Computational physical systems may exhibit indeterminacy of computation (IC). Their identified physical dynamics may not suffice to select a unique computational profile. We consider this phenomenon from the point of view of cognitive science and examine how computational profiles of cognitive systems are identified and justified in practice, in the light of IC. To that end, we look at the literature on the underdetermination of theory by evidence and argue that the same devices that can be successfully employed to confirm (...) physical hypotheses can also be used to rationally single out computational profiles, notwithstanding IC. (shrink)

How does neuronal activity give rise to cognitive capacities? To address this question, neuroscientists hypothesize about what neurons “represent,” “encode,” or “compute,” and test these hypotheses empirically. This process is similar to the assessment of hypotheses in other fields of science and as such is subject to the same limitations and difficulties that have been discussed at length by philosophers of science. In this paper, we highlight an additional difficulty in the process of empirical assessment of hypotheses that is unique (...) to the cognitive sciences. We argue that, unlike in other scientific fields, comparing hypotheses according to the extent to which they explain or predict empirical data can lead to absurd results. Other considerations, which are perhaps more subjective, must be taken into account. We focus on one such consideration, which is the purposeful function of the neurons as part of a biological system. We believe that progress in neuroscience critically depends on properly addressing this difficulty. (shrink)

A skeptical worry known as ‘the indeterminacy of computation’ animates much recent philosophical reflection on the computational identity of physical systems. On the one hand, computational explanation seems to require that physical computing systems fall under a single, unique computational description at a time. On the other, if a physical system falls under any computational description, it seems to fall under many simultaneously. Absent some principled reason to take just one of these descriptions in particular as relevant for computational explanation, (...) widespread failure of computational explanation would appear to follow. This paper advances a new solution to the indeterminacy of computation. Very roughly, I argue that the computational identity of a physical system is determinate relative to a contextually specified way of regarding that system computationally—known as a labelling scheme. When a system simultaneously implements multiple computations, it does so relative to different labelling schemes. But relative to a fixed labelling scheme, a physical system has a unique computational identity. I argue that this relativistic conception of computational identity vindicates computational explanation in the face of simultaneous implementation. (shrink)