* Approved For Release 2003/09/16 : CIA-RDP96-00788R002000260002-1 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.’ 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-11 in digital format via the DR11-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- ’ We 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. Approved For Release 2003/09/16 : CIA-RDP96-00788R002000260002-1
Approved For Release 2003/09/16 : CIA-RDP96-00788R002000260002-1 ‘, 156 Journal of the American Society for Psychical Research dently of the PDP-11, for simple kinds of experimental tasks (see Appendix 1 for further details). The ADC system 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 212 = 4096 possible numerical values. In our system, the noise level amounts to somewhat less than one bit, so that we have effectively 11 significant bits of signal; in general, eight bits is regarded as minimally adequate, and 10 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 DRII-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 DR11-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 DR1II-C. Up to eight digital sources may be attached to the multiplexer and thus share the one DR11-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 * This part of the system was constructed by Ross Dunseath, who was also responsible for parts of its design. ‘ Approved For Release 2003/09/16 : CIA-RDP96-00788R002000260002-1
TT ee a ee aaa nea ene nr, Approved For Release 2003/09/16 : CIA-RDP96-00788R002000260002-1 A Computer-Based Laboratory 157 become 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 . per second, and its output has shown excellent approximation to ¢ ideal randomness.? Ill. 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 long-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 ° Our thanks to Helmut Schmidt for consulting with us on design considerations for RNGs. The final version of our RNG was designed and built by Jack Hebrank. Technical details are provided in Appendix 2. Approved For Release 2003/09/16 : CIA-RDP96-00788R002000260002-1
io . Approved For Release 2003/09/16 : CIA-RDP96-00788R002000260002:1 158 Journal of the American Society for Psychical Research , be traded off against the amount of storage needed for data and the speed of execution of a program. An easy-to-use system with many seldom-used features usually requires much computer storage . space and may run notoriously slowly. Thus, in our system, which must handle large amounts of data in a relatively small computer, certain niceties had to be avoided. The rapid execution necessary > in the data acquisition system also required certain compromises. True exportability is also a problem in a program written in an assembly language for a particular piece of hardware. The data acquisition system is such a program and its ability to be shared -with other labs is thus quite limited. Despite these limitations, however, the overall system has proved to be fairly exportable,'® and it meets our current needs in terms of generality and ease of use. We now describe this software in some detail. The overall organization of the software system is outlined in Figure 2, details of which will become clear as we proceed. The system has two main parts—a collection of facilities for construct- ing and executing programs which control experiments and acquire data on-line; and a collection of data management, data reduction, and statistical analysis programs. A. Real-Time Data Acquisition System The major component of the real-time system is a collection of assembly-language subroutines which allows construction, entirely in FORTRAN IV, of computer programs for on-line control of any of a wide variety of experiments. Using these facilities, an experiment is organized as a temporal structure of events controlled by the programmable LPS clock. Associated with each event is a user-provided FORTRAN sub- routine which typically performs some elementary activity such as generating a target, receiving a response, storing sampled physi- ological data, etc. The real-time subroutines provide for defining events and their attributes (such as repetititon rate and priority of execution), scheduling and cancelling events, and starting and stopping the clock and setting its ‘‘tick’’ or interrupt rate. 10 The current Duke implementation runs under the single-user Disk Operating System (DOS). However, parallel versions of all our software have also been developed for the parapsychology laboratory of the University of Utrecht, in The Netherlands, which runs the multiple-user RSX-11M operating system. Technical » details of the DOS real-time software are contained in Appendix 3. The first two authors wish to express their thanks to Martin Johnson and Sybo Schouten, and to the Parapsychology Foundation, for supporting nine months of work at the Utrecht jaboratory. Approved For Release 2003/09/16 : CIA-RDP96-00788R002000260002-1