The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Altered temporal correlations in parietal alpha and prefrontal theta oscillations in early-stage Alzheimer disease
Open accessAbstract
Encoding and retention of information in memory are associated with a sustained increase in the amplitude of neuronal oscillations for up to several seconds. We reasoned that coordination of oscillatory activity over time might be important for memory and, therefore, that the amplitude modulation of oscillations may be abnormal in Alzheimer disease (AD). To test this hypothesis, we measured magnetoencephalography (MEG) during eyes-closed rest in 19 patients diagnosed with early-stage AD and 16 age-matched control subjects and characterized the autocorrelation structure of ongoing oscillations using detrended fluctuation analysis and an analysis of the life- and waiting-time statistics of oscillation bursts. We found that Alzheimer's patients had a strongly reduced incidence of alpha-band oscillation bursts with long life- or waiting-times (< 1 s) over temporo-parietal regions and markedly weaker autocorrelations on long time scales (1–25 seconds). Interestingly, the life- and waiting-times of theta oscillations over medial prefrontal regions were greatly increased. Whereas both temporo-parietal alpha and medial prefrontal theta oscillations are associated with retrieval and retention of information, metabolic and structural deficits in early-stage AD are observed primarily in temporo-parietal areas, suggesting that the enhanced oscillations in medial prefrontal cortex reflect a compensatory mechanism. Together, our results suggest that amplitude modulation of neuronal oscillations is important for cognition and that indices of amplitude dynamics of oscillations may prove useful as neuroimaging biomarkers of early-stage AD.
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
The Brain's Default Network: Anatomy, Function, and Relevance to Disease
Buckner, R. L., Andrews‐Hanna, J. R., & Schacter, D. L. (2008) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1440.011 · Cited by 9,761
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
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
Self-citationGreicius, M. D., Srivastava, G., Reiss, A. L., & Menon, V. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0308627101 · Cited by 3,684
Wandering minds: the default network and stimulus-independent thought
Mason, M. F., Norton, M. I., Van Horn, J. D., Wegner, D. M., Grafton, S. T., & Macrae, C. N. (2007) · Science · doi:10.1126/science.1131295 · Cited by 2,792
Smallwood, J., & Schooler, J. W. (2006) · Psychological Bulletin · doi:10.1037/0033-2909.132.6.946 · Cited by 2,067
Long-Range Temporal Correlations and Scaling Behavior in Human Brain Oscillations
Linkenkaer-Hansen, K., Nikouline, V. V., Palva, J. M., & Ilmoniemi, R. J. (2001) · The Journal of Neuroscience · doi:10.1523/jneurosci.21-04-01370.2001 · Cited by 1,149 · cited 2×
“The main steps from the broadband MEG signal to the quantification of LRTC using DFA have been explained in detail elsewhere (23, 49, 50).”
BackgroundMethodSelf-citationDynamics of Gray Matter Loss in Alzheimer's Disease
Thompson, P. M., Hayashi, K. M., de Zubicaray, G., Janke, A. L., Rose, S. E., Semple, J., Herman, D., Hong, M. S., Dittmer, S. S., Doddrell, D. M., et al. (2003) · The Journal of Neuroscience · doi:10.1523/jneurosci.23-03-00994.2003 · Cited by 1,132
Conceptual Processing during the Conscious Resting State: A Functional MRI Study
Binder, J. R., Frost, J. A., Hammeke, T. A., Bellgowan, P. S. F., Rao, S. M., & Cox, R. W. (1999) · Journal of Cognitive Neuroscience · doi:10.1162/089892999563265 · Cited by 1,066
Cited by
Transcranial Alternating Current Stimulation Enhances Individual Alpha Activity in Human EEG
Zaehle, T., Rach, S., & Herrmann, C. S. (2010) · PLoS ONE · doi:10.1371/journal.pone.0013766 · Cited by 803
Scale-free brain activity: past, present, and future
He, B. J. (2014) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2014.04.003 · Cited by 802
Palva, J. M., Zhigalov, A., Hirvonen, J., Korhonen, O., Linkenkaer-Hansen, K., & Palva, S. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1216855110 · Cited by 462
Self-citationScaling laws in cognitive sciences
Kello, C. T., Brown, G. D. A., Ferrer-i-Cancho, R., Holden, J. G., Linkenkaer-Hansen, K., Rhodes, T., & Van Orden, G. C. (2010) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2010.02.005 · Cited by 384
Self-citationGrandy, T. H., Werkle‐Bergner, M., Chicherio, C., Schmiedek, F., Lövdén, M., & Lindenberger, U. (2013) · Psychophysiology · doi:10.1111/psyp.12043 · Cited by 276
Metadata
- Authors
- Montez, T., Poil, S.-S., Jones, B. F., Manshanden, I., Verbunt, J. P. A., van Dijk, B. W., Brussaard, A. B., van Ooyen, A., Stam, C. J., Scheltens, P., & Linkenkaer-Hansen, K.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2009-02-03
- Volume
- 106
- Issue
- 5
- Pages
- 1614-1619
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W1989973983
- Cited by
- 315
- References
- 13
- FWCI
- 7.46
- Type
- journal article
- Language
- en
- Open access
- green
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: Altered temporal correlations in parietal alpha and prefrontal theta oscillations in early-stage Alzheimer disease. https://app.cochat.ai/papers/10.1073/pnas.0811699106
- The paper
- Montez, T., Poil, S.-S., Jones, B. F., Manshanden, I., Verbunt, J. P. A., van Dijk, B. W., Brussaard, A. B., van Ooyen, A., Stam, C. J., Scheltens, P., & Linkenkaer-Hansen, K. (2009). Altered temporal correlations in parietal alpha and prefrontal theta oscillations in early-stage Alzheimer disease. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.0811699106
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.
