Methods in Studies of the Nervous System
Theoretical Methods in Studies of the Nervous System, 1920–60
The use of methods from the exact sciences in biology during the twentieth century, entailing issues of the disciplinary authority of physics, the reduction of biological phenomena to physical terms, and the autonomy of biology, has been a topic of interest in both the history and philosophy of biology. Philosopher of biology Michael Ruse, amongst others, has noted that the complexity and uniqueness of biological phenomena can be used as an argument for the autonomy of biology from physics, and implicitly from mathematics.
Today, many historians and philosophers of biology, even biologists themselves, are calling for an approach involving more theoretical tools. Although many theoretical biologists today work at the interface between theoretical and experimental biology (particularly in the neurosciences), theoretical biologists—often “migrant” physicists and mathematicians—for decades have largely operated separately from experimental biologists. Superficially, differences in methodology have caused this rift. Methodological arguments are tied to the question, “What are the means and methods appropriate for studying biological phenomena?” Resistance to theoretical methods in biology has often rested on arguments about complexity.
A closer look at the development of theoretical methods in twentieth-century life sciences shows that this is a more complicated story. Many scientists during this period—particularly cyberneticians, mathematicians, and physicists—saw the complexity of living processes as a justification for the use of mechanical analogies and the theoretical methods to address problems in the life sciences.
By the end of the 1940s, a picture of the nervous system emerged that characterized the neuron as a digital entity. This view was largely the result of theories presented by neuropsychiatrist Warren S. McCulloch and mathematician Walter Pitts. Their fundamental presupposition was taken from neurophysiology itself: the all-or-none principle. Expressed in 1914 by neurophysiologist Edgar D. Adrian, the all-or-none law held that the relation between a neural stimulus and the activity it produces is “all or nothing.” In 1943, McCulloch and Pitts translated this principle into the supposition that just as propositions in logic can be “true” or “false,” neurons can be “on” or “off”—they either fire or they do not.
The McCulloch-Pitts neuron was a key element of the cybernetic vision, and allowed cyberneticians to conceptualize the brain and its functioning as a digital computer. While some physiologists, like Ralph W. Gerard, pointed to complexities of the nervous system that should prevent one from making abstractions and conceiving of neural activity as exclusively digital, proponents of the “modelling” approach, like McCulloch, argued that simplifying the activity of individual neural elements allowed one to grasp the functions of the nervous system that were too complex to understand through empirical methods alone. In the end, the “modeling” approach favored by certain members of the “cybernetics group”—for example, McCulloch, Pitts, and Norbert Wiener—proved to be central to theory-based studies of the brain and its functioning during the second half of the twentieth century.