Evidence map›Paper›PMID 41282656›Full record

ArticlemedRxiv : the preprint server for health sciences2025

An open, longitudinal resource for mapping interindividual variation in the aging connectome.

Anna MacKay-Brandt, Yunglin Gazes, Daniel Garcia-Barnett, Lauren Grebe, Olivia Ripley, Kai Xuan Gan, Kristin T Trautman, Melissa Kramer, Melissa Breland, Russell Tobe and 4 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors.

Anna MacKay-BrandtBrain Aging and Mental Health Laboratory, Clinical Research, Nathan Kline Institute, Orangeburg, NY, USA.ORCID 0009-0007-7960-6636
Yunglin GazesDesign Acquisition and Neuromodulation Laboratories, Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY, USA.ORCID 0000-0002-3268-3438
Daniel Garcia-BarnettDesign Acquisition and Neuromodulation Laboratories, Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY, USA.
Lauren GrebeCommunication Sciences and Disorders, St. John's University, Queens, NY, USA.
Olivia RipleyDesign Acquisition and Neuromodulation Laboratories, Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY, USA.
Kai Xuan GanBrain Aging and Mental Health Laboratory, Clinical Research, Nathan Kline Institute, Orangeburg, NY, USA.
Kristin T TrautmanBrain Aging and Mental Health Laboratory, Clinical Research, Nathan Kline Institute, Orangeburg, NY, USA.
Melissa KramerClinical Research, Nathan Kline Institute, Orangeburg, NY, 10962, USA.
Melissa BrelandClinical Research, Nathan Kline Institute, Orangeburg, NY, 10962, USA.
Russell TobeClinical Research, Nathan Kline Institute, Orangeburg, NY, 10962, USA.ORCID 0000-0002-7738-8344
Alexandre FrancoDesign Acquisition and Neuromodulation Laboratories, Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY, USA.ORCID 0000-0002-1552-1090
Vilma GabbayClinical Research, Nathan Kline Institute, Orangeburg, NY, 10962, USA.ORCID 0000-0001-8819-5137
Michael MilhamDesign Acquisition and Neuromodulation Laboratories, Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY, USA.ORCID 0000-0003-3532-1210
Stan ColcombeDesign Acquisition and Neuromodulation Laboratories, Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY, USA.ORCID 0000-0001-5051-2491

Funding

Mapping interindividual variation in the aging connectomeR01AG047596 · NIA · NATHAN S. KLINE INSTITUTE FOR PSYCH RES · PI COLCOMBE, STAN J, MILHAM, MICHAEL PETER · 2015 to 2019
$3.1M
Discovery Science of Human Brain Function Across the LifespanR01MH094639 · NIMH · NATHAN S. KLINE INSTITUTE FOR PSYCH RES · PI MILHAM, MICHAEL PETER · 2011 to 2014
$2.7M
Real-time fMRI Neurofeedback Based Stratification of Default Network RegulationR01MH101555 · NIMH · NATHAN S. KLINE INSTITUTE FOR PSYCH RES · PI CRADDOCK, RICHARD CAMERON · 2013 to 2016
$2.6M
NIA NIH HHS R01 AG047596NIMH NIH HHS R01 MH094639NIMH NIH HHS R01 MH101555
6 · The paper itself

Abstract

Trajectories of age-related neurocognitive decline are not uniform, and are impacted by numerous environmental and physiological factors. Earlier life phases set the stage for later life neurocognitive function, with midlife marking a critical transition characterized by increasing variability in cognitive, affective, and physiological functioning. Despite its importance, this turbulent period remains underrepresented in open neuroimaging and phenotypic data resources. To address this gap, the Nathan Kline Institute - Rockland Sample (NKI-RS) initiative created the 'Mapping Interindividual Variation in the Aging Connectome' (MIVAC) substudy-an openly shared, multimodal dataset designed to map brain aging trajectories beginning in midlife and assess the influence of modifiable factors such as cardiorespiratory fitness. This longitudinal investigation includes 348 community-ascertained participants aged 38 to 71 years at baseline. Data collection incorporated deep phenotyping across cognitive, behavioral, medical, and cardiorespiratory fitness domains, along with multimodal neuroimaging (resting-state fMRI, diffusion MRI, morphometric MRI, and arterial spin labeling) and biospecimen collection. The protocol harmonizes with prior NKI-RS substudies while incorporating age-specific considerations for cognitive and neural aging. The full dataset is openly available.

Identifiers

PMID41282656
PMCPMC12633132

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.