Connectivity

Certainly the brain’s billions of neurons create an energy-producing system, but it is also an astonishingly complex self-adjusting communication system. A cellular phone network has the potential to facilitate communication over a great area, but if every time I call someone his phone is turned off and when he tries to call me back, mine is out or range, the communication doesn’t happen very well.

Measuring Connectivity

Neurons in the brain and throughout the body link with thousands of others via direct electrical connections and synapses which pass chemical signals. Each neuron has a tree of dendrites which receive messages from other neurons in its network. Each message tells the neuron pass along (excitatory) or block (inhibitory) it. These messages are summed on the surface of the neuron’s cell body—its energy-producing plant. The result then passes down the axon—the cable leading away from the cell body—to branches which link with the downstream neurons in the network.

There are three primary measures of the efficiency of these connections which we will discuss here.

Phase

Each neuron builds an electrical charge within the cell body, discharge that pulse then rests before starting the cycle again. Of course the signal of an individual neuron is too small to register on an EEG unless it joins with a significant group all firing and resting at the same time. One way we measure connectivity is by looking at the timing relationship between multiple pools of neurons. If two pools fire at the same time and recharge at the same time, we say we say that they are operating in phase. Communication among pools which share this timing relationship is more efficient and effective.

There are two primary ways pools of neurons can fire in phase. They can work together on the same task, or both pools can resonate to a signal from a third source. Since there are millions of these pools distributed throughout the landscape of the brain, the chance of any two being involved in the same task at the same time is relatively small. However, there are very good reasons why pools of neurons might be linked to a central source—a rhythm generator—and receive the same pulse at the same time.

Neurons need not be firing in phase, however. They may fire at different frequencies. If one pool of neurons is firing four times a second (Theta) and another is firing 14 times per second (Beta) they may occasionally fire in phase, but most of the time they will not. It’s also possible for pools of neurons to fire at the same frequency but without the timing relationship. If one pool discharging at the moment the other is recharging, and vice-versa, they are 180 degrees out of phase. Communication among such pools is less efficient. Phase is measured in the number of degrees between the firing point of one pool and the firing point of another. The smaller this so-called “phase-angle”, the closer the neurons are to effective communication.

Coherence

In addition to their timing relationship, we can measure the stability of the link between pools of neurons using coherence. Two pools of neurons may be firing perfectly in phase, or they may be firing 180 degrees out of phase, but it is their ability to sustain this relationship which coherence measures. One pool of neurons firing four times per second and another firing 16 times per second will have a measurable phase relationship 4 times per second, but the rest of the time there will be no clear timing relationship between them. Two pools of neurons firing at the same frequency in phase may sustain that condition over a. second or more. If one pool is consistently bursting into another frequency, they will not sustain coherence. Coherence is not dependent on how many neurons are firing in each pool or all the phase relationship between them. It simply measures how stable the relationship is. Coherence is usually measured from 0-1 (as a decimal) or 0-100 (as a percentage).

One way to think of coherence is the measure of our ability to predict what we will find in a second pool of neurons based on what we find in the first. If two pools are 100% coherent, and I know that the second pool is in phase, if the first pool is discharging at this moment, I can say with 100% certainty that the second pool will also be firing. If the two pools have very low coherence, regardless of what I see happening in the first, I have zero chance of accurately predicting what the second will be doing.

Synchrony

Synchrony is the most powerful measure of connectivity in the brain. Synchrony means that 2 pools of neurons are firing coherently in phase. Two pools may be coherent, sharing a stable relationship, but 180 degrees out of phase. They are not synchronous. We’ll see in the upcoming sections that this phase-synchrony is a normal characteristic of pools of neurons in specific frequencies.  We can tell a great deal about how effectively pools of neurons are able to work independently, share information and rest when no task is at hand by looking at their connectivity.