About us

The OHBA Analysis Group develops novel computational methodologies for analysing neuroimaging data, in order to investigate the human brain in fundamental and clinical neuroscience research. We use techniques from Bayesian statistics, machine learning, pattern recognition and image/signal processing.

Our projects


Tools for analysis and visualiation of M/EEG data

osl-core provides a set of tools build on Fieldtrip and SPM for analysis of MEG and EEG data in SPM12 format.


Segmentation and characterisation of transient connectivity

HMM-MAR is a Matlab toolbox to identify recurrent brain states of distinct multi-region spectral properties, providing parametric and nonparametric estimations of power, coherence and partial directed coherence for each state


Empirical Mode Decomposition for Neuronal Oscillations

EMD is an analysis approach for characterising non-stationary and non-sinusoidal oscillations. The EMD toolbox is a python package containing a range of decompositions and functions for instantaneous spectral analyses

MEG ROI nets

Region of Interest Network Analysis for MEG

ROI nets is a Matlab toolbox for performing parcellation, leakage correction and network analysis in MEG data, written for SPM12.