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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Adam C. Gravitis; Uilki Tufa; Katherine Zukotynski; Katherine Zukotynski; +10 Authors

    IntroductionPrevious case-control studies of sudden unexpected death in epilepsy (SUDEP) patients failed to identify ECG features (peri-ictal heart rate, heart rate variability, corrected QT interval, postictal heart rate recovery, and cardiac rhythm) predictive of SUDEP risk. This implied a need to derive novel metrics to assess SUDEP risk from ECG.MethodsWe applied Single Spectrum Analysis and Independent Component Analysis (SSA-ICA) to remove artifact from ECG recordings. Then cross-frequency phase-phase coupling (PPC) was applied to a 20-s mid-seizure window and a contour of −3 dB coupling strength was determined. The contour centroid polar coordinates, amplitude (alpha) and angle (theta), were calculated. Association of alpha and theta with SUDEP was assessed and a logistic classifier for alpha was constructed.ResultsAlpha was higher in SUDEP patients, compared to non-SUDEP patients (p < 0.001). Theta showed no significant difference between patient populations. The receiver operating characteristic (ROC) of a logistic classifier for alpha resulted in an area under the ROC curve (AUC) of 94% and correctly classified two test SUDEP patients.DiscussionThis study develops a novel metric alpha, which highlights non-linear interactions between two rhythms in the ECG, and is predictive of SUDEP risk.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ PubMed Central; Fron...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Frontiers in Neurology
    Article . 2023
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Sean L. Carter; Sean L. Carter; Ronak Patel; John D. Fisk; +21 Authors

    BackgroundFifty-one percent of individuals with multiple sclerosis (MS) develop cognitive impairment (CI) in information processing speed (IPS). Although IPS scores are associated with health and well-being, neural changes that underlie IPS impairments in MS are not understood. Resting state fMRI can provide insight into brain function changes underlying impairment in persons with MS.ObjectivesWe aimed to assess functional connectivity (FC) differences in (i) persons with MS compared to healthy controls (HC), (ii) persons with both MS and CI (MS-CI) compared to HC, (iii) persons with MS that are cognitively preserved (MS-CP) compared to HC, (iv) MS-CI compared to MS-CP, and (v) in relation to cognition within the MS group.MethodsWe included 107 participants with MS (age 49.5 ± 12.9, 82% women), and 94 controls (age 37.9 ± 15.4, 66% women). Each participant was administered the Symbol Digit Modalities Test (SDMT) and underwent a resting state fMRI scan. The MS-CI group was created by applying a z-score cut-off of ≤−1.5 to locally normalized SDMT scores. The MS-CP group was created by applying a z-score of ≥0. Control groups (HCMS-CI and HCMS-CP) were based on the nearest age-matched HC participants. A whole-brain ROI-to-ROI analysis was performed followed by specific contrasts and a regression analysis.ResultsIndividuals with MS showed FC differences compared to HC that involved the cerebellum, visual and language-associated brain regions, and the thalamus, hippocampus, and basal ganglia. The MS-CI showed FC differences compared to HCMS-CI that involved the cerebellum, visual and language-associated areas, thalamus, and caudate. SDMT scores were correlated with FC between the cerebellum and lateral occipital cortex in MS. No differences were observed between the MS-CP and HCMS-CP or MS-CI and MS-CP groups.ConclusionOur findings emphasize FC changes of cerebellar, visual, and language-associated areas in persons with MS. These differences were apparent for (i) all MS participants compared to HC, (ii) MS-CI subgroup and their matched controls, and (iii) the association between FC and SDMT scores within the MS group. Our findings strongly suggest that future work that examines the associations between FC and IPS impairments in MS should focus on the involvement of these regions.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Frontiers in Neurolo...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Frontiers in Neurology
    Article . 2023
    Data sources: DOAJ
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Ruth Ann Marrie; Ruth Ann Marrie; Ronak Patel; Chase R. Figley; +15 Authors

    ObjectiveVascular comorbidities are associated with reduced cognitive performance and with changes in brain structure in people with multiple sclerosis (MS). Understanding causal pathways is necessary to support the design of interventions to mitigate the impacts of comorbidities, and to monitor their effectiveness. We assessed the inter-relationships among vascular comorbidity, cognition and brain structure in people with MS.MethodsAdults with neurologist-confirmed MS reported comorbidities, and underwent assessment of their blood pressure, HbA1c, and cognitive functioning (i.e., Symbol Digit Modalities Test, California Verbal Learning Test, Brief Visuospatial Memory Test-Revised, and verbal fluency). Test scores were converted to age-, sex-, and education-adjusted z-scores. Whole brain magnetic resonance imaging (MRI) was completed, from which measures of thalamic and hippocampal volumes, and mean diffusivity of gray matter and normal-appearing white matter were converted to age and sex-adjusted z-scores. Canonical correlation analysis was used to identify linear combinations of cognitive measures (cognitive variate) and MRI measures (MRI variate) that accounted for the most correlation between the cognitive and MRI measures. Regression analyses were used to test whether MRI measures mediated the relationships between the number of vascular comorbidities and cognition measures.ResultsOf 105 participants, most were women (84.8%) with a mean (SD) age of 51.8 (12.8) years and age of symptom onset of 29.4 (10.5) years. Vascular comorbidity was common, with 35.2% of participants reporting one, 15.2% reporting two, and 8.6% reporting three or more. Canonical correlation analysis of the cognitive and MRI variables identified one pair of variates (Pillai's trace = 0.45, p = 0.0035). The biggest contributors to the cognitive variate were the SDMT and CVLT-II, and to the MRI variate were gray matter MD and thalamic volume. The correlation between cognitive and MRI variates was 0.50; these variates were used in regression analyses. On regression analysis, vascular comorbidity was associated with the MRI variate, and with the cognitive variate. After adjusting for the MRI variate, vascular comorbidity was not associated with the cognitive variate.ConclusionVascular comorbidity is associated with lower cognitive function in people with MS and this association is partially mediated via changes in brain macrostructure and microstructure.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Frontiers in Neurolo...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Frontiers in Neurology
    Article . 2022
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Anwar S. Shatil; Anwar S. Shatil; Kant M. Matsuda; Kant M. Matsuda; +5 Authors

    Magnetic resonance imaging (MRI) is a non-destructive technique that is capable of localizing pathologies and assessing other anatomical features (e.g., tissue volume, microstructure, and white matter connectivity) in postmortem, ex vivo human brains. However, when brains are removed from the skull and cerebrospinal fluid (i.e., their normal in vivo magnetic environment), air bubbles and air–tissue interfaces typically cause magnetic susceptibility artifacts that severely degrade the quality of ex vivo MRI data. In this report, we describe a relatively simple and cost-effective experimental setup for acquiring artifact-free ex vivo brain images using a clinical MRI system with standard hardware. In particular, we outline the necessary steps, from collecting an ex vivo human brain to the MRI scanner setup, and have also described changing the formalin (as might be necessary in longitudinal postmortem studies). Finally, we share some representative ex vivo MRI images that have been acquired using the proposed setup in order to demonstrate the efficacy of this approach. We hope that this protocol will provide both clinicians and researchers with a straight-forward and cost-effective solution for acquiring ex vivo MRI data from whole postmortem human brains.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Frontiers in Neurolo...arrow_drop_down
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    Frontiers in Neurology; PubMed Central
    Article . Other literature type . 2016 . Peer-reviewed
    License: CC BY
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Frontiers in Neurology
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Frontiers in Neurology
    Article . 2016
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Frontiers in Neurolo...arrow_drop_down
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      Frontiers in Neurology; PubMed Central
      Article . Other literature type . 2016 . Peer-reviewed
      License: CC BY
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Frontiers in Neurology
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Frontiers in Neurology
      Article . 2016
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Campbell, Jennifer S. W.; MomayyezSiahkal, Parya; Savadjiev, Peter; Leppert, Ilana R.; +2 Authors

    Diffusion magnetic resonance imaging fiber tractography is a powerful tool for investigating human white matter connectivity in vivo. However, it is prone to false positive and false negative results, making interpretation of the tractography result difficult. Optimal tractography must begin with an accurate description of the subvoxel white matter fiber structure, includes quantification of the uncertainty in the fiber directions obtained, and quantifies the confidence in each reconstructed fiber tract. This paper presents a novel and comprehensive pipeline for fiber tractography that meets the above requirements. The subvoxel fiber geometry is described in detail using a technique that allows not only for straight crossing fibers but for fibers that curve and splay. This technique is repeatedly performed within a residual bootstrap statistical process in order to efficiently quantify the uncertainty in the subvoxel geometries obtained. A robust connectivity index is defined to quantify the confidence in the reconstructed connections. The tractography pipeline is demonstrated in the human brain.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Frontiers in Neurolo...arrow_drop_down
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Frontiers in Neurology
    Article . 2014
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    Frontiers in Neurology
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    Frontiers in Neurology; PubMed Central
    Article . Other literature type . 2014 . Peer-reviewed
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      Article . 2014
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    Authors: Gabriela Ioachim; Howard J. M. Warren; Jocelyn M. Powers; Roland Staud; +5 Authors

    Chronic pain associated with fibromyalgia (FM) affects a large portion of the population but the underlying mechanisms leading to this altered pain are still poorly understood. Evidence suggests that FM involves altered neural processes in the central nervous system and neuroimaging methods such as functional magnetic resonance imaging (fMRI) are used to reveal these underlying alterations. While many fMRI studies of FM have been conducted in the brain, recent evidence shows that the changes in pain processing in FM may be linked to autonomic and homeostatic dysregulation, thus requiring further investigation in the brainstem and spinal cord. Functional magnetic resonance imaging data from 15 women with FM and 15 healthy controls were obtained in the cervical spinal cord and brainstem at 3 tesla using previously established methods. In order to investigate differences in pain processing in these groups, participants underwent trials in which they anticipated and received a predictable painful stimulus, randomly interleaved with trials with no stimulus. Differences in functional connectivity between the groups were investigated by means of structural equation modeling. The results demonstrate significant differences in brainstem/spinal cord network connectivity between the FM and control groups which also correlated with individual differences in pain responses. The regions involved in these differences in connectivity included the LC, hypothalamus, PAG, and PBN, which are known to be associated with autonomic homeostatic regulation, including fight or flight responses. This study extends our understanding of altered neural processes associated with FM and the important link between sensory and autonomic regulation systems in this disorder.

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    Frontiers in Neurology
    Article . 2022
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    Authors: Yassine Lamrani; Thi Phuoc Yen Tran; Dènahin Hinnoutondji Toffa; Dènahin Hinnoutondji Toffa; +7 Authors

    IntroductionMechanisms underlying sudden unexpected death in epilepsy (SUDEP) are unclear, but autonomic disorders are thought to play a critical role. However, those dysfunctions have mainly been reported in the peri-ictal context of generalized tonic–clonic seizures. Here, we explored whether heart rate variability (HRV), heart rate (HR), and breathing rate (BR) changes could be observed perictally during focal seizures with or without impaired awareness as well as interictally to assess the risk of SUDEP. We report the case of a 33-year-old patient with drug-resistant bilateral temporal lobe epilepsy who died at home probably from an unwitnessed nocturnal seizure (“probable SUDEP”).MethodsIctal and interictal HRV as well as postictal cardiorespiratory analyses were conducted to assess autonomic functions and overall SUDEP risk. The SUDEP patient was compared to two living male patients from our local database matched for age, sex, and location of the epileptic focus.ResultsInterictal HRV analysis showed that all sleep HRV parameters and most awake HRV parameters of the SUDEP patient were significantly lower than those of our two control subjects with bitemporal lobe epilepsy without SUDEP (p < 0.01). In two focal with impaired awareness seizures (FIAS) of the SUDEP patient, increased postictal mean HR and reduced preictal mean high frequency signals (HF), known markers of increased seizure severity in convulsive seizures, were seen postictally. Furthermore, important autonomic instability and hypersensitivity were seen through fluctuations in LF/HF ratio following two seizures of the SUDEP patient, with a rapid transition between sympathetic and parasympathetic activity. In addition, a combination of severe hypopnea (202 s) and bradycardia (10 s), illustrating autonomic dysfunction, was found after one of the SUDEP patient’s FIAS.DiscussionThe unusual cardiorespiratory and HRV patterns found in this case indicated autonomic abnormalities that were possibly predictive of an increased risk of SUDEP. It will be interesting to perform similar analyses in other SUDEP cases to see whether our findings are anecdotal or instead suggestive of reliable biomarkers of high SUDEP risk in focal epilepsy, in particular focal with or without impaired awareness seizures.

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    Frontiers in Neurology
    Article . 2023
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    Authors: Lucas D. Crosby; Jennifer S. Wong; Joyce L. Chen; Joyce L. Chen; +5 Authors

    Temporal gait asymmetry (TGA) is a persistent post-stroke gait deficit. Compared to conventional gait training techniques, rhythmic auditory stimulation (RAS; i.e., walking to a metronome) has demonstrated positive effects on post-stroke TGA. Responsiveness of TGA to RAS may be related to several factors including motor impairment, time post-stroke, and individual rhythm abilities. The purpose of this study was to investigate the relationship between rhythm abilities and responsiveness of TGA when walking to RAS. Assessed using behavioral tests of beat perception and production, participants with post-stroke TGA (measured as single limb support time ratio) were categorized according to rhythm ability (as strong or weak beat perceivers/producers). We assessed change in TGA between walking without cues (baseline) and walking while synchronizing footsteps with metronome cues. Most individuals with stroke were able to maintain or improve TGA with a single session of RAS. Within-group analyses revealed a difference between strong and weak rhythm ability groups. Strong beat perceivers and producers showed significant reduction (improvement) in TGA with the metronome. Those with weak ability did not and exhibited high variability in the TGA response to metronome. Moreover, individuals who worsened in TGA when walking to metronome had poorer beat production scores than those who did not change in TGA. However, no interaction between TGA improvement when walking to metronome and rhythm perception or production ability was found. While responsiveness of TGA to RAS did not significantly differ based on strength of rhythm abilities, these preliminary findings highlight rhythm ability as a potential consideration when treating post-stroke individuals with rhythm-based treatments.

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    Article . 2020
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    PubMed Central; Frontiers in Neurology
    Article . Other literature type . 2020 . Peer-reviewed
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      PubMed Central; Frontiers in Neurology
      Article . Other literature type . 2020 . Peer-reviewed
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    Authors: Warren Y. L. Sun; Kai Cheng; Zhibin Ning; Bo Xu; +9 Authors

    The circadian clock is an endogenous oscillator that drives daily rhythms in physiology, behavior, and gene expression. The underlying mechanisms of circadian timekeeping are cell-autonomous and involve oscillatory expression of core clock genes that is driven by interconnecting transcription-translation feedback loops (TTFLs). Circadian clock TTFLs are further regulated by posttranslational modifications, in particular, phosphorylation. The hippocampus plays an important role in spatial memory and the conversion of short- to long-term memory. Several studies have reported the presence of a peripheral oscillator in the hippocampus and have highlighted the importance of circadian regulation in memory formation. Given the general importance of phosphorylation in circadian clock regulation, we performed global quantitative proteome and phosphoproteome analyses of the murine hippocampus across the circadian cycle, applying spiked-in labeled reference and high accuracy mass spectrometry (MS). Of the 3,052 proteins and 2,868 phosphosites on 1,368 proteins that were accurately quantified, 1.7% of proteins and 5.2% of phosphorylation events exhibited time-of-day-dependent expression profiles. The majority of circadian phosphopeptides displayed abrupt fluctuations at mid-to-late day without underlying rhythms of protein abundance. Bioinformatic analysis of cyclic phosphorylation events revealed their diverse distribution in different biological pathways, most notably, cytoskeletal organization and neuronal morphogenesis. This study provides the first large-scale, quantitative MS analysis of the circadian phosphoproteome and proteome of the murine hippocampus and highlights the significance of rhythmic regulation at the posttranslational level in this peripheral oscillator. In addition to providing molecular insights into the hippocampal circadian clock, our results will assist in the understanding of genetic factors that underlie rhythms-associated pathological states of the hippocampus.

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    Frontiers in Neurology; PubMed Central
    Other literature type . Article . 2017 . Peer-reviewed
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    Authors: Shatil, Anwar S.; Matsuda, Kant M.; Figley, Chase R.;

    Magnetic resonance imaging (MRI) is a non-destructive technique that is capable of localizing pathologies and assessing other anatomical features (e.g., tissue volume, microstructure, and white matter connectivity) in postmortem, ex vivo human brains. However, when brains are removed from the skull and cerebrospinal fluid (i.e., their normal in vivo magnetic environment), air bubbles and air–tissue interfaces typically cause magnetic susceptibility artifacts that severely degrade the quality of ex vivo MRI data. In this report, we describe a relatively simple and cost-effective experimental setup for acquiring artifact-free ex vivo brain images using a clinical MRI system with standard hardware. In particular, we outline the necessary steps, from collecting an ex vivo human brain to the MRI scanner setup, and have also described changing the formalin (as might be necessary in longitudinal postmortem studies). Finally, we share some representative ex vivo MRI images that have been acquired using the proposed setup in order to demonstrate the efficacy of this approach. We hope that this protocol will provide both clinicians and researchers with a straight-forward and cost-effective solution for acquiring ex vivo MRI data from whole postmortem human brains.

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    Frontiers in Neurology
    2016 . Peer-reviewed
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    Authors: Adam C. Gravitis; Uilki Tufa; Katherine Zukotynski; Katherine Zukotynski; +10 Authors

    IntroductionPrevious case-control studies of sudden unexpected death in epilepsy (SUDEP) patients failed to identify ECG features (peri-ictal heart rate, heart rate variability, corrected QT interval, postictal heart rate recovery, and cardiac rhythm) predictive of SUDEP risk. This implied a need to derive novel metrics to assess SUDEP risk from ECG.MethodsWe applied Single Spectrum Analysis and Independent Component Analysis (SSA-ICA) to remove artifact from ECG recordings. Then cross-frequency phase-phase coupling (PPC) was applied to a 20-s mid-seizure window and a contour of −3 dB coupling strength was determined. The contour centroid polar coordinates, amplitude (alpha) and angle (theta), were calculated. Association of alpha and theta with SUDEP was assessed and a logistic classifier for alpha was constructed.ResultsAlpha was higher in SUDEP patients, compared to non-SUDEP patients (p < 0.001). Theta showed no significant difference between patient populations. The receiver operating characteristic (ROC) of a logistic classifier for alpha resulted in an area under the ROC curve (AUC) of 94% and correctly classified two test SUDEP patients.DiscussionThis study develops a novel metric alpha, which highlights non-linear interactions between two rhythms in the ECG, and is predictive of SUDEP risk.

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    Authors: Sean L. Carter; Sean L. Carter; Ronak Patel; John D. Fisk; +21 Authors

    BackgroundFifty-one percent of individuals with multiple sclerosis (MS) develop cognitive impairment (CI) in information processing speed (IPS). Although IPS scores are associated with health and well-being, neural changes that underlie IPS impairments in MS are not understood. Resting state fMRI can provide insight into brain function changes underlying impairment in persons with MS.ObjectivesWe aimed to assess functional connectivity (FC) differences in (i) persons with MS compared to healthy controls (HC), (ii) persons with both MS and CI (MS-CI) compared to HC, (iii) persons with MS that are cognitively preserved (MS-CP) compared to HC, (iv) MS-CI compared to MS-CP, and (v) in relation to cognition within the MS group.MethodsWe included 107 participants with MS (age 49.5 ± 12.9, 82% women), and 94 controls (age 37.9 ± 15.4, 66% women). Each participant was administered the Symbol Digit Modalities Test (SDMT) and underwent a resting state fMRI scan. The MS-CI group was created by applying a z-score cut-off of ≤−1.5 to locally normalized SDMT scores. The MS-CP group was created by applying a z-score of ≥0. Control groups (HCMS-CI and HCMS-CP) were based on the nearest age-matched HC participants. A whole-brain ROI-to-ROI analysis was performed followed by specific contrasts and a regression analysis.ResultsIndividuals with MS showed FC differences compared to HC that involved the cerebellum, visual and language-associated brain regions, and the thalamus, hippocampus, and basal ganglia. The MS-CI showed FC differences compared to HCMS-CI that involved the cerebellum, visual and language-associated areas, thalamus, and caudate. SDMT scores were correlated with FC between the cerebellum and lateral occipital cortex in MS. No differences were observed between the MS-CP and HCMS-CP or MS-CI and MS-CP groups.ConclusionOur findings emphasize FC changes of cerebellar, visual, and language-associated areas in persons with MS. These differences were apparent for (i) all MS participants compared to HC, (ii) MS-CI subgroup and their matched controls, and (iii) the association between FC and SDMT scores within the MS group. Our findings strongly suggest that future work that examines the associations between FC and IPS impairments in MS should focus on the involvement of these regions.

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    Frontiers in Neurology
    Article . 2023
    Data sources: DOAJ
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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