Biology subjects

Adluru, N.

Publications and source records attributed to Adluru, N..

3 recordsLinked to original sources

bioRxiv2017

Heritability of hierarchical structural brain network

We present a new structural brain network parcellation scheme that can subdivide existing parcellations into smaller subregions in a hierarchically nested fashion. The hierarchical parcellation was used to build multilayer convolutional structural brain networks that preserve topology across different network scales. As an application, we applied the method to diffusion weighted imaging study of 111 twin pairs. The genetic contribution of the whole brain structural connectivity was determined. We showed that the overall heritability is consistent across different network scales.

neuroscience↗

bioRxiv2017

Local Low Frequency fMRI Synchrony Is A Proxy For The Spatial Extent Of Functional Connectivity

Functional connectivity Magnetic Resonance Imaging (fcMRI) has assumed a central role in neuroimaging efforts to understand the changes underlying brain disorders. Current models of the spatial and temporal structure of fcMRI based connectivity contain strong a priori assumptions. We report that low temporal frequency fMRI signal synchrony within the local (3 mm radius) neighborhood of a location on the cortical surface strongly predicts the scale of its global functional connectivity. This relationship is tested vertex-wise across the cortex using Spearmans rank order correlation on an individual subject basis. Furthermore, this relationship is shown to be dynamically preserved across repeated within session scans. These results provide a model free data driven method to visualize and quantitatively analyze patterns of connectivity at the imaging voxel resolution across the entire cortex on an individual subject basis. The procedure thus provides a tool to check directly the validity of spatial and temporal prior assumptions incorporated in the analysis of fcMRI data.

neuroscience↗

bioRxiv2017

Integrative Structural Brain Network Analysis In Diffusion Tensor Imaging

In diffusion tensor imaging, structural connectivity between brain regions is often measured by the number of white matter fiber tracts connecting them. Other features such as the length of tracts or fractional anisotropy (FA) are also used in measuring the strength of connectivity. In this study, we investigated the effects of incorporating the number of tracts, the tract length and FA-values into the connectivity model. Using various node-degree based graph theory features, the three connectivity models are compared. The methods are applied in characterizing structural networks between normal controls and maltreated children, who experienced maltreatment while living in post-institutional settings before being adopted by families in the US.

neuroscience↗