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Open Imaging Index
MRI Brain

PAN HML MRI

Precision Aging Network: Closing the Gap Between Cognitive Healthspan and Human Lifespan

Brain MRI of cognitively unimpaired adults aged 50 to 79, collected to find what drives risk of and resilience to age-related cognitive decline. Structural, susceptibility, diffusion, perfusion and resting-state scans from four US sites, with two-year follow-up for some participants.

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Overview

The Healthy Minds for Life study of the Precision Aging Network examines why some people keep their memory and thinking into old age while others decline, with the aim of tailoring interventions to the individual. It recruited adults from the online MindCrowd cohort at four US universities: Arizona (Tucson), Miami, Emory (Atlanta) and Johns Hopkins (Baltimore). This entry covers only the 3T brain MRI, which the network shares on OpenNeuro as ds007522 under a CC0 waiver. The other study data are held on the network's own portal under a separate data use agreement.

Composition

Release 2.0.1 holds 969 participants and 1064 imaging sessions. Participants self-identified as White, Black or Hispanic, were aged 50 to 79 at enrolment (two are listed as 49), spoke English and had no diagnosis of memory loss or dementia. About 70% are women. Most have one baseline session; 78 people scanned in Tucson also have a follow-up about two years later. Further sessions labeled as repeats replace scans that failed for technical reasons. participants.tsv gives age, sex, handedness and site.

Acquisition

Each site used one scanner: Siemens Skyra in Tucson, Siemens Prisma Fit in Atlanta, Siemens Vida in Miami and a Philips Ingenia Elition X in Baltimore. The protocol has a defaced T1w and FLAIR, a high-resolution hippocampal T2w, a five-echo T2starw series with magnitude and phase (suitable for susceptibility mapping), diffusion MRI with a reversed phase-encoding scan, arterial spin labeling with an M0 scan, and resting-state BOLD. No dedicated field maps were run for ASL and fMRI; the README explains how to derive them from the multi-echo and reversed phase-encoded scans. Per session, sessions.tsv lists scanner model, software version and free-text notes. Several scanner software upgrades happened during the study.

Annotations

There are no image labels. Derived MRI measures and processing protocols are available on the network's data portal under its agreement, not in this release.

Known limitations

  • Manual quality control is still in progress; failed scans were removed and the reasons are listed under derivatives.
  • Not every subject has every contrast: 611 have all seven, and the hippocampal T2w is missing for about a third.
  • One scanner per site, so site and vendor are confounded.
  • Scan dates were shifted by 1 to 15 days per subject.

Cohort

Aggregate numbers from the sources below. Bars are relative to the 969 subjects.

Sex

  • Female 673 69%
  • Male 296 31%

sex in participants.tsv of ds007522 snapshot 2.0.1 (CC0), counted per row

Modality

  • MRI 969 100%

sub-*/ses-*/ in BIDS file tree and per-subject sessions.tsv of ds007522 snapshot 2.0.1 (CC0), NIfTI files counted per suffix and scanner models per session

Condition

Groups can overlap

  • Healthy control 969 100%

README, Participant Recruitment & Eligibility in OpenNeuro ds007522 snapshot 2.0.1 (dataset_description.json, README, CHANGES and snapshot size)

Scanner vendor

  • Siemens Healthineers 750 77%
  • Philips 219 23%

sub-*/sub-*_sessions.tsv (manufacturer_model) in BIDS file tree and per-subject sessions.tsv of ds007522 snapshot 2.0.1 (CC0), NIfTI files counted per suffix and scanner models per session

Field strength

  • 3 T 969 100%

README in OpenNeuro ds007522 snapshot 2.0.1 (dataset_description.json, README, CHANGES and snapshot size)

Age

mean 63.9 ± 7.8, median 64, range 49 to 79

0
100
200
300
400
412
40-4950-5960-6970-79

age in participants.tsv of ds007522 snapshot 2.0.1 (CC0), counted per row

Contrast / sequence

Groups can overlap

  • T1-weighted 968 100%
  • Diffusion-weighted 963 99%
  • BOLD fMRI 963 99%
  • FLAIR 955 99%
  • Arterial spin labeling 951 98%
  • T2*-weighted 932 96%
  • T2-weighted 618 64%

anat/*_T1w.nii.gz, anat/*_FLAIR.nii.gz, anat/*_T2w.nii.gz, anat/*_T2starw.nii.gz, dwi/*_dwi.nii.gz, perf/*_asl.nii.gz, func/*_task-rest_bold.nii.gz in BIDS file tree and per-subject sessions.tsv of ds007522 snapshot 2.0.1 (CC0), NIfTI files counted per suffix and scanner models per session

Country

  • United States 969 100%

site in participants.tsv of ds007522 snapshot 2.0.1 (CC0), counted per row

Age by sex

Reported cross table. Missing cells were not published (fewer than 10 or not reported).

Female Male
  • 164
    70-79
    91
  • 287
    60-69
    125
  • 220
    50-59
    80

sex, age in participants.tsv of ds007522 snapshot 2.0.1 (CC0), counted per row

Contrast combinations

How many subjects have exactly each set of contrasts.

T1wT2wFLAIRT2starwdwiboldaslSubjects with exactly this set
611
309
23
5
4
4
3
3
3
1
1
1
1

From BIDS file tree and per-subject sessions.tsv of ds007522 snapshot 2.0.1 (CC0), NIfTI files counted per suffix and scanner models per session

License and access

Our reading of the license, not legal advice. Before you use the data, read the original license and confirm that your use is allowed. We take no responsibility for how you use a dataset. Full disclaimer

Access
Open download

Download without an account

Access page

Creative Commons Zero 1.0 Universal

Public domain dedication. Do anything with the data, including commercial use, without asking and without having to give credit.

dataset_description.json and README of snapshot 2.0.1 state CC0 for the MRI data on OpenNeuro. Cognitive, biomarker, survey and derived MRI data of the same study are on the PAN data portal under the Precision Aging Network data use agreement and are not part of this entry.

Original license text Version read: 1.0 Checked 2026-10-07

What you can do

  • Yes
  • Yes
  • Yes
  • Yes
  • Yes

What you can share

  • Yes
  • Yes
  • Yes

What you must do

  • No
  • Share alike No
  • No
  • No
  • Manuscript review No
  • Release code No
  • Return results No
  • Delete after use No

Limits

  • No
  • Location limits No

Citation

Barnes CA, Huentelman MJ, Chen Z, Ryan L, Rundek T, et al. Precision Aging Network: Closing the Gap Between Cognitive Healthspan and Human Lifespan. OpenNeuro ds007522, version 2.0.1 (2026). doi:10.18112/openneuro.ds007522.v2.0.1. Publications should include the Precision Aging Network writing block and funding statement given in the README.

Sources

Every number on this page comes from one of these documents. Each chart names the table or page it is taken from. The raw numbers are in stats.csv.