EFFECTS OF FEEDBACK CONTROL ON SLOW CORTICAL POTENTIALS AND RANDOM EVENTS
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Hinterberger, Houtkooper, & Kotchoubey
EFFECTS OF FEEDBACK CONTROL ON SLOW CORTICAL
POTENTIALS AND RANDOM EVENTS
Thilo Hinterberger1, Joop M. Houtkooper2, & Boris Kotchoubey1
1
Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen
2
Center for Psychobiology and Behavioral Medicine, University of Giessen
ABSTRACT
As known for more than two decades, humans can learn to achieve self-control over their brain activity such as
the polarity of slow cortical potential (SCP) shifts referred to as positivity or negativity. This learning process is
supported by the visual feedback of the SCP in a time-locked trial structure. On the other hand, it has been
repeatedly shown that humans are able to regulate the random distribution of events, produced by an electronic
random event generator (REG) as a psychokinetic effect. This procedure also entails feedback of the distribution
of binary random events to the subject; however, contrary to the feedback of SCP, there is no known physical
connection from the subject to REG. In both cases, the to-be-controlled function should be changed in one of
two alternative directions (“bi-directional control”) by use of two different cognitive strategies or states of
consciousness. In the present experiment the effect of a self-chosen strategy was examined for the regulation of a
feedback signal in a pseudorandomized predefined direction both on the SCP and the REG. Therefore, the
system, called “Thought Translation Device” (TTD) provided feedback of the SCP or the REG. This modality
was changed every block of 300-400 trials of 4.5 to 5s duration each. The task requirement was assigned
pseudorandomly. A correctly produced SCP or REG shift was rewarded with a smily face. The simultaneous
recording of the Electroencephalogram (EEG) and the REG signal allowed investigating psychophysiological
correlates of psychokinetic effects. This study focused on the differentiation between the two tasks of the REG or
SCP signal when feeding back one of them. Four subjects performed in total 3500 trials with SCP feedback and
3500 trials with feedback of the REG. The average feedback value of all trials was analyzed and tested for being
different from a baseline value taken before the start of the feedback in each trial using a t-test. The previous
findings that human subjects can self-regulate their SCP within the first sessions were replicated. Highly
significant SCP control was achieved only by the highly motivated subjects (S 2+S 3) who attended in more than
one day. S 2 attained a constant high correct response rate of 70 to 80 % during the second and third training
day. It was also shown that a temporary “false feedback” given by the REG did not necessarily disturb the
acquisition of SCP self-control. Task-specific lateralization of the SCP (which was not fed back) was not
significant. The highly motivated subjects achieved higher t-values in the REG control than S 1 and S 4. When
considering both feedback modes together, a significant correlation between pre-defined task requirement and
the deviation from chance expectancy produced by the REG (p=0.02) was produced. This can be interpreted as a
psychokinetic effect. The correlation between task and REG result produced by the system when running the
same number of trials was far from significance. Feedback of SCP seemed not to disturb the positive correlation
between task and REG. Despite these similarities between the behavior of the REG and the SCPs, the
differentiation of the REG signal did not significantly correlate with SCP amplitudes or SCP lateralization.
INTRODUCTION
Slow cortical potentials and their meaning
Slow cortical potentials (SCPs) are potential shifts of the cerebral cortex, which are settled in the
frequency range below 1-2 Hz and can persist over several seconds. The SCPs can be measured using the
electroencephalography (EEG) or by means of the magnetoencephalography (slow cortical magnetic fields).
The amplitudes of the SCP shifts usually vary within a range of 10 to 100 µV RMS and reach a maximum at
vertex (electrode position Cz of the international 10/20-system). The fact that the SCPs are not very
localized refers to a common activity of expanded neuronal areas. SCPs emerge as synchronous discharge of
afferent excitation of the apical dendrites of cortical neurons. These dendrites are located in the upper
The Parapsychological Association Convention 2004 39Control of slow cortical potentials and random event generator
cortex layer. A negative potential shift (negativity) indicates a lowering of the excitatory threshold and is
related to the mobilization of resources for behavioral and cognitive tasks. Positive potential shifts
(positivity) can be measured during the execution of cognitive tasks (consumption of resources) or in
cognitively inactive states (Birbaumer et al. 1990, Rockstroh et al. 1989). Lutzenberger et al. (1982), for
example, showed that subjects could solve arithmetic problems faster after producing cortical negativity.
Likewise, response times were shortened if the task was presented during cortical negativity (Rockstroh et al.
1982). The positivity can also result from postsynaptic excitation in deeper cortical layers. Thus firing of the
pyramidal cells during cerebral performance can lead to a positivity on the scalp. To sum, negativity
represents the mobilization or readiness, positivity represents ongoing cognitive and neural performance or
inhibition of neuronal activity.
The relationship between cortical negativity and readiness is best seen in an S1/S2 paradigm which
produces the so-called contingent negative variation (CNV): A warning stimulus S1 is presented to a subject
and followed by an important “imperative” stimulus S2. Then a cortical negativity appears 300 to 500 ms
after S1, which prepares the subject to perform a task after S2 (Walter et al., 1964; Rockstroh et al. 1989,
pp. 99). In real life the CNV emerges, for instance,. at a traffic light when expecting the green light and
preparing for driving; a positivity can be recorded, however, while the brain is already busy with processing
of the stimulus. Although humans are usually not aware of these potential shifts, they can learn to change
the amplitudes of the SCP voluntarily into electrically negative or positive direction. This can be achieved by
feedback of SCP amplitude changes and positive reinforcement for changes in the correct direction (operant
conditioning) (Birbaumer et al. 1981; 1984; 1988; 1992). After having learnt to control the SCPs, humans
can also acquire the ability to consciously perceive them (Kotchoubey et al., 2002).
SCP self-control has also been applied to communication by means of a direct interface between brain
and computer in completely paralyzed individuals (Birbaumer et al., 1999). These authors have developed a
“Thought Translation Device” (TTD) in which self-regulation of slow cortical potentials is used to generate a
binary signal. This signal can further be employed to choose letters and words on a computer menu. The
TTD has already enabled several completely paralyzed patients diagnosed with amyotrophic lateral sclerosis
to communicate solely with their brain potentials (Perelmouter et al. 1999; Hinterberger et al., 2001).
Intention and random event generators
In the last 30 years, studies have been carried out, where the correlations between pre-stated intentions
and the output distribution of different kinds of binary random event generators (REGs) have been
investigated. A meta-analysis of these studies yielded a highly significant result (Radin & Nelson, 1989). An
example of a consistent effort are the studies of Jahn et al. (1997), demonstrating comparable deviations of
the mean results from chance expectation in the order of 10-4 bits per bit processed. Although the absolute
effect sizes are quite small, these authors showed that the composite effect of a 12-year study exceeded 7
standard deviations, which suggests a very high significance level. The effect does not depend on the
distance between subject and the REG device. Even when subjects exerted their efforts at different times
from collecting the REG data, the effect sizes were similar. It seems that solely the information about the
coherence between an human intention and a (classical) physically independent process is linking these
together. The effect vanished when fully deterministic random processes were used, such as the random
number generator of a PC, where an algorithm calculates pseudo-randomized numbers. REGs which
showed anomalous features were using the thermal noise or quantum noise of electronic components
(resistors or diodes) or other physical random processes which are determined by micro-states (e.g. the
throwing of dice). This approach led to speculations about the role of consciousness in quantum physics,
specifically about the possible influence of an intent observer of a random physical system (Walker, 1979;
Houtkooper, 1983; Josephson & Pallikari-Viras, 1991). Although progress towards plausibility has been
made (Houtkooper, 2002), a generally accepted explanation for these effects is lacking.
An approach to clarify the interactions between intention and its effect on remote physical processes is to
investigate the correlations between the anomalous effects of the REG and the physiological correlates of
40 Proceedings of Presented PapersHinterberger, Houtkooper, & Kotchoubey
intention. Such a correlate is produced in every physiological variable which can be self controlled, because
self control is an act of intention. Such a variable is the slow cortical potential shifts which can be obtained
during the SCP-self control training. For this reason, the self-control of SCPs has been chosen to be
compared with the intentional control of REG output in this study.
TTD and REG:
The TTD is a neurophysiological feedback system that can feed back not only different kinds of EEG but
any kind of signal such as an REG signal. The TTD program was modified to read in the signals of the REG
and handle it simultaneously with the EEG signal processing. Thus the REG signal could be fed back to the
subject and its self-control could be trained, if possible. The intention was to collect physiological variables
which significantly correlate with REG control, and thereby to clarify the issue of physiological processes
possibly mediating psychokinetic (PK) effects. An advanced application of such physiological correlates
could (reversely) raise the question of whether it is possible to facilitate PK effects by feeding back and
training those variables. This study provides information concerning the following questions:
1. Is there a correlation between the required intention and the result of the REG (the PK effect)?
2. Can this PK-effect be improved by the feedback of the REG result?
3. Is there also a significant PK-effect in case of feeding back the SCP?
4. How does the attempt to control the REG correlate with the EEG (especially the SCP) of the subject?
METHODS
Feedback and SCP self control
The feedback of slow cortical potentials is provided in a setup shown in Figure 1. The EEG-signal was
conducted by means of Ag/AgCl electrodes placed at the vertex of the head and amplified in the EEG
amplifier that was connected to the TTD via an A/D converter. The impedances of the electrodes were
below 5 kOhms. One central electrode (Cz; international 10/20-system) served as the active electrode for the
feedback. The potential at Cz was referred to the mastoids at position A1 and A2. Since it has been shown
that also lateralized SCP self control can be learned (Kotchoubey et al., 1996a) the signals at the positions
C3 and C4, i.e. over the left and right motor cortex were recorded too. The EEG was sampled with 256 S/s
and recorded with a frequency range from 0.01 Hz to 40 Hz. The low cut-off frequency of 0.01 Hz was
important since very slow EEG components were fed back; therefore a time constant of more than 10 s was
required. To control and correct artifacts caused by vertical eye movements and blinks, two additional
electrodes above and below one eye were attached (vertical electro-oculogram, vEOG). The feedback-signal
was calculated on-line using the mean of the channels Cz-A1 and Cz-A2 corrected with the vEOG. The
algorithm for the artifact correction is described in Kotchoubey et al. (1996b; 1997). Artifacts larger than 1
mV and EEG fluctuations larger than 200 µV led to the cancellation of a current trial (invalid data). The
SCP feedback-signal was generated from low-pass filtering of the artifact-corrected EEG using a sliding
averaging window of 500 ms. Thus frequencies above 2 Hz were filtered out, leading to a smooth movement
of the feedback cursor which was updated 16 times per second. This cursor was symbolized by a yellow circle
(ball) whose vertical position reflected the actual SCP value. Cortical positivity moved the cursor downwards
whereas cortical negativity lead to an upward movement. The screen also showed the randomly alternating
task requirements (negativity versus positivity) by two rectangles (“goals”), displayed at the upper or lower
edge of the screen. The illumination of a goal indicated the direction to which the cursor should be moved.
Successes were reinforced with a “smiley face”. The operator was sitting in another room where he could
control the experiment (for details see Hinterberger (1999)).
The Parapsychological Association Convention 2004 41Control of slow cortical potentials and random event generator
Figure 1: Experimental setup: An eight channel EEG-amplifier is connected to a personal computer with the TTD-software. The
random event generator is connected to the serial port. Both data types can be fed back to the subject as the movement of
a yellow cursor on a second monitor. The required intention is either to move the ball upwards or downwards.
Feedback of random event generator signals
The REG produced a sequence of binary numbers. The proportion of ones and zeros was equally
distributed and was supposed to be psychokinetically influenced. The binary-coded data were transmitted
into the PC with a data transmission rate of 9600 Baud. Thus approx. 3850 ones and approx. 3850 zeros
were generated per second and transferred. In the present experiment, the difference between the number
of ones and zeros in a certain time interval served as the REG signal amplitude. Because the TTD was
already successfully used as SCP training and feedback software, only small modifications were necessary to
use it for REG feedback. The REG data were read and handled as a separate EEG channel in the software.
There was no electronic interference between the analogue REG signal and the EEG signal, because the
REG data were read in as an already digitized signal through the serial port whereas the EEG was digitized
by an A/D-board in the computer. This zero correlation between the two signals is of great importance since
previous data (Hinterberger, 1999) indicate that task related differences in SCP may be very large, whereas
task related differences in the REG signal, even if significant, are expected to be very small. Therefore, even
a weak correlation between the two channels might lead to REG signal changes that would be erroneously
interpreted as a PK effect. A digital switching mechanism inside the REG guaranteed that possible
influences of slow waves on the analogue noise of the REG cannot disturb the digital random distribution.
To make the feedback of the REG signal similar to the feedback of SCPs, the same paradigm and the
same calculation method was applied to the difference between ones and zeros as to the EEG. The screen
for the feedback signal also was kept identical. The vertical ball movement reflected the difference between
ones [1] and zeros [0] within the time interval of the last 500 ms. To achieve an upward movement more
ones than zeros had to be produced, and a downward movement required more zeros than ones. Each
feedback value Fi(t), calculated from the last tFB=500 ms consisted of 3850 random bits:
t
(1) Fi (t ) = ∑ ([1] − [0])
tn = t − t FB
tn = Fi
The feedback was also updated each 1/16 s, leading per trial of 4.5 s duration to 72 feedback values.
These are indicated with the time indices i=1..72. Regardless of the signal used for feedback (SCP or REG),
a data file was created containing both signals for off-line analysis. Thus SCP shifts and other EEG
components could be investigated while the subject was trying to control the REG and vice versa.
42 Proceedings of Presented PapersHinterberger, Houtkooper, & Kotchoubey
The feedback paradigm
The feedback training of SCP and REG signals was conducted in a sequence of individual trials with no
intertrial intervals. 100 trials constituted a run after which a short resting period was permitted. A trial
lasted 4.5 to 5 seconds and consisted of two time intervals:
1. a preparatory interval of 2 s duration. The subject received the information about the following task by
illumination of the upper or lower rectangle on the screen. At the end of the preparatory interval, the
current signal level was set as baseline level, which corresponded to the vertical center position of the ball as
starting position for the following feedback. This interval was followed by
2. the feedback interval of a duration between 2.5 to 3 seconds. Here the subject received feedback over
the SCP or the REG and had to move the ball towards the rectangle that was still illuminated during this
interval, too. The movement of the ball was a linear function of the feedback value Fi. E.g., if the upper goal
was lit, the ball should be moved upwards during the 2.5 to 3 s feedback time. This was achieved by
producing cortical negativity in the case of SCP feedback or by producing more ones than zeros in the case
of REG feedback. The reverse was true for the lower goal. If the average of all ball positions was in the
correct half of the screen, the subject received a positive reinforcement by a smiling face ('smiley '), which
was presented during the final 500 ms of the trial after the feedback.
Experimental design
The two criteria for selection of subjects were the ability to concentrate during the experiment and the
belief in parapsychological phenomena. Therefore, subjects were selected who had experience in
transcendental meditation (TM) for many years. Four subjects (two female and two male) ranging in age
from 40 to 60 years took part at the study. The subjects were seated in a comfortable chair in a small
isolated, electromagnetically shielded room. Each subject participated in the experiment on at least one
training day comprising 1000 trials. The subjects were instructed that there were two kinds of feedback
signals (i.e. A or B). They were informed when there was a switch between signals A and B, but they had no
knowledge about the nature of these signals (i.e., that the REG signal served as A and the SCP signal, as B).
Beforehand, they only were informed that this was a parapsychological experiment.
Table 1: Each of the four subjects attended the study in one to three days, depending on his/her own motivation. One training day
comprised about 1000 feedback trials of either the REG or the SCP. The modality was altered twice resulting in three trial
blocks per day.
training day S 1 (m) S 2 (m) S 3 (f) S 4 (f)
feedback signal, trials feedback signal, trials feedback signal, trials feedback signal, trials
REG, 300 trials REG, 300 trials SCP, 300 trials SCP, 300 trials
1st day SCP, 400 trials SCP, 400 trials REG, 400 trials REG, 300 trials
REG, 300 trials REG, 300 trials SCP, 300 trials SCP, 200 trials
- SCP, 300 trials REG, 300 trials -
2nd day - REG, 400 trials SCP, 500 trials -
- SCP, 300 trials REG, 300 trials -
- REG, 300 trials - -
3rd day - SCP, 400 trials - -
- REG, 300 trials - -
Table 1 illustrates the experimental schedule leading to almost 7000 trials over all. With this setup the
following questions and interactions can be explored:
1. Analysis of the task specific SCP-shifts:
a) Can subjects learn to self-control their SCP?
b) Is this learning process critically dependent on the SCP feedback?
The Parapsychological Association Convention 2004 43Control of slow cortical potentials and random event generator
2. Analysis of the task specific REG results:
a) Can subjects significantly influence the REG result in the desired direction?
b) If yes, does this effect depend on REG feedback?
Analysis of task specific SCP shifts:
To analyze task specific SCP-shifts, all trials were averaged in the time domain, separately for the
positivity task and the negativity task, leading to two average EEG waveforms for a trial. The ability to self-
control the SCP can be seen in the amplitude difference between the two tasks during the feedback interval.
This difference, called SCP differentiation (see figure 3), was calculated as difference between the mean
amplitude during the second half of the feedback interval. A t-test was applied to calculate the significance
of this differentiation (see below, Eq. 5).
Another measure for the ability of SCP self-control is the correct response rate. It is the percentage of
correctly classified cursor movement responses. During on-line training the classification algorithm
calculated a response for each trial as the integral of all cursor positions during the feedback. A correct
response was counted when the sign of this integral matched with the task requirement (positivity or
negativity). An off-line classification using a discriminant analysis (Hinterberger, 1999) instead of a simple
integral can lead to higher correct response rates but needs information of previous runs. However, this
method supplies more precise information about the ability to produce two different signals and thus was
used off-line. As there was a strong correlation between off-line correct response rate and SCP
differentiation (r=0.92), the SCP-differentiation can be regarded as a satisfying measure for performance.
Analysis of task specific REG results:
As already mentioned, each feedback value Fi was the difference between approx. 1925 ones and 1925
zeros. The standard deviation σi for Fi can then be estimated for equally distributed values as
[1]i + [0]i
(2) σi = 2* 2 ≈ 62 .
2
The assumption with these formulas is that the number of ones is binomially distributed with p=1/2. For
our analysis the standard deviation was calculated using the actual REG numbers. The uncertainty σg,i for
the mean Gi over Ng trials with Ng=N(1)+N(0) is
(3) σ g ,i = σ i 2 N g for Gi = ∑ Fi .
Ng
can be estimated by
∑ (F i
(1)
− Gi(1) ) 2 + ∑ ( Fi ( 0) − Gi( 0 ) ) 2
(4) σˆ i = N (1) N (0)
(N (1)
− 1) + ( N ( 0 ) − 1)
The means Gi(1) resp. Gi(0) of the Fi(1) resp. Fi(1) over N(1) resp. N(0) trials were calculated separately for each
task. The significance of REG control was assessed by means of a t-test (Bortz, 1999).
Gi(1) − Gi( 0 )
(5) ti = ,
1 1
σˆ i ⋅ (1) + ( 0 )
N N
where Gi(1) and Gi(0) - the means for the tasks to produce more ones than zeros or more zeros than ones,
respectively; σˆ i – the corresponding standard deviation; N(1) and N(0) – the number of trials of each task, in
which the corresponding σˆ i and Gi were calculated.
44 Proceedings of Presented PapersHinterberger, Houtkooper, & Kotchoubey
RESULTS
Analysis of task specific SCP shifts:
Subjects S 1 and S 4 were not very motivated and took part in the first training day only. With the SCP
feedback, S 1 could achieve an average SCP differentiation of 2 µV resulting in a maximum correct response
rate of about 60 %, which is significantly better than 50 % expected by chance (t=4.0, N=400, pControl of slow cortical potentials and random event generator
task requ irem ent
up
R EG feedbac k dow n
-20
-10
0
10
A m plitu de [µV]
20
30
0 ,0 0, 5 1,0 1,5 2 ,0 2 ,5 3, 0 3,5 4 ,0 4 ,5
SC P feedba ck
-20
-10
0
10
20
30
0 ,0 0, 5 1,0 1,5 2 ,0 2 ,5 3, 0 3,5 4,0 4 ,5
T im e [s]
Figure 3: Averaged (over all trials) SCP waveforms of subject 2, separately for two task requirements, during REG feedback (top) and
SCP feedback (bottom). The shaded area indicates the baseline period.
Lateralization: Although the feedback of left-right SCP-differences was not presented, in some blocks
subjects showed significant lateralized SCP shifts (see Figure 4). Mostly, when a downward movement of the
cursor (cortical positivity during the SCP feedback) was required, this positivity was larger over the right
hemisphere as compared with the left hemisphere during the feedback interval. In addition, subject S 2
produced a significant right hemispherical negativity during the required upward cursor movement during
the first training day,. This effect vanished in the following training days. The correlation between the
differentiation of the central SCPs and the lateralised SCPs was not significant (r=0.15, p=0.22, N=66).
6
S 1 S 2 S 3 S 4
4
Sig nifica nce [t]
2
0
-2 fe e db a ck s ig n al
RE G
-4 SC P a t C z
-6
1 6-1 9
2 0-2 2
1 1-1 3
9 -11
9- 12
13 -15
23-2 5
26- 29
30- 32
8 -10
14- 18
19- 22
1 -3
5 -8
1- 4
5- 8
1- 3
4- 7
1- 3
4- 6
8- 9
R un N o.
Figure 4: SCP lateralization measured at electrode positions C4-C3 during feedback of SCP and the REG. Positive values indicate
that the left hemisphere is more positive while the cursor should be moved upwards, whereas negative values indicate a left
positivity while the cursor should be moved downwards.
Task specific REG results:
Figure 5 shows the t-values of the deviation of the achieved REG results from chance, which would be an
equal number of ones and zeros. The REG changes were analyzed like the SCP changes reported above and
were taken as the difference between the currently measured REG signal and the baseline level (i.e. the
mean of the 500 ms before the FB-interval starts).
46 Proceedings of Presented PapersHinterberger, Houtkooper, & Kotchoubey
Subject S 1 started with REG feedback and did not attain a significant influence on the REG (t=0.62,
p=0.27, Ng=1007; one tailed t-test). Also S 4 showed no significant REG results (t=-0.66, p=0.75, Ng=507).
In contrast, S 2 achieved a high correlation between task requirement and REG result in the first block
with REG feedback (t=2.4, pControl of slow cortical potentials and random event generator
DISCUSSION
The ability of humans to learn to self-control their SCPs is already well known (Birbaumer, 1984;
Rockstroh et al., 1989). Surprisingly, however, three of four subjects participating in the present experiment
achieved this self-control already in the first runs. Moreover, the data of S 2 show that this acquired ability is
not necessarily disturbed or impaired when a random signal (such as the REG) is presented as the feedback.
This stability indicates that the strategy may be more important than the feedback signal. Such an
interpretation is in line with the self-control theory of Lacroix (1981) who suggested that during operant
conditioning of bodily functions, subjects frequently (at least on the first stages of training) select a strategy
from their already existent cognitive-behavioral repertoire and keep this strategy as long as it does not result
in a clear failure. In the present data, such strategy (particularly employed by S 2) was the development of a
negative SCP shift during the baseline interval to support subsequent positivity. During the baseline, waiting
for the stimulus indicating the onset of the feedback interval served as a condition in which a negativity (i.e.,
the contingent negative variation (CNV), see Walter et al., 1964) could easily be produced (see also Brunia,
1993).
This stability of self-regulating strategy can also be a particular trait of S 2, because in S 3, in contrast, the
presentation of the REG signal as feedback did deteriorate the already acquired SCP control. The present
data do not allow to specify factors which might determine the outcome of this conflict.
Again in line with the data of the literature (Radin & Nelson, 1989), a very small but significant (pHinterberger, Houtkooper, & Kotchoubey
An alternative to this motivational explanation may be, of course, some specific effect of SCP changes,
based on the fact that these changes at the central electrode are related to regulation of excitability of large
cortical regions as mentioned in the introduction.
From the point of view of SCP training, REG feedback can be referred to as 'false feedback'. Particularly,
the small size of the PK effect makes the task very frustrating, thus the subjects can resignate and their
resignation can generalize to the easier SCP regulation task. A better result might be obtained with mixed
feedback, which would contain partly SCP and partly REG trials to support some level of success and to
avoid frustration. Alternating pure SCP with mixed feedback (announcing it as a more difficult task) or
mixed feedback alone might therefore be explored.
In further studies, the presently used TTD can be extended to a generalized program to feed back various
physiological parameters correlated to PK-effects. Thereby self-regulation of all these parameters can be
trained to check their influence on the PK-effect. Such a training program might then enable people to
develop their PK abilities.
ACKNOWLEDGEMENTS
We thank our assistant Slavica von Hartlieb for help in the measurements. We also thank the Institut für
Grenzgebiete der Psychologie und Psychohygiene, Freiburg i.Br., Germany for the financial support.
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Address for correspondence: Thilo Hinterberger,
Institute of Medical Psychology and Behavioral
Neurobiology, Eberhard-Karls-University Tübingen,
Gartenstr. 29, D-72074 Tübingen.
E-mail: thilo.hinterberger@uni-tuebingen.de
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