Open Access Highly Accessed Research article

Functional neural network analysis in frontotemporal dementia and Alzheimer's disease using EEG and graph theory

Willem de Haan1*, Yolande AL Pijnenburg1, Rob LM Strijers2, Yolande van der Made2, Wiesje M van der Flier1, Philip Scheltens1 and Cornelis J Stam2

Author Affiliations

1 Alzheimer center and Department of Neurology, VU University Medical Center, Amsterdam, the Netherlands

2 Department of Clinical Neurophysiology, VU University Medical Center, Amsterdam, the Netherlands

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BMC Neuroscience 2009, 10:101  doi:10.1186/1471-2202-10-101

Published: 21 August 2009

Additional files

Additional file 1:

Threshold analysis in the lower alpha frequency band (8–10 Hz). Graph analysis results of unweighted networks as presented in this paper are dependent on an arbitrarily chosen threshold (in our study K, mean degree of the network). This supplement, including 3 figures, shows that the reported results (K = 5) are representative for a broad range of K thresholds.

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Additional file 2:

Clustering coefficient. Group comparison of the normalized clustering coefficient (Cp/Cp-s or γ) between conditions for different mean network degrees K (* p < 0.05 ** p < 0.01 compared to SMC).

Format: TIFF Size: 94KB Download file

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Additional file 3:

Path Length. Group comparison of the normalized characteristic path length (Lp/Lp-s or λ) between conditions for different mean network degrees K (* p < 0.05 ** p < 0.01 compared to SMC).

Format: TIFF Size: 90KB Download file

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Additional file 4:

Degree correlation. Group comparison of the degree correlation (R) for different mean network degrees K (* p < 0.05 ** p < 0.01 compared to SMC).

Format: TIFF Size: 91KB Download file

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