Biology subjects

Whi, W.

Publications and source records attributed to Whi, W..

3 recordsLinked to original sources

bioRxiv2022

Time-varying hierarchical core voxels disclosed by k-core percolation on dynamic inter-voxel connectivity resting-state fMRI

k-core percolation on the scale-free static brain connectivity revealed hierarchical structure of inter-voxel correlations, which was successfully visualized by hyperbolic disc embedding on resting-state fMRI. In static study, flagplots and brain rendered kmax-core display showed the changes of hierarchical structures of voxels belonging to functional independent components (IC). In this dynamic sliding-window study, temporal progress of hierarchical structure of voxels were investigated in individuals and in sessions of an individual. kmax-core and coreness k values characterizing time-varying core voxels were visualized on animated stacked-histogram/flagplots and animated brain-rendered images. Resting-state fMRI of Human Connectome Project and of Kirby weekly revealed the slow progress and multiple abrupt state transitions of the voxels of coreness k and at the uppermost hierarchy, representing their correlative time-varying mental states in individuals and in sessions. We suggest this characteristic core voxels-IC compositions on dynamic study fingerprint the time-varying resting states of human minds. One Sentence SummaryDynamic state transitions of hierarchical functional inter-voxel connectivity implied time-varying mental states at rest on fMRI

neuroscience↗

bioRxiv2021

Characteristic core voxels in normal individuals revealed by hyperbolic disc embedding and k-core percolation on resting state fMRI

Hyperbolic disc embedding and k-core percolation reveal the core structure of the functional connectivity on resting-state fMRI (rsfMRI). Inter-voxel relations were visualized on embedded hyperbolic discs, and their core composition was traced using k-core percolation. Using 180 normal adults rsfMRI data from the Human Connectome Project database, scale- free intervoxel connectivity represented by IC-voxels composition, while visualized on hyperbolic discs using [Formula] model, showed the expected change of the largest component decreasing its size on k-core percolation eventually yielding the core structures of individuals. This kmax-core voxels-ICs composition revealed such stereotypes of individuals as visual network dominant, default mode network dominant, and distributed patterns. Characteristic core structures of resting-state brain connectivity of normal subjects disclosed the distributed or asymmetric contribution of voxels to the kmax-core, which suggests the hierarchical dominance of certain IC subnetworks characteristic to subgroups of individuals at rest.

neuroscience↗

bioRxiv2021

Hyperbolic disc embedding of functional human brain connectomes using resting state fMRI

The brain presents a real complex network of modular, small-world, and hierarchical nature, which are features of non-Euclidean geometry. Using resting-state functional magnetic resonance imaging (rs-fMRI), we constructed a scale-free binary graph for each subject, using internodal time-series correlation of regions-of-interest (ROIs) as a proximity measure. The resulted network could be embedded onto manifolds of various curvature and dimensions. While maintaining the fidelity of embedding (low distortion, high mean average precision), functional brain networks were found to be best represented in the hyperbolic disc. Using [Formula] model, we reduced the dimension of the network into 2-D hyperbolic space and were able to efficiently visualize the internodal connections of the brain, preserving proximity as distances and angles on the hyperbolic discs. Each individual disc revealed decentralized nature of information flow and anatomic relevance. Using the hyperbolic distance on the [Formula] model, we could detect the anomaly of network in autistic spectrum disorder (ASD) subjects. This procedure of embedding grants us a reliable new framework for studying functional brain networks and the possibility of detecting anomalies of the network in the hyperbolic disc on an individual scale.

neuroscience↗