The DOI matches its Crossref record; 85 of the 85 references it cites were found in a registry or an index.
Neural Mechanisms of Sustained Attention Are Rhythmic
Open accessAbstract
Summary Classic models of attention suggest that sustained neural firing constitutes a neural correlate of sustained attention. However, recent evidence indicates that behavioral performance fluctuates over time, exhibiting temporal dynamics that closely resemble the spectral features of ongoing, oscillatory brain activity. Therefore, it has been proposed that periodic neuronal excitability fluctuations might shape attentional allocation and overt behavior. However, empirical evidence to support this notion is sparse. Here, we address this issue by examining data from large-scale subdural recordings, using two different attention tasks that track perceptual ability at high temporal resolution. Our results reveal that perceptual outcome varies as a function of the theta phase even in states of sustained spatial attention. These effects were robust at the single-subject level, suggesting that rhythmic perceptual sampling is an inherent property of the frontoparietal attention network. Collectively, these findings support the notion that the functional architecture of top-down attention is intrinsically rhythmic.
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
Delorme, A., & Makeig, S. (2004) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2003.10.009 · Cited by 24,371
Cortical Surface-Based Analysis
Dale, A. M., Fischl, B., & Sereno, M. I. (1999) · NeuroImage · doi:10.1006/nimg.1998.0395 · Cited by 10,910
Oostenveld, R., Fries, P., Maris, E., & Schoffelen, J.-M. (2011) · Computational Intelligence and Neuroscience · doi:10.1155/2011/156869 · Cited by 10,323
Nonparametric statistical testing of EEG- and MEG-data
Maris, E., & Oostenveld, R. (2007) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2007.03.024 · Cited by 8,496
Neuronal Oscillations in Cortical Networks
Buzsáki, G., & Draguhn, A. (2004) · Science · doi:10.1126/science.1099745 · Cited by 6,576
Statistical Parametric Mapping: The Analysis of Functional Brain Images
Penny, W. D., Friston, K. J., Ashburner, J., Kiebel, S. J., & Thomas, N. (2007) · UCL Discovery (University College London) · Cited by 3,339
CircStat : A MATLAB Toolbox for Circular Statistics
Berens, P. (2009) · Journal of Statistical Software · doi:10.18637/jss.v031.i10 · Cited by 3,099
High Gamma Power Is Phase-Locked to Theta Oscillations in Human Neocortex
Canolty, R. T., Edwards, E., Dalal, S. S., Soltani, M., Nagarajan, S. S., Kirsch, H. E., Berger, M. S., Barbaro, N. M., & Knight, R. T. (2006) · Science · doi:10.1126/science.1128115 · Cited by 2,650
Self-citationParameterizing neural power spectra into periodic and aperiodic components
Donoghue, T., Haller, M., Peterson, E. J., Varma, P., Sebastian, P., Gao, R., Noto, T., Lara, A. H., Wallis, J. D., Knight, R. T., et al. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-00744-x · Cited by 2,254
Self-citationLow-frequency neuronal oscillations as instruments of sensory selection
Schroeder, C. E., & Lakatos, P. (2009) · Trends in Neurosciences · doi:10.1016/j.tins.2008.09.012 · Cited by 1,528
Cited by
Miller, E. K., Lundqvist, M., & Bastos, A. M. (2018) · Neuron · doi:10.1016/j.neuron.2018.09.023 · Cited by 797
A New Unifying Account of the Roles of Neuronal Entrainment
Lakatos, P., Gross, J., & Thut, G. (2019) · Current Biology · doi:10.1016/j.cub.2019.07.075 · Cited by 508
A Rhythmic Theory of Attention
Fiebelkorn, I. C., & Kastner, S. (2019) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2018.11.009 · Cited by 478
Self-citationNeural Entrainment and Attentional Selection in the Listening Brain
Obleser, J., & Kayser, C. (2019) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2019.08.004 · Cited by 432
A Dynamic Interplay within the Frontoparietal Network Underlies Rhythmic Spatial Attention
Fiebelkorn, I. C., Pinsk, M. A., & Kastner, S. (2018) · Neuron · doi:10.1016/j.neuron.2018.07.038 · Cited by 356
Self-citation
Metadata
- Authors
- Helfrich, R. F., Fiebelkorn, I. C., Szczepanski, S. M., Lin, J. J., Parvizi, J., Knight, R. T., & Kastner, S.
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2018-08
- Volume
- 99
- Issue
- 4
- Pages
- 854-865.e5
- ISSN
- 0896-6273 (ISSN-L)
- OpenAlex
- W2888238712
- Cited by
- 447
- References
- 85
- FWCI
- 21.86
- 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: Neural Mechanisms of Sustained Attention Are Rhythmic. https://app.cochat.ai/papers/10.1016/j.neuron.2018.07.032
- The paper
- Helfrich, R. F., Fiebelkorn, I. C., Szczepanski, S. M., Lin, J. J., Parvizi, J., Knight, R. T., & Kastner, S. (2018). Neural Mechanisms of Sustained Attention Are Rhythmic. Neuron. https://doi.org/10.1016/j.neuron.2018.07.032
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.
