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Not so rational: A more natural way to understand the ANS

Published online by Cambridge University Press:  15 December 2021

Eli Hecht
Affiliation:
Program in Cognitive Science, Dartmouth College, Hanover, NH 03755, USA. Eli.C.Hecht.23@dartmouth.edu Tracey.E.Mills.22@dartmouth.edu Steven.M.Shin.23@dartmouth.edu Jonathan.S.Phillips@dartmouth.edu http://phillab.host.dartmouth.edu/
Tracey Mills
Affiliation:
Program in Cognitive Science, Dartmouth College, Hanover, NH 03755, USA. Eli.C.Hecht.23@dartmouth.edu Tracey.E.Mills.22@dartmouth.edu Steven.M.Shin.23@dartmouth.edu Jonathan.S.Phillips@dartmouth.edu http://phillab.host.dartmouth.edu/
Steven Shin
Affiliation:
Program in Cognitive Science, Dartmouth College, Hanover, NH 03755, USA. Eli.C.Hecht.23@dartmouth.edu Tracey.E.Mills.22@dartmouth.edu Steven.M.Shin.23@dartmouth.edu Jonathan.S.Phillips@dartmouth.edu http://phillab.host.dartmouth.edu/
Jonathan Phillips
Affiliation:
Program in Cognitive Science, Dartmouth College, Hanover, NH 03755, USA. Eli.C.Hecht.23@dartmouth.edu Tracey.E.Mills.22@dartmouth.edu Steven.M.Shin.23@dartmouth.edu Jonathan.S.Phillips@dartmouth.edu http://phillab.host.dartmouth.edu/

Abstract

In contrast to Clarke and Beck's claim that that the approximate number system (ANS) represents rational numbers, we argue for a more modest alternative: The ANS represents natural numbers, and there are separate, non-numeric processes that can be used to represent ratios across a wide range of domains, including natural numbers.

Information

Type
Open Peer Commentary
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press