The metastable brain

I just finished reading a fascinating theoretical paper that addresses how the brain coordinates its activity on various spatial scales from the individual neuron, to local ensembles of neurons working together, to widespread networks within the brain. The article is called “The metastable brain”, and is published in January’s issue of the journal Neuron. The authors, Emmanuelle Tognoli and Scott Kelso, address themselves to a central paradox that arises in our attempts to understand how the brain works, namely, how different areas of the brain can get together and work in concert for the purpose of doing a task or a computation, without the brain becoming locked into a rut that renders it inflexible and unresponsive to changing circumstances. This is an old theoretical problem that has gone by a number of names and been formulated in various contexts. Stephen Grossberg of Boston University has referred to something similar in his articulation of the stability-plasticity dilemma. How does a brain balance between continuity and preservation of function on the one hand, and responsiveness and adaptation on the other?

Tognoli and Kelso draw on principles from nonlinear dynamics (what used to be popularly referred to as “chaos theory”) in articulating their vision of the brain. They view the brain as containing numerous oscillating elements (think of elements as simply being physically located functional entities) that exist on different spatial scales, from individual neurons, to local ensembles of neurons working together in the same neighborhood, to functional networks reaching across the whole brain. The rising and falling of these oscillating elements can synchronize with that of other elements, or it can be unsynchronized and independent.  The authors postulate that the brain is organized to be a “metastable” system, that is, a system that is perpetually balanced between integrative influences (those that pull neural elements into synchrony) and segregative influences (those that pull the elements out of association with each other). This leads to an immensely flexible regime, where neural elements can be called into collective action and form into functional units rapidly, and with minimal input of energy from outside; then, just as easily, they can fall back out of tight association with each other when the job is done, or when they’re needed for some other job.

The authors adduce empirical evidence from various spatial scales showing that the brain at each of those scales shows the properties, mathematically, of a metastable system. They note that because of the properties of these systems, what we observe as the oscillations—and coupling/uncoupling behavior or phase locking/unlocking of the oscillations—at one spatial scale doesn’t necessarily tell us everything about what’s happening at other spatial scales. For example, the oscillations of the EEG may show bursts of activity or periods of relative silence, but the silence can be misleading, because there may be plenty going on underneath (at smaller scales), but it isn’t visible as EEG because it’s either not coordinated, or it is coordinated but is out of phase and therefore self-cancelling. The authors recommend that researchers try to find ways to study brain activity at multiple spatial scales simultaneously, so that they can better characterize the relationships that form in space and time.

As someone who is fascinated by EEG (witness Choratech’s employment of QEEG and neurofeedback), I find papers like this to be exciting. I’ve long believed that the oscillating patterns observable in the EEG are reflective of something fundamental about how the brain self-organizes. Neuroscientists seem to be coming to the same conclusion.

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