Cross-Frequency Coupling in Childhood Absence Epilepsy

Modification of pre-ictal cortico-hippocampal oscillations by medial ganglionic eminence precursor cells grafting in the pilocarpine model of epilepsy

Cell replacement therapies using medial ganglionic eminence (MGE)-derived GABAergic precursors reduce seizures by restoring inhibition in animal models of epilepsy. However, how MGE-derived cells affect abnormal neuronal networks and consequently brain oscillations to reduce ictogenesis is still under investigation. We performed quantitative analysis of pre-ictal local field potentials (LFP) of cortical and hippocampal CA1 areas recorded in vivo in the pilocarpine rat model of epilepsy, with or without intrahippocampal MGE-precursor grafts (PILO and PILO+MGE groups, respectively). The PILO+MGE animals had a significant reduction in the number of seizures. The quantitative analysis of pre-ictal LFP showed decreased power of cortical and hippocampal delta, theta and beta oscillations from the 5 min. interictal baseline to the 20 s. pre-ictal period in both groups. However, PILO+MGE animals had higher power of slow and fast oscillations in the cortex and lower power of slow and fast oscillations in the hippocampus compared to the PILO group. Additionally, PILO+MGE animals exhibited decreased cortico-hippocampal synchrony for theta and gamma oscillations at seizure onset and lower hippocampal CA1 synchrony between delta and theta with slow gamma oscillations compared to PILO animals. These findings suggest that MGE-derived cell integration into the abnormally rewired network may help control ictogenesis.

Hyper-brain hyper-frequency network topology dynamics when playing guitar in quartet

Ensemble music performance is a highly coordinated form of social behavior requiring not only precise motor actions but also synchronization of different neural processes both within and between the brains of ensemble players. In previous analyses, which were restricted to within-frequency coupling (WFC), we showed that different frequencies participate in intra- and inter-brain coordination, exhibiting distinct network topology dynamics that underlie coordinated actions and interactions. However, many of the couplings both within and between brains are likely to operate across frequencies. Hence, to obtain a more complete picture of hyper-brain interaction when musicians play the guitar in a quartet, cross-frequency coupling (CFC) has to be considered as well. Furthermore, WFC and CFC can be used to construct hyper-brain hyper-frequency networks (HB-HFNs) integrating all the information flows between different oscillation frequencies, providing important details about ensemble interaction in terms of network topology dynamics (NTD). Here, we reanalyzed EEG (electroencephalogram) data obtained from four guitarists playing together in quartet to explore changes in HB-HFN topology dynamics and their relation to acoustic signals of the music. Our findings demonstrate that low-frequency oscillations (e.g., delta, theta, and alpha) play an integrative or pacemaker role in such complex networks and that HFN topology dynamics are specifically related to the guitar quartet playing dynamics assessed by sound properties. Simulations by link removal showed that the HB-HFN is relatively robust against loss of connections, especially when the strongest connections are preserved and when the loss of connections only affects the brain of one guitarist. We conclude that HB-HFNs capture neural mechanisms that support interpersonally coordinated action and behavioral synchrony.

Interictal EEG features as computational biomarkers of West syndrome

Background

West syndrome (WS) is a devastating epileptic encephalopathy with onset in infancy and early childhood. It is characterized by clustered epileptic spasms, developmental arrest, and interictal hypsarrhythmia on electroencephalogram (EEG). Hypsarrhythmia is considered the hallmark of WS, but its visual assessment is challenging due to its wide variability and lack of a quantifiable definition. This study aims to analyze the EEG patterns in WS and identify computational diagnostic biomarkers of the disease.

Method

Linear and non-linear features derived from EEG recordings of 31 WS patients and 20 age-matched controls were compared. Subsequently, the correlation of the identified features with structural and genetic abnormalities was investigated.

Results

WS patients showed significantly elevated alpha-band activity (0.2516 vs. 0.1914, p < 0.001) and decreased delta-band activity (0.5117 vs. 0.5479, p < 0.001), particularly in the occipital region, as well as globally strengthened theta-band activity (0.2145 vs. 0.1655, p < 0.001) in power spectrum analysis. Moreover, wavelet-bicoherence analysis revealed significantly attenuated cross-frequency coupling in WS patients. Additionally, bi-channel coherence analysis indicated minor connectivity alterations in WS patients. Among the four non-linear characteristics of the EEG data (i.e., approximate entropy, sample entropy, permutation entropy, and wavelet entropy), permutation entropy showed the most prominent global reduction in the EEG of WS patients compared to controls (1.4411 vs. 1.5544, p < 0.001). Multivariate regression results suggested that genetic etiologies could influence the EEG profiles of WS, whereas structural factors could not.

Significance

A combined global strengthening of theta activity and global reduction of permutation entropy can serve as computational EEG biomarkers for WS. Implementing these biomarkers in clinical practice may expedite diagnosis and treatment in WS, thereby improving long-term outcomes.

Structural and functional multilayer network analysis in restless legs syndrome patients

The combination of brain structural and functional connectivity offers complementary insights into its organisation. Multilayer network analysis explores various relationships across different layers within a single system. We aimed to investigate changes in the structural and functional multilayer network in 69 patients with primary restless legs syndrome (RLS) compared with 50 healthy controls. Participants underwent diffusion tensor imaging (DTI) and resting state-functional magnetic resonance imaging (rs-fMRI) using a three-tesla MRI scanner. We constructed a structural connectivity matrix derived from DTI using a DSI program and made a functional connectivity matrix based on rs-fMRI using an SPM program and CONN toolbox. A multilayer network analysis, using BRAPH program, was then conducted to assess the connectivity patterns in both groups. At the global level, significant differences there were between the patients with RLS and healthy controls. The average multiplex participation was lower in patients with RLS than in healthy controls (0.804 vs. 0.821, p = 0.042). Additionally, several regions showed significant differences in the nodal level in multiplex participation between patients with RLS and healthy controls, particularly the frontal and temporal lobes. The regions affected included the inferior frontal gyrus, medial orbital gyrus, precentral gyrus, rectus gyrus, insula, superior and inferior temporal gyrus, medial and lateral occipitotemporal gyrus, and temporal pole. These results represent evidence of diversity in interactions between structural and functional connectivity in patients with RLS, providing a more comprehensive understanding of the brain network in RLS. This may contribute to a precise diagnosis of RLS, and aid the development of a biomarker to track treatment effectiveness.

Neurostimulation for Generalized Epilepsy: Should Therapy be Syndrome-specific?

Current applications of neurostimulation for generalized epilepsy use a one-target-fits-all approach that is agnostic to the specific epilepsy syndrome and seizure type being treated. The authors describe similarities and differences between the 2 "archetypes" of generalized epilepsy-Lennox-Gastaut syndrome and Idiopathic Generalized Epilepsy-and review recent neuroimaging evidence for syndrome-specific brain networks underlying seizures. Implications for stimulation targeting and programming are discussed using 5 clinical questions: What epilepsy syndrome does the patient have? What brain networks are involved? What is the optimal stimulation target? What is the optimal stimulation paradigm? What is the plan for adjusting stimulation over time?

Differences in generation and maintenance between ictal and interictal generalized spike-and-wave discharges in childhood absence epilepsy: A magnetoencephalography study

PURPOSE

Childhood absence epilepsy (CAE) is characterized by impaired consciousness and distinct electroencephalogram (EEG) patterns. However, interictal epileptiform discharges (IEDs) do not lead to noticeable symptoms. This study examines the disparity between ictal and interictal generalized spike-and-wave discharges (GSWDs) to determine the mechanisms behind CAE and consciousness.

METHODS

We enrolled 24 patients with ictal and interictal GSWDs in the study. The magnetoencephalography (MEG) data were recorded before and during GSWDs at a sampling rate of 6000 Hz and analyzed across six frequency bands. The absolute and relative spectral power were estimated with the Minimum Norm Estimate (MNE) combined with the Welch technique. All the statistical analyses were performed using paired-sample tests.

RESULTS

During GSWDs, the right lateral occipital cortex indicated a significant difference in the theta band (5-7 Hz) with stronger power (P = 0.027). The interictal group possessed stronger spectral power in the delta band (P < 0.01) and weaker power in the alpha band (P < 0.01) as early as 10 s before GSWDs in absolute and relative spectral power. Additionally, the ictal group revealed enhanced spectral power inside the occipital cortex in the alpha band and stronger spectral power in the right frontal regions within beta (15-29 Hz), gamma 1 (30-59 Hz), and gamma 2 (60-90 Hz) bands.

CONCLUSIONS

GSWDs seem to change gradually, with local neural activity changing even 10 s before discharge. During GSWDs, visual afferent stimulus insensitivity could be related to the impaired response state in CAE. The inhibitory signal in the low-frequency band can shorten GSWD duration, thereby achieving seizure control through inhibitory effect strengthening.

Paroxysmal slow-wave discharges in a model of absence seizure are coupled to gamma oscillations in the thalamocortical and limbic systems

OBJECTIVE

Using the gamma-butyrolactone (GBL) model of absence seizures in Long-Evans rats, this study investigated if gamma (30-160 Hz) activity were cross-frequency modulated by the 2-6 Hz slow-wave discharges induced by GBL in the limbic system. We hypothesized that inactivation of the nucleus reuniens (RE), which projects to frontal cortex (FC) and hippocampus, would affect the cross-frequency coupling of gamma (γ) in different brain regions.

METHODS

Local field potentials were recorded by electrodes implanted in the FC, ventrolateral thalamus (TH), basolateral amygdala (BLA), nucleus accumbens (NAC), and dorsal hippocampus (CA1) of behaving rats. At each electrode, the coupling between the γ amplitude envelope to the phase of the 2-6 Hz slow-waves (SW) was measured by modulation index (MI) or cross-frequency coherence (CFC) of γ amplitude with SW. In separate experiments, the RE was infused with saline or GABA_A receptor agonist, muscimol, before the injection of GBL.

RESULTS

Following GBL injection, an increase in MI and CFC of SW to γ1 (30-58 Hz), γ2 (62-100 Hz) and γ3 (100-160 Hz) bands was observed at the FC, hippocampus and BLA, with significant increase in SW-γ1 and SW-γ3 coupling at TH, and increase in peak SW-γ1 CFC at NAC. Strong SW-γ modulation was also found during baseline immobility high-voltage spindles. Muscimol inactivation of RE, as compared to saline infusion, significantly decreased SW-γ1 CFC in the FC, and peak frequency of the SW-γ1 CFC in the thalamus, but did not significantly alter SW-γ CFCs in the hippocampus, BLA or NAC.

SIGNIFICANCE

The paroxysmal 2-6 Hz SW discharges, a hallmark of absence seizure, significantly modulate γ activity in the hippocampus, BLA and NAC, suggesting a modulation of limbic functions. RE inactivation disrupted the SW modulation of FC and TH, partly supporting our hypothesis that RE participates in the modulation of SW discharges.

EEG Oscillatory Networks in Peri-Ictal Period of Absence Epilepsy

Objective

To investigate the dynamical brain network changes before and after an absence seizure episode in absence epilepsy (AE).

Methods

21 AE patients with a current high frequency of seizures and 21 sex- and age-matched health control (HC) who reported no history of neurological or psychiatric disorders and visited the hospital for routine physical examinations were included. Each included subject underwent a 2-h and 19-channel video EEG examination. For AE patients, five epochs of 10-s EEG data in inter-ictal, pre-ictal, and post-ictal states were collected. For the HC group, five 10-s resting-state EEG epochs were extracted. Functional independent components analysis (ICA) was carried out using the LORETA KEY tool.

Results

Compared with the resting-state EEG data of the HC group, the EEG data from AE patients during inter-ictal periods showed decreased alpha oscillations in regions involving the superior frontal gyrus (SFG) (BA11). From inter-ictal to pre-ictal, SFG (BA10) showed maximum decreased delta oscillations. Additionally, from pre-ictal to post-ictal, superior temporal gyrus (STG) (BA 22) presented maximum increased neural activity in the alpha band. Moreover, compared with inter-ictal EEG, post-ictal EEG showed significantly decreased theta activity in SFG (BA8).

Conclusion

The changes in SFG alpha oscillations are the key brain network differences between inter-ictal EEG of AE patients and resting-state EEG of HCs. The brain networks of EEG oscillatory during peri-ictal episodes are mainly involving SFG and STG. Our study suggests that altered EEG brain networks dynamics exist between inter-ictal EEG of AE patients and resting-state EEG of HCs and between pre- and post-ictal EEG in AE patients.

Neural Synchrony and Network Dynamics in Social Interaction: A Hyper-Brain Cell Assembly Hypothesis

Mounting neurophysiological evidence suggests that interpersonal interaction relies on continual communication between cell assemblies within interacting brains and continual adjustments of these neuronal dynamic states between the brains. In this Hypothesis and Theory article, a Hyper-Brain Cell Assembly Hypothesis is suggested on the basis of a conceptual review of neural synchrony and network dynamics and their roles in emerging cell assemblies within the interacting brains. The proposed hypothesis states that such cell assemblies can emerge not only within, but also between the interacting brains. More precisely, the hyper-brain cell assembly encompasses and integrates oscillatory activity within and between brains, and represents a common hyper-brain unit, which has a certain relation to social behavior and interaction. Hyper-brain modules or communities, comprising nodes across two or several brains, are considered as one of the possible representations of the hypothesized hyper-brain cell assemblies, which can also have a multidimensional or multilayer structure. It is concluded that the neuronal dynamics during interpersonal interaction is brain-wide, i.e., it is based on common neuronal activity of several brains or, more generally, of the coupled physiological systems including brains.

Contributions of Magnetoencephalography to Understanding Mechanisms of Generalized Epilepsies: Blurring the Boundary Between Focal and Generalized Epilepsies?

According to the latest operational 2017 ILAE classification of epileptic seizures, the generalized epileptic seizure is still conceptualized as "originating at some point within and rapidly engaging, bilaterally distributed networks." In contrast, the focal epileptic seizure is defined as "originating within networks limited to one hemisphere." Hence, one of the main concepts of "generalized" and "focal" epilepsy comes from EEG descriptions before the era of source localization, and a presumed simultaneous bilateral onset and bi-synchrony of epileptiform discharges remains a hallmark for generalized seizures. Current literature on the pathophysiology of generalized epilepsy supports the concept of a cortical epileptogenic focus triggering rapidly generalized epileptic discharges involving intact corticothalamic and corticocortical networks, known as the cortical focus theory. Likewise, focal epilepsy with rich connectivity can give rise to generalized spike and wave discharges resulting from widespread bilateral synchronization. Therefore, making this key distinction between generalized and focal epilepsy may be challenging in some cases, and for the first time, a combined generalized and focal epilepsy is categorized in the 2017 ILAE classification. Nevertheless, treatment options, such as the choice of antiseizure medications or surgical treatment, are the reason behind the importance of accurate epilepsy classification. Over the past several decades, plentiful scientific research on the pathophysiology of generalized epilepsy has been conducted using non-invasive neuroimaging and postprocessing of the electromagnetic neural signal by measuring the spatiotemporal and interhemispheric latency of bi-synchronous or generalized epileptiform discharges as well as network analysis to identify diagnostic and prognostic biomarkers for accurate diagnosis of the two major types of epilepsy. Among all the advanced techniques, magnetoencephalography (MEG) and multiple other methods provide excellent temporal and spatial resolution, inherently suited to analyzing and visualizing the propagation of generalized EEG activities. This article aims to provide a comprehensive literature review of recent innovations in MEG methodology using source localization and network analysis techniques that contributed to the literature of idiopathic generalized epilepsy in terms of pathophysiology and clinical prognosis, thus further blurring the boundary between focal and generalized epilepsy.