Natural Settings and Attention

A few weeks ago, I was able to embark on something very special, yet essentially cost-free: after lunch, a few good friends and I went for a walk around Lake Harriet. Although I spend a lot of time outside running for cross-country and track & field, rarely do I set aside the time to experience the outdoors at a relaxed, more mindful pace. It doesn’t matter how fit I get; in my mind, I can just absorb more from my surroundings while walking than while running. On this Saturday morning stroll, I delighted in noticing what the trees looked like, how blue the sky was, and how placid the frozen lake stood. I guess more than anything though, I noticed the words shared with my friends. My thinking and my responding seemed clearer and easier; I could more easily listen to and parse through their sentences, take more pause in contemplating and mouthing my own, and I could just simply reflect on our ideas, both their nuances and their larger scopes.

It would seem that there is something about walking in nature that is influencing how I think, or, more specifically, how I pay attention. Researchers as the University of Michigan would certainly think so. In one study, they were interested in the differences in the restorative affects on cognition in ‘natural’ settings versus urban settings. Their hypotheses were centered around Attention Restoration Theory (ART), which builds off research differentiating involuntary attention from directed attention—your attention is either grabbed by stimuli (involuntary), or you focus your attention in a top-down fashion (directed). The theory goes like this: inherently fascinating stimuli grab your attention involuntarily, yet modestly, so your directed-attention mechanisms can work alongside the attention dedicated to the bottom-up stimuli. In contrast, more intense stimuli grab your attention dramatically, so your directed-attention mechanisms have to compete with the stimuli themselves. If you want to use your directed-attention for cognitive tasks, it follows that you would be better suited in an environment with stimuli that give your attention room to work, rather than compete for your cognitive resources. The researchers argue that this is the difference between ‘natural’ environments and urban ones.

Thirty-eight University of Michigan students participated in the first experiment of two. Before the manipulation, participants filled out a scale to assess their mood, then they performed what’s called a backwards digit-span task; basically, they heard number sequences of varying length and they had to repeat them backwards in order—this a solid measure of directed-attention. To tax directed-attention even further, participants took a directed-forgetting task as well, in which they are presented with words to either remember or forget, and then they are asked to recall every word presented. This extra cognitive-fatigue was induced in hopes of making the environmental manipulation more sensitive to differences in performance.

Next, half the participants took a walk through the Ann Arbor Arboretum, and half walked through downtown Ann Arbor. Essentially, participants were walking by lots of pretty tress, or by heavy traffic and boring buildings. When they got back, they retook the backwards digit-span task and the mood scale, and then they answered questions about their walk. They came back a week later to do it all again, except they walked in the other condition’s route. Performance on the backwards digit-span task improved only in the ‘nature walk’ condition, controlling for the order of the walk conditions, mood, and even different weather conditions.

In the second experiment, 12 University of Michigan students took the mood scale and performed the backwards digit-span task, but they also completed the Attention Network Task (ANT). Basically, participants respond to the direction of a ‘target’ arrow on the middle of the screen (which way’s it pointing?), and performance reflects three components of attention: alerting, orienting, and executive. In the alerting component, a central cue (an asterisk) indicates when the target arrow is going to appear. Performance is measured by the difference in reaction time (RT) and in accurate identification of the arrow’s direction (ACC) when participants get the cue, or not. The orienting component measures differences in RT and ACC when participants get a cue indicating where the arrow will be on the screen (sometimes the target’s on the top, or the bottom), or not. Finally, the executive component measures differences in RT and ACC when the screen has either congruent (same direction) or incongruent (opposite direction) ‘flanking arrows’ next to the center target arrow.

After this battery of tasks, half the participants looked at ‘nature’ pictures (Nova Scotia!), and the other half looked at urban pictures (Ann Arbor, Detroit, Chicago). Then, they rated how much they liked the pictures, followed by another backwards digit-span task, a mood scale, and the ANT. They came back a week later and did it all again, but they looked at the other pictures. Improvements on the ANT and the backwards digit-span task were significant only after viewing ‘nature’ pictures, and only the in the executive component of the ANT. The researchers noted that if orienting and alerting components of the ANT would have improved significantly, increases in motivation or in effort, instead of attention, could have explained ‘nature’s’ influence on performance.

Alas, this is a neuroscience blog, not a cognition blog; where are they fMRIs and the rat models!? It’s actually a little difficult to find direct research on the neuroscience of interacting with nature. Unfortunately, fMRI studies require a little more persuasive, academically-sexy grant proposals than do cognitive and social psychology studies (something about expensive, intricately calibrated, high-powered magnets), so researchers have yet to stick nature walkers in an MRI machine and publish a paper about it. However, since most, if not all, cognitive measures have been studied both behaviorally and neurally, we can look at the neuroscience of ‘nature’ indirectly. In the case of the Michigan study cited above, the independence of the attention components measured in the Attention Network Task have been validated with neuroimaging. In one such study at the Weill Medical College of Cornell University, sixteen right-handed adults (mean age of about 27, half male, half female) completed the ANT while in an MRI scanner. Since many neuroimaging studies had looked at the brain areas that ‘light up’ during only 1 of 3 ANT components, these researchers wanted to look at every components’ associated brain activity in one study. Behaviorally, they found the usual results: no cues produced slower RTs than center cues, center cues produced slower RTs than spatial cues, and incongruent ‘flanking arrows’ produced slower RTs than congruent ones. There were no significant correlations between attention component scores (alerting, orienting, and conflict).

This is what participants viewed as they were performing the Attentional Network Task (ANT).

During the alerting component (a central cue indicates the target is coming), there was activation in the fronto-parietal cortex and the thalamus. The superior colliculus (involved in shifting gaze in the startle response) and the right temporal parietal junction were activated as well. Then, for the orienting component (a cue indicates where the target will be), the left and right parietal lobes lit up, as did the precentral gyrus (by the frontal eye field). The authors noted that there’s consensus on the activation prefrontal and parietal areas during orienting attention. Finally, for the executive/conflict component (the target is accompanied with flanking arrows), there was activity in the anterior cingulate plus the right and left frontal area, and the left and right fusiform gyrus. The anterior cingulate cortex has been demonstrated previously to be involved in conflict resolution (pay attention to one stimulus ignore another).

One of the main findings of this study was that these three facets of attention were activated in pretty independent brain regions. There were some notable exceptions, like the thalamus and the left fusiform gyrus were activated during both conflict and orienting, as were the left superior prefrontal gyrus and both the left and right fuisform gyrus. Overall though, this evidence suggests that directed attention activates generally independent regions of the brain. We can couple this with the evidence that performance on cognitive tasks that require directed attention are improved in ‘natural’ settings as opposed to urban settings, and this is associated with the anterior cingulate cortex and the left and right frontal cortices. Nothing suggests that other parts of the brain aren’t activated ever, at all, or even that other attention components of the ANT aren’t functionally involved in directed attention.  However, it is quite likely that ‘natural’ settings can measurably affect our cognitive functioning, and we can map these effects at the level of the brain.

References

  1. Berman, M. G., Jonides, J., & Kaplan, S. (2008). The cognitive benefits of interacting with nature. Psychological Science, 19(12), 1207-1212. doi:10.1111/j.1467-9280.2008.02225.x
  2. Fan, J., McCandliss, B. D., Fossella, J., Flombaum, J. I., & Posner, M. I. (2005). The activation of attentional networks. NeuroImage, 26(2), 471-479. doi:10.1016/j.neuroimage.2005.02.004
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