Neil Mittal

Fruit bats in the genus Pteropus are the natural reservoirs for zoonotic paramyxoviruses, notably henipaviruses and pararubulaviruses, which are found across Southeast Asia and Oceania. The genetic and antigenic diversity of viruses in both genera, and region specificity, are ill-defined, limiting health security measures aimed at minimizing spillover. For example, Nipah virus has been isolated from bats in the Battambang province of western Cambodia, and surveys suggest bat foraging behaviors occur in close proximity to human settlements. However, there have been no historical cases of Nipah virus in Cambodia. Here, we use a multiplex microsphere immunoassay to identify cryptic human exposure to selected henipaviruses and pararubulaviruses in Cambodia. Convalescent human sera from persons presenting with acute respiratory illness were screened to detect the presence or absence of antibodies reactive with attachment glycoprotein antigens from Nipah virus, Hendra virus, Cedar virus, and Ghana virus, and a hemagglutinin-neuraminidase antigen from Menangle virus. In this sero-survey, we detected antibodies that were specifically reactive with Cedar virus and Menangle virus, including one serum sample that neutralized a recombinant Cedar virus. Additionally, we detected a pattern of cross-reactivity with Hendra virus, Cedar virus, and Ghana virus, suggesting previous infection by an antigenically-related henipavirus. We did not detect high antibody reactivity with the NiV glycoprotein. Future studies should expand serological surveillance for these transboundary pathogens, including genetic surveillance to aid in henipavirus discovery, and focused biosurveillance where interfaces with livestock and humans occur.

Transcranial magnetic stimulation (TMS) is a noninvasive brain stimulation technique used in the treatment of several neurological conditions. The dosage parameter for TMS protocols is the resting motor threshold (RMT) which has been shown to vary between participants with limited understanding. The goal of this study was to investigate how white matter-derived fiber tracts integrated into finite element analysis simulations influence TMS response in the form of RMT. Ten healthy participants were included in this study who underwent TMS, diffusion tensor imaging, and structural magnetic resonance imaging. Anatomically accurate head models were created, and fiber tracts were extracted from Diffusion tensor imaging and integrated into these head models before finite element analysis simulations were performed to model the effects of empirical TMS. Linear mixed effects models were used to evaluate how the induced electric field strength on the fiber tracts (EFSTract) influenced RMT. We found the induced electric field strength along fiber tracts did influence RMT, however the effect of this relationship on RMT is not clinically relevant due to its small magnitude. This suggests finite element analysis of the fiber tracts is not meaningful when tracts are considered a homogenous material and thus lacking physiology. However, tractography provides a valuable framework within which to organize physiological models of signal transmission, and it is likely a combination of this approach with more physiologically detailed modeling would provide more accurate RMT prediction.

Schizophrenia is a neurological disorder known to influence the motor region. Transcranial magnetic stimulation (TMS) is a non-invasive neuromodulation technique being investigated as a treatment for schizophrenia. Resting motor threshold (RMT) is the dosage parameter for TMS treatment protocols and is known to vary between participants with limited understanding of the drivers of this variance. Previous investigations have used functional magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), and individual level neuroanatomy to explain RMT variability. Our previous investigation showed neuroanatomy influences RMT in both schizophrenia and healthy populations and this relationship was weakened by the presence of schizophrenia. In this study, 54 participants with schizophrenia-diagnosed, who were antipsychotic naive and 43 non-impaired controls underwent single pulse TMS, structural magnetic resonance imaging, and fMRI. An independent component analysis (ICA) was used to process fMRI data into 25 distinct channels where correlations were derived between channels. Linear and multiple regression models were used to evaluate first, the influence of these channel interactions on RMT followed by their influence when individual level neuroanatomy was also considered. We found that between-channel functional connectivity was altered in individuals with schizophrenia and that fMRI can contribute to prediction of RMT, but differently in both cohorts and to a lesser degree than individual level neuroanatomical measures. This suggests that functional connectivity influences TMS response and fMRI might help in dosage calculations of clinical TMS protocols.

Neural circuits have explained motor learning observed in animal populations, and plastic synaptic reorganization, but simulation of network modeling at larger scales lacks circuit organization. As a result, while large scale models capture general population behavior, there remains no canonical circuit, or simplest circuit-based functional subunit, that can be studied to determine the most discrete level of neuromodulation effect. The purpose of this study was to integrate a canonical neural circuit of the motor cortex with mathematical representation of membrane potentials across multiple neurons. The circuit model was evaluated by comparing changes in modeled resting outputter cell spike rate to changes in empirically recorded motor evoked potential amplitudes following intermittent theta burst stimulation (iTBS) delivered via transcranial magnetic stimulation. Effect sizes measured the magnitude of effect in both modeled and experimental data. The model successfully showed an increase in resting spike rate with relation to increased AMPA receptor permeability, scaled by simulated effects of iTBS to induce long-term potentiation (LTP), in an excitatory change similar to that seen in empirically recorded motor evoked potentials from human subjects. Thus, the model captured the mechanism of LTP in its simplest form. The representation is incomplete, however, as the model overestimated the responsivity based on the increased effect size relative to empirical data and noise. The overestimation is likely due to the lack of the disinhibition mechanism being fully represented in this iteration of the circuit, the simplicity of the cellular compartments modeled relative to the physiological complexity of neurons, and model parameter approximations of values controlling AMPA receptors. The circuit model is a building block for wider and more complex cortical networks that can be used to test mechanisms and applications of neuromodulation modalities.

Transcranial magnetic stimulation (TMS) is a non-invasive treatment protocol for treating several psychiatric conditions, including depression, migraine, smoking cessation, and obsessive-compulsive disorder. Past research suggests that TMS treatment outcomes vary based on neuroanatomy, functional connectivity, and tractography-based structural connectivity. In a previous study, 26 mild to moderate traumatic brain injury (mTBI) patients underwent repetitive transcranial magnetic stimulation (rTMS) and showed improvements in depression, post-concussive symptoms, and sleep dysfunction. The present study was a secondary analysis of that data. Anatomically accurate head models were derived from magnetic resonance imaging (MRI), and finite element analysis simulations were performed to mimic empirical data collection. This allowed for examination of the roles that age, brain scalp distance (BSD), gray matter volume (GMV), site-specific electrical field strength (EFS), and depolarized gray matter volume (DGMV) had on resting motor threshold (RMT) at the precentral gyrus (PreCG). We also investigated how EFS simulated at the dorsolateral prefrontal cortex (DLPFC) and RMT influenced rTMS treatment outcomes. Linear regression showed BSD was associated with EFS, RMT, and DGMV supporting efforts to derive accurate parameters from MRI-based modeling. Furthermore, linear mixed effects modeling showed RMT was associated with EFS and DGMV at the PreCG when age and individual neuroanatomy was accounted for suggesting MRI based anatomy and simulated EFS potentially determine TMS dosage. We did not observe any significant relationship between any of the measures from this study on empirically collected rTMS outcomes in mTBI suggesting further investigations into the mechanisms behind these outcomes are needed.

Background: Intermittent theta burst stimulation (iTBS) is a form of repetitive transcranial magnetic stimulation (TMS) that can increase corticomotor excitability of hand muscles in individuals with spinal cord injury (SCI). The objective of this study was to determine the effect of iTBS on the corticomotor excitability of the biceps brachii in individuals with tetraplegia. Methods: Ten individuals with low cervical SCI (C5-C8) and ten nonimpaired individuals completed three independent sessions. Motor evoked potentials (MEPs) served as our measure of corticomotor excitability and were collected before and after iTBS. MEPs were normalized by the electromyography corresponding to maximum voluntary contraction and analyzed using linear mixed effects models to determine the effect of iTBS (active or sham) on normalized MEPs (nMEPs). iTBS effects were compared to a ratio of active and resting motor thresholds as a measurement of corticomotor conductance potential. Results: Relative to sham, active iTBS increased nMEPs over time (p < 0.001) in individuals with SCI, but not nonimpaired individuals (p = 0.915). The amplitude of nMEPs were correlated with the biceps corticomotor conductance potential (p < 0.001), with nMEPs decreasing as the ratio increased at different rates after sham or active iTBS. Conclusions: Preliminary results suggest that iTBS increases biceps corticomotor excitability in individuals with tetraplegia with effects that may be predicted by corticomotor conductance potential. Clinical trial registration NCT03277521 Registered on clinicaltrials.gov on August 24, 2017

Individual neuroanatomy can influence motor responses to transcranial magnetic stimulation (TMS) and corticomotor excitability after intermittent theta burst stimulation (iTBS). The purpose of this study was to examine the relationship between individual neuroanatomy and both TMS response measured using resting motor threshold (RMT) and iTBS measured using motor evoked potentials (MEPs) targeting the biceps brachii and first dorsal interosseus (FDI). Ten nonimpaired individuals completed sham‐controlled iTBS sessions and underwent MRI, from which anatomically accurate head models were generated. Neuroanatomical parameters established through fiber tractography were fiber tract surface area (FTSA), tract fiber count (TFC), and brain scalp distance (BSD) at the point of stimulation. Cortical magnetic field induced electric field strength (EFS) was obtained using finite element simulations. A linear mixed effects model was used to assess effects of these parameters on RMT and iTBS (post‐iTBS MEPs). FDI RMT was dependent on interactions between EFS and both FTSA and TFC. Biceps RMT was dependent on interactions between EFS and and both FTSA and BSD. There was no groupwide effect of iTBS on the FDI but individual changes in corticomotor excitability scaled with RMT, EFS, BSD, and FTSA. iTBS targeting the biceps was facilitatory, and dependent on FTSA and TFC. MRI‐based measures of neuroanatomy highlight how individual anatomy affects motor system responses to different TMS paradigms and may be useful for selecting appropriate motor targets when designing TMS based therapies.

Transcranial magnetic stimulation (TMS) is a treatment procedure for some neuropsychiatric disorders, and it has been used for brain mapping, as well as diagnosis and treatment of neuromuscular dysfunctions. There is a disconnect between TMS modeling and clinical data: several groups have reported the simulated induced electric field and measured resting motor threshold (RMT) with inconsistent results in the relationship between RMT and brain scalp distance. This necessitates the use of simulation parameters that further account for individual differences in neuroanatomy. We recruited ten healthy subjects and obtained empirical RMT, magnetic resonance imaging (MRI), and diffusion tensor imaging (DTI). We developed anatomically accurate brain models from MRI and simulated TMS to determine the percent depolarized volume of gray matter (DVG) from TMS-induced electric fields. Corticospinal fiber tracts were extracted from the primary motor cortex from DTI to obtain fiber tract surface areas (FTSAs) for each participant. Linear mixed-effects models were used to evaluate the effect of DVG and FTSA on RMT. We report that DVG correlates with RMT when accounting for corticospinal FTSA.