├── LICENSE
└── README.md


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 1 | MIT License
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 3 | Copyright (c) 2022 František Váša
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 5 | Permission is hereby granted, free of charge, to any person obtaining a copy
 6 | of this software and associated documentation files (the "Software"), to deal
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/README.md:
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  1 | # Null models in network neuroscience
  2 | 
  3 | Implementations of randomization and generative null models for network neuroscience, in Python, MATLAB and R. 
  4 | 
  5 | The "live" version of Supplementary Table 1 in [**Null models in network neuroscience**](https://www.nature.com/articles/s41583-022-00601-9) by František Váša & Bratislav Mišić.
  6 | 
  7 | ## Python
  8 | 
  9 | ### Randomization
 10 | 
 11 | #### Edges (rewiring)
 12 | 
 13 | * BCTpy (https://github.com/aestrivex/bctpy)
 14 | 
 15 | * brainconn (https://github.com/fiuneuro/brainconn)
 16 | 
 17 | #### Nodes (spin)
 18 | 
 19 | * NeuroMaps (https://netneurolab.github.io/neuromaps/)
 20 | 
 21 | #### Nodes (parametrized)
 22 | 
 23 | * BrainSMASH (https://github.com/murraylab/brainsmash)
 24 | 
 25 | * BrainSpace (https://brainspace.readthedocs.io)
 26 | 
 27 | #### Time-series
 28 | 
 29 | * pyunicorn (https://github.com/pik-copan/pyunicorn)
 30 | 
 31 | #### Correlation matrices (HQS algorithm / configuration model) 
 32 | 
 33 | * spatiotemporal (https://github.com/mwshinn/spatiotemporal)
 34 | 
 35 | * scola (https://github.com/skojaku/scola)
 36 | 
 37 | ### Generative models
 38 | 
 39 | #### Edges
 40 | 
 41 | * neofunkatron (https://github.com/neofunkatron/neofunkatron)
 42 | 
 43 | #### Time-series
 44 | 
 45 | * spatiotemporal (https://github.com/mwshinn/spatiotemporal)
 46 | 
 47 | ## MATLAB
 48 | 
 49 | ### Randomization
 50 | 
 51 | #### Edges (rewiring)
 52 | 
 53 | * BCT (https://sites.google.com/site/bctnet)
 54 | 
 55 | * GRETNA (GUI) (https://nitrc.org/projects/gretna)
 56 | 
 57 | #### Nodes (spin)
 58 | 
 59 | * rotate_parcellation (https://github.com/frantisekvasa/rotate_parcellation)
 60 | 
 61 | * spin-test (vertices) (https://github.com/spin-test/spin-test)
 62 | 
 63 | #### Nodes (parametrized)
 64 | 
 65 | * JuSpace (https://github.com/juryxy/JuSpace)
 66 | 
 67 | * BrainSpace (https://brainspace.readthedocs.io)
 68 | 
 69 | #### Time-series
 70 | 
 71 | * Measures of Analysis of Time Series toolkit (https://mathworks.com/matlabcentral/fileexchange/27561)
 72 | 
 73 | * LancsBioMed (https://github.com/PhysLancIT/LancsBioMed)
 74 | 
 75 | #### Correlation matrices (HQS algorithm / configuration model) 
 76 | 
 77 | * DDT (https://github.com/Emory-CBIS/DDT)
 78 | 
 79 | #### Correlation matrices (distance-dependence)
 80 | 
 81 | * spatial_fc (https://github.com/brain-networks/spatial_fc)
 82 | 
 83 | #### Graph signal processing 
 84 | 
 85 | * Surrogate Graph Signals (https://miplab.epfl.ch/index.php/software/graph-surrogates)
 86 | 
 87 | ### Generative models
 88 | 
 89 | #### Edges
 90 | 
 91 | * generative_models (https://github.com/brain-networks/generative_models)
 92 | 
 93 | * generativenetworkmodel (https://github.com/DanAkarca/generativenetworkmodel)
 94 | 
 95 | ## R
 96 | 
 97 | ### Randomization
 98 | 
 99 | #### Edges (rewiring)
100 | 
101 | * brainGraph (https://github.com/cwatson/brainGraph)
102 | 
103 | * evalClust (https://github.com/GatesLab/evalClust)
104 | 
105 | #### Nodes (spin)
106 | 
107 | * rotate_parcellation (https://github.com/frantisekvasa/rotate_parcellation)
108 | 
109 | #### Time-series
110 | 
111 | * nonlinearTseries (https://github.com/constantino-garcia/nonlinearTseries)
112 | 
113 | #### Correlation matrices (HQS algorithm / configuration model) 
114 | 
115 | * evalClust (https://github.com/GatesLab/evalClust)
116 | 


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