Orne, M. T., & Wilson, S. K. On the nature of alpha feedback training. In G. Schwartz & D. Shapiro (Eds.), Consciousness and self-regulation: Advances in research and theory. Vol. 2. New York: Plenum Press, 1978. Pp.359-400.

9 On the Nature of Alpha Feedback Training

I. INTRODUCTION

A new kind of interaction between man and his body, biofeedback, elicited enthusiastic interest in many sectors of the scientific community in the late 1960s. A number of investigators had shown that automatic electronic sensing and feedback of a wide variety of usually unconscious physiological functions allowed individuals to directly influence internal processes that had previously been considered beyond volitional control. These included galvanic skin response (Crider, Shapiro, and Tursky, 1966), heart rate (Engel and Chism, 1967; Engel and Hansen, 1966), blood pressure (Shapiro, Tursky, Gershon, and Stern, 1969), evoked cortical potentials (Fox and Rudell, 1968; Rosenfeld, Rudell, and Fox, 1969), and EEG (Hart, 1968; Kamiya, 1969; Mulholland, 1968). Perhaps most impressive was the elegant demonstration by Miller and DiCara (1967) that curarized animals could acquire instrumental control over visceral and glandular responses.

EEG brain alpha wave feedback had particularly struck the imagination of researchers and public alike. Alpha waves -- the large sinusoidal 8 - 13 cycle per second EEG activity -- had been linked by earlier studies (Lindsley, 1952; Stennett, 1957) to intermediate levels of arousal. The alpha rhythm was felt to be most prominent when the individual was neither drowsy nor hyperalert. Within this theoretical context, Kamiya (1969) demonstrated that individuals could control

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alpha density through feedback and consequently maintain higher alpha levels. Further, this enhanced alpha density was associated with pleasant, relaxed feelings (Brown, 1970, 1971; Hart, 1968; Kamiya, 1969). These results thus suggested that alpha feedback was a method by which modern man might achieve direct control over the level of his neurophysiological arousal and, therefore, over his anxiety and dysphoria. The potential, not only for the troubled individual but for everyone, appeared unlimited and held out the promise of our advancing beyond the age of drugs into an age of direct, conscious control of many psychobiological processes.

In the discussion to follow, we seek to evaluate the disparate scientific observations that made this dream plausible. We also focus on the line of research carried out at the Unit for Experimental Psychiatry specifically intended to clarify those aspects of alpha feedback training, and of the alpha mechanism itself, that are crucial to the potential therapeutic application of alpha feedback training. Finally, we try to spell out to what extent these hopes now seem justified and the possible directions of future research.

II. STUDIES SUGGESTING ALPHA FEEDBACK TRAINING MAY INFLUENCE SUBJECTIVE EXPERIENCE

Berger (1929) demonstrated in his initial studies that the predominant EEG rhythm in relaxed individuals sitting with their eyes closed in a darkened room is alpha. He found that when the individual becomes drowsy, alpha activity rapidly disappears, while a stimulus that causes the individual to be startled, surprised, anxious, or frightened blocks the presence of alpha, at least temporarily. Later, Jasper (1936) suggested, and Lindsley (1952) and Stennett (1957) tried to document, that the relationship between alpha density and activation or arousal (both physiological and subjective) may be described by an inverted U-shaped function. They felt that during high arousal, as in anxiety-tension, alpha density seemed reduced and that it approached minimal levels with extreme excitement or panic. Alpha density was at maximal levels during alert, but relaxed, nonfocused mind-wandering. It disappeared from the EEG record with the onset of sleep. Thus, maximal alpha density appeared to reflect an intermediate level of arousal, that level at which an individual is neither drowsy nor hyperalert but rather comfortably relaxed. If alpha feedback training could teach an anxious individual to produce high alpha density he might concomitantly reduce his level of arousal to relaxed alertness, with its associated subjective state of pleasant relaxation.

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The issue to be resolved seemed to be whether it was possible to learn to control such neurophysiological functions directly.

The initial enthusiasm for alpha feedback training appeared particularly warranted because brain functioning, in contrast to heart rate or blood pressure, logically seems to be more closely connected with subjective experience. Further, while not dealing directly with alpha feedback, the studies of feedback control over other visceral states, such as blood pressure or galvanic skin response, provided substantial scientific support for the view that feedback might be used to gain control over otherwise automatic physiological processes. Some investigators, from purely teleological deduction, felt even then that nature could never afford to leave life-supporting homeostatic systems to the capriciousness of conscious intent. However, the original study of heart rate feedback with curarized rats had dramatically shown that an animal could be induced to slow its heart, even to the point of death (Miller and DiCara, 1967).

A. Subjective Identification of Alpha Production

In light of the hypothesized relationship between alpha and arousal, Kamiya's (1969) anecdotal report of early work showing that subjects could learn to recognize the presence of alpha in their EEG was of great conceptual importance in providing a logical link to suggest that direct biofeedback of alpha wave production might produce desired subjective experiences. While observing the clinical EEG of a number of subjects, Kamiya instructed them to indicate whether they were producing brain wave state A (alpha) or brain wave state B (non-alpha) each time a bell rang. He provided feedback by telling them whether their statements were correct. Over a period of several hours some subjects apparently learned how to correctly identify alpha 100% of the time. Further, in Kamiya's later experiments on training the subject to enhance or suppress alpha, spontaneous alpha density during rests between training trials was higher than before, apparently because these subjects preferred the high alpha state.

Kamiya (1969) felt that it was not possible to conclude from the available data that the presence or absence of alpha was associated with perceptible alterations in subjective experience, but he reported that the subjects appeared to have gained some control over their brain wave states. It was not clear to Kamiya how and to what extent alpha production itself was represented in conscious experience; nor was it clear whether in order to identify it, the person was associating

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certain levels of arousal or other behaviors with the concomitant changes in alpha production. He proposed that the data did suggest that it was possible to learn both to control alpha and to produce specific subjective states by attending to simple biofeedback signals based on EEG activity.

Given the above observations, it seemed reasonable to interpret Kamiya's (1969) finding as indicating that feeding back the presence or absence of alpha would allow an individual to learn to produce maximal levels of alpha density. This, in turn, would produce a level of arousal between drowsiness and hyperalertness -- a state of mind (and body) that, furthermore, might produce the salutary effects reported by meditators, who also seemed to have high-amplitude and high-density alpha in their EEG (Anand, Chhina, and Singh, 1961; Wenger and Bagchi, 1961).

B. Meditation and Alpha Waves

Another important theoretical support for the use of alpha feedback training emerged from an increasingly widespread interest in Eastern religions in general and meditation in particular. Previous studies of the physiological status of Far Eastern meditators during normal waking and meditation produced apparently striking confirmation of the notion that alpha waves were directly related to relaxed states of mind. Anand et al. (1961) and Wenger and Bagchi (1961) studied the EEG of yogis and reported that their brain waves showed a predominance of very-high-amplitude alpha waves. Further, the kind of stimuli that normally caused subjects to block alpha failed to block alpha production in meditating yogis, whose discipline trains them to turn inward and ignore the outside world. Kasamatsu and Hirai (1966) studied Zen masters, who, in their meditation, are trained to remain open and seek to experience even mundane stimuli as continually new and fresh. They also noted very-high-amplitude alpha in these subjects. In contrast to yogis, however, these individuals not only showed the usual alpha blocking response to novel stimuli but continued to block alpha indefinitely, even to the same trivial stimulus. In other words, the meditating Zen masters failed to habituate.

These studies of Zen masters and yogis, considered together, were of special interest, not only because they suggested that meditators in general tended to have large amounts of high-amplitude alpha, but also because their EEG demonstrated alpha characteristics commensurate with their mental discipline. The meditating yogis failed to show alpha blocking in response to a stimulus, while the Zen masters

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failed to show habituation. Thus, particular states of mind seemed reliably associated with easily measured neurophysiological processes.

III. THE BASIC ALPHA FEEDBACK EXPERIMENTS

Taken together, the several lines of preliminary inquiry described above were felt to be potential evidence for the idea that alpha feedback might be developed into a major tool for the self-control of subjective experience. All that seemed necessary was the proper electronic equipment, adequate training methods, and properly motivated individuals. A number of studies that supported this general hypothesis soon appeared.

A. Some Encouraging Alpha Feedback Results

Kamiya (1969), following up his early experiments on the identification of alpha, used electronic circuitry to identify the presence or absence of alpha waves in the EEG. He arranged the equipment so that either a light or a tone would go on whenever alpha waves were present. The subject sat in a dimly lit room and attended to either a visual or an auditory feedback signal. He then was trained to produce or block alpha by instructions to keep the signal on or off, respectively. Kamiya, as well as Hart (1968) and Mulholland (1969) independently, showed that in such conditions subjects could exert volitional control over the presence or absence of alpha. Kamiya pointed out that this control was manifested most dramatically in the ability to reduce alpha but added that subjects seemed to prefer the alpha state. Further, they tended to describe the state in characteristic terms, such as relaxed, calm, and pleasant. Brown (1970) found similar reports of relaxation, total concentration on the feedback light with a loss of awareness of the surroundings, etc. Interestingly, although Mulholland's subjects also were able to increase alpha, they did not report many of the striking subjective changes found by Kamiya and others.

The subjective experiences apparently associated with alpha wave production were explored more carefully by several investigators but substantiated perhaps most intricately by Brown (1971). Using appropriate electronic circuitry, she illuminated different colored lights, depending on the type of EEG wave in the subject's record. For example, blue or red lights were used for alpha, red or green for beta, and green or blue for theta. The subjects were encouraged to play with the lights for an hour and try to associate specific feelings with each of them. Forty-five subjects received this kind of feedback.

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For each subject, one of the two possible light colors was associated with one of the three EEG frequency bands identified above. The subjects were then asked to sort more than 100 mood-descriptor terms into the appropriate red, blue, green, or white bin, symbolizing the three colored lights and no particular color association, respectively. Brown (1971) compared their sorting with the sorting performed by 45 control subjects who had not undergone the three-light feedback and had not associated any colors with the experimental situation. She was able to show that the experience of linking an EEG state with a colored light significantly changed the mood terms sorted with that color. Descriptors significantly associated more frequently with alpha colors were calm, peaceful, pleasant, at ease, neutral, illusion, dreamlike, mysterious, and uncertainty. Beta wave production (low voltage or small waves of greater than 13 Hz) was associated with feelings of being angry, aggravated, irritated, impatient, unhappy, troubled, frustrated, touchy, shaky, and investigative, as well as with feeling a void inside.

Thus, a much more specific assessment of the associated subjective experiences again seemed to confirm Kamiya's (1969) original reports. It appeared, then, eminently reasonable to try to utilize alpha feedback training as a means of helping the individual learn to gain control over the extremes of arousal. The only further requirements seemed to be an appropriate learning context for the subject and the necessary learning schedules.

IV. ESSENTIAL REFINEMENTS OF ALPHA FEEDBACK METHODS

If the therapeutic applications of the above findings were to be justified, several issues of both practical and theoretical importance required attention. Perhaps the most readily apparent problem was the wide individual differences in alpha density found among subjects -- an observation Berger (1930) made early in his research. Some subjects in a darkened room show almost continuous alpha, which may persist even in the presence of light, while others show none. In a dimly lit room, under novel circumstances, Kamiya (1969) observed that most subjects had relatively low levels of alpha, which gradually increased over the session. Individual differences in baseline alpha density and the rising levels of alpha density that occurred during sessions presented serious methodological problems for efforts to document the effectiveness of feedback enhancement of alpha density.

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A. Control of Subject, Methodological, and Situational Factors

The solution to the problem of individual differences originally attempted by Kamiya (1969) was to equate individuals with widely differing levels of baseline alpha production by setting the electronic filter gains arbitrarily for each subject so that the alpha-on signal would be presented 50% of the time regardless of the actual amount of alpha shown on the EEG record. Working in an operant conditioning context, Kamiya could equate, between subjects, the amount of positive reinforcement -- the subject's feeling of success -- in the task. Unfortunately, this procedure tended to focus attention away from the individual's actual changes in alpha density and artificially created a situation in which changes in apparent alpha density were emphasized. Only in later work (Nowlis and Kamiya, 1970) was any attention paid to the interaction between the initial level of alpha density and the effects of training procedures.

Other means of equating extreme differences between subjects were also employed in the later Kamiya studies. For example, Nowlis and Kamiya (1970) provided feedback to subjects with their eyes closed but asked some subjects to keep their eyes open if their initial alpha density was high. The latter condition would depress the high resting alpha levels and thus bring the starting alpha density of these subjects to a level more similar to that of individuals with moderate alpha density.

In these early alpha feedback studies the assumption was made that alpha density somehow reflected a basic psychobiological process, and little attention was paid to whether the individual's eyes were open or closed or to whether the circumstances were novel or the subject was well habituated; nor was there much concern with whether the feedback modality was auditory or visual. The possible interactions among initial baseline alpha levels, the circumstances of recording, and subsequent changes in alpha density were not considered. However, these issues must be taken into account, and extensive baseline measures of alpha density levels must be obtained before the results of feedback training can be compared between laboratories.

B. Replication of Alpha Feedback Results with Refined Methodology

Our first study sought to replicate the findings reported by Kamiya (1969) and others mentioned above (Brown, 1971; Nowlis and

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Kamiya, 1970) but hoped, by attention to methodological detail, to gain a clearer understanding of the process. To facilitate analysis, eyes-closed and eyes-open baselines were obtained at both the beginning and the end of the experiment. The learning trials consisted of 2-min periods interspersed with 1-min rest periods. In order to demarcate clearly the beginning of rest, the feedback signal was arranged to provide a green light for the presence of alpha and a red light for the absence of alpha. The light was turned off to signal the onset of the rest periods. Instead of arbitrarily setting the electronic equipment to register 50% alpha, we set the equipment to reflect the presence of alpha as defined by standard definitions for the hand scoring of EEG wave forms. To accomplish this goal, a special filter with extremely sharp cutoffs, providing almost immediate discrimination of alpha, was developed (Paskewitz, 1971).

In addition to recording EEG from monopolar frontal (F4) and occipital (O2) electrode placements referenced to the ipsilateral mastoid, the procedure, followed in virtually all the early studies, also involved the recording of eye movements, heart rate, and the electrodermal response. Continuous paper recordings were made on a Beckman dynograph, and the data were also recorded on magnetic tape. The feedback system used occipital EEG signals, with the specially developed hybrid filters having step-function cutoffs at 8 and 12 Hz. There was a further amplitude criterion of 15 or 20 µV, depending on the particular experiment. At the completion of each session, a postexperimental interview was carried out during which the subject was asked about both the strategies employed to increase alpha density and the nature of his experiences during the experiment.

The first study included an initial session devoted to classical conditioning, followed by two feedback sessions on successive days (Lynch, Paskewitz, and Orne, 1974; Paskewitz, Lynch, Orne, and Costello, 1970). The results demonstrated that individuals did indeed learn to increase alpha density across trials, as had been reported by others. Figure 1 shows the effect of alpha feedback on seconds per minute of alpha produced by 16 males. Using visual feedback, subjects quadrupled the amount of alpha emitted during their first feedback session. However, we noted that this apparently dramatic increase took place from a very low initial level of alpha density. Thus, they went from an average of 2 sec/min of alpha density to an average of 8 sec/min of alpha density during the ten 2-min trials interspersed with 1-min rest periods.

Previous experimenters (Kamiya, 1969; Mulholland, 1969) had shown that subjects could volitionally block alpha as well as increase it when given appropriate instructions. We were also able to confirm

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this finding in the same study. Thus, on the second day of feedback training, subjects had five feedback trials with instructions to augment alpha, followed by several trials during which they were alternately told to increase and decrease alpha density. Figure 2 certainly seems to document the claim that subjects can be taught to reduce, as well as to increase, alpha; however, careful examination indicates that something other than learning could explain this observation. On the very first trial during which subjects were told to "keep the red light on," alpha density dropped to a level nonsignificantly below the initial trial on Day 1, when feedback training with the visual display was started. Since subjects were producing almost no alpha under these circumstances, performance during subsequent "alpha-off" trials could not manifest any significant increase in alpha blocking from that seen during the first trial. It would, therefore, appear inappropriate to speak of subjects' learning to block alpha, since this is a skill that they seem to possess from the very beginning.

C. The Effects of Alpha Feedback on Subjective Experience

Care was taken in this study to solicit subjects for an experiment in conditioning rather than running self-selected individuals who wanted to be trained to increase alpha density. Only rarely did we encounter any subjective reports reminiscent of those described by

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Kamiya (1969). In those occasional instances when subjects did report a kind of calmness or relaxation, it was invariably associated with the feedback trials, when the actual alpha density was, of course, far lower than during the rest periods in total darkness. While we were not prepared to dismiss the possibility that alpha feedback training might lead to systematic subjective effects, such effects were clearly not a simple function of alpha density. If this were the case, subjects would have reported being in an "alpha state" during the baseline periods of rest, when the actual alpha density was significantly higher than during feedback trials in the presence of light. We never encountered a subject giving such reports, and we therefore concluded, even at this early stage, that the subjective changes could not be simply a matter of the level of alpha density. However, it was felt that they might conceivably involve an increase in alpha density under circumstances that normally depress it.

D. Alpha Density during Light Feedback versus Resting in Darkness

The nature of the results of feedback training during the first study may be understood more clearly when placed in the context of

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the alpha density during the initial eyes-open and eyes-closed baselines in total darkness as well as the alpha density during the rest periods. In these intervals, the feedback light was turned off and the feedback room again became totally dark. It is evident in Figure 3 that subjects in total darkness began with a spontaneously high baseline level of alpha density, which was promptly depressed by the visual feedback stimulus. However, during the rest period, when the room again was in total darkness, the alpha density returned to the much higher baseline levels.

V. THE SIGNIFICANCE OF THE VISUOMOTOR SYSTEM FOR ALPHA FEEDBACK TRAINING

As Berger (1929) had already recognized, the presence of light is typically associated with a precipitous drop in alpha density. It

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seemed that the increase in alpha density associated with visual feedback, a circumstance that normally suppresses alpha, involved learning to avoid attending directly to the visual stimuli. Therefore, since the alpha density with visual feedback was of a far lower order of magnitude than that produced spontaneously in total darkness, it seemed more appropriate to speak of individuals' learning to disinhibit -- in the Pavlovian sense -- the alpha blocking effects associated with the presence of light, rather than to consider these data as a demonstration of learning to increase alpha.1 Mulholland (1969) had independently shown that the process of habituation to the feedback stimulus is reflected by a gradual increase in the length of alpha bursts associated with it. Thus, the increase is also a product of adaptation to the feedback signal rather than of learning alone. This phenomenon explains in part why one typically sees a gradual increase in alpha density during feedback, regardless of the subject's success in producing alpha density greater than baseline levels.

In view of the dramatic effects associated with the visual feedback system, it seemed evident that if one hoped to find a true enhancement of alpha density, it would be necessary to carry out feedback training in the absence of light. Thus, we sought to determine whether individuals starting feedback training with alpha density already at a high baseline level could learn to increase alpha density to significantly higher levels. Accordingly, feedback signals were changed to tones, and all light was eliminated from the experimental room. The presence of alpha was signaled by a 75-dB tone presented at 360 Hz, and its absence was signaled by a 75-dB tone presented at 280

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Hz. The frequency difference was easily discriminated by the subject, and the tones were not experienced as noxious. In pilot studies, we determined that it made no intrinsic difference which tone was used to signal alpha and which was used to signal nonalpha.

A. Alpha Feedback in Total Darkness versus Dim Ambient Light

A study was conducted with nine subjects run in total darkness for six sessions, each separated by approximately one week (Paskewitz and Orne, 1973). Monopolar EEG recordings of the right occipital and the right frontal brain areas, each referenced to the right mastoid, were made. After an initial 3-min eyes-closed and a 3-min eyes-open baseline, an orientation period of 5 min was provided during which feedback was available, and the subject was encouraged to experiment with the tones to learn how his thoughts and behavior could affect them. The subject was then instructed to try to keep the high-pitched tone on and was given ten 2-min feedback trials interspersed with 1min no-feedback rest periods. All feedback training was carried out in total darkness. 2

Although during the first session subjects' initial high alpha activity was reduced markedly when they first opened their eyes in total darkness, they recovered much of this drop by the middle of the initial 5-min orientation period (Figure 4). These increases occurred within 2 or 3 min without instructions to augment alpha density. Whether they represent true learning or adaptation is unclear, but the rapidity of the increase was different from what was usually described as occurring with feedback training. Further, during the later sessions, this initial drop in alpha density during eyes-open baseline became

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progressively less, presumably as subjects ceased to orient in a situation that was no longer novel.

The data suggested that subjects approached their maximal alpha density during the initial orientation period. The highest alpha density reached during any of the 10 alpha augmentation trials was only 7.2% more than that during this orientation period (t = 1.81, p > 0.10). Although in the group data the resting levels tended to be below trial levels, these differences were not significant.

When both trial and resting averages for all six sessions were examined with an analysis of variance, repeated-measures design, not one of the differences was significant (trials: F = 0.19, p > 0.20; rest: F = 0.05, p > 0.20). The largest difference between any two trial averages was only about 4 sec of alpha activity per minute. The trial average for the sixth session was not greater than the level of alpha density reached during the third minute of the orientation feedback period in the first session (t = 0.35, p > 0.20). Thus, within sessions or across sessions, no evidence indicative of learning to augment alpha density beyond the highest half-minute of alpha during the initial eyes-closed baseline period was noted in any of the subjects. Most important, subjects' initial eyes-closed baseline was not significantly exceeded at any time during the six days of training (Figure 5).

It appeared that by eliminating light from the feedback setting,

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one also eliminated any evidence of alpha augmentation during feedback training. These data, in conjunction with extensive pilot studies, led us to conclude that subjects do not appear to exceed their initial optimal baseline levels of alpha density with feedback training. Evidence of learning was present only if alpha density levels had somehow been depressed. To document this last point, it was necessary to clarify the relationship of these data to the effect of light on alpha density.

So that we could confirm the essential effect of the presence of light, the subjects who previously had failed to show any evidence of learning after six sessions spread over six days were asked to return for one additional day of feedback. Eight of the nine subjects were able to participate. Their EEG response in the identical experiment except for the presence of ambient light was far more similar to that of earlier subjects given light-signal feedback than it was to their own past performance during six sessions in total darkness (Figure 6). Recovery from the initial drop took place slowly, but their highest trial alpha density was 55.7% higher than their highest minute during the orientation period (t = 3.04, p < 0.02). The difference between trial and resting averages was significant (t = 2.47, p < 0.05). Tests between the results of the first session in total darkness and the subsequent session with dim ambient light indicated that the session with light for those same subjects was significantly different -- both in reduced trial averages (t = 9.11, p < 0.001) and reduced resting averages (t = 5.57, p < 0.001) -- from their performance in darkness.

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The importance of light, which had long been noted and again underlined in the earlier studies, was now clearly identified as being of major significance to any understanding of the alpha feedback experience. Further, the data supported the hypothesis that the apparent augmentation of alpha density during feedback occurred only when alpha density previously had been depressed by light. The increment in density shown during feedback seemed to involve the individual's gradually learning to ignore the stimuli that had been responsible for alpha suppression in the first place; that is, to cease orienting to visual stimulation.

B. "Looking" and Alpha Density

Mulholland (1969) previously suggested that alpha production was intimately related to visuomotor activity, specifically that of the triad of visual accommodation (convergence, pupillary constriction, and lens accommodation) rather than to visual stimulation, visual attention, or attention itself. He argued that only to the degree that

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attention is coupled with oculomotor control is it likely to be linked with alpha. This hypothesis regarding the connection between alpha production and the triad of accommodation was tested by Pollen and Trachtenberg (1972), who demonstrated that alpha blocking still occurred when the visual task was arranged so that feedback for accommodative effort was neither available nor required (accommodation was blocked with a cycloplegic agent, and lenses were provided to allow focused vision). Thus, although there are obvious limitations to the use of peripheral nerve blocks to examine central nervous system performance, this study suggested that the specific nature of the link between alpha and vision was still obscure. However, the general conclusions that could be reached included that, in some way, visual activity had a powerful influence on alpha density. Our data were also in agreement with this idea. Therefore, we sought to tease apart the relationship between visual attention and that of attention in general with regard to alpha density.

An unpublished study 3 compared attempting to see a barely perceptible visual stimulus with attempting to hear a barely perceptible auditory stimulus. Nine subjects participated in the experiment, which was conducted in a totally dark room. Baselines for eyes-closed and eyes-open alpha density were obtained. Counterbalanced sequences of an auditory and a visual attention task were then conducted as follows: The subject was told that sometime after a tone sounded a very dim light would be turned on. As soon as he perceived that the dim light was actually on, he was to press a button to let the experimenter know. The contingencies were arranged so that the very faint and difficult-to-identify light was turned on some 45 sec after the signal. A closely analogous task involved the identification of the presence of an auditory stimulus that was barely above threshold. This task, although equally difficult for the subject, had a significantly different impact on alpha density.

As Figure 7 shows, alpha density dropped precipitously -- approaching zero in several subjects -- as soon as the signal was given to search for the light and well before the stimulus was actually present. Once the light was identified, alpha density tended to increase again. In some cases, the light was not actually identified by the subjects, but the effort of trying to locate it was nonetheless sufficient to depress alpha density. Thus, even in total darkness, the attempt to see an object served to depress alpha density. Visual search produced alpha levels that were significantly below those during the auditory task (ts

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for the three trials, 3.08, 2.40, and 3.45; p < 0.01) and rests (ts for the three trials, 4.43, 2.60, and 3.08; p < 0.01). Alpha density during auditory search was not significantly below resting levels of alpha density (ts for the three trials, 1.23, 0.18, and 1.16; p > 0.10). Clearly, in contrast to visual search, the auditory search task caused very little drop in alpha density.

It is apparent that the attempt to see, even in the total absence of visual stimuli, is sufficient to produce alpha blocking. Thus, these findings replicated the visual-attention effects on alpha density reported by Adrian and Matthews (1934), supported by Durup and Fessard (1935), and suggested as part of the definition of alpha by Storm van Leeuwen and committee (1966). However, it would appear that the actual relationship of alpha rhythm to visual activity, brain activity, and subjective state is considerably less clear than one might expect 40 years after those simple and elegant studies that first demonstrated the connection between alpha density and the visuomotor system. Certainly, our work within the feedback setting did confirm and expand upon some of the original observations of the alpha rhythm's basic characteristics.

The primary finding was that the visuomotor system is of overriding importance in the suppression of, and in subsequent learning to

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enhance, alpha production in the typical feedback session. This connection between visual processes and alpha density is particularly direct for parieto-occipital alpha but, although still present to a considerable degree, is less so for temporal, central, and frontal areas of the brain. The importance of these regional differences in alpha density and alpha dynamics for alpha enhancement effects has not been fully clarified. However, early published reports (Brown, 1970; Kamiya, 1969; Nowlis and Kamiya, 1970) of the subjective effects of alpha increases did not direct attention to lateralized or regional differences in brain function. The enhancement of alpha and the subjective effects were demonstrated with occipital alpha recording but were assumed, or implied, to be whole-brain phenomena based on a change in overall psychophysiological state.

With the above data available, it seemed apparent that the effects of alpha feedback training should be reconceptualized as an experience that teaches the subject to augment alpha under circumstances that ordinarily reduce the amount of alpha in the EEG (Paskewitz et al., 1970). The visuomotor system seems to be the overriding factor determining alpha levels in those circumstances in which the person can see visual patterns or, in a totally dark room, attempt to see them. Further, alpha enhancement under conditions that include the subject's eyes being open in a dimly lighted room seems to require different learning strategies, such as avoiding looking at anything directly. In addition, it may have different subjective effects when compared with alpha increases that might occur in a subject sitting with closed eyes in a totally dark room (Plotkin, 1976b; Travis, Kondo, and Knott, 1975).

Of considerable importance to the utilization of alpha feedback in a totally dark room is whether, under such conditions, a subject can increase his alpha density over an optimum eyes-closed resting baseline level. This question remains the center of current controversy. The recent papers by Hardt and Kamiya (1976) on the affirmative side and Plotkin (1976a) on the negative side adequately review the conflicting evidence. It would seem that it may be possible, as Hardt and Kamiya have pointed out, that different kinds of alpha recording and different feedback techniques, as well as longer periods of training than those described here, would allow subjects to demonstrate significant increases in alpha. However, we would agree with Plotkin that the burden of proof remains with those who make the claim. A convincing demonstration of such alpha changes has not yet been forthcoming.

Given that previous feedback enhancement of alpha wave density appeared to result from the lifting of alpha suppression mechanisms,

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such as those connected with light, the exploration of other potential sources of alpha inhibition seemed the most important area for further research. As we noted above, in the absence of light the suppression of alpha density that seemed to occur in the routine feedback setting could be seen only during the first session, when the subject opened his eyes in the total darkness. Once this relatively brief blocking effect is overcome -- a process that occurs spontaneously during the first 2 - 3 min of the free-play period -- the subject's alpha level again approximates that of the initial baseline, and no further augmentation can be seen during training. It seemed appropriate, therefore, to recognize that it might be necessary to reconceptualize the nature of the mechanisms underlying alpha density changes in the alert subject.

VI. ALPHA AND AROUSAL/ACTIVATION

The findings on levels of alpha density during visuomotor activity had begun to clarify some of the issues surrounding alpha blocking in the feedback context. At the same time, the basic link between alpha density and arousal began to appear to be much more complex than earlier workers had assumed. The initial experimentation, as reported above, had implicated the visuomotor system much more than arousal in alpha density changes, but no controlled manipulation of activation/ arousal had been carried out. Therefore, the most appropriate next step seemed to be to explore directly the key hypothesis justifying the use of alpha feedback in the clinical setting: that alpha density is linked to subjective and physiological arousal by an inverted Ushaped function.

In brief, both Lindsley (1952) and Stennett (1957) hypothesized that alpha density is related to activation or arousal by an inverted Ushaped function. That is, alpha density was felt to be at a maximum during alert, but relaxed, nonfocused mind-wandering, while dropping to zero with the onset of sleep. During physiological and subjective arousal, as in anxiety-tension, alpha density seemed reduced and approached minimal levels during periods of extreme excitement or panic. These assertions, based on laboratory-manipulated changes in arousal, appeared to receive further support from clinical research (Cohn, 1946; Costa, Cox, and Katzman, 1965; Jasper, 1936; Lemere, 1936; Ulett and Gleser, 1952; Ulett, Gleser, Winokur, and Lawler, 1953) on neurotic and schizophrenic patients with constant high arousal. Therefore, we began our exploration of the relationship of alpha density to levels of arousal with the assumption that the hypothesized relationships were essentially confirmed. However,

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it was apparent that visuomotor activity had to be controlled if we were to obtain uncontaminated observations on alpha-arousal interactions.

Since the previous data suggested that visuomotor activity in an alert subject under lighted conditions overwhelmed the effects on alpha density of any other behavior, the additional alpha blocking from activation/arousal might be difficult to discern under those circumstances. It was expected that a highly anxious person in a lighted room would block alpha more from his visuomotor activity than from the effects of fear itself. However, it was assumed that only learning to inhibit the fear effect would produce the dramatic subjective change relevant to controlling emotional turmoil in response to stress. For this reason, the presence of ambient light was eliminated from further experiments, and the hypothesized arousal mechanisms that might be responsible for reducing alpha density below optimal levels became the focus of attention.

A. High Levels o f Arousal -- Fear

We were left to confirm the assumption that since activation/arousal leads to decrements in alpha density, as did visuomotor activity, feedback training might permit the subject to disregard the alpha blocking effects of anxiety, just as it did those of light. It seemed entirely plausible that an anxious or aroused individual with reduced alpha in a totally dark room might learn to increase alpha density with feedback training and thereby learn to inhibit the mechanisms responsible for the physiological and psychological concomitants of anxiety.

Therefore, a study was specifically designed to: (1) establish during Day 1 the relaxed individual's optimal initial baseline; (2) create anxiety or fear in the subject over returning to the laboratory for a second session so that baseline alpha density for his second session presumably would be depressed; (3) show, then, how alpha feedback training can serve to increase alpha density even in total darkness, if it had initially been depressed by this situational anxiety; and (4) create a situation in which the subject would periodically be placed in jeopardy of being shocked (which would, presumably, again depress the level of alpha density) and in which an increase in alpha density would reduce or eliminate the likelihood of being shocked. In other words, the paradigm would approximate the all-too-common life situation in which the anxiety response is counterproductive and must somehow be controlled.

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In an experiment by Orne and Paskewitz (1974), subjects first came to the laboratory to participate in a simple alpha feedback training experience. Every effort was exerted to make the subject comfortable and relaxed. A number of baselines were obtained, and feedback was given in the presence and the absence of ambient light. At the conclusion of this initial session, those subjects who had greater than 25% alpha were given the option of returning for a second session. It was explained that although it was very important for them to return, they were under no pressure to do so since the subsequent sessions involved receiving mildly uncomfortable to quite painful electric shocks to the calf of the leg. Thus, the experimenter refrained from actually reassuring the potential volunteers, although he made it clear that no injury would result. Of the 22 eligible subjects, 10 agreed to continue.

During the second session, two large silver electrodes and a ground were attached over the right gastrocnemius muscle, after the routine sensory electrodes had been positioned for recording EEG, EOG, GSR, and heart rate. The subject was informed about the nature of the silver shock electrodes but was given no instructions regarding when shocks might occur, since it was felt that any ambiguity about the shock would maximize anxiety. The experimenter left the room, the lights were turned out, and the entire session was conducted in total darkness.

Eyes-closed and eyes-open baselines as well as four routine 5-min feedback trials were given to the subject before shock instructions occurred. It was then explained that during the next part of the experiment he would, from time to time, receive electric shocks. "Jeopardy" periods (those times when he was in danger of being shocked) would be signaled by a third tone, clearly distinct from the alpha and no-alpha tones. This third tone would be on only when he was not producing alpha. Simply by turning on alpha, he could turn off the jeopardy tone and prevent his being shocked. It was emphasized that the only time he could be shocked would be while the jeopardy tone was on. Therefore, the more alpha he could produce, the less the likelihood of his being shocked.

Following these shock instructions, the subjects were given five 5-min feedback trials. Each of these trials was divided into 10 contiguous half-minute segments, 5 of which were jeopardy segments during which the third (or shock warning) tone was always present simultaneously with the no-alpha tone. During the other 5 segments, only the usual alpha or no-alpha tones were presented.

The shock contingencies were, in fact, arranged so that subjects received one to two shocks during each 5-min feedback segment.

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Shock intensity was varied during the experiment, with only one or two being sufficiently intense to feel painful (since the purpose of the shock was to create apprehension rather than to inflict discomfort). These same procedures were repeated during a third visit to the laboratory.

The findings did not confirm the predictions of the theory. The initial alpha baselines during the second session were just as high as those in the first session, when no shock threat was present. During the first four feedback trials, alpha density was sustained at baseline levels (see Figure 8). The lack of alpha blocking following the shock instructions was most striking, in view of previous reports that fear causes drops in alpha density (Stennett, 1957). Alpha density did drop slightly, but transiently, during the first two jeopardy periods themselves. However, by the third jeopardy feedback period, alpha density levels were no different than those during nonshock feedback trials. The data from the third session showed alpha density differences between jeopardy and nonjeopardy periods only during the first jeopardy feedback trial. The group mean alpha density was equivalent to baseline levels during the rest of the trials. Thus, neither the anticipation of receiving electric shock nor the signal of the imminent

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onset of shock served to reduce the subjects' production of alpha density levels comparable to those found during resting baselines in the dark.

In an interpretation of these data, the first possibility to be considered was that the shock manipulation was not successful in making the subjects anxious. However, postexperimental inquiries clearly substantiated predictions that subjects would be anxious. Furthermore, during the experiment itself, visual observation (an infrared video system, included as a safety precaution, had permitted unobtrusive observation in the total darkness) revealed that the facial expression and demeanor of the subjects clearly suggested that they were anxious. Finally, other physiological data, notably heart rate and electrodermal responses, substantiated the subjects' reports and our behavioral observations. For example, as can be seen in Figure 8, when shock instructions were given, an instantaneous and dramatic increase in heart rate of well over 10 beats per minute took place (t = 2.98, p < 0.01). Pertinently, heart rate was significantly higher during jeopardy periods than during nonjeopardy periods (t = 2.05, p < 0.05), and when shock trials were over, heart rate returned to baseline levels. A second measure of activation, the number of spontaneous skin conductance responses (SSCRs), showed a closely analogous sequence of arousal. Data from the third session showed alpha, heart rate, and SSCR patterns very similar to those of the second and, therefore, replicated the findings.

Thus, neither the apprehension about the shock session in general, which might have been reflected in a drop in the second session's initial baseline densities, nor even the acute fear of being shocked resulted in the anticipated sharp drop in alpha density. The expected relationship between high levels of activation and reduced alpha density did not materialize. The data clearly indicated the lack of a necessary relationship between alpha density and the apprehension, anxiety, fear, or arousal levels of the subjects in this experiment. The discrepancy between these observations and previous reports (Lindsley, 1952; Stennett, 1957) of a link between alpha density, on the one hand, and subjective state and physiological arousal, on the other, clearly suggested that the old hypothesis required further exploration.

Insofar as the above results might reflect on the possible effects of alpha feedback training, they must be considered tentative because of the lack of yoked noncontingent feedback controls and the use of selected volunteer subjects. However, these findings call into question the assumed relationship between subjective anxiety-tension and alpha density, the basic notion upon which the rationale for the use of alpha biofeedback to reduce the effects of stress was founded. The

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study suggests that the simplistic assumption that alpha density always reflects a specific level of physiological activation/arousal does not hold, at least following and/or during alpha feedback training. Although these data, since they were collected during alpha enhancement feedback, cannot directly demonstrate the inadequacy of the inverted U-shape hypothesis describing the relationship between alpha density and arousal, they call into question the continued, unconsidered use of this conceptualization of the relationship of subjective and objective arousal with EEG alpha wave generation.

It is possible that the older literature (Lindsley, 1952; Stennett, 1957) suggesting a connection between high levels of arousal and decreased alpha density reflects a fortuitous combination of situation-specific factors and mediating influences that are not yet understood. Several phenomena were not adequately considered or controlled in previous studies. For example, the effects of novelty on the interaction between alpha density and arousal appear to be of considerable importance, particularly during the first visit to the laboratory. Johnson and Ulett (1959) found an inverse relationship between alpha density and Taylor Manifest Anxiety in 44 males during the first baseline recording session. However, they noted that this relationship was not present during the second and third visits to the laboratory. Johnson and Ulett recognized that they were not dealing with a simple relationship between optimal tonic level of alpha activity and anxiety but, rather, with a correlation that followed from differential response to a new and subjectively important experimental context. This point has been independently documented by Evans (1972) with regard to attempts to relate hypnotic responsivity to a subject's baseline alpha density. Most previous EEG studies of patients or of laboratory manipulation of fear have been carried out with subjects during their first experience with EEG recording. Thus, the interactions among the effects of novelty and fear with cortical activation cannot be separated without further controlled experimentation that takes these underlying factors into account.

The failure in earlier work to distinguish between studies performed with subjects having their eyes open in the presence of some ambient light versus those with subjects with their eyes closed or in the total absence of light produced even more confusion. The presence or absence of light not only interacts with habituation to the environmental situation but also plays a major role itself, with or without alpha feedback. Thus, attempts to relate current data to previous studies are frequently frustrated by the absence of standardized recording conditions in work performed before the effects of these phenomena were clearly recognized.

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Early studies (Adrian and Matthews, 1934; Berger, 1929; Thiesen, 1943), which reported the alpha blocking effects of anxiety and arousal, typically used stimuli that were both novel and anxiety arousing. Further, little concern was given to concurrent visual activity. However, it now seems plausible to consider that any drop in alpha density that previous studies ascribed to arousal might actually have been the result of orienting to novelty or the visual activity provoked by the same stimulus responsible for emotional arousal.

Finally, Surwillo (1965) criticized Stennett's (1957) frequently cited study of the inverted U-shaped function as the result of an erroneous analysis of the data. Surwillo used the relationship between alpha amplitude and heart rate in his subjects to show that a single individual rarely demonstrates the inverted-U function. He found that his data, as well as Stennett's, produced such a curve only if subjects who increased alpha with increasing arousal were juxtaposed with those who decreased alpha with increasing arousal. The combination of the two limbs thus formed then created the inverted-U shape. However, this juxtaposition was possible only if the relative level of activation among the subjects was ignored. Thus, some of the key data ostensibly supporting the hypothesis have themselves been questioned.

It appeared possible, then, that our failure to find significant changes in alpha density with high arousal might be in agreement with Stennett's (1957) data as interpreted by Surwillo (1965), while still serving to discredit the inverted U-shaped function hypothesis. It was clear that it was necessary to reexamine carefully the nature of the high arousal end of the curve. However, the data for the low end seemed much less likely to be confounded by the above problems. For example, subjects falling asleep would have their eyes closed and would thus be exposed to the same low visual stimulation rates. Indeed, as will be demonstrated, our data seemed to confirm the older literature (Lindsley, 1960; Stennett, 1957) on the relationship between drowsiness and low alpha density.

B. Low Levels of Arousal-Drowsiness

Initially, practical concerns over obtaining valid baseline alpha densities against which to compare feedback results led us to examine some of the circumstances under which measures of alpha density were or were not characteristic of the individual. The initial 3-min eyes-closed and final 2-min eyes-closed baselines of subjects coming to the laboratory for a variety of feedback sessions were evaluated

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(Paskewitz and Orne, 1972). The 24 subjects were primarily males who had participated in at least three laboratory feedback sessions.

The average intercorrelation (Pearson) between the mean alpha density for the six periods (two baselines during each of three visits) was 0.76, with individual coefficients ranging from 0.67 to 0.95. In spite of the generally high correlations, some baselines were highly atypical and failed to reflect the subject's usual alpha density. Baselines with reductions in alpha density of greater than 50% during 30-sec intervals were examined more closely in a subset of 9 subjects for whom eye movement data were available. Of 22 atypical baselines, 15 were accompanied by slow eye movements, a characteristic precursor of the onset of sleep (see Table 1).

Thus, a study of the reliability of baseline EEG alpha measures also clearly documented the now well-established relationship between the onset of drowsiness, which merges into Stage 1 sleep, and a corresponding decrease in alpha density. It is tempting to accept these data as documenting the relationship between low arousal and the absence of alpha. Here too, however, caution is needed. The drop in alpha density may not be a function of low arousal at all; rather it may be an incidental manifestation of the active processes associated with sleep onset.

For example, if one examines nighttime sleep records, there are periods when individuals show a great deal of arousal. Notably, REM is associated not only with the rapid eye movements that give the sleep stage its name but also with other manifestations suggesting heightened arousal, such as penile erection and marked variation in heart rate. Nonetheless, during these periods there is a disproportion-

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ately small increase in alpha, especially when one considers the amount of mentation associated with dreaming as well as the autonomic arousal.

A similar paradoxical relationship between alpha density and arousal indices is suggested by the periods of GSR storms during Stage 4 sleep (Burch, 1965). This fascinating phenomenon does not seem to be accompanied by large changes in other physiological parameters, such as heart rate and respiration, but again, we are unaware of any evidence suggesting that alpha density normally increases during such periods.

Thus, activation within sleep appears to demonstrate a major separation of what seems to be a relatively unified physiological arousal in the waking individual. No considerable emergence of increased alpha density during normal sleep has been documented, yet arousal from these EEG sleep stages may be followed by reports of vivid dreaming experiences. We see, then, an apparent clear separation of processes signaling increased subjective and physiological activation from cortical alpha production. The absence of evidence demonstrating a continued link between brain-stem activation, the cortex, and subjective experience strongly suggests that the decrease in alpha density seen as an individual approaches sleep may reflect an active disengagement of alpha-wave-producing mechanisms from the cortex, rather than a low level of general brain arousal. The specific concomitants of the connection between general activation/arousal and cortical arousal indices such as alpha wave production has yet to be determined.

At this juncture, it may be concluded that a number of subjectively and objectively different mechanisms might have one final common effect: a reduction in alpha production. As demonstrated by the preceding experiments, both attempting to see an object and drowsiness have alpha blocking effects. While high arousal appeared, in previous experiments, to result in reduced alpha density, it is not clear at this point whether this was an independent effect, secondary to increased eye movements, or the effect of unspecified mechanisms. However, given the several apparently fundamentally different types of alpha blocking, it would follow that different skills might be necessary to learn to augment alpha density, depending on the nature of the primary stimulus that is depressing alpha activity. With this new perspective, it becomes relatively meaningless to speak of alpha feedback training in a generic sense. We have to understand what influences have served to depress alpha density below the person's optimum levels in each specific feedback circumstance.

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The problem of specificity of response in biofeedback has also been explored by Schwartz (1972, 1974, 1975), particularly with regard to cardiovascular parameters. His group's further work on brain processes has led them to postulate that patterns of brain and peripheral physiological processes, rather than isolated parameters, may be more meaningfully linked to cognitive-affective experiences. Schwartz (1976a,b) suggested that emotions and conscious states must be seen as emergent properties of neural patterning -- perhaps, for example, in interactions between the two hemispheres -- rather than merely as functions of general neurophysiological activation. Although such a perspective adds to our ability to plan meaningful experiments, an understanding of the nature of phenomena such as lateralization of hemispheric activation depends on the central issue of the significance of alpha density for brain arousal or activation, as a whole or in regions. This significance is by no means clear at this point, and therefore, we shall not seek to comment further on this line of inquiry.

VII. IS DIRECT AWARENESS OF ALPHA WAVE PRODUCTION POSSIBLE?

Since a number of underlying relationships between alpha and subjective experience were now at least vaguely apparent, the conceptual importance of Kamiya's (1969) early study -- reported anecdotally, to demonstrate that subjects could rapidly learn to discriminate between alpha and no-alpha periods in their own EEG -- became even greater. The most direct approach to the potential link between subjective experience and alpha production seemed to lie in attempting to replicate, with more rigorous controls, the original Kamiya finding that subjects could learn to identify periods of alpha wave production. Very early in our pilot work, we had run one subject in 2 of his total of over 30 sessions while providing him with a manipulandum so that he could signal the presence or absence of alpha as he thought it occurred. Visual inspection seemed to support Kamiya's observations that a subject could learn to identify alpha periods, but a number of problems made it very difficult to quantify such data. Therefore, we did not at that time pursue the matter further. However, the findings summarized above had convinced us of the need to address systematically the basic question of whether alpha bursts were reliably accompanied by an identifiable alteration in subjective experience.

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An appropriate procedure was devised (Orne, Evans, Wilson, and Paskewitz, 1975) to allow for a more rigorous test of Kamiya's (1969) hypothesis. Subjects were automatically signaled periodically with a tone and required to indicate, by pressing the appropriate one of two buttons, whether they believed that they had or had not just been generating alpha. If the subject answered correctly, the signal tone was replaced by another, somewhat higher tone. If the choice was incorrect, the tone merely terminated. Thus, this situation provided "feedback" regarding only the presence or absence of alpha each time the subject responded to the tone. It is evident that this approach fits the classical signal detection model. Such a paradigm makes it possible to separate the accuracy of correctly identifying the presence of alpha independently from the accuracy of correctly identifying the absence of alpha. Further, it permits the identification of guessing strategies.

Though conceptually the experiment seemed straightforward and potentially elegant in its approach to the problem, the execution proved to present a series of unexpected problems. For example, even though care was taken to choose subjects with moderate amounts of alpha in order that alpha and no-alpha events would be equally frequent, these subjects, although well acclimated to the laboratory, showed a considerable increase in alpha, without feedback, during the second session and an even greater rise in the third session. Because of this dramatic increase in alpha density, finding periods of non-alpha with a duration of even 1-3 sec was very difficult. Thus, inequalities in the time intervals between alpha and no-alpha events developed.

The results were examined from several different perspectives. First, a day-by-day chi-square analysis for each subject suggested that correct discrimination was being acquired over time, but a more careful analysis showed that a significant chi-square reflected, in large part, an increase in correct guesses during alpha events with a corresponding increase in incorrect guesses during no-alpha events. Thus, the results were apparently a function of response bias on the part of the subjects, who seemed to believe that their alpha density gradually increased across days.

Further assessment through a one-sample runs test and a signal detection analysis confirmed that response bias was the central factor in producing the results. Although the relatively small number of trials and the possible violation of some of the underlying assumptions of signal detection make the results of such an analysis less than ideally clear, it did show that there was a very low d' index of discriminability. The response bias criterion showed signs of a strong "alpha" response bias effect that was relatively consistent throughout the

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series, except for the seventh session, when two of the subjects reported feeling extremely drowsy.

Legewie (1975) and Pavloski, Cott, and Black (1975) also used this alpha/no-alpha discrimination procedure in experiments attempting to replicate Kamiya's (1969) original findings. Neither group was able to demonstrate that their subjects could actually discriminate between these two EEG states. When trial probabilities and confounding cues were controlled, the subjects could not determine at any one moment whether alpha or no-alpha was occurring in their EEG recording. In summary, these alpha state discrimination studies suggested that the apparent ability to discriminate between alpha and no-alpha events during the pilot studies was probably an artifact of the individual's strategy within the experiment. For example, our subjects tried to increase their incidence of alpha without instructions to do so and followed this attempt with the strong tendency to choose "alpha" more often than "no-alpha" for their decision.

While it would be all too easy to dismiss Kamiya's (1969) anecdotal findings in light of the above studies, we are not yet prepared to do so. The number of subjects examined for the ability to discriminate alpha and no-alpha conditions is small, and our automated procedures may be obscuring the issue as much as helping to clarify it. Thus, our failure to replicate the earlier Kamiya results may be as much a function of our approach as of the nature of alpha. However, while it is, of course, possible that it is necessary to train individuals with longer windows than those that were used in these studies, it would seem essential that more carefully controlled positive observations be obtained before we are justified in assuming that the simple presence of alpha has cortical representation.

The line of inquiry into alpha and its connections with subjective experience had thus demonstrated that: (1) subjects do not appear to learn to increase their alpha density above their resting baseline through feedback; (2) visuomotor activity is of prime importance in depressing optimal alpha density and in subsequently learning to enhance alpha; (3) high levels of alpha density can be present even during very high arousal and subjective fear during alpha feedback; (4) the absence of alpha during activation/arousal changes during sleep suggests that whatever relationship exists in the waking state between alpha density and arousal levels is not readily seen during sleep itself; and (5) subjects may not be able to discriminate directly between alpha and no-alpha events during waking states. In sum, the view that alpha production is closely related to subjective experiences, has specific cortical representation, and alone reflects level of activation/ arousal cannot be justified with currently available data.

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Given these observations, it seems that the entire basis justifying the potential benefits of alpha feedback training is lacking, and accordingly, one might well choose to dismiss this entire line of inquiry. However, throughout our efforts to understand alpha feedback, we have become increasingly aware of the need to understand the underlying processes, and we have been forced to reevaluate issues that were assumed to be resolved by previous work in order to reconcile the conflicting reports in the literature. Of several issues that arose, the single most important factor, which has been essentially ignored in the reported work to date, related to systematic individual differences in the dynamics of the alpha response. Such differences may provide further clarification of the nature of the conflicting findings reported above.

VIII. THE EFFECTS OF COGNITIVE ACTIVITY ON ALPHA DYNAMICS

The view that alpha blocking is always associated with concentrated mental activity was first hypothesized by Berger (1929) and was supported by Adrian and Matthews (1934). Several subsequent studies seemed to demonstrate a clear relationship between mental tasks themselves and the blocking of alpha activity in the EEG (Chapman, Armington, and Bragdon, 1962; Darrow, Vieth, and Wilson, 1957; Glanzer, Chapman, Clark, and Bragdon, 1964; Glass, 1964, 1967; Lorens and Darrow, 1962). We also found, in early studies, that combining the task of incrementing alpha through feedback with a cognitive task such as subtracting by sevens produced more alpha blocking.

Individual differences in the degree of blocking, depending on the person's proficiency at the task and his self-paced rate of performance, seemed to substantiate such an interpretation. For example, one subject, choosing to do an arithmetic task more quickly than he could readily manage, showed large amounts of blocking, while another, going more slowly than justified by his skill in arithmetic, showed little blocking. It appeared obvious that the task difficulty at any given time was determined not only by the task itself and the individual's proficiency in the task but also by the individual's rate of task performance (Paskewitz and Orne, 1972). However, several other studies (discussed below) also seemed to indicate that there are other individual differences that might mediate the different alpha blocking reactions between persons.

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A. Previously Reported General Effects of Tasks on Alpha Density

Mundy-Castle (1957) found that both mental arithmetic and imagery could be carried on without necessarily leading to alpha blocking. He concluded from his studies that there was no one-to-one relationship between alpha blocking and visual activity or attention. Further, Chapman et al. (1962) noted that mental arithmetic reduced alpha in an eyes-closed but increased it in an eyes-open condition. Kreitman and Shaw (1965) observed, in a study of eight subjects, that alpha density increased in some individuals during most tasks. Legewie, Simonova, and Creutzfeldt (1969) replicated a previous finding (Creutzfeldt, Grunewald, Simonova, and Schmitz, 1969) that a number of experimental tasks performed during an eyes-open condition increased temporo-occipital alpha in seven of eight subjects, while decreasing it when their eyes were closed. Thus, this group of studies tended to concentrate on the interaction between direction of alpha change during a task and visuomotor effects.

In contrast, Pollen and Trachtenberg (1972) focused on the impact of task difficulty. By varying the demand on mental effort, they found that in an eyes-closed condition, no alpha blocking occurred during the easier parts of their progressively more difficult range of tasks. In those sections that demanded greater mental effort, alpha blocking was present and continued until the problem was solved. Their results thus suggested that alpha augmentation might be expected only during lower-level mental effort. Any differences in alpha attenuation between subjects over different tasks could then be attributed to individual differences in task-related skills or effort.

In sum, the literature has concentrated on the effects of light on alpha changes during a task or on experienced task difficulty. However, the effects of the novelty of the experimental setting and the tasks were not well controlled. Further, the meaning of the fact that some individuals, when performing a mental task with their eyes open, augmented alpha was not clarified.

B. Individual Differences in Alpha Response to a Task

In view of the possible individual differences inherent in previous data and their potential practical and theoretical import, the effect of cognitive tasks on alpha density was reexamined (Orne et al., 1975), with particular attention given to the control of novelty effects and to

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the elimination of light from the experimental setting. Subjects were run through the same baseline recordings and essentially similar tasks on three different days, both as a preliminary familiarization with procedures in order to control novelty and to permit selection of those who were to participate in a feedback study to extend over several days.

The three sessions were designed to record alpha density while the subject sat in a totally dark room. Conditions included were eyes-open and eyes-closed resting baselines, as well as carrying out a number of tasks requiring different levels of cognitive effort. Following the initial eyes-closed and eyes-open baselines, a number of 90-sec serial subtraction tasks using several different numbers, as well as descending subtraction, were interspersed with 1- and 2-min baselines. The subtraction tasks varied in difficulty from simply counting backward by ones to the most difficult descending subtraction task. For the latter, the subject began by subtracting 9 from a three-digit number, then 8 from the remainder, then 7 from that remainder, and so on until reaching 2, when he began again with 9, 8, 7, etc., until told to stop.

The tasks were followed by ones designed to elicit left- or right-hemisphere activation specifically, such as verbal and mathematical problems for the left and visualization of scenes and visuospatial problems for the right. Five problems of each of the two types were performed in a counterbalanced order, with intervening 20-sec rests separating them. Essentially similar, although slightly modified, tasks and baselines were carried out during all three sessions. Thus, it was possible to compare alpha changes between tasks after novelty had been eliminated. All EEG data were obtained from bilateral recordings of monopolar occipital EEG, with the right mastoid used as reference, and recorded on paper. Criterion alpha was measured by use of a 15-µV amplitude standard for the presence of alpha.

During the first session, there was a general tendency to block alpha while performing the tasks, although some subjects blocked alpha much more than others. However, when the data from the second session were examined, strikingly specific individual differences in alpha dynamics emerged. Among these subjects, all of whom were used to the experimental procedures and were dark-adapted, seven responded to subtraction by ones by incrementing their alpha density above their own baselines and four responded by blocking alpha. However, given the Pollen and Trachtenberg (1972) findings on task-difficulty effects, one would anticipate that all subjects would block alpha during the difficult descending subtraction.

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Subjects were therefore divided on the basis of whether they increased or decreased alpha density while counting by ones, so that we could see if this dichotomy would differentiate them when they performed descending subtraction. Figure 9 shows the mean percentage of left-hemisphere alpha density of two groups: four alpha blockers (dotted lines) and seven alpha augmenters (solid lines). The individual was assigned to the augmenting or blocking group on the basis of his alpha density change from baseline during subtraction by ones in the second session. Subjects who blocked alpha while counting backward by ones also did so during descending subtraction. However, contrary to expectations, those who increased alpha density while performing the simple task increased it during the difficult one as well!

As Figure 9 demonstrates, the two kinds of alpha response to a task are not related to differences in resting alpha density either during the initial baseline or in the rests preceding the tasks. Since the two groups were defined by the direction of their alpha response during subtraction by ones, it is hardly surprising that their alpha density is significantly different during that task. However, the continued differences (Trial 1, t = 1.82, p = 0.05; Trial 2, t = 3.09, p < 0.01) in their alpha response to the much more demanding descending subtraction task were remarkable, particularly since these differences were not related to the individual's success or speed in counting backward during the descending subtraction task.

The consistency of an individual's alpha response to a task is further demonstrated by the continued significant differences between these two groups, separated by direction of alpha change with subtraction by ones on Day 2, during the descending subtraction task

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on Day 3. Again, the two groups showed their characteristic directions of response during the task, and their alpha densities were significantly different (t = 3.02, Trial 1; and 3.58, Trial 2; p < 0.01 for both). The Pearson correlations between Day 2 and Day 3 alpha density change scores during the descending subtraction tasks were 0.56, Trial 1, and 0.66, Trial 2 (p < 0.05). Pearson correlations of alpha density between tasks on the same day were uniformly above 0.66, regardless of the differences in the difficulty of the task. Thus, the individual differences in alpha dynamics appeared to be more important modifiers of alpha density response than task difficulty on the second and third days of the experiment.

The bimodality of these response characteristics, evident during the second and third days, was not present in the first day. On the contrary, a fairly uniform tendency to block alpha while performing a cognitive task was apparent. So that we could determine whether there were any individual differences reflected in Day 1 data, the number of subtraction tasks (total possible, five) during which an individual showed alpha augmentation was tabulated. Seven subjects identified as augmenters on Day 2 augmented alpha during a mean of 1.86 of the 5 subtraction tasks on Day 1, while six identified as blockers on Day 2 augmented during a mean of 0.33 tasks on Day 1 (t = 2.69, p < 0.25). (Two subjects who did not complete the third day are included in the Day 1 data.) Thus, an individual characteristic that was easily identified in Day 2 data was also present on Day 1 but not readily discernible because of the relatively uniform response to novelty.

These striking, reliable, and significant differences in the direction of alpha density changes during cognitive tasks, although observed by others in the past, have tended to be ignored because they were masked either by the presence of light or by novelty on the first day of testing. Therefore, they have been taken to represent random variation in alpha blocking. However, the persistent direction and amount of alpha change that occurred in our subjects across tasks and across days suggests that what may be manifest in these phenomena is a powerful and pervasive characteristic of the person's neurophysiological dynamics, rather than merely phasic changes whose nature is closely tied to his immediate mental effort or content. Thus, the same subjective experience and objective performance in some subjects may elicit considerable alpha blocking, in others alpha augmentation, and in still others little or no change in alpha density.

Clearly, such individual differences in response to cognitive tasks are not taken into account by current theories regarding alpha,

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activation, behavior, and subjective experience outside of the feedback context. Still, one might consider dismissing them as irrelevant to the general activation/arousal theory justifying the use of alpha feedback in a clinical setting. However, conceptually similar spontaneous changes in alpha density occurred during high activation/ arousal in an alpha feedback experiment (Wilson, Orne, and Paskewitz, 1976). Some individuals blocked alpha during fear of electric shock and some showed no change, while others increased alpha; all these different responses occurred during periods of large increases in autonomic indices, such as heart rate and spontaneous skin conductance activity. Thus, these individual differences may be quite pertinent to an understanding of the conflicting reports in alpha feedback research.

Travis et al. (1975), for example, reported that only about 60% of their subjects felt the attempt to enhance their alpha density as a neutral or pleasant experience. This kind of variability in reports of positive subjective experience has been explained in a number of ways. For example, Walsh (1974) showed that subject expectations and demand characteristics of the experiment have a significant impact on whether the individual reports positive experiences. However, individual differences in alpha dynamics such as those reported here may help explicate the findings in a more basic and ultimately more useful manner. They may also clarify the controversy surrounding the potential of individuals to augent alpha density over baseline levels. Our data demonstrate that such increases are possible, at least in some persons. However, they have occurred in response to difficult cognitive tasks, or high activation/arousal, rather than during relaxation.

In sum, although there is little question that the nature of a cognitive task or an emotional experience has an impact on alpha dynamics, directing data analysis toward individual differences permits the identification of another important dimension in alpha phenomena. This dimension has previously been obscured by the effects of light or by orientation to novelty on the first day of participation in an experiment. Once these effects are controlled by the subject's being adapted both to darkness and to the circumstances of the experiment, individual differences in alpha dynamics become evident. It seems apparent that one cannot expect to apply alpha feedback to obtain predictable results unless these powerful systematic individual differences are better understood and taken into account. Otherwise, the results of alpha feedback can, at best, be no more than confusing and, at worst, detrimental to some of those whom we would hope to aid.

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IX. OVERVIEW AND PROSPECTS

What may we then consider to be established conclusions regarding the relationship between alpha and subjective experience? First, contrary to our initial naive hopes, we cannot assume that high alpha density is uniformly accompanied by a moderate physiological arousal or subjective calm. It is now clear that a number of different mechanisms influence alpha density and interact to determine an individual's tonic levels and phasic changes in alpha. Second, visuomotor activity is of primary importance in determining alpha density and in the subject's learning to augment alpha in the presence of light. It would appear that feedback training carried out in light requires the development of different skills and may have very different subjective and objective results than that carried out in total darkness. Third, the widely accepted inverted U-shaped function hypothesized to relate alpha density to activation needs to be reevaluated. Fourth, while in early work we could not get people to exceed baseline alpha levels, it is now clear that some subjects do -- in response to activation. Fifth, very important systematic individual differences in alpha dynamics must be taken into account in any further studies of the relationship between cortical electrical activity, subjective experience, and behavior, as well as in alpha feedback training research.

The disappointing overall results of alpha biofeedback training, compared with the initial hopes, have forced a reconceptualization of the necessary conditions for the clinical application of alpha feedback. Our results suggest that once novelty and visuomotor effects are eliminated, alpha augmentation may be the product of relaxation in one individual and of hyperarousal in another, while a third may show little relationship between subjective state and alpha density. Thus, regardless of the area of the brain from which recordings are taken, or the pattern of other autonomic parameters, uniform subjective experiences over a population of subjects are unlikely to emerge from a single direction of alpha change. Unless the individual differences are taken into account, it would seem foolhardy to expect that alpha feedback would lead to uniform effects once novelty and visuomotor factors are excluded.

In sum, the research that has followed the original reports of a reliable connection between alpha production and subjective experience has tended to negate and/or qualify the early results. However, three more recently defined areas of inquiry must be understood before the final chapter on the potential subjective effects of alpha enhancement through feedback training can be written. More careful examination of the relationship of specialized areas of the brain to

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behavior, as well as of the specific pattern of physiological reactions associated with particular emotional states, must be carried out. Perhaps most important to any future applications of EEG alpha feedback will be an in-depth exploration of individual differences in alpha dynamics. The potential new integration of basic neurophysiological and neuropsychological perspectives that may follow would then permit a more scientifically mature second approach to the use of this elusive method of interacting with man's neurophysiological self.

ACKNOWLEDGMENTS

The line of research reported here would not have been possible without the close collaboration of David A. Paskewitz, who designed the equipment, ran the subjects, and supervised the analysis of all but the most recent studies. This later work was carried out in collaboration with Frederick J. Evans, Betsy E. Lawrence, Emily Carota Orne, and Anthony L. Van Campen. We would like to express our appreciation to them and also to William M. Waid for helpful comments and suggestions in the preparation of this manuscript and to Mae C. Weglarski and Lani L. Pyles for their technical and editorial assistance.

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