Cited by 198Language, Metaphor, and CognitionCategorization, perception, and languageVisual perception and processing mechanisms

The DOI matches its Crossref record; 61 of the 61 references it cites were found in a registry or an index; none of the 44 sources its claims cite is checked for support yet.

A Common Cortical Metric for Spatial, Temporal, and Social Distance

Open access
Parkinson, Carolyn, Liu, Shari, Wheatley, Thalia·2014·The Journal of Neuroscience

Abstract

Distance describes more than physical space: we speak of close friends and distant relatives, and of the near future and distant past. Did these ubiquitous spatial metaphors arise in language coincidentally or did they arise because they are rooted in a common neural computation? To address this question, we used statistical pattern recognition techniques to analyze human fMRI data. First, a machine learning algorithm was trained to discriminate patterns of fMRI responses based on relative egocentric distance within trials from one distance domain (e.g., photographs of objects relatively close to or far away from the viewer in spatial distance trials). Next, we tested whether the decision boundary generated from this training could distinguish brain responses according to relative egocentric distance within each of two separate distance domains (e.g., phrases referring to the immediate or more remote future within temporal distance trials; photographs of participants' friends or acquaintances within social distance trials). This procedure was repeated using all possible combinations of distance domains for training and testing the classifier. In all cases, above-chance decoding across distance domains was possible in the right inferior parietal lobule (IPL). Furthermore, the representational similarity structure within this brain area reflected participants' own judgments of spatial distance, temporal soon-ness, and social familiarity. Thus, the right IPL may contain a parsimonious encoding of proximity to self in spatial, temporal, and social frames of reference.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

Using fMRI and multivoxel pattern analysis, the paper reports that relative egocentric distance can be decoded across spatial, temporal, and social domains in right inferior parietal lobule (IPL), with representational similarity in this region tracking participants’ subjective distance ratings. The authors conclude that right IPL may contain a common cortical metric for proximity to self across these domains.

Key findings

  • Cross-domain distance decoding was above chance for all pairwise combinations of spatial, temporal, and social domains in right IPL; the largest cluster was 273 voxels in right IPL (AG/STG, BA 39/22), with average peak accuracy 62.33%, and a medial occipital cluster (200 voxels, BA 18) had average peak accuracy 66.12% (Table 1).
  • RSA showed that local neural similarity structure was significantly related to behavioral distance ratings in right IPL (113 voxels, BA 39/40), left SMA (BA 6), and right IFG (BA 47) (Table 2).
  • Postscan ratings were high for closer (6.21 ± 0.70), sooner (6.29 ± 0.82), and more familiar (6.52 ± 0.62) trials on a 1–7 scale, with no significant difference across domains (F(2,22) = 1.94, p = 0.17); probe response accuracy during scanning was 97.97 ± 1.34%.
  • Univariate analyses found no voxels surviving FDR-corrected p < 0.05 for sooner vs later, closer vs farther, or more familiar vs less familiar trials; even at p < 0.01 uncorrected, no regions emerged in the conjunction analysis, suggesting distributed patterns rather than average magnitude carried the cross-domain distance information.

Methods

  • Fifteen participants (10 females; aged 20–28 years; mean age 24.6 years) were scanned at 3 T during a slow event-related fMRI paradigm with spatial object photographs, temporal phrases, and social names/photographs; there were 96 unique trials, 8 runs, 36 trials per run, and six trial types. Twelve participants completed the postscan distance-rating questionnaire.
  • MVPA used searchlights (radius 3 voxels) with a linear SVM trained to discriminate relative distance within one domain and tested on another, repeated for all pairwise domain combinations; accuracy maps were arcsine transformed, tested against chance across participants, and submitted to a conjunction analysis at p < 0.05 FDR corrected.
  • RSA compared neural representational dissimilarity matrices (Pearson correlation distances between local multivoxel patterns) with behavioral RDMs (Euclidean distances between postscan ratings) using Spearman’s rank coefficient and permutation testing with 1000 shuffles; conventional univariate GLM paired t tests were also run.

Limitations

  • The paper states that its evolutionary “recycling” interpretation provides “preliminary support” and calls for future studies; it does not present a formal limitations section.
  • Evident from the text: the sample was modest (n = 15, with only 12 completing postscan ratings), cross-domain decoding accuracies were modest (roughly 60–66% versus 50% chance), and the univariate analyses found no significant effects, so the main conclusions rest on MVPA and RSA.
  • Evident from the text: temporal distance stimuli could in principle be compared by duration without self-reference, although the authors argue this would often produce incorrect cross-domain classifications.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1523/jneurosci.2159-13.2014

Cites

61 of 61 references verified0 citation errors · 0 not checkable

Statistics

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Verification

Claims the paper makes

32 Not checked yet · 18 Own interpretation · 18 Own result · 14 Own method · 1 No basis given

Verify all 44 references — free account

Show all 48 claims

  • It may state two separate claims as one. 13
  • Probably not a substantial claim. 24
35 of 35
  • The paper relies on this without support.

    The spatial, temporal, and social distance stimuli validly operationalize egocentric distance in their respective domains.

    “To make distances meaningfully comparable across domains, participants were asked to compare each stimulus with a reference point or anchor from the same distance domain.”
  • The paper relies on this without support.

    Participants' postscan ratings of psychological distance accurately reflect their subjective psychological distance.

    “After scanning, 12 participants completed a paper-and-pencil questionnaire consisting of behavioral ratings of psychological distance between stimuli.”
  • The paper relies on this without support.

    The probe questions ensured that participants compared the anchor and target stimuli in terms of relative egocentric distance rather than other aspects of the stimuli.

    “a probe (e.g., “Later?”) that was intended to ensure that participants were comparing the anchor and target stimuli in the intended manner (i.e., in terms of relative egocentric distance and not other aspects of the stimuli).”
  • The paper relies on this without support.

    Postscan written questionnaire ratings reflect participants' perceived egocentric psychological distance during scanning.

    “Results of postscan written questionnaires confirmed that participants perceived stimuli pairs from trials in all domains to differ substantially in terms of relative egocentric psychological distance.”
    “After scanning, 12 participants rated each pair of stimuli seen in the scanner in terms of relative temporal soon-ness, social familiarity, and physical closeness on a 1-7 point scale.”
  • The paper relies on this without support.

    Cross-domain decoding accuracy above chance reflects a shared neural representation of relative egocentric distance rather than shared task or stimulus properties.

    “This suggests, at least at the current level of observation, using the current experimental paradigm, that the local distributed patterns, rather than average magnitude, of fMRI responses contain information that distinguishes between different relative egocentric distances across social, spatial, and temporal distance domains.”
    “In several clusters throughout the right IPL, a classifier trained to distinguish trials based on relative egocentric distance within any single domain could distinguish trials within any other domain according to distance above chance across participants.”
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Citations

Cites

Research works printed but not linked: 1

  1. Zar JH (1996) Biostatistical analysis (Prentice Hall, Upper Saddle River, NJ).

Cited by

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Metadata

Authors
Parkinson, C., Liu, S., & Wheatley, T.
Affiliations
Dartmouth College (US)
Venue
The Journal of Neuroscience
Published
2014-01-29
Volume
34
Issue
5
Pages
1979-1987
ISSN
  • 0270-6474 (ISSN-L)
  • 1529-2401
OpenAlex
W2056416465
Cited by
198
References
61
Citations by year
2026: 11 · 2025: 15 · 2024: 23 · 2023: 17 · 2022: 31 · 2021: 22 · 2020: 12 · 2019: 19 · 2018: 11 · 2017: 14 · 2016: 9 · 2015: 9 · 2014: 5
FWCI
17.11
Type
journal article
Language
en
Open access
Locations
  • Journal of Neuroscience (publishedVersion, cc-by-nc-sa)
  • Europe PMC (PubMed Central) (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • Dartmouth College
  • Natural Sciences and Engineering Research Council of Canada
Topics
  • Social Sciences › Linguistics and Language › Language, Metaphor, and Cognition
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Categorization, perception, and language
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
Keywords
spatial distance, temporal distance, social distance, egocentric distance, inferior parietal lobule, representational similarity, spatial metaphor, social familiarity
MeSH terms
Adult, Algorithms, Analysis of Variance, Artificial Intelligence, Brain Mapping, Cerebral Cortex, Female, Humans, Image Processing, Computer-Assisted, Judgment, Magnetic Resonance Imaging, Male, Oxygen, Surveys and Questionnaires, Reaction Time, Psychological Distance, Space Perception, Young Adult

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