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Abstract Background Vagus nerve stimulation (VNS) is a FDA approved therapy regularly used to treat a variety of neurological disorders that impact the central nervous system (CNS) including epilepsy and stroke. Putatively, the therapeutic efficacy of VNS results from its action on neuromodulatory centers via projections of the vagus nerve to the solitary tract nucleus. Currently, there is not an established large animal model that facilitates detailed mechanistic studies exploring how VNS impacts the function of the CNS, especially during complex behaviors requiring motor action and decision making. Methods We describe the anatomical organization, surgical methodology to implant VNS electrodes on the left gagus nerve and characterization of target engagement/neural interface properties in a non-human primate (NHP) model of VNS that permits chronic stimulation over long periods of time. Furthermore, we describe the results of pilot experiments in a small number of NHPs to demonstrate how this preparation might be used in an animal model capable of performing complex motor and decision making tasks. Results VNS electrode impedance remained constant over months suggesting a stable interface. VNS elicited robust activation of the vagus nerve which resulted in decreases of respiration rate and/or partial pressure of carbon dioxide in expired air, but not changes in heart rate in both awake and anesthetized NHPs. Conclusions We anticipate that this preparation will be very useful to study the mechanisms underlying the effects of VNS for the treatment of conditions such as epilepsy and depression, for which VNS is extensively used, as well as for the study of the neurobiological basis underlying higher order functions such as learning and memory.

An increasing number of research teams are investigating the efficacy of brain-computer interface (BCI)-mediated interventions for promoting motor recovery following stroke. A growing body of evidence suggests that of the various BCI designs, most effective are those that deliver functional electrical stimulation (FES) of upper extremity (UE) muscles contingent on movement intent. More specifically, BCI-FES interventions utilize algorithms that isolate motor signals—user-generated intent-to-move neural activity recorded from cerebral cortical motor areas—to drive electrical stimulation of individual muscles or muscle synergies. BCI-FES interventions aim to recover sensorimotor function of an impaired extremity by facilitating and/or inducing long-term motor learning-related neuroplastic changes in appropriate control circuitry. We developed a non-invasive, electroencephalogram (EEG)-based BCI-FES system that delivers closed-loop neural activity-triggered electrical stimulation of targeted distal muscles while providing the user with multimodal sensory feedback. This BCI-FES system consists of three components: (1) EEG acquisition and signal processing to extract real-time volitional and task-dependent neural command signals from cerebral cortical motor areas, (2) FES of muscles of the impaired hand contingent on the motor cortical neural command signals, and (3) multimodal sensory feedback associated with performance of the behavioral task, including visual information, linked activation of somatosensory afferents through intact sensorimotor circuits, and electro-tactile stimulation of the tongue. In this report, we describe device parameters and intervention protocols of our BCI-FES system which, combined with standard physical rehabilitation approaches, has proven efficacious in treating UE motor impairment in stroke survivors, regardless of level of impairment and chronicity.

Introduction: Vagus nerve stimulation (VNS) is an FDA-approved neuromodulatory treatment used in the clinic today for epilepsy, depression, and cluster headaches. Moreover, evidence in the literature has led to a growing list of possible clinical indications, with several small clinical trials applying VNS to treat conditions ranging from neurodegenerative diseases to arthritis, anxiety disorders, and obesity. Despite the growing list of therapeutic applications, the fundamental mechanisms by which VNS achieves its beneficial effects are poorly understood. In parallel, the glymphatic and meningeal lymphatic systems have recently been described as methods by which the brain maintains a healthy homeostasis and removes waste without a traditionally defined lymphatic system. In particular, the glymphatic system relates to the interchange of cerebrospinal fluid (CSF) and interstitial fluid (ISF) whose net effect is to wash through the brain parenchyma removing metabolic waste products and misfolded proteins. Objective/Hypothesis: As VNS has well-documented effects on many of the pathways recently linked to the clearance systems of the brain, we hypothesized that VNS could increase CSF penetrance in the brain. Methods: We injected a low molecular weight lysine-fixable fluorescent tracer (TxRed-3kD) into the CSF system of mice with a cervical vagus nerve cuff implant and measured the amount of CSF penetrance following an application of a clinically-derived VNS paradigm (30 Hz, 10% duty cycle). Results: We found that the clinical VNS group showed a significant increase in CSF tracer penetrance as compared to the naïve control and sham groups. Conclusion: (s): This study demonstrates that VNS therapeutic strategies already being applied in the clinic today may induce intended effects and/or unwanted side effects by altering CSF/ISF exchange in the brain. This may have broad ranging implications in the treatment of various CNS pathologies.

The creation of protected areas is an important public policy strategy for protecting species, as mentioned in the Aichi targets. This paper formulates spatial integer programming (set covering) models to protect both rare species (arbitrarily defined here as species breeding in 1% or less of the territory) and common species. Spatial constraints are used to form buffer zones around core areas that protect rare species, and cost-efficient corridors linking these buffered cores are then designed. The models are applied on a portion of the State of Oregon and results are evaluated in light of the expected United Nations post-2020 targets for area-based conservation measures. It is estimated that such results aimed at covering all species and enhancing protection of at-risk species seem locally consistent with the global biodiversity objectives for 2030.

Background: Placement of the clinical vagus nerve stimulating cuff is a standard surgical procedure based on anatomical landmarks, with limited patient specificity in terms of fascicular organization or vagal anatomy. As such, the therapeutic effects are generally limited by unwanted side effects of neck muscle contractions, demonstrated by previous studies to result from stimulation of (1) motor fibers near the cuff in the superior laryngeal and (2) motor fibers within the cuff projecting to the recurrent laryngeal.Objective: Conventional non-invasive ultrasound, where the transducer is placed on the surface of the skin, has been previously used to visualize the vagus with respect to other landmarks such as the carotid and internal jugular vein. However, it lacks sufficient resolution to provide details about the vagus fascicular organization, or detail about smaller neural structures such as the recurrent and superior laryngeal branch responsible for therapy limiting side effects. Here, we characterize the use of ultrasound with the transducer placed in the surgical pocket to improve resolution without adding significant additional risk to the surgical procedure in the pig model.Methods: Ultrasound images were obtained from a point of known functional organization at the nodose ganglia to the point of placement of stimulating electrodes within the surgical window. Naïve volunteers with minimal training were then asked to use these ultrasound videos to trace afferent groupings of fascicles from the nodose to their location within the surgical window where a stimulating cuff would normally be placed. Volunteers were asked to select a location for epineural electrode placement away from the fascicles containing efferent motor nerves responsible for therapy limiting side effects. 2-D and 3-D reconstructions of the ultrasound were directly compared to post-mortem histology in the same animals.Results: High-resolution ultrasound from the surgical pocket enabled 2-D and 3-D reconstruction of the cervical vagus and surrounding structures that accurately depicted the functional vagotopy of the pig vagus nerve as confirmed via histology. Although resolution was not sufficient to match specific fascicles between ultrasound and histology 1 to 1, it was sufficient to trace fascicle groupings from a point of known functional organization at the nodose ganglia to their locations within the surgical window at stimulating electrode placement. Naïve volunteers were able place an electrode proximal to the sensory afferent grouping of fascicles and away from the motor nerve efferent grouping of fascicles in each subject (n = 3).Conclusion: The surgical pocket itself provides a unique opportunity to obtain higher resolution ultrasound images of neural targets responsible for intended therapeutic effect and limiting off-target effects. We demonstrate the increase in resolution is sufficient to aid patient-specific electrode placement to optimize outcomes. This simple technique could be easily adopted for multiple neuromodulation targets to better understand how patient specific anatomy impacts functional outcomes.

Stroke is a leading cause of acquired long-term upper extremity motor disability. Current standard of care trajectories fail to deliver sufficient motor rehabilitation to stroke survivors. Recent research suggests that use of brain-computer interface (BCI) devices improves motor function in stroke survivors, regardless of stroke severity and chronicity, and may induce and/or facilitate neuroplastic changes associated with motor rehabilitation. The present sub analyses of ongoing crossover-controlled trial NCT02098265 examine first whether, during movements of the affected hand compared to rest, ipsilesional Mu rhythm desynchronization of cerebral cortical sensorimotor areas [Brodmann’s areas (BA) 1-7] is localized and tracks with changes in grip force strength. Secondly, we test the hypothesis that BCI intervention results in changes in frequency-specific directional flow of information transmission (direct path functional connectivity) in BA 1-7 by measuring changes in isolated effective coherence (iCoh) between cerebral cortical sensorimotor areas thought to relate to electrophysiological signatures of motor actions and motor learning. A sample of 16 stroke survivors with right hemisphere lesions (left hand motor impairment), received a maximum of 18–30 h of BCI intervention. Electroencephalograms were recorded during intervention sessions while outcome measures of motor function and capacity were assessed at baseline and completion of intervention. Greater desynchronization of Mu rhythm, during movements of the impaired hand compared to rest, were primarily localized to ipsilesional sensorimotor cortices (BA 1-7). In addition, increased Mu desynchronization in the ipsilesional primary motor cortex, Post vs. Pre BCI intervention, correlated significantly with improvements in hand function as assessed by grip force measurements. Moreover, the results show a significant change in the direction of causal information flow, as measured by iCoh, toward the ipsilesional motor (BA 4) and ipsilesional premotor cortices (BA 6) during BCI intervention. Significant iCoh increases from ipsilesional BA 4 to ipsilesional BA 6 were observed in both Mu [8–12 Hz] and Beta [18–26 Hz] frequency ranges. In summary, the present results are indicative of improvements in motor capacity and behavior, and they are consistent with the view that BCI-FES intervention improves functional motor capacity of the ipsilesional hemisphere and the impaired hand.

Background: The auricular branch of the vagus nerve runs superficially, which makes it a favorable target for non-invasive stimulation techniques to modulate vagal activity. For this reason, there have been many early-stage clinical trials on a diverse range of conditions. These trials often report conflicting results for the same indication.Methods: Using the Cochrane Risk of Bias tool we conducted a systematic review of auricular vagus nerve stimulation (aVNS) randomized controlled trials (RCTs) to identify the factors that led to these conflicting results. The majority of aVNS studies were assessed as having “some” or “high” risk of bias, which makes it difficult to interpret their results in a broader context.Results: There is evidence of a modest decrease in heart rate during higher stimulation dosages, sometimes at above the level of sensory discomfort. Findings on heart rate variability conflict between studies and are hindered by trial design, including inappropriate washout periods, and multiple methods used to quantify heart rate variability. There is early-stage evidence to suggest aVNS may reduce circulating levels and endotoxin-induced levels of inflammatory markers. Studies on epilepsy reached primary endpoints similar to previous RCTs testing implantable vagus nerve stimulation therapy. Preliminary evidence shows that aVNS ameliorated pathological pain but not evoked pain.Discussion: Based on results of the Cochrane analysis we list common improvements for the reporting of results, which can be implemented immediately to improve the quality of evidence. In the long term, existing data from aVNS studies and salient lessons from drug development highlight the need for direct measures of local neural target engagement. Direct measures of neural activity around the electrode will provide data for the optimization of electrode design, placement, and stimulation waveform parameters to improve on-target engagement and minimize off-target activation. Furthermore, direct measures of target engagement, along with consistent evaluation of blinding success, must be used to improve the design of controls—a major source of concern identified in the Cochrane analysis. The need for direct measures of neural target engagement and consistent evaluation of blinding success is applicable to the development of other paresthesia-inducing neuromodulation therapies and their control designs.

Sieve electrodes stand poised to deliver the selectivity required for driving advanced prosthetics but are considered inherently invasive and lack the stability required for a chronic solution. This proof of concept experiment investigates the potential for the housing and engagement of a sieve electrode within the medullary canal as part of an osseointegrated neural interface (ONI) for greater selectivity toward improving prosthetic control. The working hypotheses are that (A) the addition of a sieve interface to a cuff electrode housed within the medullary canal of the femur as part of an ONI would be capable of measuring efferent and afferent compound nerve action potentials (CNAPs) through a greater number of channels; (B) that signaling improves over time; and (C) that stimulation at this interface generates measurable cortical somatosensory evoked potentials through a greater number of channels. The modified ONI was tested in a rabbit (n = 1) amputation model over 12 weeks, comparing the sieve component to the cuff, and subsequently compared to historical data. Efferent CNAPs were successfully recorded from the sieve demonstrating physiological improvements in CNAPs between weeks 3 and 5, and somatosensory cortical responses recorded at 12 weeks postoperatively. This demonstrates that sieve electrodes can be housed and function within the medullary canal, demonstrated by improved nerve engagement and distinct cortical sensory feedback. This data presents the conceptual framework for housing more sophisticated sieve electrodes in bone as part of an ONI for improving selectivity with percutaneous connectivity toward improved prosthetic control.

Automated computational analysis techniques utilizing machine learning have been demonstrated to be able to extract more data from different imaging modalities compared to traditional analysis techniques. One new approach is to use machine learning techniques to existing multiphoton imaging modalities to better interpret intrinsically fluorescent cellular signals to characterize different cell types. Fluorescence Lifetime Imaging Microscopy (FLIM) is a high-resolution quantitative imaging tool that can detect metabolic cellular signatures based on the lifetime variations of intrinsically fluorescent metabolic co-factors such as nicotinamide adenine dinucleotide [NAD(P)H]. NAD(P)H lifetime-based discrimination techniques have previously been used to develop metabolic cell signatures for diverse cell types including immune cells such as macrophages. However, FLIM could be even more effective in characterizing cell types if machine learning was used to classify cells by utilizing FLIM parameters for classification. Here, we demonstrate the potential for FLIM-based, label-free NAD(P)H imaging to distinguish different cell types using Artificial Neural Network (ANN)-based machine learning. For our biological use case, we used the challenge of differentiating microglia from other glia cell types in the brain. Microglia are the resident macrophages of the brain and spinal cord and play a critical role in maintaining the neural environment and responding to injury. Microglia are challenging to identify as most fluorescent labeling approaches cross-react with other immune cell types, are often insensitive to activation state, and require the use of multiple specialized antibody labels. Furthermore, the use of these extrinsic antibody labels prevents application in in vivo animal models and possible future clinical adaptations such as neurodegenerative pathologies. With the ANN-based NAD(P)H FLIM analysis approach, we found that microglia in cell culture mixed with other glial cells can be identified with more than 0.9 True Positive Rate (TPR). We also extended our approach to identify microglia in fixed brain tissue with a TPR of 0.79. In both cases the False Discovery Rate was around 30%. This method can be further extended to potentially study and better understand microglia’s role in neurodegenerative disease with improved detection accuracy.

Advances in neural engineering have brought about a number of implantable devices for improved brain stimulation and recording. Unfortunately, many of these micro-implants have not been adopted due to issues of signal loss, deterioration, and host response to the device. While glial scar characterization is critical to better understand the mechanisms that affect device functionality or tissue viability, analysis is frequently hindered by immunohistochemical tissue processing methods that result in device shattering and tissue tearing artifacts. Devices are commonly removed prior to sectioning, which can itself disturb the quality of the study. In this methods implementation study, we use the label free, optical sectioning method of second harmonic generation (SHG) to examine brain slices of various implanted intracortical electrodes and demonstrate collagen fiber distribution not found in normal brain tissue. SHG can easily be used in conjunction with multiphoton microscopy to allow direct intrinsic visualization of collagen-containing glial scars on the surface of cortically implanted electrode probes without imposing the physical strain of tissue sectioning methods required for other high resolution light microscopy modalities. Identification and future measurements of these collagen fibers may be useful in predicting host immune response and device signal fidelity.

Abstract To screen the complex central nervous system (CNS) injury responses, we created a quadruple-labelled ‘PrismPlus’ mouse line with a genetically encoded distinct fluorescent tag in oligodendrocytes, microglia, neurons, and astrocytes. Cx3cr1-gfp and Prism mice originally developed by Jung et al., 2000 and Dougherty et al., 2012, respectively, were cross-bred. First, we confirmed the presence of fluorophores in appropriate cell types in PrismPlus mice. PrismPlus mice were then used to examine the cellular responses to brain implanted micro-devices. We observed an increase in microglial response at earlier time points as compared to 4 weeks, a progressive astrocytic response, and fewer neurons at the vicinity of an implanted device. These results are similar to what has been described in literature using other rodent strains, previously attainable only through time-consuming and variable immunohistochemistry methods. Finally, we demonstrate the compatibility of PrismPlus brain tissue with CLARITY, an advanced tissue clearing technique, opening the door to future thick tissue imaging studies. This report confirms PrismPlus transgenic fluorescence and highlights the utility of these mice to study CNS injuries. The work herein seeks to establish a novel transgenic mouse line to improve experimental scope, consistency, and efficiency for CNS researchers.

The studies described in this paper for the first time characterize the acute and chronic performance of optically transparent thin-film micro-electrocorticography (μECoG) grids implanted on a thinned skull as both an electrophysiological complement to existing thinned skull preparation for optical recordings/manipulations, and a less invasive alternative to epidural or subdurally placed μECoG arrays. In a longitudinal chronic study, μECoG grids placed on top of a thinned skull maintain impedances comparable to epidurally placed μECoG grids that are stable for periods of at least 1 month. Optogenetic activation of cortex is also reliably demonstrated through the optically transparent μECoG grids acutely placed on the thinned skull. Finally, spatially distinct electrophysiological recordings were evident on μECoG electrodes placed on a thinned skull separated by 500–750 μm, as assessed by stimulation evoked responses using optogenetic activation of cortex as well as invasive and epidermal stimulation of the sciatic and median nerve at chronic time points. Neural signals were collected through a thinned skull in mice and rats, demonstrating potential utility in neuroscience research applications such as in vivo imaging and optogenetics.

Loss of motor function is a common deficit following stroke insult and often manifests as persistent upper extremity (UE) disability which can affect a survivor’s ability to participate in activities of daily living. Recent research suggests the use of brain–computer interface (BCI) devices might improve UE function in stroke survivors at various times since stroke. This randomized crossover-controlled trial examines whether intervention with this BCI device design attenuates the effects of hemiparesis, encourages reorganization of motor related brain signals (EEG measured sensorimotor rhythm desynchronization), and improves movement, as measured by the Action Research Arm Test (ARAT). A sample of 21 stroke survivors, presenting with varied times since stroke and levels of UE impairment, received a maximum of 18–30 h of intervention with a novel electroencephalogram-based BCI-driven functional electrical stimulator (EEG-BCI-FES) device. Driven by spectral power recordings from contralateral EEG electrodes during cued attempted grasping of the hand, the user’s input to the EEG-BCI-FES device modulates horizontal movement of a virtual cursor and also facilitates concurrent stimulation of the impaired UE. Outcome measures of function and capacity were assessed at baseline, mid-therapy, and at completion of therapy while EEG was recorded only during intervention sessions. A significant increase in r-squared values [reflecting Mu rhythm (8–12 Hz) desynchronization as the result of attempted movements of the impaired hand] presented post-therapy compared to baseline. These findings suggest that intervention corresponds with greater desynchronization of Mu rhythm in the ipsilesional hemisphere during attempted movements of the impaired hand and this change is related to changes in behavior as a result of the intervention. BCI intervention may be an effective way of addressing the recovery of a stroke impaired UE and studying neuromechanical coupling with motor outputs.Clinical Trial Registration:ClinicalTrials.gov, identifier NCT02098265.

Stroke is a leading cause of persistent upper extremity (UE) motor disability in adults. Brain–computer interface (BCI) intervention has demonstrated potential as a motor rehabilitation strategy for stroke survivors. This sub-analysis of ongoing clinical trial (NCT02098265) examines rehabilitative efficacy of this BCI design and seeks to identify stroke participant characteristics associated with behavioral improvement. Stroke participants (n = 21) with UE impairment were assessed using Action Research Arm Test (ARAT) and measures of function. Nine participants completed three assessments during the experimental BCI intervention period and at 1-month follow-up. Twelve other participants first completed three assessments over a parallel time-matched control period and then crossed over into the BCI intervention condition 1-month later. Participants who realized positive change (≥1 point) in total ARAT performance of the stroke affected UE between the first and third assessments of the intervention period were dichotomized as “responders” (

The primary goal of this work was to apply data-driven machine learning regression to assess if resting state functional connectivity (rs-FC) could estimate measures of behavioral domains in stroke subjects who completed brain-computer interface (BCI) intervention for motor rehabilitation. The study cohort consisted of 20 chronic-stage stroke subjects exhibiting persistent upper-extremity motor deficits who received the intervention using a closed-loop neurofeedback BCI device. Over the course of this intervention, resting state functional MRI scans were collected at four distinct time points: namely, pre-intervention, mid-intervention, post-intervention and 1-month after completion of intervention. Behavioral assessments were administered outside the scanner at each time-point to collect objective measures such as the Action Research Arm Test, Nine-Hole Peg Test, and Barthel Index as well as subjective measures including the Stroke Impact Scale. The present analysis focused on neuroplasticity and behavioral outcomes measured across pre-intervention, post-intervention and 1-month post-intervention to study immediate and carry-over effects. Rs-FC, changes in rs-FC within the motor network and the behavioral measures at preceding stages were used as input features and behavioral measures and associated changes at succeeding stages were used as outcomes for machine-learning-based support vector regression (SVR) models. Potential clinical confounding factors such as age, gender, lesion hemisphere, and stroke severity were included as additional features in each of the regression models. Sequential forward feature selection procedure narrowed the search for important correlates. Behavioral outcomes at preceding time-points outperformed rs-FC-based correlates. Rs-FC and changes associated with bilateral primary motor areas were found to be important correlates of across several behavioral outcomes and were stable upon inclusion of clinical variables as well. NIH Stroke Scale and motor impairment severity were the most influential clinical variables. Comparatively, linear SVR models aided in evaluation of contribution of individual correlates and seed regions while non-linear SVR models achieved higher performance in prediction of behavioral outcomes.

Interventional therapy using brain-computer interface (BCI) technology has shown promise in facilitating motor recovery in stroke survivors; however, the impact of this form of intervention on functional networks outside of the motor network specifically is not well-understood. Here, we investigated resting-state functional connectivity (rs-FC) in stroke participants undergoing BCI therapy across stages, namely pre- and post-intervention, to identify discriminative functional changes using a machine learning classifier with the goal of categorizing participants into one of the two therapy stages. Twenty chronic stroke participants with persistent upper-extremity motor impairment received neuromodulatory training using a closed-loop neurofeedback BCI device, and rs-functional MRI (rs-fMRI) scans were collected at four time points: pre-, mid-, post-, and 1 month post-therapy. To evaluate the peak effects of this intervention, rs-FC was analyzed from two specific stages, namely pre- and post-therapy. In total, 236 seeds spanning both motor and non-motor regions of the brain were computed at each stage. A univariate feature selection was applied to reduce the number of features followed by a principal component-based data transformation used by a linear binary support vector machine (SVM) classifier to classify each participant into a therapy stage. The SVM classifier achieved a cross-validation accuracy of 92.5% using a leave-one-out method. Outside of the motor network, seeds from the fronto-parietal task control, default mode, subcortical, and visual networks emerged as important contributors to the classification. Furthermore, a higher number of functional changes were observed to be strengthening from the pre- to post-therapy stage than the ones weakening, both of which involved motor and non-motor regions of the brain. These findings may provide new evidence to support the potential clinical utility of BCI therapy as a form of stroke rehabilitation that not only benefits motor recovery but also facilitates recovery in other brain networks. Moreover, delineation of stronger and weaker changes may inform more optimal designs of BCI interventional therapy so as to facilitate strengthened and suppress weakened changes in the recovery process.

Summary:. Symptomatic neuroma after major extremity amputation is a challenging clinical problem for which there are many described treatment options. Neuroma excision and implantation into the medullary canal of long bones offers durability and insulation, and minimizes chronic pain. Another challenge in amputees is impaired function and an ongoing need for accessible and functional prostheses that are “bidirectional,” in that they provide both fine motor control and sensory feedback. Drawing on clinical experience with neuroma implantation into the medullary canal of long bones, the authors propose a novel neural interface whereby a terminal nerve end is redirected into the medullary canal of a nearby long bone and interfaced with an electrode array. The osseointegrated neural interface aims to exploit electrical signals from peripheral nerves to control advanced prosthetic devices for amputees. The purpose of this article is to present 2 clinical cases of nerve translocation into bone that serve as the clinical foundation of the osseointegrated neural interface as an innovative interface for prosthetic control.

Background:. Clinical outcomes after nerve injury and repair remain suboptimal. Patients may be plagued by poor functional recovery and painful neuroma at the repair site, characterized by disorganized collagen and sprouting axons. Collagen deposition during wound healing can be intrinsically imaged using second harmonic generation (SHG) microscopy. The purpose of this study was to develop a protocol for SHG imaging of nerves and to assess whether collagen alignment can be quantified after nerve repair. Methods:. Sciatic nerve transection and epineural repair was performed in male rats. The contralateral nerves were used as intra-animal controls. Ten-millimeter nerve segments were harvested and fixed onto slides. SHG images were collected using a 20× objective on a multiphoton microscope. Collagen fiber alignment was calculated using CurveAlign software. Alignment was calculated on a scale from 0 to 1, where 1 represents perfect alignment. Statistical analysis was performed using a linear mixed-effects model. Results:. Eight male rats underwent right sciatic nerve repair using 9-0 Nylon suture. There were gross variations in collagen fiber organization in the repaired nerves compared with the controls. Quantitatively, collagen fibers were more aligned in the control nerves (mean alignment 0.754, SE 0.055) than in the repairs (mean alignment 0.413, SE 0.047; P < 0.001). Conclusions:. SHG microscopy can be used to quantitate collagen after nerve repair via fiber alignment. Given that the development of neuroma likely reflects aberrant wound healing, ex vivo and/or in vivo SHG imaging may be useful for further investigation of the variables predisposing to neuroma.