Spread of activation and deactivation in the brain: Does age matter?

Brian A. Gordon, Chun Yu Tse, Gabriele Gratton, Monica Fabiani

Research output: Contribution to journalArticle

Abstract

Cross-sectional aging functional MRI results are sometimes difficult to interpret, as standard measures of activation and deactivation may confound variations in signal amplitude and spread, which however, may be differentially affected by age-related changes in various anatomical and physiological factors. To disentangle these two types of measures, here we propose a novel method to obtain independent estimates of the peak amplitude and spread of the BOLD signal in areas activated (task-positive) and deactivated (task-negative) by a Sternberg task, in 14 younger and 28 older adults. The peak measures indicated that, compared to younger adults, older adults had increased activation of the task-positive network, but similar levels of deactivation in the task-negative network. Measures of signal spread revealed that older adults had an increased spread of activation in task-positive areas, but a starkly reduced spread of deactivation in task-negative areas. These effects were consistent across regions within each network. Further, there was greater variability in the anatomical localization of peak points in older adults, leading to reduced cross-subject overlap. These results reveal factors that may confound the interpretation of studies of aging. Additionally, spread measures may be linked to local connectivity phenomena and could be particularly useful to analyze age-related deactivation patterns, complementing the results obtained with standard peak and region of interest analyses.

Original languageEnglish (US)
Article number288
JournalFrontiers in Aging Neuroscience
Volume6
Issue numberOCT
DOIs
StatePublished - 2014

Keywords

  • Activation
  • Aging
  • Deactivation
  • Default mode network (DMN)
  • Functional magnetic resonance imaging (fMRI)
  • Spread
  • Task-negative network
  • Task-positive network

ASJC Scopus subject areas

  • Aging
  • Cognitive Neuroscience

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