Use it or lose it, they say. The saying holds not only for muscle fitness, but also for the brain. The Romans already knew that 'mens sana in corpore sano' and today we know that both physical and mental fitness, exercise and training can stave off many signs of aging. Even debilitating diseases such as Alzheimer's disease can be delayed, or at least their symptoms reduced by staying physically and mentally fit and active. I recently handled a manuscript in my function as Academic Editor for the journal PLoS One, which suggests that the analogy goes even further.

The paper entitled "Endogenous Human Brain Dynamics Recover Slowly Following Cognitive Effort" has now been published and I thought it's worth highlighting.

The authors of this study used functional magnetic resonance imaging or fMRI for short (colloquially: brain scanner). In 2001 Marcus Raichle coined the term default network for the brain areas that were discovered to be active when the test subjects in the scanner were at rest, i.e. not occupied with any task. The existence of this default network is a puzzle, as one would assume the brain would reduce its activity in the absence of any explicit tasks, given the high energetic cost of neural activity. Instead, the brain keeps running at ~99% of maximum load, even when we're not doing anything. This is precisely where the brain isn't like a muscle: muscles don't keep on contracting when we rest.

But I wanted to explain how the current paper extends the analogy.
Well then. Barnes et al. evaluated brain activity in a rest-task-rest experiment. This means they continuously scanned the brains of the participants before, during and after a cognitively demanding working memory task. Each participant went into the scanner twice, once with the task level set to easy and once with the level set to difficult. The way they analyzed their data is another way in which the brain is like a muscle, the heart muscle. Like heart beat and other physiological measures, the slow fMRI fluctuations also show fractal scaling behavior. We also found similar mathematics in our analysis of spontaneous fly behavior which was one of the reasons I became interested in the default network in general and in this manuscript in particular. The authors looked at one such measure, the Hurst exponent. Comparing this H-exponent before and after the difficult and easy task, respectively, Barnes et al. found that it can take several minutes until the H-values reach pre-task values after the task. Moreover, this time was extended after high cognitive load, compared to the low cognitive load task.

These results make the brain even more like a muscle: after we use it, it takes some time for the brain to come back to the state in which it was before we used it. I'm not sure fatigue would be the right word to describe what is going on there, but the practical implications of this work are clear: what if you have designed an experiment where the rest periods between the tasks are shorter than the few minutes found in this study? Will the earlier tasks influence the brain scanner readings of the later tasks?

But I found these results interesting for a much more general reason. The function of the default network is still a mystery. We know it's altered in patients, ranging from Alzheimer’s disease, autism, depression, schizophrenia, and attention-deficit-hyperactivity disorder to post-traumatic stress disorder, Tourette syndrome or amyotrophic lateral sclerosis. It's not surprising that it is thought to underly daydreaming and creativity. As such it may be involved in planning and strategizing. Mechanistically, the default network seems to be competing with the task related-networks in a sort of push-pull system: whenever we perform a task, the default network is suppressed and the network required for the task is enhanced. As soon as the task is over, the default network comes back online (albeit slightly disturbed from the task for some minutes as Barnes  et al. show). Moreover, sometimes, the default network comes back during the task. The instances where the default network is 'pushing through' are usually the ones where the participant is making an error. Even if the participant is not making any errors, there seems to be a little default network activity left during the task and the variability in these fluctuations explain about 80% of the variability in the behavior during the task.

All of this looks a lot like internal and external processing are competing for the computing capacity of the brain. Evolutionarily, this hypothesis would fit a lot of circumstantial evidence from other, basically unrelated fields. For instance, I recently blogged about a study which suggested that the ancestral organization of behavior may have been motor-sensory or output-input, meaning that stimuli only modulate ongoing activity, rather than eliciting behavior directly. This organization would also fit the solution of the explore-exploit dilemma underlying habit formation described in another recent blog-post. According to the hypothesis, the default network would underlie (at least to some extent) exploratory behavior (or at least the behavioral variability required for exploration) and repetition (or stress) would suppress the default network when habits are formed or executed. It also fits with our fly data showing that the variability in spontaneous behavior is decreased when the flies are flying towards an object as opposed to not having any visual cues.
Could it be that this push-pull relationship between external and internal processing is not just a special feature of mammalian or even primate brains, but of all brains? It could explain why brains seem to passively react to external stimuli in one set of experiments (default network suppressed), but to actively explore the environment in other experiments (default network active). It would mean that brains are indeed not input-output devices, but neither are they output-input devices. Maybe they are both at the same time and neither function alone would lead to evolutionarily stable brains?

To answer this question we need to look for default networks also in other brains. Unfortunately, this is technically somewhat tricky and the microscope I'd need to do that in flies costs about half a million Euros. I'm in the process of finding out how and where I have to apply to get my hands on one of these. If indeed this push-pull organization were universal, it would be the first evidence-based formulation of a general principle of brain function. It would fit a host of observations from a variety of different fields and model organisms. In what exciting times we are living!

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Barnes, A., Bullmore, E., & Suckling, J. (2009). Endogenous Human Brain Dynamics Recover Slowly Following Cognitive Effort PLoS ONE, 4 (8) DOI: 10.1371/journal.pone.0006626
Maye, A., Hsieh, C., Sugihara, G., & Brembs, B. (2007). Order in Spontaneous Behavior PLoS ONE, 2 (5) DOI: 10.1371/journal.pone.0000443