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Publication details

Year: 2016

Pages: 1287-1321

Series: Synthese

Full citation:

William Bechtel, "Investigating neural representations", Synthese 193 (5), 2016, pp. 1287-1321.

Investigating neural representations

the tale of place cells

William Bechtel

pp. 1287-1321

in: Gualtiero Piccinini (ed), Neuroscience and its philosophy, Synthese 193 (5), 2016.

Abstract

While neuroscientists often characterize brain activity as representational, many philosophers have construed these accounts as just theorists’ glosses on the mechanism. Moreover, philosophical discussions commonly focus on finished accounts of explanation, not research in progress. I adopt a different perspective, considering how characterizations of neural activity as representational contributes to the development of mechanistic accounts, guiding the investigations neuroscientists pursue as they work from an initial proposal to a more detailed understanding of a mechanism. I develop one illustrative example involving research on the information-processing mechanisms mammals employ in navigating their environments. This research was galvanized by the discovery in the 1970s of place cells in the hippocampus. This discovery prompted research in what the activity of these cells represents and how place representations figure in navigation. It also led to the discovery of a host of other types of neurons—grid cells, head-direction cells, boundary cells—that carry other types of spatial information and interact with place cells in the mechanism underlying spatial navigation. As I will try to make clear, the research is explicitly devoted to identifying representations and determining how they are constructed and used in an information processing mechanism. Construals of neural activity as representations are not mere glosses but are characterizations to which neuroscientists are committed in the development of their explanatory accounts.

Publication details

Year: 2016

Pages: 1287-1321

Series: Synthese

Full citation:

William Bechtel, "Investigating neural representations", Synthese 193 (5), 2016, pp. 1287-1321.