Summary: The Dallas Lifespan Brain Study (DLBS) has released its complete, decade-long dataset, offering an unusually detailed longitudinal view of brain and cognitive changes across adulthood. The project tracked nearly 500 healthy adults, ages 21 to 89, across three assessment waves over roughly 10 years, combining MRI and PET imaging, comprehensive cognitive testing, and health and behavioral surveys.
This open-access resource reveals that brain aging follows multiple biological pathways rather than a single uniform cause for cognitive decline. Making the full dataset publicly available enables researchers worldwide to test hypotheses about healthy aging, early decline, and disease progression with rich, multi-modal longitudinal data.
Key Facts:
- Longitudinal design: The same individuals were followed across three timepoints spanning about a decade—rare for brain-aging research.
- Multi-modal and comprehensive: The dataset includes structural and functional MRI, diffusion imaging, arterial spin labeling, hypercapnia scans, amyloid and tau PET, extensive neuropsychological batteries, and health and psychosocial questionnaires.
- Open access: The full dataset is published for scientific reuse, supporting cross-disciplinary studies of brain aging and cognitive trajectories.
Source: UT Dallas
Overview
The Dallas Lifespan Brain Study (DLBS), led by researchers at The University of Texas at Dallas’ Center for Vital Longevity (CVL), was designed to integrate brain imaging and cognitive assessment across the adult lifespan. Data were collected between 2008 and 2020 from an initial sample of 464 participants aged 21–89, with 338 returning for a second assessment and 224 returning for a third, each separated by approximately three to five years.
An overview article describing the dataset and its scientific value appeared in Nature’s Scientific Data on May 26. The project was initiated by Dr. Denise Park, Distinguished University Chair in Behavioral and Brain Sciences and Director of Research at CVL, and supported by long-term funding from the National Institute on Aging via a MERIT (R37) award. That sustained support allowed the team to emphasize careful data collection over a long time horizon rather than short-term publication pressure.
Each participant evaluation combined a broad neuropsychological battery, questionnaires on physical and mental health and lifestyle, multiple MRI modalities (including T1-weighted structural scans and diffusion-weighted imaging), arterial spin labeling and hypercapnia scans, several functional MRI tasks, and PET scans measuring amyloid (AV-45/Florbetapir) and tau (AV-1451/Flortaucipir).
Scientific significance
DLBS findings have already shaped understanding of brain aging. The data revealed patterns of brain network breakdown that occur across the adult lifespan and documented that elevated amyloid burden can be found in cognitively normal adults—evidence that amyloid alone may not be sufficient to cause cognitive impairment. Subsequent waves of the study include tau PET measurements, which help researchers examine how amyloid and tau interact in aging and Alzheimer’s disease risk.
Dr. Park likens the brain to an orchestra in which different sections become more or less important over time. The dataset lets researchers examine multiple neural features simultaneously—white matter integrity, gray matter volume, and task-related neural activation—to understand why individuals follow different cognitive trajectories.
Dr. Gagan Wig, co-corresponding author and associate professor of psychology, emphasized the value of longitudinal data that include middle age, a period often understudied. Following the same people over time makes it possible to identify individual characteristics that predict later cognitive decline or resilience.
Practical value and future research
Publishing this complete open-access repository broadens opportunities for neuroscientists, clinicians, and psychologists to explore questions about normal and pathological aging. Beyond cognition and imaging, the dataset contains rich demographic, health, behavioral, and personality measures that support multidisciplinary analyses of aging risk factors and protective mechanisms.
Although the CVL team and collaborators have already published many papers using parts of this dataset, the public release is intended to accelerate discovery by making the full resource readily accessible. The CVL team plans to continue mining the data for years, and the repository should enable many more independent analyses and new models of cognitive aging.
As Dr. Park approached retirement, she chose to dedicate time to preparing and publishing the dataset for public use, viewing the open repository as a lasting contribution that will pose new questions and enable others to find answers. “I take a lot of pride in completing this in an elegant manner,” she said, noting the data are structured to be accessible for researchers with clear hypotheses.
Contributors and funding
Other UT Dallas authors include Dr. Kristen Kennedy and Dr. Karen Rodrigue, along with additional CVL scientists. Collaborators come from UT Southwestern Medical Center, Harvard Medical School, University of Maryland School of Medicine, Stony Brook University, Johns Hopkins School of Medicine, and Icahn School of Medicine at Mount Sinai. Funding was provided by NIA grants 5R37AG-006265-27 and RC1AG036199.
About this neuroscience and brain aging research news
Author: Stephen Fontenot
Source: UT Dallas
Contact: Stephen Fontenot – UT Dallas
Image: Image credited to Neuroscience News
Original Research: Open access. “The Dallas Lifespan Brain Study: A Comprehensive Adult Lifespan Data Set of Brain and Cognitive Aging” by Denise Park et al., Scientific Data
Abstract
The Dallas Lifespan Brain Study: A Comprehensive Adult Lifespan Data Set of Brain and Cognitive Aging
The DLBS was designed to integrate brain imaging and cognitive assessment across adulthood. Participants (n = 464) ranged from 21 to 89 years at the first assessment and returned roughly every 3.5–5 years for a second (n = 338) and third (n = 224) epoch. Each epoch included a comprehensive neuropsychological battery; questionnaires on physical health, psychosocial status, and brain health; structural MRI (T1-weighted and diffusion-weighted imaging); hypercapnia and arterial spin labeling scans; and multiple functional MRI tasks. PET measures of amyloid and tau were collected with Florbetapir (AV-45) and Flortaucipir (AV-1451). Key innovations include strong sampling of middle-aged adults and PET data in a cognitively normal sample. The full dataset is available as an open-access resource to support wide-ranging longitudinal research into brain aging and cognition.