Thomas W. Polger

The nature of explanation is an important area of inquiry in philosophy of science. Consensus has been that explanation in the cognitive and brain sciences is typically a special case of causal explanation, specifically, mechanistic explanation. But recently there has been increased attention to computational explanation in the brain sciences and to whether that can be understood as a variety of mechanistic explanation. After laying out the stakes for a proper understanding of scientific explanation, we consider the status of computational explanation in the brain sciences by comparing the mechanistic proposal to computational accounts advanced by Piccinini, Milkowski, Cao, Chirimuuta and Ross. We argue that many of these accounts of computational explanation in neuroscience can satisfy the same explanatory criteria as causal explanations, but not all. This has implications for interpretation of those computational explanations that satisfy different criteria.

The nature of explanation is an important area of inquiry in philosophy of science. Consensus has been that explanation in the cognitive and brain sciences is typically a special case of causal explanation, specifically, mechanistic explanation (Craver 2007). But recently there has been increased attention to computational explanation in the brain sciences, and to whether that can be understood as a variety of mechanistic explanation. After laying out the stakes for a proper understanding of scientific explanation, we consider the status of computational explanation in the brain sciences by comparing the mechanistic proposal to computational accounts advanced by Piccinini (2015), Milkowski (2013)), Cao (2019), Chirimuuta (2014, 2018), and Ross (Ross 2015, 2023). We argue that many of these accounts of computational explanation in neuroscience can satisfy the same explanatory criteria as causal explanations, but not all. This has implications for interpretation of those computational explanations that satisfy different criteria.

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.

A common view is that the truth of multiple realization—e.g., about psychological states—entails the truth of functionalism. This is supposed to follow because what is multiply realized iseo ipsorealized. I argue that view is mistaken by demonstrating how it misrepresents arguments from multiple realization. In particular, it undermines the empirical component of the arguments, and renders the multiplicity of the realization irrelevant. I suggest an alternative reading of multiple realizability arguments, particularly in philosophy of psychology. And I explain the proper way to understand the relation between realization and multiple realization.

This chapter compares and evaluates two theories of qualitative states that is, states that have a proprietary phenomenological dimension. The first theory is known as type materialism or the central state identity theory. The second theory is representationalism. The most compelling virtue of the central state theory is that it can do justice to the fact that qualitative phenomena appear to be perfectly correlated with cortical phenomena. According to the central state identity theory, all awareness of qualitative states takes the form of judgments and therefore necessarily involves conceptualization. The main virtue of representationalism is its account of qualitative awareness. This chapter focuses on the apparent virtues of the two theories with respect to each whether it in fact confers a decisive advantage on the theory that possesses it. It also focuses on paradigmatic qualitative state pain and considers additional examples on future occasions.