This thesis contributes to a better conceptual understanding of how self-organized control works. I begin by analyzing the control problem and its solution space. I argue that the two prominent solutions offered by classical cognitive science (centralized control with rich commands, e.g., the Fodorian central systems) and embodied cognitive science (distributed control with simple commands, such as the subsumption architecture by Rodney Brooks) are merely two positions in a two-dimensional solution space. I outline two alternative positions: one is distributed control (...) with rich commands, defended by proponents of massive modularity hypothesis; the other is centralized control with simple commands. My goal is to develop a hybrid account that combines aspects of the second alternative position and that of the embodied cognitive science (i.e., centralized and distributed controls with simple commands). Before developing my account, I discuss the virtues and challenges of the first three. This discussion results in a set of criteria for successful neural control mechanisms. Then, I develop my account through analyzing neuroscientific models of decision-making and control with the theoretical lenses provided by formal decision and social choice theories. I contend that neural processes can be productively modeled as a collective of agents, and neural self-organization is analogous to democratic self-governance. In particular, I show that the basal ganglia, a set of subcortical structures, contribute to the production of coherent and intelligent behaviors through implementing “democratic" procedures. Unlike the Fodorian central system—which is a micro-managing “neural commander-in-chief”—the basal ganglia are a “central election commission.” They delegate control of habitual behaviors to other distributed control mechanisms. Yet, when novel problems arise, they engage and determine the result on the basis of simple information (the votes) from across the system with the principles of neurodemocracy, and control with simple commands of inhibition and disinhibition. By actively managing and taking advantage of the wisdom-of-the-crowd effect, these democratic processes enhance the intelligence and coherence of the mind’s final "collective" decisions. I end by defending this account from both philosophical and empirical criticisms and showing that it meets the criteria for successful solution. (shrink)

I give a defense of the Massive Modularity hypothesis: the view that the mind is composed of discrete, encapsulated, informationally isolated computational structures dedicated to particular problem domains. This view contrasts with Psychological Rationalism: the view that mental structures take the form of unencapsulated representational items, all available as inputs to one domain-general computational processor. I argue that although Psychological Rationalism is in principle able to overcome the `intractability objection', the view must borrow many features of a massively modular architecture (...) in order to do so, that although it can, in principle, overcome the `optimality objection', the way it does so does not correlate with the way we think, and that although it can, in principle, respond to the `argument from biology', it cannot do so without advancing an unrealistic and unsupported account of cognitive evolution. (shrink)

Is there a notion of domain specificity which affords genuine insight in the context of the highly modular mind, i.e. a mind which has not only input modules, but also central ‘conceptual’ modules? Our answer to this question is no. The main argument is simple enough: we lay out some constraints that a theoretically useful notion of domain specificity, in the context of the highly modular mind, would need to meet. We then survey a host of accounts of what domain (...) specificity is, based on the intuitive idea that a domain specific mechanism is restricted in the kind of information that it processes, and show that each fails at least one of those constraints. (shrink)

In the Philosophy of Cognitive Science, it is a common held view that the modularity hypothesis for cognitive mechanisms and the innateness hypothesis for mental contents are conceptually independent. In this paper I distinguish between substantial and deflationist modularity as well as between substantial and deflationist innatism, and I analyze whether the conceptual independence between substantial modularity and innatism holds. My conclusion will be that if what is taken into account are the essential properties of the substantial modules, i.e. domain (...) specificity and informational encapsulation, then it seems to be such independence. However, if what is taken into account is the function of the substantial modules, then it seems to be a conceptual connection from modularity to substantial innateness. (shrink)

Two prevailing accounts of the structure of the mind have been provided, respectively, by the Dual System Theory and by the Massive Modularity Hypothesis. It has been claimed, however, that they cannot both be true at the same time, i.e., that they are incompatible and, thus, that one of them must be abandoned. I will offer some arguments to challenge this claim. I will show that a plausible understanding of each theory makes it possible for them both to be true (...) at the same time. Moreover, I will argue that by appealing to each other they can offer a more complete and detailed account of the architecture of the mind. (shrink)

A fundamental task for any prospective cognitive architecture is information control: routing information to the relevant mechanisms to support a variety of tasks. Jerry Fodor has argued that the Massive Modularity Hypothesis cannot account for flexible information control due to its architectural commitments and its reliance on heuristic information processing. I argue instead that the real trouble lies in its commitment to nativism—recent massive modularity models, despite incorporating mechanisms for learning and self-organization, still cannot learn to control information flexibly enough. (...) After defending this position, I close the paper by discussing wider implications for control and cognitive architecture. (shrink)