# . ‘Approved For Release 2003/09/16 : CIA-RDP96-00788R002000260002-1 A Computer-Based Laboratory 167 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—1)/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. Approved For Release 2003/09/16 : CIA-RDP96-00788R002000260002-1
~ | Approved For Release 2003/09/16 : CIA-RDP96-00788R002000260002-1 © 168 Journal of the American Society for Psychical Research 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. REFERENCES Apgey, W. R. Computer analysis in neurophysiology. In R. W. Stacy and B. D. Waxman (Eds.), Computers in Biomedical Re- search. (Vol. 1.) New York: Academic Press, 1965. Pp. 223-263. Apey, W. R. Spontaneous electrical rhythms accompanying learned responses. In F. O. Schmitt (Ed.), The Neurosciences: Second Study Program. New York: Rockefeller University Press, 1970. Pp. 224-243. Benpat, J. S., and Piersol, A. G. Random Data: Analysis and Measurement Procedures. New York: Wiley, 1971. Bock, R. D. Programming univariate and multivariate analysis of variance. Technometrics, 1963, 5, 95-117. CLusiIn, W., GIANNITRAPANI, D., AND ROCCAFORTE, P. A nu- merical approach to matching amplification for the spectral analysis of recorded EEG. Electroencephalography and Clinical Neurophysiology, 1970, 28, 639-641. * Coorer, R. Measurement of time and phase relationships of the , EEG. In G. Dolce and H. Kunkel (Eds.), CEAN: Computerized EEG Analysis. Stuttgart: Fischer, 1975. Pp. 85-97. Approved For Release 2003/09/16 : CIA-RDP96-00788R002000260002-1 =
— TTS, earn anrecp Approved For Release 2003/09/16 : CIA-RDP96-00788R002000260002-1 A Computer-Based Laboratory 169 Davis, J. W., AND AKERS, C. Randomization and tests for ran- a domness. Journal of Parapsychology, 1974, 38, 393-407. Doncuin, E., AND Herrley, E. Minicomputers in the signal- averaging laboratory. American Psychologist Special Issue: In- strumentation in Psychology, 1975, 30, 299-312. ¢ DUMERMUTH, G. Numerical spectral analysis. In M. Matousek, Frequency and Correlation Analysis. Part SA, Handbook of Electroencephalography and Neurophysiology, A. Remond (Ed.). Amsterdam: Elsevier, 1973. Pp. 33-60. ELUL, R. Gaussian behavior of the electroencephalogram: Changes during performance of mental task. Science, 1969, 164, 328-331. Ke ry, E. F. Physiological correlates of psi processes. Parapsy- chology Review, 1977, 8, 1-9. KELLY, E. F. Converging lines of evidence on mind/brain relations. In B. Shapin and L. Coly (Eds.), Brain/Mind and Parapsychol- ogy. (Proceedings of the 27th International Conference of the Parapsychology Foundation, Montreal, 1978.) New York: Para- psychology Foundation, 1979. Pp. 1-34. KELLY, E. F., AND LENZ, J. E. EEG changes correlated with a remote stroboscopic stimulus: A preliminary study. In J. D. Morris, W. G. Roll, and R. L. Morris (Eds.), Research in Para- psychology 1975, Metuchen, N.J.: Scarecrow Press, 1976. Pp. 58-63. Kem, F. A waveform analyzer applied to the human EEG. [EEE Transactions on Biomedical Engineering, 1976, BME-23, 246- 252. (a) KLEIN, F. A low-powered 4-channel physiological radiotelemetry system for use in surgical patient monitoring. ZEEE Transactions on Biomedical Engineering, 1976, BME-23, 478-481. (b) Lenz, J. E.,.AND Keiiy, E. F, Computer-based calibration and system measurement procedures for psychophysiology research. Submitted for publication, 1980. Luria, A. R. The Working Brain: An Introduction to Neuro- psychology. New York: Basic Books, 1973. Morrison, D. F. Multivariate Statistical Methods. New York: McGraw-Hill, 1967. Nitsson, N. J. Learning Machines—Foundations of Trainable 2 Pattern-Classifying Systems. New York: McGraw-Hill, 1965. ’  OverALL, J. E., AND KLEetTT, C. J. Applied Multivariate Analysis. New York: McGraw-Hill, 1972. PALMER, J. ESP and out-of-body experiences: EEG correlations. In W. G. Roll (Ed.), Research in Parapsychology 1978. Metuchen, N.J.: Scarecrow Press, 1979. Pp. 135-138. SALTZBERG, B. Period analysis. In M. Matousek, Frequency and ’ Correlation Analysis. Part 5A, Handbook of Electroencephalog- Approved For Release 2003/09/16 : CIA-RDP96-00788R002000260002-1
Approved For Release 2003/09/16 : CIA-RDP96-00788R002060260002-1 a 170 Journal of the American Society for Psychical Research raphy and Neurophysiology, A Remond (Ed.). Amsterdam: Elsevier, 1973. Pp. 67-78. SCHMIDT, H. A quantum mechanical random number generator for , psi tests. Journal of Parapsychology, 1970, 34, 219-224. Scumipt, H. PK tests with a high-speed random number i generator. Journal of Parapsychology, 1973, 37, 105-118. t SCHOUTEN, S. A., AND KeELty, E. F. The experiment of Brug- mans, Heymans, and Weinberg. European Journal of Parapsy- chology, 1978, 4, 247-290. SOLFVIN, G. L., RoLLt, W. G., AND KELLY, E. F. A psychophysiological study of mediumistic communicators. Parapsychology Review, 1977, 8, 21—22. TimM, N. H. Multivariate Analysis: With Applications in Educa- tion and Psychology. Belmont, Calif: Wadsworth, 1975. Vos, J. E. Between EEG-machine and computer: Data storage and data conversion. In A. Remond (Ed.), EEG Informatics: A Di- dactic Review of Methods and Applications of EEG Data Pro- cessing. Amsterdam: Elsevier-North Holland, 1977. P. 143-155. WALTER, D. O. Digital processing of bioelectrical phenomena. In A. Remond (Ed.), Handbook of Electroencephalography and Clinical Neurophysiology. (Vol. 4B). Amsterdam: Elsevier, 1972. Department of Electrical Engineering Duke University Durham, North Carolina 27706 Approved For Release 2003/09/16 : CIA-RDP96-00788R0N02000260002-1