Multi-channel Analysis for Gradient Artifact Removal from Concurrent EEG-fMRI Studies

Concurrent electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) recordings are susceptible to large amounts of noise due to the static and dynamic magnetic fields present inside the MR scanner. EEG-fMRI studies are conducted to provide better spatial and temporal resolution for each recording, respectively, but the artifacts found in the EEG render the data impossible to interpret. Past studies have focused on signal post-processing techniques which are able to effectively remove noise upon the completion of a study, but there are no techniques able to process the data in real-time without extensive calibration. This research addresses this issue by exploring multi-channel analysis techniques on data combined from each of the EEG channels with a limited number of epochs. In particular, the spatial dependency between the three orthogonal components of the magnetic field gradients was studied to find corresponding templates that can be used to remove this artifact. The resulting algorithms were then tested against an existing algorithm to evaluate their performance. The multi-channel average artifact regression algorithm was found to be robust against the motion artifact and functioned well with few epochs. This algorithm has been implemented in a MATLAB toolbox which will soon be available to the public. Further studies are needed to extend this approach to remove the pulse artifact

Method Validation of Functional Magnetic Resonance Imaging and Electrophysiological Recording to Investigate Mechanisms of Vagus Nerve

Vagus nerve stimulation (VNS) is used clinically to treat epilepsy and depression, but its mechanism of action is unknown. Useful techniques to study this are functional magnetic resonance imaging (fMRI) and the local field potential (LFP). fMRI relies on oxygen use in the brain to show areas where neurons are active. The LFP is an electrical signal created by neuron action potentials and other current moving across cell membranes. The most information can be gained when the two methods are used simultaneously, however, this is difficult to do. This study seeks to validate the technique of fMRI-LFP as applied to study the mechanism of VNS. The rat is used as an animal model. Previously collected data is analyzed to determine effects of stimulation on respiration, since this will affect oxygen levels in the blood. Recording electrodes of different materials are tested to find the artifact size created in an MRI environment. Iridium electrodes were found to have the smallest artifact and therefore the best performance. It is unclear whether the stimulation used affects respiration, so a simultaneous fMRI-LFP experiment is needed to interpret fMR images. More work needs to be done before fMRI-LFP recordings can be taken during VNS

In vivo tracing of the ascending vagal projections to the brain with manganese enhanced magnetic resonance imaging

IntroductionThe vagus nerve, the primary neural pathway mediating brain-body interactions, plays an essential role in transmitting bodily signals to the brain. Despite its significance, our understanding of the detailed organization and functionality of vagal afferent projections remains incomplete.MethodsIn this study, we utilized manganese-enhanced magnetic resonance imaging (MEMRI) as a non-invasive and in vivo method for tracing vagal nerve projections to the brainstem and assessing their functional dependence on cervical vagus nerve stimulation (VNS). Manganese chloride solution was injected into the nodose ganglion of rats, and T1-weighted MRI scans were performed at both 12 and 24 h after the injection.ResultsOur findings reveal that vagal afferent neurons can uptake and transport manganese ions, serving as a surrogate for calcium ions, to the nucleus tractus solitarius (NTS) in the brainstem. In the absence of VNS, we observed significant contrast enhancements of around 19–24% in the NTS ipsilateral to the injection side. Application of VNS for 4 h further promoted nerve activity, leading to greater contrast enhancements of 40–43% in the NTS.DiscussionThese results demonstrate the potential of MEMRI for high-resolution, activity-dependent tracing of vagal afferents, providing a valuable tool for the structural and functional assessment of the vagus nerve and its influence on brain activity

The Potential Roles of Long Noncoding RNAs (lncRNA) in Glioblastoma Development

Long noncoding RNA (lncRNA) may contribute to the initiation and progression of tumor. In this study, we first systematically compared lncRNA and mRNA expression between glioblastoma and paired normal brain tissues using microarray data. We found 27 lncRNA and 82 mRNA significantly upregulated in glioblastoma, as well as 198 lncRNA and 285 mRNA significantly downregulated in glioblastoma. We identified 138 coexpressed lncRNA–mRNA pairs from these differentially expressed lncRNA and genes. Subsequent pathway analysis of the lncRNA-paired genes indicated that EphrinB–EPHB, p75-mediated signaling, TNFα/NF-κB, and ErbB2/ErbB3 signaling pathways might be altered in glioblastoma. Specifically, lncRNA RAMP2-AS1 had significant decrease of expression in glioblastoma tissues and showed coexpressional relationship with NOTCH3, an important tumor promoter in many neoplastic diseases. Our follow up experiment indicated that (i) an overexpression of RAMP2-AS1 reduced glioblastoma cell proliferation in vitro and also reduced glioblastoma xenograft tumors in vivo; (ii) NOTCH3 and RAMP2-AS1 coexpression rescued the inhibitory action of RAMP2-AS1 in glioblastoma cells; and (iii) RNA pull-down assay revealed a direct interaction of RAMP2-AS1 with DHC10, which may consequently inhibit, as we hypothesize, the expression of NOTCH3 and its downstream signaling molecule HES1 in glioblastoma. Taken together, our data revealed that lncRNA expression profile in glioblastoma tissue was significantly altered; and RAMP2-AS1 might play a tumor suppressive role in glioblastoma through an indirect inhibition of NOTCH3. Our results provided some insights into understanding the key roles of lncRNA–mRNA coregulation in human glioblastoma and the mechanisms responsible for glioblastoma progression and pathogenesis. Mol Cancer Ther; 15(12); 2977–86. ©2016 AACR