I finished reading Chapter 3 in Practical Approach To Electroencephalography. Chapter 3 introduces common EEG terms. And while reading about epileptiform activity (which is a fancy way of describing peaks in an EEG graph) I learned something very important about how EEG is used to diagnose epilepsy.

Epileptic events are rare while a patient's EEG is being taken.

So how is epilepsy diagnosed? Through abnormal EEG reports. These abnormalities happen between seizures.

And here is my favorite part:

"It is these interictal 'footprints' that make the EEG such an effective tool in the diagnosis of seizures. Epileptiform activity is felt to represent increased cortical excitability or irritability."

This is really important, because it helps me consider the idea of identifying footprints for other "abnormal" brain states or brain activity patterns.

What are the 'footprints' of suicidal ideation?

If there are 'footprints' or well-known brain activity patterns detected by EEGs to distinguish a patient's state of wakefulness, drowsiness, or sleep, then why can't there be more footprints to discover for other states of being?

I also wonder why EEG technologists continue to specialize in reading EEG graphs (which are so hard to read) and why not devise simpler and more reliable forms of data visualization or pattern recognition to aid in the assessment's of a person's brain activity health.