Modular Brain Networks

The Elements of Statistical Learning

Hastie, T., Tibshirani, R., & Friedman, J. (2009) · Springer Series in Statistics · doi:10.1007/978-0-387-84858-7 · Cited by 25,970

Fast unfolding of communities in large networks

Blondel, V. D., Guillaume, J.-L., Lambiotte, R., & Lefebvre, E. (2008) · Journal of Statistical Mechanics: Theory and Experiment · doi:10.1088/1742-5468/2008/10/p10008 · Cited by 21,424

Community structure in social and biological networks

Girvan, M., & Newman, M. E. J. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.122653799 · Cited by 15,502

Finding and evaluating community structure in networks

Newman, M. E. J., & Girvan, M. (2004) · Physical Review E · doi:10.1103/physreve.69.026113 · Cited by 13,931

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

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

Community detection in graphs

Fortunato, S. (2010) · Physics Reports · doi:10.1016/j.physrep.2009.11.002 · Cited by 11,293

The organization of the human cerebral cortex estimated by intrinsic functional connectivity

Thomas Yeo, B. T., Krienen, F. M., Sepulcre, J., Sabuncu, M. R., Lashkari, D., Hollinshead, M., Roffman, J. L., Smoller, J. W., Zöllei, L., Polimeni, J. R., et al. (2011) · Journal of Neurophysiology · doi:10.1152/jn.00338.2011 · Cited by 9,182

Distributed hierarchical processing in the primate cerebral cortex

Felleman, D. J., & Van Essen, D. C. (1991) · Cerebral Cortex · doi:10.1093/cercor/1.1.1 · Cited by 7,783

The Modularity of Mind

Fodor, J. A. (1983) · doi:10.7551/mitpress/4737.001.0001 · Cited by 7,734

Body Weight Control Is a Key Element of Motor Control for Toddlers’ Walking

Kerkman, J. N., Zandvoort, C. S., Daffertshofer, A., & Dominici, N. (2022) · Frontiers in Network Physiology · doi:10.3389/fnetp.2022.844607 · Cited by 22

Parameter estimation for connectome generative models: Accuracy, reliability, and a fast parameter fitting method

Liu, Y., Seguin, C., Sina Mansour, L., Oldham, S., Betzel, R. F., Biase, M. A. D., & Zalesky, A. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.119962 · Cited by 20

Transcriptomic and Macroscopic Architectures of Multimodal Covariance Network Reveal Molecular–Structural–Functional Co-alterations

Jiang, L., Peng, Y., He, R., Yang, Q., Yi, C., Li, Y., Zhu, B., Si, Y., Zhang, T., Biswal, B. B., et al. (2023) · Research · doi:10.34133/research.0171 · Cited by 22

Multiscale effects of excitatory-inhibitory homeostasis in lesioned cortical networks: A computational study

dos Santos, F. P., Vohryzek, J., & Verschure, P. F. M. J. (2023) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1011279 · Cited by 23

The brain as a “hyper-network”: the key role of neural networks as main producers of the integrated brain actions especially via the “broadcasted” neuroconnectomics

Agnati, L. F., Marcoli, M., Maura, G., Woods, A. S., & Guidolin, D. (2018) · Journal of Neural Transmission · doi:10.1007/s00702-018-1855-7 · Cited by 22

The dynamics of human cognition: Increasing global integration coupled with decreasing segregation found using iEEG

Cruzat, J., Deco, G., Campo, A. T., Príncipe, A., Costa, A., Kringelbach, M. L., & Rocamora, R. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.01.064 · Cited by 21

Functional networks underlying item and source memory: shared and distinct network components and age-related differences

Monge, Z. A., Stanley, M. L., Geib, B. R., Davis, S. W., & Cabeza, R. E. L. (2018) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2018.05.016 · Cited by 21

Uncovering differential identifiability in network properties of human brain functional connectomes

Rajapandian, M., Amico, E., Abbas, K., Ventresca, M., & Goñi, J. (2020) · Network Neuroscience · doi:10.1162/netn_a_00140 · Cited by 21

Spontaneous Functional Recovery after Focal Damage in Neuronal Cultures

Teller, S., Estévez-Priego, E., Granell, C., Tornero, D., Andilla, J., Olarte, O. E., Loza‐Álvarez, P., Arenas, À., & Soriano, J. (2019) · eNeuro · doi:10.1523/eneuro.0254-19.2019 · Cited by 22

Ambivert degree identifies crucial brain functional hubs and improves detection of Alzheimer’s Disease and Autism Spectrum Disorder

Gupta, S., Rajapakse, J. C., & Welsch, R. E. (2020) · NeuroImage Clinical · doi:10.1016/j.nicl.2020.102186 · Cited by 21

Inner Hemispheric and Interhemispheric Connectivity Balance in the Human Brain

Krupnik, R., Yovel, Y., & Assaf, Y. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.1074-21.2021 · Cited by 24

The Emergence of Canalization and Evolvability in an Open-Ended, Interactive Evolutionary System

Huizinga, J., Stanley, K. O., & Clune, J. (2018) · Artificial Life · doi:10.1162/artl_a_00263 · Cited by 22

Metabolic Brain Network Analysis of FDG-PET in Alzheimer’s Disease Using Kernel-Based Persistent Features

Kuang, L., Zhao, D., Xing, J., Chen, Z., Xiong, F., & Han, X. (2019) · Molecules · doi:10.3390/molecules24122301 · Cited by 21

Decreased modular segregation of the frontal–parietal network in major depressive disorder

Lan, Z., Zhang, W., Wang, D., Tan, Z., Wang, Y., Pan, C., Xiao, Y., Kuai, C., & Xue, S. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.929812 · Cited by 21

Measures of resting-state brain network segregation and integration vary in relation to data quantity: implications for within and between subject comparisons of functional brain network organization

Han, L., Chan, M. Y., Agres, P. F., Winter-Nelson, E., Zhang, Z., & Wig, G. S. (2024) · Cerebral Cortex · doi:10.1093/cercor/bhad506 · Cited by 21

Graphlet characteristics in directed networks

Trpevski, I., Dimitrova, T., Boshkovski, T., Stikov, N., & Kocarev, L. (2016) · Scientific Reports · doi:10.1038/srep37057 · Cited by 21

Reconfiguration of hub-level community structure in depressions: A follow-up study via diffusion tensor imaging

Qin, J., Liu, H., Wei, M., Zhao, K., Chen, J., Zhu, J., Shen, X., Yan, R., Yao, Z., & Lü, Q. (2016) · Journal of Affective Disorders · doi:10.1016/j.jad.2016.09.048 · Cited by 21

Temporal Stable Community in Time-Varying Networks

Wang, W., & Li, X. (2019) · IEEE Transactions on Network Science and Engineering · doi:10.1109/tnse.2019.2936865 · Cited by 21

Quantifying the Variability in Resting-State Networks

Oliver, I., Hlinka, J., Kopál, J., & Davidsen, J. (2019) · Entropy · doi:10.3390/e21090882 · Cited by 21

The Prospective Sense of Agency is Rooted in Local and Global Properties of Intrinsic Functional Brain Networks

Plinio, S. D., Perrucci, M. G., & Ebisch, S. J. H. (2020) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01590 · Cited by 20

Obtaining leaner deep neural networks for decoding brain functional connectome in a single shot

Gupta, S., Chan, Y. H., Rajapakse, J. C., & Initiative, T. A. D. N. (2020) · Neurocomputing · doi:10.1016/j.neucom.2020.04.152 · Cited by 21

Bridging Brain and Cognition: A Multilayer Network Analysis of Brain Structural Covariance and General Intelligence in a Developmental Sample of Struggling Learners

Simpson-Kent, I. L., Fried, E. I., Akarca, D., Mareva, S., Bullmore, E. T., the CALM Team, & Kievit, R. (2021) · Journal of Intelligence · doi:10.3390/jintelligence9020032 · Cited by 26

Connectional axis of individual functional variability: Patterns, structural correlates, and relevance for development and cognition

Yang, H., Wu, G., Li, Y., Xu, X., Cong, J., Xu, H., Ma, Y., Yang, L., Chen, R., Pines, A. R., et al. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2420228122 · Cited by 22

The impact of long-term abacus training on modular properties of functional brain network

Xie, Y., Weng, J., Wang, C., Xu, T., Peng, X., & Chen, F. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.08.057 · Cited by 20

Neural network correlates of high‐altitude adaptive genetic variants in Tibetans: A pilot, exploratory study

Guo, Z., Fan, C., Li, T., Gesang, L., Yin, W., Wang, N., Weng, X., Gong, Q., Zhang, J., & Wang, J. (2020) · Human Brain Mapping · doi:10.1002/hbm.24954 · Cited by 21

A Pilot Adaptive Neurofeedback Investigation of the Neural Mechanisms of Implicit Emotion Regulation Among Women With PTSD

Weaver, S. S., Birn, R. M., & Cisler, J. M. (2020) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2020.00040 · Cited by 22

Network Neuroscience and the Adapted Mind: Rethinking the Role of Network Theories in Evolutionary Psychology

Elimari, N., & Lafargue, G. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.545632 · Cited by 21

Increased dynamic flexibility in the medial temporal lobe network following an exercise intervention mediates generalization of prior learning

Sinha, N., Berg, C. N., Yassa, M. A., & Gluck, M. A. (2020) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2020.107340 · Cited by 21

Cortical autonomic network connectivity predicts symptoms in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS)

Zinn, M. A., & Jason, L. A. (2021) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2021.10.004 · Cited by 21

Modelling brain dynamics by Boolean networks

Bertacchini, F., Scuro, C., Pantano, P., & Bilotta, E. (2022) · Scientific Reports · doi:10.1038/s41598-022-20979-x · Cited by 20

Learning long-term motor timing/patterns on an orthogonal basis in random neural networks

Kawai, Y., Park, J., Tsuda, I., & Asada, M. (2023) · Neural Networks · doi:10.1016/j.neunet.2023.04.006 · Cited by 20

Sex differences in neural networks recruited by frontloaded binge alcohol drinking

Ardinger, C. E., Chen, Y., Kimbrough, A., Grahame, N. J., & Lapish, C. C. (2024) · Addiction Biology · doi:10.1111/adb.13434 · Cited by 20

Does Aligning Phenotypic and Genotypic Modularity Improve the Evolution of Neural Networks?

Huizinga, J., Mouret, J.-B., & Clune, J. (2016) · Genetic and Evolutionary Computation Conference (GECCO) · doi:10.1145/2908812.2908836 · Cited by 19

The impacts of pesticide and nicotine exposures on functional brain networks in Latino immigrant workers

Bahrami, M., Laurienti, P. J., Quandt, S. A., Talton, J. W., Pope, C., Summers, P., Burdette, J. H., Chen, H., Liu, J., Howard, T. D., et al. (2017) · NeuroToxicology · doi:10.1016/j.neuro.2017.06.001 · Cited by 20

Harnessing networks and machine learning in neuropsychiatric care

Cornblath, E. J., Lydon‐Staley, D. M., & Bassett, D. S. (2019) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2018.12.010 · Cited by 23

Multiscale Community Detection in Functional Brain Networks Constructed Using Dynamic Time Warping

Jin, D., Li, R., & Xu, J. (2019) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2019.2948055 · Cited by 19

Abnormal Dynamic Community Structure of Patients with Attention-Deficit/Hyperactivity Disorder in the Resting State

Ding, C., Xiang, J., Cui, X., Wang, X., Li, D., Chen, C., & Wang, B. (2020) · Journal of Attention Disorders · doi:10.1177/1087054720959712 · Cited by 19

Critical Avalanches in Excitation-Inhibition Balanced Networks Reconcile Response Reliability with Sensitivity for Optimal Neural Representation

Yang, Z., Liang, J., & Zhou, C. (2025) · Physical Review Letters · doi:10.1103/physrevlett.134.028401 · Cited by 19

Functional Brain Connectivity Analysis in Intellectual Developmental Disorder During Music Perception

Sareen, E., Singh, L., Gupta, A., Verma, R., Achary, G. K., & Varkey, B. (2020) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2020.3024937 · Cited by 19

A morphospace of functional configuration to assess configural breadth based on brain functional networks

Duong-Tran, D. A., Abbas, K., Amico, E., Corominas‐Murtra, B., Džemidžić, M., Kareken, D. A., Ventresca, M., & Goñi, J. (2021) · Network Neuroscience · doi:10.1162/netn_a_00193 · Cited by 20

Linked Social–Communication Dimensions and Connectivity in Functional Brain Networks in Autism Spectrum Disorder

Xiao, J., Chen, H., Shan, X., He, C., Li, Y., Guo, X., Chen, H., Liao, W., Uddin, L. Q., & Duan, X. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab057 · Cited by 19

Benchmarking functional connectivity by the structure and geometry of the human brain

Liu, Z.-Q., Betzel, R. F., & Mišić, B. (2022) · Network Neuroscience · doi:10.1162/netn_a_00236 · Cited by 20

Multidimensional Assessment of Electroencephalography in the Neuromodulation of Disorders of Consciousness

Zhang, C., Han, S., Li, Z., Wang, X., Lv, C., Zou, X., Zhu, F., Zhang, K., Lu, S., Bie, L., et al. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.903703 · Cited by 19

A spatio-temporal decomposition framework for dynamic functional connectivity in the human brain

Xiao, J., Uddin, L. Q., Meng, Y., Li, L., Gao, L., Shan, X., Huang, X., Liao, W., Chen, H., & Duan, X. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119618 · Cited by 19

Edge-centric functional network analyses reveal disrupted network configuration in autism spectrum disorder

Yang, B., Wang, M., Zhou, W., Wang, X., Chen, S., Yuan, L., & Dong, G. (2023) · Journal of Affective Disorders · doi:10.1016/j.jad.2023.05.025 · Cited by 19

Brain network topology predicts participant adherence to mental training programs

Saghayi, M., Greenberg, J., O’Grady, C., Varno, F., Hashmi, M. A., Bracken, B. K., Matwin, S., Lazar, S. W., & Hashmi, J. A. (2020) · Network Neuroscience · doi:10.1162/netn_a_00136 · Cited by 21

Event‐related network changes unfold the dynamics of cortical integration during face processing

Maffei, A., & Sessa, P. (2021) · Psychophysiology · doi:10.1111/psyp.13786 · Cited by 19

Distance-based functional criticality in the human brain: intelligence and emotional intelligence

Jiang, L., Qiao, K., & Li, C. (2021) · BMC Bioinformatics · doi:10.1186/s12859-021-03973-4 · Cited by 22

Testing the structure of human cognitive ability using evidence obtained from the impact of brain lesions over abilities

Protzko, J., & Colom, R. (2021) · Intelligence · doi:10.1016/j.intell.2021.101581 · Cited by 18

Automated Classification of Mild Cognitive Impairment by Machine Learning With Hippocampus-Related White Matter Network

Yu, Z., Si, X., Chao, Y., Chen, Y., Lin, C., Li, S., Zhang, X., Sun, Y., Ming, D., & Li, Q. (2022) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2022.866230 · Cited by 18

Community modularity structure promotes the evolution of phase clusters and chimeralike states

Yu, D., Li, X., Wang, X., Huang, W., Hu, X., & Jia, Y. (2025) · Physical review. E · doi:10.1103/physreve.111.034311 · Cited by 18

Intrinsic overlapping modular organization of human brain functional networks revealed by a multiobjective evolutionary algorithm

Lin, Y., Ma, J., Gu, Y., Shen, Y., Li, L. M. W., & Dai, Z. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.07.019 · Cited by 18

Altered Functional and Structural Connectomes in Female High School Soccer Athletes After a Season of Head Impact Exposure and the Effect of a Novel Collar

Dudley, J. A., Yuan, W., Diekfuss, J. A., Foss, K. D. B., DiCesare, C. A., Altaye, M., Logan, K., Leach, J. L., & Myer, G. D. (2020) · Brain Connectivity · doi:10.1089/brain.2019.0729 · Cited by 18

Iterative consensus spectral clustering improves detection of subject and group level brain functional modules

Gupta, S., & Rajapakse, J. C. (2020) · Scientific Reports · doi:10.1038/s41598-020-63552-0 · Cited by 18

Dynamic Reconfiguration, Fragmentation, and Integration of Whole-Brain Modular Structure across Depths of Unconsciousness

Standage, D., Areshenkoff, C. N., Nashed, J. Y., Hutchison, R. M., Hutchison, M., Heinke, D. G., Menon, R. S., Everling, S., & Gallivan, J. P. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa085 · Cited by 17

Efficient search for informational cores in complex systems: Application to brain networks

Kitazono, J., Kanai, R., & Oizumi, M. (2020) · Neural Networks · doi:10.1016/j.neunet.2020.08.020 · Cited by 17

The Hidden Brain: Uncovering Previously Overlooked Brain Regions by Employing Novel Preclinical Unbiased Network Approaches

Simpson, S., Chen, Y., Wellmeyer, E., Smith, L. C., Montes, B. A., George, O., & Kimbrough, A. (2021) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2021.595507 · Cited by 16

Modular and state-relevant functional network connectivity in high-frequency eyes open vs eyes closed resting fMRI data

DeRamus, T. P., Faghiri, A., Iraji, A., Agcaoglu, O., Vergara, V. M., Fu, Z., Silva, R. F., Gazula, H., Stephen, J. M., Wilson, T. W., et al. (2021) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2021.109202 · Cited by 18

Whole-Brain Resting-State Functional Connectivity Patterns Associated With Pediatric Anxiety and Involuntary Attention Capture

Perino, M. T., Myers, M. J., Wheelock, M. D., Yu, Q., Harper, J., Manhart, M., Gordon, E. M., Eggebrecht, A. T., Pine, D. S., Barch, D. M., et al. (2021) · Biological Psychiatry Global Open Science · doi:10.1016/j.bpsgos.2021.05.007 · Cited by 19

Left temporal pole contributes to creative thinking via an individual semantic network

Yan, T., Zhuang, K., He, L., Liu, C., Zeng, R., & Qiu, J. (2021) · Psychophysiology · doi:10.1111/psyp.13841 · Cited by 17

The integrated understanding of structural and functional connectomes in depression: A multimodal meta-analysis of graph metrics

Xu, S., Deng, W.-F., Qu, Y., Lai, W., Huang, T.-Y., Rong, H., & Xie, X. (2021) · Journal of Affective Disorders · doi:10.1016/j.jad.2021.08.120 · Cited by 17

Modular structure in C. elegans neural network and its response to external localized stimuli

Moreira, C. A., & de Aguiar, M. A. M. (2019) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2019.122051 · Cited by 18

The biological role of local and global fMRI BOLD signal variability in human brain organizationPreprint

Baracchini, G., Zhou, Y., Castanheira, J. D. S., Hansen, J. Y., Rieck, J. R., Turner, G. R., Grady, C. L., Mišić, B., Nomi, J. S., Uddin, L. Q., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.10.22.563476 · Cited by 18

Structural diverseness of neurons between brain areas and between cases

Mizutani, R., Saiga, R., Yamamoto, Y., Uesugi, M., Takeuchi, A., Uesugi, K., Terada, Y., Suzuki, Y., Andrade, V. D., Carlo, F. D., et al. (2021) · Translational Psychiatry · doi:10.1038/s41398-020-01173-x · Cited by 17

Changes in Brain Functional and Effective Connectivity After Treatment for Breast Cancer and Implications for Intervention Targets

Phillips, N. S., Rao, V., Kmetz, L., Vela, R. D., Medick, S., Krull, K. R., & Kesler, S. R. (2021) · Brain Connectivity · doi:10.1089/brain.2021.0049 · Cited by 21

Dynamic large-scale connectivity of intrinsic cortical oscillations supports adaptive listening in challenging conditions

Alavash, M., Tune, S., & Obleser, J. (2021) · PLoS Biology · doi:10.1371/journal.pbio.3001410 · Cited by 18

Flexible and Modular Brain Network Dynamics Characterize Flow Experiences During Media Use: A Functional Magnetic Resonance Imaging Study

Huskey, R., Keene, J. R., Wilcox, S., Gong, X., Adams, R., & Najera, C. J. (2021) · Journal of Communication · doi:10.1093/joc/jqab044 · Cited by 17

Network controllability mediates the relationship between rigid structure and flexible dynamics

Gu, S., Fotiadis, P., Parkes, L., Xia, C. H., Gur, R. C., Gur, R. E., Roalf, D. R., Satterthwaite, T. D., & Bassett, D. S. (2021) · Network Neuroscience · doi:10.1162/netn_a_00225 · Cited by 17

Local neurodynamics as a signature of cortical areas: new insights from sleep

Armonaité, K., Nobili, L., Paulon, L., Balsi, M., Conti, L., & Tecchio, F. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhac274 · Cited by 18

Classification of multiple sclerosis clinical profiles using machine learning and grey matter connectome

Barile, B., Ashtari, P., Stamile, C., Marzullo, A., Maes, F., Durand‐Dubief, F., Huffel, S. V., & Sappey‐Marinier, D. (2022) · Frontiers in Robotics and AI · doi:10.3389/frobt.2022.926255 · Cited by 18

Characterizing functional modules in the human thalamus: coactivation-based parcellation and systems-level functional decoding

Boeken, O. J., Cieslik, E. C., Langner, R., & Markett, S. A. (2022) · Brain Structure and Function · doi:10.1007/s00429-022-02603-w · Cited by 18

Functional connectome fingerprinting across the lifespan

St‐Onge, F., Javanray, M., Binette, A. P., Strikwerda‐Brown, C., Remz, J., Spreng, R. N., Shafiei, G., Mišić, B., Vachon‐Presseau, É., & Villeneuve, S. (2023) · Network Neuroscience · doi:10.1162/netn_a_00320 · Cited by 17

Network Modularity as a Foundation for Neural Reuse

Stanley, M. L., Gessell, B. S., & Brigard, F. D. (2018) · Philosophy of Science · doi:10.1086/701037 · Cited by 16

Intrinsic gray-matter connectivity of the brain in major depressive disorder

Zhang, H., Qiu, M., Ding, L., Mellor, D. J., Li, G., Shen, T., & Peng, D. (2019) · Journal of Affective Disorders · doi:10.1016/j.jad.2019.01.048 · Cited by 19

Parkinson’s Disease Affects Functional Connectivity within the Olfactory-Trigeminal Network

Tremblay, C., Iravani, B., Aubry-Lafontaine, É., Steffener, J., Fischmeister, F. P. S., Lundström, J. N., & Frasnelli, J. (2020) · Journal of Parkinson s Disease · doi:10.3233/jpd-202062 · Cited by 17

Functional sensitivity and mutational robustness of proteins

Tang, Q.-Y., Hatakeyama, T. S., & Kaneko, K. (2020) · Physical Review Research · doi:10.1103/physrevresearch.2.033452 · Cited by 16

Three-dimensionality shapes the dynamics of cortical interconnected to hippocampal networks

Brofiga, M., Pisano, M., Tedesco, M., Raiteri, R., & Massobrio, P. (2020) · Journal of Neural Engineering · doi:10.1088/1741-2552/abc023 · Cited by 17

Age-Associated Differences of Modules and Hubs in Brain Functional Networks

Zhang, Y., Wang, Y., Chen, N., Guo, M., Wang, X., Chen, G., Li, Y., Yang, L., Li, S., Yao, Z., et al. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2020.607445 · Cited by 17

Disentangling age‐ and disease‐related alterations in schizophrenia brain network using structural equation modeling: A graph theoretical study based on minimum spanning tree

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 19

PAGANI Toolkit: Parallel graph‐theoretical analysis package for brain network big data

Du, H., Xia, M., Zhao, K., Liao, X., Yang, H., Wang, Y., & Yong He, A. (2018) · Human Brain Mapping · doi:10.1002/hbm.23996 · Cited by 17

Contributions of electrophysiology for identifying cortical language systems in patients with epilepsy

Trébuchon, A., Liégeois‐Chauvel, C., Gonzalez-Martinez, J. A., & Alario, F. ‐. (2020) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2020.107407 · Cited by 18

Detecting network anomalies using Forman–Ricci curvature and a case study for human brain networks

Chatterjee, T., Albert, R., Thapliyal, S., Azarhooshang, N., & DasGupta, B. (2021) · Scientific Reports · doi:10.1038/s41598-021-87587-z · Cited by 23

Persistence of information flow: A multiscale characterization of human brain

Benigni, B., Ghavasieh, A., Corso, A., d’Andrea, V., & Domenico, M. D. (2021) · Network Neuroscience · doi:10.1162/netn_a_00203 · Cited by 16

Abnormal Brain Topological Structure of Mild Depression During Visual Search Processing Based on EEG Signals

Sun, S., Liu, L., Shao, X., Yan, C., Li, X., & Hu, B. (2022) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2022.3181690 · Cited by 16

Biotypes of major depressive disorder identified by a multiview clustering framework

Chen, X., Dai, Z., & Lin, Y. (2023) · Journal of Affective Disorders · doi:10.1016/j.jad.2023.02.118 · Cited by 15

Self‐Folding Graphene‐Based Interface for Brain‐Like Modular 3D Tissue

Sakai, K., Teshima, T., Goto, T., Nakashima, H., & Yamaguchi, M. (2023) · Advanced Functional Materials · doi:10.1002/adfm.202301836 · Cited by 19

A Gaussian Process Model of Human Electrocorticographic Data

Owen, L. L. W., Muntianu, T. A., Heusser, A. C., Daly, P. M., Scangos, K. W., & Manning, J. R. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa115 · Cited by 16

Path-dependent connectivity, not modularity, consistently predicts controllability of structural brain networks

Patankar, S. P., Kim, J. Z., Pasqualetti, F., & Bassett, D. S. (2020) · Network Neuroscience · doi:10.1162/netn_a_00157 · Cited by 16

Network neuroscience and the connectomics revolution

Betzel, R. F. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-821861-7.00002-6 · Cited by 18

Characterizing the theory of mind network in schizophrenia reveals a sparser network structure

Bitsch, F., Berger, P., Nagels, A., Falkenberg, I., & Straube, B. (2020) · Schizophrenia Research · doi:10.1016/j.schres.2020.11.026 · Cited by 17

Dynamic functional connectivity in modular organization of the hippocampal network marks memory phenotypes in temporal lobe epilepsy

Li, H., Ding, F., Chen, C., Huang, P., Xu, J., Chen, Z., Wang, S., & Zhang, M. (2021) · Human Brain Mapping · doi:10.1002/hbm.25763 · Cited by 16

Altered global modular organization of intrinsic functional connectivity in autism arises from atypical node‐level processing

Sigar, P., Uddin, L. Q., & Roy, D. (2022) · Autism Research · doi:10.1002/aur.2840 · Cited by 17

Bayesian modeling of dependence in brain connectivity data

Chen, S., Xing, Y., Kang, J., Kochunov, P., & Hong, L. E. (2018) · Biostatistics · doi:10.1093/biostatistics/kxy046 · Cited by 16

Metabolic and amyloid PET network reorganization in Alzheimer’s disease: differential patterns and partial volume effects

Initiative, A. D. N., González‐Escamilla, G., Miederer, I., Grothe, M. J., Schreckenberger, M., Muthuraman, M., & Groppa, S. (2020) · Brain Imaging and Behavior · doi:10.1007/s11682-019-00247-9 · Cited by 16

Analysis of population functional connectivity data via multilayer network embeddings

Wilson, J. D., Baybay, M., Sankar, R., Stillman, P. E., & Popa, A. M. (2020) · Network Science · doi:10.1017/nws.2020.39 · Cited by 18

Age-associated reorganization of metabolic brain connectivity in Chinese children

Huang, Q., Zhang, J., Zhang, T., Wang, H., & Yan, J. (2019) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-019-04508-z · Cited by 14

Characterizing multiscale modular structures in medication‐free obsessive–compulsive disorder patients with no comorbidity

Li, X., Li, H., Jiang, X., Li, J., Cao, L., Liu, J., Xing, H., Huang, X., & Gong, Q. (2022) · Human Brain Mapping · doi:10.1002/hbm.25794 · Cited by 14

Human motor sequence learning drives transient changes in network topology and hippocampal connectivity early during memory consolidation

Deleglise, Á., Donnelly-Kehoe, P. A., Yeffal, A., Jacobacci, F., Jovicich, J., Amaro, E., Armony, J. L., Doyon, J., & Della‐Maggiore, V. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhac489 · Cited by 16

Adolescent neurodevelopment and psychopathology: The interplay between adversity exposure and genetic risk for accelerated brain ageing

Petrican, R., & Fornito, A. (2023) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2023.101229 · Cited by 16

Dynamic Community Detection for Brain Functional Networks During Music Listening With Block Component Analysis

Zhu, Y., Liu, J., & Cong, F. (2023) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2023.3277509 · Cited by 15

Graph theory methods: applications in brain networks

Sporns, O. (2018) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2018.20.2/osporns · Cited by 671

The modular organization of human anatomical brain networks: Accounting for the cost of wiring

Betzel, R. F., Medaglia, J. D., Papadopoulos, L., Baum, G. L., Gur, R. C., Gur, R. E., Roalf, D. R., Satterthwaite, T. D., & Bassett, D. S. (2017) · Network Neuroscience · doi:10.1162/netn_a_00002 · Cited by 148

The structural and functional multilayer modular organization of the human brain

Puxeddu, M. G. (2020) · IRIS Research product catalog (Sapienza University of Rome)

The modular structure of brain functional connectivity networks: a graph theoretical approach

Nicolini, C. (2017)

Detecting brain network communities: Considering the role of information flow and its different temporal scales

Sanchez-Rodriguez, L. M., Iturria‐Medina, Y., Mouchès, P., & Sotero, R. C. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117431 · Cited by 25