Brain connectivity and information-flow breakdown revealed by a minimum spanning tree-based analysis of MRI data in behavioral variant frontotemporal dementia
Open accessAbstract
Brain functional disruption and cognitive shortfalls as consequences of neurodegeneration are among the most investigated aspects in current clinical research. Traditionally, specific anatomical and behavioral traits have been associated with neurodegeneration, thus directly translatable in clinical terms. However, these qualitative traits, do not account for the extensive information flow breakdown within the functional brain network that deeply affect cognitive skills. Behavioural variant Frontotemporal Dementia (bvFTD) is a neurodegenerative disorder characterized by behavioral and executive functions disturbances. Deviations from the physiological cognitive functioning can be accurately inferred and modeled from functional connectivity alterations. Although the need for unbiased metrics is still an open issue in imaging studies, the graph-theory approach applied to neuroimaging techniques is becoming popular in the study of brain dysfunction. In this work, we assessed the global connectivity and topological alterations among brain regions in bvFTD patients using a minimum spanning tree (MST) based analysis of resting state functional MRI (rs-fMRI) data. Whilst several graph theoretical methods require arbitrary criteria (including the choice of network construction thresholds and weight normalization methods), MST is an unambiguous modeling solution, ensuring accuracy, robustness, and reproducibility. MST networks of 116 regions of interest (ROIs) were built on wavelet correlation matrices, extracted from 41 bvFTD patients and 39 healthy controls (HC). We observed a global fragmentation of the functional network backbone with severe disruption of information-flow highways. Frontotemporal areas were less compact, more isolated, and concentrated in less integrated structures, respect to healthy subjects. Our results reflected such complex breakdown of the frontal and temporal areas at both intra-regional and long-range connections. Our findings highlighted that MST, in conjunction with rs-fMRI data, was an effective method for quantifying and detecting functional brain network impairments, leading to characteristic bvFTD cognitive, social, and executive functions disorders.
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
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
These findings may reflect compensatory mechanisms as a result of disconnection of critical brain regions specific to each pathology.
“These findings may reflect compensatory mechanisms as a result of the disconnection of critical brain regions specific to each pathology (Jalilianhasanpour et al., 2019; Saba et al., 2019).”
From Multiclass characterization of frontotemporal dementia variants via multimodal brain network computational inference (2023) · cites this paper as Saba et al., 2019
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
WGCNA: an R package for weighted correlation network analysis
Langfelder, P., & Horvath, S. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-559 · Cited by 27,252 · see citing works
Statistical mechanics of complex networks
Albert, R., & Barabási, A.-L. (2002) · Reviews of Modern Physics · doi:10.1103/revmodphys.74.47 · Cited by 20,471 · see citing works
Tzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N., Mazoyer, B., & Joliot, M. (2002) · NeuroImage · doi:10.1006/nimg.2001.0978 · Cited by 16,319 · see citing works
Complex brain networks: graph theoretical analysis of structural and functional systems
Bullmore, E., & Sporns, O. (2009) · Nature Reviews Neuroscience · doi:10.1038/nrn2575 · Cited by 11,820 · see citing works
Complex network measures of brain connectivity: Uses and interpretations
Rubinov, M., & Sporns, O. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.10.003 · Cited by 11,522 · see citing works
Jenkinson, M., Beckmann, C. F., Behrens, T. E. J., Woolrich, M. W., & Smith, S. M. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.09.015 · Cited by 11,314 · see citing works
The igraph software package for complex network research
Csárdi, G., & Nepusz, T. (2006) · Medical Entomology and Zoology · Cited by 10,078 · see citing works
Brain magnetic resonance imaging with contrast dependent on blood oxygenation.
Ogawa, S., Lee, T. M., Kay, A. R., & Tank, D. W. (1990) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.87.24.9868 · Cited by 6,483 · see citing works
A General Framework for Weighted Gene Co-Expression Network Analysis
Zhang, B., & Horvath, S. (2005) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1128 · Cited by 5,684 · see citing works
Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia
Rascovsky, K., Hodges, J. R., Knopman, D., Mendez, M. F., Kramer, J. H., Neuhaus, J., van Swieten, J. C., Seelaar, H., Dopper, E. G. P., Onyike, C. U., et al. (2011) · Brain · doi:10.1093/brain/awr179 · Cited by 5,221 · see citing works
Classification of primary progressive aphasia and its variants
Gorno-Tempini, M. L., Hillis, A. E., Weintraub, S., Kertesz, A., Mendez, M., Cappa, S. F., Ogar, J. M., Rohrer, J. D., Black, S., Boeve, B. F., et al. (2011) · Neurology · doi:10.1212/wnl.0b013e31821103e6 · Cited by 5,141 · see citing works
Hierarchical Organization of Modularity in Metabolic Networks
Ravasz, E., Somera, A. L., Mongru, D. A., Oltvai, Z. N., & Barabási, A.-L. (2002) · Science · doi:10.1126/science.1073374 · Cited by 4,224 · see citing works
The brain's default mode network
Raichle, M. E. (2015) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-071013-014030 · Cited by 3,904 · see citing works
The economy of brain network organization
Bullmore, E., & Sporns, O. (2012) · Nature Reviews Neuroscience · doi:10.1038/nrn3214 · Cited by 3,284 · see citing works
Newman, M. (2002) · Physical review. E, Statistical, nonlinear, and soft matter physics · doi:10.1103/physreve.67.026126 · Cited by 3,130 · see citing works
Appelhof, B., Bakker, C., den IJssel, J. C. L. V. D., Zwijsen, S. A., Smalbrugge, M., Verhey, F. R. J., de Vugt, M. E., Zuidema, S. U., & Koopmans, R. T. C. M. (2017) · Dementia and Geriatric Cognitive Disorders · doi:10.1159/000477087 · Cited by 2,773 · see citing works
Probabilistic Independent Component Analysis for Functional Magnetic Resonance Imaging
Beckmann, C. F., & Smith, S. M. (2004) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2003.822821 · Cited by 2,707 · see citing works
Achard, S., Salvador, R., Whitcher, B., Suckling, J., & Bullmore, E. (2006) · The Journal of Neuroscience · doi:10.1523/jneurosci.3874-05.2006 · Cited by 2,393 · see citing works
Neurodegenerative Diseases Target Large-Scale Human Brain Networks
Seeley, W. W., Crawford, R. K., Zhou, J., Miller, B. L., & Greicius, M. D. (2009) · Neuron · doi:10.1016/j.neuron.2009.03.024 · Cited by 2,350 · see citing works
Qualitative Assessment of Verbal Fluency Performance in Frontotemporal Dementia
van den Berg, E., Jiskoot, L. C., Grosveld, M. J. H., Swieten, J. C. V., & Papma, J. M. (2017) · Dementia and Geriatric Cognitive Disorders · doi:10.1159/000477538 · Cited by 2,061 · see citing works
Extended Bayesian information criteria for model selection with large model spaces
Chen, J., & Chen, Z. (2008) · Biometrika · doi:10.1093/biomet/asn034 · Cited by 1,993 · see citing works
Functional Connectivity and Brain Networks in Schizophrenia
Lynall, M.-E., Bassett, D. S., Kerwin, R., McKenna, P. J., Kitzbichler, M. G., Müller, U., & Bullmore, E. T. (2010) · Journal of Neuroscience · doi:10.1523/jneurosci.0333-10.2010 · Cited by 1,348 · see citing works
Griffanti, L., Salimi‐Khorshidi, G., Beckmann, C. F., Auerbach, E. J., Douaud, G., Sexton, C. E., Zsoldos, E., Ebmeier, K. P., Filippini, N., Mackay, C. E., et al. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.03.034 · Cited by 1,234 · see citing works
Comparing Brain Networks of Different Size and Connectivity Density Using Graph Theory
van Wijk, B. C. M., Stam, C. J., & Daffertshofer, A. (2010) · PLoS ONE · doi:10.1371/journal.pone.0013701 · Cited by 1,161 · see citing works
Zhou, J., Greicius, M. D., Gennatas, E. D., Growdon, M. E., Jang, J. Y., Rabinovici, G. D., Kramer, J. H., Weiner, M., Miller, B. L., & Seeley, W. W. (2010) · Brain · doi:10.1093/brain/awq075 · Cited by 1,016 · see citing works
Rohrer, J. D., Nicholas, J. M., Cash, D. M., van Swieten, J., Dopper, E., Jiskoot, L., van Minkelen, R., Rombouts, S. A., Cardoso, M. J., Clegg, S., et al. (2015) · The Lancet Neurology · doi:10.1016/s1474-4422(14)70324-2 · Cited by 538 · see citing works
Self-citationThe Ubiquity of Small-World Networks
Telesford, Q. K., Joyce, K. E., Hayasaka, S., Burdette, J. H., & Laurienti, P. J. (2011) · Brain Connectivity · doi:10.1089/brain.2011.0038 · Cited by 517 · see citing works
Frontal Paralimbic Network Atrophy in Very Mild Behavioral Variant Frontotemporal Dementia
Seeley, W. W., Crawford, R., Rascovsky, K., Kramer, J. H., Weiner, M., Miller, B. L., & Gorno-Tempini, M. L. (2008) · Archives of Neurology · doi:10.1001/archneurol.2007.38 · Cited by 506 · see citing works
On the use of correlation as a measure of network connectivity
Zalesky, A., Fornito, A., & Bullmore, E. T. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.02.001 · Cited by 430 · see citing works
Fortney, J. P. (2020) · Chapman & Hall/CRC eBooks · doi:10.1201/9781003091479-1 · Cited by 429 · see citing works
Independent component analysis of functional MRI: what is signal and what is noise?
McKeown, M. J., Hansen, L. K., & Sejnowsk, T. J. (2003) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2003.09.012 · Cited by 414 · see citing works
de Haan, W., Pijnenburg, Y. A. L., STRIJERS, R. L. M., van der Made, Y., van der Flier, W. M., Scheltens, P., & Stam, C. J. (2009) · BMC Neuroscience · doi:10.1186/1471-2202-10-101 · Cited by 404 · see citing works
Rashid, B., Damaraju, E., Pearlson, G. D., & Calhoun, V. D. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00897 · Cited by 399 · see citing works
The trees and the forest: Characterization of complex brain networks with minimum spanning trees
Stam, C. J., Tewarie, P. K. B., van Dellen, E., van Straaten, E. C. W., Hillebrand, A., & Mieghem, P. V. (2014) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2014.04.001 · Cited by 348 · see citing works
The minimum spanning tree: An unbiased method for brain network analysis
Tewarie, P. K. B., van Dellen, E., Hillebrand, A., & Stam, C. J. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.10.015 · Cited by 346 · see citing works
Wavelets and functional magnetic resonance imaging of the human brain
Bullmore, E. T., Fadili, J. M., Maxim, V., Sendur, L., Whitcher, B. J., John Suckling, A., Brammer, M. J., & Breakspear, M. J. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.012 · Cited by 257 · see citing works
Hohenfeld, C., Werner, C. J., & Reetz, K. (2018) · NeuroImage: Clinical · doi:10.1016/j.nicl.2018.03.013 · Cited by 232 · see citing works
Specificity and robustness of long-distance connections in weighted, interareal connectomes
Betzel, R. F., & Bassett, D. S. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1720186115 · Cited by 214 · see citing works
Guo, C. C., Tan, R. H., Hodges, J. R., Hu, X., Sami, S. A. K., & Hornberger, M. (2016) · Brain · doi:10.1093/brain/aww003 · Cited by 206 · see citing works
Abnormal network connectivity in frontotemporal dementia: Evidence for prefrontal isolation
Farb, N. A. S., Grady, C. L., Strother, S. C., Tang‐Wai, D. F., Masellis, M., Black, S. E., Freedman, M., Pollock, B. G., Campbell, K. L., Hasher, L., et al. (2012) · Cortex · doi:10.1016/j.cortex.2012.09.008 · Cited by 191 · see citing works
Brain network connectivity assessed using graph theory in frontotemporal dementia
Agosta, F., Sala, S., Valsasina, P., Meani, A., Canu, E., Magnani, G., Cappa, S. F., Scola, E., Quatto, P., Horsfield, M. A., et al. (2013) · Neurology · doi:10.1212/wnl.0b013e31829a33f8 · Cited by 168 · see citing works
Transport in Weighted Networks: Partition into Superhighways and Roads
Wu, Z., Braunstein, L. A., Havlin, S., & Stanley, E. (2006) · Physical Review Letters · doi:10.1103/physrevlett.96.148702 · Cited by 161 · see citing works
Altered network connectivity in frontotemporal dementia with C9orf72 hexanucleotide repeat expansion
Lee, S. E., Khazenzon, A. M., Trujillo, A. J., Guo, C. C., Yokoyama, J. S., Sha, S. J., Takada, L. T., Karydas, A. M., Block, N., Coppola, G., et al. (2014) · Brain · doi:10.1093/brain/awu248 · Cited by 158 · see citing works
Drakesmith, M., Caeyenberghs, K., Dutt, A., Lewis, G., David, A. S., & Jones, D. K. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.05.011 · Cited by 157 · see citing works
Yu, M., Gouw, A. A., Hillebrand, A., Tijms, B. M., Stam, C. J., van Straaten, E. C. W., & Pijnenburg, Y. A. L. (2016) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2016.03.018 · Cited by 154 · see citing works
Frontotemporal lobar degeneration: Pathogenesis, pathology and pathways to phenotype
Mann, D. M. A., & Snowden, J. S. (2017) · Brain Pathology · doi:10.1111/bpa.12486 · Cited by 153 · see citing works
Altered functional connectivity in asymptomatic MAPT subjects
Whitwell, J. L., Josephs, K. A., Avula, R. T. V., Tosakulwong, N., Weigand, S. D., Senjem, M. L., Vemuri, P., Jones, D. T., Gunter, J. L., Baker, M., et al. (2011) · Neurology · doi:10.1212/wnl.0b013e31822c61f2 · Cited by 142 · see citing works
Tewarie, P. K. B., Hillebrand, A., Schoonheim, M. M., van Dijk, B. W., Geurts, J. J. G., Barkhof, F., Polman, C. H., & Stam, C. J. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.10.022 · Cited by 133 · see citing works
van Dellen, E., Douw, L., Hillebrand, A., Hamer, P. C. D. W., Baayen, J. C., Heimans, J. J., Reijneveld, J. C., & Stam, C. J. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.10.010 · Cited by 124 · see citing works
Choosing Wavelet Methods, Filters, and Lengths for Functional Brain Network Construction
Zhang, Z., Telesford, Q. K., Giusti, C., Lim, K. O., & Bassett, D. S. (2016) · PLoS ONE · doi:10.1371/journal.pone.0157243 · Cited by 120 · see citing works
Brain network connectivity differs in early-onset neurodegenerative dementia
Filippi, M., Basaia, S., Canu, E., Imperiale, F., Meani, A., Caso, F., Magnani, G., Falautano, M., Comı, G., Falini, A., et al. (2017) · Neurology · doi:10.1212/wnl.0000000000004577 · Cited by 120 · see citing works
Mears, D. J., & Pollard, H. B. (2016) · Journal of Neuroscience Research · doi:10.1002/jnr.23705 · Cited by 118 · see citing works
Granulin mutation drives brain damage and reorganization from preclinical to symptomatic FTLD
Borroni, B., Alberici, A., Cercignani, M., Premi, E., Serra, L., Cerini, C., Cosseddu, M., Pettenati, C., Turla, M., Archetti, S., et al. (2011) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2011.10.031 · Cited by 113 · see citing works
Self-citationA Topological Criterion for Filtering Information in Complex Brain Networks
Fallani, F. D. V., Latora, V., & Chávez, M. (2017) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005305 · Cited by 113 · see citing works
Functional connectivity and network analysis during hypoactive delirium and recovery from anesthesia
Numan, T., Slooter, A. J. C., van der Kooi, A. W., Hoekman, A. M. L., Suyker, W. J. L., Stam, C. J., & van Dellen, E. (2017) · Clinical Neurophysiology · doi:10.1016/j.clinph.2017.02.022 · Cited by 111 · see citing works
Selecting high-dimensional mixed graphical models using minimal AIC or BIC forests
Edwards, D., de Abreu, G. C. G., & Labouriau, R. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-18 · Cited by 96 · see citing works
Advances in neuroimaging in frontotemporal dementia
Gordón, E., Rohrer, J. D., & Fox, N. C. (2016) · Journal of Neurochemistry · doi:10.1111/jnc.13656 · Cited by 92 · see citing works
Meditation is associated with increased brain network integration
van Lutterveld, R., van Dellen, E., Pal, P., Yang, H., Stam, C. J., & Brewer, J. A. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.06.071 · Cited by 88 · see citing works
Threshold selection in gene co-expression networks using spectral graph theory techniques
Perkins, A., & Langston, M. A. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-s11-s4 · Cited by 87 · see citing works
Detecting network modules in fMRI time series: A weighted network analysis approach
Mumford, J. A., Horvath, S., Oldham, M. C., Langfelder, P., Geschwind, D. H., & Poldrack, R. A. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.05.047 · Cited by 81 · see citing works
OPTIMAL PATH AND MINIMAL SPANNING TREES IN RANDOM WEIGHTED NETWORKS
Braunstein, L. A., Wu, Z., Chen, Y., Buldyrev, S. V., Tomer Kalisky, C., Sreenivasan, S., Reuven Cohen, C., López, E., Havlin, S., & Stanley, E. (2007) · International Journal of Bifurcation and Chaos · doi:10.1142/s0218127407018361 · Cited by 76 · see citing works
Brain Network Organization and Social Executive Performance in Frontotemporal Dementia
Sedeño, L., Couto, B., Cordero, I. R. G., Melloni, M., Báez, S., Sepúlveda, J. P. M., Fraiman, D., Huepe, D., Hurtado, E., Matallana, D., et al. (2016) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617715000703 · Cited by 73 · see citing works
Cerebellum in Alzheimer’s disease and frontotemporal dementia: not a silent bystander
Schmahmann, J. D. (2016) · Brain · doi:10.1093/brain/aww064 · Cited by 72 · see citing works
Functional overlap and divergence between ALS and bvFTD
Trojsi, F., Esposito, F., Stefano, M. D., Buonanno, D., Conforti, F. L., Corbo, D., Piccirillo, G., Cirillo, M., Monsurrò, M. R., Montella, P., et al. (2014) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2014.06.025 · Cited by 70 · see citing works
Neuronal and behavioral effects of multi-day brain stimulation and memory training
Antonenko, D., Külzow, N., Sousa, A., Prehn, K., Grittner, U., & Flöel, A. (2018) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2017.09.017 · Cited by 70 · see citing works
(2002) · NeuroImage · doi:10.1016/s1053-8119(02)90013-3 · Cited by 63 · see citing works
Griffanti, L., Dipasquale, O., Laganà, M. M., Nemni, R., Clerici, M., Smith, S. M., Baselli, G., & Baglio, F. (2015) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2015.00449 · Cited by 60 · see citing works
Otte, W. M., Diessen, E. G. A. L. V., Paul, S., Ramaswamy, R., Rallabandi, V. P. S., Stam, C. J., & Roy, P. K. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.01.011 · Cited by 55 · see citing works
Hierarchical clustering in minimum spanning trees
Yu, M., Hillebrand, A., Tewarie, P. K. B., Meier, J. M., van Dijk, B. W., Mieghem, P. V., & Stam, C. J. (2015) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/1.4908014 · Cited by 55 · see citing works
Time-dependence of graph theory metrics in functional connectivity analysis
Chiang, S., Cassese, A., Guindani, M., Vannucci, M., Yeh, H. J., Haneef, Z., & Stern, J. M. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.10.070 · Cited by 54 · see citing works
Electroencephalography based functional networks in newly diagnosed childhood epilepsies
Diessen, E. G. A. L. V., Otte, W. M., Stam, C. J., Braun, K. P. J., & Jansen, F. E. (2016) · Clinical Neurophysiology · doi:10.1016/j.clinph.2016.03.015 · Cited by 47 · see citing works
Phase transition in the link weight structure of networks
Mieghem, P. V., & Magdalena, S. M. (2005) · Physical Review E · doi:10.1103/physreve.72.056138 · Cited by 46 · see citing works
Guo, H., Liu, L., Chen, J., Xu, Y. J., & Xiang, J. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00639 · Cited by 44 · see citing works
Cui, X., Xiang, J., Guo, H., Yin, G., Zhang, H., Lan, F., & Chen, J. (2018) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2018.00031 · Cited by 43 · see citing works
Park, B., Moon, T., & Park, H. (2017) · Behavioural Brain Research · doi:10.1016/j.bbr.2017.10.001 · Cited by 38 · see citing works
Influence of the link weight structure on the shortest path
Mieghem, P. V., & van Langen, S. (2005) · Physical Review E · doi:10.1103/physreve.71.056113 · Cited by 37 · see citing works
The Union of Shortest Path Trees of Functional Brain Networks
Meier, J. M., Tewarie, P. K. B., & Mieghem, P. V. (2015) · Brain Connectivity · doi:10.1089/brain.2014.0330 · Cited by 24 · see citing works
Iron in Frontotemporal Lobar Degeneration: A New Subcortical Pathological Pathway?
Gazzina, S., Premi, E., Zanella, I., Biasiotto, G., Archetti, S., Cosseddu, M., Scarpini, E. A., Galimberti, D., Serpente, M., Gasparotti, R., et al. (2015) · Neurodegenerative Diseases · doi:10.1159/000440843 · Cited by 18 · see citing works
Self-citationMendelian forms of disease and age at onset affect survival in frontotemporal dementia
Cosseddu, M., Benussi, A., Gazzina, S., Turrone, R., Archetti, S., Bonomi, E., Biasiotto, G., Zanella, I., Ferrari, R., Cotelli, M. S., et al. (2017) · Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration · doi:10.1080/21678421.2017.1384020 · Cited by 17 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Non-invasive mapping of epileptogenic networks predicts surgical outcome
Corona, L., Tamilia, E., Perry, M. S., Madsen, J. R., Bolton, J. B., Stone, S. S. D., Stufflebeam, S. M., Pearl, P. L., & Papadelis, C. L. (2022) · Brain · doi:10.1093/brain/awac477 · Cited by 69 · see citing works
Jalilianhasanpour, R., Beheshtian, E., Sherbaf, G., Sahraian, S., & Sair, H. I. (2019) · Topics in Magnetic Resonance Imaging · doi:10.1097/rmr.0000000000000223 · Cited by 57 · see citing works
Hyperconnectivity in Dementia Is Early and Focal and Wanes with Progression
Bonanni, L., Moretti, D. V., Benussi, A., Ferri, L., Russo, M., Carrarini, C., Barbone, F., Arnaldi, D., Falasca, N. W., Koch, G., et al. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa209 · Cited by 47 · see citing works
Self-citationBlomsma, N., de Rooy, B., Gerritse, F. L., van der Spek, R., Tewarie, P. K. B., Hillebrand, A., Otte, W. M., Stam, C. J., & van Dellen, E. (2022) · Network Neuroscience · doi:10.1162/netn_a_00245 · Cited by 43 · see citing works
Simos, N. J., Dimitriadis, S. I., Kavroulakis, E., Manikis, G. C., Bertsias, G. K., Simos, P. G., Maris, T. G., & Papadaki, E. Z. (2020) · Brain Sciences · doi:10.3390/brainsci10110777 · Cited by 32 · see citing works
Chakladar, D. D., Roy, P. P., & Iwamura, M. (2021) · IEEE Transactions on Cognitive and Developmental Systems · doi:10.1109/tcds.2021.3116079 · Cited by 32 · see citing works
Shahdadian, S., Wang, X., Wanniarachchi, H. I., Chaudhari, A., Truong, N. C. D., & Liu, H. (2022) · Journal of Neural Engineering · doi:10.1088/1741-2552/ac9ede · Cited by 28 · see citing works
The Role of Graph Theory in Evaluating Brain Network Alterations in Frontotemporal Dementia
Nigro, S. L., Filardi, M., Tafuri, B., Blasi, R. D., Cedola, A., Gigli, G., & Logroscino, G. (2022) · Frontiers in Neurology · doi:10.3389/fneur.2022.910054 · Cited by 24 · see citing works
Functional connectivity in behavioral variant frontotemporal dementia
Ferreira, L. K., Lindberg, O. E., Santillo, A. F., & Wahlund, L. (2022) · Brain and Behavior · doi:10.1002/brb3.2790 · Cited by 25 · see citing works
Neuroimaging in Frontotemporal Lobar Degeneration: Research and Clinical Utility
Dev, S. I., Dickerson, B. C., & Touroutoglou, A. (2021) · Advances in experimental medicine and biology · doi:10.1007/978-3-030-51140-1_7 · Cited by 16 · see citing works
Liu, X., Yang, H., Becker, B., Huang, X., Luo, C., Meng, C., & Biswal, B. B. (2021) · Human Brain Mapping · doi:10.1002/hbm.25403 · Cited by 17 · see citing works
Brain Structural Covariance Networks in Behavioral Variant of Frontotemporal Dementia
Nigro, S. L., Tafuri, B., Urso, D., Blasi, R. D., Frisullo, M. E., Barulli, M. R., Capozzo, R., Cedola, A., Gigli, G., & Logroscino, G. (2021) · Brain Sciences · doi:10.3390/brainsci11020192 · Cited by 16 · see citing works
Franciotti, R., Moretti, D. V., Benussi, A., Ferri, L., Russo, M., Carrarini, C., Barbone, F., Arnaldi, D., Falasca, N. W., Koch, G., et al. (2021) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2021.10.016 · Cited by 13 · see citing works
Self-citationA data-driven brain network modeling for epileptogenic spread analysis
Liu, X., Yu, Y., Han, F., Zhou, J., Liu, Z., Luan, G., & Wang, Q. (2025) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2025.107645 · Cited by 11 · see citing works
Gonzalez-Gomez, R., Ibañez, A., & Moguilner, S. (2023) · Network Neuroscience · doi:10.1162/netn_a_00285 · Cited by 10 · see citing works
Changes in local brain function in mild cognitive impairment due to semantic dementia
Cui, L., Chen, K., Huang, L., Sun, J., Lv, Y., Jia, X., & Guo, Q. (2021) · CNS Neuroscience & Therapeutics · doi:10.1111/cns.13621 · Cited by 10 · see citing works
Ryu, H. M., Habeck, C. G., Stern, Y., & Lee, S. (2023) · Human Brain Mapping · doi:10.1002/hbm.26304 · Cited by 10 · see citing works
Ramírez-Carrillo, E., González‐Santoyo, I., López-Corona, O., Rojas-Ramos, O. A., Falcón, L. I., Gaona, O., Rodríguez, R. M. D. L. F., Hernández-Castillo, A., Cerqueda‐García, D., Sánchez-Quinto, A., et al. (2023) · PLoS ONE · doi:10.1371/journal.pone.0281385 · Cited by 10 · see citing works
Chu, M. K., Jiang, D., Liu, L., Nie, B., Rosa‐Neto, P., Chen, K., & Wu, L. (2023) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2023.01.004 · Cited by 9 · see citing works
González‐Santoyo, I., Ramírez-Carrillo, E., Sanchez, J. D., & López-Corona, O. (2023) · Journal of Developmental Origins of Health and Disease · doi:10.1017/s2040174423000144 · Cited by 6 · see citing works
Leng, M., Sun, Y., Chang, H., & Wang, Z. (2022) · Journal of Alzheimer s Disease · doi:10.3233/jad-215682 · Cited by 4 · see citing works
Belowska-Bień, K., Bień, B., & Software, W. S. (2021) · Aktualności Neurologiczne · doi:10.15557/an.2021.0021 · Cited by 4 · see citing works
Persistent Homology-based Functional Connectivity Explains Cognitive Ability: Life-span StudyPreprint
Ryu, H. M., Habeck, C. G., Stern, Y., & Lee, S. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.10.17.512619 · Cited by 3 · see citing works
Nawani, H., Sunil, S., Jaganathan, R., & Baths, V. (2025) · Brain and Behavior · doi:10.1002/brb3.70903 · Cited by 2 · see citing works
Yin, Z., Wang, Y., Dong, M., Ren, S., Hu, H., Yin, K., & Liang, J. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.652920 · Cited by 2 · see citing works
Spontaneous Feedforward Connectivity in Electrically Stimulated Retinal Degeneration Mice
Agadagba, S. K., & Chan, L. L.-H. (2020) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc44109.2020.9175231 · Cited by 2 · see citing works
Agadagba, S. K., & Chan, L. L. H. (2021) · HKIE Transactions · doi:10.33430/thie-2020-0006 · Cited by 2 · see citing works
Dinámica Cerebral de Varones con Estrés tras una Intervención en Línea de Atención Plena Compasiva
Martínez-Pelayo, M., Carrillo, E. R., González‐Santoyo, I., & Moreno-Coutiño, A. B. (2024) · PSICUMEX · doi:10.36793/psicumex.v14i1.654 · Cited by 1 · see citing works
Cotelli, M., Pagnoni, I., Gobbi, E., Campana, E., Bellini, S., Longobardi, A., Saraceno, C., Geviti, A., Cantoni, V., Alberici, A., et al. (2025) · Brain Communications · doi:10.1093/braincomms/fcaf295 · Cited by 1 · see citing works
Self-citationRamírez-Carrillo, E., Isaac, G.-S., Oliver, L.-C., Rojas-Ramos, O. A., Falcón, L. I., Gaona, O., Cerqueda‐García, D., Sánchez-Quinto, A., Rodríguez, R. M. D. L. F., Hernández-Castillo, A., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.07.25.221408 · Cited by 1 · see citing works
Leng, M., Sun, Y., Chang, H., & Wang, Z. (2021) · doi:10.2196/preprints.35011
Axenie, C., Bauer, R., López-Corona, O., & West, J. (2025) · SpringerBriefs in computer science · doi:10.1007/978-3-031-90391-5_3
Increased pre-alpha functional connectivity in dementia with Lewy bodies
D’Anselmo, A., Prete, G., Crosta, A. D., Bristot, L., Carrarini, C., Jaramillo-Jiménez, A., Palumbo, R., Varanese, S., Pilotto, A., Pardini, M., et al. (2025) · Journal of Alzheimer s Disease · doi:10.1177/13872877251385424
Self-citation
- Authors
- Saba, V., Premi, E., Cristillo, V., Gazzina, S., Palluzzi, F., Zanetti, O., Gasparotti, R., Padovani, A., Borroni, B., & Grassi, M.
- Affiliations
- University of Pavia (IT)
- University of Brescia (IT)
- Centro San Giovanni di Dio Fatebenefratelli (IT)
- Corresponding author
- Saba, Valentina
- ORCID
- Venue
- Frontiers in Neuroscience
- Publisher
- Frontiers Media SA
- Published
- 2019-03-14
- Volume
- 13
- Pages
- 211-211
- ISSN
- 1662-453X (ISSN-L)
- PMC
- PMC6427927
- OpenAlex
- W2921655079
- Cited by
- 33
- References
- 79
- Citations by year
- 2025: 5 · 2024: 1 · 2023: 4 · 2022: 8 · 2021: 10 · 2020: 4 · 2019: 1
- FWCI
- 3.34
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Neuroscience (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Institutional Research Information System (Università degli Studi di Brescia) (submittedVersion)
- Funders
- University College London
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- behavioral variant frontotemporal dementia, minimum spanning tree, resting-state functional connectivity, graph theory, wavelet correlation, frontotemporal region, executive dysfunction, neurodegeneration
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
