James insisted on the existence and importance of consciousness and, unlike so many explorers in the new field of psychology, he resisted any idea of the unconscious or of intelligent automatisms, like “unconscious cerebration.” But his “stream of consciousness” included not only definite images, but also the “free water of consciousness” that flows around them, which he would call a “halo,” “penumbra,” or most often, a “fringe.” This was the elusive, transitory territory of “the vague” and evanescent, the peripheral and unarticulated, of feelings, recognitions, meaningfulness. Not unconscious, but on the margin, it provided the necessary context for the focus of attention. This essay extends James’s conception (more fully than he did) to aesthetic experience, which is also nondiscursive, unarticulable, ineffable – but not unconscious. And it draws James’s “fringe” into the twenty-first century by nudging it toward the nonconscious cognitive processing that has captured the interest of so much contemporary psychology.

In this introductory chapter, I will outline what this book is about and aims to achieve, which is to continue what I started in a prequel book, A Mind for Language: An Introduction to the Innateness Debate (ML). Both books share the same central theme, namely the so-called Innateness Hypothesis for language, which is the conjecture proposed by the linguist Noam Chomsky many decades ago that children acquire language guided by an innate, genetically based mental system that is specifically dedicated to this task. Both ML and this book critically examine the arguments that have been used, or could be used, to support this idea. Where ML considered arguments coming from linguistics proper, the present book delves into arguments from neighboring fields that overlap with linguistics in various ways, including cognitive science and neurolinguistics. The chapter concludes with a review of the linguistic arguments in support of Chomsky’s innateness hypothesis that formed the focus of ML.

Legal outcomes often depend on whether conduct is reasonable. But how do we judge what is reasonable? What are the relevant criteria? Legal theorists have long debated these questions. This chapter outlines some of the leading theories. It then describes recent experimental work probing whether those theories align with lay judgments of what is reasonable. The findings indicate that reasonableness is best understood as a hybrid concept – a product of multiple inputs. Working from this perspective, the chapter raises important additional questions about reasonableness – questions that experimental jurisprudence is well suited to explore.

This final chapter returns to the issues that the cognitive neuroscience of autoscopy raise for the philosophy of mind. The neuroscience project is to develop a detailed understanding and explanation of the relation between the physical and mental. I appeal to the works of Paul Schilder, Antonio Damasio, and Mohed Constandi to forge a tentative way of understanding how multiple perceptual modalities such as proprioception, vision, touch, and somatic perception are integrated to form a unified sense of the self and the body.

In this chapter, the remit of theoretical linguistics is located within the background of a set of theoretical questions. These questions pertain to issues of ontology, methodology, acquisition, communication, and evolution. The overarching field is distinguished from other pursuits within applied linguistics that have a more practical focus but are argued to subsume certain experimental approaches. The first part of the chapter discusses the role of grammaticality and formal grammars in linguistic theory. Here, the issue of whether the rules of language have normative force is introduced as well as whether the target of scientific linguistics is individual languages or some universal core of human language generally. The question of what a grammar is, a theory, model, or some other device, is presented based on a brief literature review on the topic with a nudge towards a certain scientific instrumentalism about these matters. Next, the chapter asks whether linguistics is best viewed as an empirical social or cognitive science. Arguments are presented on both sides. Naturalism and normativity figure prominently in this debate. Finally, an outline of each chapter of the book is provided with an aim to either precisify or reflect on the philosophical issues presented in this opening chapter.

This introductory chapter delves into the inception of developmental cognitive neuroscience, a field shaped by historical inquiries into brain development, childhood learning, and the nature–nurture debate. We trace the origins of this interdisciplinary endeavor, revealing how it has emerged as a pioneering approach to comprehending human development. In this chapter, we dissect the core components of developmental cognitive neuroscience: development, cognition, and neuroscience. We elucidate their interconnectedness, underpinning theories, and evolving methodologies, spotlighting the transformative impact of recent technological strides. Throughout the book, our emphasis remains on the synthesis of these elements, illustrating their collective role in advancing our comprehension of human development. This chapter establishes the groundwork for an engaging exploration of the intricate interplay between brain maturation, cognitive processes, and the unfolding of human potential.

This chapter provides an introduction and an overview of computational cognitive sciences. Computational cognitive sciences explore the essence of cognition and various cognitive functionalities through developing mechanistic, process-based understanding by specifying corresponding computational models. These models impute computational processes onto cognitive functions and thereby produce runnable programs. Detailed simulations and other operations can then be conducted. Understanding the human mind strictly from observations of, and experiments with, human behavior is ultimately untenable. Computational modeling is therefore both useful and necessary. Computational cognitive models are theoretically important because they represent detailed cognitive theories in a unique, indispensable way. Computational cognitive modeling has thus far deepened the understanding of the processes and the mechanisms of the mind in a variety of ways.