Quantifying changes in local basal ganglia structural connectivity in the 6-hydroxydopamine model of Parkinson's Disease using correlational tractography.

In recent years, tractography based on diffusion magnetic resonance imaging (dMRI) has become a popular tool for studying microstructural changes resulting from brain diseases like Parkinson's Disease (PD). Quantitative anisotropy (QA) is a parameter that is used in deterministic fiber tracking as a measure of connection between brain regions. It remains unclear, however, if microstructural changes caused by lesioning the median forebrain bundle (MFB) to create a Parkinsonian rat model can be resolved using tractography based on ex-vivo diffusion MRI. This study aims to fill this gap and enable future mechanistic research on structural changes of the whole brain network rodent models of PD. Specifically, it evaluated the ability of correlational tractography to detect structural changes in the MFB of 6-hydroxydopamine (6-OHDA) lesioned rats. The findings reveal that correlational tractography can detect structural changes in lesioned MFB and differentiate between the 6-OHDA and control groups. Imaging results are supported by behavioral and histological evidence demonstrating that 6-OHDA lesioned rats were indeed Parkinsonian. The results suggest that QA and correlational tractography is appropriate to examine local structural changes in rodent models of neurodegenerative disease. More broadly, we expect that similar techniques may provide insight on how disease alters structure throughout the brain, and as a tool to optimize therapeutic interventions.

Machine Learning Methods for Fluorescence Lifetime Imaging (FLIM) Based Label-Free Detection of Microglia.

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.

Microglia activation visualization via fluorescence lifetime imaging microscopy of intrinsically fluorescent metabolic cofactors.

Significance: A major obstacle to studying resident microglia has been their similarity to infiltrating immune cell types and the lack of unique protein markers for identifying the functional state. Given the role of microglia in all neural diseases and insults, accurate tools for detecting their function beyond morphologic alterations are necessary. Aims: We hypothesized that microglia would have unique metabolic fluxes in reduced nicotinamide adenine dinucleotide (NADH) that would be detectable by relative changes in fluorescence lifetime imaging microscopy (FLIM) parameters, allowing for identification of their activation status. Fluorescence lifetime of NADH has been previously demonstrated to show differences in metabolic fluxes. Approach: Here, we investigate the use of the label-free method of FLIM-based detection of the endogenous metabolic cofactor NADH to identify microglia and characterize their activation status. To test whether microglial activation would also confer a unique NADH lifetime signature, murine primary microglial cultures and adult mice were treated with lipopolysaccharide (LPS). Results: We found that LPS-induced microglia activation correlates with detected changes in NADH lifetime and its free-bound ratio. This indicates that NADH lifetime can be used to monitor microglia activation in a label-free fashion. Moreover, we found that there is an LPS dose-dependent change associated with reactive microglia lifetime fluxes, which is also replicated over time after LPS treatment. Conclusion: We have demonstrated a label-free way of monitoring microglia activation via quantifying lifetime of endogenous metabolic coenzyme NADH. Upon LPS-induced activation, there is a significant change in the fluorescence lifetime following activation. Together, these results indicate that NADH FLIM approaches can be used as a method to characterize microglia activation state, both in vitro and ex vivo.

Clinically-derived vagus nerve stimulation enhances cerebrospinal fluid penetrance.

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.

µECoG Recordings Through a Thinned Skull.

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.

Blue Light Modulates Murine Microglial Gene Expression in the Absence of Optogenetic Protein Expression.

Neural optogenetic applications over the past decade have steadily increased; however the effects of commonly used blue light paradigms on surrounding, non-optogenetic protein-expressing CNS cells are rarely considered, despite their simultaneous exposure. Here we report that blue light (450 nm) repetitively delivered in both long-duration boluses and rapid optogenetic bursts gene-specifically altered basal expression of inflammatory and neurotrophic genes in immortalized and primary murine wild type microglial cultures. In addition, blue light reduced pro-inflammatory gene expression in microglia activated with lipopolysaccharide. These results demonstrate previously unreported, off-target effects of blue light in cells not expressing optogenetic constructs. The unexpected gene modulatory effects of blue light on wild type CNS resident immune cells have novel and important implications for the neuro-optogenetic field. Further studies are needed to elucidate the molecular mechanisms and potential therapeutic utility of blue light modulation of the wild type CNS.