Exploration of the relationship between brain function and cortical development in the human preterm period with simultaneous EEG-fMRI

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In animal models, spontaneous bursts of synchronized neuronal activity play an instructiverole in key developmental processes that set early cortical circuits. Experimental disruptionleads to permanent loss of healthy cortical organization, suggesting this may represent a keypathological process in conditions like autism which originate in early life and are associatedwith cortical dysfunction.Although similar bursts of neural activity are seen on scalp electroencephalography [EEG] inpreterm human infants, they cannot be directly related to cortical development due tolimitations in spatial specificity. Simultaneously acquired EEG and functional MRI [fMRI] dataovercomes these restrictions and crucially can be combined with data from other MRIcontrasts. This can provide detailed characterisation of the underlying brain anatomy [eg,cortical folding and key developmental regions like the subplate], and allows analysis of therelationship with key deep brain structures [ie, thalamus and cerebellum] and MR derivedmeasures of tissue microstructure [such as neurite density and orientation dispersion index].This project will test the hypothesis that spontaneous bursting neural activity localises todeveloping brain regions in preterm infants. In addition to 50 existing simultaneous EEG-fMRIneonatal datasets [the only dataset in the world], new data will be collected to provide adeeper characterisation of brain development at different ages. A machine learningclassification algorithm will be used to characterise spontaneous bursting events within theEEG data and then a combination of source localization algorithms and traditional fMRItimeseries analysis used to identify spatial relationships. Resulting spatial maps can then bealigned to other subject-specific and population level MRI data.