Literature DB >> 29857048

Characterizing the neural coding of symbolic quantities.

Ian M Lyons1, Sian L Beilock2.   

Abstract

How the brain encodes abstract numerical symbols is a fundamental question in philosophy and cognitive neuroscience alike. Here we probe the nature of symbolic number representation in the brain by characterizing the neural similarity space for symbolic quantities in regions sensitive to their semantic content. In parietal and occipital regions, the similarity space of number symbols was positively predicted by the lexical frequency of numerals in parietal and occipital areas, and was unrelated to numerical ratio. These results are more consistent with a categorical, frequency-based account of symbolic quantity encoding. In contrast, the similarity space of analog quantities was positively predicted by ratio in prefrontal, parietal and occipital regions. We thus provide an explanation for why previous work has indicated that symbolic and analog quantities are distinct: number symbols operate primarily like discrete categories sensitive to input frequency, while analog quantities operate more like approximate perceptual magnitudes. In addition, we find substantial evidence for related patterns of activity across formats in prefrontal, parietal and occipital regions. Crucially however, between-format relations were not specific to individual quantities, indicating common processing as opposed to common representation. Moreover, evidence for between-format processing was strongest for quantities that could be represented as exact, discrete values in both systems (quantities in the 'subitizing' range: 1-4). In sum, converging evidence presented here indicates that symbolic quantities are coded in the brain as discrete categories sensitive to input frequency and largely independent of approximate, analog quantities.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Analog quantity; Associative structure; Cross-format; Neural similarity; Number symbols; Similarity space; Symbolic representation

Mesh:

Year:  2018        PMID: 29857048     DOI: 10.1016/j.neuroimage.2018.05.062

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  5 in total

1.  Shared and distinct neural circuitry for nonsymbolic and symbolic double-digit addition.

Authors:  Stephanie Bugden; Marty G Woldorff; Elizabeth M Brannon
Journal:  Hum Brain Mapp       Date:  2018-12-12       Impact factor: 5.038

2.  Shared Numerosity Representations Across Formats and Tasks Revealed with 7 Tesla fMRI: Decoding, Generalization, and Individual Differences in Behavior.

Authors:  Eric D Wilkey; Benjamin N Conrad; Darren J Yeo; Gavin R Price
Journal:  Cereb Cortex Commun       Date:  2020-07-30

3.  Neural representational similarity between symbolic and non-symbolic quantities predicts arithmetic skills in childhood but not adolescence.

Authors:  Flora Schwartz; Yuan Zhang; Hyesang Chang; Shelby Karraker; Julia Boram Kang; Vinod Menon
Journal:  Dev Sci       Date:  2021-06-01

4.  Processing symbolic magnitude information conveyed by number words and by scalar adjectives.

Authors:  Arnold R Kochari; Herbert Schriefers
Journal:  Q J Exp Psychol (Hove)       Date:  2021-07-16       Impact factor: 2.143

5.  Representation of visual numerosity information during working memory in humans: An fMRI decoding study.

Authors:  Ian Morgan Leo Pennock; Timo Torsten Schmidt; Dilara Zorbek; Felix Blankenburg
Journal:  Hum Brain Mapp       Date:  2021-03-11       Impact factor: 5.038

  5 in total

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