The Adaptable Mind: What Neuroplasticity and Neural Reuse Tell Us about Language and Cognition - John Zerilli 2021
I’d have never ventured into the field of cognitive science had it not been for the inspiring work of the linguist Noam Chomsky. I’m sure ten thousand tongues could sing this song, but whether it’s a cliché or not, it’s the truth. The technical brilliance, formal beauty, and extraordinary precision of his early work in transformational-generative grammar have never ceased to dazzle me. That he managed to contrive such a system while still in his twenties is simply astonishing. Anyone who has prepared a doctoral dissertation in a technical discipline knows something of the sheer brutality involved. To subvert, then reinvent, a whole technical discipline—in your twenties!—is nonpareil. I’ll be forever grateful that I was able to meet him personally during his visit to Australia in November 2011. I was even fortunate enough to be able to discuss with him some of the ideas that have found their way into this book. As it happens, I have arrived at conclusions that diverge from his in significant respects. But I have not done so lightly.
A second, but equally important, source of inspiration has been the work of the cognitive neuroscientist Michael L. Anderson, whom I was also privileged to meet, this time at a workshop run by Macquarie University’s Department of Cognitive Science in June 2016. The idea of neural reuse had been with me as a kind of premonition for years: indeed, from the moment I first turned away from the practice of law and began to inquire seriously into matters concerning the mind and its structure. As a 27-year-old, having never formally studied biology, linguistics, mathematics, or philosophy, I incautiously submitted a master’s thesis to the University of Sydney, canvassing issues in which some knowledge of these subjects would have been advantageous (to put it mildly). It was an unmitigated disaster, and I have ever since wished to eradicate all traces of it, prevented only by the limits of my jurisdiction over the University’s thesis repository. Curiously enough, I was actually awarded the degree, albeit on condition that I make a few emendations; but it was so poorly crafted and misinformed that to this day I can hardly say why. Nonetheless, and despite my embarrassment, a few ideas in the thesis stood out for being clearly articulated and not obviously implausible. One was the idea of neural reuse. Of course, I didn’t call it “reuse” at the time, and had devised a rather clumsy apparatus with which to express my theoretical inklings. When I encountered Anderson’s own elegantly conceived and much more skillfully executed theory of “massive redeployment,” I was able to take its descriptive apparatus on board. Anderson’s influence will be evident to anyone familiar with his work in the pages that follow.
A Note on my Conception of Philosophy
This is somewhat of a personal impression, but I suspect that many philosophers who work in the space around the theoretical and experimental sciences will have a similar idea of what they understand by “philosophy.” As a general rule, philosophy investigates questions that cannot be satisfactorily answered by the use of either formal or axiomatic methods of inquiry (the methods of logic and mathematics), on the one hand, or by the use of empirical, scientific methods, on the other (e.g., through observation, experiment, simulation, and modeling). Thus, questions concerning the nature of knowledge—for example, regarding what we know, and how we know what we know—as well as questions concerning the ends of life—what is the good, the beautiful, and so on—are paradigms of philosophical questions. In more concrete terms, however, philosophy consists chiefly of three interrelated activities:
(i)the systematic study of concepts and schemas;
(ii)the systematic study of the presuppositions of science; and
(iii)the systematic study of values and systems of values.
I see my philosophical work here, and that of most empirically minded philosophers, as primarily engaged in the second of these activities. But as I see things, (ii) is really only one part of a broader endeavor that is properly called “Theoretical Science.” Theoretical Science (as in Theoretical Physics, Theoretical Biology, Theoretical Linguistics, Theoretical Psychology, and so on) encompasses both the study of presuppositions in the above sense—the “Foundations of x”/the “Philosophy of x”—as well as all other scientific work that is not strictly experimental, as opposed to deductive, conjectural, or interpretative. And, truth be told, there is actually very little “Foundations of”/“Philosophy of” going on in this book. The little that there is can certainly be described as the “Philosophy of Science,” broadly, and the “Philosophy of Cognitive Science” (or “Philosophy of Psychology”), in particular. Most of the book, however, doesn’t deal with foundational concepts and presuppositions in cognitive science (e.g., “Is the computational analogy for the mind a good one?” “Are connectionist architectures better at accounting for mental operations than digital ones?” and so on). In fact, it completely sidesteps the most fundamental questions that could be asked of psychology (the proper purview of the “Philosophy of Mind”): for example, questions concerning the nature of the self, the relationship between mind and body, and the possibility of free will. Instead, most of the book operates at the deductive/conjectural/interpretative end of the Theoretical Science spectrum. This means that the book is more “Theoretical Psychology” than “Philosophy of Psychology,” per se. My guess is that the book is about 20% Philosophy of Psychology, and 80% Theoretical Psychology.
As one might have gathered, I am sympathetic to Quine’s ideas of a science—philosophy continuum, in which at one extreme, science deals with observation and verification, and at the other extreme, with conceptual difficulties. Both science and philosophy are concerned with understanding the nature of things, and both proceed by analysis and synthesis. As for which is more important, one might as well ask whether length is more important than height when calculating the area of a rectangle. Experiments never occur in a vacuum—they proceed against a background of shared and often implicit theoretical commitments, which it is the job of the philosopher to unearth and reformulate. Philosophy, for its part, needs the ballast of science to stop it from keeling over.
Special thanks are due to Kim Sterelny, Michael Anderson, Noam Chomsky, Richard Menary, Stephen Stich, Carl Craver, Colin Klein, Cecilia Heyes, Tori McGeer, Eva Jablonka, Paul Griffiths, Gualtiero Piccinini, Larry Shapiro, Tom Polger, Mark Couch, Matt Spike, Ron Planer, and Liz Irvine. Each provided support, inspiration, and encouragement one way or another, and helped me hone the arguments that form the backbone of this book.
Thanks are also due to my three friends Rebecca Riva, Jesse Hambly, and Hezki Symonds; and especially to my partner, Gavin Leuzzi, for his unfailing strength and forbearance throughout the entire process of the book’s composition.
Parts of Chapter 1 are reprinted by permission from Taylor and Francis, Philosophical Psychology, “Against the ’system’ module,” by John Zerilli (copyright 2017). Parts of chapters 3, 4, and 5 are reprinted by permission from Springer Nature, Biological Theory, “Neural reuse and the modularity of mind: Where to next for modularity?” by John Zerilli (copyright 2019). Parts of Chapter 4 were also reprinted by permission from Taylor and Francis, Philosophical Psychology, “Against the ’system’ module” by John Zerilli (copyright 2017). Parts of Chapter 7 (§ 7.5) were reprinted from “Neural redundancy and its relation to neural reuse” by John Zerilli (Philosophy of Science 86(5), 1—11; copyright 2019 by the Philosophy of Science Association; reprinted by permission from University of Chicago Press). Parts of Chapter 8 are reprinted by permission from Springer Nature, Synthese, “Multiple realization and the commensurability of taxonomies” by John Zerilli (copyright 2019).
The work here was supported by an Australian Government Research Training Program Scholarship.