Social approach-avoidance conflict: Behavioural, emotional, and neural correlates along a depression-social anxiety spectrum.
The 2 matches · 1 of them tie a paragraph to a whole file, not to given lines: a weak match, whose lines are not tinted
- [1] § Methods › fMRI image acquisition and data analyses ↔ fMRI analysis/Preprocessing/PREPROCESAMIENTO_job.m, the whole file · a weak match · score 0.69 · realigned image, preprocessing, FWHM, MNI, SPM12, smoothed
- [2] § Methods › Emotional response questionnaires ↔ Behavioral analysis/figuras_emocionales_notas.R, lines 22–94 · score 0.51 · 1–2, 3–4, discrete, grade, feedback, emotions
Paper
Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC
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The authors' code
MATLAB · 99 lines · 7.5 KB · no license · 1 match
PREPROCESAMIENTO_job.m, no license · at the source
Overview
- Center for Basic Research in Psychology (CIBPsi), Facultad de Psicología, Universidad de la República, Montevideo, Uruguay
- Sección Neurociencias, Facultad de Ciencias, Universidad de la República, Montevideo, Uruguay
- Instituto de Fundamentos y Métodos en Psicología, Facultad de Psicología, Universidad de la República, Montevideo, Uruguay
- Centro Uruguayo de Imagenología Molecular (CUDIM), Montevideo, Uruguay
- Centro Interdisciplinario de Ciencia de Datos y Aprendizaje Automático (CICADA), Universidad de la República, Montevideo, Uruguay
- Department of Psychology, McGill University, Montreal, Canada
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
Abstract
Approach-avoidance conflict, in which the same option entails both rewarding and aversive consequences, has been proposed as a key process in internalizing disorders such as depression and social anxiety. Yet, human paradigms that model approach-avoidance conflict and link it to brain function remain scarce. In particular, it has been emphasized the need for studying this conflict in social contexts. We developed a Social Approach-Avoidance Conflict (SAAC) task that involved a social evaluative demand manipulation, and combined it with functional magnetic resonance imaging (fMRI) in 135 young adults. On each trial, participants decided whether to accept a variable reward at the cost of increasing the presence of more or less demanding judges in a future public speaking evaluation, or to avoid and receive a minimal default reward. Depression and social anxiety (D-SA) symptoms were summarized into a single continuous dimension derived from principal component analysis of psychological questionnaires. Behaviourally, higher payments increased approach, whereas higher judge ranks increased negative affect and avoidance. Higher D-SA scores were associated with reduced positive and heightened negative emotional responses to higher-rank judges, stronger preferences for low-rank judges, and greater avoidance of high-rank judges. Neurally, increasing judge rank recruited the dmPFC/
Reproduced under the paper's license (CC BY), from the paper cited above.
Repository
Its files are read in the Code ↔ Paper reader above, with 2 matches between paragraphs and lines of code.
OSF uq837
Availability: 1 check, the latest on 26 September 2026: the link answers (HTTP 200)
- 26 September 2026: the link answers (HTTP 200)
18 files, to read at the source
This repository has no license: its authors keep all rights. Read it at the source.
- Behavioral analysis/
analisis_decision_making — R, 82 lines, not shown here_main_model.R - Behavioral analysis/
figuras_emocionales_elec — R, 126 lines, not shown herecion.R - Behavioral analysis/
figuras_emocionales_nota — R, 102 lines, 1 match, not shown heres.R - fMRI analysis/
First levels/ — MATLAB, 21 lines, not shown hereApAv/ compute_contrastes.m - fMRI analysis/
First levels/ — MATLAB, 287 lines, not shown hereApAv/ first_level_job_parametr ic.m - fMRI analysis/
First levels/ — MATLAB, 46 lines, not shown hereApAv/ first_level_parametric.m - fMRI analysis/
First levels/ — MATLAB, 27 lines, not shown hereNoAp/ compute_contrastes.m - fMRI analysis/
First levels/ — MATLAB, 283 lines, not shown hereNoAp/ first_level_job_parametr ic.m - fMRI analysis/
First levels/ — MATLAB, 58 lines, not shown hereNoAp/ first_level_parametric.m - fMRI analysis/
First levels/ — MATLAB, 27 lines, not shown hereNoAv/ compute_contrastes.m - fMRI analysis/
First levels/ — MATLAB, 286 lines, not shown hereNoAv/ first_level_job_parametr ic.m - fMRI analysis/
First levels/ — MATLAB, 59 lines, not shown hereNoAv/ first_level_parametric.m - fMRI analysis/
Preprocessing/ — MATLAB, 30 lines, not shown herePREPROCESAMIENTO.m - fMRI analysis/
Preprocessing/ — MATLAB, 99 lines, 1 match, not shown herePREPROCESAMIENTO_job.m - fMRI analysis/
Second levels/ — MATLAB, 54 lines, not shown hereStandard/ second_level_moldeVickyC uatro.m - fMRI analysis/
Second levels/ — MATLAB, 34 lines, not shown hereStandard/ second_level_moldeVickyC uatro_job.m - fMRI analysis/
Second levels/ — MATLAB, 98 lines, not shown hereWith covariates/ second_level_moldefcoVic ky_nuisancecovsCuatro.m - fMRI analysis/
Second levels/ — MATLAB, 86 lines, not shown hereWith covariates/ second_level_moldefcoVic ky_nuisancecovsCuatro_jo b.m
The paper's code and data availability statement is in the Data section.
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- neither the text of the paper nor the code itself.
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Data
No dataset and no data link were found in the paper.
Data and Code Availability
The data underlying this article cannot be shared publicly because it would require participants to sign an additional consent form, which is not possible to implement at the moment. The code used for the analysis is available at https://
Reproduced under the paper's license (CC BY), from the paper cited above.
Versions
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Version 1, 27 September 2026: the first record
Recorded: type, language, journal, volume, pages, dates, 15 authors, 5 keywords, 16 MeSH terms, 3 funders, 92 references.
Cite
This paper
Cervantes Constantino, F., Acuña, A., Fernandez, C., Guillen, M., Mendaro, L., Brandani, A., Morales, S., Pérez, A., Mattos, J., Cuña, E., García-Fontes, M., Cabana, Á., Armony, J. L., Gaebler, M., & Gradin, V. B. (2026). Social approach-avoidance conflict: Behavioural, emotional, and neural correlates along a depression-social anxiety spectrum. Imaging neuroscience (Cambridge, Mass.), 4, IMAG.a.1363. https://
BibTeX
@article{cervantesconsta
author = {Cervantes Constantino, Francisco and Acuña, Alejo and Fernandez, Catalina and Guillen, Michelle and Mendaro, Laura and Brandani, Antonella and Morales, Sebastián and Pérez, Alfonso and Mattos, Javier and Cuña, Enrique and García-Fontes, Margarita and Cabana, Álvaro and Armony, Jorge L. and Gaebler, Michael and Gradin, Victoria B.},
title = {{Social approach-avoidance conflict: Behavioural, emotional, and neural correlates along a depression-social anxiety spectrum}},
journal = {Imaging neuroscience (Cambridge, Mass.)},
year = {2026},
month = sep,
volume = {4},
pages = {IMAG.a.1363},
publisher = {MIT Press},
issn = {2837-6056},
doi = {10.1162/
url = {https://
pmid = {42729754},
pmcid = {PMC13563531}
}
RIS
TY - JOUR
AU - Cervantes Constantino, Francisco
AU - Acuña, Alejo
AU - Fernandez, Catalina
AU - Guillen, Michelle
AU - Mendaro, Laura
AU - Brandani, Antonella
AU - Morales, Sebastián
AU - Pérez, Alfonso
AU - Mattos, Javier
AU - Cuña, Enrique
AU - García-Fontes, Margarita
AU - Cabana, Álvaro
AU - Armony, Jorge L.
AU - Gaebler, Michael
AU - Gradin, Victoria B.
TI - Social approach-avoidance conflict: Behavioural, emotional, and neural correlates along a depression-social anxiety spectrum
T2 - Imaging neuroscience (Cambridge, Mass.)
J2 - Imaging Neurosci (Camb)
PY - 2026
DA - 2026/
VL - 4
SP - IMAG.a.1363
SN - 2837-6056
PB - MIT Press
DO - 10.1162/
UR - https://
LA - en
ER -
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