This week I thought I would simply share the data that I received from Leslie Hendrickson, and put together for the AAPB Poster. Collectively it makes the case for the Disregulation Model, in that it shows the systematic progression toward resolution of a wide variety of symptoms with a very limited set of protocols. In some instances, a subset of symptoms is initially resistant to remediation, and then shows improvement later. In these cases several different mechanisms must be operative. That is no surprise. What’s remarkable is the variety of symptoms that do respond to a simple, straight-forward self-regulation strategy, not that there are exceptions to this simple picture.

Leslie did not use neurofeedback alone. She also made nutritional suggestions when appropriate, and used homeopathic remedies as well. But our critics are even less likely to give homeopathy the credit than neurofeedback, so we have that base covered. And in one case Irlen lenses were provided at some point during the training process. This allows a distinction to be recognized between those symptoms that were correlated with the visual hyper-sensitivity and those that continued to depend on neurofeedback for resolution.

All this has me looking forward to the new symptom tracking software that is taking shape on www.eegexpert.com, so that the plotting of these data is automatic rather than labor-intensive. There is an obvious graphic impact of these plots on even the naïve observer. We should have done more of this sooner!

If someone wishes to take issue and say that these plots do not constitute data, then my response would be that these data are at a minimum existence proofs. Most people unfamiliar with neurofeedback would argue at the outset that such remediation of such a variety of conditions at such a pace with a non-medical, non-invasive technique is not possible. In the negation of such a mindset, these plots do constitute data. Those of us familiar with neurofeedback can draw the further conclusion that comprehensive remedies are available with a simple set of training protocols, judiciously applied. Again, this proposition also only requires an existence proof, not a controlled study.

The number of issues in life that get settled with controlled studies are preciously few, and that holds true even in the life of a scientist. And the controlled studies that actually resolve outstanding issues, as opposed to just going through the motions for purposes of a government contract or the FDA, is even smaller.

The Crows are Back

Last year the West Nile virus was wreaking havoc with the crow population here in Los Angeles. That was by itself not entirely bad news, since crows seemed to be on their way to becoming the dominant bird species, if not the dominant species overall. With the West Nile virus mortality making inroads, suddenly there was not a crow to be seen anywhere. Were they all dead? Unlikely.

Most likely they had done in their birdbrains a kind of Bayesian analysis of the likelihood that over a period of mere days or weeks, they should be seeing fellow crows succumbing one after another. Something must be amiss in chez LA, they must have concluded in their mental risk assessment, and they all left. Now the crows are back, and they must have done another Bayesian analysis in their heads to conclude that it was safe to return. Incrementally their initial estimates of survival probability were improved, and more crows joined the early brave ones to feast at the bountiful detritus of our civilization.

In the absence of an ability to run a blinded and controlled study, Bayesian inference was the best alternative. It is ours as well. Remarkably, the crows got it right both times. When the proposition that life in Los Angeles is reasonably safe was first violated, the crows figured that out. Then when life became safe again after the mosquito season, they figured that out rather promptly as well. We have a chance to put Bayesian analysis on a firmer foundation with our clinical data, but the process is the same. Ultimately any arbitrary level of certainty can be reached with Bayesian inference alone, and any uncertainties in the initial assumptions will be washed out. That is where we are with neurofeedback. No controlled studies are needed to prove basic efficacy. We do not have to play catch-up.

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