{"title":"Symbol and Substrate: A Methodological Approach to Computation in Cognitive Science","authors":"","doi":"10.1007/s13164-023-00719-4","DOIUrl":null,"url":null,"abstract":"<h3>Abstract</h3> <p>Cognitive scientists use computational models to represent the results of their experimental work and to guide further research. Neither of these claims is particularly controversial, but the philosophical and evidentiary statuses of these models are hotly debated. To clarify the issues, I return to Newell and Simon’s 1972 exposition on the computational approach; they herald its ability to describe mental operations despite that the neuroscience of the time could not. Using work on visual imagery (cf. imagination) as a guide, I examine the extent to which this holds true today. Does contemporary neuroscience contain mechanisms capable of describing experimental results in imagery? I argue that it does not, first by exploring foundational achievements in imagery research then by showing that their neural basis cannot be specified. Newell and Simon’s methodological position accordingly stands, even 50 years later. Computational — as opposed to physiological — descriptions must be retained to characterize and study mental phenomena, even as we learn high-level details of their implementation via brain data.</p>","PeriodicalId":47055,"journal":{"name":"Review of Philosophy and Psychology","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Review of Philosophy and Psychology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s13164-023-00719-4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PSYCHOLOGY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Cognitive scientists use computational models to represent the results of their experimental work and to guide further research. Neither of these claims is particularly controversial, but the philosophical and evidentiary statuses of these models are hotly debated. To clarify the issues, I return to Newell and Simon’s 1972 exposition on the computational approach; they herald its ability to describe mental operations despite that the neuroscience of the time could not. Using work on visual imagery (cf. imagination) as a guide, I examine the extent to which this holds true today. Does contemporary neuroscience contain mechanisms capable of describing experimental results in imagery? I argue that it does not, first by exploring foundational achievements in imagery research then by showing that their neural basis cannot be specified. Newell and Simon’s methodological position accordingly stands, even 50 years later. Computational — as opposed to physiological — descriptions must be retained to characterize and study mental phenomena, even as we learn high-level details of their implementation via brain data.
期刊介绍:
The Review of Philosophy and Psychology is a peer-reviewed journal focusing on philosophical and foundational issues in cognitive science.
The aim of the journal is to provide a forum for discussion on topics of mutual interest to philosophers and psychologists and to foster interdisciplinary research at the crossroads of philosophy and the sciences of the mind, including the neural, behavioural and social sciences.
The journal publishes theoretical works grounded in empirical research as well as empirical articles on issues of philosophical relevance. It includes thematic issues featuring invited contributions from leading authors together with articles answering a call for papers.
The Review of Philosophy and Psychology is published quarterly and is hosted at the Jean Nicod Institute, a research centre of the French Centre National de la Recherche Scientifique. It was formerly published as the "European Review of Philosophy" by CSLI Publications, Stanford.