Chapter 7 - Rats, Mazes, and the Long Shadow of McDougall

In 1920, sixteen years before Rupert Sheldrake was born, a Harvard psychologist named William McDougall began an experiment that would run for more than three decades, consume the working lives of several successive research assistants, and eventually become the closest thing morphic resonance has to a genuine, extensive, quantitative body of prior data - despite the fact that McDougall himself was testing a completely different, and by then already unfashionable, hypothesis: Lamarckian inheritance of acquired characteristics, the same discredited idea we distinguished carefully from morphic resonance back in Chapter 5.

This chapter tells McDougall's story in full, examines what his data actually showed, traces how his results were received and contested at the time, follows the twenty-year Australian replication that came after him, and then brings the story forward to the more recent, morphic-resonance-specific reinterpretation that Sheldrake gave the whole dataset decades later.

McDougall's Original Experiment

McDougall trained white rats to escape a water tank with two exits, one safe and leading to a platform, one delivering a mild electric shock, using visual cues - illuminated versus dark exits - to signal which was which. He then bred from these trained rats across successive generations, retraining each new generation on the identical task, and carefully recording the average number of errors each generation made before learning the correct association. If Lamarckian inheritance were operating, McDougall reasoned, each successive generation, descended from parents who had themselves learned the task, should make measurably fewer errors than the generation before it - the acquired learning ability passed down, quite literally, in the germline.

The numbers, as McDougall reported them across the 1920s and 1930s, told a striking story. His first generation of rats averaged roughly 165 errors before reaching the learning criterion. By the twenty-second generation, that average had fallen to around 20 errors - an eightfold improvement, tracked generation by generation, with enough consistency that McDougall's own statistical analysis judged the trend too smooth to attribute to chance. This was a real, published, seemingly robust empirical finding from a serious, credentialed psychologist - McDougall had previously chaired psychology departments at Oxford, Harvard, and Duke - and it caused exactly the stir you'd expect, because it appeared to contradict the hardening genetic consensus of the era. Following the rediscovery of Mendelian genetics and August Weismann's earlier work establishing the separation of germline and somatic cells - the "Weismann barrier," which holds that changes to an organism's body during its lifetime cannot, in the general case, be written back into the DNA passed to its offspring - biology was already moving decisively away from any Lamarckian mechanism.

Crew's Rebuttal, and a Wrinkle Worth Understanding

The most serious and influential challenge to McDougall's results came from Francis Crew, a University of Edinburgh geneticist who ran a large, carefully controlled version of essentially the same experiment specifically to test whether McDougall's declining error trend would replicate under conditions designed to rule out confounds. Crew's results showed no such trend across the generations he tested, and this null result was widely taken, at the time and since, as strong evidence that McDougall's original finding was an artifact of some confound in his experimental setup - general improvement over the successive years of a single research program's methodology, unconscious selective breeding for more "trainable" rats even without deliberate intent, subtle changes in handling or experimenter behavior over the study's long duration, or simple selection effects in which generation's data got included in the final published analysis.

Here is the wrinkle worth understanding, because it's exactly the kind of detail that gets flattened in both dismissive and credulous popular retellings. A later reassessment of the historical record - by the psychologists E.W.P. Halloran and H.T. Kalmus, reviewing the archival data and correspondence from both McDougall's and Crew's laboratories - found that Crew's own rats had actually shown declining error rates across generations too, in the earlier part of his study, before the trend disappeared, and that some of the apparent "clean refutation" narrative that entered later textbook and popular treatments simplified a messier, more ambiguous actual data record on both sides. This is not a vindication of McDougall, and it is not evidence for Lamarckian inheritance or for morphic resonance. It is, rather, a demonstration of exactly the pattern this book keeps returning to: the popular, textbook-simplified version of a scientific controversy - "McDougall found an effect, Crew ran a clean replication and found nothing, case closed" - is often a tidier and more decisive story than the actual archival data supports.

Twenty Years in Melbourne

The controversy did not end with Crew. In 1954, an Australian research team led by W.E. Agar at the University of Melbourne published the results of a replication attempt that dwarfed both McDougall's and Crew's studies in scale and duration: twenty years, spanning fifty generations of rats, run specifically to settle the question with more statistical power and tighter controls than either of the earlier studies had managed.

Agar's team found no overall Lamarckian trend across their trained line - the improvement McDougall reported did not reappear. But their study contained a detail that has kept it central to this controversy for seventy years since: their untrained control line - rats never exposed to the water-tank task at all, bred purely as a comparison population - also showed a modest downward drift in errors on tasks they were eventually tested on, a drift the Melbourne team themselves could not fully explain through deliberate selection, since no one on the team was selecting control-line rats for trainability at all. Agar's own interpretation leaned toward general, non-Lamarckian improvements in the health and vigor of the laboratory rat population across the study's two decades - better diet, better husbandry, incidental genetic drift in a large managed colony - rather than anything resembling inherited learning. But the fact that even the untrained control population showed some drift is exactly the kind of finding that later researchers, including Sheldrake, would seize on as evidence that something beyond straightforward genetics might be operating across the whole of a laboratory rat population, trained or not.

Sheldrake's Reinterpretation

Sheldrake picked up this dormant, largely settled-by-textbook-convention controversy decades later and offered a reinterpretation worth understanding precisely, because it illustrates both the appeal and the risk of morphic resonance as an explanatory framework. Sheldrake argued that McDougall's original declining-error trend, and Agar's puzzling control-line drift, need not require Lamarckian genetic transmission at all - they could instead reflect morphic resonance, with each successive generation of rats benefiting from the accumulated resonant influence of all previous rats, anywhere, that had learned the same or a similar task, meaning the effect, if real, should not be limited to any one bred lineage at all.

This reframing is, in one sense, a genuinely elegant move: it offers to rescue a historically interesting, real if contested finding from its apparent refutation by genetics, without requiring any revision to accepted genetic mechanisms, by relocating the explanatory burden to an entirely different, non-genetic channel. But - and this is exactly the falsifiability-and-Lakatos concern built up in Chapter 6 - this reinterpretation also generates a new, sharper prediction that goes beyond simply re-explaining old data: if morphic resonance, rather than genetic inheritance, is responsible, the effect should appear in genetically unrelated rat populations too, trained on the same task in different, unconnected laboratories, with no breeding relationship to McDougall's, Crew's, or Agar's animals at all. Sheldrake has pointed to some subsequent findings suggesting that entirely new, genetically unrelated rat populations seemed to learn certain standard laboratory tasks - not McDougall's exact water-tank task, but structurally comparable maze and discrimination tasks - increasingly quickly across the decades, across many different labs worldwide, in a pattern not well explained by any single lab's own genetic selection, since the improvement appears distributed globally rather than confined to specific bred lineages.

This is, I think, the single strongest and most carefully arguable piece of quantitative evidence in the entire morphic resonance literature, and it deserves to be taken seriously as such - and it is also extremely difficult to disentangle from entirely mundane, well-understood confounds that have nothing to do with any non-local effect: general improvements in laboratory animal husbandry and rat strain standardization over the twentieth century, general improvements in experimental apparatus design and experimenter training passed on through ordinary scientific mentorship and published methodology, and publication bias favoring the reporting of successful, clean experimental results over messier ones from earlier, less standardized eras. Separating a genuine cross-population resonance signal from this thicket of entirely conventional explanations is a real, unsolved, and - this is the point I most want you to take from this chapter - a genuinely tractable modern statistical and computational problem, one we return to with concrete methodological proposals in Chapter 22, once we've built up the machine learning toolkit to actually attempt the disentanglement rigorously.

A Note on McDougall Himself

It's worth pausing on who William McDougall actually was, because it bears on how much weight his data deserves independent of its statistical merits, and because it illustrates a discipline this book has tried to model throughout: evaluating a specific empirical claim on its own terms, separately from a researcher's broader reputation, rather than letting one contaminate the other in either direction. McDougall was, by the standards of his own era, a genuinely eminent psychologist - department chair at three major universities, a founding figure in social psychology, president of both the American Psychological Association and the Society for Psychical Research at different points in his career. He was also, by the standards of any era, a committed and vocal proponent of eugenics, publishing arguments in favor of selective breeding policies that are rightly considered abhorrent today and were controversial even among many of his contemporaries. Some later commentators, hostile to his Lamarckian rat experiments, have suggested his eugenicist commitments motivated or biased his interpretation of the trainable-rat data, since a hereditarian reading of "trainability improves across generations" fit comfortably with his broader views about heritable mental capacity. This is a fair point to raise as a possible source of motivated reasoning, and it belongs in any honest accounting of the controversy. It is not, on its own, a refutation of his data, which Crew and later Agar were able to independently test and partially, if messily, corroborate using their own separate apparatus and their own separate rat populations - precisely the kind of independent replication that should carry more evidential weight than an assessment of the original researcher's character, however troubling that character's other views were. Holding both of these facts in mind simultaneously - a scientist's documented views can be genuinely disqualifying for trusting their own interpretation of ambiguous data, while not being sufficient grounds for dismissing data that others have independently, if partially, reproduced - is exactly the kind of source-by-source discipline Chapter 8 will ask of you again in a very different context.

The Broader Pattern in Animal Behavior Claims

McDougall's rats are the most historically significant example, but they are not the only body of evidence offered in this domain, and it's worth briefly surveying the broader landscape before we move to more recent chapters, because the same structural pattern - a real, interesting, but confound-laden finding, susceptible to multiple competing explanations of wildly different levels of exoticism - recurs across nearly every animal behavior claim associated with morphic resonance.

Claims about the coordinated behavior of bird flocks and fish schools - how a flock of thousands of starlings can execute what appear to be near-instantaneous, whole-flock direction changes with no apparent central coordination - have sometimes been offered as evidence for field-like, non-local coordination. But this specific phenomenon, murmuration, has, over the past two decades, been given an increasingly successful and detailed mainstream explanation through exactly the kind of complex-systems modeling we'll examine fully in Chapter 18: local interaction rules between each bird and its handful of nearest neighbors turn out to be sufficient, in well-validated computational models, to reproduce the observed flocking behavior with remarkable fidelity, including the rapid whole-flock direction changes that look, to a casual observer, like they must require instantaneous global coordination.

Claims about homing behavior in pigeons - how pigeons find their way back to a home loft across unfamiliar terrain - have been genuinely important to Sheldrake's own research program; he has published specific work proposing that homing pigeons may be guided in part by a resonant connection to their home loft, rather than solely by the magnetic-field, solar, and olfactory navigation cues that mainstream ornithology has documented in increasing mechanistic detail. This remains a genuinely open and actively studied area of animal navigation research, and it is fair to say that the mainstream, non-resonance account, while increasingly sophisticated, is not yet fully complete - a point we return to when discussing sensor-network research proposals in Chapter 23.

Looking Forward

McDougall's rats give us as clear a window as this book has to offer into the actual texture of morphic-resonance-relevant evidence: not fabricated drama, but a genuinely messy, genuinely contested, partially replicated body of data that admits multiple competing explanations, several entirely mundane, none fully ruled out, and all of it crying out for the kind of large-scale, well-controlled, statistically sophisticated modern re-examination that simply wasn't possible with 1920s, or even 1980s, research infrastructure.

Chapter 8 turns to a very different kind of evidence - not messy and contested, but famous, vivid, and, in its most popular form, almost entirely invented. Understanding exactly how the story of monkeys washing sweet potatoes escaped from a modest field observation into an urban legend, and how Sheldrake himself came to publicly disown it, will sharpen every judgment you make about the genuinely contested evidence still to come.