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Operant Conditioning Best Practices

Posted: Tue Jan 10, 2023 2:22 pm
by mtp
Hi,

Looking at the neurofeedback apps, there seems to be a focus on increasing noise (ie: positive reinforcement) vs reducing noise (ie: negative reinforcement). I would have assumed that the focus on removing noise to be at the mentally quiet state would be more effective than increasing something that the minss.needs to hunt for.

Obviously positive punishment is similar (ie, when the mind drifts it gets something that may take it out of the zone faster).

Happy to review and research papers or similar.

Re: Operant Conditioning Best Practices

Posted: Thu Jan 12, 2023 1:10 pm
by Grasping Infinity
Very interested in this!
I'll add an option to "inverse" the sound conditioning to the next versions my Neurofeedback apps that use the mind monitor.

The only draw back I can see is that with sound, there is information. And in silence there is much less or no information. If the user had the goal of increase there Alpha, silence might be able to tell them if they are peaking in alpha, but it could only do that. Silence couldn't let them know if they wanted to further increase their amplitude of alpha.

So if there was a specific state (ei The Awakened Mind pattern) silence would be useable (because it's basically yes or no) but if they wanted to go anywhere from there, there would be no way for them to get any feedback.

But there are always other possibilities / configurations!

Re: Operant Conditioning Best Practices

Posted: Thu Jan 12, 2023 5:08 pm
by mtp
Yes. I'm pondering the negative vs positive reinforcement. Negative reinforcement removes to silence. Positive is the typical add something (increase pitch, birds in muse). Negative is removing something (like the wind in muse). I intend to be agnostic and make it an option (positive/negative) And the method (noise, visual, etc).

The other part is how to help train.

My gut feel is that it can be adaptive. Looking at mean error can influence the aggressiveness of the feedback.

From what I've seen with some of the mind monitor graphs, good practitioners can nail it almost immediately. They would have very little variance. For me, it would be all over the place.

My vision would be the following choices
- regions to target ( ave, left/right/front, EEG probe point, etc).
- band to target (increase/decrease, ratio/limit)
- reinforcement type (positive,/negative, sound/visual, strong/weak, adaptive/fixed).

I'm hoping to use it for both meditation and focus/therapeutic for ADHD.

From what I can see muse-js seems to support most of what I'd need to make it client free and portable.