Previous research has been equivocal about whether cognitive training helps cognitively healthy older adults. One recent review concluded that cognitive training could help slow age-related decline in a range of cognitive tasks; another found no evidence that such training helps slow or prevent the development of Alzheimer’s in healthy older adults. Most of the studies reviewed looked at single-domain training only: memory, reasoning, processing speed, reading, solving arithmetic problems, or strategy training (1). As we know from other studies, training in specific tasks is undeniably helpful for improving your performance at those specific tasks. However, there is little evidence for wider transfer. There have been few studies employing multi-domain training, although two such have found positive benefits.

In a new Chinese study, 270 healthy older adults (65-75) were randomly assigned to one of three groups. In the two experimental groups, participants were given one-hour training sessions twice a week for 12 weeks. Training took place in small groups of around 15. The first 15 minutes of each hour involved a lecture focusing on diseases common in older adults. The next 30 minutes were spent in instruction in one specific technique and how to use it in real life. The last 15 minutes were used to consolidate the skills by solving real-life problems.

One group were trained using a multi-domain approach, involving memory, reasoning, problem solving, map reading, handicrafts, health education and exercise. The other group trained on reasoning only (involving the towers of Hanoi, numerical reasoning, Raven Progressive Matrices, and verbal reasoning). Homework was assigned. Six months after training, three booster sessions (a month apart) were offered to 60% of the participants. The third group (the control) was put on a waiting list. All three groups attended a lecture on aspects of healthy living every two months.

All participants were given cognitive tests before training and after training, and again after 6 months, and after one year. Cognitive function was assessed using the Stroop Test, the Trail Making test, the Visual Reasoning test, and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS, Form A).

Both the multi-domain and single-domain cognitive training produced significant improvement in cognitive scores (the former in RBANS, visual reasoning, and immediate and delayed memory; the latter in RBANS, visual reasoning, word interference, and visuospatial/constructional score), although single-domain training produced less durable benefits (after a year, the multi-domain group still showed the benefit in RBANS, delayed memory and visual reasoning, while the single-domain group only showed benefits in word interference). Booster training also produced benefits, consolidating training in reasoning, visuospatial/constructional abilities and faster processing.

Reasoning ability seemed particularly responsive to training. Although it would be reasonable to assume that single-domain training, which focused on reasoning, would produce greater improvement than multi-domain training in this specific area, there was in fact no difference between the two groups right after training or at six months. And at 12 months, the multi-domain group was clearly superior.

In sum, the study provides evidence that cognitive training helps prevent cognitive decline in healthy older people, that specific training can generalize to other tasks, but that programs that involve several cognitive domains produce more lasting benefits.

A study involving 86 older women (aged 70-80) with probable MCI has compared the effectiveness of resistance and aerobic training in improving executive function. The women were randomly allocated either to resistance training, aerobic training, or balance and tone training (control group). The programs all ran twice weekly for six months.

The 60-minute classes involved lifting weights (resistance training), outdoor walking (aerobic training), or stretching, balancing, and relaxation exercises (control).

Executive function was primarily assessed by the Stroop Test (measuring selective attention/conflict resolution), and also by Trail Making Tests (set-shifting) and Verbal Digits Tests (working memory). Associative memory (face-scene pairs) and problem-solving ability (Everyday Problems Test) were also assessed.

The study found that resistance training significantly improved performance on the Stroop Test and also the associative memory task. These improvements were associated with changes in some brain regions. In contrast to previous studies in healthy older adults, aerobic training didn’t produce any significant cognitive improvement, although it did produce significantly better balance and mobility, and cardiovascular capacity, compared to the control.

Interestingly, a previous study from these researchers demonstrated that it took a year of resistance training to achieve such results in cognitively healthy women aged 65-75. This suggests that the benefits may be greater for those at greater risk.

It may be that the greater benefits of resistance training over aerobic training are not be solely due to physical differences in the exercise. The researchers point out that resistance training required more cognitive engagement (“If you’re lifting weights you have to monitor your sets, your reps, you use weight machines and you have to adjust the seat, etc.”) compared to walking.

Note that impaired associative memory is one of the earliest cognitive functions affected in Alzheimer’s.

It’s also worth noting that exercise compliance was low (55-60%), suggesting that benefits might have been greater if the participants had been more motivated — or found the programs more enjoyable! The failure of aerobic exercise to improve cognition is somewhat surprising, and perhaps it, too, may be attributed to insufficient engagement — in terms of intensity as well as amount.

The researchers have put up a YouTube video of the resistance training exercises used in the study.

Over the years, I have reported on several studies that have found evidence that colorful berries — blueberries in particular (but I think that’s more of an artifact, due to the relative cheapness of these berries in North America) — benefit older brains. Indeed, I myself consume these every day (in my lunch smoothie) for this very reason (of course, the fact that they taste so good doesn’t hurt!).

But to date these studies have involved rodents or only very small numbers of humans. Now a new study analyzes data from the very large and long-running Nurses' Health Study, which has questioned 121,700 female, registered nurses about their health and lifestyle since 1976. Since 1980, participants were also asked about their frequency of food consumption. Between 1995 and 2001, memory was measured in 16,010 participants over the age of 70 years (average age 74), at 2-year intervals.

The study found that those women who had 2 or more servings of strawberries and blueberries every week had a slower rate of cognitive decline. The effects were equivalent to some 1.5-2.5 years of normal cognitive aging.

While the researchers cannot completely rule out the possibility that higher berry consumption is associated with slower cognitive decline because of its association with some other factor that affects brain aging, they did take into account a large number of potentially confounding factors, including: education, smoking history and status, antidepressant use, BMI, blood pressure, cholesterol, diabetes, physical activity, total calorie intake, fish consumption, alcohol use, overall diet scores, and various indirect measures of socioeconomic status.

Moreover, the findings are both consistent with both animal and cell studies, and with what we know about how the brain ages. The ‘magic’ ingredient of these berries is thought to lie in their flavonoids (particularly anthocyanidins), which have powerful antioxidant and anti-inflammatory properties. It’s thought that berries help the brain stay healthy both because they contain high levels of antioxidants, which protect cells from damage by harmful free radicals, and because they change the way neurons in the brain communicate, protecting against inflammation and oxidative stress.

As a rule of thumb, the deeper the color of the berry (or other fruit or vegetable), the more flavonoids it has. You can see a list of anthocyanin-rich foods here (acai isn’t in the list, but it also has a very high rating).

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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