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Retinal nerve fibre layer thickness reflects characteristics of brain grey and white matter.

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  1. [1] § Results › Correlations between RNFLT and brain WMM (N = 550 whole-brain TBSS) › Averaged global RNFLT correlations with FA ↔ VBM_batches/matlab_scripts/secondLevel_averaged_global_RNFLT_withCVR.m, the whole file · a weak match · score 0.80 · retina scanning radius, physical activity, multiple regression, global RNFLT, CC, HDL
  2. [2] § Results › Correlations between RNFLT and brain GMD (N = 769 whole-brain VBM) › Correlations with global RNFLT ↔ VBM_batches/matlab_scripts/secondLevel_averaged_global_RNFLT_withCVR.m, the whole file · a weak match · score 0.79 · retina scanning radius, physical activity, cardiovascular risk, grey matter density, global RNFLT, HDL
  3. [3] § Methods › Statistical analysis › T1-weighted data analysis using VBM ↔ VBM_batches/matlab_scripts/secondLevel_CVR_variable.m, the whole file · a weak match · score 0.67 · brain grey matter, smoothed, VBM, masked, SPM12, density
  4. [4] § Methods › Statistical analysis › T1-weighted data analysis using VBM ↔ VBM_batches/matlab_scripts/secondLevel_averaged_global_RNFLT_withoutCVR.m, the whole file · a weak match · score 0.66 · retina scanning radius, multiple regression, global RNFLT, VBM, TIV, model
  5. [5] § Methods › Statistical analysis › Laterality of nasal sectoral and global RNFLT on brain structure ↔ TBSS_commands/shell_bash_scripts/atlasQuery_coordinates.sh, the whole file · a weak match · score 0.63 · Juelich histological atlas, FSL, global RNFLT
  6. [6] § Methods › Statistical analysis › Laterality of nasal sectoral and global RNFLT on brain structure ↔ TBSS_commands/shell_bash_scripts/cluster_atlasQ.sh, the whole file · a weak match · score 0.61 · Juelich histological atlas, FSL
  7. [7] § Methods › Statistical analysis › T1-weighted data analysis using VBM ↔ VBM_batches/matlab_scripts/segmentation.m, the whole file · a weak match · score 0.60 · bias, SPM, raw, segmentation, preprocessed, template
  8. [8] § Methods › Statistical analysis › Confirmational region-of-interest (ROI) analysis using regional and global grey matter volume ↔ VBM_batches/matlab_scripts/secondLevel_averaged_global_RNFLT_withoutCVR.m, the whole file · a weak match · score 0.57 · brain grey matter, scanning radius, global RNFLT, VBM, TIV, CAT12

Paper

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The authors' code

MATLAB · 77 lines · 5.1 KB · no license · 2 matches

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Overview

Authors: Nazife Ayyıldız1, Karsten Mueller1,2, Samyogita Hardikar1, Frauke Beyer1,3, Cornelia Enzenbach4,5, Ronny Baber5,6, Kerstin Wirkner5, Silke Zachariae4,5, Johanna Girbardt1,4, Jordan D Hassett1,7, Alfred Anwander8, Tobias Elze9, Mengyu Wang9, A Veronica Witte1,3,5, Franziska G Rauscher4,5,10, Arno Villringer1,3,5,7,11
ORCID iDs: Nazife Ayyıldız, Karsten Mueller, Samyogita Hardikar, Frauke Beyer, Ronny Baber, Kerstin Wirkner, Silke Zachariae, Johanna Girbardt, Jordan D Hassett, Alfred Anwander, Tobias Elze, A Veronica Witte, Franziska G Rauscher, Arno Villringer
  1. Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
  2. Department of Neurology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
  3. Day Clinic for Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
  4. Institute for Medical Informatics, Statistics and Epidemiology, Leipzig University, Leipzig, Germany
  5. Leipzig Research Centre for Civilization Diseases (LIFE), Leipzig University, Leipzig, Germany
  6. Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, Leipzig University Medical Center, Leipzig, Germany
  7. Max Planck School of Cognition, Leipzig, Germany
  8. Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
  9. Schepens Eye Research Institute, Harvard Medical School, Boston, MA, United States
  10. Department of Medical Data Science, Medical Informatics Center, Leipzig University, Leipzig, Germany
  11. MindBrainBody Institute, Berlin School of Mind and Brain, Humboldt University, Berlin, Germany
Institutions: Max Planck Institute for Human Cognitive and Brain Sciences (Germany); Charles University (Czechia); General University Hospital in Prague (Czechia); University Hospital Leipzig (Germany); Leipzig University (Germany); Harvard University (United States); Humboldt-Universität zu Berlin (Germany)
Journal: Imaging neuroscience (Cambridge, Mass.), volume 4, article IMAG.a.1174
Dates: received 16 May 2025; accepted 19 February 2026; published online 2 April 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1162/imag.a.1174 · PMID 41958634 · PMCID PMC13058853 · OpenAlex W7133227165
Open access: diamond, a free copy (OpenAlex)
Status: code verified
Categories: structural MRI / diffusion (modality), other (modality), clinical / translational (subfield)
Methods: Statistics, Connectivity, Preprocessing, fMRI & imaging, Physiology & signal measures
Keywords: brain grey matter, cardiovascular risk factors, magnetic resonance imaging, optical coherence tomography, circumpapillary retinal nerve fibre layer thickness, white matter
Topic: Glaucoma and retinal disorders (Ophthalmology, Medicine), according to OpenAlex
Funding: Research to Prevent Blindness (R00 EY028631, R21 EY030631, R01 EY030575, P30EY003790, R21 EY030142); Deutsche Forschungsgemeinschaft (497989466); Max-Planck-Gesellschaft; German Academic Exchange Service
Citations: not cited yet (Europe PMC); 182 references in the paper

Abstract

The retina is an optically accessible part of the central nervous system. Using high-resolution optical coherence tomography, we explored the relationship between retinal thickness and structural features of the brain obtained with magnetic resonance imaging. We hypothesized that there are associations between circumpapillary (i.e., around optic disc) retinal nerve fibre layer thickness and structural features of (i) brain areas and pathways related to visual information processing and (ii) more widespread brain areas affected by the consequences of cardiovascular risk factors and/or age-related neurodegeneration. In a population-based sample of over 500 subjects, in support of the first hypothesis, we showed associations of circumpapillary retinal nerve fibre layer thickness with visual cortex grey matter density and with optic radiation fractional anisotropy. These correlations were stronger for the right eye, possibly reflecting right ocular dominancy. Regarding the second hypothesis, while we confirmed the broad impact of cardiovascular risk factors such as body mass index, diabetes, and hypertension on brain structure, we did not find (adequate) significant partial correlations between circumpapillary retinal nerve fibre layer thickness and cardiovascular risk factors. Consequently, we were unable to confirm an association between circumpapillary retinal nerve fibre layer thickness and the impact of cardiovascular risk factors on brain structure especially on grey matter rather than white matter. However, even when the effects of cardiovascular risk factors were accounted for statistically, circumpapillary retinal nerve fibre layer thickness (particularly on the right side) was associated with fractional anisotropy of limbic system tracts, that is, the fornix and stria terminalis including hippocampus and amygdala, areas which are commonly affected by Alzheimer’s disease. To further explore the structural associations between eye and brain, in terms of a possible common underlying pathology related to cardiovascular risk factors and progressive neurodegenerative diseases on the central nervous system, longitudinal and interventional studies are necessary.

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

Repository

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n-ayyildiz/EyeBrain_project

License: none: the authors keep all their rights
State: the link answers, verified on 28 September 2026
Evidence: files inventoried
Commit: b3e8a23da3f5d96e1d00755b19e6f6e17628c5a2, 21 January 2026
Languages: MATLAB (12), R (10), Python (2), Shell (2)
Size: 33 files, 26 scripts
Software Heritage: not archived
Found in: the text, “Methods”
Holds: README
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: SPM (12 files), broom (10 files), easystats (10 files), ggplot2 (10 files), tidyverse (10 files), NiBabel (2 files), Nilearn (2 files), NumPy (2 files), FSL (1 file), Matplotlib (1 file), patchwork (1 file)
Availability: 1 check, the latest on 28 September 2026: the link answers
  • 28 September 2026: the link answers
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At the source: github.com/n-ayyildiz/EyeBrain_project.git

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

Tracing map

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  • 26 scripts, each with its path and the digest of its content;
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Data

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

Data and Code Availability

We used the data obtained within the LIFE-Adult-Study (Engel et al., 2023; Loeffler et al., 2015). The scripts used for the analyses and visualization of the results can be found here: https://github.com/n-ayyildiz/EyeBrain_project.git.

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

Versions

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Version 2, 28 September 2026

  • Funding: added Research to Prevent Blindness: R00 EY028631, R21 EY030631, R01 EY030575, P30EY003790, R21 EY030142; Deutsche Forschungsgemeinschaft: 497989466; Max-Planck-Gesellschaft; German Academic Exchange Service

Version 1, 28 September 2026: the first record

Recorded: type, language, journal, volume, pages, dates, 16 authors, 6 keywords, 182 references.

Cite

This paper

Ayyıldız, N., Mueller, K., Hardikar, S., Beyer, F., Enzenbach, C., Baber, R., Wirkner, K., Zachariae, S., Girbardt, J., Hassett, J. D., Anwander, A., Elze, T., Wang, M., Witte, A. V., Rauscher, F. G., & Villringer, A. (2026). Retinal nerve fibre layer thickness reflects characteristics of brain grey and white matter. Imaging neuroscience (Cambridge, Mass.), 4, IMAG.a.1174. https://doi.org/10.1162/imag.a.1174

BibTeX

@article{ayyldz2026retinal,
author = {Ayyıldız, Nazife and Mueller, Karsten and Hardikar, Samyogita and Beyer, Frauke and Enzenbach, Cornelia and Baber, Ronny and Wirkner, Kerstin and Zachariae, Silke and Girbardt, Johanna and Hassett, Jordan D and Anwander, Alfred and Elze, Tobias and Wang, Mengyu and Witte, A Veronica and Rauscher, Franziska G and Villringer, Arno},
title = {{Retinal nerve fibre layer thickness reflects characteristics of brain grey and white matter}},
journal = {Imaging neuroscience (Cambridge, Mass.)},
year = {2026},
month = apr,
volume = {4},
pages = {IMAG.a.1174},
publisher = {MIT Press},
issn = {2837-6056},
doi = {10.1162/imag.a.1174},
url = {https://doi.org/10.1162/imag.a.1174},
pmid = {41958634},
pmcid = {PMC13058853}
}

RIS

TY - JOUR
AU - Ayyıldız, Nazife
AU - Mueller, Karsten
AU - Hardikar, Samyogita
AU - Beyer, Frauke
AU - Enzenbach, Cornelia
AU - Baber, Ronny
AU - Wirkner, Kerstin
AU - Zachariae, Silke
AU - Girbardt, Johanna
AU - Hassett, Jordan D
AU - Anwander, Alfred
AU - Elze, Tobias
AU - Wang, Mengyu
AU - Witte, A Veronica
AU - Rauscher, Franziska G
AU - Villringer, Arno
TI - Retinal nerve fibre layer thickness reflects characteristics of brain grey and white matter
T2 - Imaging neuroscience (Cambridge, Mass.)
J2 - Imaging Neurosci (Camb)
PY - 2026
DA - 2026/04/02
VL - 4
SP - IMAG.a.1174
SN - 2837-6056
PB - MIT Press
DO - 10.1162/imag.a.1174
UR - https://doi.org/10.1162/imag.a.1174
LA - en
ER -

CSL-JSON

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