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

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

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

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

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

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

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

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

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

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

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

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

The study involved 74 non-smokers with amnestic MCI (average age 76), of whom half were given a nicotine patch of 15 mg a day for six months and half received a placebo. Cognitive tests were given at the start of the study and again after three and six months.

After 6 months of treatment, the nicotine-treated group showed significant improvement in attention, memory, speed of processing and consistency of processing. For example, the nicotine-treated group regained 46% of normal performance for age on long-term memory, whereas the placebo group worsened by 26%.

Nicotine is an interesting drug, in that, while predominantly harmful, it can have positive effects if the dose is just right, and if the person’s cognitive state is at a particular level (slipping below their normal state, but not too far below). Too much nicotine will make things worse, so it’s important not to self-medicate.

Nicotine has been shown to improve cognitive performance in smokers who have stopped smoking and previous short-term studies with nicotine have shown attention and memory improvement in people with Alzheimer's disease. Nicotine receptors in the brain are reduced in Alzheimer’s brains.

Because the dose is so crucial, and the effects so dependent on brain state (including, one assumes, whether the person has been a smoker or not), more research is needed before this can be used as a treatment.

We know that physical exercise greatly helps you prevent cognitive decline with aging. We know that mental stimulation also helps you prevent age-related cognitive decline. So it was only a matter of time before someone came up with a way of combining the two. A new study found that older adults improved executive function more by participating in virtual reality-enhanced exercise ("exergames") that combine physical exercise with computer-simulated environments and interactive videogame features, compared to the same exercise without the enhancements.

The Cybercycle Study involved 79 older adults (aged 58-99) from independent living facilities with indoor access to a stationary exercise bike. Of the 79, 63 participants completed the three-month study, meaning that they achieved at least 25 rides during the three months.

Unfortunately, randomization was not as good as it should have been — although the researchers planned to randomize on an individual basis, various technical problems led them to randomize on a site basis (there were eight sites), with the result that the cybercycle group and the control bike group were significantly different in age and education. Although the researchers took this into account in the analysis, that is not the same as having groups that match in these all-important variables. However, at least the variables went in opposite directions: while the cybercycle group was significantly younger (average 75.7 vs 81.6 years), it was significantly less educated (average 12.6 vs 14.8 years).

Perhaps also partly off-setting the age advantage, the cybercycle group was in poorer shape than the control group (higher BMI, glucose levels, lower physical activity level, etc), although these differences weren’t statistically significant. IQ was also lower for the cybercycle group, if not significantly so (but note the high averages for both groups: 117.6 vs 120.6). One of the three tests of executive function, Color Trails, also showed a marked group difference, but the large variability in scores meant that this difference was not statistically significant.

Although participants were screened for disorders such as Alzheimer’s and Parkinson’s, and functional disability, many of both groups were assessed as having MCI — 16 of the 38 in the cybercycle group and 14 of the 41 in the control bike group.

Participants were given cognitive tests at enrolment, one month later (before the intervention began), and after the intervention ended. The stationary bikes were identical for both groups, except the experimental bike was equipped with a virtual reality display. Cybercycle participants experienced 3D tours and raced against a "ghost rider," an avatar based on their last best ride.

The hypothesis was that cybercycling would particularly benefit executive function, and this was borne out. Executive function (measured by the Color Trails, Stroop test, and Digits Backward) improved significantly more in the cybercycle condition, and indeed was the only cognitive task to do so (other cognitive tests included verbal fluency, verbal memory, visuospatial skill, motor function). Indeed, the control group, despite getting the same amount of exercise, got worse at the Digits Backward test, and failed to show any improvement on the Stroop test.

Moreover, significantly fewer cybercyclists progressed to MCI compared to the control group (three vs nine).

There were no differences in exercise quantity or quality between the two groups — which does argue against the idea that cyber-enhanced physical activity would be more motivating. However, the cybercycling group did tend to comment on their enjoyment of the exercise. While the enjoyment may not have translated into increased activity in this situation, it may well do so in a longer, less directed intervention — i.e. real life.

It should also be remembered that the intervention was relatively short, and that other cognitive tasks might take longer to show improvement than the more sensitive executive function. This is supported by the fact that levels of the brain growth factor BDNF, assessed in 30 participants, showed a significantly greater increase of BDNF in cybercyclists.

I should also emphasize that the level of physical exercise really wasn't that great, but nevertheless the size of the cybercycle's effect on executive function was greater than usually produced by aerobic exercise (a medium effect rather than a small one).

The idea that activities that combine physical and mental exercise are of greater cognitive benefit than the sum of benefits from each type of exercise on its own is not inconsistent with previous research, and in keeping with evidence from animal studies that physical exercise and mental stimulation help the brain via different mechanisms. Moreover, I have an idea that enjoyment (in itself, not as a proxy for motivation) may be a factor in the cognitive benefits derived from activities, whether physical or mental. Mere speculation, derived from two quite separate areas of research: the idea of “flow” / “being in the zone”, and the idea that humor has physiological benefits.

Of course, as discussed, this study has a number of methodological issues that limit its findings, but hopefully it will be the beginning of an interesting line of research.  

The study involved 104 healthy older adults (average age 87) participating in the Oregon Brain Aging Study. Analysis of the nutrient biomarkers in their blood revealed that those with diets high in omega 3 fatty acids and in vitamins C, D, E and the B vitamins had higher scores on cognitive tests than people with diets low in those nutrients, while those with diets high in trans fats were more likely to score more poorly on cognitive tests.

These were dose-dependent, with each standard deviation increase in the vitamin BCDE score ssociated with a 0.28 SD increase in global cognitive score, and each SD increase in the trans fat score associated with a 0.30 SD decrease in global cognitive score.

Trans fats are primarily found in packaged, fast, fried and frozen food, baked goods and margarine spreads.

Brain scans of 42 of the participants found that those with diets high in vitamins BCDE and omega 3 fatty acids were also less likely to have the brain shrinkage associated with Alzheimer's, while those with high trans fats were more likely to show such brain atrophy.

Those with higher omega-3 scores also had fewer white matter hyperintensities. However, this association became weaker once depression and hypertension were taken into account.

Overall, the participants had good nutritional status, but 7% were deficient in vitamin B12 (I’m surprised it’s so low, but bear in mind that these are already a select group, being healthy at such an advanced age) and 25% were deficient in vitamin D.

The nutrient biomarkers accounted for 17% of the variation in cognitive performance, while age, education, APOE genotype (presence or absence of the ‘Alzheimer’s gene’), depression and high blood pressure together accounted for 46%. Diet was more important for brain atrophy: here, the nutrient biomarkers accounted for 37% of the variation, while the other factors accounted for 40% (meaning that diet was nearly as important as all these other factors combined!).

The findings add to the growing evidence that diet has a significant role in determining whether or not, and when, you develop Alzheimer’s disease.

A study involving 159 older adults (average age 76) has confirmed that the amount of brain tissue in specific regions is a predictor of Alzheimer’s disease development. Of the 159 people, 19 were classified as at high risk on the basis of the smaller size of nine small regions previously shown to be vulnerable to Alzheimer's), and 24 as low risk. The regions, in order of importance, are the medial temporal, inferior temporal, temporal pole, angular gyrus, superior parietal, superior frontal, inferior frontal cortex, supramarginal gyrus, precuneus.

There was no difference between the three risk groups at the beginning of the study on global cognitive measures (MMSE; Alzheimer’s Disease Assessment Scale—cognitive subscale; Clinical Dementia Rating—sum of boxes), or in episodic memory. The high-risk group did perform significantly more slowly on the Trail-making test part B, with similar trends on the Digit Symbol and Verbal Fluency tests.

After three years, 125 participants were re-tested. Nine met the criteria for cognitive decline. Of these, 21% were from the small high-risk group (3/14) and 7% from the much larger average-risk group (6/90). None were from the low-risk group.

The results were even more marked when less stringent criteria were used. On the basis of an increase on the Clinical Dementia Rating, 28.5% of the high-risk group and 9.7% of the average-risk group showed decline. On the basis of declining at least one standard deviation on any one of the three neuropsychological tests, half the high-risk group, 35% of the average risk group, and 14% (3/21) of the low-risk group showed decline. (The composite criteria required both of these criteria.)

Analysis estimated that every standard deviation of cortical thinning (reduced brain tissue) was associated with a nearly tripled risk of cognitive decline.

The 84 individuals for whom amyloid-beta levels in the cerebrospinal fluid were available also revealed that 60% of the high-risk group had levels consistent with the presence of Alzheimer's pathology, compared to 36% of those at average risk and 19% of those at low risk.

The findings extend and confirm the evidence that brain atrophy in specific regions is a biomarker for developing Alzheimer’s.