Acute and Chronic Effects of Hypobaric Exposure upon the Brain

Exposure to the hypobaric environment presents numerous physiological challenges to both aviators/pilots, mountain climbers and astronauts. Decompression sickness (DCS) is one of the most commonly experienced maladies and may present variably in protean fashion from mild symptoms such as the bends to severe neurological or pulmonary (i.e. chokes) symptomatology. Furthermore, exposure to extreme non-hypoxic hypobaric environments such as those experienced by our U-2 pilots, irrespective of clinical history of decompression sickness, incites development of white matter hyperintensity lesions that are diffuse in nature. Additionally, non-hypoxic hypobaric exposure also impacts white matter integrity independent of presence of white matter hyperintensities as measured by fractional anisotropy. Functionally, this translated into subtle but significantly lower neurocognitive test performance in U-2 pilots exposed to extreme non-hypoxic hypobaric conditions when compared to pilots without repeated exposure and correlated with degree of white matter lesion burden. In this chapter, we discuss results of our U-2 pilot studies along with published research on high-altitude climbers. We also review ongoing and future directional research and discuss operational implications due to our findings of non-hypoxic hypobaric exposure. Lastly, we examine the incidence of DCS in our astronaut population as well as the risks of performing extravehicular activity (EVA)

Characterizing individual differences in functional connectivity using dual-regression and seed-based approaches

A central challenge for neuroscience lies in relating inter-individual variability to the functional properties of specific brain regions. Yet, considerable variability exists in the connectivity patterns between different brain areas, potentially producing reliable group differences. Using sex differences as a motivating example, we examined two separate resting-state datasets comprising a total of 188 human participants. Both datasets were decomposed into resting-state networks (RSNs) using a probabilistic spatial independent component analysis (ICA). We estimated voxel-wise functional connectivity with these networks using a dual-regression analysis, which characterizes the participant-level spatiotemporal dynamics of each network while controlling for (via multiple regression) the influence of other networks and sources of variability. We found that males and females exhibit distinct patterns of connectivity with multiple RSNs, including both visual and auditory networks and the right frontal–parietal network. These results replicated across both datasets and were not explained by differences in head motion, data quality, brain volume, cortisol levels, or testosterone levels. Importantly, we also demonstrate that dual-regression functional connectivity is better at detecting inter-individual variability than traditional seed-based functional connectivity approaches. Our findings characterize robust—yet frequently ignored—neural differences between males and females, pointing to the necessity of controlling for sex in neuroscience studies of individual differences. Moreover, our results highlight the importance of employing network-based models to study variability in functional connectivity

Atypical Myasthenia Gravis Presentation with Limb-Girdle Weakness

Myasthenia Gravis is a disorder characterized by autoantibodies targeting different proteins across the neuromuscular junction. The typical presentation of Myasthenia Gravis involves oculobulbar weakness, classically ptosis that may or may not be symmetric. Patients may also present with a more dramatic presentation of generalized weakness or even in myasthenic crisis requiring respiratory support for oxygenation. While these are the common presentations, our patient, a 63 year old male, presented with an atypical presentation of what is described as Limb-Girdle Myasthenia Gravis. This patient presented with proximal arm and leg weakness that rapidly progressed and lead to loss of reflexes, appearing to be a myelopathy prior to obtaining an electromyography/nerve conduction study which demonstrated decrement of 21% in ulnar, 22% in median, and 59% of radial nerves during 2Hz repetitive stimulation. Our patient improved with plasmapheresis and prednisone with full recovery of strength

OpenNFT: an open-source Python/Matlab framework for real-time fMRI neurofeedback training based on activity, connectivity and multivariate pattern analysis

Neurofeedback based on real-time functional magnetic resonance imaging (rt-fMRI) is a novel and rapidly developing research field. It allows for training of voluntary control over localized brain activity and connectivity and has demonstrated promising clinical applications. Because of the rapid technical developments of MRI techniques and the availability of high-performance computing, new methodological advances in rt-fMRI neurofeedback become possible. Here we outline the core components of a novel open-source neurofeedback framework, termed Open NeuroFeedback Training (OpenNFT), which efficiently integrates these new developments. This framework is implemented using Python and Matlab source code to allow for diverse functionality, high modularity, and rapid extendibility of the software depending on the user's needs. In addition, it provides an easy interface to the functionality of Statistical Parametric Mapping (SPM) that is also open-source and one of the most widely used fMRI data analysis software. We demonstrate the functionality of our new framework by describing case studies that include neurofeedback protocols based on brain activity levels, effective connectivity models, and pattern classification approaches. This open-source initiative provides a suitable framework to actively engage in the development of novel neurofeedback approaches, so that local methodological developments can be easily made accessible to a wider range of users

Real-time fMRI data for testing OpenNFT functionality

Here, we briefly describe the real-time fMRI data that is provided for testing the functionality of the open-source Python/Matlab framework for neurofeedback, termed Open NeuroFeedback Training (OpenNFT, Koush et al. [1]). The data set contains real-time fMRI runs from three anonymized participants (i.e., one neurofeedback run per participant), their structural scans and pre-selected ROIs/masks/weights. The data allows for simulating the neurofeedback experiment without an MR scanner, exploring the software functionality, and measuring data processing times on the local hardware. In accordance with the descriptions in our main article, we provide data of (1) periodically displayed (intermittent) activation-based feedback; (2) intermittent effective connectivity feedback, based on dynamic causal modeling (DCM) estimations; and (3) continuous classification-based feedback based on support-vector-machine (SVM) estimations. The data is available on our public GitHub repository: https://github.com/OpenNFT/OpenNFT_Demo/releases

Intravenous immunoglobulin as a therapeutic option for Mycoplasma pneumoniae encephalitis

OBJECTIVE: To analyze the outcomes of a cohort of children diagnosed with Mycoplasma pneumoniae encephalitis whose treatment regimens included intravenous immunoglobulin (IVIG). METHODS: A retrospective study was performed at a single center between 2011 and 2016 of children diagnosed with Mycoplasma pneumoniae encephalitis whose acute treatment regimen included IVIG. Details of therapeutic interventions and the clinical course were retrieved from medical records via an institutionally approved protocol. The modified Rankin score was used to quantify outcomes. RESULTS: Four children met inclusion criteria, 3 of whom had prodromal symptoms of infection lasting 5 to 7 days before onset of their neurologic symptoms. One patient presented with neurologic symptoms with no clinical prodrome. The initial treatment regimen included systemic corticosteroids, antibiotics, or both. IVIG was administered for a total dose of 2 g/kg divided over 2 to 4 days to all 4 children. All children showed clinical improvement after IVIG. The 3 children with prodromal symptoms showed immediate and dramatic clinical improvement after IVIG therapy. DISCUSSION: The immediate response to immunomodulatory therapy in the patients with prodrome suggests that the neurologic syndrome may be caused at least in part by an autoimmune process. The child who did not respond to IVIG had no prodrome, and also had normal electroencephalographic (EEG) and brain magnetic resonance imaging (MRI) findings. These cases suggest that early administration of IVIG should be considered in patients suspected of having Mycoplasma encephalitis, particularly in those who have had prodromal symptoms