Multi-TE Diffusion MRI Across Lifespan

This dataset provides high-resolution relaxation-diffusion MRI (rdMRI) data of mouse brains across the lifespan, enabling the study of age-related microstructural changes using multi-echo diffusion imaging at ultra-high field strength.

• Source: https://doi.org/10.6084/m9.figshare.28433102

Dataset Overview

• Species: Mouse

• Total subjects: 30

• Age groups:

  • 2, 6, 12, 18, 24 months
  • (6 animals per group)

• Scanner: 9.4 Tesla Bruker MRI

• Purpose:

  • Characterize microstructural changes across aging
  • Study relaxation–diffusion interactions
  • Support advanced diffusion modeling (e.g., multi-TE analysis)

Imaging Protocol

Anatomical Imaging

• Sequence: 2D TurboRARE (T2-weighted)
• TR/TE: 3200 / 11 ms
• Resolution: 0.08 × 0.08 mm²
• Slice thickness: 0.5 mm

Diffusion MRI (Multi-TE)

• Sequence: Multi-shot SE-EPI

• TR: 3200 ms

• Echo times (TEs):

  • 22, 37, 52, 67, 82 ms

• b-values:

  • 500, 1000, 1500, 2500 s/mm²

• Directions:

  • 30 per shell

• b0 images:

  • 6

• Resolution:

  • 0.1 × 0.1 mm²

• Slice thickness:

  • 0.5 mm

Multi-TE Design

Each subject includes five diffusion sessions corresponding to different echo times:

• ses-01 → TE = 22 ms
• ses-02 → TE = 37 ms
• ses-03 → TE = 52 ms
• ses-04 → TE = 67 ms
• ses-05 → TE = 82 ms

Additionally:

• Reversed phase-encoding acquisitions provided for distortion correction

Data Structure

Each subject includes:

1. Anatomical data

   • T2-weighted images (anat/)

2. Diffusion data

   • Multi-TE DWI (dwi/)

3. Reversed phase-encoding DWI

   • For susceptibility correction

• Format: NIfTI (DICOM not included)

Processing and Code

• Custom pipeline included

• Scripts available for:

  • Diffusion preprocessing
  • Registration (MRtrix3, ANTs)
  • Tractography
  • NODDI modeling

• Key components:

  • dwipreprocess_script.bash
  • MRtrix3_rigid_register_script.bash
  • ANTs_register_transform.bash
  • processing_DTI_FOD_tractography.bash
  • noddi_script_auto.py

• REDIM method implementation included

Scientific Applications

This dataset enables:

• Lifespan analysis of brain microstructure
• Relaxation–diffusion modeling
• Multi-TE diffusion analysis
• Validation of advanced diffusion models (e.g., NODDI, FOD)
• Aging-related connectomics studies

Data Quality and Ethics

• All experiments approved by:

  • Institutional Animal Care and Use Committee
  • Southern Medical University

• High-resolution acquisition at ultra-high field (9.4T)

Funding

• Guangdong Basic and Applied Basic Research Foundation
• National Natural Science Foundation of China

Contact

• Xinyuan Zhang
  • Email: zhangxyn@smu.edu.cn

This dataset provides in vivo diffusion MRI (DTI), together with companion PET, behavioral, and post‑mortem histology data from 16 non‑human primates (macaques) subjected to unilateral MPTP lesions of the nigrostriatal pathway. It supports validation of diffusion‑based markers of dopaminergic neuron integrity against gold‑standard histological and neurochemical measures.

License

Public domain (Dryad)

Citation

Shimony, J. S., Rutlin, J., Karimi, M., Tian, L., Snyder, A. Z., Loftin, S. K., Norris, S. A., & Perlmutter, J. S. (2019).
Validation of diffusion tensor imaging measures of nigrostriatal neurons in macaques [Data set]. Dryad.
https://doi.org/10.5061/dryad.2f8j75d

Primary article: PLOS ONE — https://doi.org/10.1371/journal.pone.0202201

Source

https://doi.org/10.5061/dryad.2f8j75d
Publisher: Dryad (Published Aug 14, 2019)
Affiliation: University of Washington School of Medicine

Dataset Information

Experimental Overview

• Design: Each animal received unilateral MPTP to induce varying degrees of nigrostriatal injury.
• Imaging: Pre/post DTI and PET with three presynaptic radioligands; blinded motor ratings.
• Endpoints: Post‑mortem quantification of striatal dopamine, TH‑positive striatal fibers, and TH‑positive nigral cell bodies.
• Analysis: Diffusion measures along the nigrostriatal tract compared to PET and histology across injury severities.

Suggested Uses

• Validation of tract‑specific diffusion biomarkers for dopaminergic neurodegeneration.
• Method development for nigrostriatal tractography and ROI quantification in NHPs.
• Comparative evaluation of DTI vs PET sensitivity across lesion severity.
• Benchmarking pipelines for DICOM→NIfTI conversion and diffusion processing in NHP datasets.

Notes

• Dryad distribution provides raw DICOM per subject; users should convert to NIfTI (e.g., dcm2niix) and perform species‑appropriate preprocessing.
• Tract definitions (midbrain↔striatum) and ROI placement should follow the primary article’s methods to reproduce correlations.

Keywords

Diffusion MRI • DTI • Nigrostriatal • MPTP • Macaque • Dopamine • TH immunostaining • PET • Parkinson’s disease • Non‑human primate • Validation

This dataset provides diffusion-weighted MRI (dMRI) and high-resolution 3D structural MRI of post-mortem rat brains, enabling detailed reconstruction of the cortical connectome.
It accompanies the publication by Sinke et al. (2018) and includes 10 perfusion-fixed Wistar rat brains scanned at ultra-high field (9.4 T).
The dataset contains raw dMRI and balanced SSFP data, along with derived diffusion metrics and anatomical references for connectome analysis.

All experiments were approved by the Animal Experiments Committee of the University Medical Center Utrecht and Utrecht University, and conducted in compliance with the European Communities Council Directive on animal research.

License

Creative Commons Attribution 4.0 International (CC BY 4.0)

Citation

Sinke, M. R. T., Otte, W. M., van der Toorn, A., Dijkhuizen, R., & Sarabdjitsingh, R. A. (2024).
Diffusion weighted MR imaging of post-mortem rat brain to allow reconstruction of the cortical connectome [Data set].
Brain Structure and Function, 223(5). Zenodo.
https://doi.org/10.5281/zenodo.11119038

Source

https://doi.org/10.5281/zenodo.11119038
Contact: m.r.t.sinke@umcutrecht.nl
Institution: University Medical Center Utrecht
Journal: Brain Structure and Function, 223(5), 2024

Dataset Information

Purpose

The dataset supports investigation of rat cortical microstructure and connectivity using ex-vivo diffusion MRI.
It enables validation of diffusion tractography and modeling of cortical connectivity at high resolution, providing a reference for algorithm development, structural mapping, and interspecies comparison.

MR Acquisition Details

• Diffusion MRI

  • 3D diffusion-weighted spin-echo sequence
  • Isotropic resolution: 150 μm
  • TR/TE: 500/32.4 ms
  • 60 diffusion-weighted directions (b = 1031–7756 s/mm²)
  • 24 b₀ images
  • Total: 325 images

• Balanced SSFP (BSSFP)

  • 4 × 3D acquisitions, isotropic 100 μm
  • TR/TE: 15.4/7.7 ms, flip angle 40°
  • Phase shifts: 0°, 90°, 180°, 270°
  • Combined to reduce banding artifacts

• Spoiled Gradient Echo (SPGR)

  • Echo times: 5, 10, 15 ms
  • TR: 20 ms, flip angle 40°
  • 24 averages

File Information

Keywords

MRI • Diffusion MRI • Rat Brain • Post-mortem • Cortical Connectome • High-field MRI • Ex-vivo Imaging • Tractography

This dataset includes diffusion MRI and BOLD-fMRI data acquired from female Wistar rats (N = 10) subjected to forepaw electrical stimulation under ultra-high-field MRI.
The experiment was conducted to investigate how neural activity modulates mean diffusivity (MD) and mean kurtosis (MK) over multiple diffusion times, and how these changes relate to BOLD-fMRI activation.

License

Creative Commons Attribution 4.0 International (CC BY 4.0)

Citation

Hertanu, A. (2025). Forepaw electrical stimulation: MD and MK time-dependence vs. BOLD-fMRI [Data set].
Imaging Neuroscience.
Zenodo. https://doi.org/10.5281/zenodo.14793797

Related article: https://doi.org/10.1162/imag_a_00445

Source

https://doi.org/10.5281/zenodo.14793797
Publisher: Zenodo (Version v2, February 2025)
Associated Journal: Imaging Neuroscience (2025)
Contact: andreea.hertanu@weizmann.ac.il
Institution: Weizmann Institute of Science, Israel
Hardware: Bruker BioSpin 14.1 T MRI system with custom-built surface quadrature transceiver RF coil

Dataset Information

Experimental Design

Each rat underwent repeated imaging sessions including diffusion-weighted imaging (DWI) and BOLD-fMRI under forepaw stimulation.
Both modalities included reversed EPI phase-encode direction acquisitions for distortion correction.

Diffusion-weighted Imaging (DWI)

• 14 images at rest, 14 during stimulation
• Repeated until 84 total volumes (excluding initial b0)
• Acquired using fast kurtosis imaging (Hansen et al., 2016)

BOLD-fMRI

• 28 images at rest, 28 during stimulation
• Repeated until 336 total volumes per run
• Temporal resolution = 1 s

Functional Runs

Each session consisted of five runs alternating rest and stimulation blocks.
Rats 000002 and 000003 completed four runs due to motion or physiological constraints.

Analysis Focus

The dataset supports multimodal analysis of:

• Activity-driven microstructural changes via MD and MK modulations
• Diffusion-time dependence of kurtosis metrics under activation
• BOLD-dMRI correlations in somatosensory cortex

Region-of-interest analyses were conducted in the left hemisphere (contralateral to the right forepaw stimulation).
Signals were labeled as contralateral or ipsilateral based on expected somatosensory activation patterns.

Potential Applications

• Joint modeling of BOLD and diffusion time-dependence
• Validation of microstructural-functional coupling models
• Exploration of neuronal vs. vascular origins of diffusion changes
• Preclinical pipeline testing for multimodal rat fMRI

Keywords

Rat fMRI • Diffusion Kurtosis • MD Time-Dependence • Functional MRI • Forepaw Stimulation • BOLD • Fast Kurtosis Imaging • 14.1 Tesla MRI • Bruker BioSpin • Weizmann Institute

The Brain/MINDS Marmoset MRI NA216 and eNA91 Datasets represent the largest publicly available marmoset brain MRI resource to date, comprising data from 483 individuals. These datasets offer a comprehensive range of in vivo and ex vivo MRI data across various imaging modalities, covering a wide age span of marmoset subjects.

License

This dataset is shared under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
https://dataportal.brainminds.jp/marmoset-mri-na216

Dataset Composition

In Vivo Data (NA216)

• Subjects: 455 individuals
• Age Range: 0.6 to 12.7 years (Mean: 3.86 ± 2.63 years)
• Standard Brain Data: 216 individuals (Mean age: 4.46 ± 2.62 years)

Available Modalities:

• T1-weighted Imaging (T1WI)

• T2-weighted Imaging (T2WI)

• T1WI/T2WI ratio maps

• Diffusion Tensor Imaging (DTI) metrics:

  • Fractional Anisotropy (FA)
  • Corrected FA (FAc)
  • Mean Diffusivity (MD)
  • Radial Diffusivity (RD)
  • Axial Diffusivity (AD)

• Diffusion Weighted Imaging (DWI)

• Resting-State fMRI (rs-fMRI) in awake and anesthetized states

• Structural and functional connectome matrices (CSV format)

• Standardized label data (NIfTI .nii.gz files)

Ex Vivo Data (eNA91)

• Subjects: 91 individuals (Mean age: 5.27 ± 2.39 years)

Available Modalities:

• Standard Brain Images (NIfTI .nii.gz)
• T2WI
• DTI Metrics: FA, FAc, MD, RD, AD
• DWI
• Standardized label data
• Structural connectome matrices (individual and population average, CSV format)

Imaging Methods

For detailed information on imaging protocols, visit the Imaging Methods Documentation.

Usage Notes

• Region names for structural and functional connectome matrices can be found here.

• Original data have been preprocessed and optimized for online previews, including:

  • Standardized resolution between in vivo and ex vivo datasets
  • Bit-depth reduction to 8-bits for faster display
  • Contrast enhancements for improved visualization

Download Tips:

• On some browsers (e.g., Safari), CSV files may open directly in a new tab. To download, either:

  • Press [Command] + S on the newly opened tab, or
  • Ctrl + Click on the download link and choose "Download linked file."

Go to Data Download & Preview

Citation

Hata J., Nakae K., Yoshimaru D., Okano H. Brain/MINDS Marmoset Brain MRI Dataset NA216 and eNA91 (DataID: 4624).
DOI: https://doi.org/10.24475/bminds.mri.thj.4624

The Brain/MINDS Marmoset MRI NA216 and eNA91 datasets currently constitutes the largest public marmoset brain MRI resource (483 individuals), and includes in vivo and ex vivo data for large variety of image modalities covering a wide age range of marmoset subjects.

The in vivo part corresponds to a total of 455 individuals, ranging in age from 0.6 to 12.7 years (mean age: 3.86 ± 2.63), and standard brain data (NA216) from 216 of these individuals (mean age: 4.46 ± 2.62).
T1WI, T2WI, T1WI/T2WI, DTI metrics (FA, FAc, MD, RD, AD), DWI, rs-fMRI in awake and anesthetized states, NIfTI files (.nii.gz) of label data, individual brain and population average connectome matrix (structural and functional) csv files are included.
The ex vivo part is ex vivo data, mainly from a subset of 91 individuals with a mean age of 5.27 ± 2.39 years.
It includes NIfTI files (.nii.gz) of standard brain, T2WI, DTI metrics (FA, FAc, MD, RD, AD), DWI, and label data, and csv files of individual brain and population average structural connectome matrices.
Go to Data Download & Preview.

Citation

Junichi Hata, Ken Nakae, Daisuke Yoshimaru, Hideyuki Okano. Brain/MINDS Marmoset Brain MRI Dataset NA216 and eNA91: (DataID: 4624)
doi: https://doi.org/10.24475/bminds.mri.thj.4624

License

Creative Commons License.
This work is licensed under a Creative Commons Attribution 4.0 International License.

Data Source

https://dataportal.brainminds.jp/marmoset-mri-na216

Issues

quality problem
T1w: 410,412
T2w: 412

Imaging Method

Usage Notes

A description of the region names for individual lines and columns of the SC and FC matrices can be found here.
For the purpose of online previews, original data have been preprocessed and formatted for optimized display. E.g. for most Nifti files, contrast enhancement of the data was performed to improve visibility. The resolution across in vivo and ex vivo was standardized and bit-depth reduction (to 8-bits) on the majority of data was used to reduce loading times.
Some web browsers (e.g. Safari) might display CSV files in a new tab when clicking on the download button. In that case, the file can either be saved from the newly opened tab (shortcut: [Command]+S), or directly downloaded using [Ctrl]+click on the download button and selecting “Download linked file”.

This repository provides curated, research-ready derivatives and documentation derived from the Marmoset Brain Connectivity Atlas (adult Callithrix jacchus), with emphasis on transparent provenance, standardized organization, and reproducible usage in connectivity analysis.

Scope. Fluorescent retrograde tracer injection cases registered to a marmoset cortical template (Paxinos et al., 2012), with section images, cell-label coordinates, and per-case metadata suitable for quantitative analyses and atlas overlays.

Provenance (Original Project)

The original atlas collates two decades of tracer experiments using fluorescent retrograde tracers in adult marmosets to map cortico-cortical and subcortical inputs to defined sites. Data were digitized and registered to a Paxinos et al. (2012) template, viewable as 3D mid-thickness cortex or unfolded cortical maps.

Key references stemming from the source material include (non-exhaustive):
Rosa 2009; Burman 2011, 2014, 2015; Reser 2013; Majka 2016, 2018; Woodward 2018.

Methods (Brief)

Tracer types (retrograde):

• Fluororuby (FR), Fluoroemerald (FE), Fast Blue (FB), Diamidino Yellow (DY), and CTB (Alexa 488 = CTBgr; Alexa 594 = CTBr).
• Typical injections: 0.02 µL deposits over 15–20 min at multiple depths; up to four tracers per animal.

Sectioning & imaging:

• 40 µm frozen sections (mostly coronal); 1-in-5 series for fluorescence mapping.
• Histology (Nissl/NeuN, myelin, cytochrome oxidase) on adjacent series.
• Scanned at ~0.50 µm/pixel (×20). Left-hemisphere injections horizontally flipped for consistency.

Preprocessing & registration:

• Downsampled section series assembled in rostro-caudal order; artefact padding as needed.
• Cell-label SVG overlays aligned to histology (translation/rotation/scale).
• 3D reconstruction with iterative in-plane alignments + deformable corrections.
• Atlas registration (affine + SyN deformable) using ANTs; QC included.

Template:

• Cortical parcellation from Paxinos et al. (2012); stereotaxic coordinate system.
• 3D Brain Atlas Reconstructor / custom scripts for volume/surface generation.

Software (source project):

• ANTs, Convert3D, ImageMagick, VTK/ITK; pipelines via poSSum framework.
• Original web viewer: OpenLayers-based tiled imagery with vector overlays.

Data Organization

• Per-case folder: sections/CASE_ID/ (tiles) · cells/CASE_ID.csv (label points) · registration/CASE_ID/ (affine, warp fields, QC) · metadata/CASE_ID.json
• Coordinates:
  • *_section: pixel coordinates in section space
  • *_template: coordinates in template space (after warp)
• Template surfaces: mid-thickness mesh (template/surface/) and unfolded maps (template/unfolded/)

How to Use

1. Visualize sections + labels
   Use examples/01_view_sections.ipynb to load a section tile and overlay cell points.
2. Map to cortical areas
   Apply registration/CASE_ID transforms to bring cell points into template space, then intersect with area labels.
3. Quantify connectivity
   Aggregate counts by parcel (optionally normalize by parcel area / section sampling), export CSV for stats.

License & Citation

• License: Images and figures from the source project are distributed under CC BY 4.0; see LICENSE and the original Licensing and Citation Policy. Derived metadata and code in this repository follow the license declared in LICENSE.
• Acknowledge (example):
  “Data derived from the Marmoset Brain Connectivity Atlas. Please see the original project and licensing page for details.”
• Suggested citation (source project):
  Cite the Marmoset Brain Connectivity Atlas and relevant methods papers (e.g., Majka et al., 2016/2018; Paxinos et al., 2012), plus this repository (Pittsburgh team) for derivatives.

Funding acknowledgements (source project): Support from ARC and NHMRC projects; ARC Centre of Excellence for Integrative Brain Function; INCF seed grant; and related institutional support (Monash University, CSHL). See original project pages for full details.

This dataset provides structural and diffusion MRI data of seven non-human primate species from the Primate Brain Bank at the Netherlands Institute for Neuroscience (Amsterdam).
It includes raw data, surface reconstructions generated using FreeSurfer, and connectome reconstructions generated with CATO. The dataset supports comparative neuroanatomy and connectomics research across primate species.

License

Creative Commons Attribution 4.0 International (CC BY 4.0)

Citation

Ardesch, D. J., Bryant, K. L., Roumazeilles, L., Scholtens, L. H., Khrapitchev, A. A., Tendler, B. C., Wu, W., Miller, K. L., Sallet, J., van den Heuvel, M. P., & Mars, R. B. (2021).
Primate Brain Bank MRI (1.0.0) [Data set]. Zenodo.
https://doi.org/10.5281/zenodo.5044936

Source

https://doi.org/10.5281/zenodo.5044936
Contact: d.j.ardesch@nin.knaw.nl
Institutions: Netherlands Institute for Neuroscience, University of Oxford, Radboud University, Wellcome Centre for Integrative Neuroimaging
Funding: Biotechnology and Biological Sciences Research Council (BBSRC, UK) [BB/N019814/1], Wellcome Trust [203139/Z/16/Z], Netherlands Organization for Scientific Research (NWO) [VIDI-452-16-015, ALW-179]

Dataset Information

Demographics

Demographic details (age, sex, and Primate Brain Bank sample codes) are provided in the accompanying demographics.csv file.

Processing Overview

• Structural MRI:
  Processed with FreeSurfer 6.0 using a modified non-human primate pipeline
  (https://github.com/ardesch/nhp-freesurfer).

• Diffusion MRI:
  Processed using CATO v2.5
  (https://github.com/dutchconnectomelab/CATO)
  to reconstruct fiber tracts and connectomes.

• Data Outputs:
  Include preprocessed DWI data, FreeSurfer-derived cortical surfaces, and species-specific connectomes.

Purpose

This dataset provides a cross-species framework for studying evolutionary connectomics, comparative cortical anatomy, and inter-species variation in structural connectivity.
It enables quantitative analyses linking diffusion tractography, sulcal morphology, and network topology across multiple primate lineages.

Keywords

Primate • Diffusion MRI • Tractography • Connectome • FreeSurfer • CATO • Comparative Anatomy • Non-Human Primate • Evolutionary Neuroscience • Sulcal Morphology

This dataset contains manganese-enhanced T1-weighted and diffusion-weighted MRI of the optic pathways in 18 healthy C57BL/6 female mice.
The study investigates white matter organization and manganese transport in the mouse visual system using in vivo high-field MRI.
Raw Bruker files and a subset of NIfTI-converted images are included to support both reprocessing and immediate analysis.

License

Creative Commons Attribution 4.0 International (CC BY 4.0)

Citation

Filipiak, P., Sajitha, T. A., Shepherd, T. M., Clarke, K., Goldman, H., Placantonakis, D. G., Zhang, J., Chan, K. C., Boada, F. E., & Baete, S. H. (2023).
In vivo diffusion MRI of optic pathways in 18 healthy mice [Data set]. Zenodo.
https://doi.org/10.5281/zenodo.8120834

Source

https://doi.org/10.5281/zenodo.8120834
Institution: NYU Langone Health, Center for Advanced Imaging Innovation and Research (CAI2R)
Contact: steven.baete@nyulangone.org
Funded by: NIH grants R01 EB028774, R01 EB029306, R01 NS082436, P41 EB017183, and 1S10OD018337-01.

Dataset Information

Experimental Protocol

Following baseline imaging, each mouse received intravitreally administered manganese chloride (MnCl₂) to enhance the T1-weighted signal along the visual pathways.

• Injection volume: 1.0 µL (Mice 1–2), reduced to 0.5 µL (Mice 3–18) of 0.1 M MnCl₂
• Injection side: Left eye (n = 8) or right eye (n = 10)
• Follow-up scan: 21 ± 4 hours post-injection using the same FLASH T1-weighted sequence

To minimize motion artifacts, mice were secured using a bite bar and ear bars and monitored via a breathing pressure pad coupled to a TTL-triggered acquisition system.

Image Processing

The DWI preprocessing pipeline employed MRtrix3 and ANTs tools:

• Denoising: dwidenoise (MP-PCA)
• Gibbs artifact removal: mrdegibbs
• Bias field correction: dwibiascorrect ants
• Resampling: Interpolation to 100 µm isotropic resolution (matching anatomical scans)
• Registration: antsRegistrationSyN.sh (rigid-body transform aligning follow-up MEMRI to b=0 images)

Acknowledgments

This work was supported by the NIH Center for Advanced Imaging Innovation and Research (CAI2R), a NIBIB Biomedical Technology Resource Center (P41 EB017183).
Special thanks to Orin Mishkit, Zakia Ben Youss Gironda, Orlando Aristizabal, and Youssef Wadghiri at the NYU Langone Health Preclinical Imaging Laboratory for technical assistance.

Keywords

Mouse MRI • Diffusion MRI • MEMRI • Optic Pathways • Visual System • MRtrix3 • ANTs • Preclinical Imaging • Bruker BioSpec • Multi-shell DWI • 7 Tesla MRI

This dataset contains whole-brain MRI data from three rhesus macaques, acquired at the Nathan Kline Institute (NKI) Translational Neuroscience Laboratory.
It includes functional MRI (fMRI) with contrast-enhanced (MION) echo planar imaging, T1- and T2-weighted structural scans, and diffusion-weighted imaging (DWI) for each subject.

The fMRI component encompasses a mix of anesthetized resting-state scans, somatosensory stimulation, and awake movie-watching paradigms, enabling multimodal analysis of cortical organization and brain network function in non-human primates.

License

Creative Commons Attribution 4.0 International (CC BY 4.0)

Citation

Russ, B. E., Falchier, A., Linn, G. S., Ross, D. A., Xu, T., Gutierrez, C., Colcombe, S., Schroeder, C. E., & Milham, M. P. (2018).
NKI Translational Neuroscience Laboratory Macaque MRI Dataset (1.0.0) [Data set]. Zenodo.
https://doi.org/10.5281/zenodo.1303400

Source

https://doi.org/10.5281/zenodo.1303400
Contact: michael.milham@childmind.org
Institution: Nathan Kline Institute for Psychiatric Research
Associated Labs: Translational Neuroscience Laboratory, Child Mind Institute, Columbia University
Funding: Supported by the Nathan Kline Institute and the Child Mind Institute

Dataset Information

Purpose

The NKI Macaque MRI Dataset provides a multimodal reference for investigating cross-species neuroimaging, particularly in the context of functional connectivity, anatomical tractography, and comparative cortical mapping.
It enables validation of non-human primate connectomics and supports methodological development in fMRI preprocessing, motion correction, and cross-species registration workflows.

File Information

Keywords

fMRI • Macaque • Resting-State • Somatosensory Stimulation • DTI • Non-Human Primate • MION • Diffusion MRI • Comparative Neuroscience