Sleep is phenomenologically rich, teeming with different kinds of conscious thought and experience. Dreaming is the most prominent example, but there is more to conscious experience in sleep than dreaming. Especially in non‐rapid eye movement sleep, conscious experience, sometimes dreamful, sometimes dreamless, also alternates with a loss of consciousness. Yet while dreaming has become established as a topic for interdisciplinary consciousness science and empirically informed philosophy of mind, the same is not true of other kinds of sleep‐related experience, nor is (...) it true of sleep itself. I argue that this is a mistake. Conscious experience in sleep is more diverse than dreaming and we need to explain its different forms as well as the alternation between conscious and unconscious sleep states. We also need to ask how different kinds of sleep‐related experience relate to foundational issues about sleep and wakefulness as well as sleep stages. I survey recent findings and theoretical developments from sleep and dream research to show how the traditional view of sleep and its relation to wakefulness and consciousness is flawed. I then suggest that by refining our frameworks of sleep‐related experiences and sleep staging in tandem, we can work toward a better view. As we are only beginning to understand the diversity of consciousness in sleep, an important aim is programmatic: We need a philosophy of sleep and of consciousness in sleep, not just a philosophy of dreaming, and a future theory of sleep needs to integrate phenomenological considerations with neuroscientific and behavioral evidence. Working toward such a theory will radically transform our understanding of sleep, wakefulness, and our conscious minds. (shrink)

In a recent paper, Cheng and Werning (2016) argue that the class of episodic memories constitutes a natural kind. Endorsing the homeostatic property cluster view of natural kinds, they suggest that episodic memories can be characterized by a cluster of properties unified by an underlying neural mechanism for coding sequences of events. Here, I argue that Cheng & Werning’s proposal faces some significant, and potentially insurmountable, difficulties. Two are described as most prominent. First, the proposal fails to satisfy an important (...) normative constraint on natural kind theorizing, not providing the requisite theoretical resources for arbitration between rival taxonomies of memory. Second, the proposal is in a direct tension with a foundational principle of the HPC view: the rejection of essentialism. This has far-reaching consequences, threatening to undermine the coherence of the proposal. (shrink)

In response to points raised by our critics in this book symposium, we offer some clarifications about how to understand the role of science in assessing the multiple realization thesis. We also consider the connection between functionalism and multiple realization in the contexts of both psychological and biological sciences.

We provide two programmatic frameworks for integrating philosophical research on understanding with complementary work in computer science, psychology, and neuroscience. First, philosophical theories of understanding have consequences about how agents should reason if they are to understand that can then be evaluated empirically by their concordance with findings in scientific studies of reasoning. Second, these studies use a multitude of explanations, and a philosophical theory of understanding is well suited to integrating these explanations in illuminating ways.

The central task of cognitive neuroscience to map cognitive capacities to neural mechanisms faces three interlocking conceptual problems that together frame the problem of cognitive ontology. First, they must establish which tasks elicit which cognitive capacities, and specifically when different tasks elicit the same capacity. To address this operationalization problem, scientists often assess whether the tasks engage the same neural mechanisms. But to determine whether mechanisms are of the same or different kinds, we need to solve the abstraction problem by (...) determining which mechanistic differences are and are not relevant, and also the boundary problem by distinguishing the mechanism from its background conditions. Solving these problems, in turn, requires understanding how cognitive capacities are elicited in tasks. These three problems, which have been noted and discussed elsewhere in the literature, together form a ‘cycle of kinds’ that frames the central problem-space of cognitive ontology. We describe this cycle to clarify the intellectual challenges facing the cognitive ontologist and to reveal the kind of iterative process by which ontological revision in cognitive neuroscience is likely to unfold. (shrink)

The aim of the article is to outline several valuable elements of Mead’s pragmatist theory of perception in action developed in his The Philosophy of the Act, in order to strengthen the pragmatist legacy of the enactivist approach. In particular, Mead’s theory of perception in action turns out to be a forerunner of sensorimotor enactivist theory. Unlike the latter, however, Mead explicitly refers to imagery as an essential capacity for agency. Nonetheless, the article argues that the ways in which Mead (...) refers to this capacity do not necessarily place it in opposition to enactivist non-representationalism. On the contrary, as a synthetic process of re-presenting of present and past sensorimotor elements, imagery can be seen as the hallmark of a pragmatically inspired sensorimotor enactivist approach that bypasses the opposition between representationalists and non-representationalists. (shrink)

Cognitive ontology has become a popular topic in philosophy, cognitive psychology, and cognitive neuroscience. At its center is the question of which cognitive capacities should be included in the ontology of cognitive psychology and cognitive neuroscience. One common strategy for answering this question is to look at brain structures and determine the cognitive capacities for which they are responsible. Some authors interpret this strategy as a search for neural mechanisms, as understood by the so-called new mechanistic approach. In this article, (...) I will show that this new mechanistic answer is confronted with what I call the triviality problem. A discussion of this problem will show that one cannot derive a meaningful cognitive ontology from neural mechanisms alone. Nonetheless, neural mechanisms play a crucial role in the discovery of a cognitive ontology because they are epistemic proxies for best systematizations. (shrink)