Neurofeedback Equipment: A Buyers Guide for Neurofeedback Professionals

The threshold is what activates the feedback, and tells the client when he is approaching the goal and when not. An example would be ‘when the Alpha brainwaves rise above this level, activate the feedback’. This level is the threshold.

There are two ways of setting this threshold.

The first is manually. You can watch the data, and manually set a bar to reach. Above that level, the feedback starts, below that level it stops. When the client improves, you make it a bit harder. When they tire, you make it a bit easier. You’re engaged with the training.

Automatic thresholds work a little differently. The software makes the difficulty level adjustments automatically. Auto-thresholds are a huge labour and skill saver, as you start the protocol and go hands-off from there. The main downside is that the skill level is constantly changing, so the client has no clear target to reach.

So, be sure your software has the option of manual thresholding.

There is a lot of debate around whether to use absolute training or Z-score training.

The difference comes down to this; an example of absolute is ‘reduce the activity in this area from what it is now’. With a Z-score, you say ‘reduce the activity in this area down to this level, and no more than that’.

The argument can be made that with Z-scores, you’re training towards an ‘average’ brain. And who wants to be average? On the other hand, getting back to a ‘comfortable’ position is exactly what you want if you are looking to resolve a particular symptom or get out of a mental jam.

Z-score training can be used with any number of sensors, and is almost a requisite for more complex protocols. By setting training limits, Z-score training eliminates the risk of over-training (training too far).

Not all systems are compatible with Z-score databases. It’s nice to have the option, especially if you’re working with more serious cases.

The feedback is the signal for your client, telling him when he is reaching his objective and when not.

You could visual feedback (like something happening on a screen), a game (for example a car that drives when the client reaches the target), a sound (tone, music, a change in volume), or even a physical vibration (like a sonic cushion or vibrating teddy bear). Any signal will do.

Most software platforms have a good selection of feedback options available, and there are some excellent third-party games packs available. This is another areas where software compatibility is important.

Reflection neurofeedback is ‘non-directional’; it doesn’t give any particular ‘goal’ as standard feedback does. It ‘reflects’ or ‘mirrors’ the activity in a given part of the brain, and relies on the brain’s ability to decode that signal and adjust its activity accordingly.

For example; when certain activity in one area is high, a high note is sounded. When it is low, a low note is played, with a note scale between the two. Visual or tactile reflection feedback methods work along similar lines.

This is a favorite among package systems, who brand it under all sorts of names (‘quantum principles’ is a common description). It requires minimal training, so is good for beginners, and puts some neuro-age mystery into the sales jig.

It’s also used with ILF or infra-low neurofeedback (training at very low frequencies <.1Hz). One wave every 10 seconds is too sluggish for standard neurofeedback, though training such slow waves is pretty sketchy using refection neurofeedback as well.

Compared to standard neurofeedback, the efficacy rates of the reflection method are lower, and the results unpredictable. If your client has a particular goal for the training, reflection feedback is not the method to use.