Surface-based cortical morphometry in fibromyalgia

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Main Author: Carp, Nicholas
Format: Recurso digital
Language:English
Published: Zenodo 2026
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author Carp, Nicholas
author_facet Carp, Nicholas
contents <p class="font-claude-response-body break-words whitespace-normal leading-[1.7]">Analysis code for: <em>Surface based cortical morphometry in fibromyalgia reveals left temporal lobe thinning and dissociated thickness area patterns: a FreeSurfer replication and extension study</em></p> <p class="font-claude-response-body break-words whitespace-normal leading-[1.7]">This repository contains a single Google Colab notebook (<code class="bg-text-200/5 border border-0.5 border-border-300 text-danger-000 whitespace-pre-wrap rounded-[0.4rem] px-1 py-px text-[0.9rem]">freesurfer_brain_morphology.ipynb</code>) implementing all analyses reported in the manuscript: subcortical volume comparisons (16 structures, age + eTIV covaried), cortical thickness group comparisons across 68 Desikan-Killiany parcels (FDR-BH corrected), surface area dissociation analysis (thickness vs area decomposition), hemisphere asymmetry analysis (k=12 pre-specified regions), brain-behaviour correlations (FM group, n=20), depression sensitivity analysis (CES-D residualisation), and post-hoc power analysis. Validation cells confirm key methodological choices (Welch correction, age interaction sensitivity, thalamus null verification). All five manuscript figures are generated at submission-ready resolution.</p> <p class="font-claude-response-body break-words whitespace-normal leading-[1.7]">Data: OpenNeuro ds001928 v1.1.0 (doi:10.18112/openneuro.ds001928.v1.1.0), 20 women with fibromyalgia and 20 age-matched healthy controls, GE Discovery MR750 3T. FreeSurfer 7.4.1. Python 3.12 (pandas 2.2.2, NumPy 2.0.2, SciPy 1.16.3, statsmodels 0.14.6).</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_19928956
institution Zenodo
language eng
publishDate 2026
publisher Zenodo
record_format zenodo
spellingShingle Surface-based cortical morphometry in fibromyalgia
Carp, Nicholas
<p class="font-claude-response-body break-words whitespace-normal leading-[1.7]">Analysis code for: <em>Surface based cortical morphometry in fibromyalgia reveals left temporal lobe thinning and dissociated thickness area patterns: a FreeSurfer replication and extension study</em></p> <p class="font-claude-response-body break-words whitespace-normal leading-[1.7]">This repository contains a single Google Colab notebook (<code class="bg-text-200/5 border border-0.5 border-border-300 text-danger-000 whitespace-pre-wrap rounded-[0.4rem] px-1 py-px text-[0.9rem]">freesurfer_brain_morphology.ipynb</code>) implementing all analyses reported in the manuscript: subcortical volume comparisons (16 structures, age + eTIV covaried), cortical thickness group comparisons across 68 Desikan-Killiany parcels (FDR-BH corrected), surface area dissociation analysis (thickness vs area decomposition), hemisphere asymmetry analysis (k=12 pre-specified regions), brain-behaviour correlations (FM group, n=20), depression sensitivity analysis (CES-D residualisation), and post-hoc power analysis. Validation cells confirm key methodological choices (Welch correction, age interaction sensitivity, thalamus null verification). All five manuscript figures are generated at submission-ready resolution.</p> <p class="font-claude-response-body break-words whitespace-normal leading-[1.7]">Data: OpenNeuro ds001928 v1.1.0 (doi:10.18112/openneuro.ds001928.v1.1.0), 20 women with fibromyalgia and 20 age-matched healthy controls, GE Discovery MR750 3T. FreeSurfer 7.4.1. Python 3.12 (pandas 2.2.2, NumPy 2.0.2, SciPy 1.16.3, statsmodels 0.14.6).</p>
title Surface-based cortical morphometry in fibromyalgia
url https://doi.org/10.5281/zenodo.19928956