Literature DB >> 21268671

Puddles, parties, and professors: linking word categorization to neural patterns of visuospatial coding.

Susanne Quadflieg1, Joset A Etzel, Valeria Gazzola, Christian Keysers, Thomas W Schubert, Gordon D Waiter, C Neil Macrae.   

Abstract

Behavioral evidence suggests that during word processing people spontaneously map object, valence, and power information to locations in vertical space. Specifically, whereas "overhead" (e.g., attic), positive (e.g., party), and powerful nouns (e.g., professor) are associated with "up," "underfoot" (e.g., carpet), negative (e.g., accident), and powerless nouns (e.g., assistant) are associated with "down." What has yet to be elucidated, however, is the precise nature of these effects. To explore this issue, an fMRI experiment was undertaken, during which participants were required to categorize the position in which geometrical shapes appeared on a computer screen (i.e., upper or lower part of the display). In addition, they also judged a series of words with regard to location (i.e., up vs. down), valence (i.e., good vs. bad), and power (i.e., powerful vs. powerless). Using multivoxel pattern analysis, it was found that classifiers that successfully distinguished between the positions of shapes in subregions of the inferior parietal lobe also provided discriminatory information to separate location and valence, but not power word judgments. Correlational analyses further revealed that, for location words, pattern transfer was more successful the stronger was participants' propensity to use visual imagery. These findings indicate that visual coding and conceptual processing can elicit common representations of verticality but that divergent mechanisms may support the reported effects.

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Year:  2011        PMID: 21268671     DOI: 10.1162/jocn.2011.21628

Source DB:  PubMed          Journal:  J Cogn Neurosci        ISSN: 0898-929X            Impact factor:   3.225


  10 in total

1.  Vertical metaphor with motion and judgment: a valenced congruency effect with fluency.

Authors:  Sébastien Freddi; Joël Cretenet; Vincent Dru
Journal:  Psychol Res       Date:  2014-09

2.  Multivariate pattern analysis reveals common neural patterns across individuals during touch observation.

Authors:  Jonas T Kaplan; Kaspar Meyer
Journal:  Neuroimage       Date:  2011-12-30       Impact factor: 6.556

3.  No semantic information is necessary to evoke general neural signatures of face familiarity: evidence from cross-experiment classification.

Authors:  Alexia Dalski; Gyula Kovács; Géza Gergely Ambrus
Journal:  Brain Struct Funct       Date:  2022-10-16       Impact factor: 3.748

4.  Searchlight analysis: promise, pitfalls, and potential.

Authors:  Joset A Etzel; Jeffrey M Zacks; Todd S Braver
Journal:  Neuroimage       Date:  2013-04-01       Impact factor: 6.556

5.  A common cortical metric for spatial, temporal, and social distance.

Authors:  Carolyn Parkinson; Shari Liu; Thalia Wheatley
Journal:  J Neurosci       Date:  2014-01-29       Impact factor: 6.167

6.  Development of visual category selectivity in ventral visual cortex does not require visual experience.

Authors:  Job van den Hurk; Marc Van Baelen; Hans P Op de Beeck
Journal:  Proc Natl Acad Sci U S A       Date:  2017-05-15       Impact factor: 11.205

7.  On the ups and downs of emotion: testing between conceptual-metaphor and polarity accounts of emotional valence-spatial location interactions.

Authors:  Dermot Lynott; Kenny Coventry
Journal:  Psychon Bull Rev       Date:  2014-02

Review 8.  Multivariate cross-classification: applying machine learning techniques to characterize abstraction in neural representations.

Authors:  Jonas T Kaplan; Kingson Man; Steven G Greening
Journal:  Front Hum Neurosci       Date:  2015-03-25       Impact factor: 3.169

9.  Old cortex, new contexts: re-purposing spatial perception for social cognition.

Authors:  Carolyn Parkinson; Thalia Wheatley
Journal:  Front Hum Neurosci       Date:  2013-10-08       Impact factor: 3.169

10.  Action Observation Areas Represent Intentions From Subtle Kinematic Features.

Authors:  Atesh Koul; Andrea Cavallo; Franco Cauda; Tommaso Costa; Matteo Diano; Massimiliano Pontil; Cristina Becchio
Journal:  Cereb Cortex       Date:  2018-07-01       Impact factor: 5.357

  10 in total

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