Meeting Banner
Abstract #0176

Whole-Brain Connectivity Mapping in Infants Reveals Widespread Areas of White Matter Damage Associated with Prematurity

Anand Pandit1, 2, Emma Robinson3, Paul Aljabar1, Gareth Ball1, Ioannis S. Gousias4, Zi Wang5, Giovanni Montana5, Jo Hajnal1, Daniel Rueckert6, Serena J. Counsell7, A. David Edwards1

1Centre for the Developing Brain, King's College, London, United Kingdom; 2Centre for the Developing Brain, Imperial College, London, London, United Kingdom; 3FMRIB, University of Oxford, Oxford, Oxfordshire, United Kingdom; 4Centre for the Developing Brain, Imperial College, London, United Kingdom; 5Statistics Section, Department of Mathematics, Imperial College, London, United Kingdom; 6Department of Computing, Imperial College, London, United Kingdom; 7Centre for the Developing Brain, King's College London, London, United Kingdom

Combining a novel pipeline which maps whole-brain structural connectivity with sophisticated statistical techniques, namely sparse penalised regression and stability selection, we explore the influence of two factors predicted to affect connectivity in the early infant population: development and the degree of prematurity at birth. White matter tracts joining anterior structures were positively associated with development, while more extreme prematurity at birth was related to widespread reductions in connections involving all cortical lobes and several subcortical structures.

Keywords

affect anatomical anisotropy anterior approaches background ball birth born brain carried cerebral coarse coefficients college combining computing conceptional connection connections connectivity corrected cortical create damage degree described detected developing development diffusion early employed excluded explore extreme fifty fits fitted genome gestational highlights identify imperial in vivo infancy infant infants influence intra involving joining king kingdom lambda lasso lobes major make mapping mathematics measure merges model months oxford pathology pipeline positively post postnatal predicted premature prematurity previously probability processing random reductions regression related repeated response reveals sample scanner scanning section segmentations selected selection several space sparse stability statistics strength structural structures subjective subjects suggests taken taking tissue topographical tract tracts variable weeks whilst white whole widespread wise