The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Moment-to-Moment BOLD Signal Variability Reflects Regional Changes in Neural Flexibility across the Lifespan
Open accessAbstract
Variability of neuronal responses is thought to underlie flexible and optimal brain function. Because previous work investigating BOLD signal variability has been conducted within task-based fMRI contexts on adults and older individuals, very little is currently known regarding regional changes in spontaneous BOLD signal variability in the human brain across the lifespan. The current study used resting-state fMRI data from a large sample of male and female human participants covering a wide age range (6–85 years) across two different fMRI acquisition parameters (TR = 0.645 and 1.4 s). Variability in brain regions including a key node of the salience network (anterior insula) increased linearly across the lifespan across datasets. In contrast, variability in most other large-scale networks decreased linearly over the lifespan. These results demonstrate unique lifespan trajectories of BOLD variability related to specific regions of the brain and add to a growing literature demonstrating the importance of identifying normative trajectories of functional brain maturation. SIGNIFICANCE STATEMENT Although brain signal variability has traditionally been considered a source of unwanted noise, recent work demonstrates that variability in brain signals during task performance is related to brain maturation in old age as well as individual differences in behavioral performance. The current results demonstrate that intrinsic fluctuations in resting-state variability exhibit unique maturation trajectories in specific brain regions and systems, particularly those supporting salience detection. These results have implications for investigations of brain development and aging, as well as interpretations of brain function underlying behavioral changes across the lifespan.
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“Across the age range from 6 to 85 years, BOLD signal variability decreases linearly across most of the brain, with the exception of the AI, a critical M-CIN node involved in flexibility, which shows the opposite pattern60 (Fig. 3).”
From Cognitive and behavioural flexibility: Neural mechanisms and clinical considerations (2021) · cites this paper as [60]
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The assessment and analysis of handedness: The Edinburgh inventory
Oldfield, R. C. (1971) · Neuropsychologia · doi:10.1016/0028-3932(71)90067-4 · Cited by 35,900
Saliency, switching, attention and control: a network model of insula function
Menon, V., & Uddin, L. Q. (2010) · Brain Structure and Function · doi:10.1007/s00429-010-0262-0 · Cited by 5,592
Self-citationBrain development during childhood and adolescence: a longitudinal MRI study
Giedd, J. N., Blumenthal, J., Jeffries, N. O., Castellanos, F. X., Liu, H., Zijdenbos, A., Paus, T., Evans, A. C., & Rapoport, J. L. (1999) · Nature Neuroscience · doi:10.1038/13158 · Cited by 5,552
Consistent resting-state networks across healthy subjects
Damoiseaux, J. S., Rombouts, S. A. R. B., Barkhof, F., Scheltens, P., Stam, C. J., Smith, S. M., & Beckmann, C. F. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0601417103 · Cited by 4,326
Cluster failure: why fMRI inferences for spatial extent have inflated false-positive rates
Eklund, A., Nichols, T. E., & Knutsson, H. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1602413113 · Cited by 3,487
Salience processing and insular cortical function and dysfunction
Uddin, L. Q. (2015) · Nature Reviews Neuroscience · doi:10.1038/nrn3857 · Cited by 2,083
Self-citationResting-state fMRI in the human connectome project
Smith, S. M., Beckmann, C. F., Andersson, J., Auerbach, E. J., Bijsterbosch, J., Douaud, G., Duff, E., Feinberg, D. A., Griffanti, L., Harms, M. P., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.039 · Cited by 1,502
Griffanti, L., Salimi‐Khorshidi, G., Beckmann, C. F., Auerbach, E. J., Douaud, G., Sexton, C. E., Zsoldos, E., Ebmeier, K. P., Filippini, N., Mackay, C. E., et al. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.03.034 · Cited by 1,273
Reduced resting-state brain activity in the “default network” in normal aging
Damoiseaux, J. S., Beckmann, C. F., Arigita, E. J. S., Barkhof, F., Scheltens, P., Stam, C. J., Smith, S. M., & Rombouts, S. A. R. B. (2008) · Cerebral Cortex · doi:10.1093/cercor/bhm207 · Cited by 1,187
Alterations in the BOLD fMRI signal with ageing and disease: a challenge for neuroimaging
D’Esposito, M., Deouell, L. Y., & Gazzaley, A. H. (2003) · Nature reviews. Neuroscience · doi:10.1038/nrn1246 · Cited by 852
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Cognitive and behavioural flexibility: Neural mechanisms and clinical considerations
Uddin, L. Q. (2021) · Nature Reviews Neuroscience · doi:10.1038/s41583-021-00428-w · Cited by 698
Self-citationBehavior needs neural variability
Waschke, L., Kloosterman, N. A., Obleser, J., & Garrett, D. D. (2021) · Neuron · doi:10.1016/j.neuron.2021.01.023 · Cited by 317
Deery, H. A., Paolo, R. D., Moran, C., Egan, G. F., & Jamadar, S. D. (2022) · Psychophysiology · doi:10.1111/psyp.14159 · Cited by 188
Bring the Noise: Reconceptualizing Spontaneous Neural Activity
Uddin, L. Q. (2020) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2020.06.003 · Cited by 179
Self-citationEndless Fluctuations: Temporal Dynamics of the Amplitude of Low Frequency Fluctuations
Liao, W., Chen, H., Li, J., Ji, G., Wu, G., Long, Z., Xu, Q., Duan, X., Cui, Q., & Biswal, B. B. (2019) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2019.2904555 · Cited by 143
Metadata
- Authors
- Nomi, J. S., Bolt, T. S., Ezie, C. E. C., Uddin, L. Q., & Heller, A. S.
- Affiliations
- University of Miami (US)
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2017-05-04
- Volume
- 37
- Issue
- 22
- Pages
- 5539-5548
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC5452342
- OpenAlex
- W2611008202
- Cited by
- 164
- References
- 38
- Citations by year
- 2026: 16 · 2025: 16 · 2024: 21 · 2023: 17 · 2022: 21 · 2021: 24 · 2020: 20 · 2019: 14 · 2018: 9 · 2017: 6
- FWCI
- 7.60
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Neuroscience (publishedVersion, cc-by-nc-sa)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- University of Miami
- National Alliance for Research on Schizophrenia and Depression (R01MH107549)
- National Institute of Mental Health (R01MH107549)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- BOLD signal variability, resting-state fMRI, lifespan development, brain maturation, neural flexibility, salience network, anterior insula, large-scale brain networks, aging, individual differences
- MeSH terms
- Adolescent, Adult, Aged, Aged, 80 and over, Aging, Brain, Brain Mapping, Cerebrovascular Circulation, Child, Female, Humans, Longevity, Magnetic Resonance Imaging, Male, Middle Aged, Nerve Net, Neuronal Plasticity, Oxygen Consumption, Rest, Young Adult
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