Our understanding of communication and its evolution has advanced significantly through the study of simple models involving interacting senders and receivers of signals. Many theorists have thought that the resources of mathematical information theory are all that are needed to capture the meaning or content that is being communicated in these systems. However, the way theorists routinely talk about the models implicitly draws on a conception of content that is richer than bare informational content, especially in contexts where false content (...) is important. This article shows that this concept can be made precise by defining a notion of functional content that captures the degree to which different states of the world are involved in stabilizing senders’ and receivers’ use of a signal at equilibrium. A series of case studies is used to contrast functional content with informational content, and to illustrate the explanatory role and limitations of this definition of functional content. _1_ Introduction _2_ Modelling Framework _3_ Two Kinds of Content _3.1_ Informational content _3.2_ Functional content _4_ Cases _4.1_ Case 1: Simplest case _4.2_ Case 2: Partial pooling _4.3_ Case 3: Bottleneck _4.4_ Case 4: Partial common interest _4.5_ Case 5: Deception _4.6_ Case 6: A further problem arising from divergent interests _5_ Discussion Appendix. (shrink)

Researchers of language origins typically try to explain how compositional communication might evolve to bridge the gap between animal communication and natural language. However, as an explanatory target, compositionality has been shown to be problematic for a gradualist approach to the evolution of language. In this article, I suggest that reflexivity provides an apt and plausible alternative target that does not succumb to the problems that compositionality faces. I further explain how protoreflexivity, which depends on functional reference, gives rise to (...) complex communication systems via modular composition. (shrink)

Sceptics of informational terminology argue that by attributing content to signals, we fail to address nonhuman animal communication on its own terms. Primarily, we ignore that communication is sender driven: i.e. driven by the intrinsic physical properties of signals, themselves the result of selection pressures acting on signals to influence receivers in ways beneficial for senders. In contrast, information proponents argue that this ignores the degree to which communication is, in fact, receiver driven. The latter argue that an exclusive focus (...) on the intrinsic mechanical properties of signals cannot explain why receivers respond as they do. This is because receivers are not prisoners of sender influence. They possess response flexibility, and so we can only explain why receivers respond to signals as they do by positing that receivers ‘derive information’ from signals. I argue that, while basically true, this response flexibility can take one of two forms depending on the causal-explanatory role of information in understanding the response of the receiver: diachronic, on the one hand; and synchronic, on the other. In species with diachronic response flexibility only, information is derived by receivers from signals in a minimal sense. In such cases, information is an ultimate explanatory construct: one underpinned by historical facts at the population level. Alternatively, in species with synchronic response flexibility, information is derived by receivers from signals in a richer sense. Here, information is a proximate explanatory construct: one underpinned by cognitive-mechanistic facts at the level of the individual organism. Without recognising the different ways information can be derived from signals, and the different causal-explanatory roles information can play in understanding alternate kinds of receiver flexibility, proponents of information leave themselves open to the charge of anthropomorphising some signalling systems. (shrink)

The claims that “The brain processes information” or “Cognition is information processing” are accepted as truisms in cognitive science. However, it is unclear how to evaluate such claims absent a specification of “information” as it is used by neurocognitive theories. The aim of this article is, thus, to identify the key features of information that information-based neurocognitive theories posit. A systematic identification of these features can reveal the explanatory role that information plays in specific neurocognitive theories, and can, therefore, be (...) both theoretically and practically important. These features can be used, in turn, as desiderata against which candidate theories of information may be evaluated. After discussing some characteristics of explanation in cognitive science and their implications for “information”, three notions are briefly introduced: natural, sensory, and endogenous information. Subsequently, six desiderata are identified and defended based on cognitive scientific practices. The global workspace theory of consciousness is then used as a specific case study that arguably posits either five or six corresponding features of information. (shrink)

Although the definition of ‘signal’ has been controversial for some time within the life sciences, current approaches seem to be converging toward a common analysis. This powerful framework can satisfactorily accommodate many cases of signaling and captures some of its main features. This paper argues, however, that there is a central feature of signals that so far has been largely overlooked: its special causal role. More precisely, I argue that a distinctive feature of signals is that they are minimal causes. (...) I explain this notion, suggest some strategies for identifying its instances and defend its relevance by means of conceptual and empirical considerations. (shrink)

The idea that only complex brains can possess genuine representations is an important element in mainstream philosophical thinking. An alternative view, which I label ‘liberal representationalism’, holds that we should accept the existence of many more full-blown representations, from activity in retinal ganglion cells to the neural states produced by innate releasing mechanisms in cognitively unsophisticated organisms. A promising way of supporting liberal representationalism is to show it to be a consequence of our best naturalistic theories of representation. However, several (...) philosophers and scientists have recently argued against this strategy. In the paper I counter these objections in defense of liberal representationalism. (shrink)