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

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References in zbMATH (referenced in 90 articles )

Showing results 1 to 20 of 90.
Sorted by year (citations)

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  1. Chen, Yaqing; Müller, Hans-Georg: Uniform convergence of local Fréchet regression with applications to locating extrema and time warping for metric space valued trajectories (2022)
  2. Saha, Papri; Sarkar, Debasish: Allometric scaling of von Neumann entropy in animal connectomes and its evolutionary aspect (2022)
  3. Zhang, Yuan; Xia, Dong: Edgeworth expansions for network moments (2022)
  4. Al Mugahwi, Mohammed; De La Cruz Cabrera, Omar; Fenu, Caterina; Reichel, Lothar; Rodriguez, Giuseppe: Block matrix models for dynamic networks (2021)
  5. Bayrak, Şeyma; Hövel, Philipp; Vuksanović, Vesna: Modeling functional connectivity on empirical and randomized structural brain networks (2021)
  6. Calimeri, Francesco; Cauteruccio, Francesco; Cinelli, Luca; Marzullo, Aldo; Stamile, Claudio; Terracina, Giorgio; Durand-Dubief, Françoise; Sappey-Marinier, Dominique: A logic-based framework leveraging neural networks for studying the evolution of neurological disorders (2021)
  7. Gopalakrishnan Meena, Muralikrishnan; Taira, Kunihiko: Identifying vortical network connectors for turbulent flow modification (2021)
  8. Govc, Dejan; Levi, Ran; Smith, Jason P.: Complexes of tournaments, directionality filtrations and persistent homology (2021)
  9. Gutiérrez, Caracé; Gancio, Juan; Cabeza, Cecilia; Rubido, Nicolás: Finding the resistance distance and eigenvector centrality from the network’s eigenvalues (2021)
  10. Lima, Verusca S.; Madeiro, Francisco; Lima, Juliano B.: Three-dimensional steerable discrete cosine transform with application to 3D image compression (2021)
  11. Lukemire, Joshua; Kundu, Suprateek; Pagnoni, Giuseppe; Guo, Ying: Bayesian joint modeling of multiple brain functional networks (2021)
  12. Ofori-Boateng, Dorcas; Gel, Yulia R.; Cribben, Ivor: Nonparametric anomaly detection on time series of graphs (2021)
  13. Torres, Leo; Blevins, Ann S.; Bassett, Danielle; Eliassi-Rad, Tina: The why, how, and when of representations for complex systems (2021)
  14. Cheng, Hong; Cai, David; Zhou, Douglas: The extended Granger causality analysis for Hodgkin-Huxley neuronal models (2020)
  15. Chen, Shuo; Bowman, F. DuBois; Xing, Yishi: Detecting and testing altered brain connectivity networks with k-partite network topology (2020)
  16. Chen, Ximing; Ogura, Masaki; Preciado, Victor M.: Bounds on the spectral radius of digraphs from subgraph counts (2020)
  17. Coninck, José C. P.; Ferrari, Fabiano A. S.; Reis, Adriane S.; Iarosz, Kelly C.; Caldas, Iberê L.; Batista, Antonio M.; Viana, Ricardo L.: Network properties of healthy and Alzheimer brains (2020)
  18. Demšar, Jure; Forsyth, Rob: Synaptic scaling improves the stability of neural mass models capable of simulating brain plasticity (2020)
  19. 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)
  20. Hövel, Philipp; Viol, Aline; Loske, Philipp; Merfort, Leon; Vuksanović, Vesna: Synchronization in functional networks of the human brain (2020)

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