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Register a new userCoherent Fourier scatterometry reveals nerve fiber crossings in the brain
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Previous simulation studies by Menzel et al. [Phys. Rev. X 10, 021002 (2020)] have shown that scattering patterns of light transmitted through artificial nerve fiber constellations contain valuable information about the tissue substructure such as the individual fiber orientations in regions with crossing nerve fibers. Here, we present a method that measures these scattering patterns in monkey and human brain tissue using coherent Fourier scatterometry with normally incident light. By transmitting a non-focused laser beam (wavelength of 633 nm) through unstained histological brain sections, we measure the scattering patterns for small tissue regions (with diameters of 0.1-1 mm), and show that they are in accordance with the simulated scattering patterns. We reveal the individual fiber orientations for up to three crossing nerve fiber bundles, with crossing angles down to 25{deg}.
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Given that many fundamental questions in neuroscience are still open, it seems pertinent to explore whether the brain might use other physical modalities than the ones that have been discovered so far. In particular it is well established that neurons can emit photons, which prompts the question whether these biophotons could serve as signals between neurons, in addition to the well-known electro-chemical signals. For such communication to be targeted, the photons would need to travel in waveguides. Here we show, based on detailed theoretical modeling, that myelinated axons could serve as photonic waveguides, taking into account realistic optical imperfections. We propose experiments, both textit{in vivo} and textit{in vitro}, to test our hypothesis. We discuss the implications of our results, including the question whether photons could mediate long-range quantum entanglement in the brain.
Wearable devices have been shown to effectively measure the head movement during impacts in sports like American football. When a head impact occurs, the device is triggered to collect and save the kinematic measurements during a predefined time window. Then, based on the collected kinematics, finite element (FE) head models can calculate brain strain, which is used to evaluate the risk of mild traumatic brain injury. To find a time window that can provide a sufficient duration of kinematics for FE analysis, we investigated 118 on-field video-confirmed head impacts collected by the Stanford Instrumented Mouthguard. Because the individual differences in brain geometry influence these calculations, we included six representative brain geometries and found that larger brains need a longer time window of kinematics for accurate calculation. Among the different sizes of brains, a pre-trigger time of 20 ms and a post-trigger time of 70 ms were found to yield calculations of brain strain and strain rate that were not significantly different from calculations using the original 200 ms time window recorded by the mouthguard.
Acoustic impedance mismatches between soft tissues and bones are known to result in strong aberrations in optoacoustic and ultrasound images. Of particular importance are the severe distortions introduced by the human skull, impeding transcranial brain imaging with these modalities. While modelling of ultrasound propagation through the skull may in principle help correcting for some of the skull-induced aberrations, these approaches are commonly challenged by the highly heterogeneous and dispersive acoustic properties of the skull and lack of exact knowledge on its geometry and internal structure. Here we demonstrate that the spatio-temporal properties of the acoustic distortions induced by the skull are preserved for signal sources generated at neighboring intracranial locations by means of optoacoustic excitation. This optoacoustic memory effect is exploited for building a three-dimensional model accurately describing the generation, propagation and detection of time-resolved broadband optoacoustic waveforms traversing the skull. The memory-based model-based inversion is then shown to accurately recover the optical absorption distribution inside the skull with spatial resolution and image quality comparable to those attained in skull-free medium.
We present a novel mathematical approach to model noise in dynamical systems. We do so by considering dynamics of a chain of diffusively coupled Nagumo cells affected by noise. We show that the noise in transmembrane current can be effectively modelled as fluctuations in electric characteristics of the membrane. The proposed approach to model noise in a nerve fibre is different from the standard additive stochastic current perturbation (the Langevin type equations).
In this note we explain that homotopy coherent simplicial nerve has to used intead of the standard definition in the authors papers on formal deformation theory. A convenient version of the notion of fibered category is presented which is useful once one works with simplicial categories.
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