A common cortical metric for spatial, temporal, and social distance
Open accessAbstract
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.
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.
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Claims the paper makes
0 of 44 cited sources checked · 0 supported · 0 flagged
- Findingown data
In all cases, above-chance decoding across distance domains was possible in the right inferior parietal lobule (IPL).
“In all cases, above-chance decoding across distance domains was possible in the right inferior parietal lobule (IPL).”
Quote in the paperSubstantial claim- Rests on an assumption: The spatial, temporal, and social distance stimuli validly operationalize egocentric distance in their respective domains.
- Findingown data
The representational similarity structure within the right IPL reflected participants' own judgments of spatial distance, temporal soon-ness, and social familiarity.
“Furthermore, the representational similarity structure within this brain area reflected participants' own judgments of spatial distance, temporal soon-ness, and social familiarity.”
Quote in the paperSubstantial claim- Rests on an assumption: The spatial, temporal, and social distance stimuli validly operationalize egocentric distance in their respective domains.
- Rests on an assumption: Participants' postscan ratings of psychological distance accurately reflect their subjective psychological distance.
- Findingown data
Participants perceived stimuli pairs from trials in all domains to differ substantially in terms of relative egocentric psychological distance.
“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.”
Quote in the paperSubstantial claim- Rests on an assumption: Postscan written questionnaire ratings reflect participants' perceived egocentric psychological distance during scanning.
- Findingown data
Relative egocentric distance could be decoded across all possible pairwise combinations of distance domains in clusters (cluster size >10 voxels) presented in Table 1.
“Clusters (cluster size Ͼ10 voxels) in which relative egocentric distance could be decoded across all possible pairwise combinations of distance domains are presented in Table 1.”
Quote in the paperSubstantial claim - Findingown data
Representational content within a large cluster in the right IPL was significantly related to behavioral distance ratings.
“Representational content within a large cluster in the right IPL was significantly related to behavioral distance ratings, suggesting that population codes within searchlights centered in this area contain representations that reflect subjective perceptions of egocentric distance.”
- Also stated in: § Discussion · plain
“Additionally, the similarity structure of population codes in this region reflected subjective proximity ratings.”
Quote in the paperSubstantial claim - Also stated in: § Discussion · plain
- Findingown data
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.
“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.”
Quote in the paperSubstantial claim - Findingown data
Perceived relative psychological distance did not significantly differ across the three tested domains of psychological distance (F(2,22)=1.94, p=0.17, ηG2=0.09).
“A one-way ANOVA indicated that perceived relative psychological distance did not significantly differ across the three tested domains of psychological distance (F (2,22) ϭ 1.94, p ϭ 0.17, G 2 ϭ 0.09).”
Quote in the paperSubstantial claim- Rests on an assumption: Postscan written questionnaire ratings reflect participants' perceived egocentric psychological distance during scanning.
- Findingown data
All voxels in each of these clusters were associated with significantly above-chance classification across participants for each of the six group analyses (p < 0.05, FDR corrected, each test).
“All voxels in each of these clusters were associated with significantly abovechance classification across participants for each of the six group analyses ( p Ͻ 0.05, FDR corrected, each test).”
Quote in the paperSubstantial claim - Findingown data
Relative egocentric distance could be decoded across all distance domains above chance across participants in searchlight spheres centered on voxels in a large (273-voxel) cluster in the right inferior parietal lobule (IPL) extending into the posterior superior temporal gyrus (STG).
“Specifically, relative egocentric distance could be decoded across all distance domains above chance across participants in searchlight spheres centered on voxels in a large (273-voxel) cluster in the right inferior parietal lobule (IPL) extending into the posterior superior temporal gyrus (STG; Fig. 2D).”
Quote in the paperSubstantial claim - Findingown data
Distance ratings for stimulus pairs from each domain significantly differed from 1 (equally soon/close/familiar; all p values <0.00001).
“One-sample t tests indicated that distance ratings for stimulus pairs from each domain significantly differed from 1 (equally soon/close/familiar; all p values Ͻ0.00001).”
Quote in the paperSubstantial claim- Rests on an assumption: Postscan written questionnaire ratings reflect participants' perceived egocentric psychological distance during scanning.
- Findingown data
Even using a dramatically reduced voxelwise threshold of p < 0.01, uncorrected, for each test, no regions emerged as significant in the conjunction analysis.
“Even using a dramatically reduced voxelwise threshold of p Ͻ 0.01, uncorrected, for each test, no regions emerged as significant in the conjunction analysis, suggesting that no regions could distinguish distances in all three distance domains tested here in terms of average activity level.”
Quote in the paperSubstantial claim - Findingown data
Local neural similarity structure in smaller clusters within the right inferior frontal gyrus (IFG) and throughout the left supplementary motor area (SMA) were significantly related to the similarity structures evinced in participants' behavioral ratings of distance.
“As summarized in Table 2, the local neural similarity structure in smaller clusters within the right inferior frontal gyrus (IFG) and throughout the left supplementary motor area (SMA) were also significantly related to the similarity structures evinced in participants' behavioral ratings of distance, suggesting that information contained in local population codes within these regions may also be”
- Also stated in: § Discussion · plain
“Smaller clusters in which local information content reflected subjective distance ratings occurred in the left SMA and right IFG.”
Quote in the paperSubstantial claim - Also stated in: § Discussion · plain
- Findingown data
No voxels survived an FDR-corrected threshold of p < 0.05 in any of the three t tests comparing trials based on distance within each distance domain (sooner vs later; more familiar vs less familiar; closer vs farther).
“No voxels survived an FDR-corrected threshold of p Ͻ 0.05 in any of the three t tests comparing trials based on distance within each distance domain (i.e., sooner vs later; more familiar vs less familiar; closer vs farther).”
Quote in the paperSubstantial claim - Findingown data
Run accuracies ranged from 95.83 to 100% (mean ± SD, 97.97 ± 1.34%).
“Run accuracies ranged from 95.83 to 100% (mean Ϯ SD, 97.97 Ϯ 1.34%).”
Quote in the paperNot a substantial claim - Findingown data
The largest significant clusters in both classification and similarity analyses were in the right IPL.
“The largest significant clusters in both classification and similarity analyses were in the right IPL.”
Quote in the paperSubstantial claim - Interpretationown data
The right IPL may contain a parsimonious encoding of proximity to self in spatial, temporal, and social frames of reference.
“Thus, the right IPL may contain a parsimonious encoding of proximity to self in spatial, temporal, and social frames of reference.”
Quote in the paperSubstantial claim- Rests on an assumption: The spatial, temporal, and social distance stimuli validly operationalize egocentric distance in their respective domains.
- Rests on an assumption: Participants' postscan ratings of psychological distance accurately reflect their subjective psychological distance.
- Premisecitation
Different domains of psychological distance impact a range of mental phenomena similarly, from visual perception to humor and moral judgment.
“Different domains of psychological distance also impact a range of mental phenomena similarly, from visual perception (Fo ¨rster et al., 2004) to humor (McGraw et al., 2012) and moral judgment (Eyal et al., 2008).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Förster et al., 2004
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- cites McGraw et al., 2012
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- cites Eyal et al., 2008
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- Interpretationreasoning
Converging evidence is consistent with the possibility of a common mechanism for representing different domains of egocentric distance.
“Thus, converging evidence is consistent with the possibility of a common mechanism for representing different domains of egocentric distance.”
Quote in the paperSubstantial claim - Premisecitation
Converging theories from cognitive linguistics, cognitive neuroscience, and social psychology suggest that different domains of psychological distance are encoded similarly.
“Converging theories from cognitive linguistics, cognitive neuroscience, and social psychology suggest that different domains of psychological distance are encoded similarly.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Lakoff and Johnson, 1980
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- Premisecitation
The common meaning shared across psychological distance domains is accessed automatically.
“The common meaning shared across psychological distance domains is accessed automatically.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Bar-Anan et al., 2007
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- Premisecitation
The degree to which information is removed from current experience in time, space, or refers to someone else carries a common meaning with implications for proximity for action and construal level.
“The degree to which information is removed from our current experience in time, space, or the extent to which it refers to someone else carries a common meaning with important implications for the perceiver: proximity for action and, thus, how concretely or abstractly it should be construed (Vallacher and Wegner, 1985;Liberman and Trope, 2008).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Vallacher and Wegner, 1985
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- cites Liberman and Trope, 2008
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- Premisecitation
The capacity to mentally traverse different domains of distance follows a similar developmental trajectory.
“Additionally, the capacity to mentally traverse different domains of distance follows a similar developmental trajectory (Suddendorf and Corballis, 2007).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Suddendorf and Corballis, 2007
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- Study design and conductreasoning
Retinal subtense was approximately consistent across near and far spatial distance pictures.
“Retinal subtense was approximately consistent across near and far pictures, because stimuli were drawn from four image pairs that depicted similar objects of different sizes (e.g., circular breads: a mini pita and a pizza shell), with the larger and smaller objects photographed at distances of 300 and 50 cm, respectively.”
Quote in the paperSubstantial claim - Study design and conductreasoning
Because RDMs are generated separately for each participant, idiosyncratic differences in relative psychological distance ratings for each participant are preserved.
“Similarly, because RDMs are generated separately for each participant, idiosyncratic differences in relative psychological distance ratings for each participant are preserved.”
Quote in the paperSubstantial claim - Interpretationcitation
A common encoding cannot be inferred from independent univariate fMRI contrasts.
“Importantly, a common encoding cannot be inferred from independent univariate fMRI contrasts.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Peelen and Downing, 2007
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- Interpretationreasoning
Comparing stimuli in terms of magnitude without respect to distance from the self in the here and now would likely often result in erroneous predictions.
“However, comparing stimuli in terms of magnitude without respect to distance from the self in the here and now would likely often result in erroneous predictions.”
Quote in the paperSubstantial claim - Interpretationown data
No regions could distinguish distances in all three distance domains tested here in terms of average activity level.
“suggesting that no regions could distinguish distances in all three distance domains tested here in terms of average activity level.”
Quote in the paperSubstantial claim - Study design and conductown data
The frequencies of words used in immediate and remote future phrases did not significantly differ.
“The frequencies of words used in the immediate (median, 1,106,896) and remote (median, 718,023) future phrases did not significantly differ (W ϭ 116.5, p ϭ 0.61, r ϭ 0.09)”
Quote in the paperNot a substantial claim - Interpretationreasoning
RDMs provide a relatively information-rich summary of the information carried in behavioral and fMRI responses.
“Thus, RDMs provide a relatively information-rich summary of the information carried in behavioral and fMRI responses.”
Quote in the paperSubstantial claim - Interpretationreasoning
Constructing an RDM is a useful dimensionality reduction step, because the number of features in the original fMRI data far exceeds the number of unique elements in each RDM.
“At the same time, constructing an RDM is a useful dimensionality reduction step, because the number of features in the original fMRI data far exceeds the number of unique elements in each RDM.”
Quote in the paperNot a substantial claim - Interpretationown data
Response accuracies to probes during scanning were high, suggesting participants were able to attend to and compare the anchors and targets in the intended manner during scanning.
“Additionally, response accuracies to probes during scanning were high, suggesting that participants were able to attend to and compare the anchors and targets in the intended manner during scanning.”
Quote in the paperSubstantial claim - Study design and conductown data
Word counts in immediate and remote future phrases did not significantly differ.
“Wilcoxon's rank-sum tests (function wilcox.test in R; R Core Team, 2013) indicated that word counts in immediate (median, 3.50) and remote (median, 4.00) future phrases did not significantly differ (W ϭ 10, p ϭ 0.61, r ϭ 0.18).”
Quote in the paperNot a substantial claim - Interpretationown data
Information contained in local population codes within the right IFG and left SMA may also be related to judgments of relative egocentric social, spatial, and temporal distance.
“suggesting that information contained in local population codes within these regions may also be related to judgments of relative egocentric social, spatial, and temporal distance.”
Quote in the paperSubstantial claim - Premisecitation
When participants evaluated their opinions and enjoyment of activities in proximal or distal scenarios, fMRI response magnitudes in areas associated with mental simulation were influenced similarly by different distance domains.
“When participants evaluated their opinions and enjoyment of activities in proximal or distal scenarios, fMRI response magnitudes in areas associated with mental simulation were influenced similarly by different distance domains.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Tamir and Mitchell (2011)
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- Study design and conductown data
The frequencies of the exact immediate and remote future phrases used did not significantly differ.
“nor did the frequencies of the exact immediate (median, 102) and remote (median, 291.5) future phrases used (W ϭ 10, p ϭ 0.69, r ϭ 0.14).”
Quote in the paperNot a substantial claim - Interpretationcitation
MVPA can provide a more stringent test of whether common cortical mechanisms encode egocentric distance across domains, because overlapping univariate contrasts could result from a shared computational process or from overlapping but functionally independent population responses.
“Additionally, MVPA can provide a more stringent test of whether common cortical mechanisms encode egocentric distance across domains, because overlapping univariate contrasts could result from a shared computational process or from the elicitation of overlapping but functionally independent population responses (Peelen and Downing, 2007).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Peelen and Downing, 2007
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- Premisecitation
The spatial variability of response patterns can reveal information that distinguishes between experimental conditions, even in the absence of overall mean activation differences.
“The spatial variability of response patterns can reveal information that distinguishes between experimental conditions, even in the absence of overall mean activation differences (Peelen and Downing, 2007).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Peelen and Downing, 2007
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- Interpretationown data
The current results provide evidence for a parsimonious representation of this shared meaning in the brain.
“The current results provide evidence for a parsimonious representation of this shared meaning in the brain.”
Quote in the paperSubstantial claim - Interpretationreasoning
Compared with univariate analyses, MVPA can be more sensitive to differences between trial types within domains.
“Thus, compared with univariate analyses, MVPA can be more sensitive to differences between trial types within domains (e.g., closer vs farther trials).”
Quote in the paperSubstantial claim - Interpretationown data
At least at the current level of observation, using the current experimental paradigm, 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.
“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.”
Quote in the paperSubstantial claim- Rests on an assumption: Cross-domain decoding accuracy above chance reflects a shared neural representation of relative egocentric distance rather than shared task or stimulus properties.
- Interpretationreasoning
Cross-domain distance decoding based on distributed patterns of fMRI responses provides a useful means of testing whether response patterns within a given brain region similarly distinguish between relatively near and relatively far egocentric distances across distance domains.
“Thus, cross-domain distance decoding based on distributed patterns of fMRI responses provides a useful means of testing whether or not response patterns within a given brain region similarly distinguish between relatively near and relatively far egocentric distances across distance domains.”
Quote in the paperSubstantial claim - Interpretationcitation
It is possible to directly compare the informational content of fMRI and behavioral data by assessing correlations between RDMs generated from fMRI data and those generated from behavioral responses.
“Thus, it is possible to directly compare the informational content of fMRI and behavioral data by assessing correlations between RDMs generated from fMRI data and those generated from behavioral responses (Kriegeskorte et al., 2008).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Kriegeskorte et al., 2008
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- Interpretationown data
Population codes within searchlights centered in the right IPL contain representations that reflect subjective perceptions of egocentric distance.
“suggesting that population codes within searchlights centered in this area contain representations that reflect subjective perceptions of egocentric distance.”
Quote in the paperSubstantial claim - Interpretationown data
The human brain contains a parsimonious encoding of relative egocentric distance that generalizes to social, spatial, and temporal frames of reference.
“The current results suggest that the human brain contains a parsimonious encoding of relative egocentric distance that generalizes to social, spatial, and temporal frames of reference.”
Quote in the paperSubstantial claim - Premisecitation
Lesions to the RTPJ produce deficits in representing space and events along a mental time line.
“Lesions to this region produce deficits in representing space (Karnath and Rorden, 2012) and events along a mental time line (Saj et al., 2013).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Karnath and Rorden, 2012
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- cites Saj et al., 2013
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- Premisecitation
A third network, the frontoparietal control network (FPCN), including the RTPJ, flexibly couples with the DMN and DAN to arbitrate between internally and externally directed cognition.
“A third network, the frontoparietal control network (FPCN; Vincent et al., 2008), including the RTPJ (Corbetta et al., 2008), flexibly couples with the DMN and DAN to arbitrate between internally and externally directed cognition (Spreng et al., 2010).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Vincent et al., 2008
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- cites Corbetta et al., 2008
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- cites Spreng et al., 2010
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- Interpretationown data
These results provide the first evidence for a common cortical code for relative egocentric spatial, temporal, and social distances.
“In summary, these results provide the first evidence for a common cortical code for relative egocentric spatial, temporal, and social distances.”
Quote in the paperSubstantial claim - Interpretationown data
The current results suggest that the RTPJ represents egocentric spatial, temporal, and social distances according to a parsimonious coding scheme.
“The current results suggest that the RTPJ represents egocentric spatial, temporal, and social distances according to a parsimonious coding scheme.”
Quote in the paperSubstantial claim
- May combine two claims. 13
- Classified as probably not a substantial claim. 24
May combine two claims.
Findingown dataThe largest significant cluster was located in right IPL, encompassing both the AG and SMG, and extending into the posterior temporal lobe, followed by a cluster in medial occipital cortex.
“The largest significant cluster was located in right IPL, encompassing both the AG and SMG, and extending into the posterior temporal lobe, followed by a cluster in medial occipital cortex.”
Quote in the paperSubstantial claim- Rests on an assumption: The spatial, temporal, and social distance stimuli validly operationalize egocentric distance in their respective domains.
May combine two claims.
Findingown dataMean ratings of perceived egocentric distance differences were 6.21 ± 0.70, 6.29 ± 0.82, and 6.52 ± 0.62 for closer, sooner, and more familiar trials, respectively.
“Mean Ϯ SD ratings of perceived egocentric distance differences on a scale from 1 (equally soon/close/familiar) to 7 (one image/phrase is a great deal sooner/closer/more familiar) were 6.21 Ϯ 0.70, 6.29 Ϯ 0.82, and 6.52 Ϯ 0.62 for closer, sooner, and more familiar trials, respectively.”
Quote in the paperSubstantial claim- Rests on an assumption: Postscan written questionnaire ratings reflect participants' perceived egocentric psychological distance during scanning.
May combine two claims.
Findingown dataCross-domain distance decoding was also possible in smaller clusters throughout the right IPL, spanning both the supramarginal (SMG) and angular (AG) gyri, as well as in one cluster in medial occipital cortex.
“Cross-domain distance decoding was also possible in smaller clusters throughout the right IPL, spanning both the supramarginal (SMG) and angular (AG) gyri, as well as in one cluster in medial occipital cortex, as summarized in Table 1.”
- Also stated in: § Discussion · plain
“Cross-domain distance decoding was also possible in medial occipital cortex.”
Quote in the paperSubstantial claim- Also stated in: § Discussion · plain
Classified as probably not a substantial claim.
PremisecitationMechanisms devoted to spatial processing may have been redeployed over evolution to plot information in increasingly abstract temporal and social frames of reference.
“Neuroscientists have suggested that, over the course of evolution, mechanisms devoted to spatial processing may have been redeployed to “plot” information in increasingly abstract (e.g., temporal, social) frames of reference (Yamazaki et al., 2009;Parkinson and Wheatley, 2013).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Yamazaki et al., 2009
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- cites Parkinson and Wheatley, 2013
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PremisecitationWords characterizing shorter social and temporal distances are automatically associated with closer spatial locations, whereas words referring to increased social and temporal distances are associated with farther locations.
“Words characterizing shorter social and temporal distances are automatically associated with closer spatial locations, whereas words referring to increased social and temporal distances are associated with farther locations (Bar-Anan et al., 2007).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Bar-Anan et al., 2007
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PremisecitationPrevious fMRI studies suggest that judging and traversing spatial, social, and temporal distances recruit overlapping brain regions.
“Previous fMRI studies suggest that judging and traversing spatial, social, and temporal distances recruit overlapping brain regions (Buckner and Carroll, 2007;Spreng et al., 2009;Yamakawa et al., 2009;Yamazaki et al., 2009;Tamir and Mitchell, 2011).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Buckner and Carroll, 2007
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- cites Spreng et al., 2009
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- cites Yamakawa et al., 2009
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PremisecitationPast studies have used univariate analyses that spatially smooth and average data to identify areas involved in tasks.
“However, past studies have used univariate analyses that spatially smooth and average data to identify areas involved in tasks (Friston et al., 1995).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Friston et al., 1995
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PremisecitationConceptual metaphor theory suggests that we use spatial language to describe social and temporal relationships because we mentally represent this information in spatial terms.
“Conceptual metaphor theory (CMT; Lakoff and Johnson, 1980) suggests that we use spatial language to describe social and temporal relationships (e.g., “close friend,” “distant future”) because we mentally represent this information in spatial terms.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Lakoff and Johnson, 1980
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PremisereasoningIf different domains of egocentric distance are conflated at some level of processing, relatively near or far distances should be represented similarly at that level of processing, regardless of domain.
“If different domains of egocentric distance are conflated at some level of processing, relatively near or far distances should be represented similarly at that level of processing, regardless of domain.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
PremisecitationRSA permits the direct, quantitative comparison of data acquired using diverse methods in terms of the information that each dataset contains about a set of experimental conditions.
“In general, RSA permits the direct, quantitative comparison of data acquired using diverse methods (e.g., fMRI, behavioral questionnaires) in terms of the information that each dataset contains about a set of experimental conditions.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Kriegeskorte et al., 2008
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Study design and conductcitationPercent accuracy maps were arcsine transformed before being tested against chance across participants, because this procedure approximates a normal and homoscedastic distribution given binary data summarized as proportions.
“Percent accuracy maps resulting from crossdomain distance decoding analyses were aligned to standard space (Talairach and Tournoux, 1988) and arcsine transformed ( y ϭ arcsine͌x, where x is proportion of classifications that were correct, and y is the result of the transformation) before being tested against chance across participants, because this procedure approximates a normal and homoscedastic”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Freeman and Tukey, 1950
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- cites Zar, 1996
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Study design and conductown dataAt each searchlight center, the statistical significance of the relationship between the behavioral and local neural RDMs was evaluated using permutation testing.
“At each searchlight center, the statistical significance of the relationship between the behavioral and local neural RDMs was evaluated using permutation testing.”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationThe RTPJ encodes egocentric space and is thought to support self-other distinctions.
“The RTPJ encodes egocentric space (Schindler and Bartels, 2013) and is thought to support self-other distinctions (Decety and Somerville, 2003).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Schindler and Bartels, 2013
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- cites Decety and Somerville, 2003
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Study design and conductcitationSpatial distance stimuli were tested previously to ensure that viewers perceive them to be at the intended egocentric distances and have been demonstrated previously to automatically elicit egocentric distance processing.
“These stimuli were tested previously to ensure that viewers perceive them to be at the intended egocentric distances and have been demonstrated previously to automatically elicit egocentric distance processing (Berryhill and Olson, 2009).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Berryhill and Olson, 2009
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Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataLetter counts did not significantly differ between immediate and remote future phrases.
“Letter counts also did not significantly differ between immediate (median, 13.50) and remote (median, 12.50) future phrases (W ϭ 6, p ϭ 0.65, r ϭ 0.16).”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationcitationEvidence from social psychology and neuroimaging demonstrates analogous effects of different distance domains on cognition and behavior, consistent with suggestions that this information implies a common psychological meaning.
“Thus, evidence from social psychology and neuroimaging demonstrates analogous effects of different distance domains on cognition and behavior, consistent with suggestions that this information implies a common psychological meaning (Liberman and Trope, 2008).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Liberman and Trope, 2008
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationTamir and Mitchell (2011) found fMRI evidence consistent with behavioral findings that different distance domains influence thoughts and actions analogously.
“Recently, Tamir and Mitchell (2011) found fMRI evidence consistent with behavioral findings that different distance domains influence our thoughts and actions analogously.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Tamir and Mitchell (2011)
Not checked in the free run.
Classified as probably not a substantial claim.
Study design and conductown dataA conjunction analysis of the six t statistic maps was performed using a threshold of p < 0.05, FDR corrected, for each map to identify regions in which psychological distance could be decoded across all distance domains.
“A conjunction analysis of these six t statistic maps was performed using a threshold of p Ͻ 0.05, false discovery rate (FDR; Benjamini and Hochberg, 1995) corrected, for each map to identify regions in which psychological distance could be decoded across all distance domains.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Benjamini and Hochberg, 1995 source
Not checked in the free run.
May combine two claims.
InterpretationreasoningBecause the conjunction analysis requires above-chance distance decoding across all pairs of distance domains, this approach should identify areas that contain a domain-general encoding of egocentric distance.
“Because the conjunction analysis requires above-chance distance decoding across all pairs of distance domains, this approach should identify areas that contain a domain-general encoding of egocentric distance.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Study design and conductnone givenRed indicates the conjunction of significant results (p < 0.05, FDR corrected, each test) across all six tests.
“Red indicates the conjunction of significant results ( p Ͻ 0.05, FDR corrected, each test) across all six tests.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
Study design and conductreasoningFor each classification searchlight, predictions were only considered correct if trials characterized by decreasing psychological distance in the test domain were classified as if they were trials characterized by decreasing psychological distance in the training domain.
“It should be emphasized that, for each classification searchlight, predictions were only considered correct if trials characterized by decreasing psychological distance in the test domain (e.g., more familiar trials) were classified as if they were trials characterized by decreasing psychological distance in the training domain (e.g., sooner trials).”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationBoth a shared encoding mechanism and nearby but distinct codes would yield overlapping results.
“Both a shared encoding mechanism and nearby but distinct codes would yield overlapping results (Peelen and Downing, 2007).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Peelen and Downing, 2007
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataRatings did not differ between the two versions of the postscan questionnaire.
“Ratings did not differ between the two versions of the questionnaire.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Study design and conductreasoningRather than assuming that all distance domains were perceived equivalently, this data analytic approach preserves differences in behavioral ratings between domains.
“Additionally, rather than assuming that all distance domains were perceived equivalently, this data analytic approach preserves differences in behavioral ratings between domains.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
Study design and conductcitationSpearman's rank coefficient was used because it does not assume a linear match between neural and behavioral RDMs.
“Custom code was written in Python and PyMVPA to compare the off-diagonal elements of the lower triangular halves of the neural and behavioral RDMs at each voxel for each participant (Fig. 3C) using the Spearman's rank coefficient, which was used because it does not assume a linear match between neural and behavioral RDMs (Kriegeskorte et al., 2008).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Kriegeskorte et al., 2008
Not checked in the free run.
Classified as probably not a substantial claim.
PremisecitationAccording to construal level theory (CLT), distance in any domain signifies a common meaning: distance from current first-hand experience.
“According to construal level theory (CLT; Trope and Liberman, 2010), distance in any domain signifies a common meaning: distance from current first-hand experience.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Trope and Liberman, 2010
Not checked in the free run.
Classified as probably not a substantial claim.
PremisecitationWalsh (2003) suggested that, on the scale of action execution, space, time, and quantity are encoded by a common metric that was repurposed for other magnitudes.
“Walsh (2003) suggested that, on the scale of action execution, space, time, and quantity are encoded by a common metric that was repurposed for other magnitudes.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Walsh (2003)
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataThe number of plural nouns was exactly matched between immediate and remote future phrases.
“Additionally, the number of plural nouns was exactly matched between the two trial types (i.e., exactly two of the immediate future phrases and two of the remote future phrases contained one plural noun).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Study design and conductnone givenThe conjunction analysis requires above-chance distance decoding across all pairs of distance domains.
“Importantly, the conjunction analysis requires above-chance distance decoding across all pairs of distance domains.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Study design and conductnone givenFamiliar and unfamiliar others were matched for gender, race, age, and facial expression.
“Familiar and unfamiliar others were matched for gender, race, age, and facial expression (which was either neutral or slightly positive).”
Quote in the paperSubstantial claimClassified as probably not a substantial claim. May combine two claims.
PremisecitationInformation relevant to present experience elicits detailed, concrete representations, whereas humans tend to think about information removed from current experience using decontextualized, abstract representations.
“Whereas information relevant to our present experience elicits detailed, concrete representations, humans tend to think about information removed from our current experience using decontextualized, abstract representations (Liberman and Trope, 2008).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Liberman and Trope, 2008
Not checked in the free run.
Classified as probably not a substantial claim. May combine two claims.
PremisecitationCLT suggests that psychologically proximal information promotes attention to concrete, contextual details, whereas distal information evokes decontextualized, abstract representations.
“CLT suggests that psychologically proximal information promotes attention to concrete, contextual details, whereas distal information evokes decontextualized, abstract representations (Liberman and Trope, 2008).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Liberman and Trope, 2008
Not checked in the free run.
May combine two claims.
InterpretationreasoningClose objects are likely to be personally relevant and elicit immediate action and, thus, may evoke similar SMA activation patterns.
“Close objects are likely to be personally relevant and elicit immediate action and, thus, may evoke similar SMA activation patterns.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
InterpretationcitationThe current results are consistent with suggestions that neural mechanisms supporting higher-order cognition may often be best understood in terms of the computations, rather than the domains of knowledge, that they involve.
“More generally, the current results are consistent with suggestions that neural mechanisms supporting higher-order cognition may often be best understood in terms of the computations, rather than the domains of knowledge, that they involve (Mitchell, 2008).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Mitchell, 2008
Not checked in the free run.
May combine two claims.
InterpretationcitationRelationships between domains of psychological distance are distinguished from those between other source and target domains because any domain of psychological distance confers a chronically accessible, automatically processed common meaning that affects perception, cognition, and behavior similarly.
“Relationships between domains of psychological distance are distinguished from those between other source and target domains because any domain of psychological distance confers a chronically accessible, automatically processed common meaning (Bar-Anan et al., 2006, 2007) that affects perception, cognition, and behavior similarly (Liberman and Trope, 2008).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Bar-Anan et al., 2006, 2007
Not checked in the free run.
- cites Liberman and Trope, 2008
Not checked in the free run.
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.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Self-PPS may contribute to gaining social, temporal, and physical proximity with others around us in addition to the regulation of social distances.
“In this way, self PPS may contribute to gaining social, temporal and physical proximity with the others around us in addition to the regulation of social distances (Parkinson, Liu, & Wheatley, 2014;Ruggiero et al., 2019;Sorokowska et al., 2017).”
From The Peripersonal Space in a social world (2021) · cites this paper as Parkinson, Liu, & Wheatley, 2014
The Discussion (page not specified) reports a common cortical code for egocentric spatial, temporal, and social distance. It does not establish that self-peripersonal space (self-PPS) helps people gain proximity to others or regulate social distances. (LLM, conf=0.86)
Experimental — accuracy not yet measuredSeveral specific brain regions represent participants' assessment of power or affiliation.
“Several specific brain regions represent participants’ assessment of power (social status in the community) (Muscatell et al., 2012) or affiliation (familiarity of acquaintances) (Parkinson et al., 2014).”
From A map for social navigation in the human brain (2015) · cites this paper as Parkinson et al., 2014
Cites
R: A Language and Environment for Statistical Computing
R Core Team (2000) · doi:10.32614/r.manuals · Cited by 355,706 · see citing works
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482 · see citing works
Lakoff, G. P., & Johnson, M. L. (2003) · University of Chicago Press eBooks · doi:10.7208/chicago/9780226470993.001.0001 · Cited by 25,252 · see citing works
Co-Planar Stereotaxic Atlas of the Human Brain
Talairach, J., & Tournoux, P. (1988) · Medical Entomology and Zoology · Cited by 11,798 · see citing works
AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages
Cox, R. W. (1996) · Computers and Biomedical Research · doi:10.1006/cbmr.1996.0014 · Cited by 10,913 · see citing works
Statistical parametric maps in functional imaging: A general linear approach
Friston, K. J., Holmes, A. P., Worsley, K. J., Poline, J. ‐., Frith, C. D., & Frackowiak, R. S. J. (1994) · Human Brain Mapping · doi:10.1002/hbm.460020402 · Cited by 9,688 · see citing works
The human brain is intrinsically organized into dynamic, anticorrelated functional networks
Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0504136102 · Cited by 8,553 · see citing works
Construal-level theory of psychological distance.
Trope, Y., & Liberman, N. (2010) · Psychological Review · doi:10.1037/a0018963 · Cited by 6,618 · see citing works
Automatically Parcellating the Human Cerebral Cortex
Fischl, B. R. (2003) · Cerebral Cortex · doi:10.1093/cercor/bhg087 · Cited by 4,208 · see citing works
The reorienting system of the human brain: from environment to theory of mind
Corbetta, M., Patel, G., & Shulman, G. L. (2008) · Neuron · doi:10.1016/j.neuron.2008.04.017 · Cited by 3,889 · see citing works
Representational similarity analysis-connecting the branches of systems neuroscience
Kriegeskorte, N. (2008) · Frontiers in Systems Neuroscience · doi:10.3389/neuro.06.004.2008 · Cited by 3,355 · see citing works
Wandering minds: the default network and stimulus-independent thought
Mason, M. F., Norton, M. I., Van Horn, J. D., Wegner, D. M., Grafton, S. T., & Macrae, C. N. (2007) · Science · doi:10.1126/science.1131295 · Cited by 2,792 · see citing works
Buckner, R. L., & Carroll, D. C. (2007) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2006.11.004 · Cited by 2,691 · see citing works
Transformations Related to the Angular and the Square Root
Freeman, M. F., & Tukey, J. W. (1950) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177729756 · Cited by 2,634 · see citing works
THREE PARIETAL CIRCUITS FOR NUMBER PROCESSING
Dehaene, S., Manuela Piazza, A., Pinel, P., & Cohen, L. (2003) · Cognitive Neuropsychology · doi:10.1080/02643290244000239 · Cited by 2,471 · see citing works
Beyond mind-reading: multi-voxel pattern analysis of fMRI data
Norman, K. A., Polyn, S. M., Detre, G. J., & Haxby, J. V. (2006) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2006.07.005 · Cited by 2,271 · see citing works
Spreng, R. N., Mar, R. A., & Kim, A. S. N. (2009) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2008.21029 · Cited by 2,143 · see citing works
Information-based functional brain mapping
Kriegeskorte, N., Goebel, R., & Bandettini, P. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0600244103 · Cited by 2,113 · see citing works
A theory of magnitude: common cortical metrics of time, space and quantity
Walsh, V. (2003) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2003.09.002 · Cited by 2,044 · see citing works
The evolution of foresight: What is mental time travel, and is it unique to humans?
Suddendorf, T., & Corballis, M. C. (2007) · Behavioral and Brain Sciences · doi:10.1017/s0140525x07001975 · Cited by 2,031 · see citing works
Evidence for a Frontoparietal Control System Revealed by Intrinsic Functional Connectivity
Vincent, J. L., Kahn, I., Snyder, A. Z., Raichle, M. E., & Buckner, R. L. (2008) · Journal of Neurophysiology · doi:10.1152/jn.90355.2008 · Cited by 1,869 · see citing works
A new neural framework for visuospatial processing
Kravitz, D. J., Saleem, K. S., Baker, C. I., & Mishkin, M. (2011) · Nature Reviews Neuroscience · doi:10.1038/nrn3008 · Cited by 1,325 · see citing works
The Psychology of Transcending the Here and Now
Liberman, N., & Trope, Y. (2008) · Science · doi:10.1126/science.1161958 · Cited by 1,264 · see citing works
Spreng, R. N., Stevens, W. D., Chamberlain, J. P., Gilmore, A. W., & Schacter, D. L. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.06.016 · Cited by 1,256 · see citing works
Time in the mind: Using space to think about time
Casasanto, D. J., & Boroditsky, L. (2007) · Cognition · doi:10.1016/j.cognition.2007.03.004 · Cited by 1,188 · see citing works
Shared representations between self and other: a social cognitive neuroscience view
Decety, J., & Sommerville, J. A. (2003) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2003.10.004 · Cited by 996 · see citing works
How does nature program neuron types?
Borst, A. (2008) · Frontiers in Neuroscience · doi:10.3389/neuro.01.016.2008 · Cited by 705 · see citing works
Bar‐Anan, Y., Liberman, N., & Trope, Y. (2006) · Journal of Experimental Psychology General · doi:10.1037/0096-3445.135.4.609 · Cited by 596 · see citing works
Förster, J., Friedman, R., & Liberman, N. (2004) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.87.2.177 · Cited by 584 · see citing works
The Corpus of Contemporary American English as the first reliable monitor corpus of English
Davies, M. (2010) · Literary and Linguistic Computing · doi:10.1093/llc/fqq018 · Cited by 485 · see citing works
Activity in Right Temporo-Parietal Junction is Not Selective for Theory-of-Mind
Mitchell, J. P. (2008) · Cerebral Cortex · doi:10.1093/cercor/bhm051 · Cited by 469 · cited 1× · see citing works
“More generally, the current results are consistent with suggestions that neural mechanisms supporting higher-order cognition may often be best understood in terms of the computations, rather than the domains of knowledge, that they involve (Mitchell, 2008).”
ResultPyMVPA: a Python Toolbox for Multivariate Pattern Analysis of fMRI Data
Hanke, M., Halchenko, Y. O., Sederberg, P. B., Hanson, S. J., Haxby, J. V., & Pollmann, S. (2009) · Neuroinformatics · doi:10.1007/s12021-008-9041-y · Cited by 468 · see citing works
A Theory of Action Identification
Vallacher, R. R., & Wegner, D. M. (2014) · Psychology Press eBooks · doi:10.4324/9781315802213 · Cited by 440 · see citing works
Cantlon, J. F., Platt, M. L., & Brannon, E. M. (2009) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2008.11.007 · Cited by 427 · see citing works
The Representation of Biological Classes in the Human Brain
Connolly, A. C., Guntupalli, J. S., Gors, J. D., Hanke, M., Halchenko, Y. O., Wu, Y., Abdi, H., & Haxby, J. V. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.5547-11.2012 · Cited by 408 · see citing works
Recruitment of an Area Involved in Eye Movements During Mental Arithmetic
Knops, A., Thirion, B., Hubbard, E. M., Michel, V., & Dehaene, S. (2009) · Science · doi:10.1126/science.1171599 · Cited by 404 · see citing works
The anatomy of spatial neglect
Karnath, H., & Rorden, C. (2011) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2011.06.027 · Cited by 385 · see citing works
Judging near and distant virtue and vice
Eyal, T., Liberman, N., & Trope, Y. (2008) · Journal of Experimental Social Psychology · doi:10.1016/j.jesp.2008.03.012 · Cited by 380 · see citing works
Automatic processing of psychological distance: Evidence from a Stroop task.
Bar‐Anan, Y., Liberman, N., Yaacov Trope, B., & Algom, D. (2007) · Journal of Experimental Psychology General · doi:10.1037/0096-3445.136.4.610 · Cited by 352 · see citing works
Space and Time in the Child’s Mind: Evidence for a Cross‐Dimensional Asymmetry
Casasanto, D. J., Fotakopoulou, O., & Boroditsky, L. (2010) · Cognitive Science · doi:10.1111/j.1551-6709.2010.01094.x · Cited by 252 · see citing works
Liberman, N., & Förster, J. (2009) · Journal of Personality and Social Psychology · doi:10.1037/a0015671 · Cited by 245 · see citing works
Deciphering Cortical Number Coding from Human Brain Activity Patterns
Eger, E., Michel, V., Thirion, B., Amadon, A., Dehaene, S., & Kleinschmidt, A. K. (2009) · Current Biology · doi:10.1016/j.cub.2009.08.047 · Cited by 221 · see citing works
Affective Signals of Threat Increase Perceived Proximity
Cole, S., Balcetis, E., & Dunning, D. A. (2012) · Psychological Science · doi:10.1177/0956797612446953 · Cited by 205 · see citing works
Neural Activity Underlying the Effect of Approach-Motivated Positive Affect on Narrowed Attention
Harmon‐Jones, E., & Gable, P. A. (2009) · Psychological Science · doi:10.1111/j.1467-9280.2009.02302.x · Cited by 187 · see citing works
Harmon‐Jones, E., Lueck, L., Fearn, M., & Harmon‐Jones, C. (2006) · Psychological Science · doi:10.1111/j.1467-9280.2006.01724.x · Cited by 181 · see citing works
Too Close for Comfort, or Too Far to Care? Finding Humor in Distant Tragedies and Close Mishaps
McGraw, A. P., Warren, C., Williams, L. E., & Leonard, B. (2012) · Psychological Science · doi:10.1177/0956797612443831 · Cited by 177 · see citing works
Threat modulates perception of looming visual stimuli
Vagnoni, E., Lourenco, S. F., & Longo, M. R. (2012) · Current Biology · doi:10.1016/j.cub.2012.07.053 · Cited by 164 · see citing works
Do monkeys think in metaphors? Representations of space and time in monkeys and humans
Merritt, D. J., Casasanto, D. J., & Brannon, E. M. (2010) · Cognition · doi:10.1016/j.cognition.2010.08.011 · Cited by 156 · see citing works
Using multi-voxel pattern analysis of fMRI data to interpret overlapping functional activations
Peelen, M. V., & Downing, P. E. (2007) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2006.10.009 · Cited by 110 · see citing works
Old cortex, new contexts: re-purposing spatial perception for social cognition
Parkinson, C. M., & Wheatley, T. P. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00645 · Cited by 101 · see citing works
Self-citationBaumann, O., Chan, E., & Mattingley, J. B. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.10.021 · Cited by 97 · see citing works
Patients With Left Spatial Neglect Also Neglect the “Left Side” of Time
Saj̈, A., Fuhrman, O., Vuilleumier, P. O., & Boroditsky, L. (2013) · Psychological Science · doi:10.1177/0956797612475222 · Cited by 94 · see citing works
Harmon‐Jones, E., Price, T. F., & Gable, P. A. (2012) · Social and Personality Psychology Compass · doi:10.1111/j.1751-9004.2012.00432.x · Cited by 93 · see citing works
The Default Network Distinguishes Construals of Proximal versus Distal Events
Tamir, D., & Mitchell, J. P. (2011) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00009 · Cited by 92 · see citing works
Parietal Cortex Codes for Egocentric Space beyond the Field of View
Schindler, A., & Bartels, A. (2012) · Current Biology · doi:10.1016/j.cub.2012.11.060 · Cited by 91 · see citing works
Susanne Quadflieg, A., Etzel, J. A., Gazzola, V., Keysers, C., Schubert, T. W., Waiter, G. D., & Macrae, C. N. (2011) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2011.21628 · Cited by 74 · see citing works
Lenggenhager, B., Smith, S., & Blanke, O. (2006) · Reviews in the Neurosciences · doi:10.1515/revneuro.2006.17.6.643 · Cited by 69 · see citing works
Social Distance Evaluation in Human Parietal Cortex
Yamakawa, Y., Ryota Kanai, C., Matsumura, M., & Naito, E. (2009) · PLoS ONE · doi:10.1371/journal.pone.0004360 · Cited by 64 · see citing works
Thompson, W. L., Slotnick, S. D., Burrage, M. S., & Kosslyn, S. M. (2009) · Psychological Science · doi:10.1111/j.1467-9280.2009.02440.x · Cited by 55 · see citing works
The posterior parietal cortex and non-spatial cognition
Yamazaki, Y., Hashimoto, T., & Iriki, A. (2009) · F1000 Biology Reports · doi:10.3410/b1-74 · Cited by 31 · see citing works
The representation of object distance: evidence from neuroimaging and neuropsychology
Berryhill, M. E. (2009) · Frontiers in Human Neuroscience · doi:10.3389/neuro.09.043.2009 · Cited by 21 · see citing works
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Research works printed but not linked: 1
- Zar JH (1996) Biostatistical analysis (Prentice Hall, Upper Saddle River, NJ).
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Wolff, P., & Barbey, A. K. (2015) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2015.00001 · Cited by 788 · see citing works
The varieties of self-transcendent experience
Yaden, D. B., Haidt, J., Hood, R. W., Vago, D. R., & Newberg, A. B. (2017) · Review of General Psychology · doi:10.1037/gpr0000102 · Cited by 701 · see citing works
A map for social navigation in the human brain
Tavares, R. M., Mendelsohn, A., Grossman, Y., Williams, C. H., Shapiro, M., Trope, Y., & Schiller, D. (2015) · Neuron · doi:10.1016/j.neuron.2015.06.011 · Cited by 505 · see citing works
The Geometry of Abstraction in the Hippocampus and Prefrontal Cortex
Bernardi, S., Benna, M. K., Rigotti, M., Munuera, J., Fusi, S., & Salzman, C. D. (2020) · Cell · doi:10.1016/j.cell.2020.09.031 · Cited by 496 · see citing works
Brain system for mental orientation in space, time, and person
Peer, M., Salomon, R., Goldberg, I., Blanke, O., & Arzy, S. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1504242112 · Cited by 278 · see citing works
Spontaneous neural encoding of social network position
Parkinson, C. M., Kleinbaum, A. M., & Wheatley, T. P. (2017) · Nature Human Behaviour · doi:10.1038/s41562-017-0072 · Cited by 253 · see citing works
Self-citationMontagrin, A., Saiote, C., & Schiller, D. (2017) · Hippocampus · doi:10.1002/hipo.22797 · Cited by 197 · see citing works
Schafer, M., & Schiller, D. (2018) · Neuron · doi:10.1016/j.neuron.2018.10.006 · Cited by 181 · see citing works
Powers, J. P., & LaBar, K. S. (2019) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2018.04.023 · Cited by 173 · see citing works
Smith, E. B., Brands, R. A., Brashears, M. E., & Kleinbaum, A. M. (2020) · Annual Review of Sociology · doi:10.1146/annurev-soc-121919-054736 · Cited by 166 · see citing works
Knowledge Across Reference Frames: Cognitive Maps and Image Spaces
Bottini, R., & Doeller, C. F. (2020) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2020.05.008 · Cited by 152 · see citing works
A Guide to Representational Similarity Analysis for Social Neuroscience
Popal, H. S., Wang, Y., & Olson, I. R. (2019) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsz099 · Cited by 150 · see citing works
How Social Status Shapes Person Perception and Evaluation: A Social Neuroscience Perspective
Mattan, B. D., Kubota, J. T., & Cloutier, J. (2017) · Perspectives on Psychological Science · doi:10.1177/1745691616677828 · Cited by 150 · see citing works
Structure learning and the posterior parietal cortex
Summerfield, C., Luyckx, F., & Sheahan, H. (2020) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2019.101717 · Cited by 118 · see citing works
Space–time interdependence: Evidence against asymmetric mapping between time and space
Cai, Z. G., & Connell, L. (2014) · Cognition · doi:10.1016/j.cognition.2014.11.039 · Cited by 114 · see citing works
The Moral brain: a multidisciplinary perspective
Decety, J., & Wheatley, T. (2015) · Choice Reviews Online · doi:10.5860/choice.192126 · Cited by 110 · see citing works
Time Adaptation Shows Duration Selectivity in the Human Parietal Cortex
Hayashi, M. J., Ditye, T., Harada, T., Hashiguchi, M., Sadato, N., Carlson, S., Walsh, V., & Kanai, R. (2015) · PLoS Biology · doi:10.1371/journal.pbio.1002262 · Cited by 100 · see citing works
Social discounting and distance perceptions in costly altruism
Vekaria, K. M., Brethel-Haurwitz, K. M., Cardinale, E. M., Stoycos, S. A., & Marsh, A. A. (2017) · Nature Human Behaviour · doi:10.1038/s41562-017-0100 · Cited by 96 · see citing works
Neural structure mapping in human probabilistic reward learning
Luyckx, F., Nili, H., Spitzer, B., & Summerfield, C. (2019) · eLife · doi:10.7554/elife.42816 · Cited by 84 · see citing works
Heinberg, M., Katsikeas, C. S., Ozkaya, H. E., & Taube, M. (2019) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-019-00637-x · Cited by 101 · see citing works
The Peripersonal Space in a social world
Bogdanova, O. V., Bogdanov, V. B., Dureux, A., Farnè, A., & Hadj-Bouziane, F. (2021) · Cortex · doi:10.1016/j.cortex.2021.05.005 · Cited by 86 · see citing works
“In this way, self PPS may contribute to gaining social, temporal and physical proximity with the others around us in addition to the regulation of social distances (Parkinson et al., 2014; Ruggiero et al., 2019; Sorokowska et al., 2017).”
BackgroundFFA and OFA Encode Distinct Types of Face Identity Information
Tsantani, M., Kriegeskorte, N., Storrs, K. R., Williams, A. L., McGettigan, C., & Garrido, L. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.1449-20.2020 · Cited by 83 · see citing works
The bodily self and its disorders: neurological, psychological and social aspects
Brugger, P., & Lenggenhager, B. (2014) · Current Opinion in Neurology · doi:10.1097/wco.0000000000000151 · Cited by 82 · see citing works
Parkinson, C. M., & Wheatley, T. P. (2015) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2015.01.003 · Cited by 78 · see citing works
Self-citationNeural state space alignment for magnitude generalization in humans and recurrent networks
Sheahan, H., Luyckx, F., Nelli, S., Teupe, C., & Summerfield, C. (2021) · Neuron · doi:10.1016/j.neuron.2021.02.004 · Cited by 67 · see citing works
Clinically relevant acute subjective effects of psychedelics beyond mystical experience
Yaden, D. B., Goldy, S. P., Weiss, B., & Griffiths, R. R. (2024) · Nature Reviews Psychology · doi:10.1038/s44159-024-00345-6 · Cited by 64 · see citing works
Neural Population Decoding Reveals the Intrinsic Positivity of the Self
Chavez, R. S., Heatherton, T. F., & Wagner, D. D. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw302 · Cited by 65 · see citing works
Nook, E. C., Hull, T. D., Nock, M. K., & Somerville, L. H. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2114737119 · Cited by 61 · see citing works
Time Is Not Space: Core Computations and Domain-Specific Networks for Mental Travels
Gauthier, B., & van Wassenhove, V. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.1400-16.2016 · Cited by 58 · see citing works
Mason, M. F., Magee, J. C., & Fiske, S. T. (2014) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00553 · Cited by 56 · see citing works
Creative expertise is associated with transcending the here and now.
Meyer, M. L., Ersner-Hershfield, H., Waytz, A. G., Mildner, J. N., & Tamir, D. (2019) · Journal of Personality and Social Psychology · doi:10.1037/pspa0000148 · Cited by 56 · see citing works
Brain Coding of Social Network Structure
Peer, M., Hayman, M., Tamir, B., & Arzy, S. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.2641-20.2021 · Cited by 53 · see citing works
Cognitive mapping in mental time travel and mental space navigation
Gauthier, B., & van Wassenhove, V. (2016) · Cognition · doi:10.1016/j.cognition.2016.05.015 · Cited by 52 · see citing works
Chuan-Peng, H., Huang, Y., Eickhoff, S. B., Peng, K., & Sui, J. (2020) · Cognitive Affective & Behavioral Neuroscience · doi:10.3758/s13415-020-00827-z · Cited by 51 · see citing works
Tsantani, M., Kriegeskorte, N., McGettigan, C., & Garrido, L. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.07.017 · Cited by 49 · see citing works
Mapping the social landscape: tracking patterns of interpersonal relationships
Basyouni, R., & Parkinson, C. M. (2022) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2021.12.006 · Cited by 46 · see citing works
Self-citationChristian, B. M., Parkinson, C. M., Macrae, C. N., Miles, L. K., & Wheatley, T. P. (2014) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00754 · Cited by 45 · see citing works
Self-citationWagner, D. D., Chavez, R. S., & Broom, T. W. (2018) · Wiley Interdisciplinary Reviews Cognitive Science · doi:10.1002/wcs.1482 · Cited by 45 · see citing works
Social learning across adolescence: A Bayesian neurocognitive perspective
Hofmans, L., & van den Bos, W. (2022) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2022.101151 · Cited by 46 · see citing works
Functional brain network architecture supporting the learning of social networks in humans
Tompson, S., Kahn, A. E., Falk, E. B., Vettel, J. M., & Bassett, D. S. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2019.116498 · Cited by 43 · see citing works
Neurological evidence for the role of construal level in future-directed thought
Stillman, P. E., Lee, H., Deng, X., Unnava, H. R., Cunningham, W. A., & Fujita, K. (2017) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsx022 · Cited by 39 · see citing works
The Hippocampus and Social Cognition
Laurita, A. C., & Spreng, R. N. (2017) · Springer eBooks · doi:10.1007/978-3-319-50406-3_17 · Cited by 38 · see citing works
Gilal, R. G., Gilal, N. G., Gilal, F. G., & Gong, Z. (2021) · International Journal of Consumer Studies · doi:10.1111/ijcs.12653 · Cited by 41 · see citing works
Viganò, S., Bayramova, R., Doeller, C. F., & Bottini, R. (2023) · Nature Communications · doi:10.1038/s41467-023-43831-w · Cited by 40 · see citing works
Emotional Dysfunction in Psychopathology and Neuropathology
Sturm, V. E., Haase, C. M., & LEVENSON, R. W. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-800105-9.00022-6 · Cited by 45 · see citing works
Dafni‐Merom, A., & Arzy, S. (2020) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2020.107477 · Cited by 37 · see citing works
The neural representation of social networks
Weaverdyck, M. E., & Parkinson, C. M. (2018) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2018.05.009 · Cited by 35 · see citing works
Self-citationThe missing link: Information behavior research and its estranged relationship with embodiment
Lueg, C. (2015) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.23441 · Cited by 34 · see citing works
Fareri, D. S., Smith, D. V., & Delgado, M. R. (2020) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsaa031 · Cited by 35 · see citing works
Gaesser, B., Hirschfeld-Kroen, J., Wasserman, E. A., Horn, M., & Young, L. (2019) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsz014 · Cited by 30 · see citing works
Mental models use common neural spatial structure for spatial and abstract content
Alfred, K. L., Connolly, A. C., Cetron, J. S., & Kraemer, D. J. M. (2020) · Communications Biology · doi:10.1038/s42003-019-0740-8 · Cited by 27 · see citing works
Oosterwijk, S., Snoek, L., Rotteveel, M., Barrett, L. F., & Scholte, H. S. (2017) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsx037 · Cited by 27 · see citing works
Sheldon, S., & Levine, B. (2018) · Hippocampus · doi:10.1002/hipo.22829 · Cited by 23 · see citing works
Li, S., Krüeger, F., Camilleri, J. A., Eickhoff, S. B., & Qu, C. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118731 · Cited by 27 · see citing works
Meaning, Mind and Communication
Zlatev, J., Sonesson, G., & Konderak, P. (2016) · Peter Lang D eBooks · doi:10.3726/978-3-653-04948-0 · Cited by 26 · see citing works
Predicting emotional health indicators from linguistic evidence of psychological distancing
Shahane, A. D., & Denny, B. T. (2019) · Stress and Health · doi:10.1002/smi.2855 · Cited by 25 · see citing works
Abraham, D., Powers, J., & Kateri Mcrae, A. (2023) · Emotion Review · doi:10.1177/17540739231196577 · Cited by 25 · see citing works
Sequeira, S. L., Silk, J. S., Edershile, E. A., Jones, N. P., Hanson, J. L., Forbes, E. E., & Ladouceur, C. D. (2021) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsab038 · Cited by 23 · see citing works
An agenda for psychological distance apart from construal level
Maglio, S. J. (2020) · Social and Personality Psychology Compass · doi:10.1111/spc3.12552 · Cited by 25 · see citing works
Chilton, P. (2019) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780190273385.013.14 · Cited by 25 · see citing works
Distinct Neural Representations of Content and Ordinal Structure in Auditory Sequence Memory
Fan, Y., Han, Q., Guo, S., & Luo, H. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.0320-21.2021 · Cited by 22 · see citing works
Neural responses underlying extraordinary altruists’ generosity for socially distant others
Rhoads, S. A., O’Connell, K., Berluti, K., Ploe, M. L., Elizabeth, H. S., Amormino, P., Li, J., Dutton, M. A., VanMeter, J. W., & Marsh, A. A. (2023) · PNAS Nexus · doi:10.1093/pnasnexus/pgad199 · Cited by 21 · see citing works
Happier than thou? A self-enhancement bias in emotion attribution.
Ong, D. C., Goodman, N. D., & Zaki, J. (2017) · Emotion · doi:10.1037/emo0000309 · Cited by 23 · see citing works
Subjective Cognitive Dysfunction in Patients with Dizziness and Vertigo
Xie, D., Welgampola, M. S., Miller, L. A., Young, A. S., D’Souza, M., Breen, N., & Rosengren, S. M. (2021) · Audiology and Neurotology · doi:10.1159/000518188 · Cited by 24 · see citing works
Summerfield, C. (2022) · doi:10.1093/oso/9780192843883.001.0001 · Cited by 23 · see citing works
Multivariate spatial feature selection in fMRI
Jolly, E., & Chang, L. J. (2021) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsab010 · Cited by 22 · see citing works
Rinaldi, L., Merabet, L. B., Vecchi, T., & Cattaneo, Z. (2018) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2018.04.021 · Cited by 21 · see citing works
Spontaneous Neural Encoding of Social Network PositionPreprint
Parkinson, C. M., Kleinbaum, A. M., & Wheatley, T. P. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/098988 · Cited by 20 · see citing works
Self-citationNeural Mechanisms Underlying Individual Differences in Control-Averse Behavior
Rudorf, S., Schmelz, K., Baumgärtner, T., Wiest, R., Fischbacher, U., & Knoch, D. (2018) · Journal of Neuroscience · doi:10.1523/jneurosci.0047-18.2018 · Cited by 19 · see citing works
Collantoni, E., Meneguzzo, P., Tenconi, E., Meregalli, V., Manara, R., & Favaro, A. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.645139 · Cited by 18 · see citing works
Transforming social perspectives with cognitive maps
Arzy, S., & Kaplan, R. (2022) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsac017 · Cited by 17 · see citing works
Distance-dependent memory for pictures and words
Amit, E., Rim, S., Halbeisen, G., Priva, U. C., Stephan, E., & Trope, Y. (2019) · Journal of Memory and Language · doi:10.1016/j.jml.2019.01.001 · Cited by 18 · see citing works
A unified brain system of orientation and its disruption in Alzheimer’s disease
Dafni‐Merom, A., Peters‐Founshtein, G., Merhavi, S. K., & Arzy, S. (2019) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.50940 · Cited by 18 · see citing works
Du, M., Basyouni, R., & Parkinson, C. M. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118019 · Cited by 19 · see citing works
Self-citationMultivariate Patterns of Posterior Cortical Activity Differentiate Forms of Emotional Distancing
Powers, J. P., Graner, J. L., & LaBar, K. S. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhz273 · Cited by 16 · see citing works
Riemer, M., Achtzehn, J., Kuehn, E., & Wolbers, T. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119336 · Cited by 15 · see citing works
Heterogeneous timescales are spatially represented
Bonato, M., & Umiltà, C. A. (2014) · Frontiers in Psychology · doi:10.3389/fpsyg.2014.00542 · Cited by 15 · see citing works
Altered grid-like coding in early blind people
Sigismondi, F., Xu, Y., Silvestri, M., & Bottini, R. (2024) · Nature Communications · doi:10.1038/s41467-024-47747-x · Cited by 14 · see citing works
Neural defensive circuits underlie helping under threat in humans
Vieira, J. B., & Olsson, A. (2022) · eLife · doi:10.7554/elife.78162 · Cited by 14 · see citing works
Psychological distance intervention reminders reduce alcohol consumption frequency in daily life
Jovanova, M., Cosme, D., Doré, B., Kang, Y., Stanoi, O. A., Cooper, N., Helion, C., Lomax, S., McGowan, A. L., Boyd, Z. M., et al. (2023) · Scientific Reports · doi:10.1038/s41598-023-38478-y · Cited by 14 · see citing works
Neural bases of action abstraction
Quandt, L. C., Lee, Y. S., & Chatterjee, A. K. (2017) · Biological Psychology · doi:10.1016/j.biopsycho.2017.09.015 · Cited by 13 · see citing works
Neurocognitive Evidence for Spatial Contributions to Numerical Cognition
Knops, A. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-811529-9.00011-x · Cited by 13 · see citing works
Nejati, V., Mardanpour, A., Zabihzaheh, A., Estaji, R., Vaziri, Z. S., & Shahidi, S. (2023) · Scientific Reports · doi:10.1038/s41598-023-48099-0 · Cited by 12 · see citing works
Context-sensitive computational mechanistic explanation in cognitive neuroscience
de Wit, M. M., & Matheson, H. E. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.903960 · Cited by 13 · see citing works
Lost in space(s): Multimodal neuroimaging of disorientation along the Alzheimer's disease continuum
Peters‐Founshtein, G., Gazit, L., Naveh, T., Domachevsky, L., Korczyn, A. D., Bernstine, H., Shaharabani‐Gargir, L., Groshar, D., Marshall, G. A., & Arzy, S. (2024) · Human Brain Mapping · doi:10.1002/hbm.26623 · Cited by 10 · see citing works
Mental travel in the person domain
Hayman, M., & Arzy, S. (2021) · Journal of Neurophysiology · doi:10.1152/jn.00695.2020 · Cited by 10 · see citing works
Identifying the Representational Structure of Affect Using fMRI
Mattek, A. M., Burr, D. A., Shin, J., Whicker, C. L., & Kim, M. J. (2020) · Affective Science · doi:10.1007/s42761-020-00007-9 · Cited by 12 · see citing works
Processing of social closeness in the human brain
Roseman, M., Dunbar, R., & Arzy, S. (2024) · Communications Biology · doi:10.1038/s42003-024-06934-8 · Cited by 10 · see citing works
Cernasev, A., Desai, M., Jonkman, L. J., Connor, S. E., Ware, N., Sekar, M. C., & Schommer, J. C. (2021) · Pharmacy · doi:10.3390/pharmacy9040159 · Cited by 10 · see citing works
Koller, S., Müller, N., & Kauschke, C. (2022) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2021.791374 · Cited by 10 · see citing works
Merchant, J. S., Alkire, D. R., & Redcay, E. (2022) · Human Brain Mapping · doi:10.1002/hbm.25903 · Cited by 14 · see citing works
Park, S.-E., Lee, J., & Lee, S. A. (2023) · Journal of Neuroscience · doi:10.1523/jneurosci.0261-23.2023 · Cited by 10 · see citing works
Distance perception warped by social relations: Social interaction information compresses distance
Shao, M., Yin, J., Ji, H., Yang, Y., & Song, F. (2019) · Acta Psychologica · doi:10.1016/j.actpsy.2019.102948 · Cited by 10 · see citing works
Strengths of social ties modulate brain computations for third-party punishment
Tang, Z., Qu, C., Hu, Y., Bénistant, J., Moisan, F., Derrington, E. A., & Dreher, J. (2023) · Scientific Reports · doi:10.1038/s41598-023-37286-8 · Cited by 10 · see citing works
Nook, E. C., Ahn, H. E., Schleider, J. L., & Somerville, L. H. (2024) · Affective Science · doi:10.1007/s42761-024-00269-7 · Cited by 9 · see citing works
How physical information is used to make sense of the psychological world
Liu, S., Akbıyık, S., Outa, J., & Kim, M. J. (2025) · Nature Reviews Psychology · doi:10.1038/s44159-025-00514-1 · Cited by 9 · see citing works
Self-citationStructure Learning and the Parietal CortexPreprint
Summerfield, C., Luyckx, F., & Sheahan, H. (2019) · doi:10.31234/osf.io/zfxj2 · Cited by 9 · see citing works
Naive psychology depends on naive physicsPreprint
Liu, S., Outa, J., & Akbıyık, S. (2024) · doi:10.31234/osf.io/u6xdz · Cited by 9 · see citing works
Self-citationConstrual level shifts integration and segregation of the brain network.
Stillman, P. E., Lu, Z., & Fujita, K. (2019) · Journal of Experimental Psychology General · doi:10.1037/xge0000637 · Cited by 8 · see citing works
Moffat, R., Caruana, N., & Cross, E. S. (2024) · Open Biology · doi:10.1098/rsob.230382 · Cited by 7 · see citing works
- Authors
- Parkinson, C., Liu, S., & Wheatley, T.
- Affiliations
- Dartmouth College (US)
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2014-01-29
- Volume
- 34
- Issue
- 5
- Pages
- 1979-1987
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC6827593
- OpenAlex
- W2056416465
- Semantic Scholar
- 296de32d21658f7b60833ad09ddc6e7ae6dde5af
- 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
- hybrid
- doi.org
- Licence
- 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 › Psychology › Experimental and Cognitive Psychology › 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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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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