In the early stages of a career in brain science, one learns very quickly that the human brain is still largely unknowable.
Even as exciting new methods to investigate the human brain proliferate beyond count, our understanding of this system seems to remain fairly stagnant.
We create and re-create these infamous ‘box-models’ of purported brain functions—like the “conflict monitor” that tells us our legs which of the two pedals they should depress, the accelerator or the brake; or the “attention switcher” which tells our eyes what to bring into focus, the knife on the TV screen or the fire on the stovetop. These models are then routinely criticised as homuncular—imaginary little ‘men’ in our brains that control what we do, leaving us no closer to understanding how the brain might actually solve such problems. In spite, or in defiance, we nevertheless spend entire careers in attempts to locate these imaginary men among the structures in our head by flashing moving dots or coloured shapes on a screen in a carefully controlled environment that has no particular bearing on the world that we live in. We then apply complex mathematical analysis to the data we’ve collected that very few people truly understand, desperately hoping that the assumptions we’ve made along the way aren’t distorting the data beyond recognition.
It leaves us to wonder whether anything we might have found reflects the brain’s true operation.
These concerns live with each brain scientist, and we do our best to address them. But their existence hurts each of us who truly wishes to understand the secrets of the mind.
And so it was comforting to find advice in the pages of a manual on farming. In the 1980s, one of the founders of the art of permaculture published his foundational textbook Permaculture: A Designer’s Manual. It really is much more than a more sustainable method of farming. It also promotes a mindset and outlines a philosophy of ethics. An attempt to move from a destructive and parasitic relationship with biodiversity towards one more in keeping with the mercurial nature of… well, nature.
Of science, the author Bill Mollison had to say (emphasis mine):
Scientific method is one of the ways to know about the real world… Observation and contemplative understanding is another. We can find out many things… by timing, measuring, and observing them; enough to make calendars, computers… but not ever enough to understand the complex actions in even a simple living system. You can hit a nail on the head, or cause a machine to do so, and get a fairly predictable result. Hit a dog on the head, and it will either dodge, bite back, or die, but it will never again react in the same way. We can predict only those things we set up to be predictable, not what we encounter in the real world of living and reactive processes.
Mollison later goes on to note, more harshly:
Perverse planning is everywhere obvious: houses face not the sun, but rather the road, lawns replace gardens, and trees are planted to be pruned and tended. Make-work is the rule, and I suspect most theoretical scientists inhabit demented domestic environments, just as many psychiatrists are inhabitants of mental institutions.
Brain science contains a great deal of perverse planning, it seems to me, and many of our scientists inhabit demented environments. One of the more disheartening features of the practice is the constant battle between the adherents of the latest ‘grand unifying’ hypothesis or complex-beyond-understanding method against the inevitable torrent of evidence that the hypothesis unifies very little and the method produces results that are as incomprehensible as the method itself. Perhaps our experiments are also make-work. An attempt to find evidence for things that will simply shatter upon contact with the real world.
Mollison writes:
Life exists in conditions of flux, not imposed control, and responds to any form of control in a new fashion. Living things respond to strict control… by becoming uncontrolled, or… dysfunction… Experiments, therefore, are not decisive, rigid, or true findings but an eternal search for the variables that have not been accounted for previously.
And here is the comfort. Perhaps, rather than an attempt to know the unknowable or, as Mollison, to “understand the complex actions in… a… living system”, our attempts should be a little more humble. The quest to account for the variables that have not been accounted for previously. Those aspects of neural function that teach us about specific solutions to specific problems, or specific responses to specific inputs.
Though many of our “box-models” and “imaginary men” are likely gross over-simplifications or downright incorrect anthropomorphising of the functional abilities of a mess of electrified mush; though many of our experiments are contrived and controlled to the smallest detail; though many of our methods are as convoluted and mercurial as the brain we’re trying to understand; the very fact that so many of our ideas about the function of the mind have survived the test of time might be, not a sign of stagnation, but a sign that we are on the right path and are just approaching things with the wrong mindset.
Perhaps the brain scientist’s job is not to explain the big things, but illuminate the little ones.
Not bad advice from a design manual for farming.