The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
Intrinsic resting‐state activity predicts working memory brain activation and behavioral performance
Open accessAbstract
Although resting‐state brain activity has been demonstrated to correspond with task‐evoked brain activation, the relationship between intrinsic and evoked brain activity has not been fully characterized. For example, it is unclear whether intrinsic activity can also predict task‐evoked deactivation and whether the rest–task relationship is dependent on task load. In this study, we addressed these issues on 40 healthy control subjects using resting‐state and task‐driven [N‐back working memory (WM) task] functional magnetic resonance imaging data collected in the same session. Using amplitude of low‐frequency fluctuation (ALFF) as an index of intrinsic resting‐state activity, we found that ALFF in the middle frontal gyrus and inferior/superior parietal lobules was positively correlated with WM task‐evoked activation, while ALFF in the medial prefrontal cortex, posterior cingulate cortex, superior frontal gyrus, superior temporal gyrus, and fusiform gyrus was negatively correlated with WM task‐evoked deactivation. Further, the relationship between the intrinsic resting‐state activity and task‐evoked activation in lateral/superior frontal gyri, inferior/superior parietal lobules, superior temporal gyrus, and midline regions was stronger at higher WM task loads. In addition, both resting‐state activity and the task‐evoked activation in the superior parietal lobule/precuneus were significantly correlated with the WM task behavioral performance, explaining similar portions of intersubject performance variance. Together, these findings suggest that intrinsic resting‐state activity facilitates or is permissive of specific brain circuit engagement to perform a cognitive task, and that resting activity can predict subsequent task‐evoked brain responses and behavioral performance. Hum Brain Mapp 34:3204–3215, 2013. © 2012 Wiley Periodicals, Inc.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Advances in functional and structural MR image analysis and implementation as FSL
Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E. J., Johansen-Berg, H., Bannister, P. R., De Luca, M., Drobnjak, I., Flitney, D. E., et al. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.051 · Cited by 13,630
AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages
Cox, R. W. (1996) · Computers and Biomedical Research · doi:10.1006/cbmr.1996.0014 · Cited by 10,913
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
Functional connectivity in the resting brain: a network analysis of the default mode hypothesis
Greicius, M. D., Krasnow, B., Reiss, A. L., & Menon, V. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0135058100 · Cited by 6,358
(2023) · doi:10.1126/science · Cited by 6,063
Correspondence of the brain's functional architecture during activation and rest
Smith, S. M., Fox, P. T., Miller, K. L., Glahn, D. C., Fox, P. M., Mackay, C. E., Filippini, N., Watkins, K. E., Toro, R., Laird, A. R., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0905267106 · Cited by 5,150
N-back working memory paradigm: a meta-analysis of normative functional neuroimaging studies.
Owen, A. M., McMillan, K. M., Laird, A. R., & Bullmore, E. (2005) · Human Brain Mapping · doi:10.1002/hbm.20131 · Cited by 3,560
Functional-anatomic fractionation of the brain’s default network
Andrews-Hanna, J. R., Reidler, J. S., Sepulcre, J., Poulin, R., & Buckner, R. L. (2010) · Neuron · doi:10.1016/j.neuron.2010.02.005 · Cited by 2,767
Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI
Yu-Feng, Z., Yong, H., Chao-Zhe, Z., Qing-Jiu, C., Man-Qiu, S., Meng, L., Li-Xia, T., Tian-Zi, J., & Yu-Feng, W. (2007) · Brain and Development · doi:10.1016/j.braindev.2006.07.002 · Cited by 2,660
Cited by
Liang, X., Zou, Q., He, Y., & Yang, Y. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhu316 · Cited by 261
Self-citationKong, L., Chen, K., Tang, Y., Wu, F., Driesen, N., Womer, F., Fan, G., Ren, L., Jiang, W., Cao, Y., et al. (2013) · Journal of Psychiatry & Neuroscience · doi:10.1503/jpn.120117 · Cited by 93
The neurocognitive correlates of brain entropy estimated by resting state fMRI
Wang, Z. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.117893 · Cited by 77
Intervention-induced enhancement in intrinsic brain activity in healthy older adults
Yin, S., Zhu, X., Li, R., Niu, Y., Wang, B., Zheng, Z., Huang, X., Huo, L., & Li, J. (2014) · Scientific Reports · doi:10.1038/srep07309 · Cited by 57
Block, S. R., & Liberzon, I. (2016) · Experimental Neurology · doi:10.1016/j.expneurol.2016.05.009 · Cited by 52
Metadata
- Authors
- Zou, Q., Ross, T. J., Gu, H., Geng, X., Zuo, X., Hong, L. E., Gao, J., Stein, E. A., Zang, Y., & Yang, Y.
- Venue
- Human Brain Mapping
- Publisher
- Wiley
- Published
- 2012-06-19
- Volume
- 34
- Issue
- 12
- Pages
- 3204-3215
- ISSN
- 1065-9471 (ISSN-L)
- 1097-0193
- OpenAlex
- W1908041793
- Cited by
- 213
- References
- 20
- FWCI
- 9.06
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Intrinsic resting‐state activity predicts working memory brain activation and behavioral performance. https://app.cochat.ai/papers/10.1002/hbm.22136
- The paper
- Zou, Q., Ross, T. J., Gu, H., Geng, X., Zuo, X., Hong, L. E., Gao, J., Stein, E. A., Zang, Y., & Yang, Y. (2013). Intrinsic resting‐state activity predicts working memory brain activation and behavioral performance. Human Brain Mapping. https://doi.org/10.1002/hbm.22136
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.