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Impaired spontaneous regional activity and altered topology of the brain network have been observed in obstructive sleep apnea (OSA). However, the mechanisms of disrupted functional connectivity (FC) and topological reorganization of the default mode network (DMN) in patients with OSA remain largely unknown. We explored whether the FC is altered within the DMN and examined topological changes occur in the DMN in patients with OSA using a graph theory analysis of resting-state functional magnetic resonance imaging data and evaluated the relationship between neuroimaging measures and clinical variables. Resting-state data were obtained from 46 male patients with untreated severe OSA and 46 male good sleepers (GSs). We specifically selected 20 DMN subregions to construct the DMN architecture. The disrupted FC and topological properties of the DMN in patients with OSA were characterized using graph theory. The OSA group showed significantly decreased FC of the anterior–posterior DMN and within the posterior DMN, and also showed increased FC within the DMN. The DMN exhibited small-world topology in both OSA and GS groups. Compared to GSs, patients with OSA showed a decreased clustering coefficient (Cp) and local efficiency, and decreased nodal centralities in the left posterior cingulate cortex and dorsal medial prefrontal cortex, and increased nodal centralities in the ventral medial prefrontal cortex and the right parahippocampal cortex. Finally, the abnormal DMN FC was significantly related to Cp, path length, global efficiency, and Montreal cognitive assessment score. OSA showed disrupted FC within the DMN, which may have contributed to the observed topological reorganization. These findings may provide further evidence of cognitive deficits in patients with OSA.

Background: Ongoing or recurrent seizure activity without prominent motor features is a common burden in neurological critical care patients and people with epilepsy during ICU stays. Continuous EEG (CEEG) is the gold standard for detecting ongoing ictal EEG patterns and monitoring functional brain activity. However CEEG review is very demanding and time consuming. The purpose of the present multirater, EEG expert reviewer study, is to test and assess the clinical feasibility of an automatic EEG pattern detection method (Neurotrend).Methods: Four board certified EEG reviewers used Neurotrend to annotate 76 CEEG datasets à 6 h (in total 456 h of EEG) for rhythmic and periodic EEG patterns (RPP), unequivocal ictal EEG patterns and burst suppression. All reviewers had a predefined time limit of 5 min (± 2 min) per CEEG dataset and were compared to a predefined gold standard (conventional EEG review with unlimited time). Subanalysis of specific features of RPP was conducted as well. We used Gwet's AC1 and AC2 coefficients to calculate interrater agreement (IRA) and multirater agreement (MRA). Also, we determined individual performance measures for unequivocal ictal EEG patterns and burst suppression. Bonferroni-Holmes correction for multiple testing was applied to all statistical tests.Results: Mean review time was 3.3 min (± 1.9 min) per CEEG dataset. We found substantial IRA for unequivocal ictal EEG patterns (0.61–0.79; mean sensitivity 86.8%; mean specificity 82.2%, p < 0.001) and burst suppression (0.68–0.71; mean sensitivity 96.7%; mean specificity 76.9% p < 0.001). Two reviewers showed substantial IRA for RPP (0.68–0.72), whereas the other two showed moderate agreement (0.45–0.54), compared to the gold standard (p < 0.001). MRA showed almost perfect agreement for burst suppression (0.86) and moderate agreement for RPP (0.54) and unequivocal ictal EEG patterns (0.57).Conclusions: We demonstrated the clinical feasibility of an automatic critical care EEG pattern detection method on two levels: (1) reasonable high agreement compared to the gold standard, (2) reasonable short review times compared to previously reported EEG review times with conventional EEG analysis.

Aims: Some central nervous system (CNS) pathogens express neuraminidase (NA) on their surfaces. In the rat brain, a single intracerebroventricular (ICV) injection of NA induces myelin vacuolation in axonal tracts. Here we explore the nature, the time course, and the role of the complement system in this damage. Methods: The spatio-temporal analysis of myelin vacuolation was performed by optical and electron microscopy. Myelin basic protein (MBP)-positive area and oligodendrocyte transcription factor (Olig2)-positive cells were quantified in the damaged bundles. Neuronal death in the affected axonal tracts was assessed by Fluoro-Jade-B and anti-caspase-3 staining. To evaluate the role of the complement, membrane attack complex deposition on damaged bundles was analysed using anti-C5b9. Rats ICV injected with the anaphylatoxin C5a were studied for myelin damage. In addition, NA-induced vacuolation was studied in rats with different degrees of complement inhibition: normal rats treated with anti-C5 blocking antibody, and C6-deficient rats. Results: The stria medullaris, the optic chiasm and the fimbria were the most consistently damaged axonal tracts. Vacuolation peaked 7 days after NA injection, and reverted by day 15. Olig2+ cell number in the damaged tracts was unaltered, and neurodegeneration associated to myelin alterations was not detected. Membrane attack complex was absent on damaged axonal tracts, as revealed by C5b9 immunostaining. Rats ICV injected with the anaphylatoxin C5a displayed no myelin injury. When the complement system was experimentally or constitutively inhibited, NA-induced myelin vacuolation was similar to that observed in normal rats. Conclusions: Microbial NA induces a moderate and transient myelin vacuolation that is not caused either by neuroinflammation or complement system activation.

Pediatric-onset multiple sclerosis (POMS) may represent a model of vulnerability to damage occurring during a period of active maturation of the human brain. Whereas adaptive mechanisms seem to take place in the POMS brain in the short-medium term, natural history studies have shown that these patients reach irreversible disability, despite slower progression, at a significantly younger age than adult-onset MS (AOMS) patients. We tested for the first time whether significant brain alterations already occurred in POMS patients in their early adulthood and with no or minimal disability (n=15) in comparison to age- and disability-matched AOMS patients (n=14) and to normal controls (NC, n=20). We used a multimodal MRI approach by modelling, using FSL, voxelwise measures of microstructural integrity of white matter tracts and grey matter volumes with those of intra- and internetwork functional connectivity (analysis of variance, p≤0.01, corrected for multiple comparisons across space). POMS patients showed, when compared with both NC and AOMS patients, altered measures of diffusion tensor imaging (reduced fractional anisotropy and/or increased diffusivities) and higher probability of lesion occurrence in a clinically eloquent region for physical disability such as the posterior corona radiata. In addition, POMS patients showed, compared with the other two groups, reduced long-range functional connectivity, assessed from resting functional MRI, between default mode network and secondary visual network, whose interaction subserves important cognitive functions such as spatial attention and visual learning. Overall, this pattern of structural damage and brain connectivity disruption in early adult POMS patients with no or minimal clinical disability might explain their unfavourable clinical outcome in the long term.

It is a major challenge in clinical epilepsy to diagnose and treat a disease characterized by infrequent seizures based on patient or caregiver reports and limited duration clinical testing. The poor reliability of self-reported seizure diaries for many people with epilepsy is well-established, but these records remain necessary in clinical care and therapeutic studies. A number of wearable devices have emerged, which may be capable of detecting seizures, recording seizure data, and alerting caregivers. Developments in non-invasive wearable sensors to measure accelerometry, photoplethysmography (PPG), electrodermal activity (EDA), electromyography (EMG), and other signals outside of the traditional clinical environment may be able to identify seizure-related changes. Non-invasive scalp electroencephalography (EEG) and minimally invasive subscalp EEG may allow direct measurement of seizure activity. However, significant network and computational infrastructure is needed for continuous, secure transmission of data. The large volume of data acquired by these devices necessitates computer-assisted review and detection to reduce the burden on human reviewers. Furthermore, user acceptability of such devices must be a paramount consideration to ensure adherence with long-term device use. Such devices can identify tonic-clonic seizures, but identification of other seizure semiologies with non-EEG wearables is an ongoing challenge. Identification of electrographic seizures with subscalp EEG systems has recently been demonstrated over long (>6 month) durations, and this shows promise for accurate, objective seizure records. While the ability to detect and forecast seizures from ambulatory intracranial EEG is established, invasive devices may not be acceptable for many individuals with epilepsy. Recent studies show promising results for probabilistic forecasts of seizure risk from long-term wearable devices and electronic diaries of self-reported seizures. There may also be predictive value in individuals' symptoms, mood, and cognitive performance. However, seizure forecasting requires perpetual use of a device for monitoring, increasing the importance of the system's acceptability to users. Furthermore, long-term studies with concurrent EEG confirmation are lacking currently. This review describes the current evidence and challenges in the use of minimally and non-invasive devices for long-term epilepsy monitoring, the essential components in remote monitoring systems, and explores the feasibility to detect and forecast impending seizures via long-term use of these systems. Copyright © 2021 Brinkmann, Karoly, Nurse, Dumanis, Nasseri, Viana, Schulze-Bonhage, Freestone, Worrell, Richardson and Cook. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

Over the last 30 years, the functions (and dysfunctions) of the sensory-motor circuitry have been mostly conceptualized using linear modelizations which have resulted in two main models: the “rate hypothesis” and the “oscillatory hypothesis.” In these two models, the basal ganglia data stream is envisaged as a random temporal combination of independent simple patterns issued from its probability distribution of interval interspikes or its spectrum of frequencies respectively. More recently, non-linear analyses have been introduced in the modelization of motor circuitry activities, and they have provided evidences that complex temporal organizations exist in basal ganglia neuronal activities. Regarding movement disorders, these complex temporal organizations in the basal ganglia data stream differ between conditions (i.e., parkinsonism, dyskinesia, healthy control) and are responsive to treatments (i.e., l-DOPA, deep brain stimulation). A body of evidence has reported that basal ganglia neuronal entropy (a marker for complexity/irregularity in time series) is higher in hypokinetic state. In line with these findings, an entropy-based model has been recently formulated to introduce basal ganglia entropy as a marker for the alteration of motor processing and a factor of motor inhibition. Importantly, non-linear features have also been identified as a marker of condition and/or treatment effects in brain global signals (EEG), muscular activities (EMG), or kinetic of motor symptoms (tremor, gait) of patients with movement disorders. It is therefore warranted that the non-linear dynamics of motor circuitry will contribute to a better understanding of the neuronal dysfunctions underlying the spectrum of parkinsonian motor symptoms including tremor, rigidity, and hypokinesia.

PurposeWe developed a navigation system that superimposes the fractional anisotropy (FA) color map of pre-operative diffusion tensor imaging (DTI) and intraoperative magnetic resonance imaging (MRI). The current study aimed to investigate the usefulness of this system for neurophysiological monitoring and examination under awake craniotomy during tumor removal.MethodA total of 10 glioma patients (4 patients with right-side tumors; 5 men and 5 women; average age, 34 years) were evaluated. Among them, the tumor was localized to the frontal lobe, insular cortex, and parietal lobe in 8, 1, and 1 patient, respectively. There were 3 patients who underwent surgery on general anesthesia, while 7 patients underwent awake craniotomy. The index of DTI anisotropy taken pre-operatively (magnetic field: 3 tesla, 6 motion probing gradient directions) was analyzed as a color map (FA color map) and concurrently co-registered in the intraoperative MRI within the navigation. In addition to localization of the bipolar coagulator and the cortical stimulator for brain mapping on intraoperative MRI, the pre-operative FA color map was also concurrently integrated and displayed on the navigation monitor. This white matter nerve functional information was confirmed directly by using neurological examination and referring to the electrophysiological monitoring.ResultsIntraoperative MRI, integrated pre-operative FA color map, and microscopic surgical view were displayed on one screen in all 10 patients, and white matter fibers including the pyramidal tract were displayed as a reference in blue. Regarding motor function, motor-evoked potential was monitored as appropriate in all cases, and removal was possible while directly confirming motor symptoms under awake craniotomy. Furthermore, the white matter fibers including the superior longitudinal fasciculus were displayed in green. Importantly, it was useful not only to localize the resection site, but to identify language-related, eye movement-related, and motor fibers at the electrical stimulation site. All motor and/or language white matter tracts were identified and visualized with the co-registration and then with an acceptable post-operative neurological outcome.ConclusionCo-registering an intraoperative MR images and a pre-operative FA color map is a practical and useful method to predict the localization of critical white matter nerve functions intraoperatively in glioma surgery.