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B. Polygraph
The core of the physiological measurement system
is a Grass
(Model 7B) solid-state polygraph.
It has eight channels of amplifi-
cation: two DC preamplifiers (7P1B), four wide-band AC-coupled
preamplifiers (7P5B), and two wide-band AC-coupled preamplifiers
with
integrators
(7P3B).
All
channels
use Model 7DAE
driver
amplifiers.
Auxiliary equipment includes
the Grass (EB24)
elec-
trode plugboard and (7ESP24) electrode selector panel. s
C. Analog Tape Recorders and Telemetry Units
Many
kinds
of physiological
experiments
generate enormous
volumes of data. Analog recorders are widely used for bulk storage
of raw physiological data, and we
initially planned to follow this
practice,
taking advantage of the 4-channel Hewlett-Packard
in-
strumentation recorder, which was already on hand. Although this
approach proved fairly satisfactory,
it became evident that a com-
pletely digital system would be greatly superior. By recording data
directly in digital (sampled) form, one eliminates a variety of small
but not
negligible
sources of experimental
error. These
include
such things as irregularities of tape transport speed and tape orien-
tation,
additive environmental
noise, and other imperfections of
analog environments related to problems such as providing accu-
rate timing signals and reliable mechanisms for encoding and de-
coding responses (Bendat and
Piersol,
1971, Chapter
7;
Walter,
1972; see also Vos,
1977).
However, analog recording methods
still have occasional uses
in our work. The main use is to provide access to data collected in
other laboratories, or under field conditions, using radio telemetry
methods
developed
in
our
laboratory
by
Fritz
Klein.
These
methods encode
physiological
signals
as modulations of an FM
carrier,
using
pocket-sized
amplifier/transmitter
units and
audio
tape
recording.
The
basic
techniques
are
described
in
detail
elsewhere (Klein,
1976b) and some preliminary examples of their
many possible applications in parapsychological research are con-
tained in Palmer (1979) and Solfvin,
Roll, and Kelly (1977). 6
5 We wish to express our gratitude to W. G.
Roll and the Psychical Research
Foundation for making this essential equipment available to us. It replaces the Grass
Model 79B which we used
initially.
6 Our current
prototype
telemetry
units, which were
constructed
using funds
supplied by the John E. Fetzer Foundation, allow us to collect either two channels
of EEG,
or EKG
and GSR. We
are
presently
seeking funds
to
construct
an
expanded and improved system,
particularly for use
in poltergeist investigations.
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A Computer-Based Laboratory
155
D. Microprocessor and Data-Conversion System
A critical feature of any computer-based physiology lab
is the
analog-to-digital
conversion (ADC)
process,
which
supplies
the
interface between continuously varying physiological
signals and
their discrete numerical representation inside the computer. For
example, in order to maintain adequate fidelity in the digital repre-
sentation of EEG
signals, they must be measured accurately
at
typical rates of from 128 to 512 equally-spaced samples per second
on each EEG channel (see Vos,
1977).
ADC systems can be implemented in a large variety of ways.
One
basic
decision concerns
the physical
location
. of the ADC
process
with respect
to
the
signal
source.
Ideally ADC
should
occur close to the source to minimize possibilities of noise corrup-
tion in the analog data. One way of achieving this
is to have the
main computer itself located right in the laboratory. This of course
was
not
feasible
for us economically,
nor could we purchase
a
smaller computer of the PDP-11 family to serve the same purpose.
Instead, since the already available central computer was equipped
with an LPS-11
that included ADC
capability
(see
above), we
began by developing a low-cost system for transferring physiolog-
ical data from
the
lab
to
the PDP-11
via analog channels. 7
Al-
though this system generally worked reliably during the time when
it was in use, we continued to be concerned that the length of the
transmission lines, coupled with the variety and intensity of possi-
ble noise sources in the engineering environment, made the poten-
tial for corruption of the analog data intolerably high. As part of
our general concern for maximizing data
reliability, we therefore
continued to look for cost-effective alternative solutions. This past
year we were
able
to abandon the analog system
in favor of a
microcomputer system which performs ADC in the laboratory and
transmits data to the PDP-1 1 in digital format via the DR1 1-C (see
subsection E). This system has proved highly effective in suppress-
ing contamination from outside sources.
The microcomputer
is based on an
Intel 8085 microprocessor.
Although
it
is
small,
rather slow,
and by no means
a general-
purpose laboratory computer,
it can perform a variety of useful
functions
in addition
to ADC
(for example,
triggering the RNG,
delivering stimulus or feedback information via
its two
digital-to-
analog converters, etc.), and
it can also be used locally, indepen-
7 Wc thank James W. Davis for valuable technical advice, and FRNM for funds
to implement the resulting designs. The actual construction was carried out by Ross
Dunseath and Steven Suddharth.
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dently of the PDP-11, for simple kinds of experimental tasks (see
Appendix
for further details).
The ADC system 8
itself uses a Datel (ADC-HZ12B) converter
with
12-bit
resolution.
That
is,
the
instantaneous
voltage on
a
sampled channel can in principle be characterized by one of 2 12 =
4096
possible
numerical
values.
In
our
system,
the
noise
level
amounts to somewhat less than one bit, so that we have effectively
significant
bits of signal;
in general,
eight bits
is regarded as
minimally adequate, and
bits
is
excellent. One other
special
feature which we designed
in, and which should be mentioned
here,
is
that
each
input
channel
to
the
converter works
in
a
“sample-and-hold”
manner—that
is, when
the ADC
system
is
triggered, the contents of all channels are simultaneously “frozen”
for sequential conversion by the analog-to-digital converter. This
feature eliminates any possibility of interchannel phase distortion
arising
from
sampling
lags
between
successive
channels,
and
strengthens the technical foundation for investigations of relation-
ships between brain areas (Clusin, Giannitrapani, and Roccaforte,
1970; Cooper,
1975).
E.
Digital Multiplexer
Most data from the lab enter the PDP-11 computer through the
DR11-C. Only one digital data source at a time may be connected
directly
to
the computer through
this
device. However,
usually
several digital devices need to be used together in a given experi-
ment (the 8085 data acquisition system plus RNG and/or one or
more respondent devices). To accomplish this, the single DR11-C
input
port may be shared by routing
the data from
the
several
devices through a digital multiplexer. This device determines pre-
cedence and presents the data to the DR1 1-C port from one device
at a time
in sequence. Conflicts between devices are resolved by
assigning a fixed priority order to the sources and sending the bits
from the highest priority device
first. The source of data
is iden-
tified by a 3-bit “address” attached to the data themselves as they
are
fed
into
the DR11-C. Up
to
eight
digital
sources may be
attached to the multiplexer and thus share the one DR 1 1-C input
port.
F. Hardware Random-Number Generator (RNG)
Since
the fundamental work of Schmidt
(1970,
1973;
see
also
Davis and
Akers,
1974),
hardware
randomization
devices
have
s This
part
of the
system was constructed by
Ross
Dunseath, who was
also
responsible for parts of
its design.
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A Computer-Based Laboratory
}57
a standard fixture
in many parapsychology laboratories.
.
We have also built such a device, primarily for use in studies of the
physiological correlates of performance in a fast PK test. Our RNG
uses a noise source
to produce random
bits
at rates above
1000
pei
second, and
its output has shown excellent approximation to
ideal randomness. 9
III. Software Components
Thus far we have focused primarily on the hardware components
of the facility. In fact, however, by far the greater proportion of our
developmental
effort has gone
into construction of software
re-
sources for psychophysiology-psi research. These resources con-
sist of a collection of computer programs which allow us to exploit
effectively
the
available hardware
in
collecting,
managing,
and
analyzing physiological data.
Two
main
interrelated
design
objectives
have
guided
this
software development work. The first
is generality. Our aim has
been
to
develop
software
resources
for what we
foresee
as
a
ong-term program of systematic research on physiological corre-
lates of psi processes. Accordingly, rather than developing highly
specialized software for running each new experiment and analyz-
ing
the
resulting
data, we
set out
to develop
a
set of general-
purpose
research
tools
that can
henceforth
be
used
in
a wide
variety of contexts without further modification. Our second ob-
jective
is ease of use. Most people trained in experimental fields
have
little
experience
with computer programming,
particularly
systems-level
programming.
Yet
these
are
precisly
the
sort
of
people we hope will be able to use our system effectively. Our aim
has therefore been to make the complexities of the software rea-
sonably transparent
to users,
in the sense that they can readily
command the major resources of the system for their own research
purposes without having to invest large amounts of relatively un-
productive
effort in mastering unpleasant
details of a computer-
science nature. A corollary aim was to make the system readily
exportable,
in the sense that
its effective use should be minimally
dependent on the continued availability of its creators or similar
personnel.
The present software system represents, we believe, a good first
approximation to realization of these aims. However, certain limi-
tations were unavoidable. Generality and ease-of-use must always
,
?x,r
h:
TL
S 1° ^
elmu
f Sehmidt for consulting with us on design considerations
tor RNGs. The tinal version of our RNG was designed and built by Jack Hebrank
Technical details are provided
in Appendix
2.
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