Structural, functional and neurochemical imaging mapping of non-motor symptoms in Parkinson's disease.
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The authors' code
Markdown · 27 lines · 986 B · no license
- # Common Voxels Extraction (FSL Pipeline)
- This repository provides a Bash script to compute **voxels shared across multiple thresholded T-maps** using FSL.
- The workflow is useful for identifying consistent regions across several statistical images (e.g., group-level functional maps, lesion overlap, meta-analytic maps).
- the script performs the following steps:
- 1. **Threshold each map at T ≥ 7**
- 2. **Binarize** each thresholded map
- 3. **Compute a voxel-wise cumulative sum** across all binary maps
- 4. **Extract voxels common to all maps** (intersection) by thresholding sum_map at `N`, the number of input maps
- ---
- ## Output Files
- - `*_desc-T_funcmap.nii_bin.nii.gz` – thresholded and binarized maps
- - `sum_map.nii.gz` – voxel-wise sum of all binary maps
- - `common_voxels.nii.gz` – **final mask of voxels present in all maps**
- ---
- ## Requirements
- - **FSL** (https://fsl.fmrib.ox.ac.uk)
- - Bash (Linux/macOS)
- Ensure that `fslmaths` is available in your PATH.
README.md at commit a027be9, no license · at the source
Overview
- Neuroscience Research Center, Magna Graecia University, Catanzaro 88100, Italy
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, University of Toronto, M5T1R8 Toronto, Canada
- Institute of Neurology, Department of Medical and Surgical Sciences, Magna Graecia University, 88100 Catanzaro, Italy
Abstract
Non-motor symptoms, including rapid eye movement sleep behaviour disorder (RBD), depression and anxiety, are common and often co-occurring in patients with Parkinson’s disease. This study aimed to investigate their potential shared neurobiological substrates by integrating structural, functional and neurochemical imaging data. We analysed data from 638 Parkinson’s disease patients from the Parkinson’s Progression Markers Initiative (PPMI), with available 3T T1-weighted MRI scans. RBD, depression and anxiety severity were assessed using validated clinical scales (RBD Screening Questionnaire Score, Geriatric Depression Scale and State-Trait Anxiety Inventory). Voxel-based morphometry (VBM) multivariate regression analyses were performed to identify grey matter (GM) volume loss associated with each clinical symptom. All analyses were rigorously controlled for a comprehensive set of potential confounders, including age, sex, education, disease duration, motor severity and cognitive dysfunction, thereby minimizing confounding effects related to other aspects of the disease. Coordinate-based network mapping was then applied using a large normative resting-state functional connectome (N = 1000), to characterize symptom-specific functional networks based on brain areas functionally connected to the VBM-derived clusters. Finally, spatial correlations between these networks and normative neurotransmitter density maps from PET data were assessed. VBM analyses revealed distinct patterns of GM atrophy across the three symptoms (pFWE<0.05), overlapping in the left middle temporal and right middle frontal gyri. The coordinate-based functional network mapping approach demonstrated that the GM atrophy pattern associated with each symptom (pFWE < 10−6) converged onto brain networks involving several cortical regions and overlapping across symptoms, and with the greatest spatial affinity, among canonical large-scale networks, with the Dorsal and Ventral Attention networks. All three symptom-related networks showed significant alignment with the noradrenaline transporters (NAT) spatial distribution (pFDR < 0.05). Overall, this study proposes a novel conceptual and methodological framework integrating well-established and validated techniques to identify the neuroanatomical bases of specific diseases or symptoms, potentially of interest for future research. Our neuroimaging findings in the large PPMI cohort of early Parkinson’s disease patients demonstrate that the brain networks associated with RBD, depression and anxiety non-motor symptoms were largely overlapping, involved the attention networks and were spatially aligned with the noradrenergic system, suggesting that these symptoms may have shared neurobiological substrates.
Reproduced under the paper's license (CC BY), from the paper cited above.
Repository
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chiaracamastra/Coordinate-based-network-mapping
a027be97a3cefb9d8e4d20bbd3ab90aaaf923c90, 3 December 2025Availability: 1 check, the latest on 27 September 2026: the link answers
- 27 September 2026: the link answers
1 file
- README.md, Text, 27 lines
The paper's code and data availability statement is in the Data section.
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Data
Datasets cited
- dataverse.harvard.edu/
dataverse/ , at dataverse.harvard.edu; found in the text, “Coordinate-based network mapping”gsp
Data availability
The data supporting the findings of this study are openly available in the Image and Data Archive at https://
All custom scripts used for data analysis in this study are available on GitHub at the following repository: https://
Reproduced under the paper's license (CC BY), from the paper cited above.
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Version 2, 28 September 2026
- Funding: added Bristol-Myers Squibb; Biogen; Celgene; Allergan; Avid Radiopharmaceuticals
Version 1, 27 September 2026: the first record
Recorded: type, language, journal, volume, issue, pages, dates, 3 authors, 5 keywords, 49 references, 1 RRID.
Cite
This paper
Camastra, C., Quattrone, A., & Quattrone, A. (2026). Structural, functional and neurochemical imaging mapping of non-motor symptoms in Parkinson's disease. Brain communications, 8(4), fcag316. https://
BibTeX
@article{camastra2026str
author = {Camastra, Chiara and Quattrone, Aldo and Quattrone, Andrea},
title = {{Structural, functional and neurochemical imaging mapping of non-motor symptoms in Parkinson's disease}},
journal = {Brain communications},
year = {2026},
month = aug,
volume = {8},
number = {4},
pages = {fcag316},
publisher = {Oxford University Press},
issn = {2632-1297},
doi = {10.1093/
url = {https://
pmid = {42643997},
pmcid = {PMC13504651}
}
RIS
TY - JOUR
AU - Camastra, Chiara
AU - Quattrone, Aldo
AU - Quattrone, Andrea
TI - Structural, functional and neurochemical imaging mapping of non-motor symptoms in Parkinson's disease
T2 - Brain communications
J2 - Brain Commun
PY - 2026
DA - 2026/
VL - 8
IS - 4
SP - fcag316
SN - 2632-1297
PB - Oxford University Press
DO - 10.1093/
UR - https://
LA - en
ER -
CSL-JSON
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"ISSN": "2632-1297",
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"URL": "https://
"language": "en",
"issued": {
"date-parts": [
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}
}
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