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will use
in the course of the experiment and this combination
is
adjusted under program control. Daily calibration is completed by
running a program which measures
all channels
simultaneously,
producing
statistical averages for each channel’s offset and gain.
The product of this calibration process is an updated version of a
special disk file containing calibration data which are then read and
displayed by whatever
real-time experimental program
is
being
executed. Offsets are invariably close to zero, and gains to unity.
These values are used to correct received physiological signals for
the measured deviations from ideal calibration in the channels in
which they appear.
2. System measurement
routine.
Ideally,
all
channels
of
the
measurement system should respond identically to identical input
signals (assuming
identical arrangement of the channel bandpass
controls); that is, the frequency and phase response characteristics
of
all channels should be as nearly identical as possible. To the
degree that this condition is not met, physiological effects may be
obscured or confused with measurement system artifacts.
Although
the
daily
calibration
procedure
described
above
is
greatly superior to simple visual methods, and effectively equalizes
system response at the frequency of the calibration signal,
it is far
from guaranteeing homogeneity of response
at other frequencies
within the EEG band. To cite an unfortunate example, Clusin et al.
(1970) reported discovering massive and previously unsuspected
interchannel differences when spectral analysis was performed on a
single pre-recorded EEG signal passed simultaneously through
all
channels of their 16-channel electroencephalograph. Estimates of
corresponding
spectral magnitudes
differed by
as much
as 44%
across channels, and there were phase differences on the order of
45 degrees.
Intending
to avoid
this kind
of problem, we have
set out
to
measure carefully our system response. Our technique, detailed in
Lenz and Kelly (1980), uses trains of specially designed test signals
consisting
of computer-generated
impulses
of
modified
sinx/x
form, with known spectra. These test signals are sent from com-
puter to lab, passed through the relevant polygraph channels, and
sent back up to the computer for recovery, averaging, and spectral
analysis
of the
average
recovered
impulse
responses. The
fre-
quency and phase response functions of all channels are thus pre-
cisely measured, and can be compared with each other, with poly-
graph technical specifications, and with theoretical expectation.
Applications of this procedure to our six AC-coupled EEG chan-
nels at several bandpass and sensitivity configurations have yielded
excellent results showing that the system functions of these chan-
nels are highly homogeneous. Consequently, equation of system
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response at a single frequency, as effected by our daily calibration
procedure, does
in fact approximately equate system response at
all other frequencies
in the relevant bandpass.
IV. Prospects
This completes our outline of the research resources we have
developed to date. The system is also open-ended in the sense that
it can readily absorb additional hardware and software components
as these become available, with minimal modification of the exist-
ing software.
Certainly
we
can
imagine
numerous
extensions
and
im-
provements of our current system.
Nevertheless,
the
facility as
already described comes gratifyingly close to meeting the design
criteria we established when we first began working on this project
five years ago. These resources are sufficiently powerful to support
a serious and systematic research effort on the psychophysiology
of psi.
Many
readers may have wondered why
so much computing
power is required for this research. It will help in closing to provide
more concrete quantitative feeling for the sheer numerical scale of
the domain in which we are operating. Consider as a typical exam-
ple our remote photic
stimulation experiment
(Kelly and Lenz,
1976). In
its current form a single session of that experiment can
generate (100
trials) x
(8 seconds per
trial) x
(128 samples per
second per channel) X
(8 channels) or over 800,000 words of raw
EEG data, more than two-thirds of the usable space on a disk.
If
we now compute an intermediate
file of complex Fourier coeffi-
cients, even preserving only frequency components up to 32 Hz,
that file will consume another 800,000 words of storage. From it we
may compute autospectral and cross-spectral parameters at varying
frequency resolution. Looking at cross-spectra, for example, there
are N(N-l)/2 possible pairings of N channels, or 28 pairs for the
case we are considering. For each specified pair of physiological
channels we may
store, for
all specified frequency bands and for
every
trial, the transfer function, coherence, phase, and complex
cross-spectrum information
that collectively characterizes the
re-
lationship between the activities
in those leads during the experi-
mental
session.
Finally,
multivariate
statistical
analysis
of large
multichannel files of extracted EEG features is itself a heavy com-
putational task involving a matrix inversion and the solution of an
eigenvalue problem for each hypothesis tested, with total running
time roughly proportional to the square of the number of variables
used
in the analysis.
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This computational load can be managed on our computer, par-
ticularly since the arrival of the digital tape drive and floating-point
processor. However,
it should be entirely clear that we are working
in a world that
is quantitatively utterly remote from that of tradi-
tional parapsychological experiments.
At the same time,
it must be acknowledged that this
is in part an
expression of our essentially complete ignorance of the physiolog-
ical basis of psi processes. We do not know what we are looking
for,
and
so we
must
be
prepared
to
look
as
widely
and
as
searchingly as possible. It is conceivable, though we think unlikely,
that with inspired guesswork one might arrive at similar research
outcomes
using much
simpler procedures
and approaches
than
ours. And certainly one of our main hopes
is that we
will learn
enough through research to determine what simplifications may be
feasible and appropriate for later investigations.
Meanwhile, however, our
single
strongest intuition
is
that the
key to psychophysiological understanding, not only of psi functions
but of all human mental functions,
lies in the analysis of momen-
tary relationships between brain areas (see also Luria,
1973). The
system we have described constitutes the most elaborate resource
parapsychologists have yet had at their disposal for
this kind of
research. If physiological signals derived from the cortex do indeed
harbor
traces
of psi
processes,
then we
believe we now have
research tools powerful enough to detect and study them.
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Department of Electrical Engineering
Duke University
Durham, North Carolina 27706
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