This section contains links to code that we have developed over the years. The code is organized according to papers that have introduced the various methods.

1. Sarah Feldt Muldoon, Eric W. Bridgeford, Danielle S. Bassett. Small-world propensity in real-world weighted networks. Submitted. Associated code can be found here.

2. Shi Gu, Theodore Satterthwaite, John Medaglia, Muzhi Yang, Raquel Gur, Ruben Gur, Danielle S. Bassett. Emergence of System Roles in Normative Neurodevelopment. PNAS. In Press.  Associated code can be found here.

3. Marcelo Mattar, Michael W. Cole, Sharon Thompson-Schill, Danielle S. Bassett. A Functional Cartography of Cognitive Systems. Provisionally Accepted to PLoS Computational Biology. Associated code can be found here.

4. Urs Braun, Axel Schaefer, Henrik Walter, Susanne Erk, Nina Romanczuk-Seiferth, Leila Haddad, Janina Schweiger, Oliver Grimm, Andreas Heinz, Heike Tost, Andreas Meyer-Lindenberg, Danielle S. Bassett. Dynamic Reconfiguration of Frontal Brain Networks During Executive Cognition in Humans. PNAS. In Press. Associated code can be found here.

5. Danielle S. Bassett, Muzhi Yang, Nicholas F. Wymbs, Scott T. Grafton. Learning-Induced Autonomy of Sensorimotor Systems. Nature Neurosci, 2015, In Press. Associated code can be found here.

6. Danielle S. Bassett, Nicholas F. Wymbs, M. Puck Rombach, Mason A. Porter, Peter J. Mucha, Scott T. Grafton. Task-Based core-periphery organisation of human brain dynamics. PLoS Comp Biol, 2013, 9(9): e1003171. Associated code can be found here.

7. Danielle S. Bassett, Mason A. Porter, Nicholas F. Wymbs, Scott T. Grafton, Jean M. Carlson, Peter J. Mucha. Robust detection of dynamic community structure in networks. Chaos, 2013, 23, 1. Associated code can be found here.

8. Danielle S. Bassett, N F Wymbs, M A Porter, P J Mucha, J M Carlson, S T Grafton. Dynamic reconfiguration of human brain networks during learning. PNAS, 2011, 108(18):7641-7646. Associated code can be found here.



This section contains links to data that we have published over the years. The data is organized according to papers that used them.

1. Richard F. Betzel, Shi Gu, John D. Medaglia, Fabio Pasqualetti, Danielle S. Bassett. Optimally controlling the human connectome: the role of network topology. Scientific Reports. 2016 Jul 29;6:30770.  

2. Ari E. Kahn, Marcelo G. Mattar, Jean M. Vettel, Nicholas F. Wymbs, Scott T. Grafton, Danielle S. Bassett. Structural Pathways Supporting Swift Acquisition of New Visuo-Motor Skills. Cerebral Cortex. 2017 Jan 1;27(1):173-184. 

3. Arian Ashourvan, Shi Gu, Marcelo G. Mattar, Jean M. Vettel, Danielle S. Bassett. The Energy Landscape Underpinning Module Dynamics in the Human Brain Connectome. Neuroimage. 2017 Jun 7. pii: S1053-8119(17)30467-6.

  • DATA: bp_wtc.mat. The band passed (averaged) wavelet coherence 3D matrices [ ROI (n=10) X ROI (n=10) X TR (n=1190)] are stored in BP_WTC{subject(n=20), session(n=4),band(n=2)} cell.

4. Ann E. Sizemore, Chad Giusti, Ari E. Kahn, Richard F. Betzel, Danielle S. Bassett. Cliques and Cavities in the Human Connectome. In Revision. 2017.

  • DATA: individual_brains.mat. The file contains the 24 individual networks created from streamline counts between 83 brain regions. 

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