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 It is a useful text, although there are a few technical errors and a few bits of outdated information (see [1], updated information about one particular quibble in [2] and [3]).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.
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References
[1] I have several quibbles, but let’s stick to one (to prevent this note from becoming longer than the above text). Luke presents a view of dopamine reward system which is stuck in the early 2000’s – ages ago by the pace of neuroscientific research. Dopamine actually has a very, very complex effect on motivation, and is able to strengthen or weaken single synaptic connections based on timing of the signal relative to the signals from the sensory systems. Endocannabinoid neurotransmission (i.e. signaling through chemicals that stimulate the same receptors that are affected by active ingredients in marijuana) is being shown as more and more important in this system as well, and the relative timing of the two signals appears critical.
The complexity of the effects increases by several orders of magnitude when networks are concerned. Consider this: a planning-related network in the prefrontal cortex can influence the motivation-generating networks in the striatum. A stimulus from the outside is perceived by the sensory networks and transmitted to the dopamine system, to the prefrontal cortex, and to the striatum. The same dopamine signal can, depending on exact timing of action potential bursts, strengthen synapses in the striatum, while weakening synapses in the prefrontal cortex. The result? The link between the stimulus and the actual motivation can increase or decrease, depending on exact connectivity between networks, on the relative sensitivity and on the exact topology of the meta-network in question.
See the following two references for a broad overview of the subject area.
[2] Calabresi P, Picconi B, Tozzi A, Di Filippo M. "Dopamine-mediated regulation of corticostriatal synaptic plasticity" Trends Neurosci. 2007 30(5):211-9.
[3] Wickens JR. "Synaptic plasticity in the basal ganglia" Behav Brain Res. 2009 199(1):119-28.
[4] Recanzone GH, Merzenich MM, Jenkins WM, Grajski KA, Dinse HR. "Topographic reorganization of the hand representation in cortical area 3b of owl monkeys trained in a frequency-discrimination task" J Neurophysiol. 1992 67(5), 1031-56.
[5] Heron J, Roach NW, Whitaker D, Hanson JV. "Attention regulates the plasticity of multisensory timing" Eur J Neurosci. 2010 31(10), 1755-62.
[6] Stefan K, Wycislo M, Classen J. “Modulation of associative human motor cortical plasticity by attention” J Neurophysiol. 2004 92(1), 66-72.
[7] I’m not finding good papers directed exactly on this point, so I’ll just throw this out as a personal opinion (although I’ll say it appears well supported by indirect research). We all like to appear competent and skillful, especially in those areas where we have invested a lot of time and effort. This can lead to a bias where we focus on using those aspects of complex skills we are best at, and training those aspects most intensely. In other words, a tendency appears to exist to do exactly the opposite of what we should be doing. (If anyone has encountered a name for this bias, or has references to suggest, I would be very grateful to hear from you.)
[8] Brown KW, Ryan RM. "The benefits of being present: mindfulness and its role in psychological well-being" J Pers Soc Psychol. 2003 84(4):822-48.
[9] Davidson RJ, Kabat-Zinn J, Schumacher J, Rosenkranz M, Muller D, Santorelli SF, Urbanowski F, Harrington A, Bonus K, Sheridan JF. "Alterations in brain and immune function produced by mindfulness meditation" Psychosom Med. 2003 65(4):564-70.
[10] Shao RP, Skarlicki DP. "The role of mindfulness in predicting individual performance" Canadian J of Behavioral Sci 2009 41(4): 195–201.
An excellent question.
I would say that the effect is most likely very relevant for higher-level skills, for the following reasons:
The effect has been shown for motor planning, for estimation of timing, and for several other plastic features. Thus, it isn't limited to sensory processing alone.
If we assume a "worst case scenario" in which the higher-level networks are themselves exempt from this effect, we still have to expect an indirect improvement. The reason for this is relatively simple: higher-level mental behaviors are based on metanetworks that interconnect subnetworks which certainly are subject to attentional modulation.
I would say that transferability of the effect would depend on how transferable the trained skill is itself. If you train yourself to be really good at the go/no-go task where a red dot appears on the screen, you'll get good at it, and it won't make a difference anywhere else in your life - no matter how much attention you paid while training. If you train yourself to enunciate words better (which is predominantly motor training, and the attention effect has been shown to make a huge difference), this could transfer into many other higher-level behaviors which can be improved by speaking clearly.
Similar indirect improvements would also apply in case of music (tone discernment training is attention-dependent) and chess (spatial combinatorial thinking is dependent on attention-trainable circuitry).
So, in the worst case, this is still highly applicable, by choosing your training targets wisely.
For a molecular pathway overview, see, for instance, Conner et al. in Neuron, Vol. 38, 819–829, 2003.
Therefore, the null hypothesis based on the data we currently have is that we should see this effect in higher-level skills directly, as well as indirectly.
I don't think it means much that the molecular systems involved are universal. The fact that wires are transferring electrons in two different computers doesn't mean the computers are programmed the same way.