Kusmia, S. | bioRxiv Science

bioRxiv2021

Validating Pore Size Estimates in a Complex Microfibre Environment on a Human MRI System

PurposeRecent advances in diffusion-weighted MRI provide restricted diffusion signal fraction and restricting pore size estimates. Materials based on co-electrospun oriented hollow cylinders have been introduced to provide validation for such methods. This study extends this work, exploring accuracy and repeatability using an extended acquisition on a 300 mT/m gradient human MRI scanner, in substrates closely mimicking tissue, i.e., non-circular cross-sections, intra-voxel fibre crossing, intra-voxel distributions of pore-sizes and smaller pore-sizes overall. MethodsIn a single-blind experiment, diffusion-weighted data were collected from a biomimetic phantom on a 3T Connectom system using multiple gradient directions/diffusion times. Repeated scans established short-term and long-term repeatability. The total scan time (54 minutes) matched similar protocols used in human studies. The number of distinct fibre populations was estimated using spherical deconvolution, and median pore size estimated through the combination of CHARMED and AxCaliber3D framework. Diffusion-based estimates were compared with measurements derived from scanning electron microscopy. ResultsThe phantom contained substrates with different orientations, fibre configurations and pore size distributions. Irrespective of one or two populations within the voxel, the pore-size estimates (~5m) and orientation-estimates showed excellent agreement with the median values of pore-size derived from scanning electron microscope and phantom configuration. Measurement repeatability depended on substrate complexity, with lower values seen in samples containing crossing-fibres. Sample-level repeatability was found to be good. ConclusionWhile no phantom mimics tissue completely, this study takes a step closer to validating diffusion microstructure measurements for use in vivo by demonstrating the ability to quantify microgeometry in relatively complex configurations.

biophysics↗

bioRxiv2019

Action kinematics as an organising principle in the cortical control of human hand movement

Hand movements are controlled by neuronal networks in primary motor cortex (M1). The organising principle in M1 does not follow an anatomical body map, but rather a distributed representational structure in which motor primitives are combined to produce motor outputs. Both electrophysiological recordings in primates and human imaging data suggest that M1 encodes kinematic features of movements, such as joint position and velocity. However, M1 exhibits well-documented sensory responses to cutaneous and proprioceptive stimuli, raising questions regarding the origins of kinematic motor representations: are they relevant in top-down motor control, or are they an epiphenomenon of bottom-up sensory feedback during movement? Moreover, to what extent is information related to muscle activity encoded in motor cortex? Here we provide evidence for spatially and temporally distinct encoding of kinematic and muscle information in human M1 during the production of a wide variety of naturalistic hand movements. Using a powerful combination of high-field fMRI and MEG, a spatial and temporal multivariate representational similarity analysis revealed encoding of kinematic information from data glove recordings in more caudal regions of M1, over 200ms before movement onset. In contrast, patterns of muscle activity from EMG were encoded in more rostral motor regions later in the cycle of movement. Our spatial and temporal analysis provide compelling evidence that top-down control of dexterous movement engages kinematic representations in caudal regions of M1 prior to movement production; an area with direct cortico-motorneuronal connections. Muscle information encoded more rostrally in M1 was engaged later, suggestive of involvement in bottom-up signalling.

neuroscience↗