Estimating axon conduction velocity in vivo from microstructural MRI

Autor: Derek K. Jones, Greg D. Parker, Robbert L. Harms, Suryanarayana Umesh Rudrapatna, Mark Drakesmith, C. John Evans
Přispěvatelé: RS: FPN CN 11, Multiscale Imaging of Brain Connectivity
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Male
Neural Conduction
Nerve conduction velocity
0302 clinical medicine
MYELIN G-RATIO
Axon
BRAIN
NEURITE ORIENTATION DISPERSION
Mathematics
05 social sciences
White matter
INTERNODAL LENGTH
DIFFUSION
medicine.anatomical_structure
Neurology
Myelin
Female
SPINAL-CORD
SENSITIVITY
Biological system
Adult
Relaxometry
Optic nerve
Cognitive Neuroscience
Corpus callosum
Models
Neurological
NERVE-FIBERS
050105 experimental psychology
Article
Biophysical Phenomena
Diffusion MRI
03 medical and health sciences
Young Adult
conduction velocity
Relaxometry MRI
medicine
Humans
0501 psychology and cognitive sciences
Sensitivity (control systems)
Tissue micro-structure
Axon diameter
DIAMETER
Biophysical modelling
Neurophysiology
Axons
Electrophysiology
Diffusion Magnetic Resonance Imaging
DENSITY
G-ratio
Action potentials
030217 neurology & neurosurgery
Zdroj: Neuroimage, 203:116186. Elsevier Science
Neuroimage
ISSN: 1053-8119
Popis: The conduction velocity (CV) of action potentials along axons is a key neurophysiological property central to neural communication. The ability to estimate CV in humans in vivo from non-invasive MRI methods would therefore represent a significant advance in neuroscience. However, there are two major challenges that this paper aims to address: (1) Much of the complexity of the neurophysiology of action potentials cannot be captured with currently available MRI techniques. Therefore, we seek to establish the variability in CV that can be captured when predicting CV purely from parameters that have been reported to be estimatable from MRI: inner axon diameter (AD) and g-ratio. (2) errors inherent in existing MRI-based biophysical models of tissue will propagate through to estimates of CV, the extent to which is currently unknown. Issue (1) is investigated by performing a sensitivity analysis on a comprehensive model of axon electrophysiology and determining the relative sensitivity to various morphological and electrical parameters. The investigations suggest that 85% of the variance in CV is accounted for by variation in AD and g-ratio. The observed dependency of CV on AD and g-ratio is well characterised by the previously reported model by Rushton. Issue (2) is investigated through simulation of diffusion and relaxometry MRI data for a range of axon morphologies, applying models of restricted diffusion and relaxation processes to derive estimates of axon volume fraction (AVF), AD and g-ratio and estimating CV from the derived parameters. The results show that errors in the AVF have the biggest detrimental impact on estimates of CV, particularly for sparse fibre populations (AVF
Highlights • 85% of the variance in CV is accounted for by axon diameter and g-ratio, which are potentially accessible from in vivo MRI. • CV estimates from MRI are robust to errors in myelin and axonal volume estimates, but sensitive to errors in axon diameter. • CV estimates are feasible for large axons but limitations of in vivo imaging of small axons poses a significant challenge.
Databáze: OpenAIRE
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