In their account of learning and behavior, the authors define an interactor as emitted behavior that operates on the environment, which excludes Pavlovian learning. A unified neural-network account of the operant-Pavlovian dichotomy favors interpreting neurons as interactors and synaptic efficacies as replicators. The latter interpretation implies that single-synapse change is inherently Lamarckian.

Behavior analysis emphasizes the study of overt animal (human and nonhuman) behavior as a subject matter in its own right. This paper provides a metaphysical foundation for such an emphasis via an elucidation of a thesis that I generically call "realism about behavior," where by "realism" I mean an assertion of mind-independent existence. The elucidation takes the form of a conceptual framework that combines a property-exemplification account of events with modal realism in the context of three opposing philosophies of mind: (...) property dualism, reductive physicalism, and type behaviorism. Each philosophy leads to the thesis that at least one possible world exists in which counterparts of all actual behavioral events occur and no counterpart of any actual "mental" (either nonphysical, neuro-mental, or behavioro-mental) event occurs. The third thesis is false because it violates the assumption that nothing can exist independently of itself, which leads to a rejection of type behaviorism. The other two theses provide the sought-after foundation through a counterfactual characterization of behavior qua behavior as a scientific subject matter. Its study thus becomes the study of behavior as if the nonphysical and the neural did not exist, even if they may factually exist and play a causal role in behavior. Some implications are discussed. (shrink)

Both the target article and the precommentary demonstrate that relatively simple biobehavioral processes have the cumulative effect of fostering behavioral outcomes characteristic of attention-deficit/hyperactivity disorder (ADHD). As such, the articles illustrate a central theme of Darwinian thinking – basic processes acting over time can produce complex and diverse outcomes. In this commentary, we indicate that tracing the action of processes over time can be facilitated by quantitative methods such as artificial neural networks.