Identifying network hubs from brain anatomical similarity networks

Background Brain hubs are highly connected regions important for integrating cognitive processing in the healthy brain. also play role neurodegeneration causing dementia. However, it is not clear what brain morphometry most useful identifying critical to their involvement neurodegeneration. Method We examined network from four measures of cortical morphometry, derived using anatomical T1-weigher MRI. From a large cohort participants (N = 260) 20 85 years age, we generated 200 networks each measure bootstrapping. then tested how two hubness – nodal strength and clustering coefficient were mapped onto across all morphometric feature. Regions identified as if ranked standard deviations away corresponding group mean. Result out (features) morphometry. Nodal showed similarity behaviour features: gray volume, regional surface area its thickness deviation. differences found region qualify hub Conclusion Cortical extracted scans can be used potential imaging marker identification potentially involved early differentiation dementia subtypes. References: Vuksanović V, Staff RT, Ahearn T, Murray AD, Wischik CM. Thickness Surface Area Networks Healthy Aging, Alzheimer’s Disease Behavioral Variant Fronto-Temporal Dementia. Int J Neural Syst. 2019 Aug;29(6):1850055. https://doi.org/10.1142/S0129065718500557. Evans AC. covariance. Neuroimage. 2013 Oct 15;80:489-504. https://doi.org/10.1016/j.neuroimage.2013.05.054.