Séminaire – Erin W. Dickie


Présentateur: Dr Erin W. Dickie
Titre: Personalized Connectomics for the Study of Brain Health and Disease: Applications to Autism Spectrum Disorder and Schizophrenia Research.
Endroit: CRIUGM – Local E1910 (http://www.criugm.qc.ca/en/contact.html)
Date: Jeudi 24 mai, 13h-14h

*La conférence sera présentée en anglais

Dr. Erin Dickie (PhD, Neurological Sciences, McGill University) is a Project Scientist. Dr. Dickie’s research focus is personalized connectomics, or the ability to map brain organization at the level of the individual. Individual mapping of brain function may be a critical first step in the design of targets for stimulation therapy. Dr. Dickie recently submitted a manuscript describing her tool for mapping neurodiversity (PINT), and showed that the brains of those affected by autism and more variable in their organization that those of typically developing controls. This work suggests that personalized brain mapping might be a critical first step for future biomarker discovery. Dr. Dickie also assists with the lab’s data management and analysis system, and builds automated tools for data analysis. In the past year, she has developed a new tool for surface-based analyses (ciftify) that has been publicly available and adopted by international groups.


Emerging work from the neuroimaging community shows that everyone’s cerebral cortex has a unique functionally organisation and that this unique organisation can be mapped using neuroimaging data at the individual participant level. To do so, we start with an analytic approach, using the CIFTI file format, that allows for a more neuroanatomically-faithful representation of data. An open source set of tools ‘ciftify’ (https://edickie.github.io/ciftify) make this approach more accessible to the greater scientific community. We than introduce novel methods for incorporating resting-state fMRI data to map the spatial topography of the cortical surface in individual subjects and discuss the applications to the study of brain pathologies including Autism Spectrum Disorder and Schizophrenia. Using the ABIDEI dataset, we found greater spatial variability in resting state network location in individuals with ASD with a disrupted developmental trajectory. Accounting for this variability decreased the number of hypo-connected regions observed in individuals with ASD. This phenomenon could have far reaching implications for how clinical neuroimaging research is analysed and interpreted