Rewards and Inhibits with and without thresholds

The general rule, for me, is to minimize the number of rewards and inhibits in a session, simply because of the difficulty of providing good feedback.  With one threshold for the brain to pass, you can set a target to provide 80% feedback and have a pretty good chance of doing so.  When you add a second training parameter, you have the potential, even setting both at 80%, to reduce feedback to about 65% (if all the 20% of non-feedback on each target occurs during the 80% of feedback on the other, the feedback occurs .8 time .8 or 64%).  Adding a third target at 80% potentially reduces feedback to 50% (.8*.8*.8).

The inhibit threshold should ideally shape the brain’s activity toward cutting off the highest bursts of the target activity (outliers).  If we are talking about theta as our inhibit, then we want to get rid of the most excessive theta spikes, which will reduce the average theta level and reduce variance as well.  Of course, if the threshold is too responsive, it really won’t perform that task.  Whenever theta spikes, the target will follow it up quickly and come back down more slowly, so the brain may actually be getting positive feedback exactly when it is doing what we want it to stop doing.  Therefore, I like to use a longer epoch (generally 30-60 seconds) for my inhibit thresholds.  If there is a true trending up or down in theta, the threshold will follow, but it won’t be affected by spiking.

The reward threshold has a different problem.  In a great majority of clients, there will be an overall reduction in amplitudes in response to training preceding clinical improvement.  Theta amplitudes will come down and (gasp) beta amplitudes will as well.  In most cases, the inhibited activity will fall further than the rewarded activity, resulting in an improvement in the ratio/relationship between the two types of activity, and that’s what we want to see.  But if we have recalcitrant thresholds (manual or automatic) on the reward frequency, it’s perfectly possible – in fact quite likely – that when the brain quiets, with the inhibited frequency dropping significantly and the ratio improving, the rewarded frequency will also drop, and the brain will receive no positive feedback when it’s doing exactly what we want it to do.  So I would use a shorter epoch, maybe 15 seconds, on that threshold.

As for target percents, here there is a real range of opinions.  My best advice here is to say that the answer depends on the client and the training task.  When I began working with brains, I followed Lubar’s model which rewarded about 40-50% of the time.  Clients expected that because that’s what they experienced from the very beginning, and I really never had any complaints about such a lean reinforcement schedule.  After I trained with the Othmers, I tried the 70-80% reward level, and it did seem to work better with more wound-up clients – worse with more internal ones.  Very anxious clients tend not to let go and relax into the training when reward levels are low.

So here is what I do when I must (or choose to) use contingent feedback (beeps that come only when all the training requirements are met):  I start with auto thresholds with epochs set as stated above.  After a minute or two, when the brain starts to settle in, I switch the inhibit threshold to manual.  Now the client’s brain has a fixed target against which to exercise itself.  The better it does, the higher its scoring percent can become.  But the reward frequency can trend down with the inhibit frequency, and the auto threshold allows it to continue to score.

But let me suggest two other options that are possible with BioExplorer.

1.  You can, with BE, combine continuous feedback AND contingent feedback in the same protocol.  A tone, which rises and falls in pitch and/or volume can be playing all the time, giving the brain information about what it is doing.  And, I can set a specific target which, when met, results in some additional feedback.  Because that’s not the only sound, I like to set the auto-threshold for that band to give 10-20% reward, so it is heard only when the brain is doing its very best.  A number of the BE protocols in the package do exactly that, and they seem to work very well.

2.  You can also skip the whole question of setting targets on rewards and inhibits by using either percent or ratio trainings.  For example, instead of setting a threshold on theta and another on beta, just set up a power ratio of theta divided by beta and train for that number to give down.  That simplifies things for you and for the client.