Rapid eye movement sleep and epilepsy: exploring interactions and therapeutic prospects.

While research interest in the relationship between sleep and epilepsy is growing, it primarily centres on the effects of non-rapid eye movement (NREM) sleep in favouring seizures. Nonetheless, a noteworthy aspect is the observation that, in the lives of patients with epilepsy, REM sleep represents the moment with the least epileptic activity and the lowest probability of having a seizure. Studies demonstrate a suppressive effect of phasic REM sleep on interictal epileptiform discharges, potentially offering insights into epilepsy localisation and management. Furthermore, epilepsy impacts REM sleep, with successful treatment correlating with improved REM sleep quality. Novel therapeutic strategies aim to harness REM's anti-epileptic effects, including pharmacological approaches targeting orexinergic systems and neuromodulation techniques promoting cortical desynchronisation. These findings underscore the intricate relationship between REM sleep and epilepsy, highlighting avenues for further research and therapeutic innovation in epilepsy management.

The challenges of treating status epilepticus in rural Canada.

Though unified by challenges in the treatment of status epilepticus (SE), rural Canada is simultaneously massive and diverse, spanning the Pacific, Atlantic, and Arctic Oceans. According to the national statistical agency, the most rural jurisdiction in Canada is the Arctic territory of Nunavut. In particular, the Kivalliq region of Nunavut represents a unique epidemiologic SE space because any treatment beyond typical first-line lorazepam and second-line phenytoin by a non-neurologist locum tenens requires airborne evacuation over a thousand kilometers away to a single hospital with a single electroencephalographic (EEG) laboratory. This distinctive mode of healthcare delivery affords unique insights into the challenges of treating SE in rural Canada, such as lack of EEG infrastructure, a markedly high incidence of SE, the struggles of enduring cultural and socioeconomic trauma, and a relative lack of local epilepsy care as recommended by the World Health Organization. For example, despite empiric treatment and waiting over 2 days on average for EEG, 1 in 5 patients still had ongoing or possible electrographic seizures. At the same time, Kivalliq experiences routine dramatic changes in light-dark exposure each year to afford unique insights into circannual SE chronobiology in relation to the chief human zeitgeber of sunlight. This shows that challenges may also represent opportunities, such as for existing and emerging technologies to synergistically address enormous treatment gaps to improve SE care for the people of Kivalliq, while providing novel insights that may also help improve SE clinical care around the world.

High-definition transcranial direct current stimulation desynchronizes refractory status epilepticus.

Recently, we showed that high-definition transcranial direct current stimulation (hd-tDCS) can acutely reduce epileptic spike rates during and after stimulation in refractory status epilepticus (RSE), with a greater likelihood of patient discharge from the intensive care unit compared to historical controls. We investigate whether electroencephalographic (EEG) desynchronization during hd-tDCS can help account for observed anti-epileptic effects. Defining desynchronization as greater power in higher frequencies such as above 30 â€‹Hz ("gamma") and lesser power in frequency bands lower than 30 â€‹Hz, we analyzed 27 EEG sessions from 10 RSE patients who had received 20-minute session(s) of 2-milliamperes of transcranial direct current custom-targeted at the epileptic focus as previously determined by a clinical EEGer monitoring the EEG in real-time. During hd-tDCS, median relative power change over the EEG electrode chains in which power changes were maximal was +4.84%, -5.25%, -1.88%, -1.94%, and +4.99% for respective delta, theta, alpha, beta, and gamma frequency bands in the bipolar longitudinal montage (p â€‹= â€‹0.0001); and +4.13%, -5.44%, -1.81%, -3.23%, and +5.41% in the referential Laplacian montage (p â€‹= â€‹0.0012). After hd-tDCS, median relative power changes reversed over the EEG electrode chains in which power changes were maximal: -2.74%, +4.20%, +1.74%, +1.75%, and -4.68% for the respective delta, theta, alpha, beta, and gamma frequency bands in the bipolar longitudinal montage (p â€‹= â€‹0.0001); and +1.59%, +5.07%, +1.74%, +2.40%, and -5.12% in the referential Laplacian montage (p â€‹= â€‹0.0004). These findings are consistent with EEG desynchronization through theta-alpha-beta-gamma bands during hd-tDCS, helping account for the efficacy of hd-tDCS as an emerging novel anti-epileptic therapy against RSE.

A programmable hybrid digital chemical information processor based on the Belousov-Zhabotinsky reaction.

The exponential growth of the power of modern digital computers is based upon the miniaturization of vast nanoscale arrays of electronic switches, but this will be eventually constrained by fabrication limits and power dissipation. Chemical processes have the potential to scale beyond these limits by performing computations through chemical reactions, yet the lack of well-defined programmability limits their scalability and performance. Here, we present a hybrid digitally programmable chemical array as a probabilistic computational machine that uses chemical oscillators using Belousov-Zhabotinsky reaction partitioned in interconnected cells as a computational substrate. This hybrid architecture performs efficient computation by distributing information between chemical and digital domains together with inbuilt error correction logic. The efficiency is gained by combining digital logic with probabilistic chemical logic based on nearest neighbour interactions and hysteresis effects. We demonstrated the computational capabilities of our hybrid processor by implementing one- and two-dimensional Chemical Cellular Automata demonstrating emergent dynamics of life-like entities called Chemits. Additionally, we demonstrate hybrid probabilistic logic as a viable logic for solving combinatorial optimization problems.

Residual Seizure Rate of Intermittent Inpatient EEG Compared to a Continuous EEG Model.

BACKGROUND: Subclinical seizures are common in hospitalized patients and require electroencephalography (EEG) for detection and intervention. At our institution, continuous EEG (cEEG) is not available, but intermittent EEGs are subject to constant live interpretation. As part of quality improvement (QI), we sought to estimate the residual missed seizure rate at a typical quaternary Canadian health care center without cEEG. METHODS: We calculated residual risk percentages using the clinically validated 2HELPS2B score to risk-stratify EEGs before deriving a risk percentage using a MATLAB calculator which modeled the risk decay curve for each recording. We generated a range of estimated residual seizure rates depending on whether a pre-cEEG screening EEG was simulated, EEGs showing seizures were included, or repeat EEGs on the same patient were excluded. RESULTS: Over a 4-month QI period, 499 inpatient EEGs were scored as low (n = 125), medium (n = 123), and high (n = 251) seizure risk according to 2HELPS2B criteria. Median recording duration was 1:00:06 (interquartile range, IQR 30:40-2:21:10). The model with highest residual seizure rate included recordings with confirmed electrographic seizures (median 20.83%, IQR 20.6-26.6%), while the model with lowest residual seizure rate was in seizure-free recordings (median 10.59%, IQR 4%-20.6%). These rates were significantly higher than the benchmark 5% miss-rate threshold set by 2HELPS2B (p<0.0001). CONCLUSIONS: We estimate that intermittent inpatient EEG misses 2-4 times more subclinical seizures than the 2HELPS2B-determined acceptable 5% seizure miss-rate threshold for cEEG. Future research is needed to determine the impact of potentially missed seizures on clinical care.

Circannual seizure provocation as the day lengthens in the northern and southern hemispheres.

Circannual status epilepticus (SE) patterns in communities near Earth's poles best test the hypothesis that SE susceptibility varies with light exposure because these communities are routinely subject to large changes in annual light exposure, which may result in changes to daily sleep time. We compared northern hemispheric circannual SE occurrence in Kivalliq, Canada (latitude-62.8° N) to southern hemispheric Auckland, New Zealand (latitude-36.9° S). Instead of peaking at a similar calendar time, SE peaked at a similar solar time during the increasing daylight phase after each region's respective winter solstice. This demonstrates that cumulative effects of increasing light exposure can mediate SE susceptibility.

On-demand EEG education through competition - A novel, app-based approach to learning to identify interictal epileptiform discharges.

Objective: Misinterpretation of EEGs harms patients, yet few resources exist to help trainees practice interpreting EEGs. We therefore sought to evaluate a novel educational tool to teach trainees how to identify interictal epileptiform discharges (IEDs) on EEG. Methods: We created a public EEG test within the iOS app DiagnosUs using a pool of 13,262 candidate IEDs. Users were shown a candidate IED on EEG and asked to rate it as epileptiform (IED) or not (non-IED). They were given immediate feedback based on a gold standard. Learning was analyzed using a parametric model. We additionally analyzed IED features that best correlated with expert ratings. Results: Our analysis included 901 participants. Users achieved a mean improvement of 13% over 1,000 questions and an ending accuracy of 81%. Users and experts appeared to rely on a similar set of IED morphologic features when analyzing candidate IEDs. We additionally identified particular types of candidate EEGs that remained challenging for most users even after substantial practice. Conclusions: Users improved in their ability to properly classify candidate IEDs through repeated exposure and immediate feedback. Significance: This app-based learning activity has great potential to be an effective supplemental tool to teach neurology trainees how to accurately identify IEDs on EEG.

Do Epilepsy Patients with Cognitive Impairment Have Alzheimer's Disease-like Brain Metabolism?

Although not classically considered together, there is emerging evidence that Alzheimer's disease (AD) and epilepsy share a number of features and that each disease predisposes patients to developing the other. Using machine learning, we have previously developed an automated fluorodeoxyglucose positron emission tomography (FDG-PET) reading program (i.e., MAD), and demonstrated good sensitivity (84%) and specificity (95%) for differentiating AD patients versus healthy controls. In this retrospective chart review study, we investigated if epilepsy patients with/without mild cognitive symptoms also show AD-like metabolic patterns determined by the MAD algorithm. Scans from a total of 20 patients with epilepsy were included in this study. Because AD diagnoses are made late in life, only patients aged ≥40 years were considered. For the cognitively impaired patients, four of six were identified as MAD+ (i.e., the FDG-PET image is classified as AD-like by the MAD algorithm), while none of the five cognitively normal patients was identified as MAD+ (χ2 = 8.148, p = 0.017). These results potentially suggest the usability of FDG-PET in prognosticating later dementia development in non-demented epilepsy patients, especially when combined with machine learning algorithms. A longitudinal follow-up study is warranted to assess the effectiveness of this approach.

Coexpression of anticipatory and consummatory volitional deficits in schizophrenia and their association with memory impairment.

Avolition in schizophrenia has been attributed to the decoupling between emotion and motivation rather than an inability to perceive or distinguish emotions. Hence, goal-directed behavior incentivized by positive or negative reinforcement becomes impoverished and dull. It is further suggested that goal-directed actions directed at future outcomes (anticipatory or representational response) are preferentially affected, as opposed to actions directed to the current state of affairs (consummatory or evoked response). Attempts to dissociate them behaviorally using the "anticipatory and consummatory pleasure" (ACP) task have demonstrated deficits in both components, yet some have claimed otherwise. In this replication study, we presented further characterization of the pronounced deficits in valence-dependent consummatory as well as anticipatory responding in 40 subjects with schizophrenia in comparison with 42 healthy subjects. In addition, two novel observations were made. First, the correlation between ratings of emotional intensity and arousal levels of pictures used to motivate responding in the ACP task was markedly attenuated in the schizophrenic (SZ) group, suggesting that the decoupling from emotion may be manifested beyond goal-directed behavior in schizophrenia. Second, multiple correlations between ACP performance indices and individual scores in the letter-number span test were uniquely observed in the SZ group, not among healthy controls. The co-emergence of ACP and working memory deficiency in SZ may be linked to common psychopathological processes. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Antiseizure medication use during pregnancy and neonatal growth outcomes: A systematic review and meta-analysis.

AIMS: We aimed to systematically synthesize the current published literature on neonatal growth outcomes associated with antiseizure medication (ASM) use during pregnancy. METHODS: We searched seven databases, from inception to 23 March 2022. We investigated small for gestational age (SGA) and low birth weight (LBW) as primary outcomes and birth weight, birth height, cephalization index and head circumference as secondary outcomes. The primary analysis included pregnant people exposed to any ASM compared with unexposed pregnant people. Subgroup analysis included ASM class analysis, within epilepsy group analysis and polytherapy compared to monotherapy. RESULTS: We screened 15 720 citations and included 65 studies in the review. Exposed pregnant people had a significantly increased risk of SGA relative risk (RR) 1.33 (95% CI 1.18 to 1.50, I2 74%), LBW RR 1.54 (95% CI 1.33 to 1.77, I2 67%), and decreased birth weight with a mean difference (MD) of -118.87 (95% CI -161.03 to -76.71, I2 42%) g. A non-significant risk change in birth height and head circumference was observed. In subgroup analysis, ASM polytherapy, within epilepsy and ASM class analysis were also associated with an increased risk of SGA and LBW. CONCLUSIONS: This meta-analysis demonstrates that pregnant people exposed to ASMs have a significantly increased risk of adverse fetal growth outcomes including SGA and LBW and decreased birth weight compared to unexposed pregnant people. Polytherapy was associated with higher risks compared to monotherapy. Additional studies are warranted on specific ASM risks.

Development of Expert-Level Classification of Seizures and Rhythmic and Periodic Patterns During EEG Interpretation.

BACKGROUND AND OBJECTIVES: Seizures (SZs) and other SZ-like patterns of brain activity can harm the brain and contribute to in-hospital death, particularly when prolonged. However, experts qualified to interpret EEG data are scarce. Prior attempts to automate this task have been limited by small or inadequately labeled samples and have not convincingly demonstrated generalizable expert-level performance. There exists a critical unmet need for an automated method to classify SZs and other SZ-like events with expert-level reliability. This study was conducted to develop and validate a computer algorithm that matches the reliability and accuracy of experts in identifying SZs and SZ-like events, known as "ictal-interictal-injury continuum" (IIIC) patterns on EEG, including SZs, lateralized and generalized periodic discharges (LPD, GPD), and lateralized and generalized rhythmic delta activity (LRDA, GRDA), and in differentiating these patterns from non-IIIC patterns. METHODS: We used 6,095 scalp EEGs from 2,711 patients with and without IIIC events to train a deep neural network, SPaRCNet, to perform IIIC event classification. Independent training and test data sets were generated from 50,697 EEG segments, independently annotated by 20 fellowship-trained neurophysiologists. We assessed whether SPaRCNet performs at or above the sensitivity, specificity, precision, and calibration of fellowship-trained neurophysiologists for identifying IIIC events. Statistical performance was assessed by the calibration index and by the percentage of experts whose operating points were below the model's receiver operating characteristic curves (ROCs) and precision recall curves (PRCs) for the 6 pattern classes. RESULTS: SPaRCNet matches or exceeds most experts in classifying IIIC events based on both calibration and discrimination metrics. For SZ, LPD, GPD, LRDA, GRDA, and "other" classes, SPaRCNet exceeds the following percentages of 20 experts-ROC: 45%, 20%, 50%, 75%, 55%, and 40%; PRC: 50%, 35%, 50%, 90%, 70%, and 45%; and calibration: 95%, 100%, 95%, 100%, 100%, and 80%, respectively. DISCUSSION: SPaRCNet is the first algorithm to match expert performance in detecting SZs and other SZ-like events in a representative sample of EEGs. With further development, SPaRCNet may thus be a valuable tool for an expedited review of EEGs. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that among patients with epilepsy or critical illness undergoing EEG monitoring, SPaRCNet can differentiate (IIIC) patterns from non-IIIC events and expert neurophysiologists.

A Pilot Study of High-Definition Transcranial Direct Current Stimulation in Refractory Status Epilepticus: The SURESTEP Trial.

Refractory status epilepticus (RSE) is a life-threatening emergency with high mortality and poor functional outcomes in survivors. Treatment is typically limited to intravenous anesthetic infusions and multiple anti-seizure medications. While ongoing seizures can cause permanent neurological damage, medical therapies also pose severe and life-threatening side effects. We tested the feasibility of using high-definition transcranial direct current stimulation (hd-tDCS) in the treatment of RSE. We conducted 20-min hd-tDCS sessions at an outward field orientation, intensity of 2-mA, 4 + 1 channels, and customized for deployment over the electrographic maximum of epileptiform activity ("spikes") determined by real-time clinical EEG monitoring. There were no adverse events from 32 hd-tDCS sessions in 10 RSE patients. Over steady dosing states of infusions and medications in 29 included sessions, median spike rates/patient fell by 50% during hd-tDCS on both automated (p = 0.0069) and human (p = 0.0277) spike counting. Median spike rates for any given stimulation session also fell by 50% during hd-tDCS on automated spike counting (p = 0.0032). Immediately after hd-tDCS, median spike rates/patient remained down by 25% on human spike counting (p = 0.018). Compared to historical controls, hd-tDCS subjects were successfully discharged from the intensive care unit (ICU) 45.8% more often (p = 0.004). When controls were selected using propensity score matching, the discharge rate advantage improved to 55% (p = 0.002). Customized EEG electrode targeting of hd-tDCS is a safe and non-invasive method of hyperacutely reducing epileptiform activity in RSE. Compared to historical controls, there was evidence of a cumulative chronic clinical response with more hd-tDCS subjects discharged from ICU.

Interrater Reliability of Expert Electroencephalographers Identifying Seizures and Rhythmic and Periodic Patterns in EEGs.

BACKGROUND AND OBJECTIVES: The validity of brain monitoring using electroencephalography (EEG), particularly to guide care in patients with acute or critical illness, requires that experts can reliably identify seizures and other potentially harmful rhythmic and periodic brain activity, collectively referred to as "ictal-interictal-injury continuum" (IIIC). Previous interrater reliability (IRR) studies are limited by small samples and selection bias. This study was conducted to assess the reliability of experts in identifying IIIC. METHODS: This prospective analysis included 30 experts with subspecialty clinical neurophysiology training from 18 institutions. Experts independently scored varying numbers of ten-second EEG segments as "seizure (SZ)," "lateralized periodic discharges (LPDs)," "generalized periodic discharges (GPDs)," "lateralized rhythmic delta activity (LRDA)," "generalized rhythmic delta activity (GRDA)," or "other." EEGs were performed for clinical indications at Massachusetts General Hospital between 2006 and 2020. Primary outcome measures were pairwise IRR (average percent agreement [PA] between pairs of experts) and majority IRR (average PA with group consensus) for each class and beyond chance agreement (κ). Secondary outcomes were calibration of expert scoring to group consensus, and latent trait analysis to investigate contributions of bias and noise to scoring variability. RESULTS: Among 2,711 EEGs, 49% were from women, and the median (IQR) age was 55 (41) years. In total, experts scored 50,697 EEG segments; the median [range] number scored by each expert was 6,287.5 [1,002, 45,267]. Overall pairwise IRR was moderate (PA 52%, κ 42%), and majority IRR was substantial (PA 65%, κ 61%). Noise-bias analysis demonstrated that a single underlying receiver operating curve can account for most variation in experts' false-positive vs true-positive characteristics (median [range] of variance explained ([Formula: see text]): 95 [93, 98]%) and for most variation in experts' precision vs sensitivity characteristics ([Formula: see text]: 75 [59, 89]%). Thus, variation between experts is mostly attributable not to differences in expertise but rather to variation in decision thresholds. DISCUSSION: Our results provide precise estimates of expert reliability from a large and diverse sample and a parsimonious theory to explain the origin of disagreements between experts. The results also establish a standard for how well an automated IIIC classifier must perform to match experts. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that an independent expert review reliably identifies ictal-interictal injury continuum patterns on EEG compared with expert consensus.

Kinetic Trapping of Photoluminescent Frameworks During High-Concentration Synthesis of Non-Emissive Metal-Organic Frameworks.

Metal-organic frameworks (MOFs) are porous, crystalline materials constructed from organic linkers and inorganic nodes with potential utility in gas separations, drug delivery, sensing, and catalysis. Small variations in MOF synthesis conditions can lead to a range of accessible frameworks with divergent chemical or photophysical properties. New methods to controllably access phases with tailored properties would broaden the scope of MOFs that can be reliably prepared for specific applications. Herein, we demonstrate that simply increasing the reaction concentration during the solvothermal synthesis of M2(dobdc) (M = Mg, Mn, Ni; dobdc4- = 2,5-dioxido-1,4-benzenedicarboxylate) MOFs unexpectedly leads to trapping of a new framework termed CORN-MOF-1 (CORN = Cornell University) instead. In-depth spectroscopic, crystallographic, and computational studies support that CORN-MOF-1 has a similar structure to M2(dobdc) but with partially protonated linkers and charge-balancing or coordinated formate groups in the pores. The resultant variation in linker spacings causes CORN-MOF-1 (Mg) to be strongly photoluminescent in the solid state, whereas H4dobdc and Mg2(dobdc) are weakly emissive due to excimer formation. In-depth photophysical studies suggest that CORN-MOF-1 (Mg) is the first MOF based on the H2dobdc2- linker that likely does not emit via an excited state intramolecular proton transfer (ESIPT) pathway. In addition, CORN-MOF-1 variants can be converted into high-quality samples of the thermodynamic M2(dobdc) phases by heating in N,N-dimethylformamide (DMF). Overall, our findings support that high-concentration synthesis provides a straightforward method to identify new MOFs with properties distinct from known materials and to produce highly porous samples of MOFs, paving the way for the discovery and gram-scale synthesis of framework materials.

Measuring expertise in identifying interictal epileptiform discharges.

OBJECTIVE: Interictal epileptiform discharges on EEG are integral to diagnosing epilepsy. However, EEGs are interpreted by readers with and without specialty training, and there is no accepted method to assess skill in interpretation. We aimed to develop a test to quantify IED recognition skills. METHODS: A total of 13,262 candidate IEDs were selected from EEGs and scored by eight fellowship-trained reviewers to establish a gold standard. An online test was developed to assess how well readers with different training levels could distinguish candidate waveforms. Sensitivity, false positive rate and calibration were calculated for each reader. A simple mathematical model was developed to estimate each reader's skill and threshold in identifying an IED, and to develop receiver operating characteristics curves for each reader. We investigated the number of IEDs needed to measure skill level with acceptable precision. RESULTS: Twenty-nine raters completed the test; nine experts, seven experienced non-experts and thirteen novices. Median calibration errors for experts, experienced non-experts and novices were -0.056, 0.012, 0.046; median sensitivities were 0.800, 0.811, 0.715; and median false positive rates were 0.177, 0.272, 0.396, respectively. The number of test questions needed to measure those scores was 549. Our analysis identified that novices had a higher noise level (uncertainty) compared to experienced non-experts and experts. Using calculated noise and threshold levels, receiver operating curves were created, showing increasing median area under the curve from novices (0.735), to experienced non-experts (0.852) and experts (0.891). SIGNIFICANCE: Expert and non-expert readers can be distinguished based on ability to identify IEDs. This type of assessment could also be used to identify and correct differences in thresholds in identifying IEDs.

Trends of Utilization of Antiseizure Medications Among Pregnant Women in Manitoba, Canada: A 20-Year Population-Based Study.

Background: Evidence from developed countries demonstrates that the use of antiseizure medications (ASMs) has been increasing in the last decade. Pregnant women have a very challenging risk benefit trade-off in terms of ASM utilization, and it is crucial to know if increased utilization is seen among pregnant women. Objective: To examine time-trends of utilization of ASM therapies among pregnant women in Manitoba, Canada. Methods: We conducted a population-based cohort study using de-identified, linked administrative databases from Manitoba. Pregnancies between 1995 and 2018 were included. Four groups of pregnant people were created based on ASM exposure and epilepsy diagnosis. Results: Of 273,492 pregnancies, 812 (3/1000) had epilepsy diagnosis and were exposed to ASMs, 963 (3.5/1000) had epilepsy diagnosis and were unexposed, and 2742 (10/1000) were exposed to ASMs and did not have epilepsy diagnosis. Overall, the number of pregnancies exposed to ASMs increased significantly from 0.56% in 1997 to 2.21% in 2018 (p < 0.0001). Subgroup analysis by epilepsy diagnosis showed no significant change in ASMs exposure among pregnant women with epilepsy [the proportion of women exposed to ASM from all pregnancies was 0.37% (in 1997) and 0.36% (in 2018), p = 0.24]. A drop in carbamazepine use was observed, while the number of lamotrigine prescriptions increased from 6.45% in 1997 to 52% by 2018. ASM use among pregnant women without epilepsy increased significantly from 0.19% in 1997 to 1.85% in 2018 (p < 0.0001). In the total cohort of pregnancies, 1439 (0.53%) were exposed during their entire pregnancy, and 1369 (0.5%) were exposed only in their first trimester. Clonazepam was the most used ASM during the study period (1953 users, 0.71%), followed by gabapentin (785 users, 0.29%) and carbamazepine (449 users, 0.16%). Conclusion: No major shifts in the quantity of ASM use over the study period were observed among pregnant women with epilepsy. However, there was a significant increase in ASM use among pregnant women without epilepsy. The study results warrant further investigation into the implications of ASM use in pregnancy for indications other than epilepsy.

Canadian epilepsy priority-setting partnership: Toward a new national research agenda.

BACKGROUND: Health research agendas are often set by researchers or by industry and may not reflect the needs and priorities of end users. This priority-setting partnership (PSP) for epilepsy was undertaken to identify the most pressing unanswered questions about epilepsy and seizures from the perspective of people with epilepsy (PWE) and their care providers. METHODS: Using the methodology developed by the James Lind Alliance (JLA), evidence uncertainties were gathered via online surveys from stakeholders across Canada. Submissions were formed into summary questions and checked against existing evidence to determine if they were true uncertainties. Verified uncertainties were then ranked by patients, caregivers, and healthcare providers and a final workshop was held to reach a consensus on the top 10 priorities. RESULTS: The final top 10 list reflects the priority areas of focus for research as identified by the Canadian epilepsy community, including genetic markers for diagnosis and treatment, concerns about living with the long-term effects of epilepsy, and addressing knowledge gaps in etiology and treatment approaches. CONCLUSION: This project represents the first systematic evidence of patient- and clinician-centered research priorities for epilepsy. The results of this priority-setting exercise provide an opportunity for researchers and funding agencies to align their agendas with the values and needs of the epilepsy community in order to improve clinical outcomes and quality of life (QOL) for PWE.

Sleep-wake states change the interictal localization of candidate epileptic source generators.

STUDY OBJECTIVES: To compare estimated epileptic source localizations from 5 sleep-wake states (SWS): wakefulness (W), rapid eye movement sleep (REM), and non-REM 1-3. METHODS: Electrical source localization (sLORETA) of interictal spikes from different SWS on surface EEG from the epilepsy monitoring unit at spike peak and take-off, with results mapped to individual brain models for 75% of patients. Concordance was defined as source localization voxels shared between 2 and 5 SWS, and discordance as those unique to 1 SWS against 1-4 other SWS. RESULTS: 563 spikes from 16 prospectively recruited focal epilepsy patients across 161 day-nights. SWS exerted significant differences at spike peak but not take-off. Source localization size did not vary between SWS. REM localizations were smaller in multifocal than unifocal patients (28.8% vs. 54.4%, p = .0091). All five SWS contributed about 45% of their localizations to converge onto 17.0 ± 15.5% voxels. Against any one other SWS, REM was least concordant (54.4% vs. 66.9%, p = .0006) and most discordant (39.3% vs. 29.6%, p = .0008). REM also yielded the most unique localizations (20.0% vs. 8.6%, p = .0059). CONCLUSIONS: REM was best suited to identify candidate epileptic sources. sLORETA proposes a model in which an "omni-concordant core" of source localizations shared by all five SWS is surrounded by a "penumbra" of source localizations shared by some but not all SWS. Uniquely, REM spares this core to "move" source voxels from the penumbra to unique cortex not localized by other SWS. This may reflect differential intra-spike propagation in REM, which may account for its reported superior localizing abilities.