The Influence of Preprocessing Steps on Graph Theory Measures Derived from Resting State fMRI

Resting state functional MRI (rs-fMRI) is an imaging technique that allows the spontaneous activity of the brain to be measured. Measures of functional connectivity highly depend on the quality of the BOLD signal data processing. In this study, our aim was to study the influence of preprocessing steps and their order of application on small-world topology and their efficiency in resting state fMRI data analysis using graph theory. We applied the most standard preprocessing steps: slice-timing, realign, smoothing, filtering, and the tCompCor method. In particular, we were interested in how preprocessing can retain the small-world economic properties and how to maximize the local and global efficiency of a network while minimizing the cost. Tests that we conducted in 54 healthy subjects showed that the choice and ordering of preprocessing steps impacted the graph measures. We found that the csr (where we applied realignment, smoothing, and tCompCor as a final step) and the scr (where we applied realignment, tCompCor and smoothing as a final step) strategies had the highest mean values of global efficiency (eg). Furthermore, we found that the fscr strategy (where we applied realignment, tCompCor, smoothing, and filtering as a final step), had the highest mean local efficiency (el) values. These results confirm that the graph theory measures of functional connectivity depend on the ordering of the processing steps, with the best results being obtained using smoothing and tCompCor as the final steps for global efficiency with additional filtering for local efficiency

Neuroimaging of Sudden Unexpected Death in Epilepsy (SUDEP)

BACKGROUND: Sudden unexpected death in epilepsy (SUDEP) is the leading cause of premature death among people with epilepsy. The precise mechanisms underlying SUDEP remain elusive, though work so far demonstrates a potential centrally mediated event in which autonomic, respiratory and/or arousal processes fail to recover following a significant seizure. Neuroimaging enables non-invasive assessment of the structural and functional architecture among sites and networks involved in regulating such processes; damage or alterations may indicate a central predisposition in those at high-risk and who suffer SUDEP, and provide non-invasive biomarkers. // METHODS: In this thesis, structural and functional imaging techniques were employed to address this possibility. Both retrospective investigations of those who succumbed to SUDEP, and prospective studies of those at high-risk, were performed. Voxel-based morphometry, volumetry and resting-state functional magnetic resonance imaging (RS-fMRI) network analysis techniques were utilised to identify and characterise brain structural and functional alterations relative to low-risk subjects and controls. // RESULTS: Brain morphometric and volumetric alterations among sites involved in cardiorespiratory regulation and recovery were found in those who later suffered SUDEP and in matched, living individuals at high risk. Prospective work revealed similar, and additional, structural alterations in those at high-risk which were associated with the extent of seizure-related hypoxemia; notably among the thalamus, periaqueductal grey (PAG), medulla, vermis and hippocampus. Network analysis of functional imaging data revealed disturbed patterns of connectivity in high-risk temporal lobe epilepsy (TLE) patients, and altered functional organisation in confirmed cases of SUDEP, among regulatory brain sites as well as the whole brain. // CONCLUSIONS: Structural and resting state functional connectivity disturbances were found in patients who suffered SUDEP, and those at elevated risk. Injury and connectivity disturbances may indicate damage or dysfunction within sites and networks involved central regulatory processes, which could facilitate SUDEP. However, further work is required to elucidate the precise mechanisms of volume and functional connectivity alterations, and to provide firm links between centrally mediated autonomic and respiratory dysfunction, SUDEP and related imaging findings. A more immediate use for the imaging outcomes revealed here may rest with the development of non-invasive biomarkers, which may one day assist in identifying those at risk and evaluating individual risk for SUDEP based on injury to brain sites or altered functional networks