Seizures In Period Research Articles

Characterizing EEG signal dynamics in healthy, seizure-free, and seizure states using the chaos decision tree algorithm

Abstract Epilepsy is a multifaceted neurological condition marked by repetitive seizures that arise from irregular electrical activity in the brain. To understand this condition, a thorough examination of brain signals captured in different states is needed. In order to examine the dynamic behavior of brain signals in three different conditions: healthy, seizure-free, and seizure periods, this study uses the chaos decision tree algorithm. The findings show notable variations in these situations’ dynamics. Chaos is evident during seizure moments, showing extremely chaotic activity. The signals mostly exhibit stochastic behavior in the healthy condition, which is consistent with typical brain dynamics. It is noteworthy that an intermediate state exhibiting a blend of stochastic and chaotic signal dynamics is exhibited throughout the seizure-free time. Furthermore, the research shows that the frequency of chaotic signals rises with increasing proximity to the epileptogenic zone. These discoveries clarify the complex nature of epilepsy and offer insightful information about the dynamic properties of brain signals in various stages, aiding in improved understanding and potential diagnostic approaches.

Effects of epileptic seizures on the quality of biosignals recorded from wearables.

Wearable nonelectroencephalographic biosignal recordings captured from the wrist offer enormous potential for seizure monitoring. However, signal quality remains a challenging factor affecting data reliability. Models trained for seizure detection depend on the quality of recordings in peri-ictal periods in performing a feature-based separation of ictal periods from interictal periods. Thus, this study aims to investigate the effect of epileptic seizures on signal quality, ensuring accurate and reliable monitoring. This study assesses the signal quality of wearable data during peri-ictal phases of generalized tonic-clonic and focal to bilateral tonic-clonic seizures (TCS), focal motor seizures (FMS), and focal nonmotor seizures (FNMS). We evaluated accelerometer (ACC) activity and the signal quality of electrodermal activity (EDA) and blood volume pulse (BVP) data. Additionally, we analyzed the influence of peri-ictal movements as assessed by ACC (ACC activity) on signal quality and examined intraictal subphases of focal to bilateral TCS. We analyzed 386 seizures from 111 individuals in three international epilepsy monitoring units. BVP signal quality and ACC activity levels differed between all seizure types. We found the largest decrease in BVP signal quality and increase in ACC activity when comparing the ictal phase to the pre- and postictal phases for TCS. Additionally, ACC activity was strongly negatively correlated with BVP signal quality for TCS and FMS, and weakly for FNMS. Intraictal analysis revealed that tonic and clonic subphases have the lowest BVP signal quality and the highest ACC activity. Motor elements of seizures significantly impair BVP signal quality, but do not have significant effect on EDA signal quality, as assessed by wrist-worn wearables. The results underscore the importance of signal quality assessment methods and careful selection of robust modalities to ensure reliable seizure detection. Future research is needed to explain whether seizure detection models' decisions are based on signal responses induced by physiological processes as opposed to artifacts.

Ethanolic and aqueous extracts of Lantana camara show antiepileptic and anxiolytic effects by inhibiting the ferroptosis pathway in kainate-treated mice

In Cameroon, epilepsy is one of the most common neurological diseases. Available anti-epileptic medication, on the other hand, have been associated with pharmacological toxicity and emotional impairment. The identification of a more efficient replacement is critical. Recent research reveals that ferroptosis contributes to the pathophysiology of epilepsy and related anxiety disorders. Lantana camara is a plant with a high neuropharmacological potential, but its mechanisms of action have yet to be understood. The purpose of this study was to determine the effect of ethanolic and aqueous extracts of Lantana camara on the kainate model of epilepsy in mice. The focus was on these extracts' capacity to suppress ferroptosis. Mice were injected with kainate (12 mg/kg, i.p.) to induce epilepsy. After status epilepticus, animals were left for 19 days, which correspond to an epileptogenic period. After the appearance of spontaneous recurrent seizures, mice were treated with distilled water (10 ml/kg, p.o.), levetiracetam (80 mg/kg, p.o.), sodium valproate (300 mg/kg, p.o.), ethanolic extract of L. camara (230, 460, 920 mg/kg, p.o.), or an aqueous extract of L. camara (460 mg/kg p.o.). These treatments lasted for 14 days. During this period, the number and duration of seizures were recorded. The mice were then subjected to elevated zero-maze and open field tests to assess anxiety-like behavior. At the end, mice were sacrificed and hippocampus, amygdala, and striatum were dissected out for biochemical and histological analyses. The extracts alleviated seizure- and anxiety-like behavior in KA-treated mice. Decreased iron levels, reflected by a decrease in ferritin levels and a increase in transferrin levels, were observed in the hippocampus, striatum and amygdala of the extract-treated group compared to the KA-treated group. In addition, increase in GABA and GSH levels, and a decrease in MDA levels were observed in these groups. Hematoxylin-eosin staining revealed less pronounced neuronal degeneration and a more sustained architecture in the brain region of extract-treated mice. These findings indicated that ethanolic and aqueous extracts of L. camara effectively attenuate seizures and anxiety disorders. Probable mechanisms of action include GABAergic, iron, GSH, and MDA modulations.

Evaluation of thiopyrano[2,3-d]thiazole derivatives as potential anticonvulsant agents.

Anticonvulsant drug discovery has achieved significant progress; however, pharmacotherapy of epilepsy continues to be a challenge for modern medicine and pharmacy. To expand the chemical space of heterocycles as potential antiepileptic agents, herein we report on the synthesis and evaluation of anticonvulsant properties of a series of thiopyrano[2,3-d]thiazoles. The studied heterocycles are characterized by satisfactory drug-likeness and pharmacokinetics properties, calculated in silico using SwissADME. The anticonvulsant activity of thiopyrano[2,3-d]thiazole derivatives was evaluated in vivo using the subcutaneous pentylenetetrazole test. Three hits, that is, compounds 12, 14, and 16, that caused a pronounced anticonvulsant effect were identified. Derivatives 12, 14, and 16 positively affected the latent period of onset of clonic seizures, number of seizures, mortality rate, and duration of the seizure period of animals under experimental conditions. The anticonvulsant properties of compound 14 were equivalent to the effect of the reference drug, sodium valproate. All hit compounds are characterized by satisfying toxicity properties in the human lymphocytes and HEK293 cell line. The most active hit 14 possesses a potential affinity with the GABAA receptor in the molecular docking study and forms a stable complex in the molecular dynamics experiments equal to diazepam. Preliminary SAR results were obtained and discussed based on screening data.

Calsyntenin-1 expression and function in brain tissue of lithium-pilocarpine rat seizure models.

To present the expression of calsyntenin-1 (Clstn1) in the brain and investigate the potential mechanism of Clstn1 in lithium-pilocarpine rat seizure models. Thirty-five male SD adult rats were induced to have seizures by intraperitoneal injection of lithium chloride pilocarpine. Rats exhibiting spontaneous seizures were divided into the epilepsy (EP) group (n=15), whereas those without seizures were divided into the control group (n=14). Evaluate the expression of Clstn1 in the temporal lobe of two groups using Western blotting, immunohistochemistry, and immunofluorescence. Additionally, 55 male SD rats were subjected to status epilepticus (SE) using the same induction method. Rats experiencing seizures exceeding Racine's level 4 (n=48) were randomly divided into three groups: SE, SE+control lentivirus (lentiviral vector expressing green fluorescent protein [LV-GFP]), and SE+Clstn1-targeted RNA interference lentivirus (LV-Clstn1-RNAi). The LV-GFP group served as a control for the lentiviral vector, whereas the LV-Clstn1-RNAi group received a lentivirus designed to silence Clstn1 expression. These lentiviral treatments were administered via hippocampal stereotactic injection 2 days after SE induction. Seven days after SE, Western blot analysis was performed to evaluate the expression of Clstn1 in the hippocampus and temporal lobe. Meanwhile, we observed the latency of spontaneous seizures and the frequency of spontaneous seizures within 8 weeks among the three groups. The expression of Clstn1 in the cortex and hippocampus of the EP group was significantly increased compared to the control group (p<.05). Immunohistochemistry and immunofluorescence showed that Clstn1 was widely distributed in the cerebral cortex and hippocampus of rats, and colocalization analysis revealed that it was mainly co expressed with neurons in the cytoplasm. Compared with the SE group (11.80±2.17 days) and the SE+GFP group (12.40±1.67 days), there was a statistically significant difference (p<.05) in the latency period of spontaneous seizures (15.14±2.41 days) in the SE+Clstn1+RNAi group rats. Compared with the SE group (4.60±1.67 times) and the SE+GFP group (4.80±2.05 times), the SE+Clstn1+RNAi group (2.0±.89 times) showed a significant reduction in the frequency of spontaneous seizures within 2 weeks of chronic phase in rats (p<.05). Elevated Clstn1 expression in EP group suggests its role in EP onset. Targeting Clstn1 may be a potential therapeutic approach for EP management.

Clinical and genetic analysis of 23 Chinese children with epilepsy associated with KCNQ2 gene mutations.

To summarize the clinical features and genetic mutation characteristics of Chinese children with KCNQ2-related epilepsy. A cohort of children with genetically caused epilepsy was evaluated at Linyi People's Hospital from January 2017 to December 2023. After next-generation sequencing and pathogenicity analysis, we summarized the medical records and genetic testing data of the children who had KCNQ2 gene mutations. We identified 23 KCNQ2 gene mutations. 73.9% (n = 17) of the mutation sites were located in S5-S6 segments and the C-terminal region. In addition to the common phenotypes, 2 new phenotypes were identified: infantile convulsion with paroxysmal choreoathetosis (ICCA) and febrile seizure plus (FS+). Of all the cases with abnormal video-electro-encephalography, three cases with self-limited familial infantile epilepsy (SeLNE) exhibited a small number of multifocal discharges. Of the patients who have taken a particular antiepileptic drug, the statistics on the number of patients who have responded to the drug are as follows: oxcarbazepine (8/9, 88.9%), levetiracetam (5/7, 71.4%), phenobarbital (9/16, 56.3%), and topiramate (2/5, 40.0%). However, the efficacy of phenobarbital varied widely in treating SeLNE and KCNQ2-DEE. At the final follow-up, 1 case with SeLNE had a transient developmental regression and 7 cases with KCNQ2-DEE had mild to severe developmental backwardness. Although clinically rare, we report 10 new KCNQ2 mutations and two new phenotypes: ICCA and FS+. This further expands genetic and phenotypic spectrum of KCNQ2-related epilepsy. The gene mutation sites are mostly located in S5-S6 segments and the C-terminal region, and the former is usually associated with KCNQ2-DEE. Sodium channel blockers (including oxcarbazepine and topiramate) and levetiracetam should be prioritized over phenobarbital for KCNQ2-DEE. Some cases with KCNQ2-related epilepsy may have transient developmental regression during periods of frequent seizures. Early treatment and early seizure control may be beneficial for willing outcomes in children with KCNQ2-DEE. This article reports 23 cases of children with KCNQ2-related epilepsy, including 10 new mutation sites and 2 new phenotypes. It further expands the genetic and phenotypic spectrum of KCNQ2-related epilepsy. In addition, the article summarizes the gene mutation characteristics and clinical manifestations of children with KCNQ2-related epilepsy, with the expectation of providing a certain theoretical basis for the diagnosis and treatment of such patients.

Peri-ictal psychiatric manifestations in people with epilepsy: An umbrella review.

We aimed to conduct an umbrella review to summarize the existing evidence regarding the prevalence of peri-ictal psychiatric manifestations (PM) in people with epilepsy (PWE) including pre-ictal, ictal, and postictal stages. Databases were searched up to June 2023 for systematic reviews (SR) of observational studies that included patients with epilepsy peri-ictal PM. Data selection, data extraction, and risk of bias assessment (with the AMSTAR-2 instrument) were performed by two independent reviewers. We performed a narrative synthesis using previous guidelines. We used a self-developed decision table according to the GRADE system adapted for narrative outcomes if the certainty of outcomes was not determined by systematic review authors. Four SRs were included comprising 66 primary studies (n = 10 217). Three SRs evaluated one period (pre-ictal, ictal, and postictal), and one did not determine it. During the pre-ictal period, the more prevalent symptom was confusion, although with a low certainty (due to the heterogeneity and serious risk of bias). One systematic review that only included case reports evaluated the ictal period, finding mood/anxiety disorders, psychosis, and personality changes. The postictal period included the most PM (anxiety: 45.0% and depressive symptoms: 43.0%), with very low certainty, due to risk of bias, potential publication bias, heterogeneity, and failure to report the confidence intervals. With very low certainty, epileptic periods are characterized by a wide spectrum of PM, being postictal symptoms the most prevalent, predominantly anxiety, and depressive symptoms. Further understanding of these PM of epilepsy could improve the attention of the people with epilepsy. In this review of reviews, we summarize the frequency in which psychiatric manifestations occur in relation to an epileptic seizure. A total of 10 217 patients were reported in the reviews. The most common manifestations included symptoms of anxiety and depression, as well as changes in the normal behavior of the patient. These manifestations occurred most frequently right after the seizure finished.

EEG-fMRI in awake rat and whole-brain simulations show decreased brain responsiveness to sensory stimulations during absence seizures

In patients suffering absence epilepsy, recurring seizures can significantly decrease their quality of life and lead to yet untreatable comorbidities. Absence seizures are characterized by spike-and-wave discharges on the electroencephalogram associated with a transient alteration of consciousness. However, it is still unknown how the brain responds to external stimuli during and outside of seizures. This study aimed to investigate responsiveness to visual and somatosensory stimulation in Genetic Absence Epilepsy Rats from Strasbourg (GAERS), a well-established rat model for absence epilepsy. Animals were imaged under non-curarized awake state using a quiet, zero echo time, functional magnetic resonance imaging (fMRI) sequence. Sensory stimulations were applied during interictal and ictal periods. Whole-brain hemodynamic responses were compared between these two states. Additionally, a mean-field simulation model was used to explain the changes of neural responsiveness to visual stimulation between states. During a seizure, whole-brain responses to both sensory stimulations were suppressed and spatially hindered. In the cortex, hemodynamic responses were negatively polarized during seizures, despite the application of a stimulus. The mean-field simulation revealed restricted propagation of activity due to stimulation and agreed well with fMRI findings. Results suggest that sensory processing is hindered or even suppressed by the occurrence of an absence seizure, potentially contributing to decreased responsiveness during this absence epileptic process.

EEG-fMRI in awake rat and whole-brain simulations show decreased brain responsiveness to sensory stimulations during absence seizures.

In patients suffering absence epilepsy, recurring seizures can significantly decrease their quality of life and lead to yet untreatable comorbidities. Absence seizures are characterized by spike-and-wave discharges on the electroencephalogram associated with a transient alteration of consciousness. However, it is still unknown how the brain responds to external stimuli during and outside of seizures. This study aimed to investigate responsiveness to visual and somatosensory stimulation in Genetic Absence Epilepsy Rats from Strasbourg (GAERS), a well-established rat model for absence epilepsy. Animals were imaged under non-curarized awake state using a quiet, zero echo time, functional magnetic resonance imaging (fMRI) sequence. Sensory stimulations were applied during interictal and ictal periods. Whole-brain hemodynamic responses were compared between these two states. Additionally, a mean-field simulation model was used to explain the changes of neural responsiveness to visual stimulation between states. During a seizure, whole-brain responses to both sensory stimulations were suppressed and spatially hindered. In the cortex, hemodynamic responses were negatively polarized during seizures, despite the application of a stimulus. The mean-field simulation revealed restricted propagation of activity due to stimulation and agreed well with fMRI findings. Results suggest that sensory processing is hindered or even suppressed by the occurrence of an absence seizure, potentially contributing to decreased responsiveness during this absence epileptic process.

Risk of Seizure Recurrence Due to Autoimmune Encephalitis With NMDAR, LGI1, CASPR2, and GABABR Antibodies: Implications for Return to Driving.

Patients with ongoing seizures are usually not allowed to drive. The prognosis for seizure freedom is favorable in patients with autoimmune encephalitis (AIE) with antibodies against NMDA receptor (NMDAR), leucine-rich glioma-inactivated 1 (LGI1), contactin-associated protein-like 2 (CASPR2), and the gamma-aminobutyric-acid B receptor (GABABR). We hypothesized that after a seizure-free period of 3 months, patients with AIE have a seizure recurrence risk of <20% during the subsequent 12 months. This would render them eligible for noncommercial driving according to driving regulations in several countries. This retrospective multicenter cohort study analyzed follow-up data from patients aged 15 years or older with seizures resulting from NMDAR-, LGI1-, CASPR2-, or GABABR-AIE, who had been seizure-free for ≥3 months. We used Kaplan-Meier (KM) estimates for the seizure recurrence risk at 12 months for each antibody group and tested for the effects of potential covariates with regression models. We included 383 patients with NMDAR-, 440 with LGI1-, 114 with CASPR2-, and 44 with GABABR-AIE from 14 international centers. After being seizure-free for 3 months after an initial seizure period, we calculated the probability of remaining seizure-free for another 12 months (KM estimate) as 0.89 (95% confidence interval [CI] 0.85-0.92) for NMDAR, 0.84 (CI 0.80-0.88) for LGI1, 0.82 (CI 0.75-0.90) for CASPR2, and 0.76 (CI 0.62-0.93) for GABABR. Taking a <20% recurrence risk within 12 months as sufficient, patients with NMDAR-AIE and LGI1-AIE could be considered eligible for noncommercial driving after having been seizure-free for 3 months.

Cardiorespiratory disturbances in focal impaired awareness seizures: Insights from wearable ECG monitoring

PurposeSeizures are characterized by periictal autonomic changes. Wearable devices could help improve our understanding of these phenomena through long-term monitoring. In this study, we used wearable electrocardiogram (ECG) data to evaluate differences between temporal and extratemporal focal impaired awareness (FIA) seizures monitored in the hospital and at home. We assessed periictal heart rate, respiratory rate, heart rate variability (HRV), and respiratory sinus arrhythmia (RSA). MethodsWe extracted ECG signals across three time points — five minutes baseline and preictal, ten minutes postictal — and the seizure duration. After automatic Rpeak selection, we calculated the heart rate and estimated the respiratory rate using the ECG-derived respiration methodology. HRV was calculated in both time and frequency domains. To evaluate the influence of other modulators on the HRV after removing the respiratory influences, we recalculated the residual power in the high-frequency (HF) and low-frequency (LF) bands using orthogonal subspace projections. Finally, 5-minute and 30-second (ultra-short) ECG segments were used to calculate RSA using three different methods. Seizures from temporal and extratemporal origins were compared using mixed-effects models and estimated marginal means. ResultsThe mean preictal heart rate was 69.95 bpm (95 % CI 65.6 – 74.3), and it increased to 82 bpm, 95 % CI (77.51 – 86.47) and 84.11 bpm, 95 % CI (76.9 – 89.5) during the ictal and postictal periods. Preictal, ictal and postictal respiratory rates were 16.1 (95 % CI 15.2 – 17.1), 14.8 (95 % CI 13.4 – 16.2) and 15.1 (95 % CI 14 – 16.2), showing not statistically significant bradypnea. HRV analysis found a higher baseline power in the LF band, which was still significantly higher after removing the respiratory influences. Postictally, we found decreased power in the HF band and the respiratory influences in both frequency bands. The RSA analysis with the new methods confirmed the lower cardiorespiratory interaction during the postictal period. Additionally, using ultra-short ECG segments, we found that RSA decreases before the electroclinical seizure onset. No differences were observed in the studied parameters between temporal and extratemporal seizures. ConclusionsWe found significant increases in the ictal and postictal heart rates and lower respiratory rates. Isolating the respiratory influences on the HRV showed a postictal reduction of respiratory modulations on both LF and HF bands, suggesting a central role of respiratory influences in the periictal HRV, unlike the baseline measurements. We found a reduced cardiorespiratory interaction during the periictal period using other RSA methods, suggesting a blockade in vagal efferences before the electroclinical onset. These findings highlight the importance of respiratory influences in cardiac dynamics during seizures and emphasize the need to longitudinally assess HRV and RSA to gain insights into long-term autonomic dysregulation.

Graphical Insight: Revolutionizing Seizure Detection with EEG Representation.

Epilepsy is characterized by recurring seizures that result from abnormal electrical activity in the brain. These seizures manifest as various symptoms including muscle contractions and loss of consciousness. The challenging task of detecting epileptic seizures involves classifying electroencephalography (EEG) signals into ictal (seizure) and interictal (non-seizure) classes. This classification is crucial because it distinguishes between the states of seizure and seizure-free periods in patients with epilepsy. Our study presents an innovative approach for detecting seizures and neurological diseases using EEG signals by leveraging graph neural networks. This method effectively addresses EEG data processing challenges. We construct a graph representation of EEG signals by extracting features such as frequency-based, statistical-based, and Daubechies wavelet transform features. This graph representation allows for potential differentiation between seizure and non-seizure signals through visual inspection of the extracted features. To enhance seizure detection accuracy, we employ two models: one combining a graph convolutional network (GCN) with long short-term memory (LSTM) and the other combining a GCN with balanced random forest (BRF). Our experimental results reveal that both models significantly improve seizure detection accuracy, surpassing previous methods. Despite simplifying our approach by reducing channels, our research reveals a consistent performance, showing a significant advancement in neurodegenerative disease detection. Our models accurately identify seizures in EEG signals, underscoring the potential of graph neural networks. The streamlined method not only maintains effectiveness with fewer channels but also offers a visually distinguishable approach for discerning seizure classes. This research opens avenues for EEG analysis, emphasizing the impact of graph representations in advancing our understanding of neurodegenerative diseases.

An EEG Study on [Formula: see text] Phase-Amplitude Coupling-Based Functional Brain Network in Epilepsy Patients.

Epilepsy, a chronic neuropsychiatric brain disorder characterized with recurrent seizures, is closely associated with abnormal neural communications within the brain. Despite that the phase-amplitude coupling (PAC) has been suggested to offer a new way to observe neural interactions during epilepsy, however, few studies pay attention to alterations of the epileptic functional brain network based on PAC, especially on the [Formula: see text] PAC. Therefore, we use scalp electroencephalography (EEG) data of epileptic patients and the [Formula: see text] PAC modulation index (MI) to construct functional brain networks to examine variations of neural interactions during different epileptic phases. Statistically, the findings show that between-channel MI values in the post-ictal period significantly increase compared to that in the pre-ictal period, and the between-channel MI value has a close association with the information of phase and amplitude provided by the channels. Importantly, in both the phase-amplitude and amplitude-phase functional brain networks, the average node degree is remarkably higher in the post-ictal period than that in the pre-ictal period, whereas the characteristic path length in the ictal and post-ictal periods is significantly lower than that in the pre-ictal period. Besides, the average betweenness centrality in the post-ictal period is remarkably higher than that in the ictal period. Interestingly, the positive correlations between within-channel MI values and between-channel MI values can be observed during the pre-ictal, ictal and post-ictal periods. These findings suggest that the [Formula: see text] PAC-based functional brain network may provide a novel perspective to understanding alterations of neural interactions during the epileptic evolution, and may contribute to effectively controlling the spread of epileptic seizures.

Blood serum levels of PACAP and migraine onset: A systematic review and meta-analysis of observational studies.

We conducted a systematic review and meta-analysis to explore the relationship between blood pituitary adenylate cyclase-activating polypeptide (PACAP) levels and migraine. PACAP is involved in the onset of migraine, but the results from clinical studies on PACAP level variations across different periods of migraine are conflicting. We systematically searched for observational studies that reported PACAP levels in people with migraine and non-migraine controls published in English from the PubMed, Web of Science, and Ovid electronic databases, or in Chinese from the Chinese National Knowledge Infrastructure and the WanFang Med database. The Newcastle-Ottawa Quality Assessment Scale was used to assess the quality of the included studies. The quality of evidence for each outcome was assessed according to the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) guidelines. Of the 514 identified studies, 8 were eligible for inclusion. There was a "very low" level of evidence suggesting that the PACAP level is negatively correlated with migraine disease duration in adults with migraine (summary = -0.35, 95% confidence interval [CI] -0.49 to -0.22) and that the PACAP is higher in people with migraine during the ictal period than in the interictal period (standardized mean difference = 0.41, 95% CI 0.17 to 0.66) for both adults and children with migraine. Adult patients with episodic migraine (weighted mean difference [WMD] = -9.58 pg/mL, 95% CI -13.41 to -5.75 pg/mL) or chronic migraine (WMD = -10.93 pg/mL, 95% CI -15.57 to -6.29 pg/mL) had lower blood PACAP levels than non-migraine controls during the interictal period, supported by a "low" or "very low" quality of evidence, respectively, according to the GRADE rules. There is a very low certainty of evidence suggesting that the PACAP level is negatively correlated with migraine disease duration of adults with migraine and it varies greatly among different periods of migraine of both adults and children with migraine.

Migraine aura discrimination using machine learning: an fMRI study during ictal and interictal periods.

Functional magnetic resonance imaging (fMRI) studies on migraine with aura are challenging due to the rarity of patients with triggered cases. This study optimized methodologies to explore differences in ictal and interictal spatiotemporal activation patterns based on visual stimuli using fMRI in two patients with unique aura triggers. Both patients underwent separate fMRI sessions during the ictal and interictal periods. The Gaussian Process Classifier (GPC) was used to differentiate these periods by employing a machine learning temporal embedding approach and spatiotemporal activation patterns based on visual stimuli. When restricted to visual and occipital regions, GPC had an improved performance, with accuracy rates for patients A and B of roughly 86-90% and 77-81%, respectively (p < 0.01). The algorithm effectively differentiated visual stimulation and rest periods and identified times when aura symptoms manifested, as evident from the varying predicted probabilities in the GPC models. These findings contribute to our understanding of the role of visual processing and brain activity patterns in migraine with aura and the significance of temporal embedding techniques in examining aura phenomena. This finding has implications for diagnostic tools and therapeutic techniques, especially for patients suffering from aura symptoms.

Establishing Feasibility for Measuring Multi-unit Activity Within Ictal Period of Seizures with Preserved vs. Impaired Consciousness (P8-1.015)

Establishing Feasibility for Measuring Multi-unit Activity Within Ictal Period of Seizures with Preserved vs. Impaired Consciousness (P8-1.015)

A Novel Hypothesis for Migraine Disease Mechanism: The Creation of a New Attractor Responsible for Migraine Disease Symptoms

Migraine Disease (MD) is one of the common primary headaches that can prevent patients from their everyday life. Despite the high prevalence, the pathophysiology of the disease has not been clearly understood yet. Here, the brain is considered as a dynamical system. The Chua’s circuit with a chaotic attractor is the proposed model. This attractor has a one-scroll mode representing a healthy brain and a double-scroll mode representing a migraine sufferer brain. We believe that MD and Chua’s systems have certain behavioral similarities. The boundaries of the attractor are the sensitive brain areas in which any small trigger can start the ictal phase of the migraine. The transition from the inter-ictal phase to the ictal phase in migraine patients occurs due to a decrease in serotonin levels when the brain is within the boundaries of the first attractor. Here, this is the results of the increase of system parameters. In addition, the transition from the ictal phase to the inter-ictal phase in a migraine sufferer brain is caused by a disruption of coordination in the brain’s structures and this lasts for a certain period for every migraine patient. The structures which are the result of the Migraine Generator Network (MGN) and Cortical Spreading Depression (CSD). This explanation may propose newer methods for preventing or curing MD. To better understand MD to control it and shrink the areas involved in this disease, it is better to know the dynamic systems better. It may help prevent the formation of migraine ictal attractor or even make the migraine ictal phase attractor smaller even after it has been formed.

Parvalbumin neurons in the nucleus accumbens shell modulate seizure in temporal lobe epilepsy

A growing number of clinical and animal studies suggest that the nucleus accumbens (NAc), especially the shell, is involved in the pathogenesis of temporal lobe epilepsy (TLE). However, the role of parvalbumin (PV) GABAergic neurons in the NAc shell involved in TLE is still unclear. In this study, we induced a spontaneous TLE model by intrahippocampal administration of kainic acid (KA), which generally induce acute seizures in first 2 h (acute phase) and then lead to spontaneous recurrent seizures after two months (chronic phase). We found that chemogenetic activation of NAc shell PV neurons could alleviate TLE seizures by reducing the number and period of focal seizures (FSs) and secondary generalized seizures (sGSs), while selective inhibition of PV exacerbated seizure activity. Ruby-virus mapping results identified that the hippocampus (ventral and dorsal) is one of the projection targets of NAc shell PV neurons. Chemogenetic activation of the NAc-Hip PV projection fibers can mitigate seizures while inhibition has no effect on seizure ictogenesis. In summary, our findings reveal that PV neurons in the NAc shell could modulate the seizures in TLE via a long-range NAc-Hip circuit. All of these results enriched the investigation between NAc and epilepsy, offering new targets for future epileptogenesis research and precision therapy.

Consciousness transitions during epilepsy seizures through the lens of integrated information theory

Consciousness is one of the most complex aspects of human experience. Studying the mechanisms involved in the transitions among different levels of consciousness remains as one of the greatest challenges in neuroscience. In this study we use a measure of integrated information (ΦAR) to evaluate dynamic changes during consciousness transitions. We applied the measure to intracranial electroencephalography (SEEG) recordings collected from 6 patients that suffer from refractory epilepsy, taking into account inter-ictal, pre-ictal and ictal periods. We analyzed the dynamical evolution of ΦAR in groups of electrode contacts outside the epileptogenic region and compared it with the Consciousness Seizure Scale (CCS). We show that changes on ΦAR are significantly correlated with changes in the reported states of consciousness.

Effect of the closed-loop hippocampal low-frequency stimulation on seizure severity, learning, and memory in pilocarpine epilepsy rat model.

In this study, the anticonvulsant action of closed-loop, low-frequency deep brain stimulation (DBS) was investigated. In addition, the changes in brain rhythms and functional connectivity of the hippocampus and prefrontal cortex were evaluated. Epilepsy was induced by pilocarpine in male Wistar rats. After the chronic phase, a tripolar electrode was implanted in the right ventral hippocampus and a monopolar electrode in medial prefrontal cortex (mPFC). Subjects' spontaneous seizure behaviors were observed in continuous video recording, while the local field potentials (LFPs) were recorded simultaneously. In addition, spatial memory was evaluated by the Barnes maze test. Applying hippocampal DBS, immediately after seizure detection in epileptic animals, reduced their seizure severity and duration, and improved their performance in Barnes maze test. DBS reduced the increment in power of delta, theta, and gamma waves in pre-ictal, ictal, and post-ictal periods. Meanwhile, DBS increased the post-ictal-to-pre-ictal ratio of theta band. DBS decreased delta and increased theta coherences, and also increased the post-ictal-to-pre-ictal ratio of coherence. In addition, DBS increased the hippocampal-mPFC coupling in pre-ictal period and decreased the coupling in the ictal and post-ictal periods. Applying closed-loop, low-frequency DBS at seizure onset reduced seizure severity and improved memory. In addition, the changes in power, coherence, and coupling of the LFP oscillations in the hippocampus and mPFC demonstrate low-frequency DBS efficacy as an antiepileptic treatment, returning LFPs to a seemingly non-seizure state in subjects that received DBS.