I respond to an objection recently formulated by Barlassina and Hayward against first-order imperativism about pain, according to which it cannot account for the self-directed motivational force of pain. I am going to agree with them: it cannot. This is because pain does not have self-directed motivational force. I will argue that the alternative view—that pain is about dealing with extramental, bodily threats, not about dealing with itself—makes better sense of introspection, and of empirical research on pain avoidance. Also, a naturalistic theory of body-involving commands falls straightforwardly out of our most prominent naturalistic metasemantic accounts, while the token-reflexive contents that would underlie self-directed motivation are more problematic.

Recent research on bacteria and other microorganisms has provided interesting insights into the nature of life, cooperation, evolution, individuality or species. In this paper, I focus on the capacity of bacteria to produce molecules that are usually classifed as ‘signals’ and I defend two claims. First, I argue that certain interactions between bacteria should actually qualify as genuine forms of communication. Second, I use this case study to revise our general theories of signaling. Among other things, I argue that a plausible requirement for a state to qualify as a signal is that it is a minimal cause.

We explore the contribution made by oscillatory, synchronous neural activity to representation in the brain. We closely examine six prominent examples of brain function in which neural oscillations play a central role, and identify two levels of involvement that these oscillations take in the emergence of representations: enabling (when oscillations help to establish a communication channel between sender and receiver, or are causally involved in triggering a representation) and properly representational (when oscillations are a constitutive part of the representation). We show that even an idealized informational sender-receiver account of representation makes the representational status of oscillations a non-trivial matter, which depends on rather minute empirical details.

What are emotions? Will a machine ever be able to experience emotions? What role do emotions play in our mental life? What is the relationship between emotions and reason? These are just some of the major concerns about emotions, among many others, that will be addressed in this book.

While scientific inquiry crucially relies on the extraction of patterns from data, we still have a far from perfect understanding of the metaphysics of patterns—and, in particular, of what makes a pattern real. In this paper we derive a criterion of real-patternhood from the notion of conditional Kolmogorov complexity. The resulting account belongs to the philosophical tradition, initiated by Dennett (1991), that links real-patternhood to data compressibility, but is simpler and formally more perspicuous than other proposals previously defended in the literature. It also successfully enforces a non-redundancy principle, suggested by Ladyman and Ross (2007), that aims to exclude from real-patternhood those patterns that can be ignored without loss of information about the target dataset, and which their own account fails to enforce.