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Cracking the brain's genetic code.

Proceedings of the National Academy of Sciences of the United States of America

Thompson PM.
PMID: 26582794
Proc Natl Acad Sci U S A. 2015 Dec 15;112(50):15269-70. doi: 10.1073/pnas.1520702112. Epub 2015 Nov 18.

No abstract available.

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Thompson PM. Cracking the brain's genetic code. Proc Natl Acad Sci U S A. 2015;112(50):15269-70doi: 10.1073/pnas.1520702112.
Thompson, P. M. (2015). Cracking the brain's genetic code. Proceedings of the National Academy of Sciences of the United States of America, 112(50), 15269-70. https://doi.org/10.1073/pnas.1520702112
Thompson, Paul M. "Cracking the brain's genetic code." Proceedings of the National Academy of Sciences of the United States of America vol. 112,50 (2015): 15269-70. doi: https://doi.org/10.1073/pnas.1520702112
Thompson PM. Cracking the brain's genetic code. Proc Natl Acad Sci U S A. 2015 Dec 15;112(50):15269-70. doi: 10.1073/pnas.1520702112. Epub 2015 Nov 18. PMID: 26582794; PMCID: PMC4687571.
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Information-Theoretic Characterization of Blood Panel Predictors for Brain Atrophy and Cognitive Decline in the Elderly.

Proceedings. IEEE International Symposium on Biomedical Imaging

Madsen SK, Ver Steeg G, Mezher A, Jahanshad N, Nir TM, Hua X, Gutman BA, Galstyan A, Thompson PM.
PMID: 26413208
Proc IEEE Int Symp Biomed Imaging. 2015 Apr;2015:980-984. doi: 10.1109/ISBI.2015.7164035.

Cognitive decline in old age is tightly linked with brain atrophy, causing significant burden. It is critical to identify which biomarkers are most predictive of cognitive decline and brain atrophy in the elderly. In 566 older adults from the...

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Madsen SK, Ver Steeg G, Mezher A, et al. Information-Theoretic Characterization of Blood Panel Predictors for Brain Atrophy and Cognitive Decline in the Elderly. Proc IEEE Int Symp Biomed Imaging. 2015;2015:980-984doi: 10.1109/ISBI.2015.7164035.
Madsen, S. K., Ver Steeg, G., Mezher, A., Jahanshad, N., Nir, T. M., Hua, X., Gutman, B. A., Galstyan, A., Thompson, P. M. (2015). Information-Theoretic Characterization of Blood Panel Predictors for Brain Atrophy and Cognitive Decline in the Elderly. Proceedings. IEEE International Symposium on Biomedical Imaging, 2015980-984. https://doi.org/10.1109/ISBI.2015.7164035
Madsen, Sarah K, et al. "Information-Theoretic Characterization of Blood Panel Predictors for Brain Atrophy and Cognitive Decline in the Elderly." Proceedings. IEEE International Symposium on Biomedical Imaging vol. 2015 (2015): 980-984. doi: https://doi.org/10.1109/ISBI.2015.7164035
Madsen SK, Ver Steeg G, Mezher A, Jahanshad N, Nir TM, Hua X, Gutman BA, Galstyan A, Thompson PM. Information-Theoretic Characterization of Blood Panel Predictors for Brain Atrophy and Cognitive Decline in the Elderly. Proc IEEE Int Symp Biomed Imaging. 2015 Apr;2015:980-984. doi: 10.1109/ISBI.2015.7164035. PMID: 26413208; PMCID: PMC4578218.
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AUTOMATED MULTI-ATLAS LABELING OF THE FORNIX AND ITS INTEGRITY IN ALZHEIMER'S DISEASE.

Proceedings. IEEE International Symposium on Biomedical Imaging

Jin Y, Shi Y, Zhan L, Thompson PM.
PMID: 26413203
Proc IEEE Int Symp Biomed Imaging. 2015 Apr;2015:140-143. doi: 10.1109/ISBI.2015.7163835.

Alzheimer's disease is the most common form of dementia. Diffusion imaging provides information on white matter integrity not available with standard MRI, revealing additional information on how Alzheimer's disease affects the brain. Here we implemented and tested a multi-atlas...

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Jin Y, Shi Y, Zhan L, et al. AUTOMATED MULTI-ATLAS LABELING OF THE FORNIX AND ITS INTEGRITY IN ALZHEIMER'S DISEASE. Proc IEEE Int Symp Biomed Imaging. 2015;2015:140-143doi: 10.1109/ISBI.2015.7163835.
Jin, Y., Shi, Y., Zhan, L., Thompson, P. M. (2015). AUTOMATED MULTI-ATLAS LABELING OF THE FORNIX AND ITS INTEGRITY IN ALZHEIMER'S DISEASE. Proceedings. IEEE International Symposium on Biomedical Imaging, 2015140-143. https://doi.org/10.1109/ISBI.2015.7163835
Jin, Yan, et al. "AUTOMATED MULTI-ATLAS LABELING OF THE FORNIX AND ITS INTEGRITY IN ALZHEIMER'S DISEASE." Proceedings. IEEE International Symposium on Biomedical Imaging vol. 2015 (2015): 140-143. doi: https://doi.org/10.1109/ISBI.2015.7163835
Jin Y, Shi Y, Zhan L, Thompson PM. AUTOMATED MULTI-ATLAS LABELING OF THE FORNIX AND ITS INTEGRITY IN ALZHEIMER'S DISEASE. Proc IEEE Int Symp Biomed Imaging. 2015 Apr;2015:140-143. doi: 10.1109/ISBI.2015.7163835. PMID: 26413203; PMCID: PMC4578317.
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Impact of family structure and common environment on heritability estimation for neuroimaging genetics studies using Sequential Oligogenic Linkage Analysis Routines.

Journal of medical imaging (Bellingham, Wash.)

Koran ME, Thornton-Wells TA, Jahanshad N, Glahn DC, Thompson PM, Blangero J, Nichols TE, Kochunov P, Landman BA.
PMID: 25558465
J Med Imaging (Bellingham). 2014 Jun 27;1(1):014005. doi: 10.1117/1.JMI.1.1.014005.

Imaging genetics is an emerging methodological field that combines genetic information with medical imaging-derived metrics to understand how genetic factors impact observable phenotypes. In order for a trait to be a reasonable phenotype in an imaging genetics study, it...

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Koran ME, Thornton-Wells TA, Jahanshad N, et al. Impact of family structure and common environment on heritability estimation for neuroimaging genetics studies using Sequential Oligogenic Linkage Analysis Routines. J Med Imaging (Bellingham). 2014;1(1):014005doi: 10.1117/1.JMI.1.1.014005.
Koran, M. E., Thornton-Wells, T. A., Jahanshad, N., Glahn, D. C., Thompson, P. M., Blangero, J., Nichols, T. E., Kochunov, P., & Landman, B. A. (2014). Impact of family structure and common environment on heritability estimation for neuroimaging genetics studies using Sequential Oligogenic Linkage Analysis Routines. Journal of medical imaging (Bellingham, Wash.), 1(1), 014005. https://doi.org/10.1117/1.JMI.1.1.014005
Koran, Mary Ellen, et al. "Impact of family structure and common environment on heritability estimation for neuroimaging genetics studies using Sequential Oligogenic Linkage Analysis Routines." Journal of medical imaging (Bellingham, Wash.) vol. 1,1 (2014): 014005. doi: https://doi.org/10.1117/1.JMI.1.1.014005
Koran ME, Thornton-Wells TA, Jahanshad N, Glahn DC, Thompson PM, Blangero J, Nichols TE, Kochunov P, Landman BA. Impact of family structure and common environment on heritability estimation for neuroimaging genetics studies using Sequential Oligogenic Linkage Analysis Routines. J Med Imaging (Bellingham). 2014 Jun 27;1(1):014005. doi: 10.1117/1.JMI.1.1.014005. PMID: 25558465; PMCID: PMC4281883.
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DISCOVERY OF GENES THAT AFFECT HUMAN BRAIN CONNECTIVITY: A GENOME-WIDE ANALYSIS OF THE CONNECTOME.

Proceedings. IEEE International Symposium on Biomedical Imaging

Jahanshad N, Hibar DP, Ryles A, Toga AW, McMahon KL, de Zubicaray GI, Hansell NK, Montgomery GW, Martin NG, Wright MJ, Thompson PM.
PMID: 22903411
Proc IEEE Int Symp Biomed Imaging. 2012;542-545. doi: 10.1109/ISBI.2012.6235605.

Human brain connectivity is disrupted in a wide range of disorders - from Alzheimer's disease to autism - but little is known about which specific genes affect it. Here we conducted a genome-wide association for connectivity matrices that capture...

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Jahanshad N, Hibar DP, Ryles A, et al. DISCOVERY OF GENES THAT AFFECT HUMAN BRAIN CONNECTIVITY: A GENOME-WIDE ANALYSIS OF THE CONNECTOME. Proc IEEE Int Symp Biomed Imaging. 2012;542-545doi: 10.1109/ISBI.2012.6235605.
Jahanshad, N., Hibar, D. P., Ryles, A., Toga, A. W., McMahon, K. L., de Zubicaray, G. I., Hansell, N. K., Montgomery, G. W., Martin, N. G., Wright, M. J., & Thompson, P. M. (2012). DISCOVERY OF GENES THAT AFFECT HUMAN BRAIN CONNECTIVITY: A GENOME-WIDE ANALYSIS OF THE CONNECTOME. Proceedings. IEEE International Symposium on Biomedical Imaging, 542-545. https://doi.org/10.1109/ISBI.2012.6235605
Jahanshad, Neda, et al. "DISCOVERY OF GENES THAT AFFECT HUMAN BRAIN CONNECTIVITY: A GENOME-WIDE ANALYSIS OF THE CONNECTOME." Proceedings. IEEE International Symposium on Biomedical Imaging vol. (2012): 542-545. doi: https://doi.org/10.1109/ISBI.2012.6235605
Jahanshad N, Hibar DP, Ryles A, Toga AW, McMahon KL, de Zubicaray GI, Hansell NK, Montgomery GW, Martin NG, Wright MJ, Thompson PM. DISCOVERY OF GENES THAT AFFECT HUMAN BRAIN CONNECTIVITY: A GENOME-WIDE ANALYSIS OF THE CONNECTOME. Proc IEEE Int Symp Biomed Imaging. 2012;542-545. doi: 10.1109/ISBI.2012.6235605. PMID: 22903411; PMCID: PMC3420975.
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SPECTRAL GRAPH THEORY AND GRAPH ENERGY METRICS SHOW EVIDENCE FOR THE ALZHEIMER'S DISEASE DISCONNECTION SYNDROME IN .

Proceedings. IEEE International Symposium on Biomedical Imaging

Daianu M, Mezher A, Jahanshad N, Hibar DP, Nir TM, Jack CR, Weiner MW, Bernstein MA, Thompson PM.
PMID: 26413205
Proc IEEE Int Symp Biomed Imaging. 2015 Apr;2015:458-461. doi: 10.1109/ISBI.2015.7163910.

Our understanding of network breakdown in Alzheimer's disease (AD) is likely to be enhanced through advanced mathematical descriptors. Here, we applied spectral graph theory to provide novel metrics of structural connectivity based on 3-Tesla diffusion weighted images in 42...

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Daianu M, Mezher A, Jahanshad N, et al. SPECTRAL GRAPH THEORY AND GRAPH ENERGY METRICS SHOW EVIDENCE FOR THE ALZHEIMER'S DISEASE DISCONNECTION SYNDROME IN . Proc IEEE Int Symp Biomed Imaging. 2015;2015:458-461doi: 10.1109/ISBI.2015.7163910.
Daianu, M., Mezher, A., Jahanshad, N., Hibar, D. P., Nir, T. M., Jack, C. R., Weiner, M. W., Bernstein, M. A., & Thompson, P. M. (2015). SPECTRAL GRAPH THEORY AND GRAPH ENERGY METRICS SHOW EVIDENCE FOR THE ALZHEIMER'S DISEASE DISCONNECTION SYNDROME IN . Proceedings. IEEE International Symposium on Biomedical Imaging, 2015458-461. https://doi.org/10.1109/ISBI.2015.7163910
Daianu, Madelaine, et al. "SPECTRAL GRAPH THEORY AND GRAPH ENERGY METRICS SHOW EVIDENCE FOR THE ALZHEIMER'S DISEASE DISCONNECTION SYNDROME IN ." Proceedings. IEEE International Symposium on Biomedical Imaging vol. 2015 (2015): 458-461. doi: https://doi.org/10.1109/ISBI.2015.7163910
Daianu M, Mezher A, Jahanshad N, Hibar DP, Nir TM, Jack CR, Weiner MW, Bernstein MA, Thompson PM. SPECTRAL GRAPH THEORY AND GRAPH ENERGY METRICS SHOW EVIDENCE FOR THE ALZHEIMER'S DISEASE DISCONNECTION SYNDROME IN . Proc IEEE Int Symp Biomed Imaging. 2015 Apr;2015:458-461. doi: 10.1109/ISBI.2015.7163910. PMID: 26413205; PMCID: PMC4578320.
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Detecting Genetic Risk Factors for Alzheimer's Disease in Whole Genome Sequence Data via Lasso Screening.

Proceedings. IEEE International Symposium on Biomedical Imaging

Yang T, Wang J, Sun Q, Hibar DP, Jahanshad N, Liu L, Wang Y, Zhan L, Thompson PM, Ye J.
PMID: 26413209
Proc IEEE Int Symp Biomed Imaging. 2015 Apr;2015:985-989. doi: 10.1109/ISBI.2015.7164036.

Genetic factors play a key role in Alzheimer's disease (AD). The Alzheimer's Disease Neuroimaging Initiative (ADNI) whole genome sequence (WGS) data offers new power to investigate mechanisms of AD by combining entire genome sequences with neuroimaging and clinical data....

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Yang T, Wang J, Sun Q, et al. Detecting Genetic Risk Factors for Alzheimer's Disease in Whole Genome Sequence Data via Lasso Screening. Proc IEEE Int Symp Biomed Imaging. 2015;2015:985-989doi: 10.1109/ISBI.2015.7164036.
Yang, T., Wang, J., Sun, Q., Hibar, D. P., Jahanshad, N., Liu, L., Wang, Y., Zhan, L., Thompson, P. M., & Ye, J. (2015). Detecting Genetic Risk Factors for Alzheimer's Disease in Whole Genome Sequence Data via Lasso Screening. Proceedings. IEEE International Symposium on Biomedical Imaging, 2015985-989. https://doi.org/10.1109/ISBI.2015.7164036
Yang, Tao, et al. "Detecting Genetic Risk Factors for Alzheimer's Disease in Whole Genome Sequence Data via Lasso Screening." Proceedings. IEEE International Symposium on Biomedical Imaging vol. 2015 (2015): 985-989. doi: https://doi.org/10.1109/ISBI.2015.7164036
Yang T, Wang J, Sun Q, Hibar DP, Jahanshad N, Liu L, Wang Y, Zhan L, Thompson PM, Ye J. Detecting Genetic Risk Factors for Alzheimer's Disease in Whole Genome Sequence Data via Lasso Screening. Proc IEEE Int Symp Biomed Imaging. 2015 Apr;2015:985-989. doi: 10.1109/ISBI.2015.7164036. PMID: 26413209; PMCID: PMC4578226.
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Medial Demons Registration Localizes The Degree of Genetic Influence Over Subcortical Shape Variability: An N= 1480 Meta-Analysis.

Proceedings. IEEE International Symposium on Biomedical Imaging

Gutman BA, Jahanshad N, Ching CR, Wang Y, Kochunov PV, Nichols TE, Thompson PM.
PMID: 26413211
Proc IEEE Int Symp Biomed Imaging. 2015 Apr;2015:1402-1406. doi: 10.1109/ISBI.2015.7164138.

We present a multi-cohort shape heritability study, extending the fast spherical demons registration to subcortical shapes via medial modeling. A multi-channel demons registration based on vector spherical harmonics is applied to medial and curvature features, while controlling for metric...

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Gutman BA, Jahanshad N, Ching CR, et al. Medial Demons Registration Localizes The Degree of Genetic Influence Over Subcortical Shape Variability: An N= 1480 Meta-Analysis. Proc IEEE Int Symp Biomed Imaging. 2015;2015:1402-1406doi: 10.1109/ISBI.2015.7164138.
Gutman, B. A., Jahanshad, N., Ching, C. R., Wang, Y., Kochunov, P. V., Nichols, T. E., & Thompson, P. M. (2015). Medial Demons Registration Localizes The Degree of Genetic Influence Over Subcortical Shape Variability: An N= 1480 Meta-Analysis. Proceedings. IEEE International Symposium on Biomedical Imaging, 20151402-1406. https://doi.org/10.1109/ISBI.2015.7164138
Gutman, Boris A, et al. "Medial Demons Registration Localizes The Degree of Genetic Influence Over Subcortical Shape Variability: An N= 1480 Meta-Analysis." Proceedings. IEEE International Symposium on Biomedical Imaging vol. 2015 (2015): 1402-1406. doi: https://doi.org/10.1109/ISBI.2015.7164138
Gutman BA, Jahanshad N, Ching CR, Wang Y, Kochunov PV, Nichols TE, Thompson PM. Medial Demons Registration Localizes The Degree of Genetic Influence Over Subcortical Shape Variability: An N= 1480 Meta-Analysis. Proc IEEE Int Symp Biomed Imaging. 2015 Apr;2015:1402-1406. doi: 10.1109/ISBI.2015.7164138. PMID: 26413211; PMCID: PMC4578221.
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Discovery and Replication of Gene Influences on Brain Structure Using LASSO Regression.

Frontiers in neuroscience

Kohannim O, Hibar DP, Stein JL, Jahanshad N, Hua X, Rajagopalan P, Toga AW, Jack CR, Weiner MW, de Zubicaray GI, McMahon KL, Hansell NK, Martin NG, Wright MJ, Thompson PM.
PMID: 22888310
Front Neurosci. 2012 Aug 06;6:115. doi: 10.3389/fnins.2012.00115. eCollection 2012.

We implemented least absolute shrinkage and selection operator (LASSO) regression to evaluate gene effects in genome-wide association studies (GWAS) of brain images, using an MRI-derived temporal lobe volume measure from 729 subjects scanned as part of the Alzheimer's Disease...

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Kohannim O, Hibar DP, Stein JL, et al. Discovery and Replication of Gene Influences on Brain Structure Using LASSO Regression. Front Neurosci. 2012;6:115doi: 10.3389/fnins.2012.00115.
Kohannim, O., Hibar, D. P., Stein, J. L., Jahanshad, N., Hua, X., Rajagopalan, P., Toga, A. W., Jack, C. R., Weiner, M. W., de Zubicaray, G. I., McMahon, K. L., Hansell, N. K., Martin, N. G., Wright, M. J., Thompson, P. M. (2012). Discovery and Replication of Gene Influences on Brain Structure Using LASSO Regression. Frontiers in neuroscience, 6115. https://doi.org/10.3389/fnins.2012.00115
Kohannim, Omid, et al. "Discovery and Replication of Gene Influences on Brain Structure Using LASSO Regression." Frontiers in neuroscience vol. 6 (2012): 115. doi: https://doi.org/10.3389/fnins.2012.00115
Kohannim O, Hibar DP, Stein JL, Jahanshad N, Hua X, Rajagopalan P, Toga AW, Jack CR, Weiner MW, de Zubicaray GI, McMahon KL, Hansell NK, Martin NG, Wright MJ, Thompson PM. Discovery and Replication of Gene Influences on Brain Structure Using LASSO Regression. Front Neurosci. 2012 Aug 06;6:115. doi: 10.3389/fnins.2012.00115. eCollection 2012. PMID: 22888310; PMCID: PMC3412288.
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TRACTOGRAPHY DENSITY AND NETWORK MEASURES IN ALZHEIMER'S DISEASE.

Proceedings. IEEE International Symposium on Biomedical Imaging

Prasad G, Nir TM, Toga AW, Thompson PM.
PMID: 25404994
Proc IEEE Int Symp Biomed Imaging. 2013 Apr;2013:692-695. doi: 10.1109/ISBI.2013.6556569.

Brain connectivity declines in Alzheimer's disease (AD), both functionally and structurally. Connectivity maps and networks derived from diffusion-based tractography offer new ways to track disease progression and to understand how AD affects the brain. Here we set out to...

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Prasad G, Nir TM, Toga AW, et al. TRACTOGRAPHY DENSITY AND NETWORK MEASURES IN ALZHEIMER'S DISEASE. Proc IEEE Int Symp Biomed Imaging. 2013;2013:692-695doi: 10.1109/ISBI.2013.6556569.
Prasad, G., Nir, T. M., Toga, A. W., & Thompson, P. M. (2013). TRACTOGRAPHY DENSITY AND NETWORK MEASURES IN ALZHEIMER'S DISEASE. Proceedings. IEEE International Symposium on Biomedical Imaging, 2013692-695. https://doi.org/10.1109/ISBI.2013.6556569
Prasad, Gautam, et al. "TRACTOGRAPHY DENSITY AND NETWORK MEASURES IN ALZHEIMER'S DISEASE." Proceedings. IEEE International Symposium on Biomedical Imaging vol. 2013 (2013): 692-695. doi: https://doi.org/10.1109/ISBI.2013.6556569
Prasad G, Nir TM, Toga AW, Thompson PM. TRACTOGRAPHY DENSITY AND NETWORK MEASURES IN ALZHEIMER'S DISEASE. Proc IEEE Int Symp Biomed Imaging. 2013 Apr;2013:692-695. doi: 10.1109/ISBI.2013.6556569. PMID: 25404994; PMCID: PMC4232938.
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PREDICTING TEMPORAL LOBE VOLUME ON MRI FROM GENOTYPES USING L(1)-L(2) REGULARIZED REGRESSION.

Proceedings. IEEE International Symposium on Biomedical Imaging

Kohannim O, Hibar DP, Jahanshad N, Stein JL, Hua X, Toga AW, Jack CR, Weiner MW, Thompson PM.
PMID: 22903144
Proc IEEE Int Symp Biomed Imaging. 2012;1160-1163. doi: 10.1109/ISBI.2012.6235766.

Penalized or sparse regression methods are gaining increasing attention in imaging genomics, as they can select optimal regressors from a large set of predictors whose individual effects are small or mostly zero. We applied a multivariate approach, based on...

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Kohannim O, Hibar DP, Jahanshad N, et al. PREDICTING TEMPORAL LOBE VOLUME ON MRI FROM GENOTYPES USING L(1)-L(2) REGULARIZED REGRESSION. Proc IEEE Int Symp Biomed Imaging. 2012;1160-1163doi: 10.1109/ISBI.2012.6235766.
Kohannim, O., Hibar, D. P., Jahanshad, N., Stein, J. L., Hua, X., Toga, A. W., Jack, C. R., Weiner, M. W., Thompson, P. M. (2012). PREDICTING TEMPORAL LOBE VOLUME ON MRI FROM GENOTYPES USING L(1)-L(2) REGULARIZED REGRESSION. Proceedings. IEEE International Symposium on Biomedical Imaging, 1160-1163. https://doi.org/10.1109/ISBI.2012.6235766
Kohannim, Omid, et al. "PREDICTING TEMPORAL LOBE VOLUME ON MRI FROM GENOTYPES USING L(1)-L(2) REGULARIZED REGRESSION." Proceedings. IEEE International Symposium on Biomedical Imaging vol. (2012): 1160-1163. doi: https://doi.org/10.1109/ISBI.2012.6235766
Kohannim O, Hibar DP, Jahanshad N, Stein JL, Hua X, Toga AW, Jack CR, Weiner MW, Thompson PM. PREDICTING TEMPORAL LOBE VOLUME ON MRI FROM GENOTYPES USING L(1)-L(2) REGULARIZED REGRESSION. Proc IEEE Int Symp Biomed Imaging. 2012;1160-1163. doi: 10.1109/ISBI.2012.6235766. PMID: 22903144; PMCID: PMC3420969.
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Rich club network analysis shows distinct patterns of disruption in frontotemporal dementia and Alzheimer's disease.

Mathematics and visualization

Daianu M, Jahanshad N, Villalon-Reina JE, Mendez MF, Bartzokis G, Jimenez EE, Joshi A, Barsuglia J, Thompson PM.
PMID: 26161050
Math Vis. 2014;2014:13-22. doi: 10.1007/978-3-319-11182-7_2.

Diffusion imaging and brain connectivity analyses can reveal the underlying organizational patterns of the human brain, described as complex networks of densely interlinked regions. Here, we analyzed 1.5-Tesla whole-brain diffusion-weighted images from 64 participants - 15 patients with behavioral...

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Daianu M, Jahanshad N, Villalon-Reina JE, et al. Rich club network analysis shows distinct patterns of disruption in frontotemporal dementia and Alzheimer's disease. Math Vis. 2014;2014:13-22doi: 10.1007/978-3-319-11182-7_2.
Daianu, M., Jahanshad, N., Villalon-Reina, J. E., Mendez, M. F., Bartzokis, G., Jimenez, E. E., Joshi, A., Barsuglia, J., & Thompson, P. M. (2014). Rich club network analysis shows distinct patterns of disruption in frontotemporal dementia and Alzheimer's disease. Mathematics and visualization, 201413-22. https://doi.org/10.1007/978-3-319-11182-7_2
Daianu, Madelaine, et al. "Rich club network analysis shows distinct patterns of disruption in frontotemporal dementia and Alzheimer's disease." Mathematics and visualization vol. 2014 (2014): 13-22. doi: https://doi.org/10.1007/978-3-319-11182-7_2
Daianu M, Jahanshad N, Villalon-Reina JE, Mendez MF, Bartzokis G, Jimenez EE, Joshi A, Barsuglia J, Thompson PM. Rich club network analysis shows distinct patterns of disruption in frontotemporal dementia and Alzheimer's disease. Math Vis. 2014;2014:13-22. doi: 10.1007/978-3-319-11182-7_2. PMID: 26161050; PMCID: PMC4492471.
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