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Resting state connectivity Analysis

The study of the neural activity in the resting state has been shown to provide valuable insight into the functional organisation of the human brain. Resting state is defined as the activity observed when the subject is awake and performing no specific task in particular. It was first observed in fMRI by Biswal et al. in 1995 . Since then, studies have shown the existence of many resting state networks in the brain. Studying these functional networks has revealed interesting results on how the brain organises itself. Furthermore, functional connectivity analysis of the resting state brain has shown differences between brains of healthy people and those affected with various neurological disorders such as, Alzheimer’s disease, dementia and schizophrenia.
In this project, we seek to characterise the resting state networks in the brain using magnetoencephalography (MEG). Due to the high temporal resolution of MEG, functional network activity in higher frequency bands can be well observed. MEG recordings are source localised to specific regions of interest and functional connectivity is computed using frequency domain based methods. The connectivity structures are further analyzed using network analysis and statistics. The analysis is performed using mne-python software .
Figure 1 showing connections among various Freesurfer labels in a group of subjects based on the weighted phase lag index (WPLI) metric. The most popular connections are visualised.


Resting state connectivity Analysis

Figure 1 Connectivity circle plot showing popular WPLI connections between various Freesurfer labels in a group of subjects. Both intra and inter hemispheric connections are plotted.

References

Sripad, P., Boers, F., Clauss, R., Langen, K.-J., Shah, N. J, Dammers, J., "Differences in resting state connectivity in an injured brain under influence of Zolpidem - a case study". Poster presented at BIOMAG 2016, 20th International conference on Biomagnetism,
05 October 2016.