of preexisting beliefs about gender stereotypes
- Subjects randomly assigned to experimental conditions
Of these 23, three involved younger participants (< 18 years) and were excluded. Of the remaining 20 studies, only 11 (55%) replicated the original effect (a significant interaction between gender and stereotype threat, and women performing significantly worse in the threat condition than in the threat condition compared to men).
Moreover, half the studies confounded the results by statistically adjusting preexisting math scores. That is, the researchers tried to adjust for any preexisting differences in math performance by using a previous math assessment measure such as SAT score to ‘tweak’ the baseline score. This practice has been the subject of some debate, and the reviewers come out firmly against it, arguing that “an important assumption of a covariate analysis is that the groups do not differ on the covariate. But that group difference is exactly what stereotype threat theory tries to explain!” Note, too, that the original study didn’t make such an adjustment.
So what happens if we exclude those studies that confounded the results? That leaves ten studies, of which only three found an effect (and one of these found the effect only in a subset of the math test). In other words, overwhelmingly, it was the studies that adjusted the scores that found an effect (8/10), while those that didn’t adjust them didn’t find the effect (7/10).
The power of the adjustment in producing the effect was confirmed in a meta-analysis.
Now these researchers aren’t saying that stereotype threat doesn’t exist, or that it doesn’t have an effect on women in this domain. Their point is that the size of the effect, and the evidence for the effect, has come to be regarded as greater and more robust than the research warrants.
At a practical level, this may have led to too much emphasis on tackling this problem at the expense of investigating other possible causes and designing other useful interventions.
Kane, J. M., & Mertz, J. E. (2012). Debunking Myths about Gender and Mathematics Performance. Notices of the AMS, 59(1), 10-21.
Iron deficiency is the world's single most common nutrient deficiency, and a well-known cause of impaired cognitive, language, and motor development. Many countries therefore routinely supplement infant foods with iron. However, a new study suggests that, while there is no doubt that such fortification has helped reduce iron deficiency, it may be that there is an optimal level of iron for infant development.
In 1992-94, 835 healthy, full-term infants living in urban areas in Chile, took part in a randomized trial to receive iron-fortified formula from 6 months of age to 12 months. A follow-up study has now assessed the cognitive functioning of 473 of these children at 10 years of age. Tests measured IQ, spatial memory, arithmetic achievement, visual-motor integration, visual perception and motor functioning.
Those who had received iron-fortified formula scored significantly lower than the non-fortified group on the spatial memory and visual-motor integration tests. Moreover, their performance on the other tests also tended to be worse, although these didn’t reach statistical significance.
There was no difference in iron level between these two groups (at age 10), and only one child had iron-deficiency anemia.
The crucial point, it seems, lies in the extent to which the infants needed additional iron. Children who had high iron levels at 6 months (5.5%, i.e. 26 infants) had lower scores at 10 years if they had received the iron-fortified formula, but those with low 6-month iron levels (18.4%; 87 infants) had higher scores at 10 years.
Further research is needed to confirm these findings, but the findings are not inconsistent with the idea that iron overload promotes neurodegenerative diseases.
In another longitudinal study, brain scans have revealed that teenage iron levels are associated with white matter fiber integrity.
The study first measured iron levels in 615 adolescent twins and siblings, and then scanned their brains when they were in their early twenties. Myelin (white matter) contains a lot of iron, so the strong correlation between teenage iron level and white matter integrity in young adulthood is not unexpected.
The correlation was stronger between identical twins that non-identical twins, suggesting a genetic contribution. Again, not unexpected — the transport of iron around the body is affected by several genes. One particular gene variant, in a gene that governs cellular absorption of transferrin-bound iron, was associated with both high iron levels and improved white matter integrity. This gene variant is found in about 12-15% of Caucasians.
The vital missing bit of information (because it wasn’t investigated) is whether this gene variant is associated with better cognitive performance. Further research will hopefully also investigate whether, while it might be better to have this variant earlier in life, it is detrimental in old age, given the suggestions that iron accumulation contributes to some neurodegenerative disorders (including Alzheimer’s).
Math-anxiety can greatly lower performance on math problems, but just because you suffer from math-anxiety doesn’t mean you’re necessarily going to perform badly. A study involving 28 college students has found that some of the students anxious about math performed better than other math-anxious students, and such performance differences were associated with differences in brain activity.
Math-anxious students who performed well showed increased activity in fronto-parietal regions of the brain prior to doing math problems — that is, in preparation for it. Those students who activated these regions got an average 83% of the problems correct, compared to 88% for students with low math anxiety, and 68% for math-anxious students who didn’t activate these regions. (Students with low anxiety didn’t activate them either.)
The fronto-parietal regions activated included the inferior frontal junction, inferior parietal lobule, and left anterior inferior frontal gyrus — regions involved in cognitive control and reappraisal of negative emotional responses (e.g. task-shifting and inhibiting inappropriate responses). Such anticipatory activity in the fronto-parietal region correlated with activity in the dorsomedial caudate, nucleus accumbens, and left hippocampus during math activity. These sub-cortical regions (regions deep within the brain, beneath the cortex) are important for coordinating task demands and motivational factors during the execution of a task. In particular, the dorsomedial caudate and hippocampus are highly interconnected and thought to form a circuit important for flexible, on-line processing. In contrast, performance was not affected by activity in ‘emotional’ regions, such as the amygdala, insula, and hypothalamus.
In other words, what’s important is not your level of anxiety, but your ability to prepare yourself for it, and control your responses. What this suggests is that the best way of dealing with math anxiety is to learn how to control negative emotional responses to math, rather than trying to get rid of them.
Given that cognitive control and emotional regulation are slow to mature, it also suggests that these effects are greater among younger students.
The findings are consistent with a theory that anxiety hinders cognitive performance by limiting the ability to shift attention and inhibit irrelevant/distracting information.
Note that students in the two groups (high and low anxiety) did not differ in working memory capacity or in general levels of anxiety.
You can download a copy of the study here: Math anxiety.pdf
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'.
In the study, 18 children (aged 7-8), 20 adolescents (13-14), and 20 young adults (20-29) were shown pictures and asked to decide whether it was a new picture or one they had seen earlier. Some of the pictures were of known objects and others were fanciful figures (this was in order to measure the effects of novelty in general). After a 10-minute break, they resumed the task — with the twist that any pictures that had appeared in the first session should be judged “new” if that was the first appearance in the second session. EEG measurements (event-related potentials — ERPs) were taken during the sessions.
ERPs at the onset of a test stimulus (each picture) are different for new and old (repeated) stimuli. Previous studies have established various old/new effects that reflect item and source memory in adults. In the case of item memory, recognition is thought to be based on two processes — familiarity and recollection — which are reflected in ERPs of different timings and location (familiarity: mid-frontal at 300-500 msec; recollection: parietal at 400-70 msec). Familiarity is seen as a fast assessment of similarity, while recollection varies according to the amount of retrieved information.
Source memory appears to require control processes that involve the prefrontal cortex. Given that this region is the slowest to mature, it would not be surprising if source memory is a problematic memory task for the young. And indeed, previous research has found that children do have particular difficulty in sourcing memories when the sources are highly similar.
In the present study, children performed more poorly than adolescents and adults on both item memory and source memory. Adolescents performed more poorly than adults on item memory but not on source memory. Children performed more poorly on source memory than item memory, but adolescents and adults showed no difference between the two tasks.
All groups responded faster to new items than old, and ERP responses to general novelty were similar across the groups — although children showed a left-frontal focus that may reflect the transition from analytic to a more holistic processing approach.
ERPs to old items, however, showed a difference: for adults, they were especially pronounced at frontal sites, and occurred at around 350-450 msec; for children and adolescents they were most pronounced at posterior sites, occurring at 600-800 msec for children and 400-600 msec for adolescents. Only adults showed the early midfrontal response that is assumed to reflect familiarity processing. On the other hand, the late old/new effect occurring at parietal sites and thought to reflect recollection, was similar across all age groups. The early old/new effect seen in children and adolescents at central and parietal regions is thought to reflect early recollection.
In other words, only adults showed the brain responses typical of familiarity as well as recollection. Now, some research has found evidence of familiarity processing in children, so this shouldn’t be taken as proof against familiarity processing in the young. What seems most likely is that children are less likely to use such processing. Clearly the next step is to find out the factors that affect this.
Another interesting point is the early recollective response shown by children and adolescents. It’s speculated that these groups may have used more retrieval cues — conceptual as well as perceptual — that facilitated recollection. I’m reminded of a couple of studies I reported on some years ago, that found that young children were better than adults on a recognition task in some circumstances — because children were using a similarity-based process and adults a categorization-based one. In these cases, it had more to do with knowledge than development.
It’s also worth noting that, in adults, the recollective response was accentuated in the right-frontal area. This suggests that recollection was overlapping with post-retrieval monitoring. It’s speculated that adults’ greater use of familiarity produces a greater need for monitoring, because of the greater uncertainty.
What all this suggests is that preadolescent children are less able to strategically recollect source information, and that strategic recollection undergoes an important step in early adolescence that is probably related to improvements in cognitive control. But this process is still being refined in adolescents, in particular as regards monitoring and coping with uncertainty.
Interestingly, source memory is also one of the areas affected early in old age.
Failure to remember the source of a memory has many practical implications, in particular in the way it renders people more vulnerable to false memories.
Brain imaging data from 103 healthy people aged 5-32, each of whom was scanned at least twice, has demonstrated that wiring to the frontal lobe continues to develop after adolescence.
The brain scans focused on 10 major white matter tracts. Significant changes in white matter tracts occurred in the vast majority of children and early adolescents, and these changes were mostly complete by late adolescence for projection and commissural tracts (projection tracts project from the cortex to non-cortical areas, such as the senses and the muscles, or from the thalamus to the cortex; commissural tracts cross from one hemisphere to the other). But association tracts (which connect regions within the same hemisphere) kept developing after adolescence.
This was particularly so for the inferior and superior longitudinal and fronto-occipital fascicule (the inferior longitudinal fasciculus connects the temporal and occipital lobes; the superior longitudinal fasciculus connects the frontal lobe to the occipital lobe and parts of the temporal and parietal lobes). These frontal connections are needed for complex cognitive tasks such as inhibition, executive functioning, and attention.
The researchers speculated that this continuing development may be due to the many life experiences in young adulthood, such as pursing post-secondary education, starting a career, independence and developing new social and family relationships.
But this continuing development wasn’t seen in everyone. Indeed, in some people, there was evidence of reductions, rather than growth, in white matter integrity. It may be that this is connected with the development of psychiatric disorders that typically develop in adolescence or young adulthood — perhaps directly, or because such degradation increases vulnerability to other factors (e.g., to drug use). This is speculative at the moment, but it opens up a new avenue to research.
Binge drinking occurs most frequently among young people, and there has been concern that consequences will be especially severe if the brain is still developing, as it is in adolescence. Because of the fact that it is only some parts of the brain — most crucially the prefrontal cortex and the hippocampus — that are still developing, it makes sense that only some functions will be affected.
I recently reported on a finding that binge drinking university students, performed more poorly on tests of verbal memory, but not on a test of visual memory. A new study looks at another function: spatial working memory. This task involves the hippocampus, and animal research has indicated that this region may be especially vulnerable to binge drinking. Spatial working memory is involved in such activities as driving, figural reasoning, sports, and navigation.
The study involved 95 adolescents (aged 16-19) from San Diego-area public schools: 40 binge drinking (27 males, 13 females) and 55 control (31 males, 24 females). Brain scans while performing a spatial working memory task revealed that there were significant gender differences in brain activation patterns for those who engaged in binge drinking. Specifically, in eight regions spanning the frontal cortex, anterior cingulate, temporal cortex, and cerebellum, female binge drinkers showed less activation than female controls, while male bingers exhibited greater activation than male controls. For female binge drinkers, less activation was associated with poorer sustained attention and working memory performances, while for male binge drinkers, greater activation was linked to better spatial performance.
The differences between male binge drinkers and controls were smaller than that seen in the female groups, suggesting that female teens may be particularly vulnerable. This is not the first study to find a gender difference in the brains’ response to excess alcohol. In this case it may have to do, at least partly, with differences in maturity — female brains mature earlier than males’.
Most research into the importance of folate and B12 levels has centered on seniors, and it does seem clear now that having adequate levels of these vitamins is important for maintaining cognitive functioning as you get older. Folic acid levels are of course also regarded as crucial when the brain is developing, which is why pregnant women are urged to take supplements, and why some countries fortify their bread with it. There is less research in the extensive ground between these two end-points.
A Swedish study involving 386 15-year-olds has now found that those in the top third of folic acid intake (more than 253 micrograms per day for girls and 335 for boys) performed significantly better on their school grades compared to those in the bottom third (less than 173 micrograms folic acid per day for girls and 227 for boys).
Interestingly, while homocysteine levels in the blood were initially significant, this association disappeared after other significant predictors (gender, smoking, and SES) were controlled for. Neither was a genotype linked to higher homocysteine levels (MTHFR 677 TT homozygosity) significantly related to academic achievement. Low folate and B12 levels are associated with higher homocysteine levels in the blood, and there is evidence that it is this increase in homocysteine that is the reason for the cognitive impairment seen in age-related cognitive decline. This finding, then, suggests that this is only one part of the story.
Sweden does not fortify flour with folic acid as the United States, Canada and Australia do. Folate is a B vitamin found particularly in citrus fruit, green leafy vegetables, whole-wheat bread, and dried beans and peas; however, they are often destroyed by cooking or processing.
The sum of school grades in 10 core subjects obtained in the final semester of compulsory 9 years of schooling was used as the measure of academic achievement
Following animal research indicating that binge drinking damages the hippocampus, and other research showing that this learning and memory center is still developing during adolescence, a new study has investigated the effects of binge drinking on learning in university students. The study, involving 122 Spanish university students (aged 18-20), of whom half engaged in binge drinking, found a clear association between binge drinking and a lower ability to learn new verbal information.
Specifically, binge drinkers were more affected by interference in the Rey Auditory Verbal Learning Test, and remembered fewer words; they also performed worse on the Weschler Memory Scale-3rd ed. (WMS-III) Logical Memory subtest, both on immediate and delayed recall. However, there were no differences between the two groups on the WMS-III Family Pictures subtest (measuring visual declarative memory).
These results persisted even after controlling for other possible confounding variables such as intellectual levels, history of neurological or psychopathological disorders, other drug use, or family history of alcoholism.
The genders were evenly represented in both groups. Interestingly, and in contradiction of some other research, women were not found to be more vulnerable to the neurotoxic effects of binge drinking.
Binge drinking is, unfortunately, most common among adolescents (12-20 years). But this is a time when brains are still developing. Does this make them more vulnerable to the detrimental effects of excessive alcohol?
A study involving adolescent mice has revealed that not only did an alcoholic binge reduce the activity of many neurotransmitter genes, but that gene expression in adulthood was even more seriously reduced. Although this deficit didn’t translate into problems with spatial learning, adult mice that had been exposed to excess alcohol in adolescence were significantly worse on a reversal learning task. Moreover, certain brain regions (the olfactory bulb and basal forebrain) were smaller.
In humans, it is thought that these impairments might translate into greater difficulty in adapting to changed situations, in evaluating consequences and controlling impulses.
Similarly, another recent study involving teenagers (15-21) has found that activity in the prefrontal cortex varied according to how heavily they smoked, with those who smoked most heavily having the least activity.
The 25 smokers and 25 non-smokers were tested on a Stop-Signal Task, which tests a person’s ability to inhibit an action. Despite the differences in activity level, smokers and non-smokers performed similarly on the task, suggesting that other brain areas are in some way compensating for the impaired prefrontal cortex. Nevertheless, reduced activity in the prefrontal cortex, which is still developing in adolescence, does suggest long-term consequences for decision-making and cognitive control.
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 study involving 80 college students (34 men and 46 women) between the ages of 18 and 40, has found that those given a caffeinated energy drink reported feeling more stimulated and less tired than those given a decaffeinated soda or no drink. However, although reaction times were faster for those consuming caffeine than those given a placebo drink or no drink, reaction times slowed for increasing doses of caffeine, suggesting that smaller amounts of caffeine are more effective.
The three caffeine groups were given caffeine levels of either 1.8 ml/kg, 3.6 ml/kg or 5.4 ml/kg. The computerized "go/no-go" test which tested their reaction times was given half an hour after consuming the drinks.
In another study, 52 children aged 12-17 drank flattened Sprite containing caffeine at four concentrations: 0, 50 mg, 100 mg or 200 mg. Changes in blood pressure and heart rate were then checked every 10 minutes for one hour, at which point they were given a questionnaire and an opportunity to eat all they wanted of certain types of junk food.
Interestingly, there were significant gender differences, with boys drinking high-caffeine Sprite showing greater increases in diastolic blood pressure (the lower number) than boys drinking the low-caffeine Sprite, but girls being unaffected. Boys were also more inclined to report consuming caffeine for energy or “the rush”, than girls were.
Those participants who ingested the most caffeine also ate more high-sugar snack foods in the laboratory, and reported higher protein and fat consumption outside the lab.
A working memory training program developed to help children with ADHD has been tested by 52 students, aged 7 to 17. Between a quarter and a third of the children showed significant improvement in inattention, overall number of ADHD symptoms, initiation, planning/organization, and working memory, according to parental ratings. While teacher ratings were positive, they did not quite reach significance. It is worth noting that this improvement was maintained at the four-month follow-up.
The children used the software in their homes, under the supervision of their parents and the researchers. The program includes a set of 25 exercises in a computer-game format that students had to complete within 5 to 6 weeks. For example, in one exercise a robot will speak numbers in a certain order, and the student has to click on the numbers the robot spoke, on the computer screen, in the opposite order. Each session is 30 to 40 minutes long, and the exercises become progressively harder as the students improve.
The software was developed by a Swedish company called Cogmed in conjunction with the Karolinska Institute. Earlier studies in Sweden have been promising, but this is the first study in the United States, and the first to include children on medication (60% of the participants).
A study involving 48 adolescents, of whom 19 had been diagnosed with substance abuse/dependence, and 14 had a family history of substance abuse but no history of personal use, has found that greater alcohol use was associated with a significant decrease in attention and executive function (which is involved in planning and decision-making), while greater marijuana use was associated with poorer memory. Adolescents in the substance abuse group had lower scores in attention, memory, and processing speed, compared to the other groups, while those with a family history of abuse (but no personal history) had poorer visuospatial ability.
Children with autism often focus intently on a single activity or feature of their environment. A study involving 17 autistic children (6-16 years) and 17 controls has compared brain activity as they watched a silent video of their choice while tones and vibrations were presented, separately and simultaneously.
A simple stimulus takes about 20 milliseconds to arrive in the brain. When information from multiple senses registers at the same time, integration takes about 100 to 200 milliseconds in normally developing children. But those with autism took an average of 310 milliseconds to integrate the noise and vibration when they occurred together. The children with autism also showed weaker signal strength, signified by lower amplitude brainwaves.
The findings are consistent with theories that automatic sensory integration is impaired in autism, and may help explain autism’s characteristic sensitivity to excessive sensory stimulation.
Many survivors of childhood cancer experience cognitive problems as a result of their treatment. The drug methylphenidate (marketed under several names, the best known of which is Ritalin) has previously been shown to help attention problems in such survivors in the short term. Now a new study demonstrates that it can also be of benefit in the long term.
The study tested attention, social skills and behavior in survivors who had been on the drug for a year, comparing them to a similar group of unmedicated survivors. Although the drug did not lead to a significant gain in measured academic skills in math, reading and spelling, many did show improvements to attention that put them back in the normal range.
Nevertheless, the results also emphasize the need for other approaches, given that many did not benefit from the drug, and some may not be good candidates for medical or other reasons. The treatment group included 35 survivors of brain tumors and 33 of acute lymphoblastic leukemia (ALL). Any who suffered from ADHD before their cancer were excluded from the study.
Analysis of DNA and lifestyle data from a representative group of 2,500 U.S. middle- and high-school students tracked from 1994 to 2008 in the National Longitudinal Study of Adolescent Health has revealed that lower academic performance was associated with three dopamine gene variants. Having more of the dopamine gene variants (three rather than one, say) was associated with a significantly lower GPA.
Moreover, each of the dopamine genes (on its own) was linked to specific deficits: there was a marginally significant negative effect on English grades for students with a specific variant in the DAT1 gene, but no apparent effect on math, history or science; a specific variant in the DRD2 gene was correlated with a markedly negative effect on grades in all four subjects; those with the deleterious DRD4 variant had significantly lower grades in English and math, but only marginally lower grades in history and science.
Precisely why these specific genes might impact academic performance isn’t known with any surety, but they have previously been linked to such factors as adolescent delinquency, working memory, intelligence and cognitive abilities, and ADHD, among others.
Last year I reported on a study involving 210 subjects aged 7 to 31 that found that in contrast to the adult brain, most of the tightest connections in a child's brain are between brain regions that are physically close to each other. As the child grows to adulthood, the brain switches from an organization based on local networks based on physical proximity to long-distance networks based on functionality. Now the same researchers, using five-minute scans from 238 people aged 7 to 30, have looked at nearly 13,000 functional (rather than structural) connections and identified 200 key ones. On the basis of these 200 connections, the brains could be identified as belonging to a child (7-11) or an adult (25-30) with 92% accuracy, and adolescents or adults with 75% accuracy. Moreover, the most important factor in predicting development (accounting for about 68%) was the trimming of the vast number of childhood connections.
Apart from emphasizing the importance of pruning connections in brain development, the main value of this research is in establishing an effective analytic method and baseline measurements for normal development. It is hoped that this will eventually help researchers work out indicators for various developmental disorders.
A small study comparing 18 obese adolescents with type 2 diabetes and equally obese adolescents without diabetes or pre-diabetes has found that those with diabetes had significantly impaired cognitive performance, as well as clear abnormalities in the integrity of their white matter (specifically, reduced white matter volume, especially in the frontal lobe, as well as impaired integrity in both white and grey matter). Similar abnormalities have previously been found in adults with type 2 diabetes, but the subjects were elderly and, after many years of diabetes, generally had significant vascular disease. One study involving middle-aged diabetics found a reduction in the volume of the hippocampus, which was directly associated with poor glycaemic control.
It remains to be seen whether such changes can be reversed by exercise and diet interventions. While those with diabetes performed worse in all cognitive tasks tested, the differences were only significant for intellectual functioning, verbal memory and psychomotor efficiency.
Analysis of 30 years of SAT and ACT tests administered to the top 5% of U.S. 7th graders has found that the ratio of 7th graders scoring 700 or above on the SAT-math has dropped from about 13 boys to 1 girl to about 4 boys to 1 girl. The ratio dropped dramatically between 1981 and 1995, and has remained relatively stable since then. The top scores on scientific reasoning, a relatively new section of the ACT that was not included in the original study, show a similar ratio of boys to girls.
A study involving 163 overweight children and adolescents aged 10 to 17 has revealed that moderate to severe obstructive sleep apnea was linked to both lower academic grades and behavioral concerns. None of the students with moderate to severe OSA had an "A" average, and 30% had a "C" average or lower. In contrast, roughly 15% of those without sleep-disordered breathing had an "A" average, and only about 15% had a "C" average or lower. The results remained significant after adjustment for sex, race, socioeconomic status and sleep duration on school nights. OSA was particularly associated with inattention and poor study skills in real-world situations Forty-two students had moderate to severe OSA; 58 had mild OSA; 26 students were snorers; 37 had no sleep-disordered breathing.
Beebe, D.W. et al. 2010. The association between sleep-disordered breathing, academic grades, and neurobehavioral functioning among overweight subjects during middle to late childhood. Presented at SLEEP 2010, the 24th annual meeting of the Associated Professional Sleep Societies LLC, in San Antonio, Texas.
A large longitudinal study, comparing physical activity at teenage, age 30, age 50, and late life against cognition of 9,344 women, has revealed that women who are physically active at any point have a lower risk of cognitive impairment in late-life compared to those who are inactive, but teenage physical activity is the most important. When age, education, marital status, diabetes, hypertension, depressive symptoms, smoking, and BMI were accounted for, only teenage physical activity status remained significantly associated with cognitive performance in old age. Although becoming active later in life didn’t make up for being inactive in adolescence, it did significantly reduce the risk of cognitive impairment compared to those who remained physically inactive. The findings are a strong argument for greater effort in increasing physical activity in today's youth.
A study involving 629 12th-grade students from three Los Angeles-area high schools has revealed that, across both genders and all ethnicities, adolescents with more in-school friends, compared with out-of-school friends, had higher grade point averages. It’s assumed that this is due to the fact that in-school friends are more likely to support school-related activities, including studying.
A national Swedish study involving the 1.16 million children in a national birth cohort identified nearly 8000 on the country's Prescribed Drug Register as using a prescription for ADHD medication (and thus assumed to suffer from severe ADHD). These children were significantly more likely to come from a family on welfare benefits (135% more likely), to have a mother with only the most basic education (130% more likely than those with mothers with university degrees), and to come from a single parent family (54% more likely). Boys were three times more likely to be on ADHD medication than girls, with medication use highest in boys aged between 10 and 15. The finding that family adversity is such a strong risk factor points to the need for more research into the role of environment
Data from the same long-running study (the NICHD Study of Early Child Care and Youth Development), this time involving 1,364 youth (followed since birth), found that teens who had spent the most hours in non-relative child care in their first 4½ years reported a slightly greater tendency toward impulsiveness and risk-taking at 15 than did peers who spent less time in child care (21% were in care for more than 30 hours a week; 24% had had more than one year of care by 4 ½). But it was the quality of child care that made the difference as far as cognitive and academic performance was concerned. Those who had higher quality child care had better results on cognitive and academic assessments at both age 4½ and age 15. High-quality care was characterized by the caregivers' warmth, support, and cognitive stimulation of the children under their care. More than 40% of the children experienced high-quality (17%) or moderately high-quality (24%) care. The findings were consistent across gender and socioeconomic status. Previous research has tended to focus on the effects of child care on disadvantaged children; this one is notable for involving children across society. The study is important not only for pointing to the effects of childcare quality, but for the finding that the effect continues into adolescence.
It is well known that the onset of puberty marks the end of the optimal period for learning language and certain spatial skills, such as computer/video game operation. A mouse study has now revealed that this is connected to an increase in a specific brain receptor (named Alpha4-Beta-Delta GABA-A). However, the learning deficit could be reversed by application of a stress steroid (THP). Although this natural hormone acts on adults like a tranquilizer, in adolescents it has a stimulation effect. The findings suggest that mild stress may be useful to improve learning in adolescents.
Although we initially tend to pay attention to obvious features such as hair, it has been long established that familiar faces are recognized better from their inner (eyes, nose, mouth) rather than their outer (hair, hairline, jaw, ears) parts1. Studies have shown that this advantage of inner features does not occur in children until they’re around 10—11 years old. Children younger than this tend to use outer features to recognize people they know2.
Studies investigating the inner-face advantage have used photographs in which parts of faces have been cropped. This may be confusing to young children. It was thought that inner-face processing would be facilitated if blurring was used instead. Accordingly, in this study photographs in which either the inner face or the outer features are blurred were used.
Although it was thought that this would encourage inner-face processing, children seemed to find it harder. Extending the experiment to adolescents, it was found that the inner-face advantage typical of adults, did not appear until 14—15 years of age. A further experiment with learning-disabled adolescents, with a mental age of 5—8 years, found no shift to inner-face processing. This suggests that the shift to inner-face processing is a developmental change, rather than simply reflecting a need to gain sufficient experience in face-processing.
1. Ellis, H.D., Shepherd, J.W. & Davies, G.M. 1979. Identification of familiar and unfamiliar faces from internal and external features: Some implications for theories of face recognition. Perception, 8, 431-439.
2. Campbell, R. & Tuck, M. 1995. Children’s recognition of inner and outer face-features of famous faces. Perception, 24, 451-456.
Campbell, R., Walker, J. & Baron-Cohen, S. 1995. The use of internal and external face features in the development of familiar face identification. Journal of Experimental Child Psychology, 59, 196-210.
Campbell, Ruth, Coleman, Michael, Walker, Jane, Benson, Philip J., Wallace, Simon, Michelotti, Joanne & Baron-Cohen, Simon. 1999. When does the inner-face advantage in familiar face recognition arise and why? Visual Cognition, 6(2), 197-216.
Seventh graders given 20 mg zinc, five days per week, for 10 to 12 weeks showed improvement in cognitive performance, responding more quickly and accurately on memory tasks and with more sustained attention, than classmates who received no additional zinc. Those who received only 10mg a day did not improve their performance. Previous studies have linked zinc nutrition to motor, cognitive and psychosocial function in very young children and adults, but this is the first study of its effect in adolescents. Adolescents are at particular risk of zinc deficiency, because they are undergoing rapid growth and often have poor eating habits. Red meats, fish and grains are good sources of zinc.
The findings were presented at Experimental Biology 2005, as part of the scientific sessions of the American Society of Nutritional Sciences.
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.
Amphetamine use in adolescence may impair adult working memory
Rats exposed to high doses of amphetamines at an age that corresponds to the later years of human adolescence showed significant declines in working memory as adults, long after the exposure. The researchers tested two types of amphetamine exposure: intermittent (a steady dose every other day) and "binge-escalation," in which increasing amounts of the drug were given over a period of four days, followed by a simulated binge – a high dose every two hours for eight hours on the fifth day. The type of exposure did not make a significant difference.
Stanis, J.J. et al. 2009. Amphetamine-induced deficits in a working memory task are more significant in drug-exposed adolescent rats than drug-exposed adults. Presented October 21 at the annual meeting of the Society for Neuroscience in Chicago.
Linking education to future goals may boost grades more than helping with homework
A review of 50 studies looking at what kinds of parent involvement helps children's academic achievement has revealed that the most important thing parents can do for their middle school children (early adolescence) is relate academic achievement to future job goals, and give advice on specific study strategies. Parents' involvement in school events also had a positive effect, but a smaller one. Helping with homework had mixed results.
Hill, N.E. & Tyson, D.F. 2009. Parental Involvement in Middle School: A Meta-Analytic Assessment of the Strategies That Promote Achievement. Developmental Psychology, 45 (3), 740-763.
Adolescent binge drinking may compromise white matter
An imaging study of 28 teens, of whom half had a history of binge drinking (but did not meet the criteria for alcohol abuse), has found that those who had engaged in binge drinking episodes had lower coherence of white matter fibers in 18 different areas across the brain. The findings add to a growing literature indicating that adolescent alcohol involvement is associated with specific brain characteristics. White matter integrity is essential to the efficient relay of information in the brain.
Childhood sleep problems persisting through adolescence may affect cognitive abilities
A longitudinal study involving 916 twins whose parents reported their children's sleep problems from age 4 until 16, of whom 568 completed tests of executive functioning at 17, indicates that those whose sleep problems persisted through adolescence had poorer executive functioning at age 17 than children whose problems decreased to a greater extent. Sleep problems as early as age 9, but particularly around age 13, showed significant associations with later executive functions. Some problems appear to be more important than others: changes in levels of 'sleeping more than other children' and 'being overtired' were most important, and nightmares and 'trouble sleeping' the least. However, a child's level of sleep problems early in life don’t appear to be an important factor.
From 12 years onward you learn differently
Behavioral studies have found eight-year-olds learn primarily from positive feedback, with negative feedback having little effect. Twelve-year-olds, however, are better able to process negative feedback, and use it to learn from their mistakes. Now brain imaging reveals that the brain regions responsible for cognitive control (specifically, the dorsolateral prefrontal cortex and superior parietal cortex, and the pre-supplementary motor area/anterior cingulate cortex) react strongly to positive feedback and scarcely respond at all to negative feedback in children of eight and nine, but the opposite is the case in children of 11 to 13 years, and also in adults.
van Duijvenvoorde, A.C.K. et al. 2008. Evaluating the Negative or Valuing the Positive? Neural Mechanisms Supporting Feedback-Based Learning across Development. The Journal of Neuroscience, 28, 9495-9503.
Frequent TV viewing during adolescence linked with risk of attention and learning difficulties
A long-running study of 678 families in upstate New York, surveyed children at 14, 16 and 22 years old (averages), and again when the children in the study had reached an average age of 33. At age 14, 225 (33.2%) of the teens reported that they watched three or more hours of television per day. Those who watched 1 or more hours of television per day at mean age 14 years were at higher risk of poor homework completion, negative attitudes toward school, poor grades, and long-term academic failure. Those who watched 3 or more hours of television per day were most likely to experience these outcomes, and moreover were at higher risk of subsequent attention problems and were the least likely to receive postsecondary education. Analysis of the data also indicated that television watching contributes to learning difficulties and not vice versa.
Johnson, J.G., Cohen, P., Kasen, S. & Brook, J.S. 2007. Extensive Television Viewing and the Development of Attention and Learning Difficulties During Adolescence. Archives of Pediatrics & Adolescent Medicine, 161 (5), 480-486.
Prefrontal cortex loses neurons during adolescence
A rat study has found that adolescents lose neurons in the ventral prefrontal cortex in adolescence, with females losing about 13% more neurons than males. Human studies have found gradual reductions in the volume of gray matter in the prefrontal cortex from adolescence to adulthood, but this finding that neurons are actually dying is new, and indicates that the brain reorganizes in a very fundamental way in adolescence. The number of neurons in the dorsal prefrontal cortex didn’t change, although the number of glial cells increased there (while remaining stable in the ventral area). The finding could have implications for understanding disorders that often arise in late adolescence, such as schizophrenia and depression, and why addictions that start in adolescence are harder to overcome than those that begin in adulthood.
Markham, J.A., Morris, J.R. & Juraska, J.M. 2007. Neuron number decreases in the rat ventral, but not dorsal, medial prefrontal cortex between adolescence and adulthood. Neuroscience, 144 (3), 961-968.
Brain still developing at age 18
In a study of 19 freshman college students, it’s been found that, anatomically, significant changes in brain structure continue after age 18. The changes were localized to regions of the brain known to integrate emotion and cognition — specifically, areas that take information from our current body state and apply it for use in navigating the world (right midcingulate, inferior anterior cingulate gyrus, right caudate head, right posterior insula, and bilateral claustrum).
Bennett, C.M. & Baird, A.A. 2006. Anatomical changes in the emerging adult brain: A voxel-based morphometry study. Human Brain Mapping, Article published online 29 Nov 2005 in advance of print./span>
Study links adolescent IQ/activity levels with risk of dementia
An analysis of high school records and yearbooks from the mid-1940s, and interviews with some 400 of these graduates, now in their 70s, and their family members, has found that those who were more active in high school and who had higher IQ scores, were less likely to have mild memory and thinking problems and dementia as older adults.
Fritsch, T., Smyth, K.A., McClendon, M.J., Ogrocki, P.K., Santillan, C., Larsen, J.D. & Strauss, M.E. 2005. Associations Between Dementia/Mild Cognitive Impairment and Cognitive Performance and Activity Levels in Youth. Journal of the American Geriatrics Society, 53(7), 1191.
Teen's ability to multi-task develops late in adolescence
A study involving adolescents between 9 and 20 years old has found that the ability to multi-task continues to develop through adolescence. The ability to use recall-guided action to remember single pieces of spatial information (such as looking at the location of a dot on a computer screen, then, after a delay, indicating where the dot had been) developed until ages 11 to 12, while the ability to remember multiple units of information in the correct sequence developed until ages 13 to 15. Tasks in which participants had to search for hidden items in a manner requiring a high level of multi-tasking and strategic thinking continued to develop until ages 16 to 17. "These findings have important implications for parents and teachers who might expect too much in the way of strategic or self-organized thinking, especially from older teenagers."
The best way to get teens to learn
A recent study has been investigating how to motivate teenagers to learn. Using obese and non-obese early adolescents and a text on health-related issues, researchers found that telling the teenagers that learning more about these issues and adopting a healthier lifestyle was important for their health (an intrinsic goal) was more effective than telling them that it would help them become more physically attractive and appealing (an extrinsic goal). They also found that trying to pressure the teens by using guilt-inducing language was less effective than a more autonomy-supportive approach that enabled them to experience their studying as more self-chosen and volitional.
Vansteenkiste, M., Simons, J., Lens, W., Soenens, B. & Matos, L. 2005. Examining The Impact Of Extrinsic Vs. Intrinsic Goal Framing And Internally Controlling Vs. Autonomy-Supportive Communication Style Upon Children's Achievement. Child Development, 76 (2), 483-501.
Smoking associated with working memory impairment in adolescents
A study of 41 adolescent daily smokers and 32 nonsmokers has revealed that adolescent smokers had impairments in accuracy of working memory performance. Male adolescents as a group begin smoking at an earlier age than female smokers and were significantly more impaired during tests of selective and divided attention. All of the adolescent smokers also showed further disruption of working memory when they stopped smoking.
Alcohol's damaging effects on adolescent brain function
A number of speakers at Symposium speakers at the June 2004 Research Society on Alcoholism meeting in Vancouver, reported on research concerning the vulnerability of the adolescent brain to the damaging effects of alcohol. Some of the findings presented were:
- The adolescent brain is more vulnerable than the adult brain to disruption from activities such as binge drinking. Adolescent rats that were exposed to binge drinking appear to have permanent damage in their adult brains.
- Subtle but important brain changes occur among adolescents with Alcohol Use Disorder, resulting in a decreased ability in problem solving, verbal and non-verbal retrieval, visuospatial skills, and working memory.
- The association between antisocial behavior during adolescence and alcoholism may be explained by abnormalities in the frontal limbic system, which appears to cause "blunted emotional reactivity".
- Alcohol-induced memory impairments, such as "blackouts", are particularly common among young drinkers and may be at least in part due to disrupted neural plasticity in the hippocampus, which is centrally involved in the formation of autobiographical memories.
Changes in the brain during adolescence
A study of the post-mortem cerebral cortexes of six 12- to 17-year-olds and five 17- to 24-year-olds has revealed a number of physical differences between the adolescent and the adult brain. The average pyramidal soma size was 15.5 % smaller in the older age group, while a number of other measures (including cortical thickness and neural density) were slightly larger. These changes are thought to reflect certain cognitive changes that occur during adolescence - specifically, the increase in knowledge and understanding, and the decrease in the ability to acquire new sounds and speech patterns.
Courten-Myers, G.M. 2002. Paper presented at the American Academy of Neurology 54th Annual Meeting in Denver, Colorado, on April 19.