Sticky and Strain-Gradient Artificial Epineurium for Sutureless Nerve Repair in Rodents and Nonhuman Primates.

The need for the development of soft materials capable of stably adhering to nerve tissues without any suturing followed by additional damages is at the fore at a time when success in postoperative recovery depends largely on the surgical experience and/or specialized microsuturing skills of the surgeon. Despite fully recognizing such prerequisite conditions, designing the materials with robust adhesion to wet nerves as well as acute/chronic anti-inflammation remains to be resolved. Herein, a sticky and strain-gradient artificial epineurium (SSGAE) that overcomes the most critically challenging aspect for realizing sutureless repair of severely injured nerves is presented. In this regard, the SSGAE with a skin-inspired hierarchical structure entailing strain-gradient layers, anisotropic Janus layers including hydrophobic top and hydrophilic bottom surfaces, and synergistic self-healing capabilities enables immediate and stable neurorrhaphy in both rodent and nonhuman primate models, indicating that the bioinspired materials strategy significantly contributes to translational medicine for effective peripheral nerve repair.

Prior expectation enhances sensorimotor behavior by modulating population tuning and subspace activity in sensory cortex.

Prior knowledge facilitates our perception and goal-directed behaviors, particularly when sensory input is lacking or noisy. However, the neural mechanisms underlying the improvement in sensorimotor behavior by prior expectations remain unknown. In this study, we examine the neural activity in the middle temporal (MT) area of visual cortex while monkeys perform a smooth pursuit eye movement task with prior expectation of the visual target's motion direction. Prior expectations discriminately reduce the MT neural responses depending on their preferred directions, when the sensory evidence is weak. This response reduction effectively sharpens neural population direction tuning. Simulations with a realistic MT population demonstrate that sharpening the tuning can explain the biases and variabilities in smooth pursuit, suggesting that neural computations in the sensory area alone can underpin the integration of prior knowledge and sensory evidence. State-space analysis further supports this by revealing neural signals of prior expectations in the MT population activity that correlate with behavioral changes.

Frontal-to-visual information flow explains predictive motion tracking.

Predictive tracking demonstrates our ability to maintain a line of vision on moving objects even when they temporarily disappear. Models of smooth pursuit eye movements posit that our brain achieves this ability by directly streamlining motor programming from continuously updated sensory motion information. To test this hypothesis, we obtained sensory motion representation from multivariate electroencephalogram activity while human participants covertly tracked a temporarily occluded moving stimulus with their eyes remaining stationary at the fixation point. The sensory motion representation of the occluded target evolves to its maximum strength at the expected timing of reappearance, suggesting a timely modulation of the internal model of the visual target. We further characterize the spatiotemporal dynamics of the task-relevant motion information by computing the phase gradients of slow oscillations. We discovered a predominant posterior-to-anterior phase gradient immediately after stimulus occlusion; however, at the expected timing of reappearance, the axis reverses the gradient, becoming anterior-to-posterior. The behavioral bias of smooth pursuit eye movements, which is a signature of the predictive process of the pursuit, was correlated with the posterior division of the gradient. These results suggest that the sensory motion area modulated by the prediction signal is involved in updating motor programming.

The effect of temporal expectation on the correlations of frontal neural activity with alpha oscillation and sensory-motor latency.

In a dynamic environment, we seek to enhance behavioral responses by anticipating future events. Previous studies have shown that the probability distribution of the timing of future events could shape our expectation of event timing; furthermore, the modulation of alpha oscillation is known to be a critical neural factor. However, a link between the modulation of alpha oscillation by temporal expectation and single neural activity is missing. In this study, we investigated how temporal expectation modulated frontal neural activities and behavioral reaction time by recording neural activity from the frontal eye field smooth pursuit eye movement region of monkeys while they performed a smooth pursuit eye movement task. We found that the temporal expectation reduced the coherence between the neural spiking and alpha frequency of the local field potential, along with the trial-by-trial correlation between the neural spiking activity and pursuit latency. This result suggests that the desynchronization of alpha oscillation by temporal expectation would be related to the decorrelation of population neural activity, which could be the neural source of reaction time enhancement by temporal expectation.

Motor-effector dependent modulation of sensory-motor processes identified by the multivariate pattern analysis of EEG activity.

Sensory information received through sensory organs is constantly modulated by numerous non-sensory factors. Recent studies have demonstrated that the state of action can modulate sensory representations in cortical areas. Similarly, sensory information can be modulated by the type of action used to report perception; however, systematic investigation of this issue is scarce. In this study, we examined whether sensorimotor processes represented in electroencephalography (EEG) activities vary depending on the type of effector behavior. Nineteen participants performed motion direction discrimination tasks in which visual inputs were the same, and only the effector behaviors for reporting perceived motion directions were different (smooth pursuit, saccadic eye movement, or button press). We used multivariate pattern analysis to compare the EEG activities for identical sensory inputs under different effector behaviors. The EEG activity patterns for the identical sensory stimulus before any motor action varied across the effector behavior conditions, and the choice of motor effectors modulated the neural direction discrimination differently. We suggest that the motor-effector dependent modulation of EEG direction discrimination might be caused by effector-specific motor planning or preparation signals because it did not have functional relevance to behavioral direction discriminability.

Multivariate EEG activity reflects the Bayesian integration and the integrated Galilean relative velocity of sensory motion during sensorimotor behavior.

Humans integrate multiple sources of information for action-taking, using the reliability of each source to allocate weight to the data. This reliability-weighted information integration is a crucial property of Bayesian inference. In this study, participants were asked to perform a smooth pursuit eye movement task in which we independently manipulated the reliability of pursuit target motion and the direction-of-motion cue. Through an analysis of pursuit initiation and multivariate electroencephalography activity, we found neural and behavioral evidence of Bayesian information integration: more attraction toward the cue direction was generated when the target motion was weak and unreliable. Furthermore, using mathematical modeling, we found that the neural signature of Bayesian information integration had extra-retinal origins, although most of the multivariate electroencephalography activity patterns during pursuit were best correlated with the retinal velocity errors accumulated over time. Our results demonstrated neural implementation of Bayesian inference in human oculomotor behavior.

Generalized self-calibrating simultaneous multi-slice MR image reconstruction from 3D Fourier encoding perspective.

This work introduces a novel, k-space based one-step solution for simultaneous multi-slice MR image reconstruction from 3D Fourier encoding perspective. With undersampled SMS imaging, image reconstruction suffers from both inter-slice leakages and in-plane aliasing artifacts. Aliasing separation becomes further challenging in the presence of discrepancies between calibration and imaging. To address them, in this work a measured SMS 3D k-space with additional calibrating signals is decomposed into SMS imaging and self-calibrating data sets. Extended controlled aliasing is performed by upsampling the measured data in the kz-direction. A slice-specific null space operator is then learned using extended self-calibration exploiting target slices and additional in-plane-shifted images. Inter-slice leakages and in-plane aliasing artifacts are jointly resolved in a single step by solving a constrained optimization problem in which null space reconstruction consistency is balanced with a Hankel-structured low rank prior while data fidelity in 3D Fourier space is enforced. Retrospective and prospective studies are performed to validate the effectiveness of the proposed method in various regions including knee and L-spine.

Automatic compensation enhances the orientation perception in chronic astigmatism.

Astigmatism is a prevalent optical problem in which two or more focal points blur the retinal image at a particular meridian. Although many features of astigmatic vision, including orientation perception, are impaired at the retinal image level, the visual system appears to partly restore perceptual impairment after an extended period of astigmatism. However, the mechanism of orientation perception restoration in chronic astigmatism has not yet been clarified. We investigated the notable reduction of perceptual error in chronic astigmatism by comparing the orientation perception of a chronic astigmatism group with the perception of a normal-vision group, in which astigmatism was transiently induced. We found that orientation perception in the chronic group was more accurate than in the normal vision group. Interestingly, the reduction of perceptual errors was automatic; it remained even after the optical refractive errors were fully corrected, and the orientation perception was much more stable across different orientations, despite the uneven noise levels of the retinal images across meridians. We provide here a mechanistic explanation for how the compensation of astigmatic orientation perception occurred, using neural adaptation to the biased distribution of orientations.

The Representational Dynamics of Sequential Perceptual Averaging.

It is clear that humans can extract statistical information from streams of visual input, yet how our brain processes sequential images into the abstract representation of the mean feature value remains poorly explored. Using multivariate pattern analyses of electroencephalography recorded while human observers viewed 10 sequentially presented Gabors of different orientations to estimate their mean orientation at the end, we investigated sequential averaging mechanism by tracking the quality of individual and mean orientation as a function of sequential position. Critically, we varied the sequential variance of Gabor orientations to understand the neural basis of perceptual mean errors occurring during a sequential averaging task. We found that the mean-orientation representation emerged at specific delays from each sequential stimulus onset and became increasingly accurate as additional Gabors were viewed. Especially in frontocentral electrodes, the neural representation of mean orientation improved more rapidly and to a greater degree in less volatile environments, whereas individual orientation information was encoded precisely regardless of environmental volatility. The computational analysis of behavioral data also showed that perceptual mean errors arise from the cumulative construction of the mean orientation rather than the low-level encoding of individual stimulus orientation. Thus, our findings provide neural mechanisms to differentially accumulate increasingly abstract features from a concrete piece of information across the cortical hierarchy depending on environmental volatility.SIGNIFICANCE STATEMENT The visual system extracts behaviorally relevant summary statistical representation by exploiting statistical regularity of the visual stream over time. However, how the neural representation of the abstract mean feature value develops in a temporally changing environment remains poorly identified. Here, we directly recover the mean orientation information of sequentially delivered Gabor stimuli with different orientations as a function of their positions in time. The mean orientation representation, which is regularly updated, becomes increasingly accurate with increasing sequential position especially in the frontocentral region. Further, perceptual mean errors arise from the cumulative process rather than the low-level stimulus encoding. Overall, our study reveals a role of higher cortical areas in integrating stimulus-specific information into increasingly abstract task-oriented information.

Induced astigmatism biases the orientation information represented in multivariate electroencephalogram activities.

A small physical change in the eye influences the entire neural information process along the visual pathway, causing perceptual errors and behavioral changes. Astigmatism, a refractive error in which visual images do not evenly focus on the retina, modulates visual perception, and the accompanying neural processes in the brain. However, studies on the neural representation of visual stimuli in astigmatism are scarce. We investigated the relationship between retinal input distortions and neural bias in astigmatism and how modulated neural information causes a perceptual error. We induced astigmatism by placing a cylindrical lens on the dominant eye of human participants, while they reported the orientations of the presented Gabor patches. The simultaneously recorded electroencephalogram activity revealed that stimulus orientation information estimated from the multivariate electroencephalogram activity was biased away from the neural representation of the astigmatic axis and predictive of behavioral bias. The representational neural dynamics underlying the perceptual error revealed the temporal state transition; it was transiently dynamic and unstable (approximately 350 ms from stimulus onset) that soon stabilized. The biased stimulus orientation information represented by the spatially distributed electroencephalogram activity mediated the distorted retinal images and biased orientation perception in induced astigmatism.

Extracting single-trial neural interaction using latent dynamical systems model.

In systems neuroscience, advances in simultaneous recording technology have helped reveal the population dynamics that underlie the complex neural correlates of animal behavior and cognitive processes. To investigate these correlates, neural interactions are typically abstracted from spike trains of pairs of neurons accumulated over the course of many trials. However, the resultant averaged values do not lead to understanding of neural computation in which the responses of populations are highly variable even under identical external conditions. Accordingly, neural interactions within the population also show strong fluctuations. In the present study, we introduce an analysis method reflecting the temporal variation of neural interactions, in which cross-correlograms on rate estimates are applied via a latent dynamical systems model. Using this method, we were able to predict time-varying neural interactions within a single trial. In addition, the pairwise connections estimated in our analysis increased along behavioral epochs among neurons categorized within similar functional groups. Thus, our analysis method revealed that neurons in the same groups communicate more as the population gets involved in the assigned task. We also showed that the characteristics of neural interaction from our model differ from the results of a typical model employing cross-correlation coefficients. This suggests that our model can extract nonoverlapping information about network topology, unlike the typical model.

Rapid three-dimensional steady-state chemical exchange saturation transfer magnetic resonance imaging.

PURPOSE: To make clinically feasible whole-brain chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) by enhancing imaging efficiency. METHODS: A novel, whole-brain three-dimensional (3D) steady-state CEST MRI method was introduced by utilizing a time-efficient, fat-suppressed excitation followed by rapid, segmented 3D echo-planar-imaging with incoherent undersampling in k-ω space. Missing signals and CEST-specific spectral images were then jointly estimated directly from incomplete measurements using model-based reconstruction and robust spectral analysis. In vivo studies were performed at 3T both retrospectively (using a fully sampled reference) and prospectively to validate the effectiveness of the proposed method in patients with brain cancer. RESULTS: In retrospective studies, the proposed method exhibits superior accuracies to existing methods in estimating images, z-spectra, and APTw relative to the reference. In prospective patient studies, compared with existing methods, the proposed method is statistically significantly different in contrast-to-noise ratio of the APTw contrast between tumor and normal appearing white matter (NAWM) and amide proton transfer weighted contrast (p < 0.05) while not being significantly different in signal-to-noise ratio in an NAWM region. CONCLUSIONS: We successfully demonstrated that it is feasible to perform whole-brain CEST MRI roughly within 4 minutes for patients with brain cancer. It is expected that the proposed method widens clinical utilities of CEST MRI.

Strategies for rapid reconstruction in 3D MRI with radial data acquisition: 3D fast Fourier transform vs two-step 2D filtered back-projection.

For 3D radial data reconstruction in magnetic resonance imaging (MRI), fast Fourier transform via gridding (gFFT) is widely used for its fast processing and flexibility. In comparison, conventional 3D filtered back projection (cFBP), while more robust against common radial k-space centering errors, suffers from long computation times and is less frequently used. In this study, we revisit another back-projection reconstruction strategy, namely two-step 2D filtered back-projection (tsFBP), as an alternative 3D radial MRI reconstruction method that combines computational efficiency and certain error tolerance. In order to compare the three methods (gFFT, cFBP, and tsFBP), theoretical analysis was performed to evaluate the number of computational steps involved in each method. Actual reconstruction times were also measured and compared using 3D radial-MRI data of a phantom and a human brain. Additionally, the sensitivity of tsFBP to artifacts caused by radial k-space centering errors was compared with the other methods. Compared to cFBP, tsFBP dramatically improved the reconstruction speed while retaining the benefit of tolerance to the radial k-space errors. Our study therefore suggests that tsFBP can be a promising alternative to the conventional back projection method for 3D radial MRI reconstruction.

BOLD fMRI and hemodynamic responses to somatosensory stimulation in anesthetized mice: spontaneous breathing vs. mechanical ventilation.

Mouse functional MRI (fMRI) has been of great interest due to the abundance of transgenic models. Due to a mouse's small size, spontaneous breathing has often been used. Because the vascular physiology affecting fMRI might not be controlled normally, its effects on functional responses were investigated with optical intrinsic signal (OIS) imaging and 9.4 T BOLD fMRI. Three conditions were tested in C57BL/6 mice: spontaneous breathing under ketamine and xylazine anesthesia (KX), mechanical ventilation under KX, and mechanical ventilation under isoflurane. Spontaneous breathing under KX induced an average pCO2 of 83 mmHg, whereas a mechanical ventilation condition achieved a pCO2 of 37-41 mmHg within a physiological range. The baseline diameter of arterial and venous vessels was only 7%-9% larger with spontaneous breathing than with mechanical ventilation under KX, but it was much smaller than that in normocapnic isoflurane-anesthetized mice. Three major functional studies were performed. First, CBV-weighted OIS and arterial dilations to 4-second forepaw stimulation were rapid and larger at normocapnia than hypercapnia under KX, but very small under isoflurane. Second, CBV-weighted OIS and arterial dilations by vasodilator acetazolamide were measured for investigating vascular reactivity and were larger in the normocapnic condition than in the hypercapnic condition under KX. Third, evoked OIS and BOLD fMRI responses in the contralateral mouse somatosensory cortex to 20-second forepaw stimulation were faster and larger in the mechanical ventilation than spontaneous breathing. BOLD fMRI peaked at the end of the 20-second stimulation under hypercapnic spontaneous breathing, and at ~9 seconds under mechanical ventilation. The peak amplitude of BOLD fMRI was 2.2% at hypercapnia and ~3.4% at normocapnia. Overall, spontaneous breathing induces sluggish reduced hemodynamic and fMRI responses, but it is still viable for KX anesthesia due to its simplicity, noninvasiveness, and well-localized BOLD activity in the somatosensory cortex.

Experimental setup for bulk susceptibility effect-minimized, multi-orientation MRI of ex vivo tissue samples.

PURPOSE: Many conventional ex vivo magnetic resonance imaging (MRI) setups utilize cylindrical or other nonspherical tissue containers which can cause static field (B0 ) inhomogeneity affecting the accuracy of the measurements in an orientation-dependent manner. In this work we demonstrate an experimental method to obtain MRI of ex vivo tissue samples held in a spherical container in order to minimize bulk susceptibility-induced B0 inhomogeneity in arbitrary orientations. METHODS: B0 inhomogeneity caused by tissue-air susceptibility mismatch can be theoretically eliminated if the surface of susceptibility discontinuity is spherical. This situation can be approximated by putting a tissue sample in a spherical shell filled with materials with tissue-like magnetic susceptibility. We achieved this on an intact monkey brain by (a) holding the brain with a three-dimensional (3D)-printed holder with tissue-like (within 0.5 ppm) susceptibility, and (b) enclosing the brain and the holder in an acrylic spherical shell filled with diamagnetic liquid. Furthermore, the sphere and the radio-frequency coil for MRI were mounted on a 3D-printed frame designed to reduce B0 inhomogeneity contributions. The sphere could be rotated freely without disturbing the RF coil to facilitate multi-orientation imaging. We verified our setup by mapping B0 in the monkey brain at 13 different orientations in a human 7T scanner, and measuring orientation-dependent R 2 ∗ relaxation rates in the white and gray matters of the brain. The results were then compared with a setup where the brain was held inside a cylindrical container. RESULTS: In all orientations, the B0 standard deviation in the brain in the spherical setup (converted to Larmor frequency offset) was less than about 10 Hz. This corresponds to two-sigma deviation of B0 of <0.07 ppm. The B0 gradient was <9 Hz/mm in 95 % of the brain voxels in all orientations. In high-resolution imaging with e.g. voxel size <0.4 mm, this corresponds to voxel line broadening of <4 Hz (0.013 ppm). R 2 ∗ in the corpus callosum showed distinctly different orientation dependence compared to the gray matter. The B0 uniformity and R 2 ∗ reliability were much reduced in the cylindrical container setup. CONCLUSIONS: We have demonstrated an experimental method to effectively minimize bulk susceptibility-induced B0 perturbation in multi-orientation ex vivo MRI. The method promises to benefit a range of tissue orientation-dependent MR property studies.

Integration of locomotion and auditory signals in the mouse inferior colliculus.

The inferior colliculus (IC) is the major midbrain auditory integration center, where virtually all ascending auditory inputs converge. Although the IC has been extensively studied for sound processing, little is known about the neural activity of the IC in moving subjects, as frequently happens in natural hearing conditions. Here, by recording neural activity in walking mice, we show that the activity of IC neurons is strongly modulated by locomotion, even in the absence of sound stimuli. Similar modulation was also found in hearing-impaired mice, demonstrating that IC neurons receive non-auditory, locomotion-related neural signals. Sound-evoked activity was attenuated during locomotion, and this attenuation increased frequency selectivity across the neuronal population, while maintaining preferred frequencies. Our results suggest that during behavior, integrating movement-related and auditory information is an essential aspect of sound processing in the IC.

Model-Based Chemical Exchange Saturation Transfer MRI for Robust z-Spectrum Analysis.

This paper introduces a novel, model-based chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI), in which asymmetric spectra of interest are directly estimated from complete or incomplete measurements by incorporating subspace-based spectral signal decomposition into the measurement model of CEST MRI for a robust z-spectrum analysis. Spectral signals are decomposed into symmetric and asymmetric components. The symmetric component, which varies smoothly, is delineated by the linear superposition of a finite set of vectors in a basis trained from the simulated (Lorentzian) signal vectors augmented with data-driven signal vectors, while the asymmetric component is to be inherently lower than or equal to zero due to saturation transfer phenomena. Spectral decomposition is performed directly on the measured spectral data by solving a constrained optimization problem that employs the linearized spectral decomposition model for the symmetric component and the weighted Frobenius norm regularization for the asymmetric component while utilizing additional spatial sparsity and low-rank priors. The simulations and in vivo experiments were performed to demonstrate the feasibility of the proposed method as a reliable molecular MRI.

The Neural Basis for Response Latency in a Sensory-Motor Behavior.

We seek a neural circuit explanation for sensory-motor reaction times. In the smooth eye movement region of the frontal eye fields (FEFSEM), the latencies of pairs of neurons show trial-by-trial correlations that cause trial-by-trial correlations in neural and behavioral latency. These correlations can account for two-third of the observed variation in behavioral latency. The amplitude of preparatory activity also could contribute, but the responses of many FEFSEM neurons fail to support predictions of the traditional "ramp-to-threshold" model. As a correlate of neural processing that determines reaction time, the local field potential in FEFSEM includes a brief wave in the 5-15-Hz frequency range that precedes pursuit initiation and whose phase is correlated with the latency of pursuit in individual trials. We suggest that the latency of the incoming visual motion signals combines with the state of preparatory activity to determine the latency of the transient response that controls eye movement. IMPACT STATEMENT: The motor cortex for smooth pursuit eye movements contributes to sensory-motor reaction time through the amplitude of preparatory activity and the latency of transient, visually driven responses.

Model-Based High-Definition Dynamic Contrast Enhanced MRI for Concurrent Estimation of Perfusion and Microvascular Permeability.

This work introduces a model-based, high-definition dynamic contrast enhanced (DCE) MRI for concurrent estimation of perfusion and microvascular permeability over the whole brain. A time series of reference-subtracted signals is decomposed into one component that reflects main contrast dynamics and the other one that includes residual contrast agents (CA) and background signals. The former is described by linear superposition of a finite number of basic vectors trained from an augmented set of data that consists of tracer-kinetic model driven signal vectors and patient-specific measured ones. Contrast dynamics is estimated by solving a constrained optimization problem that incorporates the linearized signal decomposition into the measurement model of DCE MRI and then combining the main component with the background-suppressed, residual CA signals. To the best of our knowledge, this is the first work that prospectively enables rapid temporal sampling with 1.5 s (3 ∼ 4 times higher than clinical routines) while simultaneously achieving high isotropic spatial resolution with 1.0 mm3 (4 ∼ 6 times higher than routines), enhancing estimation of both patient-specific inputs and outputs for quantification of microvascular functions. Simulations and experiments are performed to demonstrate the effectiveness of the proposed method in patients with brain cancer.

Motion direction representation in multivariate electroencephalography activity for smooth pursuit eye movements.

Visually-guided smooth pursuit eye movements are composed of initial open-loop and later steady-state periods. Feedforward sensory information dominates the motor behavior during the open-loop pursuit, and a more complex feedback loop regulates the steady-state pursuit. To understand the neural representations of motion direction during open-loop and steady-state smooth pursuits, we recorded electroencephalography (EEG) responses from human observers while they tracked random-dot kinematograms as pursuit targets. We estimated population direction tuning curves from multivariate EEG activity using an inverted encoding model. We found significant direction tuning curves as early as about 60 ms from stimulus onset. Direction tuning responses were generalized to later times during the open-loop smooth pursuit, but they became more dynamic during the later steady-state pursuit. The encoding quality of retinal motion direction information estimated from the early direction tuning curves was predictive of trial-by-trial variation in initial pursuit directions. These results suggest that the movement directions of open-loop smooth pursuit are guided by the representation of the retinal motion present in the multivariate EEG activity.