This set of MATLAB m-files implement a novel complexity index for time series describing a complex system. I have presented this novel complexity index in every functional neuroimaging modality in a recent paper [1].
We have adapted this novel complexity index in conjunction with famous Lempel -Ziv complexity in two MEG datasets, one with mild traumatic brain injury and healthy control subjects [2] and one with dsylexic children and healthy controls [3]. In both datasets, we reported higher classification performance for detecting reading children and mild traumatic brain inured subjects versus healthy controls with our novel complexity index compared to Lempel -Ziv complexity.
If you use this dataset for any case, please cite mainly reference no.1
References:
[1] S.I. Dimitriadis (2018). Complexity of brain activity and connectivity in functional neuroimaging. Journal of Neuroscience Research, 96(11):1741–1757, 2018.
[2] Antonakakis M, Dimitriadis SI et al.,(2016) Improving the Detection of mTBI Via Complexity Analysis in Resting – State Magnetoencephalography. DOI: 10.1109/IST.2016.7738215 Conference: 2016 IEEE International Conference on Imaging Systems and Techniques (IST 2016)At: Chania Crete Greece
[3] Dimitriadis SI et al., (2016) Classifying Children with Reading Difficulties from Non-Impaired Readers via Symbolic Dynamics and Complexity Analysis of MEG Resting-State Data. December 2016 ; DOI: 10.1109/ISSPIT.2016.7886059 Conference: IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)At: Limassol (CYPRUS)