Strategies

I recently reported on a finding that older adults whose life-space narrowed to their immediate home were significantly more likely to have a faster rate of global cognitive decline or develop mild cognitive impairment or Alzheimer’s.

Now there are some obvious correlates of being house-bound vs feeling able to travel out of town (such as physical disability), but this relationship between cognitive decline and confined life-space remained after such factors were taken into account. The association is thought to be related to social and mental stimulation.

But I think this association also points to something more specific: the importance of distance, and difference. Different ways of thinking; different contexts. Information (in the broadest sense of the word) that stretches your mind, that gets you out of the grooves of your familiar thoughts.

Last year I reported on a study looking at creativity in problem-solving. That study found that multicultural experiences help you become more creative in solving problems. In particular, creativity was best helped by being reminded of what you’d learned about the underlying meaning or function of behaviors in the multicultural context. In other words, what was important was truly trying to understand behavior that’s very different from your own.

While travelling undoubtedly helps, you don’t need to go to a distant place to learn about different cultures. You can read about them; you can watch movies; you can listen to other people talk about what they know. And if you have those experiences, you can then think about them at any time.

A vital tool in tackling cognitive decline in old age (including the more extreme events of mild cognitive impairment and dementia) is cognitive reserve. Cognitive reserve means that your brain can take more damage before it has noticeable effects. Many people have died with advanced Alzheimer’s pathology in their brain who showed no signs of dementia in life!

Cognitive reserve is most often associated with education, but it is also associated with occupation, bilingualism, and perhaps even music. What it comes down to is this: the more redundancy in your brain, the wider and denser the networks, the more able your brain will be to find new paths for old actions, if the old paths are damaged.

The finding that life-space can affect cognitive decline is also a reminder that we are minds in bodies. I have reported on a number of examples of what is called embodied cognition (the benefits of gesture for memory are one example of this). It’s a good general principle to bear in mind — if you fake enjoyment, you may well come to feel it; if you look at the distant hills or over the sea, your mind may think distant thoughts; if you write out your worries, the weight of them on your mind may well lighten.

I made reference to bilingualism. There have been several studies now, that point to the long-term benefits of bilingualism for fighting cognitive decline and dementia. But if you are monolingual, don’t despair. You may never achieve the fluency with another language that you would have if you’d learned it earlier in life, but it’s never too late to gain some benefit! If you feel that learning a new language is beyond you, then you’re thinking of it in the wrong way.

Learning a language is not an either-or task; you don’t have to achieve near-native fluency for there to be a point. If there’s a language you’ve always yearned to know, or a culture you’ve always been interested in, dabble. There are so many resources on the Web nowadays; there has never been a better time to learn a language! You could dabble in a language because you’re interested in a culture, or you could enhance your language learning by learning a little about an associated culture.

And don’t forget that music and math are languages too. It may be too late to become a cello virtuoso, but it’s never too late to learn a musical instrument for your own pleasure. Or if that’s not to your taste, take a music appreciation class, and enrich your understanding of the language of music.

Similarly with math: there’s a thriving little world of “math for fun” out there. Go beyond Sudoku to the world of math puzzles and games and quirky facts.

Perhaps even dance should be included in this. I have heard dance described as a language, and there has been some suggestion that dancing seems to be a physical pursuit of particular cognitive benefit for older adults.

This is not simply about ‘stimulation’. It’s about making new and flexible networks. Remember my recent report on learning speed and flexible networks? The fastest learners were those whose brains showed more flexibility during learning, with different areas of the brain being linked with different regions at different times. The key to that, I suggest, is learning and thinking about things that require your brain to forge many new paths, with speed and distance being positive attributes that you should seek out (music and dance for speed, perhaps; languages and travel for distance).

Interestingly, research into brain development has found that, as a 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. It would be interesting to know if seniors with cognitive impairment show a shrinking in their networks. Research has shown that the aging brain does tend to show reduced functional connectivity in certain high-level networks, and this connectivity can be improved with regular aerobic exercise, leading to cognitive improvement.

Don’t disdain the benefits of simply daydreaming in your armchair! Daydreaming has been found to activate areas of the brain associated with complex problem-solving, and it’s been speculated that mind wandering evokes a unique mental state that allows otherwise opposing networks to work in cooperation. Daydreaming about a more distant place has also been found to impair memory for recently learned words more than if the daydreaming concerned a closer place — a context effect that demonstrates that you can create distance effects in the privacy of your own mind, without having to venture to distant lands.

I’m not saying that such daydreaming has all the benefits of actually going forth and meeting people, seeing new sights. Watching someone practice helps you learn a skill, but it’s not as good as practicing yourself. But the point is, whatever your circumstances, there is plenty you can do to stretch your mind. Why not find yourself a travel book, and get started!

Humans are the animals that manipulate their cognitive environment.

I reported recently on an intriguing study involving an African people, the Himba. The study found that the Himba, while displaying an admirable amount of focus (in a visual perception task) if they were living a traditional life, showed the same, more de-focused, distractible attention, once they moved to town. On the other hand, digit span (a measure of working memory capacity) was smaller in the traditional Himba than it was in the urbanized Himba.

This is fascinating, because working memory capacity has proved remarkably resistant to training. Yes, we can improve performance on specific tasks, but it has proven more difficult to improve the general, more fundamental, working memory capacity.

However, there have been two areas where more success has been found. One is the area of ADHD, where training has appeared to be more successful. The other is an area no one thinks of in this connection, because no one thinks of it in terms of training, but rather in terms of development — the increase in WMC with age. So, for example, average WMC increases from 4 chunks at age 4, to 5 at age 7, 6 at age 10, to 7 at age 16. It starts to decrease again in old age. (Readers familiar with my work will note that these numbers are higher than the numbers we now tend to quote for WMC — these numbers reflect the ‘magic number 7’, i.e. the number of chunks we can hold when we are given the opportunity to actively maintain them.)

Relatedly, there is the Flynn effect. The Flynn effect is ostensibly about IQ (specifically, the rise in average IQ over time), but IQ has a large WM component. Having said that, when you break IQ tests into their sub-components and look at their change over time, you find that the Digit Span subtest is one component that has made almost no gain since 1972.

But of course 1972 is still very modern! There is no doubt that there are severe constraints on how much WMC can increase, so it’s reasonable to assume we long since hit the ceiling (speaking of urbanized Western society as a group, not individuals).

It’s also reasonable to assume that WMC is affected by purely physiological factors involving connectivity, processing speed and white matter integrity — hence at least some of the age effect. But does it account for all of it?

What the Himba study suggests (and I do acknowledge that we need more and extended studies before taking these results as gospel), is that urbanization provides an environment that encourages us to use our working memory to its capacity. Urbanization provides a cognitively challenging environment. Our focus is diffused for that same reason — new information is the norm, rather than the exception; we cannot focus on one bit unless it is of such threat or interest that it justifies the risk.

ADHD shows us, perhaps, what can happen when this process is taken to the extreme. So we might take these three groups (traditional Himba, urbanized Himba, individuals with ADHD) as points on the same continuum. The continuum reflects degree of focus, and the groups reflect environmental effects. This is not to say that there are not physiological factors predisposing some individuals to react in such a way to the environment! But the putative effects of training on ADHD individuals points, surely, to the influence of the environment.

Age provides an intriguing paradox, because as we get older, two things tend to happen: we have a much wider knowledge base, meaning that less information is new, and we usually shrink our environment, meaning again that less information is new. All things being equal, you would think that would mean our focus could afford to draw in. However, as my attentive readers will know, declining cognitive capacity in old age is marked by increasing difficulties in ignoring distraction. In other words, it’s the urbanization effect writ larger.

How to account for this paradox?

Perhaps it simply reflects the fact that the modern environment is so cognitively demanding that these factors aren’t sufficient on their own to enable us to relax our alertness and tighten our focus, in the face of the slowdown in processing speed that typically occurs with age (there’s some evidence that it is this slowdown that makes it harder for older adults to suppress distracting information). Perhaps the problem is not simply, or even principally, the complexity of our environment, but the speed of it. You only have to compare a modern TV drama or sit-com with one from the 70s to see how much faster everything now moves!

I do wonder if, in a less cognitively demanding environment, say, a traditional Himba village, whether WMC shows the same early rise and late decline. In an environment where change is uncommon, it is natural for elders to be respected for their accumulated wisdom — experience is all — but perhaps this respect also reflects a constancy in WMC (and thus ‘intelligence’), so that elders are not disadvantaged in the way they may be in our society. Just a thought.

Here’s another thought: it’s always seemed to me (this is not in any way a research-based conclusion!) that musicians and composers, and writers and professors, often age very well. I’ve assumed this was because they are keeping mentally active, and certainly that must be part of it. But perhaps there’s another reason, possibly even a more important reason: these are areas of expertise where the proponent spends a good deal of time focused on one thing. Rather than allowing their attention to be diffused throughout the environment all the time, they deliberately shut off their awareness of the environment to concentrate on their music, their writing, their art.

Perhaps, indeed, this is the shared factor behind which activities help fight age-related cognitive decline, and which don’t.

I began by saying that humans are the animals that manipulate their cognitive environment. I think this is the key to fighting age-related cognitive decline, or ADHD if it comes to that. We need to be aware how much our brains try to operate in a way that is optimal for our environment — meaning that, by controlling our environment, we can change the way our brain operates.

If you are worried about your ‘scattiness’, or if you want to prevent or fight age-related cognitive decline, I suggest you find an activity that truly absorbs and challenges you, and engage in it regularly.

The increase in WMC in Himba who moved to town also suggests something else. Perhaps the reason that WM training programs have had such little success is because they are ‘programs’. What you do in a specific environment (the bounds of a computer and the program running on it) does not necessarily, or even usually, transfer to the wider environment. We are contextual creatures, used to behaving in different ways with different people and in different places. If we want to improve our WMC, we need to incorporate experiences that challenge and extend it into our daily life.

This, of course, emphasizes my previous advice: find something that absorbs you, something that becomes part of your life, not something you 'do' for an hour some days. Learn to look at the world in a different way, through music or art or another language or a passion (Civil War history; Caribbean stamps; whatever).

You can either let your cognitive environment shape you, or shape your cognitive environment.

Do you agree? What's your cognitive environment, and do you think it has affected your cognitive well-being?

Until recent times, attention has always been quite a mysterious faculty. We’ve never doubted attention mattered, but it’s only in the past few years that we’ve appreciated how absolutely central it is for all aspects of cognition, from perception to memory. The rise in our awareness of its importance has come in the wake of, and in parallel with, our understanding of working memory, for the two work hand-in-hand.

In December 2008, I reported on an intriguing study (go down to "Previous study")that demonstrated the value of a walk in the fresh air for a weary brain. The study involved two experiments in which researchers found memory performance and attention spans improved by 20% after people spent an hour interacting with nature. There are two important aspects to this finding: the first is that this effect was achieved by walking in the botanical gardens, but not by walking along main streets; the second — far less predictable, and far more astonishing — was that this benefit was also achieved by looking at photos of nature (versus looking at photos of urban settings).

Now, most of us can appreciate that a walk in a natural setting will clear a foggy brain, and that this is better than walking busy streets — even if we have no clear understanding of why that should be. But the idea that the same benefit can accrue merely from sitting in a room and looking at pictures of natural settings seems bizarre. Why on earth should that help?

Well, there’s a theory. Attention, as we all know, even if we haven’t articulated it, has two components (three if you count general arousal). These two components, or aspects, of attention are involuntary or captured attention, and voluntary or directed attention. The first of these is exemplified by the situation when you hear a loud noise, or someone claps you on the shoulder. These are events that grab your attention. The second is the sort you have control over, the attention you focus on your environment, your work, your book. This is the type of attention we need, and find so much more elusive as we get older.

Directed attention has two components to it: the direct control you exert, and the inhibition you apply to distracting events, to block them out. As I’ve said on a number of occasions, it is this ability to block out distraction that is particularly affected by age, and is now thought to be one of the major reasons for age-related cognitive impairment.

Now, this study managed to isolate the particular aspects of attention that benefited from interacting with nature. The participants were tested on three aspects: alerting, orienting, and executive control. Alerting is about being sensitive to incoming stimuli, and was tested by comparing performance on trials in which the participant was warned by a cue that a trial was about to begin, and trials where no warning was given. Alerting, then, is related to arousal — it’s general, not specifically helpful about directing your attention.

Orienting, on the other hand, is selective. To test this, some trials were initiated by a spatial cue directing the participant’s attention to the part of the screen in which the stimulus (an arrow indicating direction) would appear.

Executive control also has something to do with directed attention, but it is about resolving conflict between stimuli. It was tested through trials in which three arrows were displayed, sometimes all pointing in the same direction, other times having the distracter arrows pointing in the opposite direction to the target arrow. So this measures how well you can ignore distraction.

So this is where the findings get particularly interesting: it seems that looking at pictures of nature benefited executive control, but not alerting or orienting.

Why? Well, attention restoration theory posits that a natural environment gives your attentional abilities a chance to rest and restore themselves, because there are few elements that capture your attention and few requirements for directed attention. This is more obvious when you are actually present in these environments; it’s obvious that on a busy city street there will be far more things demanding your attention.

The fact that the same effect is evident even when you’re looking at pictures echoes, perhaps, recent findings that the same parts of the brain are activated when we’re reading about something or watching it or doing it ourselves. It’s another reminder that we live in our brains, not the world. (It does conjure up another intriguing notion: does the extent to which pictures are effective correlate with how imaginative the person is?)

It’s worth noting that mood also improved when the study participants walked in the park rather than along the streets, but this didn’t appear to be a factor in their improved cognitive performance; however, the degree to which they felt mentally refreshed did correlate with their performance. Confirming these results, mood wasn’t affected by viewing pictures of nature, but participants did report that such pictures were significantly more refreshing and enjoyable.

Now, I’ve just reported on a new study that seems to me to bear on this issue. The study compared brain activity when participants looked at images of the beach and the motorway. The researchers chose these contrasting images because they are associated with very similar sounds (the roar of waves is acoustically very similar to the roar of traffic), while varying markedly in the feelings evoked. The beach scenes evoke a feeling of tranquility; the motorway scenes do not.

I should note that the purpose of the researchers was to look at how a feeling (a sense of tranquility) could be evoked by visual and auditory features of the environment. They do not refer to the earlier work that I have been discussing, and the connection I am making between the two is entirely my own speculation.

But it seems to me that the findings of this study do provide some confirmation for the findings of the earlier study, and furthermore suggest that such natural scenes, whether because of the tranquility they evoke or their relatively low attention-demanding nature or some other reason, may improve attention by increasing synchronization between relevant brain regions.

I’d like to see these studies extended to older adults (both of them were small, and both involved young adults), and also to personality variables (do some individuals benefit more from such a strategy than others? Does reflect particular personality attributes?). I note that another study found reduced connectivity in the default mode network in older adults. The default mode network may be thought of as where your mind goes when it’s not thinking of anything in particular; the medial prefrontal cortex is part of the default mode network, and this is one of the reasons it was a focus of the most recent study.

In other words, perhaps natural scenes refresh the brain by activating the default mode network, in a particularly effective way, allowing your brain to subsequently return to action (“task-positive network”) with renewed vigor (i.e. nicely synchronized brainwaves).

Interestingly, another study has found a genetic component to default-mode connectivity (aberrant DMN connectivity is implicated in a number of disorders). It would be nice to see some research into the effect of natural scenes on attention in people who vary in this attribute.

Meditation is of course another restorative strategy, and I’d also like to see a head-to-head comparison of these two strategies. But in any case, bottom-line, these results do suggest an easy way of restoring fading attention, and because of the specific aspect of attention that is being helped, it suggests that the strategy may be of particular benefit to older adults. I would be interested to hear from any older adults who try it out.

[Note that part of this article first appeared in the December 2008 newsletter]

On my walk today, I listened to a downloaded interview from the On Being website. The interview was with ‘vocal magician and conductor’ Bobby McFerrin, and something he said early on in the interview really caught my attention.

In response to a question about why he’d once (in his teens) contemplated joining a monastic order, he said that the quiet really appealed to him, and also ‘the discipline of the hours … there’s a rhythm to the day. I liked the fact that you stopped whatever you were doing at a particular time and you reminded yourself, you brought yourself back to your calling’.

Those words resonated with me, and they made me think of the Moslem habit of prayer. Of the idea of having specified times during the day when you stop your ‘ordinary’ life, and touch base, as it were, with something that is central to your being.

I don’t think you need to be a monk or a Moslem to find value in such an activity! Nor does the activity need to be overtly religious.

Because this idea struck another echo in me — some time ago I wrote a brief report on how even a short ‘quiet time’ can help you consolidate your memories. It strikes me that developing the habit of having fixed points in the day when (if at all possible) you engage in some regular activity that helps relax you and center your thoughts, would help maintain your focus during the day, and give you a mental space in which to consolidate any new information that has come your way.

Appropriate activities could include:

• meditating on your breath;
• performing a t’ai chi routine;
• observing nature;
• listening to certain types of music;
• singing/chanting some song/verse (e.g., the Psalms; the Iliad; the Tao te Ching)

Regarding the last two suggestions, as I reported in my book on mnemonics, there’s some evidence that reciting the Iliad has physiological effects on synchronizing heartbeat and breath that is beneficial for both mood and cognitive functioning. It’s speculated that the critical factor might be the hexametric pace (dum-diddy, dum-diddy, dum-diddy, dum-diddy, dum-diddy, dum-dum). Dactylic hexameter, the rhythm of classical epic, has a musical counterpart: 6/8 time.

Similarly, another small study found that singing Ave Maria in Latin, or chanting a yoga mantra, likewise affects brain blood flow, and the crucial factor appeared to be a rhythm that involved breathing at the rate of six breaths a minute.

Something to think about!

The thing to remember about Ericsson’s famous expertise research, showing us the vital importance of deliberate practice in making an expert, is that it was challenging the long-dominant view that natural-born talent is all-important. But Gladwell’s popularizing of Ericsson’s “10,000 hours” overstates the case, and of course people are only too keen to believe that any height is achievable if you just work hard enough.

The much more believable story is that, yes, practice is vital — a great deal of the right sort of practice — but we can’t disavow “natural” abilities entirely.

Last year I reported on an experiment in which 57 pianists with a wide range of deliberate practice (from 260 to more than 31,000 hours) were compared on their ability to sight-read. Number of hours of practice did indeed predict much of the difference in performance (nearly half) — but not all. Working memory capacity also had a statistically significant impact on performance, although this impact was much smaller (accounting for only about 7% of the performance difference). Nevertheless, there’s a clear consequence: given two players who have put in the same amount of effective practice, the one with the higher WMC is likely to do better. Why should WMC affect sight-reading? Perhaps by affecting how many notes a player can look ahead as she plays — this is a factor known to affect sight-reading performance.

Interestingly, the effect of working memory capacity was quite independent of practice, and hours of practice apparently had no effect on WMC. Although it’s possible (the study was too small to tell) that a lot of practice at an early age might affect WMC. After all, music training has been shown to increase IQ in children.

So, while practice is certainly the most important factor in developing expertise, other factors, some of them less amenable to training, have a role to play too.

But do general abilities such as WMC or intelligence matter once you’ve put in the requisite hours of good practice? It may be that ability becomes less important once you achieve expertise in a domain.

The question of whether WMC interacts with domain knowledge in this way has been studied by Hambrick and his colleagues in a number of experiments. One study used a memory task in which participants listened to fictitious radio broadcasts of baseball games and tried to remember major events and information about the players. Baseball knowledge had a very strong effect on performance, and WMC had a much smaller effect, but there was no interaction between the two. Similarly, in two poker tasks, in which players had to assess the likelihood of drawing a winning card, and players had to remember hands during a game of poker, both poker knowledge and WMC affected performance, but again there was no interaction between domain knowledge and WMC.

Another study took a different tack. Participants were asked to remember the movements of spaceships flying from planet to planet in the solar system. What they didn’t know was that the spaceships flew in a pattern that matched the way baseball players run around a baseball diamond. They were then given the same task, this time with baseball players running around a diamond. Baseball knowledge only helped performance in the task in which the baseball scenario was explicit — activating baseball knowledge. But activation of domain knowledge had no effect on the influence of WMC.

Although these various studies fail to show an interaction between domain knowledge and WMC, this doesn’t mean that domain knowledge never interacts with basic abilities. The same researchers recently found such an interaction in a geological bedrock mapping task, in which geological structure of a mountainous area had to be inferred. Visuospatial ability predicted performance only at low levels of geological knowledge; geological experts were not affected by their visuospatial abilities. Unfortunately, that study is not yet published, so I don’t know the details. But I assume they mean visuospatial working memory capacity.

It’s possible that general intelligence or WMC are most important during the first stages of skill acquisition (when attention and working memory capacity are so critical), and become far less important once the skill has been mastered.

Similarly, Ericsson has argued that deliberate practice allows performers to circumvent limits on working memory capacity. This is, indeed, related to the point I often make about how to functionally increase your working memory capacity — if you have a great amount of well-organized and readily accessible knowledge on a particular topic, you can effectively expand how much your working memory can hold by keeping a much larger amount of information ‘on standby’ in what has been termed long-term working memory.

Proponents of deliberate practice don’t deny that ‘natural’ abilities have some role, but they restrict it to motivation and general activity levels (plus physical attributes such as height where that is relevant). But surely these would only affect number of hours. Clearly the ability to keep yourself on task, to motivate and discipline yourself, impinges on your ability to keep your practice up. And the general theory makes sense — that if you show some interest in something, such as music or chess, when you’re young, your parents or teachers usually encourage you in that direction; this encouragement and rewards lead you to spend more time and energy in that domain, and if you have enough persistence, enough dedication, then lo and behold, you’ll get better and better. And your parents will say, well, it was obvious from an early age that she was talented that way.

But is it really the case that attributes such as intelligence make no difference? Is it really as simple as “10,000 hours of deliberate practice = expert”? Is it really the case that each hour has the same effect on any one of us?

A survey of 104 chess masters found that, while all the players that became chess masters had practiced at least 3,000 hours, the amount of practice it took to achieve that mastery varied considerably. Although, consistent with the “10,000 hour rule”, average time to achieve mastery was around 11,000 hours, time ranged from 3,016 hours to 23,608 hours. The difference is even more extreme if you only consider individual practice (previous research has pointed to individual practice being of more importance than group practice): a range from 728 hours to 16,120 hours! And some people practiced more than 20,000 hours and still didn't achieve master level.

Moreover, a comparison of titled masters and untitled international players found that the two groups practiced the same amount of hours in the first three years of their serious dedication to chess, and yet there were significant differences in their ratings. Is this because of some subtle difference in the practice, making it less effective? Or is it that some people benefit more from practice?

A comparison of various degrees of expertise in terms of starting age is instructive. While the average age of starting to play seriously was around 18 for players without an international rating, it was around 14 for players with an international rating, and around 11 for masters. But the amount of variability within each group varies considerably. For players without an international rating, the age range within one standard deviation of the mean is over 11 years, but for those with an international rating, FIDE masters, and international masters, the range is only 2-3 years, and for grand masters, the range is less than a year. [These numbers are all approximate, from my eyeball estimates of a bar graph.]

It has been suggested that the younger starting age of chess masters and expert musicians is simply a reflection of the greater amount of practice achieved with a young start. But a contrary suggestion is that there might be other advantages to learning a skill at an early age, reflecting what might be termed a ‘sensitive period’. This study found that the association between skill and starting age was still significant after amount of practice had been taken account of.

Does this have to do with the greater plasticity of young brains? Expertise “grows” brains — in the brain regions involved in that specific domain. Given that younger brains are much more able to create new neurons and new connections, it would hardly be a surprise that it’s easier for them to start building up the dense structures that underlie expertise.

This is surely easier if the young brain is also a young brain that has particular characteristics that are useful for that domain. For music, that might relate to perceptual and motor abilities. In chess, it might have more to do with processing speed, visuospatial ability, and capacious memory.

Several studies have found higher cognitive ability in chess-playing children, but the evidence among adults has been less consistent. This may reflect the growing importance of deliberate practice. (Or perhaps it simply reflects the fact that chess is a difficult skill, for which children, lacking the advantages that longer education and training have given adults, need greater cognitive skills.)

Related to all this, there’s a popular idea that once you get past an IQ of around 120, ‘extra’ IQ really makes no difference. But in a study involving over 2,000 gifted young people, those who scored in the 99.9 percentile on the math SAT at age 13 were eighteen times more likely to go on to earn a doctorate in a STEM discipline (science, technology, engineering, math) compared to those who were only(!) in the 99.1 percentile.

Overall, it seems that while practice can take you a very long way, at the very top, ‘natural’ ability is going to sort the sheep from the goats. And ‘natural’ ability may be most important in the early stages of learning. But what do we mean by ‘natural ability’? Is it simply a matter of unalterable genetics?

Well, palpably not! Because if there’s one thing we now know, it’s that nature and nurture are inextricably entwined. It’s not about genes; it’s about the expression of genes. So let me remind you that aspects of the prenatal, the infant, and the child’s, environment affect that ‘natural’ ability. We know that these environments can affect IQ; the interesting question is what we can do, at each and any of these stages, to improve affect basic processes such as speed of processing, WMC, and inhibitory control. (Although I should say here that I am not a fan of the whole baby-Einstein movement! Nor is there evidence that many of those practices work.)

Bottom line:

• talent still matters
• effective practice is still the most important factor in developing expertise
• individuals vary in how much practice they need
• individual abilities do put limits on what’s achievable (but those limits are probably higher than most people realize).

One of my perennial themes is the importance of practice, and in the context of developing expertise, I have talked of ‘deliberate practice’ (a concept articulated by the well-known expertise researcher K. Anders Ericsson). A new paper in the journal Psychology of Music reports on an interesting study that shows how the attributes of music practice change as music students develop in expertise. Music is probably the most studied domain in expertise research, but I think we can gain some general insight from this analysis. Here’s a summary of the findings.

[Some details about the U.K. study for those interested: the self-report study involved 3,325 children aged 6-19, ranging from beginner to Grade 8 level, covering a variety of instruments, with violin the most common at 28%, and coming from a variety of musical settings: junior conservatoires, youth orchestras, Saturday music schools, comprehensive schools.]

For a start, and unsurprisingly, amount of practice (both in terms of amount each day, and number of days in the week) steadily increases as expertise develops. Interestingly, there is a point where it plateaus (around grade 5-6 music exams) before increasing more sharply (presumably this reflects a ‘sorting the sheep from the goats’ effect — that is, after grade 6, it’s increasingly only the really serious ones that continue).

It should not be overlooked, however, that there was huge variability between individuals in this regard.

More interesting are the changes in the attributes of their practice.

 

These attributes became less frequent as the players became more expert:

Practicing strategies:

Practicing pieces from beginning to end without stopping

Going back to the beginning after a mistake

Analytic strategies:

Working things out by looking at the music without actually playing it

Trying to find out what a piece sounds like before trying to play it

Analyzing the structure of a piece before learning it

Organization strategies:

Making a list of what to practice

Setting targets for each session.

 

These attributes became more frequent as the players became more expert:

Practicing strategies:

Practicing small sections;

Getting recordings of a piece that is being learned;

Practicing things slowly;

Knowing when a mistake has been made;

When making a mistake, practicing a section slowly;

When something was difficult playing it over and over again;

Marking things on the part;

Practicing with a metronome;

Recording practice and listening to the tapes;

Analytic strategies:

Identifying difficult sections;

Thinking about how to interpret the music;

Organization strategies:

Doing warm-up exercises;

Starting practice with studies;

Starting practice with scales.

 

Somewhat surprisingly, levels of concentration and distractability didn’t vary significantly as a function of level of expertise. The researchers suggest that this may reflect the reliance on self-reported data rather than reality, but, also somewhat surprisingly, enjoyment of practice didn’t change as a function of expertise either.

Interestingly (but perhaps not so surprisingly once you think about it), the adoption of systematic practicing strategies followed a U-shaped curve rather than a linear trend. Those who had passed Grade 1 scored relatively high on this, but those who had most recently passed Grade 2 scored more poorly, and those with Grade 3 were worst of all. After that, it begins to pick up again, achieving the same level at Grade 6 as at Grade 1.

Organization of practice, on the other hand, while it varied with level of expertise, showed no systematic relationship (if anything, it declined with expertise! But erratically).

The clearest result was the very steady and steep decline in the use of ineffective strategies. These include:

• Practicing pieces from beginning to end without stopping;
• Going back to the beginning after a mistake;
• Immediate correction of errors.

It should be acknowledged that these strategies might well be appropriate at the beginning, but they are not effective with longer and more complex pieces. It’s suggested that the dip at Grade 3 probably reflects the need to change strategies, and the reluctance of some students to do so.

But of course grade level in itself is only part of the story. Analysis on the basis of how well the students did on their most recent exam (in terms of fail, pass, commended, and highly commended) reveals that organization of practice, and making use of recordings and a metronome, were the most important factors (in addition to the length of time they had been learning).

The strongest predictor of expertise, however, was not using ineffective strategies.

This is a somewhat discouraging conclusion, since it implies that the most important thing to learn (or teach) is what not to do, rather than what to do. But I think a codicil to this is also implicit. Given the time spent practicing (which is steadily increasing with expertise), the reduction in wasting time on ineffective strategies means that, perforce, time is being spent on effective strategies. The fact that no specific strategies can be inequivocally pointed to, suggests that (as I have repeatedly said), effective strategies are specific to the individual.

This doesn’t mean that identifying effective strategies and their parameters is a pointless activity! Far from it. You need to know what strategies work to know what to choose from. But you cannot assume that because something is the best strategy for your best friend, that it is going to be equally good for you.

Notwithstanding this, the adoption of systematic practice strategies was significantly associated with expertise, accounting for the largest chunk of the variance between individuals — some 11%.

Similarly, organization of practice (accounting for nearly 8% of variance), making use of recordings and a metronome (nearly 8% of variance), analytic strategies (over 7% of variance) were important factors in developing expertise in music, and it seems likely that many if not most individuals would benefit from these.

It’s also worth noting that playing straight through the music was the strongest predictor of expertise — as a negative factor.

So what general conclusions can we draw from these findings?

The wide variability in practice amount is worth noting — practice is hugely important, but it’s a mistake to have hard-and-fast rules about the exact number of hours that is appropriate for a given individual.

Learning which strategies are a waste of time is very important (and one that many students don’t learn — witness the continuing popularity of rote repetition as a method of learning).

Organization — in respect of structuring your learning sessions — is perhaps one of those general principles that doesn’t necessarily apply to every individual, and certainly the nature and extent of organization is likely to vary by individual. Nevertheless, given its association with better performance, it is certainly worth trying to find the level of organization that is best for you (or your student). The most important factors in this category were starting practice with scales (for which appropriate counterparts are easily found for other skills being practiced, including language learning, although perhaps less appropriate for other forms of declarative learning), and making a list of what needs to be practiced.

Having expert models/examples/case studies (as appropriate), and appropriate levels of scaffolding, are very helpful (in the case of music, this is instantiated by the use of recordings, both listening to others and self-feedback, and use of a metronome).

Identifying difficult aspects, and dealing with them by tackling them on their own, using a slow and piecemeal process, is usually the most helpful approach. (Of the practice strategies, the most important were practicing sections slowly when having made a mistake, practicing difficult sections over and over again, slow practice, gradually speeding up when learning fast passages, and recognizing errors.)

Preparing for learning is also a generally helpful strategy. In music this is seen in the most effective analytic strategies: trying to find out what a piece sounds like before trying to play it, and getting an overall idea of a piece before practicing it. In declarative learning (as opposed to skill learning), this can be seen in such strategies as reading the Table of Contents, advance organizers and summaries (in the case of textbooks), or doing any required reading before a lecture, and (in both cases) thinking about what you expect to learn from the book or lecture.

Let’s talk about the cognitive benefits of learning and using another language.

In a recent news report, I talked about the finding that intensive learning of a very novel language significantly grew several brain regions, of which two were positively associated with language proficiency. These regions were the right hippocampus and the left superior temporal gyrus. Growth of the first of these probably reflects the learning of a great many new words, and the second may reflect heavy use of the phonological loop (a part of working memory).

There are several aspects to this study that are worth discussing in the context of using language learning as a means of protecting against age-related cognitive decline.

First of all, let me start with a general reminder. We now know that, analogous to muscles, we can ‘grow’ specific brain regions by working them. But an adult brain is confined by the skull — growth in one part is generally at the expense of another part. So, unlike body-building, you can’t just grow your whole brain!

This suggests that it pays to think about the areas you want to improve (which goes right back to the first chapter of The Memory Key: it’s no good talking about improving ‘your memory’ — rather, you should pick the memory tasks you want to improve).

One of the big advantages of growing the parts of the brain involved in language is that language is so utterly critical to our intellectual ability. Most of us use language to think and to communicate. There’s a reason why so many studies of older adults’ cognitive performance use verbal fluency as the measure!

But, in the same way that the increase in London cab drivers’ right posterior hippocampus appears to be at the expense of the anterior hippocampus, the growth in the right hippocampus may be at the expense of other functions (perhaps spatial navigation).

Is this a reason for not learning? Certainly not! But it is perhaps a reminder that we should be aiming for two things in preventing cognitive decline. The first is in ‘growing’ brain tissue: making new neurons, and new connections. This is to counteract the shrinkage (brain atrophy) that tends to occur with age.

The second concerns flexibility. Retaining the brain’s plasticity is a vital part of fighting cognitive decline, even more vital, perhaps, than retaining brain tissue. To keep this plasticity, we need to keep the brain changing.

Here’s a question we don’t yet know the answer to: how much age-related cognitive decline is down to people steadily experiencing fewer and fewer novel events, learning less, thinking fewer new thoughts?

But we do know it matters.

So let’s go back to our intensive language learners growing parts of their brain. Does the growth in the right hippocampus (unfortunately we don’t know how much that growth was localized within the right hippocampus) mean that it will now remain that size, at the expense, presumably, of some other area (and function)?

No, it doesn’t. As far as language is concerned, the hippocampus is primarily a short-term processor. As those new words are consolidated, they’ll move into long-term memory, in the language network across the cortex. Once the interpreters stop acquiring new vocabulary at this rate, I would expect to see this region reduce. Indeed (and I am speculating here), I would expect this to happen once a solid ‘semantic network’ for the new language was established in long-term memory. At this point, new vocabulary will be more and more encoded in terms of that network, and reliance on the short-term processes of the hippocampus will become less (although still important!).

I think that intensity is important. Intensity by its very nature is rarely maintained. People at the top of their field — champion sportspeople, top-ranking musicians, ‘geniuses’, and so on —they have to maintain that intensity as long as they want to stay at the top, and I would expect their brains to show more enduring changes (that is, particular regions that are unusually large, and others that are smaller than average). For the rest of us, any enduring changes are less marked.

But making those changes is important!

In recent years, research has come to suggest that, although regular moderate exercise is highly beneficial for physical and mental health, short bouts of intense activity have their own specific benefits above and beyond that. I think the same might be true for mental activity.

This may be particularly (or differently) true as we get older, when it does tend to get harder to learn — making (relatively) short bouts of intensive study/learning/activity so vital. We need that concentrated practice more than we did when we were young and learning came easier. And concentrated practice may be exactly the way to produce significant change in our brains.

But we don’t need to worry about becoming ‘muscle-bound’ — if we learn thousands of new words in a few months (an excellent step in acquiring a new language), we will then go on to acquire grammar and practice reading and writing whole sentences. The words will consolidate; different language skills will build different parts of the brain; those areas no longer being intensively worked will diminish (a little).

Moreover, it’s not only about growing particular regions, it’s also very much about building new or stronger connections between regions — building new networks. Because language learning involves so many regions, it may be especially good for that aspect too (see, for example, another recent news report, on how language learning grows white matter and reorganizes brain structures).

The important thing is that your brain is changing; the important thing is that your brain keeps changing. I think intensive periods of new learning are the way to achieve this, interspersed with consolidation periods.

As I’ve said before, variety is key. By providing variety in learning and experiences across tasks and domains, you can keep your brain flexible. By providing intense focus for a period, you can better build specific ‘mental muscles’.

A New Yorker cartoon has a man telling his glum wife, “Of course I care about how you imagined I thought you perceived I wanted you to feel.” There are a number of reasons you might find that funny, but the point here is that it is very difficult to follow all the layers. This is a sentence in which mental attributions are made to the 6^th level, and this is just about impossible for us to follow without writing it down and/or breaking it down into chunks.

According to one study, while we can comfortably follow a long sequence of events (A causes B, which leads to C, thus producing D, and so on), we can only comfortably follow four levels of intentionality (A believes that B thinks C wants D). At the 5^th level (A wants B to believe that C thinks that D wants E), error rates rose sharply to nearly 60% (compared to 5-10% for all levels below that).

Why do we have so much trouble following these nested events, as opposed to a causal chain?

Let’s talk about working memory.

Working memory (WM) has evolved over the years from a straightforward “short-term memory store” to the core of human thought. It’s become the answer to almost everything, invoked for everything related to reasoning, decision-making, and planning. And of course, it’s the first and last port of call for all things memory — to get stored in long-term memory an item first has to pass through WM, where it’s encoded; when we retrieve an item from memory, it again passes through WM, where the code is unpacked.

So, whether or not the idea of working memory has been over-worked, there is no doubt at all that it is utterly crucial for cognition.

Working memory has also been equated with attentional control, and working memory and attention are often used almost interchangeably. And working memory capacity (WMC) varies among individuals. Those with a higher WMC have an obvious advantage in reasoning, comprehension, remembering. No surprise then that WMC correlates highly with fluid intelligence.

So let’s talk about working memory capacity.

The idea that working memory can hold 7 (+/-2) items has passed into popular culture (the “magic number 7”). More recent research, however, has circled around the number 4 (+/-1). Not only that, but a number of studies suggest that in fact the true number of items we can attend to is only one. What’s the answer? (And where does it leave our high- and low-capacity individuals? There’s not a lot of room to vary there.)

Well, in one sense, 7 is still fine — that’s the practical sense. Seven items (5-9) is about what you can hold if you can rehearse them. So those who are better able to rehearse and chunk will have a higher working memory capacity (WMC). That will be affected by processing speed, among other factors.

But there is a very large body of evidence now pointing to working memory holding only four items, and a number of studies indicating that most likely we can only pay attention to one of these items at a time. So you can envision this either as a focus of attention, which can only hold one item, and a slightly larger “outer store” or area of “direct access” which can hold another three, or as a mental space holding four items of which only one can be the focus at any one time.

A further tier, which may be part of working memory or part of long-term memory, probably holds a number of items “passively”. That is, these are items you’ve put on the back burner; you don’t need them right at the moment, but you don’t want them to go too far either. (See my recent news item for more on all this.)

At present, we don’t have any idea how many items can be in this slightly higher state of activation. However, the “magic number 7” suggests that you can circulate 3 (+/-1) items from the backburner into your mental space. In this regard, it’s interesting to note that, in the case of verbal material, the amount you can hold in working memory with rehearsal has been found to more accurately equate to 2 seconds, rather than 7 items. That is, you can remember as much as you can verbalize in about 2s (so, yes, fast speakers have a distinct advantage over slower ones). You see why processing speed affects WMC.

Whether you think of WM as a focus of one and an outer store of 3, or as a direct access area with 4 boxes and a spotlight shining on one, it’s a mental space or blackboard where you can do your working out. Thinking of it this way makes it easier to conceptualize and talk about, but these items are probably not going into a special area as such. The thought now is that these items stay in long-term memory (in their relevant areas of association cortex), but they are (a) highly activated, and (b) connected to the boxes in the direct access area (which is possibly in the medial temporal lobe). This connection is vitally important, as we shall see.

Now four may not seem like much, but WM is not quite as limited as it seems, because we have different systems for verbal (includes numerical) and visuospatial information. Moreover, we can probably distinguish between the items and the processing of them, which equates to a distinction between declarative and procedural memory. So that gives us three working memory areas: verbal declarative; visuospatial declarative; procedural.

Now all of this may seem more than you needed to know, but breaking down the working memory system helps us discover two things of practical interest. First, which particular parts of the system are the parts that make a task more difficult. Second, where individual differences come from, and whether they are in aspects that are trainable.

For example, this picture of a mental space with a focus of one and a maximum of three eager-beavers waiting their turn, points to an important aspect of the working memory system: switching the focus. Experiments reveal that there is a large focus-switching cost, incurred whenever you have to switch the item in the spotlight. And the extent of this cost has been surprising — around 240ms in one study, which is about six times the length of time it takes to scan an item in a traditional memory-search paradigm.

But focus-switch costs aren’t a constant. They vary considerably depending on the difficulty of the task, and they also tend to increase with each item in the direct-access area. Indeed, just having one item in the space outside the focus causes a significant loss of efficiency in processing the focused item.

This may reflect increased difficulty in discriminating one highly activated item from other highly activated items. This brings us to competition, which, in its related aspects of interference and inhibition, is a factor probably more crucial to WMC than whether you have 3 or 4 or 5 boxes in your direct access area.

But before we discuss that, we need to look at another important aspect of working memory: updating. Updating is closely related to focus-switching, and it’s easy to get confused between them. But it’s been said that working memory updating (WMU) is the only executive function that correlates with fluid intelligence, and updating deficits have been suggested as the reason for poor comprehension (also correlated with low-WMC). So it’s worth spending a little time on.

To get the distinction clear in your mind, imagine the four boxes and the spotlight shining on one. Any time you shift the spotlight, you incur a focus-switching cost. If you don’t have to switch focus, if you simply need to update the contents of the box you’re already focusing on, then there will be an update cost, but no focus-switching cost.

Updating involves three components: retrieval; transformation; substitution. Retrieval simply involves retrieving the contents from the box. Substitution involves replacing the contents with something different. Transformation involves an operation on the contents of the box to get a new value (eg, when you have to add a certain number to an earlier number).

Clearly the difficulty in updating working memory will depend on which of these components is involved. So which of these processes is most important?

In terms of performance, the most important component is transformation. While all three components contribute to the accuracy of updating, retrieval apparently doesn’t contribute to speed of updating. For both accuracy and speed, substitution is less important than transformation.

This makes complete sense: obviously having to perform an operation on the content is going to be more difficult and time-consuming than simply replacing it. But it does help us see that the most important factor in determining the difficulty of an updating task will be the complexity of the transformation.

The finding that retrieval doesn’t affect speed of updating sounds odd, until you realize the nature of the task used to measure these components. The number of items was held constant (always three), and the focus switched from one box to another on every occasion, so focus-switching costs were constant too. What the finding says is that once you’ve shifted your focus, retrieval takes no time at all — the spotlight is shining and there the answer is. In other words, there really is no distinction between the box and its contents when the spotlight is on it — you don’t need to open the box.

However, retrieval does affect accuracy, and this implies that something is degrading or interfering in some way with the contents of the boxes. Which takes us back to the problems of competition / interference.

But before we get to that, let’s look at this issue of individual differences, because like WMC, working memory updating correlates with fluid intelligence. Is this just a reflection of WMC?

Differences in transformation accuracy correlated significantly with WMC, as did differences in retrieval accuracy. Substitution accuracy didn’t vary enough to have measurable differences. Neither transformation nor substitution speed differences correlated with WMC. This implies that the reason why people with high WMC also do better at WMU tasks is because of the transformation and retrieval components.

So what about the factors that aren’t correlated with WMC? The variance in transformation speed is argued to primarily reflect general processing speed. But what’s going on in substitution that isn’t going on in when WMC is measured?

Substitution involves two processes: removing the old contents of the box, and adding new content. In terms of the model we’ve been using, we can think of unbinding the old contents from the box, and binding new contents to it (remember that the item in the box is still in its usual place in the association cortex; it’s “in” working memory by virtue of the temporary link connecting it to the box). Or we can think of it as deleting and encoding.

Consistent with substitution not correlating with WMC, there is some evidence that high- and low-WMC individuals are equally good at encoding. Where high- and low-WMC individuals differ is in their ability to prevent irrelevant information being encoded with the item. Which brings me to my definition of intelligence (from 30 years ago — these ideas hadn’t even been invented yet. So I came at it from quite a different angle): the ability to (quickly) select what’s important.

So why do low-WMC people tend to be poorer at leaving out irrelevant information?

Well, that’s the $64,000 question, but related to that it’s been suggested that those with low working memory capacity are less able to resist capture by distracting stimuli than those with high WMC. A new study, however, provides evidence that low- and high-WMC individuals are equally easily captured by distracters. What distinguishes the two groups is the ability to disengage. High-capacity people are faster in putting aside irrelevant stimuli. They’re faster at deleting. And this, it seems, is unrelated to WMC.

This is supported by another recent finding, that when interrupted, older adults find it difficult to disengage their brain from the new task and restore the original task.

So what’s the problem with deleting / removing / putting aside items in focus? This is about inhibition, which takes us once again to competition / interference.

Now interference occurs at many different levels: during encoding, retrieval, and storage; with items, with tasks, with responses. Competition is ubiquitous in our brain.

In the case of substitution during working memory updating, it’s been argued that the contents of the box are not simply removed and replaced, but instead gradually over-written by the new contents. This fits in with a view of items as assemblies of lower-level “feature-units”. Clearly, items may share some of these units with other items (reflected in their similarity), and clearly the more they compete for these units, the greater interference there will be between the units.

You can see why it’s better to keep your codes (items) “lean and mean”, free of any irrelevant information.

Indeed, some theorists completely discard the idea of number of items as a measure of WMC, and talk instead in terms of “noise”, with processing capacity being limited by such factors as item complexity and similarity. While there seems little justification for discarding our “4+/-1”, which is much more easily quantified, this idea does help us get to grips with the concept of an “item”.

What is an item? Is it “red”? “red cow”? “red cow with blue ribbons round her neck”? “red cow with blue ribbons and the name Isabel painted on her side”? You see the problem.

An item is a fuzzy concept. We can’t say, “it’s a collection of 6 feature units” (or 4 or 14 or 42). So we have to go with a less defined description: it’s something so tightly bound that it is treated as a single unit.

Which means it’s not solely about the item. It’s also about you, and what you know, and how well you know it, and what you’re interested in.

To return to our cases of difficulty in disengaging, perhaps the problem lies in the codes being formed. If your codes aren’t tightly bound, then they’re going to start to degrade, losing some of their information, losing some of their distinctiveness. This is going to make them harder to re-instate, and it’s going to make them less distinguishable from other items.

Why should this affect disengagement?

Remember what I said about substitution being a gradual process of over-writing? What happens when your previous focus and new focus have become muddled?

This also takes us to the idea of “binding strength” — how well you can maintain the bindings between the contents and their boxes, and how well you can minimize the interference between them (which relates to how well the items are bound together). Maybe the problem with both disengagement and reinstatement has to do with poorly bound items. Indeed, it’s been suggested that the main limiting factor on WMC is in fact binding strength.

Moreover, if people vary in their ability to craft good codes, if people vary in their ability to discard the irrelevant and select the pertinent, to bind the various features together, then the “size” (the information content) of an item will vary too. And maybe this is what is behind the variation in “4 +/-1”, and experiments which suggest that sometimes the focus can be increased to 2 items. Maybe some people can hold more information in working memory because they get more information into their items.

So where does this leave us?

Let’s go back to our New Yorker cartoon. The difference between a chain of events and the nested attributions is that chaining doesn’t need to be arranged in your mental space because you don’t need to keep all the predecessors in mind to understand it. On the other hand, the nested attributions can’t be understood separately or even in partitioned groups — they must all be arranged in a mental space so we can see the structure.

We can see now that “A believes that B thinks C wants D” is easy to understand because we have four boxes in which to put these items and arrange them. But our longer nesting, “A wants B to believe that C thinks that D wants E”, is difficult because it contains one more item than we have boxes. No surprise there was a dramatic drop-off in understanding.

So given that you have to fill your mental space, what is it that makes some tasks more difficult than others?

• The complexity and similarity of the items (making it harder to select the relevant information and bind it all together).
• The complexity of the operations you need to perform on each item (the longer the processing, the more tweaking you have to do to your item, and the more time and opportunity for interference to degrade the signal).
• Changing the focus (remember our high focus-switching costs).

But in our 5^th level nested statement, the error rate was 60%, not 100%, meaning a number of people managed to grasp it. So what’s their secret? What is it that makes some people better than others at these tasks?

They could have 5 boxes (making them high-WMC). They could have sufficient processing speed and binding strength to unitize two items into one chunk. Or they could have the strategic knowledge to enable them to use the other WM system (transforming verbal data into visuospatial). All these are possible answers.

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This has been a very long post, but I hope some of you have struggled through it. Working memory is the heart of intelligence, the essence of attention, and the doorway to memory. It is utterly critical, and cognitive science is still trying to come to grips with it. But we’ve come a very long way, and I think we now have sufficient theoretical understanding to develop a model that’s useful for anyone wanting to understand how we think and remember, and how they can improve their skills.

There is, of course, far more that could be said about working memory (I’ve glossed over any number of points in an effort to say something useful in less than 50,000 words!), and I’m planning to write a short book on working memory, its place in so many educational and day-to-day tasks, and what we can do to improve our skills. But I hope some of you have found this enlightening.

In a recent news report, I talked about how walking through doorways creates event boundaries, requiring us to update our awareness of current events and making information about the previous location less available. I commented that we should be aware of the consequences of event boundaries for our memory, and how these contextual factors are important elements of our filing system. I want to talk a bit more about that.

One of the hardest, and most important, things to understand about memory is how various types of memory relate to each other. Of course, the biggest problem here is that we don’t really know! But we do have a much greater understanding than we used to do, so let’s see if I can pull out some salient points and draw a useful picture.

Let’s start with episodic memory. Now episodic memory is sometimes called memory for events, and that is reasonable enough, but it perhaps gives an inaccurate impression because of the common usage of the term ‘event’. The fact is, everything you experience is an event, or to put it another way, a lifetime is one long event, broken into many many episodes.

Similarly, we break continuous events into segments. This was demonstrated in a study ten years ago, that found that when people watched movies of everyday events, such as making the bed or ironing a shirt, brain activity showed that the event was automatically parsed into smaller segments. Moreover, changes in brain activity were larger at large boundaries (that is, the boundaries of large, superordinate units) and smaller at small boundaries (the boundaries of small, subordinate units).

Indeed, following research showing the same phenomenon when people merely read about everyday activities, this is thought to reflect a more general disposition to impose a segmented structure on events and activities (“event structure perception”).

Event Segmentation Theory postulates that perceptual systems segment activity as a side effect of trying to predict what’s going to happen. Changes in the activity make prediction more difficult and cause errors. So these are the points when we update our memory representations to keep them effective.

Such changes cover a wide gamut, from changes in movement to changes in goals.

If you’ve been following my blog, the term ‘updating’ will hopefully bring to mind another type of memory — working memory. In my article How working memory works: What you need to know, I talked about the updating component of working memory at some length. I mentioned that updating may be the crucial component behind the strong correlation between working memory capacity and intelligence, and that updating deficits might underlie poor comprehension. I distinguished between three components of updating (retrieval; transformation; substitution), and how transformation was the most important for deciding how accurately and how quickly you can update your contents in working memory. And I discussed how the most important element in determining your working memory ‘capacity’ seems to be your ability to keep irrelevant information out of your memory codes.

So this event segmentation research suggests that working memory updating occurs at event boundaries. This means that information before the boundary becomes less accessible (hence the findings from the walking through doorways studies). But event boundaries relate not only to working memory (keeping yourself updated to what’s going on) but also to long-term storage (we’re back to episodic memory now). This is because those boundaries are encoded particularly strongly — they are anchors.

Event boundaries are beginnings and endings, and we have always known that beginnings and endings are better remembered than middles. In psychology this is known formally as the primacy and recency effects. In a list of ten words (that favorite subject of psychology experiments), the first two or three items and the last two or three items are the best remembered. The idea of event boundaries gives us a new perspective on this well-established phenomenon.

Studies of reading have shown that readers slow down at event boundaries, when they are hypothesized to construct a new mental model. Such boundaries occur when the action moves to a new place, or a new time, or new characters enter the action, or a new causal sequence is begun. The most important of these is changes in characters and their goals, and changes in time.

As I’ve mentioned before, goals are thought to play a major role (probably the major role) in organizing our memories, particularly activities. Goals produce hierarchies — any task can be divided into progressively smaller elements. Research suggests that higher-order events (coarse-grained, to use the terminology of temporal grains) and lower-order events (fine-grained) are sensitive to different features. For example, in movie studies, coarse-grained events were found to focus on objects, using more precise nouns and less precise verbs. Finer-grained events, on the other hand, focused on actions on those objects, using more precise verbs but less precise nouns.

The idea that these are separate tasks is supported by the finding of selective impairments of coarse-grained segmentation in patients with frontal lobe lesions and patients with schizophrenia.

While we automatically organize events hierarchically (even infants seem to be sensitive to hierarchical organization of behavior), that doesn’t mean our organization is always effortlessly optimal. It’s been found that we can learn new procedures more easily if the hierarchical structure is laid out explicitly — contrariwise, we can make it harder to learn a new procedure by describing or constructing the wrong structure.

Using these hierarchical structures helps us because it helps us use knowledge we already have in memory. We can co-op chunks of other events/activities and plug them in. (You can see how this relates to transfer — the more chunks a new activity shares with a familiar one, the more quickly you can learn it.)

Support for the idea that event boundaries serve as anchors comes from several studies. For example, when people watched feature films with or without commercials, their recall of the film was better when there were no commercials or the commercials occurred at event boundaries. Similarly, when people watched movies of everyday events with or without bits removed, their recall was better if there were no deletions or the deletions occurred well within event segments, preserving the boundaries.

It’s also been found that we remember details better if we’ve segmented finely rather than coarsely, and some evidence supports the idea that people who segment effectively remember the activity better.

Segmentation, theory suggests, helps us anticipate what’s going to happen. This in turn helps us adaptively create memory codes that best reflect the structure of events, and by simplifying the event stream into a number of chunks of which many if not most are already encoded in your database, you save on processing resources while also improving your understanding of what’s going on (because those already-coded chunks have been processed).

All this emphasizes the importance of segmenting well, which means you need to be able to pinpoint the correct units of activity. One way we do that is by error monitoring. If we are monitoring our ongoing understanding of events, we will notice when that understanding begins to falter. We also need to pay attention to the ordering of events and the relationships between sequences of events.

The last type of memory I want to mention is semantic memory. Semantic memory refers to what we commonly think of as ‘knowledge’. This is our memory of facts, of language, of generic information that is untethered from specific events. But all this information first started out as episodic memory — before you ‘knew’ the word for cow, you had to experience it (repeatedly); before you ‘knew’ what happens when you go to the dentist, you had to (repeatedly) go to the dentist; before you ‘knew’ that the earth goes around the sun, there were a number of events in which you heard or read that fact. To get to episodic memory (your memory for specific events), you must pass through working memory (the place where you put incoming information together into some sort of meaningful chunk). To get to semantic memory, the information must pass through episodic memory.

How does information in episodic memory become information in semantic memory? Here we come to the process of reconstruction, of which I have often spoken (see my article on memory consolidation for some background on this). The crucial point here is that memories are rewritten every time they are retrieved.

Remember, too, that neurons are continually being reused — memories are held in patterns of activity, that is, networks of neurons, not individual neurons. Individual neurons may be involved in any number of networks. Here’s a new analogy for the brain: think of a manuscript, one of those old parchments, so precious that it must be re-used repeatedly. Modern technology can reveal those imperfectly erased hidden layers. So the neural networks that are memory codes may be thought of as imposed one on top of each other, none of them matching, as different patterns re-use the same individual neurons. The strongest patterns are the most accessible; patterns that are most similar (use more of the same neurons) will provide the most competition.

So, say you are told by your teacher that the earth goes around the sun. That’s the first episode, and there’ll be lots of contextual detail that relates to that particular event. Then on another occasion, you read a book showing how the earth goes around the sun. Again, lots of episodic detail, of which some will be shared with the first incident, and some will be different. Another episode, more detail, some shared, some not. And so on, again and again, until the extraneous details, irrelevant to the fact and always different, are lost, while those details that common to all the episodes will be strong, and form a new, tight chunk of information in semantic memory.

Event boundaries start off with an advantage — they are beginnings or endings, to which we are predisposed to attend (for obvious reasons). So they start off stronger than other bits of information, and by their nature are more likely to be vital elements, that will always co-occur with the event. So — if you have chosen your boundaries well (i.e., they truly are vital elements) they will become stronger with each episode, and will end up as vital parts of the chunk in semantic memory.

Let’s connect that thought back to my comment that the most important difference between those with ‘low’ working memory capacity and those with ‘high’ capacity is the ability to select the ‘right’ information and disregard the irrelevant. Segmenting your events well would seem to be another way of saying that you are good at selecting the changes that are most relevant, that will be common to any such events on other occasions.

And that, although some people are clearly ‘naturally’ better at it, is surely something that people can learn.

I’ve recently had a couple of thoughts about flow — that mental state when you lose all sense of time and whatever you’re doing (work, sport, art, whatever) seems to flow with almost magical ease. I’ve mentioned flow a couple of times more or less in passing, but today I want to have a deeper look, because learning (and perhaps especially that rewiring I was talking about in my last post) is most easily achieved if we can achieve "flow" (also known as being ‘in the zone’).

Let’s start with some background.

Mihaly Csikszentmihalyi is the man who identified and named this mental state, and he identified 9 components:

1. The skills you need to perform the task must match the challenges of the task, AND the task must exceed a certain level of difficulty (above everyday level).
2. Your concentration is such that your behavior becomes automatic and you have little conscious awareness of your self, only of what you’re doing.
3. You have a very clear sense of your goals.
4. The task provides unambiguous and immediate feedback concerning your progress toward those goals.
5. Your focus is entirely on the task and you are completely unaware of any distracting events.
6. You feel in control, but paradoxically, if you try to consciously hold onto that control, you’ll lose that sense of flow. In other words, you only feel in control as long as you don’t think about it.
7. You lose all sense of self and become one with the task.
8. You lose all sense of time.
9. You experience what Csikszentmihalyi called the ‘autotelic experience’ (from Greek auto (self) and telos (goal)), which is inherently rewarding, providing the motivation to re-experience it.

Clearly many of these components are closely related. More usefully, we can distinguish between elements of the experience, and preconditions for the experience.

The key elements of the experience are your total absorption in the task (which leads to you losing all awareness of self, of time, and any distractions in the environment), and your enjoyment of it.

The key preconditions are:

• the match between skills and task
• the amount of challenge in the task
• the clear and proximal nature of your goals (that is, at least some need to be achievable in that session)
• the presence of useful feedback.

Additionally, later research suggests:

• the task needs to be high in autonomy and meaningfulness.

Brain studies have found that this mental state is characterized by less activity in the prefrontal cortex (which provides top-down control — including that evidenced by that critical inner voice), and a small increase in alpha brainwaves (correlated with slower breathing and a lower pulse rate). This inevitably raises the question of whether meditation training can help you more readily achieve flow. Supporting this, a neurofeedback study improved performance in novice marksmen, who learned to shoot expertly in less than half the time after they had been trained to produce alpha waves. There are also indications that some forms of mild electrical stimulation to the brain (tDCS) can induce a flow state.

Some people may be more prone to falling into a flow state than others. Csikszentmihalyi referred to an ‘autotelic personality’, and suggested that such people have high levels of curiosity, persistence, and interest in performing activities for their own sake rather than to achieve some external goal. Readers of my books may be reminded of cognitive styles — those who are intrinsically motivated rather than extrinsically usually are more successful in study.

Recent research has supported the idea of the autotelic personality, and roots it particularly in the achievement motive. Those who have a strong need for achievement, and a self-determined approach, are more likely to experience flow. Such people also have a strong internal locus of control — that is, they believe that achievement rests in their own hands, in their own work and effort. I have, of course, spoken before of the importance of this factor.

There is some indication that autotelic students push themselves harder. A study of Japanese students found that autotelic students tended to put themselves in situations where the perceived challenges were higher than their perceived skills, while the reverse was true for other students.

Interestingly, a 1994 study found that college students perceived work where skills exceeded challenges to be more enjoyable than flow activities where skills matched challenges — which suggests, perhaps, that we are all inclined to underestimate our own skills, and do better when pushed a little.

In regard to occupation, research suggests that five job characteristics are positively related to flow at work. These characteristics (which come from the Job Characteristics Model) are:

• Skill variety

• Task identity (the extent to which you complete a whole and identifiable piece of work)

• Task significance

• Autonomy

• Feedback

These clearly echo the flow components.

All of this suggests that to consistently achieve a flow state, you need the right activities and the right attitude.

So, that’s the background. Now for my new thoughts. It occurred to me that flow might have something to do with working memory. I’ve suggested before that flow might have something to do with getting the processing speed just right. My new thought extends this idea.

Remember that working memory is extremely limited, and that it seems to reflect a three-tiered system, whereby you have one item in your immediate focus, with perhaps three more items hovering very closely within an inner store, able to very quickly move into immediate focus, and a further three or so items in the ‘backburner’ — and all these items have to keep moving around and around these tiers if you want to keep them all ‘alive’. Because they can’t stay very long at all in this system without being refreshed (through the focus).

Beyond this system is the huge database of your long-term memory, and that’s where all these items come from. Thus, whenever you’re working on something, you’re effectively circulating items through this whole four-tier system: long-term memory to focus to inner store to backburner and then returning to LTM or to focus. And returning to LTM is the default — if it’s to return to focus, it has to happen within a very brief period of time.

And so here’s my thesis (I don’t know if it’s original; I just had the idea this morning): flow is our mental experience of a prolonged period of balancing this circulation perfectly. Items belonging to one cohesive structure are flowing through the system at the right speed and in the right order, with no need to stop and search, and no room for any items that aren’t part of this cohesive structure (i.e., there are no slots free in which to experience any emotions or distracting thoughts).

What this requires is for the necessary information to all be sufficiently strongly connected, so that activation/retrieval occurs without delay. And what that requires is for the foundations to be laid. That is, you need to have the required action sequences or information clusters well-learned.

Here we have a mechanism for talent — initial interest and some skill produces a sense of flow; this motivating state is pursued by the individual by persevering at the same activity/subject; if they are not pushed too hard (which will not elicit flow), or held back (ditto), they will once again achieve the desired state, increasing the motivation to pursue this course. And so on.

All of which begs the question: are autotelic personalities created or made? Because the development of people who find it easier to achieve flow may well have more to do with their good luck in childhood (experiencing the right support) than their genetic makeup.

Is flow worth pursuing? Flow helps us persist at a task, because it is an intrinsically rewarding mental state. Achieving flow, then, is likely to result in greater improvement if only because we are likely to spend more time on the activity. The interesting question is whether it also, in and of itself, means we gain more from the time we spend. At the moment, we can only speculate.

But research into the value of mental stimulation in slowing cognitive decline in older people indicates that engagement, and its correlate enjoyment, are important if benefits are to accrue. I think the experience of flow is not only intrinsically rewarding, but also intrinsically beneficial in achieving the sort of physical brain changes we need to fight age-related cognitive decline.

So I’ll leave you with the findings from a recent study of flow in older adults, that has some helpful advice for anyone wanting to achieve flow, as well as demonstrating that you're never too old to achieve this state (even if it does seem harder to achieve as you age, because of the growing difficulty in inhibiting distraction).

The study, involving 197 seniors aged 60-94, found that those with higher fluid cognitive abilities (processing speed, working memory, visual spatial processing, divergent thinking, inductive reasoning, and everyday problem-solving) experienced higher levels of flow in cognitive activities, while those with lower fluid abilities experienced lower levels of flow. However, those with lower fluid abilities experienced higher levels of flow in non-cognitive activities, while those with higher fluid abilities experienced lower levels of flow.

High cognitive demand activities included: working, art and music, taking classes and teaching, reading, puzzles and games, searching for information. Low cognitive demand activities included: social events, exercise, TV, cooking, going on vacation. Note that the frequency of these activities did not differ between those of higher fluid ability and those of lower.

These findings reinforce the importance of matching skills and activities in order to achieve flow, and also remind us that flow can be achieved in any activity.