Dynamic Functional Connectome Harmonics.

Functional connectivity (FC) "gradients" enable investigation of connection topography in relation to cognitive hierarchy, and yield the primary axes along which FC is organized. In this work, we employ a variant of the "gradient" approach wherein we solve for the normal modes of FC, yielding functional connectome harmonics. Until now, research in this vein has only considered static FC, neglecting the possibility that the principal axes of FC may depend on the timescale at which they are computed.

Functional Hierarchy of the Human Neocortex from Cradle to Grave.

Recent evidence indicates that the organization of the human neocortex is underpinned by smooth spatial gradients of functional connectivity (FC). These gradients provide crucial insight into the relationship between the brain's topographic organization and the texture of human cognition. However, no studies to date have charted how intrinsic FC gradient architecture develops across the entire human lifespan.

Characterizing Intra-soma Diffusion with Spherical Mean Spectrum Imaging.

Most brain microstructure models are dedicated to the quantification of white matter microstructure, using for example sticks, cylinders, and zeppelins to model intra- and extra-axonal environments. Gray matter presents unique micro-architecture with cell bodies (somas) exhibiting diffusion characteristics that differ from axons in white matter. In this paper, we introduce a method to quantify soma microstructure, giving measures such as volume fraction, diffusivity, and kurtosis.

Intrinsic Functional Connectivity of Dentate Nuclei in Autism Spectrum Disorder.

Cerebellar abnormalities are commonly reported in autism spectrum disorder (ASD). Dentate nuclei (DNs) are key structures in the anatomical circuits linking the cerebellum to the extracerebellum. Previous resting-state functional connectivity (RsFc) analyses reported DN abnormalities in high-functioning ASD (HF-ASD).

Automated Parcellation of the Cortex Using Structural Connectome Harmonics.

Meaningful division of the human cortex into distinct regions is a longstanding goal in neuroscience. Many of the most widely cited parcellations utilize anatomical priors or depend on functional magnetic resonance imaging (MRI) data while there exists a relative dearth of parcellations that use only structural data based on diffusion MRI. In light of this, and the fact that structural connectivity represents the underlying substrates of functional connectivity, we employ a novel high-resolution, vertex-level graph model of the whole-brain structural connectome and show that the harmonic modes of this graph can be used to achieve parcellations that qualitatively agree with the widely accepted atlases in the literature.