OSCR

Progression from mild cognitive impairment to dementia in Alzheimer's disease: Whole cortex voxelwise functional connectivity analysis with multivariate distance matrix regression.

Code ↔ Paper

The paper beside its authors' code: matches between them have not been computed for this paper yet.

Paper

Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC

The paper is loaded when this pane is shown.

The authors' code

R · 89 lines · 2.4 KB · GPL-3.0

  1. # helper files for the main script
  3. load_csv_summarize_columns <- function(file_path, verbose = TRUE) {
  4. # Read the CSV file
  5. df <- read.csv(file_path, stringsAsFactors = TRUE)
  7. # Build and print the summary data frame
  8. if (verbose) {
  9. # Build the summary data frame
  10. summary_df <- data.frame(
  11. Column = names(df),
  12. Type = sapply(df, function(x) class(x)[1]),
  13. Levels = sapply(df, function(x) if (is.factor(x)) paste(levels(x), collapse = ", ") else NA),
  14. stringsAsFactors = FALSE
  15. )
  17. # Print the summary
  18. print(summary_df)
  19. }
  21. return(df)
  22. }
  25. extract_vxl_idx_from_fpath <- function(file_path) {
  26. # Extract the part after the last slash
  27. file_name <- basename(file_path)
  29. # Capture the voxel index numbers
  30. numbers <- regmatches(file_name, regexpr("\\d+_\\d+_\\d+", file_name))
  32. # Return the individual index numbers
  33. numbers_split <- unlist(strsplit(numbers, "_"))
  34. return(as.numeric(numbers_split))
  35. }
  39. read_vxl_fc_data <- function(fpath, ncores, subsample_idx = NULL) {
  40. # Read the CSV file with FC data (no header, rows = participants, cols = connections)
  41. vxl_fc <- as.matrix(
  42. data.table::fread(
  43. fpath,
  44. header = FALSE,
  45. data.table = FALSE,
  46. nThread = ncores
  47. )
  48. )
  49. # subsample
  50. if (!is.null(subsample_idx)) {
  51. vxl_fc <- vxl_fc[subsample_idx, , drop = FALSE]
  52. }
  53. # Extract voxel index from file path and ensure it is named (i, j, k)
  54. vxl_idx <- extract_vxl_idx_from_fpath(fpath)
  55. vxl_idx <- setNames(as.numeric(vxl_idx), c("i", "j", "k"))
  56. # Return both as a named list
  57. return(list(
  58. vxl_fc = vxl_fc,
  59. vxl_idx = vxl_idx
  60. ))
  61. }
  67. run_mdmr <- function(fpath, X, ncores = 1, nperm = 10000, distance_method = 'manhattan', y_row_indices=NULL) {
  68. # Runs MDMR for a single voxel's FC file.
  69. # Returns a named numeric vector: voxel indices (i, j, k) followed by the whole result of MDMR
  71. # Load voxel-level FC data
  72. vxl_data <- read_vxl_fc_data(fpath=fpath, ncores=ncores, subsample_idx=y_row_indices)
  73. vxl_zcc <- vxl_data$vxl_fc
  74. vxl_idx <- vxl_data$vxl_idx
  76. # Number of rows in X and vxl_zcc should match
  77. if (nrow(X) != nrow(vxl_zcc)) {
  78. stop("Mismatch between X and voxel FC rows.")
  79. }
  81. # Compute distance between participants
  82. D <- dist(vxl_zcc, method = distance_method)
  84. # Run MDMR
  85. res <- mdmr(X = X, D = D, ncores = ncores, nperm = nperm, perm.p = TRUE)
  87. # Return voxel indices and the whole mdmr results
  88. return(c(vxl_idx, res))
  89. }

helper_functions.R at commit 2e3e2a1, under GPL-3.0 · at the source

Overview

Authors: Luiz Kobuti Ferreira1,2, Eric Westman1,3, Lars-Olof Wahlund1, Rosaleena Mohanty1,3, for the Alzheimer's Disease Neuroimaging Initiative
ORCID iDs: Luiz Kobuti Ferreira, Rosaleena Mohanty
  1. Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
  2. Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm Health Care Services, Region Stockholm, Sweden
  3. The Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, London, UK
Institutions: Karolinska Institutet (Sweden); Imperial College London (United Kingdom)
Journal: Journal of Alzheimer's disease : JAD, volume 113, issue 3, pages 1384-1395
Dates: received 11 February 2026; accepted 4 July 2026; published online 12 August 2026; in print August 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1177/13872877261477016 · PMID 42585347 · PMCID PMC13583079 · OpenAlex W7202299544
Open access: hybrid, a free copy (OpenAlex)
Status: code verified
Categories: fMRI (modality), human (organism), Alzheimer's / dementia (population), systems (subfield)
Methods: Connectivity, Statistics, Smoothing, state filtering, decompositions, Preprocessing, Machine learning, fMRI & imaging
Keywords: Alzheimer's disease, functional connectivity, functional neuroimaging, mild cognitive impairment
Topic: Functional Brain Connectivity Studies (Cognitive Neuroscience, Neuroscience), according to OpenAlex
Funding: Vetenskapsrådet (2021-01861, 2025-02405, 2016-02282); EU Innovative Health Initiative Joint Undertaking (IHI JU) AD-RIDDLE and ACCESS-AD; VINNOVA (2025-03749); Olle Engkvists Stiftelse (224-0069, 186-0660); Hjärnfonden (FO2024-0239, FO2022-0084); the regional agreement on medical training and clinical research (ALF) between Stockholm County Council and Karolinska Institutet (FoUI-952838, FoUI-954893); The Strategic Research Programme in Neuroscience at Karolinska Institutet; Parkinsonfonden (1521/23, 1557/24, 1647/25); Alzheimerfonden (AF-967495, AF-1031812, AF-980387); Center for Innovative Medicine (FoUI-954459, FoUI-975174, FoUI-987392); Svenska Sällskapet för Medicinsk Forskning (PD21-0042); Åke Wiberg Stiftelse; King Gustaf V:s and Queen Victorias Foundation; Stiftelsen Lars Hiertas Minne; Neurofonden; NIA NIH HHS (U19 AG024904); Birgitta and Sten Westerberg; Demensfonden; Gun och Bertil Stohnes Stiftelse; Karolinska Institutet Research Grants; The Foundation for Old Maids
Citations: not cited yet (Europe PMC); 58 references in the paper

Abstract

Background: Differentiating individuals with mild cognitive impairment who convert to dementia due to Alzheimer's disease (MCI-C) from those who do not convert (MCI-NC) is increasingly important. Functional connectivity (FC) derived from resting state functional MRI (rs-fMRI) has been investigated as a potential biomarker. However, improved data analysis strategies are needed. One underexplored approach is pairwise voxel-to-voxel analysis.

Objective: To describe differences in FC between amyloid positive MCI-C and MCI-NC using a whole-cortex voxel-to-voxel pairwise approach.

Methods: Baseline rs-fMRI from the Alzheimer's Disease Neuroimaging Initiative was retrieved for amyloid positive MCI participants. Voxel-to-voxel, pairwise, cortical FC was computed. Multivariate distance matrix regression was used to identify voxels presenting FC patterns that were significantly different between MCI-C and MCI-NC.

Results: 21 MCI-C and 28 MCI-NC were included. The primary analysis with voxel-level threshold at p < 0.001 combined with cluster-level p < 0.05 yielded no significant results. At voxel-level p < 0.01 and the same cluster-level threshold, three significant clusters on the right visual cortex were found. These clusters, however, were not robust to head motion, fMRI protocol and additionally clinical or biological severity.

Conclusions: Progression from Alzheimer-related MCI to dementia was not significantly associated with FC in the primary analysis. However, a less stringent threshold yielded FC differences in the occipital lobe in alignment with previous studies but were not robust to methodological and biological covariates between groups. Our findings highlight the need for larger samples and careful control of covariates to identify robust FC alterations related to dementia conversion.

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

Repository

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

lkf-ki/mdmr-voxel-wise-mci-conversion

License: GPL-3.0
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: 2e3e2a15d6035e57fedc15b71570b4e15e4a8694, 25 May 2026
Languages: R (2)
Size: 5 files, 2 scripts
Software Heritage: not archived
Found in: the text, “Footnotes”
Holds: README, license file
Not found: CITATION.cff, environment file, tests, continuous integration, documentation
Tools: data.table (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
4 files
At the source: bitbucket.org/lkf-ki/mdmr-voxel-wise-mci-conversion/src/main/

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;
  • 2 scripts, each with its path and the digest of its content;
  • no match between paragraphs and code yet;
  • 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.

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 3, 28 September 2026

  • Publisher: n/a → IOS Press

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 5 authors, 4 keywords, 21 funders, 56 references.

Cite

This paper

Ferreira, L. K., Westman, E., Wahlund, L.-O., Mohanty, R., & for the Alzheimer's Disease Neuroimaging Initiative. (2026). Progression from mild cognitive impairment to dementia in Alzheimer's disease: Whole cortex voxelwise functional connectivity analysis with multivariate distance matrix regression. Journal of Alzheimer's disease : JAD, 113(3), 1384-1395. https://doi.org/10.1177/13872877261477016

BibTeX

@article{ferreira2026progression,
author = {Ferreira, Luiz Kobuti and Westman, Eric and Wahlund, Lars-Olof and Mohanty, Rosaleena and {for the Alzheimer's Disease Neuroimaging Initiative}},
title = {{Progression from mild cognitive impairment to dementia in Alzheimer's disease: Whole cortex voxelwise functional connectivity analysis with multivariate distance matrix regression}},
journal = {Journal of Alzheimer's disease : JAD},
year = {2026},
month = aug,
volume = {113},
number = {3},
pages = {1384--1395},
publisher = {IOS Press},
issn = {1387-2877},
doi = {10.1177/13872877261477016},
url = {https://doi.org/10.1177/13872877261477016},
pmid = {42585347},
pmcid = {PMC13583079}
}

RIS

TY - JOUR
AU - Ferreira, Luiz Kobuti
AU - Westman, Eric
AU - Wahlund, Lars-Olof
AU - Mohanty, Rosaleena
AU - for the Alzheimer's Disease Neuroimaging Initiative
TI - Progression from mild cognitive impairment to dementia in Alzheimer's disease: Whole cortex voxelwise functional connectivity analysis with multivariate distance matrix regression
T2 - Journal of Alzheimer's disease : JAD
J2 - J Alzheimers Dis
PY - 2026
DA - 2026/08/12
VL - 113
IS - 3
SP - 1384
EP - 1395
SN - 1387-2877
PB - IOS Press
DO - 10.1177/13872877261477016
UR - https://doi.org/10.1177/13872877261477016
LA - en
ER -

CSL-JSON

{
"id": "10.1177/13872877261477016",
"type": "article-journal",
"title": "Progression from mild cognitive impairment to dementia in Alzheimer's disease: Whole cortex voxelwise functional connectivity analysis with multivariate distance matrix regression",
"container-title": "Journal of Alzheimer's disease : JAD",
"author": [
{
"family": "Ferreira",
"given": "Luiz Kobuti"
},
{
"family": "Westman",
"given": "Eric"
},
{
"family": "Wahlund",
"given": "Lars-Olof"
},
{
"family": "Mohanty",
"given": "Rosaleena"
},
{
"literal": "for the Alzheimer's Disease Neuroimaging Initiative"
}
],
"container-title-short": "J Alzheimers Dis",
"volume": "113",
"issue": "3",
"page": "1384-1395",
"DOI": "10.1177/13872877261477016",
"PMID": "42585347",
"PMCID": "PMC13583079",
"ISSN": "1387-2877",
"publisher": "IOS Press",
"URL": "https://doi.org/10.1177/13872877261477016",
"language": "en",
"issued": {
"date-parts": [
[
2026,
8,
12
]
]
}
}

The tracing map gets a citation of its own once an author has validated it and it has a DOI.

Similar papers

The papers with a page that share the most with this one: the tools found in their code, their categories, datasets, cited references and authors, the rarest counting most.

[1] doi:10.1038/s41593-026-02363-4 [code]
Cortical thickness changes precede high levels of amyloid by at least 7 years.
Journal: Nature neuroscience
In common: data.table, Alzheimer's / dementia, 3 references
[2] doi:10.1126/sciadv.aee2305 [code]
Prediction of mild cognitive impairment progression using time-sensitive multimodal biomarkers.
Journal: Science advances
In common: Alzheimer's / dementia, 4 references
[3] doi:10.1002/hbm.70508 [code]
Cyclic 2.5D Perceptual Loss for Cross-Modal 3D Medical Image Synthesis: T1w MRI to Tau PET.
Journal: Human brain mapping
In common: Alzheimer's / dementia, 4 references
[4] doi:10.3389/fnagi.2026.1847611 [code]
APOE ε4-associated hippocampal atrophy trajectories across the Alzheimer's disease continuum: a systematic review, meta-analysis, and longitudinal validation.
Journal: Frontiers in aging neuroscience
In common: data.table, Alzheimer's / dementia, 3 references
[5] doi:10.1007/s00366-026-02313-5 [code]
A computational framework to predict the spreading of Alzheimer's disease.
Journal: Engineering with computers
In common: Alzheimer's / dementia, 4 references
[6] doi:10.1002/hbm.70559 [code]
Replicability of Functional Brain Networks: A Study Through the Lens of Seven Resting-State Networks.
Journal: Human brain mapping
In common: fMRI, systems, 3 references
[7] doi:10.1162/imag.a.1202
Recurring transient brain-wide co-activation patterns from EEG spatially resembling time-averaged resting-state networks.
Journal: Imaging neuroscience (Cambridge, Mass.)
In common: fMRI, systems, 3 references
[8] doi:10.1038/s41746-026-02597-3 [code]
Decoupling MCI-specific signatures from shared neurobiological substrates of cognitive aging via deep learning.
Journal: NPJ digital medicine
In common: Alzheimer's / dementia, 2 references
[9] doi:10.1186/s13195-026-02109-1
Transcranial pulse stimulation modulates spectral signatures of Alzheimer's disease in the 3×Tg-AD mouse model.
Journal: Alzheimer's research & therapy
In common: fMRI, Alzheimer's / dementia, 2 references
[10] doi:10.1038/s41588-026-02722-8 [code]
A multiancestry polygenic risk score for Alzheimer's disease is associated with cognitive decline and neuropathological hallmarks in diverse populations.
Journal: Nature genetics
In common: data.table, Alzheimer's / dementia, 2 references

Contribute

The authors of this paper can claim it, correct its record and validate its tracing map, and the maintainers of its code (its owner, or a public member of its organization) correct what it says of their repository; anyone signed in can ask for its removal. Every request goes to OSCR's own machine, which answers it; your account page follows them.

Sign in with ORCID to claim this paper as one of its authors, correct its record or validate its tracing map: when the paper's metadata lists your ORCID iD, you are recognized at once. Maintainers of its code: sign in with GitHub, then claim the repository on your account page.

Request its removal

To ask OSCR to remove this record, the copies of its authors' scripts or its tracing map, use the removal request page: signed in, you say who you are, what to remove and why, then review and confirm the request. Published rules decide every request (how).

Discussion, reproductions, activity

Discussion: questions and error reports about this paper and its code, from signed-in readers and its authors. It opens with sign-in.

Reproductions: reports from readers who ran the authors' code: what they reproduced, with which environment, commit and data. It opens with sign-in.

Activity: what happens around this paper: new versions of its record, its map's validation, discussions and reproductions. It opens with sign-in.