No, this article is not about chess. Larry Hirshberg authored a superb defense of EEG Biofeedback (EBF) in application to ADHD that appeared in Expert Reviews of Neurotherapeutics last year but just came to my attention [Expert Rev. Neurotherapeutics 7(4), 315-319 (2007)]. He makes a number of arguments that we should all have in our grab bag when challenged on neurofeedback.

First of all, the basic question of whether operant conditioning on dynamic aspects of brain function is even possible is now supported by evidence from the neighboring field of brain-computer interfaces (BCI), which is also dependent on a learning paradigm. Additional evidence is furnished by real-time functional MRI feedback (rtfMRI). “While this research has generated considerable scientific and popular interest and excitement, it is less often remarked that it validates the fundamental premise of EBF…”

The analogy is particularly close when the BCI technology employs EEG signals derived at the scalp. An initial period of feedback-based learning is required for the subject to gain control of the cursor. “This feedback-guided learning is EBF-training, pure and simple.”

Countering the argument that neurofeedback needs to establish itself against the prevailing standard approach of stimulant medication, Hirshberg retorts that “a large percentage of patients with ADHD either do not receive or do not sustain medical treatment.” So EEG biofeedback is at minimum an evidence-based treatment that can be “employed in practice when medical treatment fails or is not accepted by the patient.” Studies indicate that some 50-87% of children diagnosed with ADHD in the US “either do not begin, or fail to continue medical treatment.” It has been estimated that the average length of time that stimulants are consumed by youngsters is less than six months, so even under these limiting assumptions the potential for neurofeedback is huge. (more…)

When working with reward frequencies above 0-3 Hz, we have found that a consistent relationship emerges between optimal reward frequencies for left and right-side training. If an optimal reward is found at any right-side site, such as T4-P4, then the left-side reward is expected to be at or close to 2 Hz higher. Now that we are training some people below 0-3 Hz by narrowing the reward band, this 2 Hz rule no longer applies. It is clear that left side still needs to train higher than right, but how much higher?We have used 3 Hz-wide filters above 0-3 Hz because narrower filters have slower response times. The critical variable for the brain’s response appears to be the center frequency, so we can have a very specific effect even with a rather wide frequency band. We have now found that we can narrow the filter down toward zero, and still get a strong and specific training response at these low frequencies. Above 0-3 Hz, however, we still want to continue with 3 Hz wide filters. (more…)

Several neurofeedback clinicians have been reporting that they are tracking EEG amplitudes during training as a means of identifying the optimum reward frequency. The reported observation is that inhibit amplitudes, or amplitudes across the spectrum as seen in a 2D spectral plot, fall significantly when training with a reward frequency which produces a calm and alert state. If this is so, even just some of the time, it might be possible and useful for the software to detect the shift and bring it to the clinician’s attention. It occurred to me that we need a design that would allow for tracking of the various amplitudes over a number of time scales, so we can all see what is happening and share that information more effectively.

It is not unreasonable to expect amplitudes to decrease within session with appropriate training. The EEG is highly state dependent and can be used, for example, in tracking state changes in an overnight sleep study. Our desired training state is one of calm eyes-open alertness in which all frequencies should be low amplitude. Low frequencies might increase in amplitude as people become sleepy, foggy, distracted, fidgety, etc. And high frequency amplitudes might increase with increased agitation or tension. These state-dependent shifts are in addition to any EEG rhythms or bursts that are related to brain dysfunction resulting from developmental delays, injury, or physiological disregulation. I really wouldn’t expect low frequency bursts related to seizure or migraine, for example, to shift within a session. But even a person with a highly disregulated EEG will also show shifts in background EEG frequencies with state changes. (more…)

We are seeing increasing numbers of very difficult children. They may come diagnosed as Conduct Disorder, Oppositional Defiant Disorder, Bipolar Disorder, Reactive Attachment Disorder, Tourette’s, severe ADHD, or some combination of the above. The presenting symptoms might include unstable mood, physical agitation and hyperactivity, obsessive fears, emotional reactivity and over-reaction to perceived threats, need for complete control, rages, aggressive behavior, tics, impulsivity and attention deficits.

As we explore the benefits of inter-hemispheric versus left and right side training separately, we are rethinking the behavioral categories and how they respond to these different training approaches. We have also expanded our reach with our recent lower frequency training, which is proving very useful with this population. These behaviorally difficult children are generally very sensitive to the effects of neurofeedback. That is positive in that we are likely to significantly help them, but it also means that we need to be very careful in adjusting the reward frequency and in selecting training sites. These are kids we do not want to make worse. (more…)

Author: Larry Lewis

I first encountered Bill Hudspeth’s method of coherence analysis in his presentation at the Connectivity Conference in Armonk NY on July 29-31, 2005; and I am writing this exposition of his method because it seemed to me that his work deserves to be more widely known. Not only is his approach highly innovative, it appears to have yielded unusually good clinical results, particularly in the work of Jon Walker who also presented at Armonk. It is likely that Hudspeth’s method would be better known if it did not involve complex matrix algebra techniques that most people find unfamiliar and difficult to understand. Therefore, I have tried here to be as un-mathematical as possible in discussing it.

In Hudspeth’s method, coherence values derived from 19-electrode QEEG data collection are used to generate a graphical display which consists of a three-dimensional depiction of a cube-like space in which little circles float, something like fish in a fish tank. Upon closer look one sees that there are 19 such circles, each labeled as one of the 19 QEEG electrode sites. In general, the circles tend to cluster fairly close to one another; but at times a particular circle stands out because it floats at a distance from the others. As Hudspeth explained, when a circle stands out from the others, it identifies an electrode site that has a problematic pattern of coherence relationship with the other sites. (more…)

The current issue of Biological Psychiatry offers a trenchant study titled “Are There Differences in the Symptoms that Respond to a Selective Serotonin or Norepinephrine Reuptake inhibitor?” by Jay Craig Nelson, Laura Portera, and Andrew C. Leon (Volume 57(12), June 15, 2005, 1535-1542).

Remarkably, in two sequential, independent, randomized controlled large-scale studies (253 and 168 subjects) no significant differences were found in the response of major depression to reboxetine and fluoxetine. Symptom change was assessed with the Hamilton Depression Rating Scale (HAMD).

First of all, these results fly in the face of the core belief system of modern psychiatry, namely that of specificity not only with regard to diagnosis but with regard to pharmacological remedy. It also undermines the chemical deficiency model of depression. That model all along has had little more than the presumptive “specific efficacy” of selective serotonin reuptake inhibitors in evidence. Now that tall pole in the tent is gone. (more…)