Abstract
Within-individual blood oxygen level-dependent (BOLD) signal variability, intrinsic moment-to-moment signal fluctuations within a single individual in specific voxels across a given time course, is a relatively new metric recognized in the neuroimaging literature. Within-individual BOLD signal variability has been postulated to provide information beyond that provided by mean-based analysis. Synthesis of the literature using within-individual BOLD signal variability methodology to examine various cognitive domains is needed to understand how intrinsic signal fluctuations contribute to optimal performance. This systematic review summarizes and integrates this literature to assess task-based cognitive performance in healthy groups and few clinical groups. Included papers were published through October 17, 2022. Searches were conducted on PubMed and APA PsycInfo. Studies eligible for inclusion used within-individual BOLD signal variability methodology to examine BOLD signal fluctuations during task-based functional magnetic resonance imaging (fMRI) and/or examined relationships between task-based BOLD signal variability and out-of-scanner behavioral measure performance, were in English, and were empirical research studies. Data from each of the included 19 studies were extracted and study quality was systematically assessed. Results suggest that variability patterns for different cognitive domains across the lifespan (ages 7–85) may depend on task demands, measures, variability quantification method used, and age. As neuroimaging methods explore individual-level contributions to cognition, within-individual BOLD signal variability may be a meaningful metric that can inform understanding of neurocognitive performance. Further research in understudied domains/populations, and with consistent quantification methods/cognitive measures, will help conceptualize how intrinsic BOLD variability impacts cognitive abilities in healthy and clinical groups.
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References
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Funding
The first author (SNS) was funded by the Georgia State University Research on the Challenges of Acquiring Language and Literacy Graduate Fellowship. No other funds, grants, or other support was received.
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SNS: idea for the review article, literature search and data extraction/synthesis, draft and critically revise manuscript; TZK: critically revise manuscript.
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Appendices
Appendix 1
List of References for Neuromodulatory Implications of Within-Individual BOLD Signal Variability
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Alavash et al. (2018)
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Cools (2007)
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Cools and D’Esposito (2010)
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Cools and D’Esposito (2011)
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Day et al. (2019)
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Garrett et al. (2015)
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Guitart-Masip et al. (2016)
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Lalwani et al. (2021)
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Ricciardi et al. (2013)
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van Holstein et al. (2011)
Appendix 2
References for resting-state within-individual BOLD signal variability in clinical groups
Reference | Clinical group |
|---|---|
Easson and McIntosh (2019) | Autism Spectrum Disorder |
Good et al. (2020) | Alzheimer’s Disease |
Martino et al. (2016) | Bipolar Depression, Mania |
Millar et al. (2020a) | Alzheimer’s Disease |
Nomi et al. (2017) | Attention-Deficit Hyperactivity Disorder |
Olivé et al. (2021) | Post-Traumatic Stress Disorder |
Petracca et al. (2017) | Multiple Sclerosis |
Scarapicchia et al. (2018) | Alzheimer’s Disease |
Scarapicchia et al. (2019) | Subjective Cognitive Decline |
Zhang et al. (2020) | Alzheimer’s Disease |
Zhang et al. (2021)a | Broad “psychiatric disease” |
Zhao et al. (2020) | Cervical Spondylotic Myelopathy |
Zoller et al. (2017) | 22q11.2 Deletion Syndrome |
Zoller et al. (2018) | 22q11.2 Deletion Syndrome |
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Steinberg, S.N., King, T.Z. Within-Individual BOLD Signal Variability and its Implications for Task-Based Cognition: A Systematic Review. Neuropsychol Rev (2023). https://doi.org/10.1007/s11065-023-09619-x
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DOI: https://doi.org/10.1007/s11065-023-09619-x