David Barack

Foraging is a central competence of all mobile organisms. Models and concepts from foraging theory have been applied widely throughout biology to the search for many kinds of external resources, including food, sexual encounters, minerals, water, and the like. In cognitive science and neuroscience, the tools of foraging theory are increasingly applied to a wide range of other types of search, including for abstract resources like information or for internal resources like memories, concepts, and strategies for problem solving. Despite its importance in ecology and increasing relevance for the study of cognition, the concept of foraging is rarely analyzed. Here, I aim to rectify this situation. I outline three desiderata: first, an analysis should differentiate foraging from search and decision making more generally; second, an analysis should unify different types of foraging; and third, an analysis should help ground predictions. I present an analysis of foraging as the serial search for general resources in accept-or-reject, exclusive, persistent decision contexts. Not all search is serial and not all decision making is exclusive, differentiating foraging from search and decision making generally. With the aid of Markov decision processes and directed cyclical models, I show how the analysis implies a cyclical graph. This cyclical graph is embedded in the description of many types of foraging, unifying the different instances. Finally, I argue that the cyclical graph is also embedded in representations of novel task contexts that have not previously been viewed as foraging. I illustrate this novel application of the concept of foraging by arguing that reasoning is a type of foraging.

The dynamical hypothesis states that cognitive systems are dynamical systems. While dynamical systems play an important role in many cognitive phenomena, the dynamical hypothesis as stated applies to every system and so fails both to specify what makes cognitive systems distinct and to distinguish between proposals regarding the nature of cognitive systems. To avoid this problem, I distinguish several different types of dynamical systems, outlining four dimensions along which dynamical systems can vary: total-state versus partial-state, internal versus external, macroscopic versus microscopic, and systemic versus componential, and illustrate these with examples. I conclude with two illustrations of partial-state, internal, microscopic, componential dynamicism.

Dynamical systems play a central role in explanations in cognitive neuroscience. The grounds for these explanations are hotly debated and generally fall under two approaches: non-mechanistic and mechanistic. In this paper, I first outline a neurodynamical explanatory schema that highlights the role of dynamical systems in cognitive phenomena. I next explore the mechanistic status of such neurodynamical explanations. I argue that these explanations satisfy only some of the constraints on mechanistic explanation and should be considered pseudomechanistic explanations. I defend this argument against three alternative interpretations of the neurodynamical explanatory schema. The independent interpretation holds that neurodynamical explanations and mechanisms are independent. The constitutive interpretation holds that neurodynamical explanations are constitutive but otherwise non-mechanistic. Both the independent and constitutive interpretations fail to account for all the features of neurodynamical explanations. The partial interpretation assumes that the targets of dynamical systems models are mechanisms and so holds that neurodynamical explanations are incomplete because they lack mechanistic details. I contend instead that the targets of those models are dynamical systems distinct from mechanisms and defend this claim against several objections. I conclude with a defense of the pseudomechanistic interpretation and a discussion of the source of their explanatory power in relation to a causal-mechanical description of the world.

Theories in cognitive science, and especially cognitive neuroscience, often claim that parts of cognitive systems are reused for different cognitive functions. Philosophical analysis of this concept, however, is rare. Here, I first provide a set of criteria for an analysis of reuse, and then I analyse reuse in terms of the functions of subsystems. I also discuss how cognitive systems execute cognitive functions, the relation between learning and reuse, and how to differentiate reuse from related concepts like multi-use, redundancy, and duplication of parts. Finally, I illustrate how my account captures the reuse of dynamical subsystems as unveiled by recent research in cognitive neurobiology. This recent research suggests two different evolutionary justifications for reuse claims. _1_ Introduction _2_ Criteria for Analyses of Reuse _3_ Use and Reuse _4_ The Reuse of Dynamical Systems in Cognitive Systems _5_ Conclusion

Theories in cognitive science, and especially cognitive neuroscience, often claim that parts of cognitive systems are reused for different cognitive functions. Philosophical analysis of this concept, however, is rare. Here, I first provide a set of criteria for an analysis of reuse, and then I analyse reuse in terms of the functions of subsystems. I also discuss how cognitive systems execute cognitive functions, the relation between learning and reuse, and how to differentiate reuse from related concepts like multi-use, redundancy, and duplication of parts. Finally, I illustrate how my account captures the reuse of dynamical subsystems as unveiled by recent research in cognitive neurobiology. This recent research suggests two different evolutionary justifications for reuse claims.

Cognitive neuroscientists are turning to an increasingly rich array of neurodynamical systems to explain mental phenomena. In these explanations, cognitive capacities are decomposed into a set of functions, each of which is described mathematically, and then these descriptions are mapped on to corresponding mathematical descriptions of the dynamics of neural systems. In this paper, I outline a novel explanatory schema based on these explanations. I then argue that these explanations present a novel type of dynamicism for the philosophy of mind and neuroscience, componential dynamicism, that focuses on the parts of cognitive systems that fill certain functional roles in producing cognitive phenomena.