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Regretting a chance to connect: How neural responses to missed social opportunities predict self-disclosure.

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The authors' code

R · 166 lines · 8 KB · no license

  1. ## LOADING PACKAGES
  2. # library(lme4) # mlm
  3. library(nlme)
  4. library(lmerTest) # mlm stats
  5. library(performance) # mlm icc
  6. library(interactions) # mlm
  7. library(r2mlm) # mlm
  8. library(ggplot2) # data visualization
  9. library(ggstatsplot) # data visualization
  10. library(ggeffects) # data visualization
  11. library(psych) # describe data
  12. library(dplyr) # data wrangling
  13. library(tidyverse) # data wrangling
  14. library(reshape2) # data reshaping
  15. library(plyr)
  16. library(expss)
  17. library(DescTools)
  18. library(cowplot) # plot annotation
  19. library(emmeans)
  20. library(interactions)
  21. library(lavaan)
  22. library(multcomp)
  24. ## LOADING
  25. disc_df <- read.csv('/Users/seh-jookwon/Documents/Rutgers/Projects/SocialConnections/3-analysis/for-osf/disc1-avg.csv',header=T)
  26. disc <- disc_df
  27. disc2_df <- read.csv('/Users/seh-jookwon/Documents/Rutgers/Projects/SocialConnections/3-analysis/for-osf/disc2-trial-level.csv',header=T)
  28. disc2 <- disc2_df
  29. disc3_df <- read.csv('/Users/seh-jookwon/Documents/Rutgers/Projects/SocialConnections/3-analysis/for-osf/disc3-trial-level-regret-only.csv',header=T)
  30. disc3 <- disc3_df
  31. disc4_df <- read.csv('/Users/seh-jookwon/Documents/Rutgers/Projects/SocialConnections/3-analysis/for-osf/disc4-trial-level-closeness-only.csv',header=T)
  32. disc4 <- disc4_df
  33. disc5_df <- read.csv('/Users/seh-jookwon/Documents/Rutgers/Projects/SocialConnections/3-analysis/for-osf/disc5-intimacy.csv',header=T)
  34. disc5 <- disc5_df
  35. --------------------------------------------------------------------------------
  36. ## DESCRIPTIVE STATS
  37. # share vs. hide (behav. differences)
  38. svh <- t.test(disc$Share_Prop, mu = 0.5, alternative = "greater")
  39. svh
  41. # share vs. hide (reaction time differences)
  42. rt <- t.test(disc$Share_RT, disc$Hide_RT, paired = TRUE)
  43. rt
  44. --------------------------------------------------------------------------------
  45. ## QUESTION 1
  46. # Q1A: does closeness increase across trials?
  47. summary(q1a <- lme(Closeness ~ Trial + Version,
  48. data = disc4,
  49. random = ~ Trial|id,
  50. method = "ML",
  51. control= lmeControl(opt = "optim", maxIter = 200, msMaxIter = 200,
  52. niterEM = 50, msMaxEval = 400, msVerbose = FALSE),
  53. na.action = na.exclude))
  55. # saving each person's rate of change in closeness
  56. coef <- coef(q1a)
  58. # does rate of change in closeness predict later cooperation behavior (in prisoner's dilemma)?
  59. summary(coop <- lm(Share_Prop ~ ClosenessRate,data = disc))
  61. # Q1B: closeness development + number of various interaction types (share-share, share-hide, hide-share, hide-hide)
  62. summary(int_close <- lm(ClosenessRate ~ HS_Count,data = disc))
  63. --------------------------------------------------------------------------------
  64. ## QUESTION 2
  65. # Q2A: how interaction type predicts subsequent decision-making
  66. # model has singularity issues if interaction type is added as a random effect
  67. disc2$Int_Type <- as.factor(disc2$Int_Type)
  68. summary(q2a <- glmer(Share_Next ~ Int_Type + (1 | id),
  69. data = disc2, family = binomial, nAGQ=1, na.action = na.omit,
  70. control = glmerControl(optimizer = "bobyqa",optCtrl=list(maxfun=2e5))))
  72. # posthoc (pairwise comparisons)
  73. contrasts_q2a <- rbind("hs-sh" = c(0,-1,1,0),
  74. "hh-sh"= c(0,-1,0,1),
  75. "hh-hs"= c(0,0,-1,1))
  76. summary(glht(q2a,contrasts_q2a),test=adjusted("bonferroni"))
  78. # Q2B: the effect of interaction type on subsequent decision-making across trials
  79. summary(q2b <- glmer(Share_Next ~ Int_Type*Trial + (1 | id),
  80. data = disc2, family = binomial, nAGQ=1, na.action = na.omit,
  81. control = glmerControl(optimizer = "bobyqa",optCtrl=list(maxfun=2e5))))
  83. # posthoc (simple effects)
  84. contrasts_q2b <- rbind("sh_trial"= c(0,0,0,0,1,1,0,0),
  85. "hs_trial" = c(0,0,0,0,1,0,1,0),
  86. "hh_trial"= c(0,0,0,0,1,0,0,1))
  87. summary(glht(q2b,contrasts_q2b),test=adjusted("bonferroni"))
  89. # posthoc (pairwise comparisons)
  90. contrasts_q2b_trial <- rbind("sh_trial-hs_trial"= c(0,0,0,0,0,1,-1,0),
  91. "sh_trial-hh_trial" = c(0,0,0,0,0,1,0,-1),
  92. "hs_trial-hh_trial"= c(0,0,0,0,0,0,1,-1))
  93. summary(glht(q2b,contrasts_q2b_trial),test=adjusted("bonferroni"))
  94. --------------------------------------------------------------------------------
  95. ## QUESTION 3
  96. # Q3A: regret across interaction types
  97. disc3$Int_Type <- as.factor(disc3$Int_Type)
  98. q3a <- lmer(Regret ~ Int_Type + (1 | Subject), data = disc3)
  99. summary(q3a)
  101. # posthoc (pairwise comparisons)
  102. emm <- emmeans(q3a, ~ Int_Type)
  103. pairs(emm, adjust = "bonferroni")
  105. # Q3B: regret + subsequent behavioral change
  106. summary(q3b <- glmer(Behav_Change_Next ~ Regret + (1 | id),
  107. data = disc2, family = binomial, nAGQ=1, na.action = na.omit,
  108. control = glmerControl(optimizer = "bobyqa",optCtrl=list(maxfun=2e5))))
  110. summary(q3b_2 <- glmer(Behav_Change_Next ~ Regret + (1 + Regret | id),
  111. data = disc2, family = binomial, nAGQ=1, na.action = na.omit,
  112. control = glmerControl(optimizer = "bobyqa",optCtrl=list(maxfun=2e5))))
  114. # picking the best-fit model (q3b_2 is better!)
  115. anova(q3b,q3b_2)
  117. # whether the effect of regret on behavioral changes depend on the context / interaction type
  118. summary(q3b_3 <- glmer(Behav_Change_Next ~ Regret*Int_Type + (1 + Regret | id),
  119. data = disc2, family = binomial, nAGQ=1, na.action = na.omit,
  120. control = glmerControl(optimizer = "bobyqa",optCtrl=list(maxfun=2e5))))
  122. # posthoc (pairwise comparisons)
  123. contrasts_q3b <- rbind("sh-hs"= c(0,0,0,0,0,1,-1,0),
  124. "sh-hh" = c(0,0,0,0,0,1,0,-1),
  125. "hs-hh"= c(0,0,0,0,0,0,1,-1))
  126. summary(glht(q3b_3,contrasts_q3b),test=adjusted("bonferroni"))
  127. --------------------------------------------------------------------------------
  128. ## EXPLORATORY: intimacy
  129. # behavioral differences
  130. explor1.1 <- t.test(disc$Share_High_Prop,disc$Share_Low_Prop,paired=TRUE)
  131. explor1.1
  133. # reaction time differences
  134. explor1.2 <- lmer(AvgRT ~ Intimacy*Decision + (1 | Subject), data = disc5)
  135. summary(explor1.2)
  137. # regret differences
  138. explor1.3 <- t.test(disc$Regret_High,disc$Regret_Low,paired=TRUE)
  139. explor1.3
  140. --------------------------------------------------------------------------------
  141. ## EXPLORATORY: interaction type -> behavioral change
  142. summary(explor2.1 <- glmer(Behav_Change_Next ~ Int_Type + (1 | id),
  143. data = disc2, family = binomial, nAGQ=1, na.action = na.omit,
  144. control = glmerControl(optimizer = "bobyqa",optCtrl=list(maxfun=2e5))))
  146. # posthoc (pairwise comparisons)
  147. contrasts_explor2.1 <- rbind("hs-sh" = c(0,-1,1,0),
  148. "hh-sh"= c(0,-1,0,1),
  149. "hh-hs"= c(0,0,-1,1))
  150. summary(glht(explor2.1,contrasts_explor2.1),test=adjusted("bonferroni"))
  151. --------------------------------------------------------------------------------
  152. ## EXPLORATORY: brain + behavior links
  153. # mpfc + dmpfc estimates -> trial-level likelihood of sharing
  154. summary(explor3.1 <- glmer(Participant_Decision ~ SS_MPFC_Z + SH_MPFC_Z + HS_MPFC_Z + HH_MPFC_Z + (1 | id),
  155. data = disc2, family = binomial, nAGQ=1, na.action = na.omit,
  156. control = glmerControl(optimizer = "bobyqa",optCtrl=list(maxfun=2e5))))
  158. # mpfc + dmpfc estimates -> trial-level likelihood of sharing
  159. summary(explor3.2 <- glmer(Participant_Decision ~ SS_LPSTS_Z + SH_LPSTS_Z + HS_LPSTS_Z + HH_LPSTS_Z + (1 | id),
  160. data = disc2, family = binomial, nAGQ=1, na.action = na.omit,
  161. control = glmerControl(optimizer = "bobyqa",optCtrl=list(maxfun=2e6))))
  162. --------------------------------------------------------------------------------
  163. ## EXPLORATORY: linking disclosure task + willingness-to-pay task
  164. disc <- disc %>% mutate(value = WTP_Share_Hide_Partner - WTP_Share_Hide_Stranger)
  165. summary(explor4.1 <- lm(value ~ SS_MPFC_Z + SH_MPFC_Z + HS_MPFC_Z + HH_MPFC_Z,data = disc))
  166. summary(explor4.2 <- lm(value ~ SS_LPSTS_Z + SH_LPSTS_Z + HS_LPSTS_Z + HH_LPSTS_Z,data = disc))

disclosure.R, no license · at the source

Overview

Authors: Seh-Joo Kwon1, Casey M Nicastri1, Jamil P Bhanji1, Mauricio R Delgado1
ORCID iDs: Seh-Joo Kwon, Jamil P Bhanji
  1. Department of Psychology, Rutgers University—Newark, 101 Warren St, Newark, NJ 07103, USA
Institutions: Rutgers, The State University of New Jersey (United States)
Journal: PNAS nexus, volume 5, issue 5, article pgag138
Dates: received 17 December 2025; accepted 8 April 2026; published online 24 April 2026
Type: Research article · Language: English
License: CC BY-NC
Identifiers: DOI 10.1093/pnasnexus/pgag138 · PMID 42137770 · PMCID PMC13168892 · OpenAlex W7155524348
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: fMRI (modality), human (organism), cognitive (subfield)
Methods: fMRI & imaging
Keywords: fMRI, information valuation, regret, self-disclosure, social connection
Journal subjects: Social and Political Sciences, Psychological and Cognitive Sciences
Topic: Attachment and Relationship Dynamics (Social Psychology, Psychology), according to OpenAlex
Funding: NIH (R01DA053311)
Citations: not cited yet (Europe PMC); 42 references in the paper

Abstract

Humans value communicating information about themselves to others, and exchanges of such information between two individuals are fundamental to social bond formation. Yet, people often keep information private, potentially forfeiting the chance to connect with someone new. In this preregistered functional MRI study, participants who experienced more missed social opportunities in an iterative self-disclosure task—or instances where withholding information was met with an ostensible partner's self-disclosure—tended to feel closer to this partner faster. Missed social opportunities were regrettable and most likely followed by a change in subsequent decisions, making participants switch from withholding to sharing their information. Using conjunction analysis, activities in the medial prefrontal cortex and posterior superior temporal sulcus (pSTS), regions implicated in social-cognitive processes, were greater in response to missed social opportunities than in response to other social interactions (e.g. mutual self-disclosure). Notably, greater pSTS responses to missed social opportunities were linked to a higher likelihood of disclosing to a partner, as well as a higher amount of money willing to be spent to disclose to a partner in a follow-up task, highlighting the role of the pSTS in predicting a sustained interest in the new partner. Our findings elucidate the neurobiological, affective, and behavioral attributes of forgone moments of connection that contribute to interpersonal closeness development. We further identify context-dependent pSTS activities that support closeness-generating behaviors like self-disclosure.

Reproduced under the paper's license (CC BY-NC), from the paper cited above.

Repository

Its files are read in the Code ↔ Paper reader above.

OSF yxtwb

License: none: the authors keep all their rights
State: the link answers, verified on 29 September 2026
Evidence: files inventoried
Languages: R (1)
Size: 8 files, 1 script
Software Heritage: not checked
Found in: “Data Availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: cowplot (1 file), easystats (1 file), emmeans (1 file), ggplot2 (1 file), lavaan (1 file), lmerTest (1 file), multcomp (1 file), nlme (1 file), psych (1 file), reshape2 (1 file), tidyverse (1 file)
Availability: 1 check, the latest on 29 September 2026: the link answers (HTTP 200)
  • 29 September 2026: the link answers (HTTP 200)
1 file
At the source: osf.io/yxtwb/

The paper's code and data availability statement is in the Data section.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 1 script, each with its path and the digest of its content;
  • no match between paragraphs and code yet;
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Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

Datasets cited

Data Availability

The preregistration, de-identified behavioral data, and data analyses codes are available on OSF (https://osf.io/yxtwb/). Whole-brain group-level contrasts are available on Neurovault (https://neurovault.org/collections/21797/).

Reproduced under the paper's license (CC BY-NC), from the paper cited above.

Versions

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Version 1, 29 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 4 authors, 5 keywords, 1 funder, 31 references.

Cite

This paper

Kwon, S.-J., Nicastri, C. M., Bhanji, J. P., & Delgado, M. R. (2026). Regretting a chance to connect: How neural responses to missed social opportunities predict self-disclosure. PNAS nexus, 5(5), pgag138. https://doi.org/10.1093/pnasnexus/pgag138

BibTeX

@article{kwon2026regretting,
author = {Kwon, Seh-Joo and Nicastri, Casey M and Bhanji, Jamil P and Delgado, Mauricio R},
title = {{Regretting a chance to connect: How neural responses to missed social opportunities predict self-disclosure}},
journal = {PNAS nexus},
year = {2026},
month = apr,
volume = {5},
number = {5},
pages = {pgag138},
publisher = {Oxford University Press},
issn = {2752-6542},
doi = {10.1093/pnasnexus/pgag138},
url = {https://doi.org/10.1093/pnasnexus/pgag138},
pmid = {42137770},
pmcid = {PMC13168892}
}

RIS

TY - JOUR
AU - Kwon, Seh-Joo
AU - Nicastri, Casey M
AU - Bhanji, Jamil P
AU - Delgado, Mauricio R
TI - Regretting a chance to connect: How neural responses to missed social opportunities predict self-disclosure
T2 - PNAS nexus
J2 - PNAS Nexus
PY - 2026
DA - 2026/04/24
VL - 5
IS - 5
SP - pgag138
SN - 2752-6542
PB - Oxford University Press
DO - 10.1093/pnasnexus/pgag138
UR - https://doi.org/10.1093/pnasnexus/pgag138
LA - en
ER -

CSL-JSON

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