Transient event detection with Hidden Markov Models
This repository contains the scripts and software to run the simulations and real data analysis published in:
Andrew J. Quinn, Freek van Ede, Matthew J. Brookes, Simone G. Heideman, Magdalena Nowak, Zelekha A. Seedat, Diego Vidaurre, Catharina Zich, Anna C. Nobre, Mark W. Woolrich (2019) Unpacking Transient Event Dynamics in Electrophysiological Power Spectra. Brain Topography.
https://doi.org/10.1007/s10548-019-00745-5
The analysis requires the following software running on a Unix-Type operating system.
hmm_0_initialise
to point to the location of these toolboxes on your computerhmm_0_initialise
in MatLab, if this returns without error then you are good to go. If you see warnings then some dependencies may be missing, follow the instructions in the warning message.hmm_0_initialise
runs the initial setup and configuration for these analyses
hmm_1_dynamics_illustration
creates and plots the power simulations from figure 1
hmm_2_envelope
runs an amplitude-envelope HMM on simulated data and creates figure 2
hmm_3_embedded
runs an time-delay embedded HMM on simulated data and creates figure 3
hmm_4_realdata_trialwise
runs an time-delay embedded HMM and task-evoked analysis on source-space MEG data and creates figures 4, 5, 6 and 7