Art Kramer on the Link between Physical Fitness & Cognition
Scientist Interview: October 2011
How did you measure efficiency of brain
networks?
Pretty crudely at the time. We've gotten much better at that, as has the field. We measured differences in the activation level of different brain regions, which we knew from previous studies contributed to good performance on a task. And we used as a baseline a young adult group. What we found was that as the older adults become more fit, their brain networks, the activation patterns that predicted performance, became more like that of the 20 to 30 year olds, even though our study group was 60 to 80 years of age.
What technologies were you using to do
this?
MRI and fMRI. MRI allows us to measure anatomy and fMRI allows us to measure function or hemodynamic change from which we can then infer neuronal changes. We also use a variety of other technologies—EEG, near-infrared spectroscopy among others. We do multi-modal imaging. But the focus in that paper was MRI and fMRI.
Things have changed a lot over the years. We had a paper last year in one of the Frontiers journals, in which we used network analysis procedures to examine changes in connectivity in networks that support various cognitive behaviors.
We know that as we become older our brain networks are less well connected and that's one reason we believe that don't do so well on a number of cognitive skills and tasks, and we found more recently in a paper in 2010 that older adults who become more fit in these randomized controlled trials, more fit in the cardio-respiratory sense, have greater connectivity in networks that predict better performance (Voss MW, et al., "Functional connectivity: A source of variance in the association between cardiorespiratory fitness and cognition?" Neuropsychologia 48[5]: 1394-1406, April 2010).
Why do you think this 2004 PNAS paper was
so influential?
I think because it was one of the first that tied together the neuroscience to the cognitive psychology to the fitness intervention, as a way to start bridging the gap between human work and animal models.
Your two other most highly cited studies are both
fMRI studies of something called Stroop tasks. Could you explain those
to us?
Those studies were more focused on a specific task, not on the topic of cognitive or brain enhancement or plasticity. In these papers we examined the cognitive and brain mechanisms that enable us to selectively focus on some information in the environment and ignore other information.
A Stroop task is very simple. You are presented with a set of words, and they are painted in different colors. The word blue can be painted in blue or painted in red, and you have to just verbalize or respond manually to the color—not to the word, the color. But when the color the word is painted in and the word itself are different, people have difficulty with that, at both ends of the age continuum. Older folks have more difficulty because they can't inhibit the semantics to process the color information.
"I enjoy understanding the mechanisms underlying the basis of some of these effects, but maybe I even enjoy more, or at least as much, the ability to affect the lives of people in a positive way."
In these studies we examined the differences in networks, between young and older adults, that support effective selective attention and inhibition.
How rapidly has the state of knowledge in your
field evolved since those papers came out? And in terms of cognitive
enhancement, is it paying off in methods we all can use to up our
cognitive abilities—or at least prevent their decline as we
age?
In some ways we learned from Thorndike back over 100 years ago that it's really hard to get general transfer from new trained tasks and skills to untrained tasks. The goal is to produce broad or generalized transfer. If you google "brain training," you'll come up with dozens, if not hundreds, of products you can buy these days. And these products imply, if not directly state, that if you practice a particular task or set of tasks you'll be better at many, many other tasks as well. It's really hard to find evidence of that, which is what we mean by the term "generalized transfer."
What's interesting, however, is that in fitness training, you're not training cognition specifically, but you improve cognition broadly, the kind of goal of a lot of the cognitive training. The reason you probably do that is you change a number of the molecular and cellular building blocks of cognition in a broad sense with fitness training. Whereas when you're training memory, you might improve memory but not decision making and vice versa. You tend to train specific networks.
So I think we've started to learn, from non-human animal studies, about the differences at the molecular and cellular and systems levels of different kinds of training, and effects on enhancing learning broadly or specifically or plasticity over the years. Neuroscience techniques have been instrumental in helping us focus in on the mechanisms and the networks which support learning. Then you can ask questions about whether it's possible to enhance these networks and whether enhancing the networks will enhance learning or generalize to different kinds of skills or tasks that use either the same networks or overlapping networks.
Do you understand what mechanisms are actually
driving this improvement?
At some level, although not at an absolute reductionist level. There are a multitude of changes in the brain and we know this from the animal work. We know there are increases in various neurotransmitters, like dopamine. There are increases in various neurotrophins, like brain derived-neurotrophin and insulin-like growth factor 1, and a variety of other things that then affect the number of synapses and how quickly you can form them.