Table 8.
Information theory analysis software package comparisons.
| Software package | Information measures | Data types | Dynamic information capabilities? (ensemble methods from multiple trials) | Significance testing? | Advanced probability distribution estimation methods and/or bias correction | Language |
|---|---|---|---|---|---|---|
| Neuroscience Information Theory Toolbox | Entropy, mutual information, transfer entropy, partial information decomposition, information transmission, conditional variants | Discrete and continuous | Yes | Yes | No | MATLAB |
| JIDT (Lizier, 2014) | Entropy, mutual information, transfer entropy, information storage, conditional variants | Discrete and continuous | Yes | Yes | Yes | JAVA (with Python and MATLAB functionality) |
| Inform (Moore et al., 2017) | Entropy, Mutual Information, Transfer Entropy | Discrete | Yes | Not directly | No | C (with Python functionality) |
| Transfer Entropy Toolbox (Ito et al., 2011) | Transfer entropy | Spike trains only | No | Not directly | No | MATLAB |
| Trentool (Lindner et al., 2011) | Transfer entropy | Primarily continuous | Yes | Yes | Yes | MATLAB |
| MuTE (Montalto et al., 2014) | Transfer entropy | Primarily continuous | No | Yes | Yes | MATLAB |
| ToolConnect (Pastore et al., 2016) | Entropy, transfer entropy | Spike trains only | No | Yes | No | C++ |
| STAToolkit (Goldberg et al., 2009) | Entropy, mutual information | Spike trains only | Not directly | Yes | Yes | MATLAB |
| PyEntropy (Ince et al., 2009) | Entropy, mutual information | Discrete and continuous | Not directly | Not directly | Yes | Python |
| Information Breakdown Toolbox (Magri et al., 2009) | Entropy, mutual information, breakdown information | Discrete and continuous | Not directly | Not directly | Yes | MATLAB |
| ITE Toolbox (Szabo, 2014) | Entropy, mutual information | Discrete and Continuous | Not directly | Not directly | Yes | MATLAB and Python |
| dit (dit-contributors, 2018) | Entropy, mutual information, and many more | Discrete | Not directly | Not directly | No | Python |
We examined ten other information theory software packages and recorded important features for users. Many packages are either focused on transfer entropy alone or entropy and mutual information calculations. Many packages include advanced estimation and bias correction techniques, unlike the neuroscience information theory toolbox.