Online research in philosophy

Evolutionary Psychology is based on the idea that the mind is a set of special purpose thinking devices or modules whose domain-specific structure is an adaptation to ancestral environments. The modular view of the mind is an uncontroversial description of the periphery of the mind, the input-output sensorimotor and affective subsystems. The novelty of EP is the claim that higher order cognitive processes also exhibit a modular structure. Autism is a primary case study here, interpreted as a developmental failure of a module devoted to social intelligence or Theory of Mind. In this article I reappraise the arguments for innate modularity of TOM and argue that they fail. TOM ability is a consequence of domain general development scaffolded by early, innately specified, sensorimotor abilities. The alleged Modularity of TOM results from interpreting the outcome of developmental failures characteristic of autism at too high a level of cognitive abstraction.

A variety of inaccurate claims about Gold's Theorem have appeared in the cognitive science literature. I begin by characterizing the logic of this theorem and its proof. I then examine several claims about Gold's Theorem, and I show why they are false. Finally, I assess the significance of Gold's Theorem for cognitive science.

The theory of mind (ToM) deficit associated with autism spectrum disorder has been a central topic in the debate about the modularity of the mind. In a series of papers, Philip Gerrans and Valerie Stone argue that positing a ToM module does not best explain the deficits exhibited by individuals with autism (Gerrans 2002; Stone & Gerrans 2006a, 2006b; Gerrans & Stone 2008). In this paper, I first criticize Gerrans and Stone’s (2008) account. Second, I discuss various studies of individuals with autism and argue that they are best explained by positing a higher-level, domain-specific ToM module.

Gold & Stoljar's “trivial” neuron doctrine is neither a truism in cognitive science nor trivial; it has serious consequences for the future direction of the mind/brain sciences. Not everyone would agree that these consequences are desirable. The authors' “radical” doctrine is not so radical; their division between cognitive neuroscience and neurobiology is largely artificial. Indeed, there is no sharp distinction between cognitive neuroscience and other areas of the brain sciences.

Explanatory problems in the philosophy of neuroscience are not well captured by the division between the radical and the trivial neuron doctrines. The actual problem is, instead, whether mechanistic biological explanations across different levels of description can be extended to account for psychological phenomena. According to cognitive neuroscience, some neural levels of description at least are essential for the explanation of psychological phenomena, whereas, in traditional cognitive science, psychological explanations are completely independent of the neural levels of description. The challenge for cognitive neuroscience is to discover the levels of description appropriate for the neural explanation of psychological phenomena.

According to some philosophers, computational explanation is proprietary
to psychology—it does not belong in neuroscience. But neuroscientists routinely offer computational explanations of cognitive phenomena. In fact, computational explanation was initially imported from computability theory into the science of mind by neuroscientists, who justified this move on neurophysiological grounds. Establishing the legitimacy and importance of computational explanation in neuroscience is one thing; shedding light on it is another. I raise some philosophical questions pertaining to computational explanation and outline some promising answers that are being developed by a number of authors.