The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.
Infraslow LFP correlates to resting-state fMRI BOLD signals
Open accessAbstract
The slow fluctuations of the blood-oxygenation-level dependent (BOLD) signal in resting-state fMRI are widely utilized as a surrogate marker of ongoing neural activity. Spontaneous neural activity includes a broad range of frequencies, from infraslow (<0.5 Hz) fluctuations to fast action potentials. Recent studies have demonstrated a correlative relationship between the BOLD fluctuations and power modulations of the local field potential (LFP), particularly in the gamma band. However, the relationship between the BOLD signal and the infraslow components of the LFP, which are directly comparable in frequency to the BOLD fluctuations, has not been directly investigated. Here we report a first examination of the temporal relation between the resting-state BOLD signal and infraslow LFPs using simultaneous fMRI and full-band LFP recording in rat. The spontaneous BOLD signal at the recording sites exhibited significant localized correlation with the infraslow LFP signals as well as with the slow power modulations of higher-frequency LFPs (1-100 Hz) at a delay comparable to the hemodynamic response time under anesthesia. Infraslow electrical activity has been postulated to play a role in attentional processes, and the findings reported here suggest that infraslow LFP coordination may share a mechanism with the large-scale BOLD-based networks previously implicated in task performance, providing new insight into the mechanisms contributing to the resting state fMRI signal.
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Functional connectivity in the motor cortex of resting human brain using echo‐planar mri
Biswal, B., Zerrin Yetkin, F., Haughton, V. M., & Hyde, J. S. (1995) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910340409 · Cited by 9,812
The human brain is intrinsically organized into dynamic, anticorrelated functional networks
Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0504136102 · Cited by 8,553
Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging
Fox, M. D., & Raichle, M. E. (2007) · Nature Reviews Neuroscience · doi:10.1038/nrn2201 · Cited by 6,700
Neurophysiological investigation of the basis of the fMRI signal
Logothetis, N. K., Pauls, J., Augath, M., Trinath, T., & Oeltermann, A. (2001) · Nature · doi:10.1038/35084005 · Cited by 6,551
Thresholding of statistical maps in functional neuroimaging using the false discovery rate
Genovese, C. R., Lazar, N. A., & Nichols, T. (2002) · NeuroImage · doi:10.1006/nimg.2001.1037 · Cited by 4,923
Murphy, K., Birn, R. M., Handwerker, D. A., Jones, T. B., & Bandettini, P. A. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.09.036 · Cited by 2,387
Mitzdorf, U. (1985) · Physiological Reviews · doi:10.1152/physrev.1985.65.1.37 · Cited by 1,690
Logothetis, N. K., & Wandell, B. A. (2004) · Annual Review of Physiology · doi:10.1146/annurev.physiol.66.082602.092845 · Cited by 1,568
A Method for Removing Imaging Artifact from Continuous EEG Recorded during Functional MRI
Allen, P. J., Josephs, O., & Turner, R. (2000) · NeuroImage · doi:10.1006/nimg.2000.0599 · Cited by 1,301
Slow potentials of the cerebral cortex and behavior.
Birbaumer, N., Elbert, T. R., Canavan, A. G. M., & Rockstroh, B. S. (1990) · Physiological Reviews · doi:10.1152/physrev.1990.70.1.1 · Cited by 1,099
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Metadata
- Authors
- Pan, W.-J., Thompson, G. J., Magnuson, M. E., Jaeger, D., & Keilholz, S.
- Affiliations
- Georgia Institute of Technology (US)
- Emory University (US)
- Corresponding author
- Keilholz, Shella
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2013-07
- Volume
- 74
- Pages
- 288-297
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC3615090
- OpenAlex
- W2165465442
- Cited by
- 231
- References
- 53
- Citations by year
- 2026: 9 · 2025: 6 · 2024: 23 · 2023: 13 · 2022: 23 · 2021: 14 · 2020: 13 · 2019: 15 · 2018: 27 · 2017: 18 · 2016: 20 · 2015: 22 · 2014: 21 · 2013: 7
- FWCI
- 12.75
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NIH (1R21NS072810-01A1, 1R21NS057718-01)
- 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 dynamics and brain function
- Keywords
- slow fluctuations, spontaneous neuronal activity, rat brain, attention, large-scale brain networks
- MeSH terms
- Action Potentials, Animals, Brain, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Neurons, Oxygen, Rest, Rats, Sprague-Dawley, Rats
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