indexing (success and attention control)

I’ve just been reading Luke’s “Crash Course in the Neuroscience of Human Motivation.” It is a useful text, although there are a few technical errors and a few bits of outdated information (see [1], updated information about one particular quibble in [2] and [3]).

There is one significant missing piece, however, which is of critical importance for our subject matter here on LW: the effect of attention on plasticity, including the plasticity of motivation. Since I don’t see any other texts addressing it directly (certainly not from a neuroscientific perspective), let’s cover the main idea here.

Summary for impatient readers: focus of attention physically determines which synapses in your brain get stronger, and which areas of your cortex physically grow in size. The implications of this provide direct guidance for alteration of behaviors and motivational patterns. This is used for this purpose extensively: for instance, many benefits of the Cognitive-Behavioral Therapy approach rely on this mechanism.



I – Attention and plasticity

To illustrate this properly, we need to define two terms. I’m guessing these are very familiar to most readers here, but let’s cover them briefly just in case.

First thing to keep in mind is the plasticity of cortical maps. In essence, particular functional areas of our brain can expand or shrink based on how often (and how intensely) they are used. A small amount of this growth is physical, as new axons grow, expanding the white matter; most of it happens by repurposing any less-used circuitry in the vicinity of the active area. For example, our sense of sight is processed by our visual cortex, which turns signals from our eyes into lines, shapes, colors and movement. In blind people, however, this part of the brain becomes invaded by other senses, and begins to process sensations like touch and hearing, such that they become significantly more sensitive than in sighted people. Similarly, in deaf people, auditory cortex (part of the brain that processes sounds) becomes adapted to process visual information and gather language clues by sight.

Second concept we’ll need is somatosensory cortex (SSC for short). This is an area of the (vertebrate) brain where most of the incoming touch and positional (proprioceptive) sensations from the body converge. There is a map-like quality to this part of our brain, as every body part links to a particular bit of the SSC surface (which can be illustrated with silly-looking things, such as the sensory homunculus). More touch-sensitive areas of the body have larger corresponding areas within the SSC.

With these two in mind, let’s consider one actual experiment [4]. Scientists measured and mapped the area of an owl monkey’s SSC which became activated when one of his fingertips was touched. The monkey was then trained to hold that finger on a tactile stimulator – a moving wheel that stimulates touch receptors. The monkey had to pay attention to the stimulus, and was rewarded for letting go upon detecting certain changes in spinning frequency. After a few weeks of training, the area was measured again.

As you probably expected, the area had grown larger. The touch-processing neurons grew out, co-opting surrounding circuitry in order to achieve better and faster processing of the stimulus that produced the reward. Which is, so far, just another way of showing plasticity of cortical maps.

But then, there is something else. The SSC area expanded only when the monkey had to pay attention to the sensation of touch in order to receive the reward. If a monkey was trained to keep a hand on the wheel that moved just the same, but he did not have to pay attention to it… the cortical map remained the same size. This finding has since been replicated in humans, many times (for instance [5, 6]).

Take a moment to consider what this means.

A man is sitting in his living room, in front of a chessboard. Classical music plays in the background. The man is focused, thinking about the next move, about his chess strategy, and about the future possibilities of the game. His neural networks are optimizing, making him a better chess player.

A man is sitting in his living room, in front of a chessboard. Classical music plays in the background. The man is focused, thinking about the music he hears, listening to the chords and anticipating the sounds still to come. His neural networks are optimizing, making him better at understanding music and hearing subtleties within a melody.

A man is sitting in his living room, in front of a chessboard. Classical music plays in the background. The man is focused, gritting his teeth as another flash of pain comes from his bad back. His neural networks are optimizing, making the pain more intense, easier to feel, harder to ignore.



II – Practical implications: making and breaking habits, efficacy of CBT

Habitual learned behaviors are often illustrated with the example of driving. When we are learning to drive, we have to pay attention to everything: when to push the pedals, when to signal, where to hold our hands… A few years later, these behaviors become so automatic, we hardly pay attention at all. Indeed, most of us can drive for hours while carrying on conversations or listening to audiobooks. We are completely unaware, as our own body keeps pushing pedals, signaling turns, and changing gears.

We can therefore say that driving behaviors, through practice and attention, eventually become automatic – which is, most of the time, a good thing. But so do many other things, including some destructive ones we might want to get rid of. Let’s take a simple one: nail biting. You are reading, or watching a movie, or thinking, or driving… when you suddenly notice some minor pain, and realize that you have chewed your nail into a ragged stump. Ouch!

You catch yourself biting, you stop. Five minutes later, you catch yourself biting again. You stop again. Repeat ad infinitum, or ad nauseam, whichever comes first.

Cognitive-Behavioral Therapy has a highly successful approach for breaking habits, which requires only a very subtle alteration to this process. You notice that you are biting your nails. You immediately focus your attention on what you are doing, and you stop doing it. No rage, no blaming yourself, no negative emotions. You just stop, and you focus all the attention you can on the act of stopping. You move your arm down, focusing your attention on the act of movement, on the feeling of your arm going down, away from your mouth. That’s it. You can go back to whatever you were doing.

Five minutes later, you notice yourself biting your nails again. You calmly repeat the procedure again.

By doing this, you are training yourself to perform a new behavior – the “stop and put the hand down” behavior – which is itself triggered by the nail-biting behavior. As you go along, you will get better and better at noticing that you have started to bite your nails. You will also get better and better at stopping and putting your hand down. After a while, this will become semi-automatic; you’ll notice that your hand went to your mouth, a nail touched your tooth, and the hand went back down before you could do anything. Don’t stop training: focus your attention on the “stop and drop” part of the action.

After a while, the nail-biting simply goes away. Of course, the more complex and more ingrained a habit is, the more effort and time will be needed to break it. But for most people, even strong habits can be relatively quickly weakened, or redirected into less destructive behaviors.

It’s probably obvious that habits can be created in this way as well. We don’t become better at things we do – we become better at things we pay attention to while we’re doing them. If you want to make exercise a habit, your efforts will be much more effective if you focus your attention on your exercise technique, rather than repeatedly thinking how painful and tiring the whole process is.

There is also a direct implication for training in any complex skill. Start with the well-known learning curve effect: we gain a lot of skill relatively quickly, and then improvements slow down incrementally as we approach our maximum potential skill level. It is relatively easy to go from a poor to a mediocre tennis player; it is much, much harder to go from mediocre to good, and even harder to go from good to excellent.

Complex skills have many different aspects, which we usually attempt to train simultaneously. We can become very good at some, while staying poor at others. The optimal approach would be to focus most of our attention on those aspects where our abilities are weakest, since smaller investments of time and effort will lead to larger improvements in skill.

To keep with the tennis metaphor, one could become very good at controlling the ball direction and spin, while still having a poor awareness of the opponent’s position. Simply playing more will improve both aspects further, but our hypothetical player should optimally try to focus her attention on opponent awareness [7].

Finally, there is another implication which I’ll leave as an exercise for the readers. Mindfulness meditation, which essentially boils down to training control of attention, has been shown to exert a positive effect on many, many different things (lowering depression, anxiety and stress, as well as improving productivity [8, 9, 10]). In the light of the previous text, one obvious reason why better control over attention can produce all these beneficial effects should immediately come to mind.

Here’s a brain teaser: Your task is to move a single line so that the false arithmetic statement below becomes true.

IV = III + III

Did you get it? In this case, the solution is rather obvious – you should move the first “I” to the right side of the “V,” so that the statement now reads: VI = III + III. Not surprisingly, the vast majority of people (92 percent) quickly solve this problem, as it requires a standard problem-solving approach in which only the answer is altered. What’s perhaps a bit more surprising is that nearly 90 percent of patients with brain damage to the prefrontal lobes — this leaves them with severe attentional deficits, unable to control their mental spotlight — are also able to find the answer.

Here’s a much more challenging equation to fix:

III = III + III

In this case, only 43 percent of normal subjects were able to solve the problem. Most stared at the Roman numerals for a few minutes and then surrendered. The patients who couldn’t pay attention, however, had an 82 percent success rate. What accounts for this bizarre result? Why does brain damage dramatically improve performance on a hard creative task? The explanation is rooted in the unexpected nature of the solution, which involves moving the vertical matchstick in the plus sign, transforming it into an equal sign. (The equation is now a simple tautology: III = III = III.) The reason this puzzle is so difficult, at least for people without brain damage, has to do with the standard constraints of math problems. Because we’re not used to thinking about the operator, most people quickly fix their attention on the roman numerals. But that’s a dead end. The patients with a severe cognitive deficit, in contrast, can’t restrict their search. They are forced by their brain injury to consider a much wider range of possible answers. And this is why they’re nearly twice as likely to have a breakthrough.

Of course, this doesn’t mean you should take a hammer to your frontal lobes. Being able to direct the spotlight of attention is a crucial talent. However, the creative upside of brain damage — the unexpected benefits of not being able to focus — does reveal something important about the imagination. Sometimes, it helps to consider irrelevant information, to eavesdrop on all the stray associations unfolding in the far reaches of the brain. We are more likely to find the answer because we have less control over where we look.

This helps explain a new study led by Mareike Wieth at Albion College. The scientists surveyed 428 undergrads about their circadian habits, asking them whether they were more productive and alert in the morning or evening. As expected, the overwhelming majority were night owls, which is why they studiously avoided 9 a.m. classes. Then, the scientists gave the students a series of problem-solving tasks. Half of these tasks were creative insight puzzles, in which the answer arrives suddenly and seemingly out of nowhere. Here’s a sample insight puzzle:

A man has married 20 women in a small town. All of the women are still alive and none of them are divorced. The man has broken no laws. Who is the man?

And here’s another classic puzzle:

Marsha and Marjorie were born on the same day of the same month of the same year to the same mother and the same father, yet they are not twins. How is that possible?

Did you solve these brain teasers? (The answers are, respectively, priest and triplets.)

The other half of the problems given to the students were standard analytic problems, such as long-division and pre-algebra equations. These questions don’t require insights. Instead, they benefit from ordinary focus, as people grind out the answer and check to make sure it’s right. The subjects were given four minutes to solve each problem. Half of them were tested early in the morning (8:30 a.m.) and half were tested in the late afternoon (around 5 p.m.).

The results are a testament to the creative virtues of grogginess. When people were tested during their “least optimal time of day” — think of that night owl stumbling into the lab in the early morning — they were significantly more effective at solving insight puzzles. (On one problem, their performance increased by nearly 50 percent.) Performance on the analytic problems, meanwhile, was unaffected by the clock.

The larger lesson is that those sleepy students, like a brain-damaged patient, benefit from the inability to focus. Their minds are drowsy and disorganized, humming with associations that they’d normally ignore. When we need an insight, of course, those stray associations are the source of the answer.

One last piece of evidence: A brand-new study by scientists at the University of Illinois at Chicago compared performance on insight puzzles between sober and drunk students. (They were aiming for real intoxication, giving students enough booze to achieve a blood alcohol level of 0.075.) Once the students achieved “peak intoxication” the scientists gave them a battery of word problems – they’re known as remote associate tests – that are often solved in a moment of insight. Here’s a sample problem. Your task is to find the one additional word that goes with the following triad of words:

Cracker Union Rabbit

In this case, the answer is “jack.” According to the data, drunk students solved more of these word problems in less time. They also were much more likely to perceive their solutions as the result of a sudden insight. And the differences were dramatic: The alcohol made subjects nearly 30 percent more likely to find the unexpected solution.

Once again, the explanation for this effect returns us to the benefits of not being able to pay attention. The stupor of alcohol, like the haze of the early morning, makes it harder for us to ignore those unlikely thoughts and remote associations that are such important elements of the imagination. So the next time you are in need of insight, avoid caffeine and concentration. Don’t chain yourself to your desk. Instead, set the alarm a few minutes early and wallow in your groggy thoughts. And if that doesn’t work, chug a beer.