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. \u00a0With 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. \u00a0When 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%). \u00a0Adding a third target at 80% potentially reduces feedback to 50% (.8*.8*.8).<\/p>\r\n\r\n\r\n\r\n
The inhibit threshold should ideally shape the brain\u2019s activity toward cutting off the highest bursts of the target activity (outliers).\u00a0 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.\u00a0 Of course, if the threshold is too responsive, it really won\u2019t perform that task.\u00a0 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.\u00a0 Therefore, I like to use a longer epoch (generally 30-60 seconds) for my inhibit thresholds.\u00a0 If there is a true trending up or down in theta, the threshold will follow, but it won\u2019t be affected by spiking.<\/p>\r\n\r\n\r\n\r\n
The reward threshold has a different problem.\u00a0 In a great majority of clients, there will be an overall reduction in amplitudes in response to training preceding clinical improvement.\u00a0 Theta amplitudes will come down and (gasp) beta amplitudes will as well.\u00a0 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\u2019s what we want to see.\u00a0 But if we have recalcitrant thresholds (manual or automatic) on the reward frequency, it\u2019s perfectly possible \u2013 in fact quite likely \u2013 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\u2019s doing exactly what we want it to do.\u00a0 So I would use a shorter epoch, maybe 15 seconds, on that threshold.<\/p>\r\n\r\n\r\n\r\n
As for target percents, here there is a real range of opinions.\u00a0 My best advice here is to say that the answer depends on the client and the training task.\u00a0 When I began working with brains, I followed Lubar\u2019s model which rewarded about\u00a040-50% of the time.\u00a0 Clients expected that because that\u2019s what they experienced from the very beginning, and I really never had any complaints about such a lean reinforcement schedule.\u00a0 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 \u2013 worse with more internal ones.\u00a0 Very anxious clients tend not to let go and relax into the training when reward levels are low.<\/p>\r\n\r\n\r\n\r\n
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):\u00a0 I start with auto thresholds with epochs set as stated above.\u00a0 After a minute or two, when the brain starts to settle in, I switch the inhibit threshold to manual.\u00a0 Now the client\u2019s brain has a fixed target against which to exercise itself.\u00a0 The better it does, the higher its scoring percent can become.\u00a0 But the reward frequency can trend down with the inhibit frequency, and the auto threshold allows it to continue to score.<\/p>\r\n\r\n\r\n\r\n
But let me suggest two other options that are possible with BioExplorer.<\/p>\r\n\r\n\r\n\r\n
1.\u00a0 You can, with BE, combine continuous feedback AND contingent feedback in the same protocol.\u00a0 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.\u00a0 And, I can set a specific target which, when met, results in some additional feedback.\u00a0 Because that\u2019s 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.\u00a0 A number of the BE protocols in the package do exactly that, and they seem to work very well.<\/p>\r\n\r\n\r\n\r\n
2.\u00a0 You can also skip the whole question of setting targets on rewards and inhibits by using either percent or ratio trainings.\u00a0 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.\u00a0 That simplifies things for you and for the client.<\/p>\r\n","protected":false},"excerpt":{"rendered":"
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. \u00a0With one threshold for the brain to pass, you can set a target to provide 80% feedback and have a pretty good […]<\/p>\n","protected":false},"author":112,"featured_media":0,"parent":0,"menu_order":100,"template":"","meta":{"_acf_changed":false},"topic":[776],"class_list":["post-39165","answer","type-answer","status-publish","hentry","answer_topic-tips-for-using-bioexplorer"],"acf":[],"yoast_head":"\n