EEG Activation

As with any other part of the body, it is important for us to know how things change in the brain between resting, idling and activated states. When we assess brain activation, it is common look at eyes-closed, eyes-open Baseline and task conditions.

Eyes closed

Ordinarily we expect to see the brain with eye closed at rest, though not sleeping. In most cases this appears as a brain dominated by the Alpha frequency, especially in the rear. Slower Theta frequencies might also normally be higher in this relaxed, resting state of low external stimulation. The faster Beta speeds, used for performing cognitive functions, would normally be quite low.

However, it is not uncommon to see a highly-activated brain, with a lot of Beta or even High-Beta frequencies when a person is asked to close her eyes and relax. If the brain has adopted a hyper-vigilant strategy of protecting itself against expected danger, a situation in which it is asked to operate without the ability to see danger coming would be very frightening. Some people with such a brain cannot keep their eyes closed.

It is also not uncommon to see a brain which does not easily enter the resting-ready Alpha state with eyes closed. This may be a very fast or very slow-dominant brain.

Eyes open baseline

In the baseline state, we ask a client to sit with eyes open but fixed (not glancing around or performing any functions). This is very much like the eyes closed state, except that there is visual stimulation entering the brain. Normally we expect that Alpha levels will drop 30-50%, though meditators frequently are able to maintain high levels of alpha in this eyes open resting state as well. Levels of fast Beta frequencies relative to slower Theta frequencies also often rise. An individual who is able to remain calm and relaxed when there is no task at hand will demonstrate this in the eyes-open baseline. People who are vigilant or anxious may actually show reductions in high levels of fast or very fast Beta activity, because they can now see what is around them.

Task performance

When we ask a specific set of brain networks to go to work, we expect faster activity in the useful Beta range will appear more strongly in relation to slower Theta frequencies. We also expect to see Alpha levels drop lower or remain low at task.

As mentioned earlier, a functional brain will often actually produce less activity when it is working than it does at rest. It is also very common for a hyper-vigilant brain to shift from very high levels of fast Beta with eyes closed or even eyes open baseline to drop to functional levels when there is a task to perform. The more functional the brain is, the more likely it is that in performing a routine task it shows very little level of activation.

Frequency comparisons

Rather than looking at individual frequencies in comparing these states, we often look at relationships among them as a way of seeing how the brain activates.

The relationship between Alpha and Theta—the resting ready vs the Twilight internal frequencies—can be very helpful in showing how awake a brain is in each state. Alpha to Theta ratios are generally expected to be highest in the back of the brain and with eyes closed. We ordinarily see them drop as we move toward the front of the brain and especially when the eyes are opened or the brain is performing a task.

Ratios of internal, creative/intuitive Theta divided by faster logical/rational Beta speeds are often helpful in identifying how brain activation changes when it shifts from a resting eyes-open to a task state.

There are a number of other ratio comparisons which we use to look at an individual brain compared against itself to determine its style of activation. These ratios, like those mentioned earlier in the chapter on front/back and left/right comparisons, often reliably tell us a great deal about the types of problems a specific brain may experience and help to focus attention on potentially important training issues.

Because the ratio compares two types of activity, it can show us relative changes which can easily be missed in comparing a single frequency’s changes against some average value calculated in a database.

So far we have looked at overall patterns of frequency. We’ve also looked at the locations of specific frequencies in space. Activation shows us how frequencies change over time as level of demand changes.  These are measures of energy.  In our next section we will look at how areas of the brain connect and communicate among themselves.