Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001-4 l,O Interim Report--Objective E, Task 9 December 1986 1SS MEASURING REMOTE ACTION INFLUENCE ON THE VERTICAL COMPONENT OF DUNALIELLA VELOCITY By: EDWIN C. MAY BEVERLY S. HUMPHREY SRI international Cc. M. PLEASS University of Delaware Prepared for: PETER J. McNELIS, DSW CONTRACTING OFFICER'S TECHNICAL REPRESENTATIVE 333 Ravenswood Avenue Menlo Park, California 94025 U.S.A. (415) 326-6200 Cable: SR! INTL MPK TWX: 910-373-2046 ZA Spieved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4
Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4 Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4
pRreved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4 (ONE O S/R internat Interim Report--Objective E, Task 9 December 1986 Covering the Period 1 October 1985 to 30 September 1986 MEASURING REMOTE ACTION INFLUENCE ON THE VERTICAL COMPONENT OF DUNALIELLA VELOCITY By: EDWIN C. MAY BEVERLY S. HUMPHREY SRI International C, M. PLEASS University of Delaware Prepared for: PETER J. McNELIS, DSW CONTRACTING OFFICER'S TECHNICAL REPRESENTATIVE SRI Project 1291 Approved by: ROBERT S. LEONARD, Executive Director Geoscience and Engineering Center 333 Ravenswood Avenue * Menlo Park, California 94025 * U.S.A. (415) 326-6200 * Cable: SRI INTL MPK - TWX: 910-373-2046 Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4
Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4 ABSTRACT The College of Marine Studies, Marine Biology Laboratory, of the University of Delaware has been conducting experiments with Dunaliella for a number of years. The researchers there claim that individuals are able to change the velocity of single algae cells significantly. SRI International has formulated a different hypothesis to explain their putative effect, i.e., individuals initiate experimental runs at a time during which the algae will naturally swim at the required velocity. The ability of the individual to initiate data collection at the opportune moment is called Intuitive Data Sorting (IDS). This report contains a historical overview of the effort at the University Delaware and a detailed outline of a proposed test of the IDS model. Li Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001-4
Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001-4 I INTRODUCTION As part of the general program at the College of Marine Studies at the University of Delaware, Dr. C. M. Pleass developed a system to measure the swimming velocities of single-cell marine alga. Having had a long time interest in psychoenergetic studies, Dr. Pleass initiated a remote action (RA) investigation with the marine alga, Dunaliella, using specialized hardware. As a consequence of his early effort and his promising results, SRI International asked Dr. Pleass to conduct specific experiments to test a model of psychoenergetic functioning that we call Intuitive Data Sorting (IDS). SRI let a two-year subcontract to the University of Delaware to achieve this goal. The first year’s task was to develop appropriate statistics and protocols for a formal experiment that will be conducted during the second year of the contract. This report contains the results of the first year’s effort. If we assume that a valid psychoenergetic phenomenon exists in Dr. Pleass’ experiments, then there are two heuristic models that are discussed below, RA and IDS, that might describe the mechanism. (The proposed protocol will allow us to determine from the data whether this assumption is valid.) A. Remote Action One hypothesis proposed by Dr. Pleass is that (RA) accounts for the data. (The cells are “forced” to conform to the “intent” of the participant in the usual cause-and-effect way.) This hypothesis supposes that consciousness interacts with matter and, in particular, with living systems. As a plausibility argument included in his report to SRI, Dr. Pleass invokes one side of a controversy that suggests that physical systems (micro and macroscopic), in the absence of measurement, exist as mixtures of all their possible configurations simultaneously. Although this can be demonstrated to be true with quantum systems, two basic assumptions are required to be true to extend the idea to the Dunaliella cells: ® Consciousness is a contributing factor in the quantum measurement process. e Living systems exist in “indefinite” states and thus qualify as quantum systems, Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4
Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4 The prevailing thought in physics today is that neither of these assumptions are valid. Although there are a few respected physicists who question the role of consciousness in the physical world, virtually none of them believes that macroscopic bodies exhibit measurable quantum mechanical effects. (There are circumstances in which macroscopic bodies exhibit quantum effects-—-superconductivity for example, but these are very special cases.) A different hypothesis, therefore, will probably more appropriately account for the data. B. Intuitive Data Sorting At SRI, we have been constructing a model to explain psychoenergetic data from a different perspective. Based upon an interpretation of an experiment that we conducted in 1979,'* we propose that an informational process, rather than a causal one, is responsible for certain putative RA phenomena. It is beyond the scope of this report to present a detailed description of the model; rather, we will provide a broad overview. We propose that humans can make decisions (by psychoenergetic means) to take advantage of the natural and unperturbed fluctuations of a system. In the context of the Delaware experiments, suppose that an individual is asked to “make” the Dunaliella swim faster. Rather than “causing” the cells to swim faster, we suggest that the participant has simply initiated the trial by anticipating when the Dunaliella were going to swim faster as part of their natural fluctuation in velocity. Thus, the participant has capitalized upon natural events, rather than “causing” anything to occur. We call this ability IDS. We have been able to design the Delaware experiments in such a way as to distinguish an IDS~mediated result from a causally mediated one. By definition, causal effects, on the average, will effect the Dunaliella on a cell-by—cell basis. For example, they are phototropic (i.e., each cell is attracted by light). The net effect of such a causal relationship is that velocity averaged over a large number of cells will produce a very large statistical effect. Because any informational processes (i.e., IDS), by definition, do not perturb systems (at least classically), averaging over a large number of cells can only reduce any observed statistical effects. Therefore, if the effects that Dr. Pleass observes are causal (i.e., RA), then averaging over a large number of cells will produce a strong result. If the data are weaker as a function of cell average (but remain significant), then the effect is likely to be informational (i.e., IDS). Dr. Pleass’ FY 1986 progress report is contained in Appendix A. The complete details of the apparatus, analysis, protocols, and early results, provided by Dr. Pleass, can be found * References are listed at the end of this report. Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4
Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4 in the annex to Appendix A. A brief summary of the past experimental details are provided below. Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001-4
Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4 Il METHOD OF APPROACH A. Hardware The Dunaliella are contained in a small test tube in a temperature-controlled, darkened room. Their velocities are measured by a standard laser Doppler technique, which is sensitive to the velocities of individual cells. The laser Doppler apparatus allows for velocity measurements to be averaged over any number of cells ranging from one to an arbitrarily large number. A typical velocity for a single cell is of the order of 20 micrometers/sec. The data from the laser Doppler device are accumulated, displayed, and retained on an IBM PC. All participant and monitor interactions with the experimental apparatus are performed through the IBM PC. B. Statistics The velocity data, like those for most living systems, have a large degree of variance, for which there are a number of contributing factors, including: Living systems inherently exhibit a low signal to noise ratio. Dunaliellae are sensitive to environmental factors such as light and low frequency electromagnetic radiation. @ Dunaliellae appear to exhibit a 24-hour circadian rhythm. The initial attempt to analyze this kind of data included a double difference technique. Each set of data involved (1) a putative RA period, during which the participant attempted to modify the swimming velocities, (2) a control period immediately thereafter, and (3) two matching periods collected when the participant was absent, i.e., pseudo-RA and pseudo-control, respectively. The total run score by this technique is given by n n v4 bg = d _ do- Run Score = > ( xo _ x) _ Ss ( xP o control _ xP o-RA , where the X’s are the velocity averages for each data point, [j]. Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001-4 rrr
Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4 Although many data were collected and analyzed by this technique, the statistical method proved to be unstable; reliable probability assessments of any effects, therefore, were difficult to obtain. The current method in use at the University of Delaware is a modification of the above procedure. Run scores are accumulated for a particular participant, and the resultant distribution is fit with a Gaussian curve. Global controls are collected under conditions that emulate the experimental conditions as closely as possible (e.g., using the same phase angle in the circadian cycle, the same RA/pseudo session spacing, etc.). These data are also fit with a Gaussian curve. The statistical significance of the RA session is estimated by the ratio of the variances between the periods of effort and the periods of global control. Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4
Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4 ) III RESULTS AND RECOMMENDATIONS The subcontract with Delaware entails a two-year effort; therefore, there are no new experimental results to report as of this writing. We recommend that a number of points be considered before initiating any formal trials. A. Protocol Before any tests for mechanisms are warranted, it must first be demonstrated that there is some valid psychoenergetic effect. This obvious criterion affects the selection of participants, the details of the participant-monitor interaction protocol, and the statistics. We suggest that one or more pilot series be conducted, using the final protocol and statistics to aid in the selection of “good” participants. As described in the introduction, the tests for mechanisms require a series of trials using a known causal component (e.g., a light source). We suggest that trials be conducted when a participant is attempting to modify the algal swimming velocities; these trials should be counterbalanced by identical trials during which the participant is replaced with a light source adjacent to the cells. B. Statistics As part of our recommendations for methods of analysis, we include a detailed description of a technique that is commonly used in geophysics and that may be applicable to the Delaware experiment. 1. Background Radar technology has provided a number of powerful techniques to perform time series analysis upon “noisy” data similar to that described above. We will focus our attention upon a technique : that is in common use in geophysics. In 1913, C. Chree introduced a method to correlate sunspot activity with terrestrial magnetism.2 His approach was a particularly powerful one and exists today under a number Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001-4 a _______...  ee  rere
ofpproved For Release 2000/08/0 erent names (e.g., epoc A;RDES6-Q0789R002200030001 -4 analysis, an sigh averapin ignal averaging is a Wi used technique in such diverse fields as brain research and radar; therefore, quantities such as signal-to-noise ratios, system sensitivity, and sampling limitations are available in the literature. When applied to research with the Dunaliella cells, the technique contains one important underlying assumption--namely, that there is a time-stable (however small) component to the cell velocities that may correlate with the participant’s effort. To clarify the technique, we will use an example from central nervous system (CNS) research. To measure a visual evoked response, the following steps are performed: 1. A light is flashed in a subject’s eyes (the event). 2. Occipital EEG is measured every millisecond for 250 ms (the time series data). 3. Steps 1 and 2 are repeated for approximately 100 flashes—-the data from each step are averaged into the preceding data. If there is no time-stable component of the occipital EEG to the light flashes, the data will average to zero. What is found, of course, is that in some fraction of the population, a persistent signal survives the averaging. That signal is called the visual evoked response. To apply this technique to the Dunaliella experiment, let us assume that we have measured the cellular velocities, V, average over [q] cells (RA condition). Further, assume that we have [n] number of events (similar to the light flash above) consisting of single button presses by the participant to initiate a trial consisting of [m] velocity measurements. Figure 1 shows a matrix of data that can be constructed from such a situation. Vix is the velocity measurement at time [k] for each button press [j], and tk (k = 1,m) represents the kth data point (after all the data have been detrended). As in the CNS research example, we average the velocities across all button presses for each data point to produce column means (the V-bars in this example). The row means, V~-bars, will be discussed below. A similar data matrix can be constructed when the apparatus is completely unattended (the MCE condition). We must now determine if the RA matrix is significantly different from the MCE matrix. An Analysis of Variance (ANOVA) technique is the appropriate statistic to use to understand this situation. An ANOVA can determine: 1. If the RA-condition column means differ significantly from the MCE-condition column means (an ANOVA interaction term). Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4
Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4 ; 2. If the variation observed in the RA-condition column means is highly significant. Button|! ¢ t FIGURE 1 SIGNAL AVERAGING DATA MATRIX The second case above is particularly interesting. If the number of button presses is large, and if the RA-condition means are highly significant (i.e., ~ p < 10-15), then there is strong evidence in favor of a causal interaction rather than an IDS process. IDS is not a competing process if a system possesses a nearly infinite signal-to-noise ratio-~the case that is required if item (2) above is true. Under the condition that the ANOVA shows a significant interaction between the RA and MCE conditions, then a second analysis is imperative when working with Dunaliella. The problem is that the Viks are not necessarily statistically independent and cannot be considered random variables in the usual sense. By ignoring possible persistent temporal components to Vik (i.e., the 24- hour circadian rhythm), Forbush et al.? demonstrated that a gross underestimate of the residual variance may occur leading to a highly inflated F-ratio from the ANOVA. In their test example in geomagnetic data, the inclusion of a correction for a known temporal persistency reduced the F(26,3874) ratio from 4.96 to 1.16 (a p-value increase from 10-5 to 0.3)! Forbush et al. suggest that a variance correction must be made. Although there are a number of different techniques to provide a variance correction, the technique that Forbush et al. suggest provides a quantitative estimate of a “coherence length” beyond which a variance correction is not needed. Thus, it is possible to determine Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001-4
Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4 psychoenergetic effect that can be described by an informational process, then the data will lie along a straight line with the same slope (-0.5) as the MCE line, but with a significantly different intercept. Should the effect prove to be causal, then the data are expected to lie along a curve similar to the RA curve. One advantage of working with a living system as an RA target, is that, in this case, a known cause-and-effect relationship can act as an RA-like control. If the shift of the velocity distribution because of the phototropic behavior of the cells can be determined, then the phototropic data as a function of [m] can be calculated in advance. Thus, if the phototropic data lie along the predicted RA-like curve and the data produced by a participant lie along the IDS curve, then we should have compelling evidence in favor of the IDS hypothesis. 10 Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4
Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4 IV CONCLUSIONS By using the most powerful statistical techniques available, psychoenergetic effects if present, can be observed in this exceptionally noisy system. If psychoenergetic effects can be verified, we believe that the experiment conducted by Dr. Pleass constitutes one of the most important tests of the IDS hypothesis. 11 Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4
Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001-4 REFERENCES 1. May, E. C., Humphrey, B. S., and Hubbard, G. S., “Electronic System Perturbation Techniques,” Final Report, SRI International, Menlo Park, California (September 1980). 2.  Chree, C., “Some Phenomena of Sunspots and of Terrestrial Magnetism-Part II,” Phil. Trans. Roy. Soc. London, Vol. 213A, pp. 245-277, (1913). 3. Forbush, S. E., Pomerantz, M. A., Duggal, S. P., and Tsao, C. H., “Statistical Considerations in the Analysis of Solar Oscillations Data by the Superposed Epoch Method,” Solar Physics, Vol. 84, pp. 113-122 (1983). 12 Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4
Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4 Appendix BIO LASER DOPPLER CONSCIOUSNESS RESEARCH C. M. Pleass College of Marine Studies University of Delaware . Newark, Delaware A Progress Report for 1985-1986 to SRI International Contract No. C-11498 13 Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4
Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4 , BASELINE DATA A study of the structure of 1985 baseline velocity data derived from cultures of the motile marine alga Dunaliella has shown that any given data string may or may not exhibit trend, abrupt mean shifts, periodicity, or any combination of these. Examples are given in the Annex. Only the diurnal (or circadian) rhythm is consistently manifest. Because it is long compared to the duration of a typical set of psi runs, it normally appears as trend in the data strings that report the velocities. Figures 1 and 2 show 24 hours of velocity and vector data from Dunaliella. The correlation between circadian phase angle, the expected magnitude of the observed velocity, and the direction of motion is evident. Our 1986 baselines are “quieter” and rarely show abrupt mean shifts or periodicity, other than the trend that derives from the circadian rhythm. This results from changes in laboratory practice described in the section on microbiology. PROTOCOL FOR AN IDS EXPERIMENT A protocol has been developed for 1986-87 studies of the IDS hypothesis. The protocol allows the participant (we choose to use the word participant, instead of the more usual term operator, to try to encourage a synoptic view of the experiment) to determine the length of the psi run, which is marked on the evolving data string by using preprogrammed keys on the computer keyboard. The participant touches the key Fl when they are ready to begin the psi run, and the key F10 at the end. The psi task has been to visualize the algae at the laser beam crossover, and the variable is the resolved value of the algal velocity. We ask participants using this procedure to end their runs as abruptly as possible, the moment that an intrusive thought diverts their attention. They then read a dictionary while control data evolves. Figure 3 illustrates a hypothetical set of three runs. Note that while the participants are given a cue on the monitor at the end of the minimum control period B, they may be engrossed in Webster’s definition of fescennine and, therefore, choose to delay their next run. 14 Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4 EE eee''"!--~~
Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4 Absolute Velocity- 24 Hour Record Velocity msec7!x10- Time in hours FIGURE 1 Circadian Variation in Dunaliella in Swimming Velocity During the First 24 Hours in Continuous 6328A Light 15 Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4
Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4 Direction of Movement- 24 Hour Record % moving down Time in hours FIGURE 2 Circadian Variation in Dunaliella in Direction of Motion in the First 24 Hours in Continuous 6328A Light 16 Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4
Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4 —_ oe co fon) ~ —en oe me Sw ae of <x -_—~ om -_ ~ ~— we om ow ome 3 o nd a se — @ Qa. ~ « © tan] Cad n § co oO faa) <5) = - 2 me) 2 6 - eee eee S&S - Lu Qa. ° - So < a [+] p 5 o ~— ee _ — - mm oe me] ~ 6 Oo laa w wo S = - ob) > 2 —_—e =e oa Se ee ee ee) Q. i= c = - fy S fam) n land _  & — ao &£ > Li corm non ow on. <a © _ Lu FIGURE 3 Format for PK86 17 Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4
Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4 Feedback is provided at the end of each session, in the form of a plot of V psi minus V control for each run within the set. This procedure is likely to result in run times varying from 30 seconds to 10 minutes, with clustering around i to 4 minutes. However, we want to start in this mode. In the 1986-87 proposal there is a flow chart of the proposed research and notes about future trials with sequence lengths at equally spaced intervals of log (sequence length), and experiments in which psi alternates with light. STATISTICAL PROCESSING Because trend in the data is the norm, statistical processing starts with detrending. The method used through most of 1984-85 involved double differencing and is described in the Annex. In early 1986, a more straightforward technique was developed; all data are regressed onto a line, and the slope of this line is then used to detrend each datum. Somewhat to our surprise, detrending in this way does not blur the structure of plots of run scores (Figures 4 and 5). After detrending, the data are processed in the simplest possible manner by using the difference in the mean velocity during the psi and control periods as the “score” for the trial. Because there will normally be a “score,” even if there is no psi mediation, individual values of [psi-control] do not relate exclusively to the null hypothesis that there is no psi effect; they are qualitative indicators. Histograms of these:scores are also inconclusive until they are compared to equivalent histograms prepared from data strings that have no psi mediation at all. In 1986 we have chosen to take this "global control” data on the following day at exactly the same circadian phase angle (time). The technique used is to transfer the time markers from the real psi and control data string to the global control string. This global control data accumulates while the experimenter is doing other work in adjacent laboratories, blind to the process. One way of comparing accumulated experimental and global control data to see if there is evidence of a psi effect is to describe Gaussians that best fit the histograms, and then compare the experimental to the global using a F test. We are presently moving away from this approach because the distributions of experimental data are so non-normal, but it is informative to use this approach to check that detrending by regression does not change results originally obtained by detrending using double differencing. 18 Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4
Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4 SPrsiz mel eeJe CI ed < o 12 3 4 5 6 7 8 9 16 44 42 43 44 45 FIGURE 4 Standard Error Bars For Test 706 - Raw Velocity 17 HM iz E A N 0 2 seer e ee ene eee eee eres snares ener enres L BE cede cceseducssesesebeccseepedieeele i Y a) OS, Se OO ck ke oO ft 2 3 4 5 6 7 8 9§ 46 44 42 13 14 15 TIME FIGURE 5 Standard Error Bars For Test 706 ~ Detrended Velocity 1y Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4
Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4 Figure 6 records F tests on the output from these two different analyses. Because the data are not normally distributed the p values which result from the F test are only indicators, but they are both low, and remarkably similar. The PK86 data comes from much quieter baselines (see microbiology) and the global data are quite a good approximation to a normal distribution, with X2 = 0.44 (Figure 7). The experimental data (Figure 8) have the characteristic non-normal distribution that we are beginning to recognize as evidence of response to a stimulus. Once again, the F test is only an indicator, but the numbers are quite encouraging. EXPERIMENTAL GLOBAL 2.64, DF = 176/158 p< 10°  (Statgraphics limits!) Note that like the old WAVE data given in the Annex, the PK86 data have larger variance in the experiment. PK85 data still seem to reflect one participant’s tendency to calm the algae (Annex, page 16). As the other individual data bases grow, we will be able to sort this out. Spontaneous variation in the duration of our 1985-86 psi runs has provided an opportunity for a preliminary examination of the variation of the psi score with sequence length. Figures 9 through 12 show plots of PK85 and PK86 scores against sequence length with the corresponding globals. (Watch the varying scale on the ordinate caused by the software used). As yet, we do not feel we have enough data or enough spread in sequence length to form even tentative conclusions: that will be a task for 1986-87. 20 Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4
Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4 GLOBAL CONTROL PK85 F = ———__—__—— EXPERIMENTAL CASE 1 - PK85 data detrended and scored by double differencing: (V (Vv - Vv ) control ~ Vost? ~ pseudocontrol pseudopsi F = 1.64, 204 DF p= oxi074 CASE 2 - PK85 data detrended by regression, then scored as: Vosi - Voontrol F = 1.707, 204 DF pe 7x107° FIGURE 6 F Tests On Best Fit Gaussians From Histograms of Scores 21 Approved For Release 2000/08/08 : CIA-RDP96-00789R002200030001 -4