Deacon’s target article is a welcome contribution not only on “biological information” but, more generally, on representation in cognitive science. Some kind of explanation and justification for use of the terms “representation” and “interpretant” for primordial autogen system would be helpful. A connection between the notions of “information” and “representation” can be elaborated more in this respect.

This paper proposes an account of neurocognitive activity without leveraging the notion of neural representation. Neural representation is a concept that results from assuming that the properties of the models used in computational cognitive neuroscience must literally exist the system being modelled. Computational models are important tools to test a theory about how the collected data has been generated. While the usefulness of computational models is unquestionable, it does not follow that neurocognitive activity should literally entail the properties construed in (...) the model. While this is an assumption present in computationalist accounts, it is not held across the board in neuroscience. In the last section, the paper offers a dynamical account of neurocognitive activity with Dynamical Causal Modelling that combines dynamical systems theory mathematical formalisms with the theoretical contextualisation provided by Embodied and Enactive Cognitive Science. (shrink)

Philosophers interested in the theoretical consequences of predictive processing often assume that predictive processing is an inferentialist and representationalist theory of cognition. More specifically, they assume that predictive processing revolves around approximated Bayesian inferences drawn by inverting a generative model. Generative models, in turn, are said to be structural representations: representational vehicles that represent their targets by being structurally similar to them. Here, I challenge this assumption, claiming that, at present, it lacks an adequate justification. I examine the only argument (...) offered to establish that generative models are structural representations, and argue that it does not substantiate the desired conclusion. Having so done, I consider a number of alternative arguments aimed at showing that the relevant structural similarity obtains, and argue that all these arguments are unconvincing for a variety of reasons. I then conclude the paper by briefly highlighting three themes that might be relevant for further investigation on the matter. (shrink)

Minimal theory of mind is presented in the theory of mind literature as a middle ground between full-blown ToM and mere behavior-reading. Minimal ToM seems to be a useful construct for studying and understanding the minds of nonhuman animals and infants. However, providing an account of minimal ToM on which minimal mindreading is significantly less demanding than full-blown mindreading yet more than just a behavior-reading process is a challenge. In this paper, I argue that to address this challenge, we need (...) to depart from the traditional framework of mindreading in more radical ways than offered by current minimal theory of mind accounts. First, I explain the traditional view of mindreading on which mental state attribution is treated as essential for mindreading and analyze the general respects in which it makes mindreading demanding for the mindreader, such as requiring the mindreader to have concepts of mental states, engage in inferential reasoning processes involving mental states, and form meta-representations. Then I discuss and critically evaluate two accounts of minimal ToM and argue that these accounts either do not depart sufficiently from the demanding requirements of traditional mindreading or risk becoming re-descriptions of behavior-reading accounts. Finally, I present an alternative Millikanian account of minimal ToM that avoids this risk while departing more radically from the traditional view of mindreading by providing a way for minimal mindreaders to represent the mental states of others and respond to them without engaging in conceptual mental state attribution. (shrink)