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Low-Level Alcohol Consumption in Children 11-12 Years Old Is Linked to Neural Substrates Involved in Reward Processing and Inhibitory Control: Results From a Brain-Wide Association Study.

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  1. [1] § Methods › Neuroimaging ↔ Code/data_managment.R, lines 53–94 · score 0.54 · Desikan cortical, cortical volume, EN, ABCD, MID, neutral

Paper

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The authors' code

R · 156 lines · 9.7 KB · no license · 1 match

  1. require(tidyverse)
  2. require(lme4)
  3. require(parameters)
  5. info <- read.csv('~/Library/CloudStorage/Box-Box/ABCD 5.0/abcd-data-release-5.0/core/abcd-general/abcd_y_lt.csv')
  6. info <- info %>% select(1:4,9)
  7. info$site_id_l <- gsub('\\D','', info$site_id_l)
  8. info$site_id_l <- as.numeric(info$site_id_l)
  9. info_bl <- info[which(info$eventname==c('baseline_year_1_arm_1')),]
  10. info_y2 <- info[which(info$eventname==c('2_year_follow_up_y_arm_1')),]
  11. info_y2 <- info_y2[,c(1:5)] %>% left_join(info_bl[,c(1,4)], by ='src_subject_id')
  12. info_y2 <- info_y2[,-c(4)]
  13. names(info_y2)[names(info_y2)=='rel_family_id.y'] <- 'rel_family_id'
  14. info_y2 <- (info_y2[,c(1:3,5,4)])
  16. demo <- read.csv('~/Library/CloudStorage/Box-Box/ABCD 5.0/abcd-data-release-5.0/core/abcd-general/abcd_p_demo.csv')
  17. demo <- demo %>% select(1:2,9) #keeps sex
  18. demo$demo_sex_v2[demo$demo_sex_v2==3] <- NA
  19. demo_bl <- demo[which(demo$eventname==c('baseline_year_1_arm_1')),]
  20. demo_y2 <- demo[which(demo$eventname==c('2_year_follow_up_y_arm_1')),]
  21. demo_y2 <- demo_y2[,c(1:2)] %>% left_join(demo_bl[,c(1,3)], by = "src_subject_id")
  23. qc <- read.csv('~/Library/CloudStorage/Box-Box/ABCD 5.0/abcd-data-release-5.0/core/imaging/mri_y_qc_incl.csv')
  24. qc_bl <- qc[which(qc$eventname==c('baseline_year_1_arm_1')),]
  25. qc_y2 <- qc[which(qc$eventname==c('2_year_follow_up_y_arm_1')),]
  27. scanner <- mri_y_adm_info <- read.csv('~/Library/CloudStorage/Box-Box/ABCD 5.0/abcd-data-release-5.0/core/imaging/mri_y_adm_info.csv')
  28. scanner <- scanner %>% select(1:2,6)
  29. scanner_bl <- scanner[which(scanner$eventname==c('baseline_year_1_arm_1')),]
  30. scanner_y2 <- scanner[which(scanner$eventname==c('2_year_follow_up_y_arm_1')),]
  32. # sipping baseline
  33. su <- read.csv('~/Library/CloudStorage/Box-Box/ABCD 5.0/abcd-data-release-5.0/core/substance-use/su_y_sui.csv')
  34. su_bl <- su %>% select(1,2,86) #keeps just variable su_isip_1b_2_calc
  35. su_bl <- su_bl[which(su_bl$eventname==c('baseline_year_1_arm_1')),]
  36. names(su_bl)[3] <- 'sip_count'
  38. # sipping combined y1+y2
  39. su_y2 <- su %>% select(1,2,682) #keeps just variable su_isip_1b_calc_l for followups
  40. su_y2 <- su_y2[which(su_y2$eventname==c('2_year_follow_up_y_arm_1')),]
  41. names(su_y2)[3] <- 'sip_count_y2'
  43. su_y1<- su %>% select(1,2,682) #keeps just variable su_isip_1b_calc_l for followups
  44. su_y1 <- su_y1[which(su_y1$eventname==c('1_year_follow_up_y_arm_1')),]
  45. names(su_y1)[3] <- 'sip_count_y1'
  46. su_y1$eventname<- NULL
  48. merged_su_data <- merge(su_y1, su_y2, by = "src_subject_id")
  49. merged_su_data$combined_sips_1_2<- merged_su_data$sip_count_y1 + merged_su_data$sip_count_y2
  50. merged_su_data <- merged_su_data[, -c(2, 4)] #delete distinct Y1 and Y2 columns
  51. names(merged_su_data)[3] <- 'sip_count' #this variable is number of sips in year 1 and 2 combined
  53. # Desikan cortical volume
  54. dsk_vol <- read.csv('~/Library/CloudStorage/Box-Box/ABCD 5.0/abcd-data-release-5.0/core/imaging/mri_y_smr_vol_dsk.csv')
  55. dsk_vol_bl <- dsk_vol[which(dsk_vol$eventname==c('baseline_year_1_arm_1')),]
  56. dsk_vol_y2 <- dsk_vol[which(dsk_vol$eventname==c('2_year_follow_up_y_arm_1')),]
  58. # ASEG cortical volume
  59. aseg_vol <- read.csv('~/Library/CloudStorage/Box-Box/ABCD 5.0/abcd-data-release-5.0/core/imaging/mri_y_smr_vol_aseg.csv')
  60. aseg_vol_bl <- aseg_vol[which(aseg_vol$eventname==c('baseline_year_1_arm_1')),]
  61. aseg_vol_y2 <- aseg_vol[which(aseg_vol$eventname==c('2_year_follow_up_y_arm_1')),]
  63. # MID anticipation of large loss vs neutral
  64. # Desikan
  65. mid_allvn_des<- read.csv("/Users/isabellajackson/Library/CloudStorage/Box-Box/ABCD 5.0/abcd-data-release-5.0/core/imaging/mri_y_tfmr_mid_allvn_dsk.csv")
  66. mid_allvn_des_bl <- mid_allvn_des[which(mid_allvn_des$eventname==c('baseline_year_1_arm_1')),]
  67. mid_allvn_des_y2 <- mid_allvn_des[which(mid_allvn_des$eventname==c('2_year_follow_up_y_arm_1')),]
  69. # ASEG
  70. mid_allvn_aseg<- read.csv("/Users/isabellajackson/Library/CloudStorage/Box-Box/ABCD 5.0/abcd-data-release-5.0/core/imaging/mri_y_tfmr_mid_allvn_aseg.csv")
  71. mid_allvn_aseg_bl <- mid_allvn_aseg[which(mid_allvn_aseg$eventname==c('baseline_year_1_arm_1')),]
  72. mid_allvn_aseg_y2<- mid_allvn_aseg[which(mid_allvn_aseg$eventname==c('2_year_follow_up_y_arm_1')),]
  74. # MID anticipation of large reward vs neutral
  75. # Desikan
  76. mid_alrvn_des<- read.csv("/Users/isabellajackson/Library/CloudStorage/Box-Box/ABCD 5.0/abcd-data-release-5.0/core/imaging/mri_y_tfmr_mid_alrvn_dsk.csv")
  77. mid_alrvn_des_bl <- mid_alrvn_des[which(mid_alrvn_des$eventname==c('baseline_year_1_arm_1')),]
  78. mid_alrvn_des_y2 <- mid_alrvn_des[which(mid_alrvn_des$eventname==c('2_year_follow_up_y_arm_1')),]
  80. # ASEG
  81. mid_alrvn_aseg<-read.csv("/Users/isabellajackson/Library/CloudStorage/Box-Box/ABCD 5.0/abcd-data-release-5.0/core/imaging/mri_y_tfmr_mid_alrvn_aseg.csv")
  82. mid_alrvn_aseg_bl <- mid_alrvn_aseg[which(mid_alrvn_aseg$eventname==c('baseline_year_1_arm_1')),]
  83. mid_alrvn_aseg_y2 <- mid_alrvn_aseg[which(mid_alrvn_aseg$eventname==c('2_year_follow_up_y_arm_1')),]
  85. # EN-back Positive face vs neutral
  86. # Desikan
  87. nback_psfvntf_des<-read.csv("/Users/isabellajackson/Library/CloudStorage/Box-Box/ABCD 5.0/abcd-data-release-5.0/core/imaging/mri_y_tfmr_nback_psfvntf_dsk.csv")
  88. nback_psfvntf_des_bl<- nback_psfvntf_des[which(nback_psfvntf_des$eventname==c('baseline_year_1_arm_1')),]
  89. nback_psfvntf_des_y2<- nback_psfvntf_des[which(nback_psfvntf_des$eventname==c('2_year_follow_up_y_arm_1')),]
  91. # ASEG
  92. nback_psfvntf_aseg<- read.csv("/Users/isabellajackson/Library/CloudStorage/Box-Box/ABCD 5.0/abcd-data-release-5.0/core/imaging/mri_y_tfmr_nback_psfvntf_aseg.csv")
  93. nback_psfvntf_aseg_bl<-nback_psfvntf_aseg[which(nback_psfvntf_aseg$eventname==c('baseline_year_1_arm_1')),]
  94. nback_psfvntf_aseg_y2<- nback_psfvntf_aseg[which(nback_psfvntf_aseg$eventname==c('2_year_follow_up_y_arm_1')),]
  96. # EN-back Negative face vs neutral
  97. # Desikan
  98. nback_ngfvntf_des <-read.csv("/Users/isabellajackson/Library/CloudStorage/Box-Box/ABCD 5.0/abcd-data-release-5.0/core/imaging/mri_y_tfmr_nback_ngfvntf_dsk.csv")
  99. nback_ngfvntf_des_bl<-nback_ngfvntf_des[which(nback_ngfvntf_des$eventname==c('baseline_year_1_arm_1')),]
  100. nback_ngfvntf_des_y2<- nback_ngfvntf_des[which(nback_ngfvntf_des$eventname==c('2_year_follow_up_y_arm_1')),]
  102. # ASEG
  103. nback_ngfvntf_aseg<-read.csv("/Users/isabellajackson/Library/CloudStorage/Box-Box/ABCD 5.0/abcd-data-release-5.0/core/imaging/mri_y_tfmr_nback_ngfvntf_aseg.csv")
  104. nback_ngfvntf_aseg_bl<-nback_ngfvntf_aseg[which(nback_ngfvntf_aseg$eventname==c('baseline_year_1_arm_1')),]
  105. nback_ngfvntf_aseg_y2<- nback_ngfvntf_aseg[which(nback_ngfvntf_aseg$eventname==c('2_year_follow_up_y_arm_1')),]
  108. # T1 weighted white matter
  109. t1_white <- read.csv('~/Library/CloudStorage/Box-Box/ABCD 5.0/abcd-data-release-5.0/core/imaging/mri_y_smr_t1_white_dsk.csv')
  110. t1_white_bl <- dsk_vol[which(dsk_vol$eventname==c('baseline_year_1_arm_1')),]
  111. t1_white_y2 <- dsk_vol[which(dsk_vol$eventname==c('2_year_follow_up_y_arm_1')),]
  113. # T1 wrighted grey matter
  114. t1_grey <- read.csv('~/Library/CloudStorage/Box-Box/ABCD 5.0/abcd-data-release-5.0/core/imaging/mri_y_smr_t1_gray_dsk.csv')
  115. t1_grey_bl <- t1_grey[which(t1_grey$eventname==c('baseline_year_1_arm_1')),]
  116. t1_grey_y2 <- t1_grey[which(t1_grey$eventname==c('2_year_follow_up_y_arm_1')),]
  118. # merging baseline data
  119. combined_bl <- merge(info_bl, demo_bl, id=c('src_subject_id','eventname'))
  120. combined_bl <- merge(combined_bl, qc_bl, id=c('src_subject_id','eventname'))
  121. combined_bl <- merge(combined_bl, scanner_bl, id=c('src_subject_id','eventname'))
  122. combined_bl <- merge(combined_bl, su_bl, id=c('src_subject_id','eventname'))
  123. combined_bl <- merge(combined_bl, dsk_vol_bl, id=c('src_subject_id','eventname'))
  124. combined_bl <- merge(combined_bl,aseg_vol_bl, id=c('src_subject_id','eventname'))
  125. combined_bl<- merge(combined_bl, mid_allvn_des_bl, id=c('src_subject_id','eventname'))
  126. combined_bl<- merge(combined_bl,mid_allvn_aseg_bl, id=c('src_subject_id','eventname'))
  127. combined_bl<- merge(combined_bl,mid_alrvn_des_bl, id=c('src_subject_id','eventname'))
  128. combined_bl<- merge(combined_bl,mid_alrvn_aseg_bl, id=c('src_subject_id','eventname'))
  129. combined_bl<- merge(combined_bl,nback_psfvntf_des_bl, id=c('src_subject_id','eventname'))
  130. combined_bl<- merge(combined_bl,nback_psfvntf_aseg_bl, id=c('src_subject_id','eventname'))
  131. combined_bl<- merge(combined_bl,nback_ngfvntf_des_bl, id=c('src_subject_id','eventname'))
  132. combined_bl<- merge(combined_bl,nback_ngfvntf_aseg_bl, id=c('src_subject_id','eventname'))
  133. combined_bl <- merge(combined_bl,t1_white_bl, id=c('src_subject_id','eventname'))
  134. combined_bl <- merge(combined_bl,t1_grey_bl, id=c('src_subject_id','eventname'))
  136. # merging year 2 data (sipping is y1 +y2)
  137. combined_y2 <- merge(info_y2, demo_y2, id=c('src_subject_id','eventname'))
  138. combined_y2 <- merge(combined_y2, qc_y2, id=c('src_subject_id','eventname'))
  139. combined_y2 <- merge(combined_y2, scanner_y2, id=c('src_subject_id','eventname'))
  140. combined_y2 <- merge(combined_y2, merged_su_data, id=c('src_subject_id','eventname'))
  141. combined_y2 <- merge(combined_y2, dsk_vol_y2, id=c('src_subject_id','eventname'))
  142. combined_y2 <- merge(combined_y2, aseg_vol_y2, id=c('src_subject_id','eventname'))
  143. combined_y2 <- merge(combined_y2, mid_allvn_des_y2, id=c('src_subject_id','eventname'))
  144. combined_y2 <- merge(combined_y2, mid_allvn_aseg_y2, id=c('src_subject_id','eventname'))
  145. combined_y2 <- merge(combined_y2, mid_alrvn_des_y2, id=c('src_subject_id','eventname'))
  146. combined_y2 <- merge(combined_y2, mid_alrvn_aseg_y2, id=c('src_subject_id','eventname'))
  147. combined_y2 <- merge(combined_y2, nback_psfvntf_des_y2, id=c('src_subject_id','eventname'))
  148. combined_y2 <- merge(combined_y2, nback_psfvntf_aseg_y2, id=c('src_subject_id','eventname'))
  149. combined_y2 <- merge(combined_y2, nback_ngfvntf_des_y2, id=c('src_subject_id','eventname'))
  150. combined_y2 <- merge(combined_y2, nback_ngfvntf_aseg_y2, id=c('src_subject_id','eventname'))
  152. # tossing cases that didn't pass QC
  153. combined_bl <- combined_bl[which(combined_bl$imgincl_t1w_include==1),]
  154. combined_y2 <- combined_y2[which(combined_y2$imgincl_t1w_include==1),]

data_managment.R, no license · at the source

Overview

Authors: Isabella F Jackson1, Francisco A C Meyer2, Ryan M Sullivan3, Ashley L Watts1
ORCID iDs: Isabella F Jackson, Francisco A C Meyer, Ryan M Sullivan
  1. Department of Psychological Sciences, Vanderbilt University, Nashville, Tennessee, USA
  2. Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, USA
  3. Department of Psychiatry, University of California, San Diego, California, USA
Institutions: Vanderbilt University (United States); Yale University (United States); University of California San Diego (United States)
Journal: Alcohol, clinical & experimental research, volume 50, issue 7, article e70370
Dates: received 19 September 2025; accepted 26 June 2026; published online 9 July 2026; in print July 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1111/acer.70370 · PMID 42423002 · PMCID PMC13347280 · OpenAlex W7167822535
Open access: hybrid, a free copy (OpenAlex)
Status: code verified
Categories: human (organism), other condition (population)
Methods: Statistics, fMRI & imaging
Keywords: adolescent development, alcohol use, neuroimaging
MeSH: Alcohol Drinking*, Brain*, Inhibition, Psychological*, Reward*, Child, Cross-Sectional Studies, Female, Humans, Magnetic Resonance Imaging, Male, Prospective Studies (* major topic)
Topic: Substance Abuse Treatment and Outcomes (Epidemiology, Medicine), according to OpenAlex
Funding: National Institute on Alcohol Abuse and Alcoholism (R00AA028306); NIAAA NIH HHS (R00AA028306)
Citations: not cited yet (Europe PMC); 66 references in the paper

Abstract

Background: We comprehensively examined the cross‐sectional and prospective structural (i.e., cortical volume and subcortical volume) and functional (i.e., activation during the Monetary Incentive Delay task and the emotional N‐back task) neural correlates of alcohol sipping in early adolescence across two waves of data from the Adolescent Brain Cognitive Development (ABCD) Study (baseline: ages 9–10, n = 7555; 2‐year follow‐up: ages 11–12, n = 5892).

Methods: Generalized linear mixed models examined individual brain regions of interests' ability to predict alcohol sipping.

Results: At the 2‐year follow‐up, sipping was associated with activation during the MID large reward versus neutral contrast in 12 regions (e.g., nucleus accumbens), and activation during the MID large loss versus neutral contrast in 13 regions (e.g., insula).

Conclusions: These findings aligned with existing literature on alcohol consumption, with neural regions involved in reward and inhibitory control being associated with alcohol sipping. Given that the findings from year 2 mirror several well‐established neural correlates of alcohol use and alcohol use disorder in adults, alcohol sipping may be an important phenotype for predicting future alcohol involvement.

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 1 match between paragraphs and lines of code.

OSF nshfb

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Languages: R (11)
Size: 21 files, 11 scripts
Software Heritage: not checked
Found in: “Data Availability Statement”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: easystats (11 files), lme4 (11 files), tidyverse (11 files), emmeans (10 files)
Availability: 1 check, the latest on 27 September 2026: the link answers (HTTP 200)
  • 27 September 2026: the link answers (HTTP 200)
11 files
At the source: doi.org/10.17605/OSF.IO/NSHFB

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;
  • 11 scripts, each with its path and the digest of its content;
  • 1 match between paragraphs of the paper and lines of the code (method lexical-v1);
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

No dataset and no data link were found in the paper.

Data Availability Statement

Data used in the preparation of this article were obtained from the Adolescent Brain Cognitive Study (ABCD; https://abcdstudy.org), held in the NIMH Data Archive (NDA). This is a multisite, longitudinal study designed to recruit more than 10,000 children aged 9–10 and follow them over 10 years into early adulthood. The ABCD study is supported by the National Institutes of Health and additional federal partners under award numbers U01DA041048, U01DA050989, U01DA051016, U01DA041022, U01DA051018, U01DA051037, U01DA050987, U01DA041174, U01DA041106, U01DA041117, U01DA041028, U01DA041134, U01DA050988, U01DA051039, U01DA041156, U01DA041025, U01DA041120, U01DA051038, U01DA041148, U01DA041093, U01DA041089, U24DA041123, U24DA041147. A full list of supporters is available at https://abcdstudy.org/federal‐partners.html (https://abcdstudy.org/federal-partners.html). A listing of participating sites and a complete listing of the study investigators can be found at https://abcdstudy.org/consortium_members/. ABCD consortium investigators designed and implemented the study and/or provided data but did not necessarily participate in the analysis or writing of this report. This manuscript reflects the views of the authors and may not reflect the opinions or views of the NIH or ABCD consortium investigators. The ABCD data repository grows and changes over time. The ABCD data used in this report came from DOI: 10.15154/8873‐zj65. The code necessary to reproduce the analyses presented here are publicly accessible: https://doi.org/10.17605/OSF.IO/NSHFB.

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

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 2, 28 September 2026

  • Publisher: n/a → Wiley

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 4 authors, 3 keywords, 11 MeSH terms, 2 funders, 62 references.

Cite

This paper

Jackson, I. F., Meyer, F. A. C., Sullivan, R. M., & Watts, A. L. (2026). Low-Level Alcohol Consumption in Children 11-12 Years Old Is Linked to Neural Substrates Involved in Reward Processing and Inhibitory Control: Results From a Brain-Wide Association Study. Alcohol, clinical & experimental research, 50(7), e70370. https://doi.org/10.1111/acer.70370

BibTeX

@article{jackson2026low,
author = {Jackson, Isabella F and Meyer, Francisco A C and Sullivan, Ryan M and Watts, Ashley L},
title = {{Low-Level Alcohol Consumption in Children 11-12 Years Old Is Linked to Neural Substrates Involved in Reward Processing and Inhibitory Control: Results From a Brain-Wide Association Study}},
journal = {Alcohol, clinical \& experimental research},
year = {2026},
month = jul,
volume = {50},
number = {7},
pages = {e70370},
publisher = {Wiley},
issn = {2993-7175},
doi = {10.1111/acer.70370},
url = {https://doi.org/10.1111/acer.70370},
pmid = {42423002},
pmcid = {PMC13347280}
}

RIS

TY - JOUR
AU - Jackson, Isabella F
AU - Meyer, Francisco A C
AU - Sullivan, Ryan M
AU - Watts, Ashley L
TI - Low-Level Alcohol Consumption in Children 11-12 Years Old Is Linked to Neural Substrates Involved in Reward Processing and Inhibitory Control: Results From a Brain-Wide Association Study
T2 - Alcohol, clinical & experimental research
J2 - Alcohol Clin Exp Res (Hoboken)
PY - 2026
DA - 2026/07/01
VL - 50
IS - 7
SP - e70370
SN - 2993-7175
PB - Wiley
DO - 10.1111/acer.70370
UR - https://doi.org/10.1111/acer.70370
LA - en
ER -

CSL-JSON

{
"id": "10.1111/acer.70370",
"type": "article-journal",
"title": "Low-Level Alcohol Consumption in Children 11-12 Years Old Is Linked to Neural Substrates Involved in Reward Processing and Inhibitory Control: Results From a Brain-Wide Association Study",
"container-title": "Alcohol, clinical & experimental research",
"author": [
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"family": "Jackson",
"given": "Isabella F"
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{
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"given": "Ashley L"
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],
"container-title-short": "Alcohol Clin Exp Res (Hoboken)",
"volume": "50",
"issue": "7",
"page": "e70370",
"DOI": "10.1111/acer.70370",
"PMID": "42423002",
"PMCID": "PMC13347280",
"ISSN": "2993-7175",
"publisher": "Wiley",
"URL": "https://doi.org/10.1111/acer.70370",
"language": "en",
"issued": {
"date-parts": [
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2026,
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1
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]
}
}

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[5] doi:10.1111/jcpp.70178 [code]
What makes a lonely child: environmental, health, and multimodal neuroimaging correlates of prospective loneliness in the ABCD study.
Journal: Journal of child psychology and psychiatry, and allied disciplines
In common: easystats, lme4, tidyverse, 4 references
[6] doi:10.1002/hbm.70512 [code]
Precision Imaging for Intraindividual Investigation of the Reward Response.
Journal: Human brain mapping
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[7] doi:10.1038/s41398-026-04045-y [code]
Physical-Digital and social-nonsocial extracurricular engagement: differential effects on brain development and psychological outcomes in children.
Journal: Translational psychiatry
In common: lme4, tidyverse, 5 references
[8] doi:10.1038/s41467-026-73072-6 [code]
Mapping the spatiotemporal continuum of structural connectivity development across the human connectome in youth.
Journal: Nature communications
In common: easystats, lme4, tidyverse, 3 references
[9] doi:10.1038/s41467-026-73262-2 [code]
Robust but independent sex differences in human brain function, structure, and behavior.
Journal: Nature communications
In common: easystats, lme4, tidyverse, 3 references
[10] doi:10.1093/cercor/bhag034 [code]
Individual differences in adolescent cortical development are associated with neighborhood characteristics: Longitudinal findings from the ABCD study.
Journal: Cerebral cortex (New York, N.Y. : 1991)
In common: tidyverse, 5 references

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