A Formal Computational Account of the Allostatic Theory of Oxytocin

Oxytocin's effects on human behaviour are inconsistent across studies, persisting despite improvements in methodological rigour. Part of this problem is theoretical: existing verbal accounts do not specify predictions precisely enough to be falsified. Here I formalise the Allostatic Theory of Oxytocin as a computational model, deriving eight testable propositions and evaluating each against simulation evidence. Three structural predictions that follow directly from the model's assumptions were confirmed. Of five genuinely discriminating tests, three were supported. The two unsupported propositions revealed boundary conditions the verbal theory could not identify. Formalisation underscored the importance of validating auxiliary assumptions regarding optimal oxytocin dosing and the measurement of baseline endogenous oxytocin levels, without which tests of the theory cannot be conclusively interpreted. Altogether, this formalisation provides a more precise and falsifiable account of oxytocin's role in behaviour than currently exists, and a template for incrementally refining verbal theories in psychology through formal specification.