Treating Rhythmic and Periodic EEG Patterns in Comatose Survivors of Cardiac Arrest.

BACKGROUND: Whether the treatment of rhythmic and periodic electroencephalographic (EEG) patterns in comatose survivors of cardiac arrest improves outcomes is uncertain. METHODS: We conducted an open-label trial of suppressing rhythmic and periodic EEG patterns detected on continuous EEG monitoring in comatose survivors of cardiac arrest. Patients were randomly assigned in a 1:1 ratio to a stepwise strategy of antiseizure medications to suppress this activity for at least 48 consecutive hours plus standard care (antiseizure-treatment group) or to standard care alone (control group); standard care included targeted temperature management in both groups. The primary outcome was neurologic outcome according to the score on the Cerebral Performance Category (CPC) scale at 3 months, dichotomized as a good outcome (CPC score indicating no, mild, or moderate disability) or a poor outcome (CPC score indicating severe disability, coma, or death). Secondary outcomes were mortality, length of stay in the intensive care unit (ICU), and duration of mechanical ventilation. RESULTS: We enrolled 172 patients, with 88 assigned to the antiseizure-treatment group and 84 to the control group. Rhythmic or periodic EEG activity was detected a median of 35 hours after cardiac arrest; 98 of 157 patients (62%) with available data had myoclonus. Complete suppression of rhythmic and periodic EEG activity for 48 consecutive hours occurred in 49 of 88 patients (56%) in the antiseizure-treatment group and in 2 of 83 patients (2%) in the control group. At 3 months, 79 of 88 patients (90%) in the antiseizure-treatment group and 77 of 84 patients (92%) in the control group had a poor outcome (difference, 2 percentage points; 95% confidence interval, -7 to 11; P = 0.68). Mortality at 3 months was 80% in the antiseizure-treatment group and 82% in the control group. The mean length of stay in the ICU and mean duration of mechanical ventilation were slightly longer in the antiseizure-treatment group than in the control group. CONCLUSIONS: In comatose survivors of cardiac arrest, the incidence of a poor neurologic outcome at 3 months did not differ significantly between a strategy of suppressing rhythmic and periodic EEG activity with the use of antiseizure medication for at least 48 hours plus standard care and standard care alone. (Funded by the Dutch Epilepsy Foundation; TELSTAR ClinicalTrials.gov number, NCT02056236.).

Changes in postictal cerebral perfusion are related to the duration of electroconvulsive therapy-induced seizures.

OBJECTIVE: Postictal symptoms may result from cerebral hypoperfusion, which is possibly a consequence of seizure-induced vasoconstriction. Longer seizures have previously been shown to cause more severe postictal hypoperfusion in rats and epilepsy patients. We studied cerebral perfusion after generalized seizures elicited by electroconvulsive therapy (ECT) and its relation to seizure duration. METHODS: Patients with a major depressive episode who underwent ECT were included. During treatment, 21-channel continuous electroencephalogram (EEG) was recorded. Arterial spin labeling magnetic resonance imaging scans were acquired before the ECT course (baseline) and approximately 1 h after an ECT-induced seizure (postictal) to quantify global and regional gray matter cerebral blood flow (CBF). Seizure duration was assessed from the period of epileptiform discharges on the EEG. Healthy controls were scanned twice to assess test-retest variability. We performed hypothesis-driven Bayesian analyses to study the relation between global and regional perfusion changes and seizure duration. RESULTS: Twenty-four patients and 27 healthy controls were included. Changes in postictal global and regional CBF were correlated with seizure duration. In patients with longer seizure durations, global decrease in CBF reached values up to 28 mL/100 g/min. Regional reductions in CBF were most prominent in the inferior frontal gyrus, cingulate gyrus, and insula (up to 35 mL/100 g/min). In patients with shorter seizures, global and regional perfusion increased (up to 20 mL/100 g/min). These perfusion changes were larger than changes observed in healthy controls, with a maximum median global CBF increase of 12 mL/100 g/min and a maximum median global CBF decrease of 20 mL/100 g/min. SIGNIFICANCE: Seizure duration is a key factor determining postictal perfusion changes. In future studies, seizure duration needs to be considered as a confounding factor due to its opposite effect on postictal perfusion.

Feasibility and repeatability of ultrasound-guided surface electroenterography to measure colonic slow wave motility in healthy adults.

Surface electroenterography is a potential non-invasive alternative to current diagnostics of colonic motility disorders. However, electrode positioning in electroenterography is often based on general anatomy and may lack generalizability. Furthermore, the repeatability of electroenterography measurements is unknown. This study aimed to evaluate ultrasound-guided electrode positioning for electroenterography measurements and to determine the repeatability of those measurements. In ten healthy adults, two electroenterography procedures were performed, consisting of fasting, ultrasound-guided electrode localization and two 20-minute electroenterography recordings separated by a meal. The dominant frequency, the mean power density (magnitude of colonic motility) and the power percent difference (relative pre- to postprandial increase in magnitude) were determined. Repeatability was determined by Lin's concordance correlation coefficient. The results demonstrated that the dominant frequency did not differ between pre- and postprandial recordings and was 3 cpm, characteristic of colonic motility. The mean power density increased between the pre- and postprandial measurements, with an average difference of over 200%. The repeatability of both the dominant frequency and power density was poor to moderate, whereas the correlation coefficient of the power percent difference was poor. Concluding, ultrasound-guided surface electroenterography seems able to measure the gastrocolic reflex, but the dissatisfactory repeatability necessitates optimization of the measurement protocol.

Neurophysiological signatures of mild traumatic brain injury in the acute and subacute phase.

BACKGROUND: Mild traumatic brain injury (mTBI) affects 48 million people annually, with up to 30% experiencing long-term complaints such as fatigue, blurred vision, and poor concentration. Assessing neurophysiological features related to visual attention and outcome measures aids in understanding clinical symptoms and prognostication. METHODS: We recorded EEG and eye movements in mTBI patients during a computerized task performed in the acute (< 24 h, TBI-A) and subacute phase (4-6 weeks thereafter). We estimated the posterior dominant rhythm, reaction times (RTs), fixation duration, and event-related potentials (ERPs). Clinical outcome measures were assessed using the Head Injury Symptom Checklist (HISC) and the Extended Glasgow Outcome Scale (GOSE) at 6 months post-injury. Similar analyses were performed in an age-matched control group (measured once). Linear mixed effect modeling was used to examine group differences and temporal changes within the mTBI group. RESULTS: Twenty-nine patients were included in the acute phase, 30 in the subacute phase, and 19 controls. RTs and fixation duration were longer in mTBI patients compared to controls (p < 0.05), but not between TBI-A and TBI-S (p < 0.05). The frequency of the posterior dominant rhythm was significantly slower in TBI-A (0.6 Hz, p < 0.05) than TBI-S. ERP mean amplitude was significantly lower in mTBI patients than in controls. Neurophysiological features did not significantly relate to clinical outcome measures. CONCLUSION: mTBI patients demonstrate impaired processing speed and stimulus evaluation compared to controls, persisting up to 6 weeks after injury. Neurophysiological features in mTBI can assist in determining the extent and temporal progression of recovery.

The International Cardiac Arrest Research Consortium Electroencephalography Database.

OBJECTIVES: To develop the International Cardiac Arrest Research (I-CARE), a harmonized multicenter clinical and electroencephalography database for acute hypoxic-ischemic brain injury research involving patients with cardiac arrest. DESIGN: Multicenter cohort, partly prospective and partly retrospective. SETTING: Seven academic or teaching hospitals from the United States and Europe. PATIENTS: Individuals 16 years old or older who were comatose after return of spontaneous circulation following a cardiac arrest who had continuous electroencephalography monitoring were included. INTERVENTIONS: Not applicable. MEASUREMENTS AND MAIN RESULTS: Clinical and electroencephalography data were harmonized and stored in a common Waveform Database-compatible format. Automated spike frequency, background continuity, and artifact detection on electroencephalography were calculated with 10-second resolution and summarized hourly. Neurologic outcome was determined at 3-6 months using the best Cerebral Performance Category (CPC) scale. This database includes clinical data and 56,676 hours (3.9 terabytes) of continuous electroencephalography data for 1,020 patients. Most patients died ( n = 603, 59%), 48 (5%) had severe neurologic disability (CPC 3 or 4), and 369 (36%) had good functional recovery (CPC 1-2). There is significant variability in mean electroencephalography recording duration depending on the neurologic outcome (range, 53-102 hr for CPC 1 and CPC 4, respectively). Epileptiform activity averaging 1 Hz or more in frequency for at least 1 hour was seen in 258 patients (25%) (19% for CPC 1-2 and 29% for CPC 3-5). Burst suppression was observed for at least 1 hour in 207 (56%) and 635 (97%) patients with CPC 1-2 and CPC 3-5, respectively. CONCLUSIONS: The I-CARE consortium electroencephalography database provides a comprehensive real-world clinical and electroencephalography dataset for neurophysiology research of comatose patients after cardiac arrest. This dataset covers the spectrum of abnormal electroencephalography patterns after cardiac arrest, including epileptiform patterns and those in the ictal-interictal continuum.

Cortical excitation/inhibition ratios in patients with major depression treated with electroconvulsive therapy: an EEG analysis.

Electroconvulsive therapy (ECT) is an effective treatment for major depression, but its working mechanisms are poorly understood. Modulation of excitation/inhibition (E/I) ratios may be a driving factor. Here, we estimate cortical E/I ratios in depressed patients and study whether these ratios change over the course of ECT in relation to clinical effectiveness. Five-minute resting-state electroencephalography (EEG) recordings of 28 depressed patients were recorded before and after their ECT course. Using a novel method based on critical dynamics, functional E/I (fE/I) ratios in the frequency range of 0.5-30 Hz were estimated in frequency bins of 1 Hz for the whole brain and for pre-defined brain regions. Change in Hamilton Depression Rating Scale (HDRS) score was used to estimate clinical effectiveness. To account for test-retest variability, repeated EEG recordings from an independent sample of 31 healthy controls (HC) were included. At baseline, no differences in whole brain and regional fE/I ratios were found between patients and HC. At group level, whole brain and regional fE/I ratios did not change over the ECT course. However, in responders, frontal fE/I ratios in the frequencies 12-28 Hz increased significantly (pFDR < 0.05 [FDR = false discovery rate]) over the ECT course. In non-responders and HC, no changes occurred over time. In this sample, frontal fE/I ratios increased over the ECT course in relation to treatment response. Modulation of frontal fE/I ratios may be an important mechanism of action of ECT.

Ion dynamics at the energy-deprived tripartite synapse.

The anatomical and functional organization of neurons and astrocytes at 'tripartite synapses' is essential for reliable neurotransmission, which critically depends on ATP. In low energy conditions, synaptic transmission fails, accompanied by a breakdown of ion gradients, changes in membrane potentials and cell swelling. The resulting cellular damage and cell death are causal to the often devastating consequences of an ischemic stroke. The severity of ischemic damage depends on the age and the brain region in which a stroke occurs, but the reasons for this differential vulnerability are far from understood. In the present study, we address this question by developing a comprehensive biophysical model of a glutamatergic synapse to identify key determinants of synaptic failure during energy deprivation. Our model is based on fundamental biophysical principles, includes dynamics of the most relevant ions, i.e., Na+, K+, Ca2+, Cl- and glutamate, and is calibrated with experimental data. It confirms the critical role of the Na+/K+-ATPase in maintaining ion gradients, membrane potentials and cell volumes. Our simulations demonstrate that the system exhibits two stable states, one physiological and one pathological. During energy deprivation, the physiological state may disappear, forcing a transit to the pathological state, which can be reverted when blocking voltage-gated Na+ and K+ channels. Our model predicts that the transition to the pathological state is favoured if the extracellular space fraction is small. A reduction in the extracellular space volume fraction, as, e.g. observed with ageing, will thus promote the brain's susceptibility to ischemic damage. Our work provides new insights into the brain's ability to recover from energy deprivation, with translational relevance for diagnosis and treatment of ischemic strokes.

Transcranial magnetic stimulation as biomarker of excitability in drug development: A randomized, double-blind, placebo-controlled, cross-over study.

AIMS: The purpose of this study was to investigate pharmacodynamic effects of drugs targeting cortical excitability using transcranial magnetic stimulation (TMS) combined with electromyography (EMG) and electroencephalography (EEG) in healthy subjects, to further develop TMS outcomes as biomarkers for proof-of-mechanism in early-phase clinical drug development. Antiepileptic drugs presumably modulate cortical excitability. Therefore, we studied effects of levetiracetam, valproic acid and lorazepam on cortical excitability in a double-blind, placebo-controlled, 4-way cross-over study. METHODS: In 16 healthy male subjects, single- and paired-pulse TMS-EMG-EEG measurements were performed predose and 1.5, 7 and 24 hours postdose. Treatment effects on motor-evoked potential, short and long intracortical inhibition and TMS-evoked potential amplitudes, were analysed using a mixed model ANCOVA and cluster-based permutation analysis. RESULTS: We show that motor-evoked potential amplitudes decreased after administration of levetiracetam (estimated difference [ED] -378.4 µV; 95%CI: -644.3, -112.5 µV; P < .01), valproic acid (ED -268.8 µV; 95%CI: -532.9, -4.6 µV; P = .047) and lorazepam (ED -330.7 µV; 95%CI: -595.6, -65.8 µV; P = .02) when compared with placebo. Long intracortical inhibition was enhanced by levetiracetam (ED -60.3%; 95%CI: -87.1%, -33.5%; P < .001) and lorazepam (ED -68.2%; 95%CI: -94.7%, -41.7%; P < .001) at a 50-ms interstimulus interval. Levetiracetam increased TMS-evoked potential component N45 (P = .004) in a central cluster and decreased N100 (P < .001) in a contralateral cluster. CONCLUSION: This study shows that levetiracetam, valproic acid and lorazepam decrease cortical excitability, which can be detected using TMS-EMG-EEG in healthy subjects. These findings provide support for the use of TMS excitability measures as biomarkers to demonstrate pharmacodynamic effects of drugs that influence cortical excitability.

Can we learn from hidden mistakes? Self-fulfilling prophecy and responsible neuroprognostic innovation.

A self-fulfilling prophecy (SFP) in neuroprognostication occurs when a patient in coma is predicted to have a poor outcome, and life-sustaining treatment is withdrawn on the basis of that prediction, thus directly bringing about a poor outcome (viz. death) for that patient. In contrast to the predominant emphasis in the bioethics literature, we look beyond the moral issues raised by the possibility that an erroneous prediction might lead to the death of a patient who otherwise would have lived. Instead, we focus on the problematic epistemic consequences of neuroprognostic SFPs in settings where research and practice intersect. When this sort of SFP occurs, the problem is that physicians and researchers are never in a position to notice whether their original prognosis was correct or incorrect, since the patient dies anyway. Thus, SFPs keep us from discerning false positives from true positives, inhibiting proper assessment of novel prognostic tests. This epistemic problem of SFPs thus impedes learning, but ethical obligations of patient care make it difficult to avoid SFPs. We then show how the impediment to catching false positive indicators of poor outcome distorts research on novel techniques for neuroprognostication, allowing biases to persist in prognostic tests. We finally highlight a particular risk that a precautionary bias towards early withdrawal of life-sustaining treatment may be amplified. We conclude with guidelines about how researchers can mitigate the epistemic problems of SFPs, to achieve more responsible innovation of neuroprognostication for patients in coma.

Outcome Prediction of Postanoxic Coma: A Comparison of Automated Electroencephalography Analysis Methods.

BACKGROUND: To compare three computer-assisted quantitative electroencephalography (EEG) prediction models for the outcome prediction of comatose patients after cardiac arrest regarding predictive performance and robustness to artifacts. METHODS: A total of 871 continuous EEGs recorded up to 3 days after cardiac arrest in intensive care units of five teaching hospitals in the Netherlands were retrospectively analyzed. Outcome at 6 months was dichotomized as "good" (Cerebral Performance Category 1-2) or "poor" (Cerebral Performance Category 3-5). Three prediction models were implemented: a logistic regression model using two quantitative features, a random forest model with nine features, and a deep learning model based on a convolutional neural network. Data from two centers were used for training and fivefold cross-validation (n = 663), and data from three other centers were used for external validation (n = 208). Model output was the probability of good outcome. Predictive performances were evaluated by using receiver operating characteristic analysis and the calculation of predictive values. Robustness to artifacts was evaluated by using an artifact rejection algorithm, manually added noise, and randomly flattened channels in the EEG. RESULTS: The deep learning network showed the best overall predictive performance. On the external test set, poor outcome could be predicted by the deep learning network at 24 h with a sensitivity of 54% (95% confidence interval [CI] 44-64%) at a false positive rate (FPR) of 0% (95% CI 0-2%), significantly higher than the logistic regression (sensitivity 33%, FPR 0%) and random forest models (sensitivity 13%, FPR, 0%) (p < 0.05). Good outcome at 12 h could be predicted by the deep learning network with a sensitivity of 78% (95% CI 52-100%) at a FPR of 12% (95% CI 0-24%) and by the logistic regression model with a sensitivity of 83% (95% CI 83-83%) at a FPR of 3% (95% CI 3-3%), both significantly higher than the random forest model (sensitivity 1%, FPR 0%) (p < 0.05). The results of the deep learning network were the least affected by the presence of artifacts, added white noise, and flat EEG channels. CONCLUSIONS: A deep learning model outperformed logistic regression and random forest models for reliable, robust, EEG-based outcome prediction of comatose patients after cardiac arrest.

The Association between Hypoxia-Induced Low Activity and Apoptosis Strongly Resembles That between TTX-Induced Silencing and Apoptosis.

In the penumbra of a brain infarct, neurons initially remain structurally intact, but perfusion is insufficient to maintain neuronal activity at physiological levels. Improving neuronal recovery in the penumbra has large potential to advance recovery of stroke patients, but penumbral pathology is incompletely understood, and treatments are scarce. We hypothesize that low activity in the penumbra is associated with apoptosis and thus contributes to irreversible neuronal damage. We explored the putative relationship between low neuronal activity and apoptosis in cultured neurons exposed to variable durations of hypoxia or TTX. We combined electrophysiology and live apoptosis staining in 42 cultures, and compared effects of hypoxia and TTX silencing in terms of network activity and apoptosis. Hypoxia rapidly reduced network activity, but cultures showed limited apoptosis during the first 12 h. After 24 h, widespread apoptosis had occurred. This was associated with full activity recovery observed upon reoxygenation within 12 h, but not after 24 h. Similarly, TTX exposure strongly reduced activity, with full recovery upon washout within 12 h, but not after 24 h. Mean temporal evolution of apoptosis in TTX-treated cultures was the same as in hypoxic cultures. These results suggest that prolonged low activity may be a common factor in the pathways towards apoptosis.

Dysregulation of Astrocyte Ion Homeostasis and Its Relevance for Stroke-Induced Brain Damage.

Ischemic stroke is a leading cause of mortality and chronic disability. Either recovery or progression towards irreversible failure of neurons and astrocytes occurs within minutes to days, depending on remaining perfusion levels. Initial damage arises from energy depletion resulting in a failure to maintain homeostasis and ion gradients between extra- and intracellular spaces. Astrocytes play a key role in these processes and are thus central players in the dynamics towards recovery or progression of stroke-induced brain damage. Here, we present a synopsis of the pivotal functions of astrocytes at the tripartite synapse, which form the basis of physiological brain functioning. We summarize the evidence of astrocytic failure and its consequences under ischemic conditions. Special emphasis is put on the homeostasis and stroke-induced dysregulation of the major monovalent ions, namely Na+, K+, H+, and Cl-, and their involvement in maintenance of cellular volume and generation of cerebral edema.

Electroencephalographic reactivity as predictor of neurological outcome in postanoxic coma: A multicenter prospective cohort study.

OBJECTIVE: Outcome prediction in patients after cardiac arrest (CA) is challenging. Electroencephalographic reactivity (EEG-R) might be a reliable predictor. We aimed to determine the prognostic value of EEG-R using a standardized assessment. METHODS: In a prospective cohort study, a strictly defined EEG-R assessment protocol was executed twice per day in adult patients after CA. EEG-R was classified as present or absent by 3 EEG readers, blinded to patient characteristics. Uncertain reactivity was classified as present. Primary outcome was best Cerebral Performance Category score (CPC) in 6 months after CA, dichotomized as good (CPC = 1-2) or poor (CPC = 3-5). EEG-R was considered reliable for predicting poor outcome if specificity was ≥95%. For good outcome prediction, a specificity of ≥80% was used. Added value of EEG-R was the increase in specificity when combined with EEG background, neurological examination, and somatosensory evoked potentials (SSEPs). RESULTS: Of 160 patients enrolled, 149 were available for analyses. Absence of EEG-R for poor outcome prediction had a specificity of 82% and a sensitivity of 73%. For good outcome prediction, specificity was 73% and sensitivity 82%. Specificity for poor outcome prediction increased from 98% to 99% when EEG-R was added to a multimodal model. For good outcome prediction, specificity increased from 70% to 89%. INTERPRETATION: EEG-R testing in itself is not sufficiently reliable for outcome prediction in patients after CA. For poor outcome prediction, it has no substantial added value to EEG background, neurological examination, and SSEPs. For prediction of good outcome, EEG-R seems to have added value. ANN NEUROL 2019.

Early electroencephalography for outcome prediction of postanoxic coma: A prospective cohort study.

OBJECTIVE: To provide evidence that early electroencephalography (EEG) allows for reliable prediction of poor or good outcome after cardiac arrest. METHODS: In a 5-center prospective cohort study, we included consecutive, comatose survivors of cardiac arrest. Continuous EEG recordings were started as soon as possible and continued up to 5 days. Five-minute EEG epochs were assessed by 2 reviewers, independently, at 8 predefined time points from 6 hours to 5 days after cardiac arrest, blinded for patients' actual condition, treatment, and outcome. EEG patterns were categorized as generalized suppression (<10 µV), synchronous patterns with ≥50% suppression, continuous, or other. Outcome at 6 months was categorized as good (Cerebral Performance Category [CPC] = 1-2) or poor (CPC = 3-5). RESULTS: We included 850 patients, of whom 46% had a good outcome. Generalized suppression and synchronous patterns with ≥50% suppression predicted poor outcome without false positives at ≥6 hours after cardiac arrest. Their summed sensitivity was 0.47 (95% confidence interval [CI] = 0.42-0.51) at 12 hours and 0.30 (95% CI = 0.26-0.33) at 24 hours after cardiac arrest, with specificity of 1.00 (95% CI = 0.99-1.00) at both time points. At 36 hours or later, sensitivity for poor outcome was ≤0.22. Continuous EEG patterns at 12 hours predicted good outcome, with sensitivity of 0.50 (95% CI = 0.46-0.55) and specificity of 0.91 (95% CI = 0.88-0.93); at 24 hours or later, specificity for the prediction of good outcome was <0.90. INTERPRETATION: EEG allows for reliable prediction of poor outcome after cardiac arrest, with maximum sensitivity in the first 24 hours. Continuous EEG patterns at 12 hours after cardiac arrest are associated with good recovery. ANN NEUROL 2019;86:203-214.

The postictal state - What do we know?

This narrative review provides a broad and comprehensive overview of the most important discoveries on the postictal state over the past decades as well as recent developments. After a description and definition of the postictal state, we discuss postictal sypmtoms, their clinical manifestations, and related findings. Moreover, pathophysiological advances are reviewed, followed by current treatment options.

Spatiotemporal Dynamics of Single and Paired Pulse TMS-EEG Responses.

For physiological brain function a particular balance between excitation and inhibition is essential. Paired pulse transcranial magnetic stimulation (TMS) can estimate cortical excitability and the relative contribution of inhibitory and excitatory networks. Combining TMS with electroencephalography (EEG) enables additional assessment of the spatiotemporal dynamics of neuronal responses in the stimulated brain. This study aims to evaluate the spatiotemporal dynamics and stability of single and paired pulse TMS-EEG responses, and assess long intracortical inhibition (LICI) at the cortical level. Twenty-five healthy subjects were studied twice, approximately one week apart. Manual coil positioning was applied in sixteen subjects and robot-guided positioning in nine. Both motor cortices were stimulated with 50 single pulses and 50 paired pulses at each of the five interstimulus intervals (ISIs): 100, 150, 200, 250 and 300 ms. To assess stability and LICI, the intraclass correlation coefficient and cluster-based permutation analysis were used. We found great resemblance in the topographical distribution of the characteristic TMS-EEG components for single and paired pulse TMS. Stimulation of the dominant and non-dominant hemisphere resulted in a mirrored spatiotemporal dynamics. No significant effect on the TMS-EEG responses was found for either stimulated hemisphere, time or coil positioning method, indicating the stability of both single and paired pulse TMS-EEG responses. For all ISIs, LICI was characterized by significant suppression of the late N100 and P180 components in the central areas, without affecting the early P30, N45 and P60 components. These observations in healthy subjects can serve as reference values for future neuropsychiatric and pharmacological studies.

Absence epilepsy: Characteristics, pathophysiology, attention impairments, and the related risk of accidents. A narrative review.

OBJECTIVE: Absence epilepsy (AE) is related to both cognitive and physical impairments. In this narrative review, we critically discuss the pathophysiology of AE and the impairment of attention in children and adolescents with AE. In particular, we contextualize the attentive dysfunctions of AE with the associated risks, such as accidental injuries. DATA SOURCE: An extensive literature search on attention deficits and the rate of accidental injuries in AE was run. The search was conducted on Scopus, Pubmed, and the online libraries of the University of Twente and Maastricht University. Relevant references of the included articles were added. Retrospective and prospective studies, case reports, meta-analysis, and narrative reviews were included. Only studies written in English were considered. Date of last search is February 2020. The keywords used were "absence epilepsy" AND "attention"/"awareness", "absence epilepsy" AND "accidental injuries"/"accident*"/"injuries". RESULTS: Ten retrospective and two prospective studies on cognition and AE were fully screened. Seventeen papers explicitly referring to attention in AE were reviewed. Just one paper was found to specifically focus on accidental injuries and AE, while twelve studies generally referring to epilepsy syndromes - among which AE - and related accidents were included. CONCLUSION: Absence epilepsy and attention deficits show some patterns of pathophysiological association. This relation may account for dysfunctions in everyday activities in the pediatric population. Particular metrics, such as the risk related to biking in children with AE, should be used in future studies to address the problem in a novel way and to impact clinical indications.

Cross-scale effects of neural interactions during human neocortical seizure activity.

Small-scale neuronal networks may impose widespread effects on large network dynamics. To unravel this relationship, we analyzed eight multiscale recordings of spontaneous seizures from four patients with epilepsy. During seizures, multiunit spike activity organizes into a submillimeter-sized wavefront, and this activity correlates significantly with low-frequency rhythms from electrocorticographic recordings across a 10-cm-sized neocortical network. Notably, this correlation effect is specific to the ictal wavefront and is absent interictally or from action potential activity outside the wavefront territory. To examine the multiscale interactions, we created a model using a multiscale, nonlinear system and found evidence for a dual role for feedforward inhibition in seizures: while inhibition at the wavefront fails, allowing seizure propagation, feedforward inhibition of the surrounding centimeter-scale networks is activated via long-range excitatory connections. Bifurcation analysis revealed that distinct dynamical pathways for seizure termination depend on the surrounding inhibition strength. Using our model, we found that the mesoscopic, local wavefront acts as the forcing term of the ictal process, while the macroscopic, centimeter-sized network modulates the oscillatory seizure activity.

Infraslow activity as a potential modulator of corticomotor excitability.

Fluctuations in cortical excitability are a candidate mechanism involved in the trial-to-trial variation of motor evoked potentials (MEPs) to transcranial magnetic stimulation (TMS). We explore whether infraslow EEG activity (<0.1 Hz) modulates corticomotor excitability by evaluating the presence of temporal and phase clustering of TMS-induced MEPs. In addition, we evaluate the dependence of MEP amplitude on the phase of the infraslow activity. Twenty-three subjects were stimulated at an intensity above the resting motor threshold (rMT) and ten at the rMT. We evaluated whether temporal and phase clustering of MEP size and MEP generation were present, using 1,000 surrogates with a similar amplitude or occurrence distribution. To evaluate the MEP amplitude dependence, we used the least-square method to approximate the linear circular data by fitting a sine function. We observed significant temporal clustering at a group level, in all individual subjects stimulated at rMT and in the majority of those stimulated above rMT, suggesting underlying determinism of corticomotor excitability instead of randomly generated fluctuations. The majority of subjects showed significant phase clustering for MEP size and for MEP occurrence, and significant phase clustering was found at the group level. Furthermore, in approximately one-quarter to one-half of the subjects we found a significant correlation and dependence of MEP amplitude on the phase of infraslow activity, respectively. Although other mechanisms very likely contribute as well, our findings seem to suggest that infraslow activity is involved in the variability of cortical excitability and TMS-induced responses. NEW & NOTEWORTHY Cortical excitability measures are highly variable during transcranial magnetic stimulation. Although ongoing brain oscillations are assumed to modulate excitability, no consistent associations are found for the traditional frequency bands. We focus on the role of infraslow EEG activity, defined as rhythms with frequencies < 0.1 Hz. We provide experimental evidence suggesting that infraslow activity most likely modulates corticomotor excitability and that response variation could be reduced when stimulation is targeted at a specific infraslow phase.

Simulating perinodal changes observed in immune-mediated neuropathies: impact on conduction in a model of myelinated motor and sensory axons.

Immune-mediated neuropathies affect myelinated axons, resulting in conduction slowing or block that may affect motor and sensory axons differently. The underlying mechanisms of these neuropathies are not well understood. Using a myelinated axon model, we studied the impact of perinodal changes on conduction. We extended a longitudinal axon model (41 nodes of Ranvier) with biophysical properties unique to human myelinated motor and sensory axons. We simulated effects of temperature and axonal diameter on conduction and strength-duration properties. We then studied effects of impaired nodal sodium channel conductance and paranodal myelin detachment by reducing periaxonal resistance, as well as their interaction, on conduction in the 9 middle nodes and enclosed paranodes. Finally, we assessed the impact of reducing the affected region (5 nodes) and adding nodal widening. Physiological motor and sensory conduction velocities and changes to axonal diameter and temperature were observed. The sensory axon had a longer strength-duration time constant. Reducing sodium channel conductance and paranodal periaxonal resistance induced progressive conduction slowing. In motor axons, conduction block occurred with a 4-fold drop in sodium channel conductance or a 7.7-fold drop in periaxonal resistance. In sensory axons, block arose with a 4.8-fold drop in sodium channel conductance or a 9-fold drop in periaxonal resistance. This indicated that motor axons are more vulnerable to developing block. A boundary of block emerged when the two mechanisms interacted. This boundary shifted in opposite directions for a smaller affected region and nodal widening. These differences may contribute to the predominance of motor deficits observed in some immune-mediated neuropathies.NEW & NOTEWORTHY Immune-mediated neuropathies may affect myelinated motor and sensory axons differently. By the development of a computational model, we quantitatively studied the impact of perinodal changes on conduction in motor and sensory axons. Simulations of increasing nodal sodium channel dysfunction and paranodal myelin detachment induced progressive conduction slowing. Sensory axons were more resistant to block than motor axons. This could explain the greater predisposition of motor axons to functional deficits observed in some immune-mediated neuropathies.