Brain Connectivity Toolbox

The Brain Connectivity Toolbox (brain-connectivity-toolbox.net) is a MATLAB toolbox for complex-network (graph) analysis of structural and functional brain-connectivity data sets. Several people have contributed to the toolbox and users are welcome to contribute new functions with due acknowledgement.

Keywords for this software

Anything in here will be replaced on browsers that support the canvas element

References in zbMATH (referenced in 70 articles )

Showing results 1 to 20 of 70.
Sorted by year (citations)

1 2 3 4 next

  1. Cheng, Hong; Cai, David; Zhou, Douglas: The extended Granger causality analysis for Hodgkin-Huxley neuronal models (2020)
  2. Chen, Shuo; Bowman, F. DuBois; Xing, Yishi: Detecting and testing altered brain connectivity networks with k-partite network topology (2020)
  3. Chen, Ximing; Ogura, Masaki; Preciado, Victor M.: Bounds on the spectral radius of digraphs from subgraph counts (2020)
  4. Demšar, Jure; Forsyth, Rob: Synaptic scaling improves the stability of neural mass models capable of simulating brain plasticity (2020)
  5. Ghaderi, Amir Hossein; Baltaretu, Bianca R.; Andevari, Masood Nemati; Bharmauria, Vishal; Balci, Fuat: Synchrony and complexity in state-related EEG networks: an application of spectral graph theory (2020)
  6. Li, Yuzhe; Shi, Dawei; Chen, Tongwen: Secure analysis of dynamic networks under pinning attacks against synchronization (2020)
  7. Lovato, Ilenia; Pini, Alessia; Stamm, Aymeric; Vantini, Simone: Model-free two-sample test for network-valued data (2020)
  8. Paul, Subhadeep; Chen, Yuguo: A random effects stochastic block model for joint community detection in multiple networks with applications to neuroimaging (2020)
  9. Xu, Min; Jog, Varun; Loh, Po-Ling: Optimal rates for community estimation in the weighted stochastic block model (2020)
  10. Aliverti, Emanuele; Durante, Daniele: Spatial modeling of brain connectivity data via latent distance models with nodes clustering (2019)
  11. Bianchi, Daniele; Billio, Monica; Casarin, Roberto; Guidolin, Massimo: Modeling systemic risk with Markov switching graphical SUR models (2019)
  12. Das, Anup; Sexton, Daniel; Lainscsek, Claudia; Cash, Sydney S.; Sejnowski, Terrence J.: Characterizing brain connectivity from human electrocorticography recordings with unobserved inputs during epileptic seizures (2019)
  13. Duan, Zhen; Zou, Haodong; Min, Xing; Zhao, Shu; Chen, Jie; Zhang, Yanping: An adaptive granulation algorithm for community detection based on improved label propagation (2019)
  14. Kong, Wanzeng; Jiang, Bei; Fan, Qiaonan; Zhu, Li; Wei, Xuehui: Personal identification based on brain networks of EEG signals (2019)
  15. Nunes, Ronaldo V.; Reyes, Marcelo B.; de Camargo, Raphael Y.: Evaluation of connectivity estimates using spiking neuronal network models (2019)
  16. Wang, Daohua; Xue, Yumei; Zhang, Qian; Niu, Min: Scale-free and small-world properties of a special hierarchical network (2019)
  17. Chowdhury, Samir; Mémoli, Facundo: A functorial Dowker theorem and persistent homology of asymmetric networks (2018)
  18. Durante, Daniele; Dunson, David B.: Bayesian inference and testing of group differences in brain networks (2018)
  19. Lea Waller; Anastasia Brovkin; Lena Dorfschmidt; Danilo Bzdok; Henrik Walter; Johann Daniel Kruschwitz: GraphVar 2.0: A user-friendly toolbox for machine learning on functional connectivity measures (2018) arXiv
  20. Le, Can M.; Levin, Keith; Levina, Elizaveta: Estimating a network from multiple noisy realizations (2018)

1 2 3 4 next