EEG Biofeedback: A Generalized Approach to Neuroregulation, Othmer S. Kaiser, DA, Othmer SF

To appear in "APPLIED NEUROPHYSIOLOGY
& BRAIN BIOFEEDBACK"
Edited by Rob Kall, Joe Kamiya, and Gary Schwartz

Page 1 of 13
Overview
Many clinicians who have adopted EEG biofeedback are struck by the wide variety of clinical indications for which efficacy has been either observed directly, or claimed by others. This chapter presents a comprehensive overview of the current state of EEG biofeedback from the clinical perspective, but with an orientation toward model building. Specifically, the review covers the higher frequency training conventionally referred to as "SMR/beta" (nominally 12 to 19 Hz). Discussion of the lower frequency domain of "alpha/theta" (4 to 12 Hz), though of great interest as well, is left to others.
INTRODUCTION
First, a conceptual model is proposed and discussed. Second, the research history of the field is drawn upon to illustrate the evolution of protocols and explain elements of the emerging model. Third, an overview of our clinical results is given that depicts the use of the proposed "generalized approach" for a number of mental disorders. These results were obtained with a relatively limited set of clinical protocols that evolved out of our extrapolation of new methods from the original research. From these results emerges a need to explain how such broad efficacy can be achieved. It is postulated that the EEG feedback technique not only promotes particular functional states of the brain, but more generally exercises neural mechanisms by which the fundamental functions of arousal, attention and affect are managed by the central nervous system (CNS). Rhythmicity in the EEG is seen as a key variable in the coordination of cortical activity, and clinical improvement is traceable to improved neuroregulation in those basic functions by appeal to their underlying rhythmic mechanisms. Current models of brain function are used to explain both the frequency and the spatial specificity of the EEG biofeedback process.
It will be demonstrated in the following that EEG biofeedback cuts across the bestiary of clinical diagnostic categories that has been devised over the last thirty years, demonstrating an ability to remediate a multiplicity of diagnoses with a limited set of protocols. It acts directly on underlying physiological mechanisms, and presupposes a considerable functional plasticity of the brain, a concept that has only recently become a significant subject of inquiry within the research community. Such plasticity appears as "noise" in the search for the genetic basis of behavior, and as such has asserted itself primarily in its negative implications for such work. It will be argued that EEG biofeedback affects brain function at the network level, and a preoccupation with processes at the molecular, membrane, or even cellular level is not particularly illuminating for brain function at the higher levels. The implicit assumption of the bottom-up approach of the neurosciences seems to be that a viable conceptual model of the network cannot be constructed until we know the detailed workings of all the parts. Yet EEG biofeedback has proven to be a valuable clinical tool (as the data cited will show), and has stimulated the creation of a conceptual model based on such a top-down, systems approach. .
EEG biofeedback can be best understood, and its relevant mechanisms discerned, by viewing the brain through the action of its web of inhibitory and excitatory feedback networks. Such networks require explicit mechanisms to manage them, integrate them, and assure their functional integrity. These networks must meet global stability criteria irrespective of what neurochemical implementation nature has, by evolutionary happenstance, devised. No doubt the technique impacts very specific neuromodulatory mechanisms, which remain undefined at this time. The clinical work can nevertheless proceed fruitfully on an empirical basis. Thus, EEG biofeedback is deemed to address itself to the core issue of control, with specificity at the network level, and yet with considerable generality in terms of clinical implications.
Click foEEG Biofeedback: A Generalized Approach to Neuroregulation

By Siegfried Othmer, Susan F. Othmer, and David A. Kaiser

To appear in "APPLIED NEUROPHYSIOLOGY
& BRAIN BIOFEEDBACK"
Edited by Rob Kall, Joe Kamiya, and Gary Schwartz
Page 2 of 13
A Comprehensive Conceptual Model
In order for the field of EEG biofeedback to move forward and fulfill the promise that it has shown thus far, it is necessary to create a conceptual model that will explain the clinical results that have already been achieved in a way that will answer questions raised by skeptics, as well as facilitate a greater level of understanding and efficacy on the part of practitioners. The conceptual model presented here describes the characteristics of human neurophysiology upon which EEG biofeedback is based, how the process works, and why such wide-ranging efficacy can be gained by means of such a seemingly simple process.
Structure Versus Function
Before proceeding, it is necessary to clear some semantic underbrush: Though the process presented here is based on a "functional" approach, the hard distinction between structure and function survives in the tenacious tradition of the language of dualism. That is, structure and function are seen as the realization, if you will, of brain and mind, respectively. Every brain function, however, must have its structural underpinnings, so the more tangible distinction, and the one more accessible to experiment, is one based on the timescale of change and the ease with which change can be induced. Most of what we consider in terms of brain function involves typically rapid, transient changes in the electrical activity in the brain, activity which may leave little in terms of residual imprint. Most of what we consider in terms of brain structure is that which remains essentially unchanged over longer time constants. This is a continuum, and over much of the range in timescale, one can appropriately describe a phenomenon either in the vocabulary of structure or that of function. One analogy that comes to mind is the redefinition by David Bohm of a noun as a "slow verb".
Another way of looking at the structure/function duality is in the division between hardware and software in computers. On one hand, we have the true hardware, the semiconductor devices and ancillary items needed to service and operate them. On the other hand, we have the operating system software. Though this can be changed, it is generally modified only rarely and deliberately. At the next level is the applications software. A number of different modules may be drawn upon (brought to consciousness?) at a given moment, and there is in fact considerable "interaction" with the outside world which may make "functional" changes in the application software; and there may even be some adaptation to what the user typically wants. At the top level is the phenomenology of what is created with the applications software, which has typically a very transient quality (e.g., imagery). One could argue that at each level we are dealing with physical electrons moving around from site to site (structure), but that would be cumbersome, and not really to the point. Similarly, one could talk about software failures in terms of "electron deficiencies" in certain memory locations. This is both true and absurd as a model for software failures. Every level has its appropriate terminology, referring progressively to structure, function, and objects (gestalts).
The categories distinguished here can find their analogues within the brain. However, the boundaries are not as discernible and the distinctions between structure and function even less definitive. Nevertheless, let us push the analogy forward a little further: A similarity can be drawn between our brain's neuromodulator systems and the operating system software of a computer. There is persistence in the workings of our neuromodulator systems that puts them on a different timescale than the applications software (which might involve the processing of a visual image, for example). Yet it would not be correct to regard the characteristics of a person's neuromodulator systems as immutable (even absent any drug intervention). Over time, it is clear that environmental influences, for example, can effect changes in neuromodulator function. A person may become more or less hypervigilant over time; he may become more depressed or anxious. He could also, however, achieve "spontaneous" recoveries from depression, which can be simply interpreted as autonomous normalization of neuromodulator functioning.

The distinction, therefore, between categories of structure and function is not based so much on issues of transience versus immutability, per se, but rather on a multiplicity of factors: the timescale of change; how matters have been historically viewed; and the level of abstraction which is appropriate to the discussion. This whole issue is currently very much in flux, and somewhat confused. We have, for example, the following from Michael S. Gazzaniga, director of the Center for Neuroscience at the University of California in Davis: "When someone remembers something, is there a structural-or discrete anatomical-change in neuronal synapses? Or is it functional change, which would simply reflect reprogramming of the pattern of neuronal discharges in the nervous system?" (Gazzaniga, 1995).

Here the posited "structural" change could equivalently be talked about in terms of function, and the posited "functional" change (which clearly must be sufficiently robust to persist long-term if it is to represent a memory) can be talked about in terms of structure (altered synaptic coupling strengths).
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EEG Biofeedback: A Generalized Approach to Neuroregulation

By Siegfried Othmer, Susan F. Othmer, and David A. Kaiser

To appear in "APPLIED NEUROPHYSIOLOGY & BRAIN BIOFEEDBACK"
Edited by Rob Kall, Joe Kamiya, and Gary Schwartz

Page 3 of 13
Brain Plasticity
If we are intent on maintaining the structure/function dichotomy, we are ineluctably in a semantic swamp. This is at least in part because the neurosciences are in the process of coming to terms with mounting evidence for what is collectively called "brain plasticity", and the old dualist terminology no longer serves us well. In its most general formulation, EEG biofeedback can be seen as the deliberate exploitation of 'functional brain plasticity'. More specifically, it depends upon plasticity in our neuromodulator systems. However, this concept is at best ambiguous, and a moving target. Simply put, brain plasticity refers to long- term alteration in brain systems that were historically thought to be static. Hence, the word tends to have a historical contextual reference, much like the word 'alternative health': once an intervention becomes mainstream, it is no longer "alternative". Similarly, once plasticity becomes accepted as an attribute of a particular brain system, the term tends to be discarded and future references may simply be to brain function. Hence the term brain plasticity tends to have only a transient utility, and to serve only where the case for plasticity is still being made. However, making the case for EEG biofeedback on a model of brain plasticity may be the most accessible Ansatz.

To make the term maximally useful for our purposes, a review is in order. A remarkably prescient view of the model of brain plasticity is to be found in Brodal (1981, p. 259):

"Although our knowledge about the 'plasticity' of the nervous system is still in its beginnings, there is reason to believe that this plasticity is a general property of the central nervous system, and that it is a prerequisite for the capacity to learn (in general, be it motor patterns or pure intellectual capacities). Restitution after damage to the central nervous system may therefore in essence be likened to a learning process. Practical experience is in agreement with this."

A more modern view is summarized by Oliver Sacks in the popular book, An Anthropologist on Mars. (The views of neuroscientists are often more boldly expressed in their popular writings as opposed to their scientific ones, where they are compelled to be more reserved and circumspect.)

"Work in the last decade has shown how plastic the cerebral cortex is, and how the cerebral 'mapping' of body image, for example, may be drastically reorganized and revised, not only following injuries or immobilizations, but in consequence of the special use or disuse of individual parts. We know, for instance, that the constant use of one finger in Braille leads to a huge hypertrophy of that finger's representation in the cortex." (Sacks,1995, p.41)

Here the focus is on the long-term dendritic re-programming and/or regrowth, which has been shown to occur. However, there has still been little recognition of the obvious ability of the brain to accomplish significant reorganization on time scales much shorter than that of dendritic regrowth, which requires simply changes of state, and of regulatory function, that is, of functional rather than structural reorganization. This is now changing:

"Reorganization of somatic sensory receptive fields can appear within the dorsal column nuclei, the thalamus, and the cortex, within seconds of a peripheral manipulation. Similarly, motor cortical maps show dramatic shifts within hours of a peripheral nerve lesion or [within] minutes of a shift in arm configuration." (Donoghue, 1995)

When considering the reassignment of cortical neuronal resources within a time constant of seconds, one wonders if "plasticity" is the appropriate descriptor for the phenomenon. This is another case in point of the use of the term to describe as mutable something thought to be more permanently stable. If cortical resources can be so readily reassigned, then the mechanisms involved in stabilization must lie principally in the functional rather than structural realm. That is, there is less hard wiring than was thought! Thus we are likely to see the language of structure replaced over time by the language of function, and eventually we will see the disappearance of the term "plasticity" altogether in this connection.

With this in mind the term functional plasticity may be used to refer to all those processes by which brain functions thought to be relatively stable can be altered on a timescale short compared to that of dendritic regrowth, or the formation of new synaptic boutons. Functional plasticity is undoubtedly mediated, inter alia, via alteration of synaptic coupling strengths through the generation or attrition of receptor sites, and the alteration of neurotransmitter chemistry through changes in neuronal gene expression. The present interest will focus specifically on the neuromodulator systems and their regulation. Here the observed "functional plasticity" can have time constants short compared even to the above-postulated processes. For example, when we are frightened, we are capable of changing our state of arousal within fractions of a second. The functional plasticity of neuromodulator systems clearly exists on all behaviorally relevant timescales. The claim of EEG biofeedback is that the dynamic range of neuromodulator system plasticity (flexibility) can be increased where it is deficient, and stabilized when it is unstable, by operant conditioning techniques.
Functional Plasticity: Implications of Recent Research
A number of developments over the past several years have prepared the ground for the claims we are now making for EEG biofeedback. First of all, the findings from functional magnetic resonance imaging (fMRI) are refocusing attention on collective neuronal activity; its time course, temporal interrelationships, and change as learning and habituation take place. Inevitably, these findings will raise questions about how such neuronal populations are organized and managed by the brain. Secondly, there is the ongoing research into the thalamocortical generation of rhythmic activity in the EEG by Mircea Steriade, David McCormick, and others. (Steriade, 1984; McCormick, 1990) Thirdly, there is the emerging interest in the binding problem, the mechanism for how the brain retains as a coherent phenomenon something that is parallel-processed at multiple neuronal sites (a visual image, for example, or a phoneme.) (von der Malsburg, 1995). We shall return to this critical theme below.
At another level, it may be said that much of psychopharmacology implicitly makes the case for the kind of functional plasticity required to explain the presumptive efficacy of EEG biofeedback. Quick-acting medications like stimulants can only operate by shifting the functional state of neuromodulator systems; there is no time for significant structural adaptation. The short-term effects of EEG biofeedback can be explained by similar shifts. The longer- acting medications such as anti-depressants and anti- psychotics work on the same timescale as the cumulative effects shown in many of the recoveries claimed for EEG biofeedback. The effect of Prozac administration, for example, can be discerned in the cerebrospinal fluid within hours, just as with stimulants, and yet its anti-depressant effects may take days or weeks to manifest. Such medications may work by means of longer-term adaptations that involve both functional and structural change. But it is not a large leap to argue that such changes can be induced over time by the challenge to the nervous system imposed by operant conditioning of the EEG. Both EEG biofeedback and pharmacological intervention can even be seen as a disequilibration of nervous system functioning to which the brain responds by long-term adaptation. In this view, their mode of action is seen to be uncannily similar. Regardless of whether or not this concept can survive further scrutiny, it is clear that the claims of EEG biofeedback are consistent with, and certainly not antithetical to, the implications of pharmacology.
Efficacy of pharmacology for a variety of psychiatric disorders is often taken to imply that such chemical intervention is absolutely required for remediation, by analogy to the provision of insulin in the case of Type I diabetes. That this is not the case is demonstrated by the efficacy of electro-convulsive shock therapy for depression. Here the remediation may be long-term even absent any long- term pharmacological support. Additionally, spontaneous recovery from episodes of both mania and deep depression is the rule, not the exception, in even mature cases of bipolar disorder. Clearly, these brains have quite functional states within their inventory. The question of efficacy of EEG biofeedback (for the vast majority of applications) is then reduced to the relatively minor issue of whether a change in functional state can be induced, or at least promoted, by operant conditioning of the EEG, and the second issue of whether such a training can have lasting effects.

In the case of pharmacology, the challenge to the nervous system is provided by neurochemicals or their metabolic precursors, or other metabolic agents, or factors which modulate receptor site sensitivity or ion channel permeability. In the case of EEG biofeedback, the challenge is to the means by which brain function is organized and maintained in the time domain, which is reflected in the EEG. It will be argued in the following that neuromodulator systems function to organize both general organismic arousal and more localized activation of collective neuronal activity by modulation of rhythmicity. The EEG is preferentially sensitive to such collective, periodic, activity.
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EEG Biofeedback: A Generalized Approach to Neuroregulation By Siegfried Othmer, Susan F. Othmer, and David A. Kaiser To appear in "APPLIED NEUROPHYSIOLOGY & BRAIN BIOFEEDBACK"Edited by Rob Kall, Joe Kamiya, and Gary Schwartz Page 4 of 13 The Bio-electrical Domain: The Role of Periodicity and the EEGWe must pause in the chain of argument to admit to a degree of circularity: The normal EEG in an activated state has the appearance of a noisy signal devoid of any dominant frequency. Hence, it is not obviously rhythmic (periodic). Nevertheless, the frequency decomposition of this signal manifests the bursts of rhythmicity referred to. However, one could decompose any such noisy signal (the noise from a waterfall, for example) and obtain band-limited (frequency-decomposition) data looking much like the EEG, with similar bursts of rhythmicity. Hence, the physical reality that is ascribed to these rhythms must be based on more than the EEG signal itself. That is, looking through green sunglasses (band- limiting visual data) does not allow us to proclaim the world to be green. In the present context, the most persuasive argument for the physical reality of these rhythmic bursts comes from the fact that they appear to respond in a frequency-specific manner to EEG biofeedback training! However, we should not assume the answer in order to help us prove it. Historically, the EEG was first studied with a focus on its most obvious feature, the alpha rhythm. We now associate a prominent alpha rhythm in occipital cortex with idleness of the visual system. Similarly, the sensorimotor rhythm (14 Hz [Hertz]) so prominent in the cat (or in Stage 2 sleep in humans) is associated with stillness of the motor system (Chase 1971). Inactivation is associated with increased rhythmicity (increased amplitude), as neuronal populations coalesce to collective firing under their mutual influence in the absence of independent sensory stimuli or other inputs. When activation levels are increased, due to stimulation or processing, these neuronal populations desynchronize, to a point at which rhythmicity may no longer be readily observable in the raw signal. Hence, the normal activated EEG is seen as the relatively desynchronized extrapolation of manifest rhythmic activity, which has a defined physiological function: maintaining a state of inactivity, or perhaps of readiness. A noisy (desynchronized) EEG arises then from the superposition of many rhythmic generators of different frequencies, each undergoing its own rapid ebbing and flowing from rhythmicity to desynchronization. When any one of these generators reaches the extreme of low activation, it may begin to dominate the EEG record. "Although our knowledge about the 'plasticity' of the nervous system is still in its beginnings, there is reason to believe that this plasticity is a general property of the central nervous system, and that it is a prerequisite for the capacity to learn (in general, be it motor patterns or pure intellectual capacities). Restitution after damage to the central nervous system may therefore in essence be likened to a learning process. Practical experience is in agreement with this."Next, it is necessary to make the case that whatever role the specific EEG frequencies play in cortical regulation, that role is invariant over cortex. One of the notable features of the neocortex is that it is morphologically and histologically fairly homogeneous. Moreover, the same set of neuromodulators, by and large, subserve a variety of functional subsystems, and are not unique to any one of them. Similarly, the natural parsimony which prevails in nature makes it likely that the general role of rhythmicity in activation and time binding'whatever that role may be in detail'is probably uniform across cortical regions, varying only quantitatively over cortex, not qualitatively. Hence, operant conditioning of the EEG rhythmic activity can be seen as a general appeal to brain regulatory function, as it is manifested in the cortical EEG. Depending on scalp location, one may expect some influence on the specific thalamocortical projections to that region, and to the specific functions subserved by that cortical region. Also, one expects some influence on the nonspecific thalamocortical projections, for a general effect on activation and physiological arousal. Whether the effect is more localized or more generalized has to be answered by a review of the data. It is already clear, however, that the EEG training cannot be specific to one neuromodulator system, as might be the case for some medications. Recent findings with fluoxetine (Prozac) make it apparent that even medications which impinge directly upon one neuromodulator system (serotonin), are behaviorally non-specific in their effects! (Kramer, 1993) We therefore have every reason to suppose that EEG training affects and hopefully promotes fundamental brain regulatory integrity, and that behavioral or other improvements are simply evidence of the heightening of such self-regulatory performance. The Specific Role of Rhythmicity in Neuroregulation It has been argued above that in the extreme cases of EEG synchronization and desynchronization, an obvious correlation with low and high activation and arousal, respectively, exists. It is also well known that arousal correlates with dominant frequency in the EEG. It falls readily to hand to argue that the degree of rhythmicity, together with changes in the EEG frequency spectrum, manages the entire range of activation and arousal in the bio-electrical domain. The EEG, then, reflects a parameter that the brain tightly constrains in the ordinary course of events. An appeal to dominant frequency or to the amplitude at a given frequency by operant conditioning could therefore be expected to serve as a powerful external forcing function on the brain's management of arousal. The whole matter of the role of frequency, however, bears further discussion. One role advocated for rhythmic activity is that of time binding, the need for harnessing brain electrical activity which is spatially distributed while maintaining it as a single entity. The need for this kind of function is apparent when it is recognized that visual processing, for example, must occur by parallel processing over large areas of cortical real estate. The integrity and stability of the image must be maintained over time. Simultaneity of firing of the various neurons participating in the mapping of an image may be the relevant criterion of "belonging". The transient organization of such distributed, correlated neuronal activity may be the role of the thalamocortical rhythmic generators. At the lower frequency regimes, say less than 30 Hz, this organization ranges broadly over the cortex, and manages activation and arousal with relatively long persistence. At higher frequency regimes, above 30 Hz, and peaking in the 40-60 Hz regimes, the brain manages specific cognitive processes that are of a more transient nature, and more spatially localized. A recent study beautifully exhibits both of these roles of rhythmic activity (Munk, 1996). In this study, a visual image was moved across the visual cortex under two conditions: normal, and under electrical stimulation of the mesencephalon (brain stem region in which the nuclei reside which source the neuromodulator substances that control attention and arousal.) With stimulation, a global coherence became prominent in which the firing rates of neurons in different regions became more coincident. This coherence was observed over the region of visual cortex that was involved in mapping the moving image. If the moving image was then changed into two images, moving in opposite directions, the coherence was still present, but was restricted to the neurons belonging to each moving target. This beautiful experiment illustrates the influence of global activating mechanisms directed from the brainstem. However, this mechanism was not sufficient to guarantee time binding. That requires augmentation by information derived from the image itself, and processed 'locally' in cortex, in order to define the specific cohort to which each participating neuron belonged. This is a process of which the brainstem remains ignorant. Hence, time binding requires both brainstem and cortical governance, and both may be mediated by thalamo- cortical networks, and may also be modulated by direct cortical-cortical interaction. It must be kept in mind that most of the signal processing we do in the brain involves very transient events taking place on small time scales. The analogy to dynamic RAMs or to the refresh on your computer screen (every 17 milliseconds) comes to mind. Further, it is apparent that the real information content in neural signals (action potentials) relates in first order (and trivially) to the presence or absence of a particular signal, and, more significantly, to the actual timing of the signal. The magnitude of an action potential is not a function of the size of the stimulus that gives rise to it. Only the timing matters. And even the timing gains significance only in the context of other events. All "mental activity" must ultimately have its basis in particular neuronal firing patterns that become discernible from the ambient noise background by virtue of timing coincidences or at least correlations. It is this timing which appears to be managed by thalamocortical circuitry. Rhythmicity may be one of the key ways in which such timing is organized. Recent research by Pfurtscheller (1990) and Sterman (1996), show that the brain's ability to locally desynchronize in a timely manner defines its capacity to process the next stage of an ongoing task. The ability to resynchronize quickly allows it to reenter a state of readiness for the next task. The process breaks down when synchronization or desynchronization of specific frequencies persists or is disregulated, decoupled from the demands of the moment. EEG biofeedback is then to be seen as a challenge to the mechanisms that underlie the management of this rhythmic activity, and in application to neuromodulation of arousal and activation its natural domain is the frequency range less than thirty Hz. Training is similar to stimulation, and constitutes a push that invokes the brain's capacity for restoring homeostasis. Over the longer term, this results in a long-term increase in stability. Training at a specific frequency is then a push in a very specific direction, which can be chosen in light of specific arousal disregulation or attentional deficits found in each case. Click for Next Page

EEG Biofeedback: A Generalized Approach to Neuroregulation By Siegfried Othmer, Susan F. Othmer, and David A. Kaiser To appear in "APPLIED NEUROPHYSIOLOGY & BRAIN BIOFEEDBACK"Edited by Rob Kall, Joe Kamiya, and Gary Schwartz Page 5 of 13 The Placebo ArgumentDoes EEG biofeedback, with all its instruments, bells and whistles, include a huge "placebo" component (for which we are not entitled to claim credit)? The placebo argument sometimes serves as a talisman which the scientist, comfortable in his paradigm, may use to ward off disagreeable new claims. However, the placebo effect is no more than the body's means of mobilizing self-recovery. The placebo effect is not a cause. It is not itself a mechanism of recovery, but it does imply a mechanism'though one which may seem featureless and devoid of testable properties when looked at through the prevailing structuralist paradigm. Hence, it can provide no help to our understanding. But EEG biofeedback is by its very nature self-remediation. The part we are entitled to take credit for cannot be experimentally distinguished from "other" aspects of the self-healing process. For researchers attempting to prove the efficacy of medication, self-recovery represents the counter-hypothesis, which is wrapped up in the concept of "placebo effect" and need not be further discussed. It is not of interest to the designer of drugs. When the discussion is about self-induced recovery (such as EEG biofeedback) and the mechanisms thereof, then we must openly address the placebo effect and ask whether its self-healing properties are any different from what we are claiming. It is a moot point. The existence of the placebo effect proves the existence of self-remediation. Self- remediation cannot then be disproved by invocation of the placebo effect. The existence of a robust placebo effect in medical and mental health disciplines supports the claims of EEG biofeedback. It does not undermine them. Still, if one cannot in the individual case determine what part of recovery is due to the specific effects of EEG biofeedback training and what part is attributable to non- specific effects, can one be sure that the effects aren't all in the latter category? The normal resolution to this question is by means of statistics. In the case of EEG biofeedback, however, we are not constrained to rely exclusively on statistics (although the statistical argument is favorable as well), as there are other proofs of its efficacy. The placebo effect, seen here as stalking horse for nonspecific effects of the EEG biofeedback process, is not the explanation for the efficacy claimed for the following reasons: 1. The effects of the training are highly specific to electrode placement and to training frequency band. 2. Training protocols exist which can commonly elicit effects opposite to those desired. 3. The effects of training with one protocol can be reversed with another. 4. The effect of the training is cumulative, rather than fading with time, as is common with placebos. If EEG biofeedback were to be explained in terms of placebo phenomena, it would be the first time that placebos are dose- dependent (i.e., cumulative). 5. Training effects are in line with research from neuropsychology regarding localization of function.6. Populations can be moved to levels of performance which exceed those of na‹ve populations 7. The effects of the training often lie outside the range of expectations for spontaneous recovery or placebo effects, not only with respect to the magnitude of the changes elicited but also with respect to the consistency with which they are produced, and the timescale over which they occur. (Curiously, the more striking and unusual the claims for EEG biofeedback, the more strenuously is the placebo hypothesis invoked by critics!)8. EEG biofeedback was discovered in connection with animal research. It may be assumed that the test animals were not subject to the placebo effect. Moreover, the researcher was blind, since the discovery was by way of serendipitous connection to an unrelated experiment (Sterman, 1976). The spatial and frequency specificity of the EEG training, as well as its reversibility, allow every subject to be their own control in the training. This is not to say that conventional controlled studies are entirely superfluous. We are just at the beginning of the scientific inquiry into this technique, much of which will require controlled paradigms. Rather, we are asserting that the epistemological assumptions operative in the clinical setting are already sufficient to demonstrate efficacy in the case of EEG biofeedback because of the above-enumerated features of the training. In view of the above, then, the recoveries, remediations, and performance enhancements claimed for EEG biofeedback may be regarded on their own merits, and cannot be gainsaid either by placebo factors or by the argument that they are not individually supported by blinded controlled studies. Another prevailing perception must be examined before proceeding with review of the protocols and the clinical data. It is often asserted that the EEG biofeedback "trainee" is actually training his own behavior, and that the changed EEG is simply a manifestation of that altered behavior. Behavioral state and the EEG are clearly coupled, and a conscious redirection of one's physiological state can obviously be helpful in achieving the objectives of the training in the moment. This is the dominant theme in conventional biofeedback, which is dependent upon a great deal of deliberate engagement in the process by the subject. This is not a necessary condition for EEG biofeedback training to succeed, and in this sense it departs fundamentally from conventional, peripheral biofeedback. The successful training of cats, of very young children, and even of people in mild vegetative states, demonstrates that the training can proceed without the subject being particularly aware of their behavioral state, or intent upon altering it, or indeed very conscious about what is going on at all. The training in this case consists in operant conditioning of the EEG, neither more nor less. For example, in the use of EEG biofeedback for the remediation of epilepsy and stroke, it is not "behavior" in any conventional sense that is being trained. In fact, we have observed that people can respond quite counter to their own desires, expectations, and motivations; with the expected effects (and even some that weren't expected by either the client or the therapist) arising out of the particular protocol selected. The resulting behavioral state may be concordant with the protocol selected, and quite at odds with the participant's conscious goals. Finally, there is the compelling observation that sleep EEG is changed subsequent to EEG training in the waking state. (Sterman, 1970) All these observations are evidence for the proposition that it is 'brain behavior" that is being trained directly. And brain behavior may be non-specific with respect to overt organismic behavior. Research History: Implications for Mechanisms of EEG BiofeedbackIf EEG biofeedback training is indeed capable of promoting self-healing, its role is that of facilitating a process of change the capacity for which already exists in the human brain. But how is it that such an apparently simple tool is capable of such wide-ranging effects? What is it about the brain that allows it to be led to more functional states? And how can the operant conditioning process embodied in EEG biofeedback be applied systematically and predictably, to good effect? The implications of our clinical findings are that the EEG training is not narrowly specific in its clinical effects, but that it impacts very basic regulatory mechanisms, the disregulation of which is responsible for causing or at least maintaining the disorders discussed. In the following, the case will be further made for such a simple underlying model. A connection will be made to current models of brain function, and the central role of rhythmic brain activity will be discussed in explaining the remarkable breadth of efficacy of this emerging modality. The early model of efficacy proposed by Sterman is that the EEG training at sensorimotor cortex lowers the setpoint of the gamma motor system reactivity (Howe, 1972). As a result, cortical hyperexcitability is reduced. This manifests in higher threshold of onset of seizures, most particularly in the case of motor seizures (Sterman, 1984). Lubar initially worked only with those hyperactive children who were Ritalin- responsive, on the assumption that these were the ones whose hyperactivity was grounded in underarousal (Shouse & Lubar, 1979). So the early work already presaged our current perspective, that the principal mechanism of action of EEG biofeedback is to normalize autonomous management of arousal and to enhance overall nervous system stability. The intimate relationship between seizure susceptibility and arousal makes it plausible that efficacy for seizures is also at least partly attributable to normalization of arousal regulation. On the basis of the early work, it was close to hand to consider all the conditions being treated in terms of their arousal dimension, and in terms of the stability/instability continuum. Table 1 shows a classification of conditions with respect to the arousal axis, and with respect to the instability axis. In preparation of Table 1 it became obvious that this system of categorization represents an oversimplification, although it does provide a useful perspective. It is, for example, an oversimplification to talk about depression and anxiety as separate and distinct entities. It is a further oversimplification to appear to reduce these to merely arousal disorders. It is perhaps better to identify these as correlations or covariations. Then again, arousal itself is not a unitary concept. Moreover, the arousal dimension is very important in the conditions we have listed as instabilities (as already mentioned for seizures). It is hoped that the Table will prove useful in illustrating the connection between various conditions at the process level, and indeed the mechanisms by which EEG biofeedback can impact them. Table 1. Classification of Common Disorders in Terms of Arousal and InstabilityUnderarousal
Endogenous Unipolar or Reactive Depression Attention Deficit Disorder: Inattentive Subtype Chronic Pain (Low Pain Threshold) Insomnia (Frequent Waking)
Overarousal
Anxiety DisordersSleep Onset Problems/Nightmares Hypervigilance Attention Deficit Disorder: Impulsive SubtypeAnger/Aggression Agitated Depression Chronic Nerve Pain Spasticity
Underarousal/Overarousal
Anxiety and Depression Attention Deficit Hyperactivity Disorder: Combined Type
Instabilities
Endogenous Vulnerability
Tics Obsessive-Compulsive Disorder Aggressive Behavior Episodic Rage DisorderBruxism Panic AttacksHot Flashes Bipolar Disorder Migraine Headaches NarcolepsyEpilepsy Sleep Apnea Vertigo TinnitusAnorexia/Bulimia Suicidal ideation and behavior PMSMultiple Chemical Sensitivities Dysglycemia; Diabetes (Type II); Hypoglycemia Explosive Behavior
Exogenous Vulnerability
Just as depression has its arousal dimension, it also has its attentional dimension, and its affective dimension. Similarly for the other conditions listed. For present purposes, it is sufficient to argue that these are coupled systems. One of the most obvious implications of the biofeedback work is that it is not possible to intervene unilaterally with the brain. Impinging upon the arousal axis has implications for attention and affect, and vice versa. Moreover, challenging the brain with biofeedback tends to move the brain toward stability. The observation was made decades ago by Elmer Green that biofeedback in general moves the organism toward homeostasis and toward stability. This has been abundantly confirmed in the present work. Having said this, it is also possible to drive the brain toward any instability that may exist, with a powerful technique such as this. Skillful clinical application is still required. Instabilities can be characterized by the degree to which they arise autonomously within the CNS or require an external trigger for initiation. An internal vulnerability is referred to as endogenous, and an externally triggered vulnerability is referred to as exogenous. The relevant instabilities are distributed along a continuum in this regard, and a case can be made that there is a natural progression for different instabilities from the exogenous domain to the endogenous over the course of a lifetime. This is known as the kindling model, and it is particularly applicable to seizures, Tourette's syndrome, OCD, depression, anxiety and panic, bipolar disorder, and migraines. A crude attempt has been made at an ordering along the exogenous/ endogenous axis in Table 1.
EEG Biofeedback: A Generalized Approach to Neuroregulation By Siegfried Othmer, Susan F. Othmer, and David A. Kaiser To appear in "APPLIED NEUROPHYSIOLOGY& BRAIN BIOFEEDBACK"Edited by Rob Kall, Joe Kamiya, and Gary Schwartz Page 6 of 13 Arousal, Attention, and AffectThe conceptualization of brain function in terms of coupled systems was broached by W.R.Hess (1954). Experiments with electrical stimulation of regions of the diencephalon (thalamus and hypothalamus) in some instances led to very specific behavioral responses, and in other instances led to broad overall changes in behavior: arousal, quiescence, somnolence, torpor, and sleep. Hess subsumed these global changes in sympathetic and parasympathetic arousal in the terms ergotropia and trophotropia. The 'ergotropic shift' is characterized by a tendency toward higher sensory acuity, external focus, sympathetic arousal, high motor setpoint, etc. The 'trophotropic shift' is characterized, in contrast, by a tendency toward a more inward focus, less alertness, reduced sensory acuity, a shift toward vegetative functions, and a reduced motor system readiness. It is clear from our work that invoking either of these two shifts is possible with EEG biofeedback. What we refer to as "beta" training (15 to 18 Hz) is to be identified with a global ergotropic shift in organismic function, and that of "SMR" training (12 to 15 Hz) is to be identified with a trophotropic shift. The response of an individual to even a single session of EEG biofeedback training can make this quite obvious, an assertion which is independent of any claims for long-term efficacy of training. Long-term EEG training has the effect of exercising and expanding the brain's ability to move freely along the continuum of ergotropic or trophotropic dominance, with all its implications for arousal, attentional state, and affect regulation. This brain exercise moves the individual into regions where he or she may not heretofore have been able to reside comfortably or stably. This is made possible not only by increased flexibility of state, but by an increased ability to maintain overall nervous system stability. The reason that two primary training regimens (higher and lower frequency) are sufficient is attributable to the fact that the ergotropic shift and the trophotropic shift are mutually inhibitory. To enhance the one is to suppress the other, as was already apparent to Hess. Gellhorn (1967) originally referred to the dynamic balancing of the ergotropic and trophotropic domains in terms of 'tuning' of the nervous system. The EEG biofeedback, by explicit appeal to rhythmic mechanisms, may be seen as a particularly efficacious agency of 'nervous system tuning.' The brain's intrinsic bias toward homeostasis dictates that any training which evokes a brain response away from its then- prevailing equilibrium state will set in train forces to restore the original state. Thus, promoting an ergotropic shift will in first order tend to produce such a shift, and on the other, set in train compensatory mechanisms by which the brain restores the state it had intended for itself. Hence, even dis-equilibration can bring about improved equilibrium maintenance as a long-term consequence. Hemispheric Specificity of Training: Spatial Dependence of Protocols The clinical data reviewed below are supportive of the view that the training exercises the two hemispheres specifically, and differentially. Cumulative clinical evidence in our offices has also reinforced the view that referential training near C3 and/or C4 is generally the most effective. Small displacements from these sites laterally from the midline along the coronal plane seem to have a minor effect on the training. Small displacements in the horizontal plane, on the other hand, change the quality of the training more significantly in our experience. Hence the training sites have been determined by a process of local optimization (i.e., small spatial displacments), rather than of global optimization. For some applications (principally to the instabilities), T3 and T4 have been found preferable to C3 and C4, respectively. With a large amount of clinical data at our disposal (several thousand cases), a picture has emerged that the EEG training addresses the specific failure modes of each hemisphere. If a particular disorder could be associated more directly with one hemisphere than the other, it might give us a clue as to what part of the brain might require redress. Such a connection would then imply a unique, differential protocol. We found this to be true, and a number of disorders began to yield to assignment to one hemisphere or the other. Then, using a process of "local optimization" both in terms of spatial location and selection of the reward frequency band, a training strategy emerged which has gained considerable 'stability' from the effort at continual refinement, and what may have started out as mere clinical impressions have gradually been reinforced to the point at which they now constitute a defensible training strategy. The principal hallmarks of the strategy are as follows: 1. There appears to be a certain simplicity and directness attached to training along the sensorimotor strip. 2. Training away from the midline appears to yield stronger and more hemisphere-specific training effects, than training at Cz. 3. There is a distinct predominance of the need for up- regulation of the left hemisphere, using beta training (nominally 15-18 Hz), and a corresponding predominance of the need for down-regulation of the right hemisphere using SMR- training (nominally 12-15 Hz). Frequently, the need for both exist within the same individual. (This frequency dependence is addresses further below.)The apparent advantage of training at the sensorimotor strip for most of the conditions discussed is consistent with the early Sterman hypothesis, since amply validated, that what is being trained is the degree of rhythmicity of the thalamocortical regulatory circuitry. And whereas the rhythmic EEG activity observable anywhere on cortex is traceable to these thalamically-mediated regulatory functions, the primary sensory areas of cortex are perhaps the most direct access we have to them. Specifically, the highest cortico-thalamic fibre-density is to be found in the primary sensory areas of cortex (and also in projections to the frontal lobe). Historically, most of the EEG biofeedback training that has been done has focused on the primary sensory regions. Our continuing observation over a large clinical population of the need for up-regulation of the left hemisphere and down- regulation of the right can be explained in terms of the specific way in which the two hemispheres fail, or disregulate. The work of Malone, Kershner, and Swanson, et al, (1994), provides us with a detailed neurophysiological model which explains this hemispheric laterality in training effect. In this model, it is proposed that the left hemisphere (in collaboration with the frontal lobe) manages tonic activation for the conduct of intellectual and motor tasks, and for the maintenance of vigilance over time. This activity is preferentially under the management of the neuromodulators dopamine and to a certain extent acetylcholine. The right hemisphere, by contrast, manages phasic arousal for maintenance of sensory system readiness to receive and process new inputs from any source. This system is predominantly under the management of norepinephrine and to a certain extent serotonin.The model, as applied to ADD, which will be discussed further in the coverage of our clinical outcomes, reveals ADD to be a problem of underactivation of the left hemisphere, principally involving dopamine, and of overarousal of the right hemisphere, principally involving norepinephrine. Hence, neither the sequential processing of intellectual or motor tasks, nor the deployment of resources responding to new incoming stimuli are well managed. The efficacy of Ritalin is attributed to a dual influence, the up-regulation of the dopamine system and the down-regulation of the norepinephrine system. In a kind of parallel or equivalent model, ADD of the inattentive subtype is addressed with higher frequency left hemisphere training (central and possibly frontal) and ADD of the impulsive subtype is addressed with lower frequency training of the right hemisphere (central and possibly the parietal region as well). A mutual consistency thus emerges between the claims of EEG biofeedback and psychopharmacology for ADD. The Tucker and Williamson (1984) model lays a credible foundation for the general claim that the two hemispheres need to be specifically and differentially addressed in the training, just as they are pharmacologically. Recent clinical work has led to further refinements of the principal protocols so that they now incorporate frontal and parietal training with bipolar placements that combine left central with prefrontal sites (e.g., C3-Fpz), and right central and parietal sites (e.g., C4-Pz).These latter refinements specifically challenge communication loops between the selected sites. When a bipolar montage is used, then the reinforcement promotes an anti-phase relationship between the two sites. This may be counter- intuitive. It has been shown (Rappelsberger, 1994) that when distant cortical locations communicate with one another, they come into greater synchronization in the process. Why then would one wish to train these sites to reduce the prevailing degree of synchrony? The only justification that really counts is that this has been found effective empirically. The theoretical justification is to be found in the 'regulatory challenge' model of EEG biofeedback. The biofeedback reinforcement takes the brain momentarily out of its prevailing equilibrium, to which it then wishes to return. It may not matter in first order whether the disequilibration occurs in one direction or the other. Improved regulatory function may eventuate in either case. It may now be possible to generalize the Malone model to other conditions. Just as there are left hemisphere and right hemisphere aspects of ADD, the same may hold for affective disorders of depression and anxiety (Goodwin,1990). The left hemisphere aspects of depression and anxiety may have to do with anticipatory activity, planning, ruminating, perseverating, worrying. The right hemisphere, by contrast, may harbor the non-rational, more catastrophic aspects of depression and anxiety, namely fear, panic, agitated depression, and suicidality (Heller, 1997). With a spatially localizable technique at our disposal, hemispheric specificities have been confirmed with EEG training not only for ADD, cognitive function, anxiety, and depression, but also for pain syndromes, sleep disorders, eating disorders, endocrine and immune system disorders. Laterality turns out to be one of the key organizing principles for the evolution of protocols. The Protocols' Frequency DependenceProtocols used for EEG biofeedback training of the 12-19 Hz band, are essentially derived from Sterman's seminal work with seizures. The 12-19 Hz region was originally identified as being prominent in the bursts of sensorimotor rhythm of the cat (Sterman, 1969). Subsequently, operant conditioning of the cat EEG was restricted to the peak frequency range of this distribution, 12-15 Hz (Sterman, 1970). As additional work was undertaken with human subjects, the 15-18Hz band was also investigated in one study (Sterman, 1978). In the following, we will refer to training with the lower frequency (12-15 Hz) and higher frequency (15-18 Hz) bands. The lower frequency training has also been colloquially referred to as "SMR" training, for historical reasons, and the higher frequency as "beta" training. These terms have become commonplace through clinical usage, even though we are dealing with only a subset of the entire beta band, which extends from 12 or 13 Hz to 35 Hz. As we entered the field in 1985, we were aware only of the work of Barry Sterman, Joel Lubar et al., Michael Tansey, and Margaret Ayers with respect to the beta/SMR training. Joel Lubar et al. utilized both bands in the treatment of ADD (Lubar, 1984). Michael Tansey restricted himself to rewarding the frequency region centered on 14 Hz (Tansey, 1990), and Margaret Ayers used almost exclusively beta training (Ayers, 1993). In terms of electrode placement, Lubar et al. were typically using left-side training with bipolar placement near the sensorimotor strip, not deviating far from what Sterman had originally employed (C3-T3). Tansey exclusively used an electrode placement on the supplementary motor area, with a large-area contact that covered the space between Cz forward toward Fz, and also extending partially toward Pz. Margaret Ayers used C3-T3 placement almost exclusively, except when either symptomatology or EEG phenomenology indicated a need for right-side training at C4-T4. All of the above protocols were accompanied by inhibition of low frequency activity, typically 4-7 Hz (called "theta" in the following). In the case of Michael Tansey, the information regarding excessive theta amplitudes was verbally communicated to the client. Additionally, Sterman and Lubar provided for inhibition of high-frequency activity in the region above 20 Hz. Out of the work of these four pioneers, our protocols evolved in several stages. First, placement was changed from bipolar to referential to the ipsilateral ear, in line with a general trend within the field toward referential montage. Secondly, Cz placement was evaluated for the low frequency training on the basis of Tansey's work. For more than a year, most of the training was conducted at either C3 with the higher frequency band ('beta'), or at Cz with the lower frequency band (SMR), using an A1 reference. Excursions to C4 were, if needed, based on our early understanding of issues of laterality or in cases of localization of deficits to the right side (as in seizure disorders, head injury, and stroke). Over time, as we became more experienced and our understanding of the hemispheric specificity of certain aspects of cortical disregulation became clearer, it was observed that the C4 training was typically most effective with the lower frequency training, and that often stronger, more specific results were obtained than at Cz. Eventually, the predominant protocols became C3-beta and C4-SMR. Some frontal and parietal training was used as well to address specific issues.Though early protocol selection was based upon the prior research work, it soon became necessary to devise methods of assessment (to be discussed later in this piece) that would assist us in teasing out which of these protocols were most appropriate for the client. But if the judgment turned out to be mistaken, then there was always the option to make an early change in protocol. If the choice was appropriate, then a different protocol might be used later to address residual issues.It was observed also that if one persisted with the use of a single protocol, then eventually certain adverse symptoms could develop which called for compensatory training. Thus, with left-side training, ultimately client reports might indicate the need for right-side training, and vice-versa. Subsequently, more refined clinical skills led to an earlier integration of the secondary protocol into the training for optimization. This compensatory training led to the appreciation that in addition to addressing the specific failure modes of each hemisphere we really had to also achieve, or maintain, hemispheric balance. Symptoms could often be attributed to the inappropriate inhibition of one hemisphere by the other, or inappropriate disinhibition. This was most directly demonstrated when a left-side seizure focus was also favorably influenced by training the contralateral placement. But the principle has proved to be valid broadly. At the present stage of evolution of protocols, there has effectively been an integration of the C3-beta and C4-SMR protocols, which are both used with the majority of clients, generally within the same session, and the balance between them is titrated on the basis of symptom response. Assessment is then a matter of determining the client's physiological response characteristics, and the particular vulnerabilities expressed in their symptoms. In this appraisal, established clinical categories (from the DSM-IV) are only approximate guideposts. Whether diagnostic criteria are met in one respect or another is therefore irrelevant to the clinical burden. At least 80% of clients have been treated with this combination of protocols and this combination alone. The data reported in the following were obtained over the past eight years with the above protocols or derivations therefrom.
Back to Intro EEG Biofeedback: A Generalized Approach to Neuroregulation By Siegfried Othmer, Susan F. Othmer, and David A. Kaiser To appear in "APPLIED NEUROPHYSIOLOGY & BRAIN BIOFEEDBACK"Edited by Rob Kall, Joe Kamiya, and Gary Schwartz Page 7 of 13 Clinical Evidence: Validating the ModelClinical application is both the source and the destination of the theories and models proposed above. Without the surprises and inventiveness inherent in daily clinical practice, progress toward a comprehensive model for EEG biofeedback training would have been much slower, and the scope much narrower. By its very nature a research orientation must make certain choices and assumptions, and hold certain procedures invariant throughout the project. This does not allow for such a variety of approaches to be tried in such a short time. Yet, due to the volume of clients we were able to see since 1988, we have achieved significant depth of experience in a number of areas. It is now our goal to share this experience widely in order to allow it to be integrated with other approaches and perspectives, and subjected to more rigorous scientific evaluation and critique. The list of conditions for which clinical efficacy of EEG biofeedback has been observed is given in Table 2, along with the nature of the qualifying evidence (controlled studies; published outcome studies; single case studies and conference presentations). Key references are indicated separately at the end of the chapter. The number of subjects that fall into each category are estimated as well. No systematic inquiry was under taken to flesh out this table, so we don't claim that it is complete. All entries relate only to data of which we have become aware through various means, and are therefore a lower limit in each case. In our own work, and that of our affiliates, we have acquired confirming evidence for all of the conditions listed, with the exception of Lyme disease. Table 2. EEG Biofeedback StudiesADHD
Control Linden, Habib, & Radojevic (1996)Rossiter & LaVaque (1995)Nash & Shakelford (1995)Cartozzo, Jacobs, & Gervirtz (1995)

Outcome Kaiser (1998) Kaiser & Othmer (1997) Thompson & Thompson (1997) Lubar, Swartwood, Swartwood, & O'Donnell (1995) Scheinbaum, Newton, Zecker, & Rosenfeld (1995) Fenger (1995) Toomin, Ibric, & Othmer (1994)Samples (1994) Tansey (1991) Lubar (1985)Lubar & Lubar (1984) Shouse & Lubar (1979)

Case History Kotwal, Burns, & Montgomery (1996) Tansey & Bruner (1983)

LEARNING DISABILITIES
Control Linden, Habib, & Radojevic (1996)

Outcome Tansey, Tansey, & Tachiki (1994) Tansey (1991)Tansey (1990) Tansey (1985) Tansey (1984) Cunningham, & Murphy (1981)

Case History Kade (1995) Tansey (1993)

DEVELOPMENTAL DELAY
Control

Outcome

Case History Fleischman (1997)

AUTISM
Control

Outcome

Case History Sichel, Fehmi, & Goldstein (1995) Cowan (1994)

TOURETTE'S SYNDROME
Control

Outcome

Case History Tansey (1986)

EPILEPSY
Control Lantz & Sterman (1988) Lubar, Shabsin et al (1981)Sterman & MacDonald (1978) Lubar & Bahler (1976) Seifert, & Lubar (1975)

Outcome Hansen, Trudeau, & Grace (1996)Andrews, & Schonfeld (1992)Tozzo, Elfner, & May (1988) Tansey (1986)Cott A, Pavloski RP, Black AH (1979)Quy & Hutt (1979)Kuhlman (1978)Sterman (1977)Kuhlman (1977)Wyler, Lockard, Ward, & Finch (1976)Sterman, MacDonald, & Stone (1974) Sterman & Friar (1972)

Case History Walker (1995)Tansey (1985) Finley (1977)Finley (1977)Ellertsen & Klove (1976)Finley, Smith, & Etherton (1975)

MILD TRAUMATIC BRAIN INJURY
Control Ayers (1993)

Outcome HWalker (1998)Salerno (1997)Walker (1995)

Case History Byers (1995) Tansey (1994)Weiler, Schumann, & Brill(1994)

STROKE
Control Ayers (1994)

Outcome

Case History Rozelle, & Budzynski(1995)

MULTIPLE SCLEROSIS
Control

Outcome

Case History Walker (1995)

CHRONIC FATIGUE SYNDROME (CFS)
Control Lowe (1994)

Outcome Tansey (1994) Tansey (1993)

Case History James, & Folen (1996)

CHRONIC PAIN, MIGRAINES
Control

Outcome Othmer & Othmer (1994) Tansey (1991) Fehmi (1987)

Case History

IMMUNE DISORDERS
Control

Outcome Schummer (1995)

Case History

LYME DISEASE
Control

Outcome

Case History Brown (1995)Kirk (1994)

PRE-MENSTRUAL SYNDROME (PMS)
Control

Outcome Othmer & Othmer (1994)

Case History

POST TRAUMATIC STRESS DISORDER
Control

Outcome Manchester(1995)

Case History

BIPOLAR DISORDER
Control

Outcome

Case History Othmer & Othmer (1995)

Italics - Conference Presentation This list is staggering in the variety of conditions responding to the training. A comprehensive treatment of the claims for these conditions cannot be undertaken here. Instead, a subset of conditions will be reviewed to indicate the breadth of the remediation accomplished with respect to types of symptoms, and to demonstrate that the remediation is non-trivial. That is, it may lie quite out of the range of what can be expected via spontaneous recovery or even, in some cases, with the standard interventions. Subsequently, an understanding of these findings will be sought by looking at underlying physiological mechanisms. Before proceeding, it may be useful to make some more qualitative distinctions among the claims being made with respect to these varied conditions. Such an attempt is shown in Table 3. Here conditions are ranked according to the consistency with which remediation can be predicted; the completeness of the remediation; the duration of the training; and the simplicity or complexity of the protocols to be brought to bear. For entries in this table, the judgments are entirely our own, and are based on our own clinical experience. Click for Next Page

EEG Biofeedback: A Generalized Approach to Neuroregulation

By Siegfried Othmer, Susan F. Othmer, and David A. Kaiser

To appear in "APPLIED NEUROPHYSIOLOGY & BRAIN BIOFEEDBACK"
Edited by Rob Kall, Joe Kamiya, and Gary Schwartz
Page 8 of 13
A Review of Clinical Outcomes
In the following section, the categories listed in Table 3 will be reviewed in cursory fashion in terms of our own clinical experience (augmented by that of some other practices which have adopted the same protocols.) It goes without saying that such a cursory overview of such complex issues can only be unsatisfying to the critical scientist or the discerning clinician. We offer it only as kind of intellectual appetizer, in order to achieve a quick overview of the field that will motivate further engagement and inquiry.
Rating our Effectiveness
CRITERIA:
A) Consistency of Response B) Completeness of Remediation C) Duration of TrainingD) Ambiguity of Protocol
-Strong, Consistent Results-Full Remediation of Symptoms -Short Duration of Training -Simple, Standard Protocols -Complex, Variable and Multiple Protocols-Higher Variability of Outcome -Partial Remediation of Symptoms -Long Duration of Training

Effectivness cateories. Click the name that interests you.

Depression Hypoglycemia Stroke
Minor Traumatic Brain Injury Sleep Disorders Tourette Syndrome
Premenstrual Syndrome Anxiety Narcolepsy and Sleep Apnea
Headaches Chronic Pain Major Head Injury
Attention Deficit Disorder Oppositional-Defiant Disorder and Conduct Disorder Chronic Fatigue Syndrome
Attention Deficit Disorder-Combined Type Prenatal Substance Exposure Autoimmune Dysfunction
Bruxism Epilepsy

Depression
It is noteworthy that depression is among the easiest conditions to treat with EEG biofeedback. These findings cover not only the mild depression that is frequently seen in connection with ADD, such as the dysthymia observed in childhood or the kind of low-grade pervasive depression for which Prozac has become the palliative of choice. They also cover episodes of deep depression, including some which are accompanied by episodes of suicidality, and even reactive depression.

The early effects of the training may be observed in the first few sessions. A person may recover from an excursion into suicidality in just one or two sessions. Full recovery from depression may, however, require on the order of twenty to forty training sessions. The recovery is seen as a restoration of a normal range of physiological arousal. The recovery is not characterized, however, by a numbing of feelings or constriction in affective state (in the event of reactive depression), nor does it interfere with a normal grieving process. The training is usually effective in disrupting patterns of chronic pain that are often seen in depression, although we are not dealing here with an anesthesia. Normal pain sensitivity is retained.

It is noteworthy that with SMR/beta protocols the greatest efficacy for unipolar depression is achieved with beta training on the left hemisphere at sensorimotor cortex. Since the left hemisphere is where language resides, one is aided by the fact that the patient can usually articulate very well the consequences of each training session for left hemisphere function and thus help to guide the process. Matters are different with respect to agitated depression or suicidality. These are attributed to disregulation primarily lodged in the right hemisphere, and require the calming and more stabilizing lower frequency training in the general case. The client may not be in a position to either properly appraise or to articulate his or her own state with respect to right hemisphere dysfunction.

These findings are so startling in their import that perhaps they stretch the credulity of the reader, and are entitled to some further discussion to make this plausible. First of all, this finding of efficacy for depression is concordant with the belief among psychiatrists that depression is rather consistently responsive to electroshock treatment, as already mentioned in the introduction. In many clinical circles, ECT is considered the gold standard of treatment for depression. The severe side effects attendant to that procedure keep it from being employed except as a last resort, and in severe depression. However, the belief is firmly entrenched that depression is expected to respond to shock treatment in the general case. Shock treatment can be seen as a sudden change in the ambient electrical state of brain function. Existing reinforcement patterns of pathological arousal and affect are broken up, and a new homeostasis in terms of arousal level and affect can be quickly established and apparently sustained, often without continuing pharmacological support.

On the other therapeutic extreme, that of non-intervention, it is found that episodes of deep depression quite frequently result in spontaneous remission. Such remission is so commonplace in children and young adults, when deep depression is first observed, that anti-depressant medication has never been shown to be better than placebo (read spontaneous recovery) in children. (Just recently, a first study appeared in which statistical significance was achieved (Emslie, 1997). Yet no one would argue that the nervous system of a child is non-responsive to anti-depressants. The drugs clearly work there as well. It is simply that spontaneous recovery is so robust and commonplace that anti-depressants are not obviously superior statistically in a controlled research setting over a fixed time interval. The mechanisms are clearly in place for a natural recovery to occur in most individuals with a first experience with major depression.

Hence, the claim of efficacy of EEG biofeedback for depression would seem to have the same difficulty vis-a-vis spontaneous recovery that has confounded the drug studies. Not so. In fact, we assert that the mechanisms of spontaneous recovery and of EEG biofeedback are probably identical. The existence of a robust spontaneous recovery capability supports the claim; it does not undermine it. EEG biofeedback can simply induce a systematic re-normalization of arousal function which might also happen randomly all by itself. The difference is that when EEG biofeedback is employed, the response is prompt, predictable, relatively consistent, and more likely to be sustained over the longer term. Moreover, it tracks the specific protocols employed (in terms of electrode placement and reward frequency band). This proposition does not need to await statistical proof (although such proof would be salutary). Simple clinical observation is sufficient (just as it was for shock therapy).

Minor Traumatic Brain Injury
A second category in which rapid, substantial recovery is observed is minor traumatic brain injury. The principal symptoms associated with MTBI are listed in Table 4. Many of these symptoms relate to disregulation of arousal, and of these the majority is depressive in character: depression, inattention, irritability, effort fatigue, chronic pain, and frequent waking. Some relate to overarousal: mania, impulsivity, anxiety and fear, anger, and sleep onset problems. Others relate to cognitive function: dyslexia, loss of short-term memory, articulation problems, word retrieval problems. Other problems relate more to frontal lobe function: behavioral disinhibition, obsessive-compulsive disorder, exacerbated motor and vocal tics, perseveration.
Table 4: Characteristic Symptoms of Minor Traumatic Brain Injury
Headache Anxiety and Depression Aphasia
Chronic Pain Sleep Disturbances Visuospatial impairments
Dizziness-Vertigo Irritability Changes in appetite
Difficulty Concentrating Mood Swings Sensitivity to hot and cold
Difficulty with Attention Personality Changes Seizures
Difficulty Planning Effort Hemiparesis
Fatigue Palsies
Characteristically much of the whole spectrum of MTBI symptoms may be manifested in any one head injury victim. And characteristically also, essentially all of these symptoms remediate with the training at least to some significant degree, although at different rates. The recovery of energy, the restoration of the ability to sleep properly, and the stabilization of mood, are the early markers for EEG training. Subsequently, there is recovery of cognitive function, diminution of pain syndromes, and ultimately even recovery of memory function.
Efficacy of the biofeedback for MTBI is probably largely attributable to three factors: 1) restoration of appropriate regulation of arousal level; 2) increase in the stability of brain function; and 3) increase in the flexibility of brain function. Commonly in MTBI the EEG exhibits paroxysmal activity, or elevated low frequency activity. Typically also, significant deviations in temporal coherence may be seen between brain regions. These deviations may be in either direction. Too low a coherence would indicate insufficient coupling or communication between brain regions, and too high a coherence would indicate too tight a coupling. It is easy to explain low coherence in terms of axonal shearing or other structural injury attributable to the original trauma. However, that may be too facile.

EEG deviations tend to normalize with the training, as would be expected. However, that is not always the case. Nor does such normalization closely track the recovery of function. Hence the EEG is of limited utility as a measure of recovery of function. Diminishing of paroxysmal activity is attributed to an increase in cortical stability with a strengthening of thalamic regulatory control. Elevated low frequency amplitude could simply be a manifestation of functional disengagement, of low activation and arousal. It can also result from inappropriate cortical-cortical coupling, attributed to insufficient subcortical regulation. The recovery could therefore again be attributed to the strengthening of thalamo-cortical regulatory mechanisms. Finally there are the deviations in coherence themselves. The fact that coherence is likely to recover with training regardless of whether it is low or high indicates that we are dealing largely with functional disorganization rather than structural impediments to function. Again, it is postulated that reassertion of thalamic control of brain rhythms is sufficient to restore appropriate coherence. However, direct cortical-cortical communication surely also plays a role in normalization of coherence.

Recovery from depressive symptoms is attributed to the first factor, renormalization of arousal control. Restoration of cognitive function and short-term memory is attributed to an increase in continuity of brain function, to which the diminution of paroxysmal activity and delta and theta amplitudes are testimony. Paroxysmal activity is very likely to disrupt the temporal relationships by which images, concepts and gestalts are bound together as coherent entities and retained for processing. The subjective experience of this disruption is an inability to organize activities, to make plans, to weigh several competing ideas, to carry mental challenges through to their resolution, and to reliably retain a memory. Finally, the restoration of appropriate coherence leads to recovery of the person's original behavioral flexibility.

MTBI has been listed as responding very quickly and reliably to EEG biofeedback training. This is indeed the case, in the sense that there can be significant recoveries of function even in the first few sessions. A more complete resolution may require as many as 50-100 training sessions, although 20 ' 30 sessions are adequate in most cases. A representative sampling of 16 such cases was reported by Jonathan Walker, of the Neuroscience Centers in Dallas. The results are summarized in Table 5. The average recovery with respect to premorbid functioning, by self- report, was 83%, and the median improvement was 85%. The average number of training sessions was 32, and the median was 30. The EEGs changed in line with the protocol to a statistically significant degree (decrease in theta amplitudes, and an increase in beta amplitudes).
Table 5. Recovery by self-report from symptoms of Minor Traumatic Brain Injury.
Client Baseline Post training Baseline Post-training Percent Improvement Number of Sessions
av.pwr Beta/Cz av.pwr Beta/Cz av.pwr q/Cz av.pwr q/Cz
K.R. 5.1 8.3 12.1 7.2 100 14
R.M. 6.5 16.9 11.3 10.8 80 12
M.M. 7 9.3 14 11.9 95 18
J.M. 15.1 18.6 10.5 6.5 90 40
C.G. 4.8 5.6 22.6 19.5 80 43
A.D. 14.4 20.4 10.6 7.8 50 46
S.A. 4.4 5.2 13.9 15.7 90 13
T.G. 5.8 12.8 13.1 13 80 35
P.K. 6.1 11.7 24.7 17.8 50 86
M.D. 8.6 12 18.4 15 80 30
E.S. 9 9 17.4 17.1 100 30
C.H. 10.1 8.1 13.1 11.9 90 20
S.S. 7.7 9.5 27.8 23.1 100 42
S.B. 8.2 11 14.6 9.3 75 23
G.C. 4.7 5.1 12 9.4 98 22
S.B. 9.3 13 25.8 16.9 75 30
Data courtesy of Jonathan Walker, MD
There may also be obvious deficits remaining that relate to organic (morphological, structural) injury. In these cases significant recovery is possible as well, but the rate- limiting mechanism is presumably some dendritic regrowth or rearborization. Hence the pace of progress is only partly conditional on the schedule of training. The trainee may continue to make gains by returning to the training episodically, to exploit any new learning opportunity. This phase of training is similar to the experience of Bernard Brucker (1985) in his EMG training for spinal chord injury, where it is found that a limb which did not yield to training on one occasion may readily respond a year later.

When specific organic injury has occurred, it seems more appropriate to include this in the category of major head injury. However, the latter distinction is reserved for those head injuries in which skull fracture or major organic loss has occurred. This is a less meaningful distinction, and often uncorrelated with the severity of deficits incurred. Paradoxically, some head injury that involves skull fracture can be less severe than minor head trauma. Conceivably, this could be due to the fact that the skull fracture, by yielding somewhat on impact, can reduce the g-forces sustained by the brain and the brainstem. For present purposes, organic injury is lumped along with major head injury, and as such appears in the last column of the chart.

The intimate connection of head injury symptomatology with disregulation of arousal seems to have been under-recognized by clinicians, who have by and large retained both a structuralist perspective as well as a focus on the cortex as the locus of injury. When such techniques as CAT scans and structural MRI scans failed to confirm injury, the victim was often declared to be a malingerer and his symptoms discounted. Thus the person became a victim a second time, in this instance of the clinician's myopia. In fact, most head injury involves severe jostling of the head upon its spindly neck, resulting in trauma to the brainstem, from whence arousal is managed. Fortunately, such injury consists more likely of compressional effects such as anoxia rather than of actual axonal shearing. As such, the injury is functional in nature, rather than structural, and turns out to be eminently remediable with our techniques.

EEG Biofeedback: A Generalized Approach to Neuroregulation By Siegfried Othmer, Susan F. Othmer, and David A. Kaiser To appear in "APPLIED NEUROPHYSIOLOGY& BRAIN BIOFEEDBACK"Edited by Rob Kall, Joe Kamiya, and Gary Schwartz Page 9 of 13 Premenstrual Syndrome Another indication for which EEG biofeedback is very helpful is Premenstrual Syndrome (PMS). This condition is not recognized as a distinct disorder in the DSM-IV, but that is probably at least partially in recognition of societal sensibilities. In its severe form, it is known as Premenstrual Dysphoric Disorder, which is conditionally listed in the Appendix of the DSM-IV (DSM-IV, p. 715). The difficulties with such a listing are, among others, that the symptoms of PMS are so diverse, so highly variable, so subject to 'psychosomatic" influences, so frequently seen simply as an exacerbation of other existing disorders, and so devoid of discernible organic basis. One wishes to blame hormonal shifts, but these are not usually out of line in those suffering PMS symptoms.The weight of evidence is that PMS is a matter of brain sensitivity to ordinary shifts in hormonal levels. PMS can even be considered as the defining condition for the functionally based "brain disregulation model" of psychopathology. That is, disregulation is the defining characteristic of PMS, and the remedy offered by EEG training is to return brain function to homeostasis and to stability, i.e. to a restored capacity for neuroregulation. Almost no condition remediates as completely and consistently as does PMS with EEG training, and few conditions entail such a breadth of symptomatology. Yet PMS in all its clinical variety is successfully addressed with little more than this straight- forward training. PMS symptoms which have been identified are shown in Table 6 (O'Brien, 1987), and the symptoms which have been observed in our practice, and which have been subject to remediation, are shown with an asterisk. We have no relevant experience with the symptoms that are not marked. Physical
*Drowsiness *Blurred Vision Epilepsy *Pelvic Pain
*Fatigue *Breast Swelling Finger Swelling Edema
Thirst *Breast Tenderness *Flushes *Nausea
*Proneness to Accident *Clumsiness Formication *Muscle Pain
Acne *Constipation *Headache, Migraine *Joint Pain
Asthma *Diarrhea Weight Increase (actual) *Vomiting
Bloatedness (actually) Dizziness Increase (feeling of) Vertigo *Hypoglycemia
Behavioral
*Aggression *Hypersomnia *Loss of Self-Control
Anorexia *Impulsive Behavior *Social Isolation
*Decreased Alertness *Increased Libido *Suicidal Tendency
*Decreased Libido *Insomnia Formication
*Food Craving *Lack of Volition *Tension
*Hunger *Lethargy, Listlessness *Violent Behavior
*Bloatedness(feeling) *Loss of Judgment *Weight
Cognitive
*Confusion
*Loss of Concentration
*Proneness to Accident
*Poor Coordination
Emotional
*Agitation *Loss of Confidence
*Anxiety *Malaise
*Contentiousness *Moodiness
*Depression *Pessimism
*Emotional Lability *Sadness
*Hopelessness
*Irritability
The above results are also non-trivial. PMS symptoms can be disabling in their severity fo