Understanding variability in the BOLD signal and why it matters for aging
Recent work in neuroscience supports the idea that variability in brain function is necessary for optimal brain responsivity to a changing environment. In this review, we discuss a series of functional magnetic resonance imaging (fMRI) studies in younger and older adults to assess age-related differences in variability of the fMRI signal. This work shows that moment-to-moment brain signal variability represents an important “signal” within what is typically considered measurement-related “noise” in fMRI. This accumulation of evidence suggests that moving beyond the mean will provide a complementary window into aging-related neural processes.
KeywordfMRI BOLD signal Variability Aging Cognition
This work was supported by the Canadian Institutes of Health Research (grant #MOP14036). C.L.G. also is supported by the Canada Research Chairs program, the Ontario Research Fund, and the Canadian Foundation for Innovation.
- Deco, G., Jirsa, V. K., & McIntosh, A. R. (2011). Emerging concepts for the dynamical organization of resting-state activity in the brain. Nature reviews. Neuroscience, 12(1), 43–56.Google Scholar
- Deco, G., Jirsa, V., McIntosh, A. R., Sporns, O., & Kotter, R. (2009). Key role of coupling, delay, and noise in resting brain fluctuations. Proceedings of the National Academy of Sciences of the United States of America, 106(25), 10302–10307.Google Scholar
- Ghosh, A., Rho, Y., McIntosh, A. R., Kotter, R., & Jirsa, V. K. (2008). Noise during rest enables the exploration of the brain's dynamic repertoire. PLoS computational biology, 4(10), e1000196.Google Scholar
- Grady, C. L., Protzner, A. B., Kovacevic, N., Strother, S. C., Afshin-Pour, B., Wojtowicz, M., et al. (2010). A multivariate analysis of age-related differences in default mode and task-positive networks across multiple cognitive domains. Cerebral Cortex, 20(6), 1432–1447.PubMedCentralPubMedCrossRefGoogle Scholar
- Huettel, S. A., Song, A. W., & McCarthy, G. (2004). Functional magnetic resonance imaging. Sunderland: Sinauer Associates.Google Scholar
- Kannurpatti, S. S., Motes, M. A., Rypma, B., & Biswal, B. B. (2010a). Increasing measurement accuracy of age-related BOLD signal change: minimizing vascular contributions by resting-state-fluctuation-of-amplitude scaling. Human Brain Mapping, 32(7), 1125–1140.PubMedCentralPubMedCrossRefGoogle Scholar
- McIntosh, A. R., Vakorin, V., Kovacevic, N., Wang, H., Diaconescu, A., & Protzner, A. B. (2013). Spatiotemporal Dependency of Age-Related Changes in Brain Signal Variability. Cerebral Cortex.Google Scholar
- Miller, M. B., Van Horn, J. D., Wolford, G. L., Handy, T. C., Valsangkar-Smyth, M., Inati, S., et al. (2002). Extensive individual differences in brain activations associated with episodic retrieval are reliable over time. Journal of Cognitive Neuroscience, 14(8), 1200–1214.PubMedCrossRefGoogle Scholar
- Park, D. C., Polk, T. A., Hebrank, A. C., & Jenkins, L. J. (2010). Age differences in default mode activity on easy and difficult spatial judgment tasks. Frontiers in Human Neuroscience, 3, 10.3389/neuro.3309.3075.2009Google Scholar