On the Rational Bounds of Cognitive Control

Abstract

One of the most defining features of cognitive control is our inability to exercise it. This motivates one of the most influential tenets of cognitive psychology: that cognitive control relies on a central, limited capacity processing mechanism that imposes constraints on (1) the number of control-dependent tasks that can be executed simultaneously and (2) the amount of cognitive control that can be allocated to a single task. This thesis provides a formally explicit challenge to this view. It draws on insights from neuroscience, psychology, and machine learning to suggest that the bounds of control-dependent processing reflect, at least in part, a rational adaptation to two fundamental computational dilemmas in neural network architectures. The first part of the thesis leverages graph-theoretic analysis, neural network simulation, and behavioral experimentation to demonstrate that neural architectures are subject to a tradeoff between learning efficacy, promoted through the use of shared task representations, on the one hand, and multitasking capability, achieved through the separation of task representations, on the other hand. These analyses suggest that limitations in multitasking capability may reflect a preference of the neural system to learn tasks more quickly. As a consequence, executing multiple control-demanding tasks may only occur in serial, through flexible switching between tasks. The serial execution of tasks, however, gives rise to another tradeoff known as the stability-flexibility dilemma: allocating more control to a task results in greater activation of its neural representation but also in greater persistence of this activity upon switching to a new task, yielding switch costs. The second part of this thesis demonstrates that constraints on the amount of cognitive control allocated to a single task can reflect an optimal solution to this dilemma. Finally, the third part of this thesis explores the implications of these limitations for human decision-making and examines the interaction between motivation and the capacity for cognitive control.