Information theory is becoming an increasingly popular framework for the study of sensory coding. Despite its widespread use for the analysis of single-cell spike trains, it has found relatively limited application to the analysis of other types of neurophysiological signals: This is due to the difficulty in estimating mutual information or entropies and to the lack of fast routines for the application of these techniques to multi-dimensional responses. This toolbox for Matlab provides algorithms for the fast computation of mutual information and other entropy-like quantities which allow to perform the information breakdown described in [1]. Some possible applications of the software have been presented in [2].

[1] G Pola, A Thiele, KP Hoffmann, S Panzeri, An exact method to quantify the information transmitted by different mechanisms of correlational coding, Network 2003 vol. 14 (1) pp. 35-60

[2] C Magri, K Whittingstall, V Singh, NK Logothetis, S Panzeri, A toolbox for the fast information analysis of multiple-site LFP, EEG and spike train recordings, BMC Neuroscience 2009, 10:81