EEG resting state analysis of cortical sources in patients with benign epilepsy with centrotemporal spikes

Higher emotional synchronization is modulated by relationship quality in romantic relationships and not in close friendships

Emotions are fundamental to social interaction and deeply intertwined with interpersonal dynamics, especially in romantic relationships. Although the neural basis of interaction processes in romance has been widely explored, the underlying emotions and the connection between relationship quality and neural synchronization remain less understood. Our study employed EEG hyperscanning during a non-interactive video-watching paradigm to compare the emotional coordination between romantic couples and close friends. Couples showed significantly greater behavioral and prefrontal alpha synchronization than friends. Notably, couples with low relationship quality required heightened neural synchronization to maintain robust behavioral synchronization. Further support vector machine analysis underscores the crucial role of prefrontal activity in differentiating couples from friends. In summary, our research addresses gaps concerning how intrinsic emotions linked to relationship quality influence neural and behavioral synchronization by investigating a natural non-interactive context, thereby advancing our understanding of the neural mechanisms underlying emotional coordination in romantic relationships.

High-Density (HD) Scalp EEG Findings in "Benign" Childhood Epilepsy with Centrotemporal Spikes (BCECTS)

Despite characteristic clinical and scalp EEG findings, BCECTS pathophysiology is unclear regarding involvement of large-scale neuronal networks. Higher number of scalp electrodes with HD-EEG may promote accurate localization of the cortical generators in BCECTS providing additional insight in those with neurocognitive problems. We aimed to determine the value of visual interpretation of topographical maps using 256 channels (when compared to standard 21 channel array) HD-EEG in BCECTS and attempted to source localize interictal discharges (IEDs) using Geosource 2 software. Patient records were reviewed for demographic, seizure, brain magnetic resonance imaging (MRI) details; scalp and HD-EEG findings. HD-EEG software was used to review raw EEG data (21 scalp EEG electrodes were compared to 256 HD-EEG electrodes); select, average, and source localize IEDs.Five BCECTS patients with HD-EEG were identified. Seizure onset age ranged from 5-11 years with 1-18 lifetime seizures; both focal (n = 3) and focal to bilateral tonic-clonic (n = 2). Neurocognitive co-morbidities noted in our cohort included attention deficit hyperactivity disorder, speech/developmental delay and a specific learning disorder. Scalp EEG showed typical findings with IEDs over the centrotemporal regions (bilateral n = 3; unilateral n = 2). Visualization and inspection of expanded coverage topographic maps with HD-EEG showed well-defined islands of maximum negativity and positivity of a dipole compared to conventional channels where boundary delineation was obscured. Further, HD-EEG localized IEDs/"spike-generator" to areas such as the pre-and post-central, middle-frontal and temporal gyrus, and the inferior parietal lobule. In BCECTS, HD-EEG may show affection for a broader neural network and may provide a better insight into the associated neurocognitive morbidities.

Functional network dynamics between the anterior thalamus and the cortex in deep brain stimulation for epilepsy

Owing to its unique connectivity profile with cortical brain regions, and its suggested role in the subcortical propagation of seizures, the anterior nucleus of the thalamus (ANT) has been proposed as a key deep brain stimulation (DBS) target in drug-resistant epilepsy. However, the spatio-temporal interaction dynamics of this brain structure, and the functional mechanisms underlying ANT DBS in epilepsy remain unknown. Here, we study how the ANT interacts with the neocortex in vivo in humans and provide a detailed neurofunctional characterization of mechanisms underlying the effectiveness of ANT DBS, aiming at defining intraoperative neural biomarkers of responsiveness to therapy, assessed at 6 months post-implantation as the reduction in seizure frequency. A cohort of 15 patients with drug-resistant epilepsy (n = 6 males, age = 41.6 ± 13.79 years) underwent bilateral ANT DBS implantation. Using intraoperative cortical and ANT simultaneous electrophysiological recordings, we found that the ANT is characterized by high amplitude θ (4-8 Hz) oscillations, mostly in its superior part. The strongest functional connectivity between the ANT and the scalp EEG was also found in the θ band in ipsilateral centro-frontal regions. Upon intraoperative stimulation in the ANT, we found a decrease in higher EEG frequencies (20-70 Hz) and a generalized increase in scalp-to-scalp connectivity. Crucially, we observed that responders to ANT DBS treatment were characterized by higher EEG θ oscillations, higher θ power in the ANT, and stronger ANT-to-scalp θ connectivity, highlighting the crucial role of θ oscillations in the dynamical network characterization of these structures. Our study provides a comprehensive characterization of the interaction dynamic between the ANT and the cortex, delivering crucial information to optimize and predict clinical DBS response in patients with drug-resistant epilepsy.

Alternations of neuromagnetic activity across neurocognitive core networks among benign childhood epilepsy with centrotemporal spikes: A multi-frequency MEG study

Objective

We aimed to investigate the alternations of neuromagnetic activity across neurocognitive core networks among early untreated children having benign childhood epilepsy with centrotemporal spikes (BECTS).

Methods

We recorded the Magnetoencephalography (MEG) resting-state data from 48 untreated children having BECTS and 24 healthy children. The fourth edition of the Wechsler Intelligence Scale for Children (WISC-IV) was utilized to divide the children with BECTS into two groups: the cognitive impairment (CI) group with a full-scale intelligence quotient (FSIQ) of < 90 and the cognitive non-impairment (CNI) group with an FSIQ of > 90. We selected 26 bilateral cognitive-related regions of interest based on the triple network model. The neurocognitive core network spectral power was estimated using a minimum norm estimate (MNE).

Results

In the CNI group, the spectral power inside the bilateral anterior cingulate cortex (ACC) and the bilateral caudal middle frontal cortex (CMF) enhanced within the delta band and reduced within the alpha band. Both the CI and the CNI group demonstrated enhanced spectral power inside the bilateral posterior cingulate cortex (PCC), bilateral precuneus (PCu) region, bilateral superior and middle temporal cortex, bilateral inferior parietal lobe (IPL), and bilateral supramarginal cortex (SM) region in the delta band. Moreover, there was decreased spectral power in the alpha band. In addition, there were consistent changes in the high-frequency spectrum (> 90 Hz). The spectral power density within the insula cortex (IC), superior temporal cortex (ST), middle temporal cortex (MT), and parahippocampal cortex (PaH) also decreased. Therefore, studying high-frequency activity could lead to a new understanding of the pathogenesis of BECTS.

Conclusion

The alternations of spectral power among neurocognitive core networks could account for CI among early untreated children having BECTS. The dynamic properties of spectral power in different frequency bands could behave as biomarkers for diagnosing new BECTS.

The development of peak alpha frequency from infancy to adolescence and its role in visual temporal processing: A meta-analysis

While it has been shown that alpha frequency increases over development (Stroganova et al., 1999), a precise trajectory has not yet been specified, making it challenging to constrain theories linking alpha rhythms to perceptual development. We conducted a comprehensive review of studies measuring resting-state occipital peak alpha frequency (PAF, the frequency exhibiting maximum power) from birth to 18 years of age. From 889 potentially relevant studies, we identified 40 reporting PAF (109 samples; 3882 subjects). A nonlinear regression revealed that PAF increases quickly in early childhood (from 6.1 Hz at 6 months to 8.4 Hz at 5 years) and levels off in adolescence (9.7 Hz at 13 years), with an asymptote at 10.1 Hz. We found no effect of resting state procedure (eyes-open versus eyes-closed) or biological sex. PAF has been implicated as a clock on visual temporal processing, with faster frequencies associated with higher visual temporal resolution. Psychophysical studies have shown that temporal resolution reaches adult levels by 5 years of age (Freschl et al., 2019, 2020). The fact that PAF reaches the adult range of 8-12 Hz by that age strengthens the link between PAF and temporal resolution.

Alterations in the default mode network in rolandic epilepsy with mild spike-wave index in non-rapid eye movement sleep

Purpose

Rolandic epilepsy (RE) is one of the most common epilepsy syndromes during childhood. The aim of this study was to investigate the alterations in the default mode network (DMN) of RE patients whose spike-wave index (SWI) was within the 50–85% range during non-rapid eye movement (NREM) during sleep, as well as to detect early neuroimaging markers.

Methods

Resting-state data was recorded for each subject using magnetoencephalography (MEG). DMN-related brain regions were chosen as regions of interest. The spectral power and functional connectivity (FC) of the DMN were estimated through the use of minimum norm estimation (MNE) combined with Welch technique and corrected amplitude envelope correlation (AEC-c).

Results

The patient group included 20 patients with NREM phase 50% ≤ SWI < 85% (mild SWI group), and 18 typical RE patients (SWI < 50% group). At the regional level, the mild SWI group exhibited enhanced spectral power in the delta band of the bilateral posterial cingulate cortex and attenuated the spectral power in the alpha band of the bilateral posterial cingulate cortex. Enhanced spectral power in the bilateral precuneus (PCu) in the delta band and attenuated spectral power in the right lateral temporal cortex (LTC) in the alpha band were common across all RE patients. At the FC level, patients in the mild SWI group indicated increased AEC-c values between the bilateral posterial cingulate cortex in the delta band and between the left medial frontal cortex (MFC) and bilateral posterial cingulate cortex in the alpha band. Increased AEC-c values between the right PCu and left MFC in the delta band, and between the left PCu and right MFC in the theta band, were common across all RE patients. Moreover, the spectral power in the bilateral posterial cingulate cortex in the alpha band and the AEC-c value between the bilateral posterial cingulate cortex in the delta band demonstrated good discrimination ability.

Conclusion

The spectral power of the bilateral posterior cingulate cortex (PCC) in the alpha band and the AEC-c value between the bilateral PCC in the delta band may be promising indicators of early differentiation between mild SWI and typical RE.

Signal quality and power spectrum analysis of remote ultra long-term subcutaneous EEG

OBJECTIVE

Ultra long-term subcutaneous electroencephalography (sqEEG) monitoring is a new modality with great potential for both health and disease, including epileptic seizure detection and forecasting. However, little is known about the long-term quality and consistency of the sqEEG signal, which is the objective of this study.

METHODS

The largest multicenter cohort of sqEEG was analyzed, including 14 patients with epilepsy and 12 healthy subjects, implanted with a sqEEG device (24/7 EEG^™ SubQ), and recorded from 23 to 230 days (median 42 days), with a median data capture rate of 75% (17.9 hours/day). Median power spectral density plots of each subject were examined for physiological peaks, including at diurnal and nocturnal periods. Long-term temporal trends in signal impedance and power spectral features were investigated with subject-specific linear regression models and group-level linear mixed-effects models.

RESULTS

sqEEG spectrograms showed an approximate 1/f power distribution. Diurnal peaks in the alpha range (8-13Hz) and nocturnal peaks in the sigma range (12-16Hz) were seen in the majority of subjects. Signal impedances remained low, and frequency band powers were highly stable throughout the recording periods.

SIGNIFICANCE

The spectral characteristics of minimally invasive, ultra long-term sqEEG are similar to scalp EEG, whereas the signal is highly stationary. Our findings reinforce the suitability of this system for chronic implantation on diverse clinical applications, from seizure detection and forecasting to brain-computer interfaces.

Different Functional Network Connectivity Patterns in Epilepsy: A Rest-State fMRI Study on Mesial Temporal Lobe Epilepsy and Benign Epilepsy With Centrotemporal Spike

The stark discrepancy in the prognosis of epilepsy is closely related to brain damage features and underlying mechanisms, which have not yet been unraveled. In this study, differences in the epileptic brain functional connectivity states were explored through a network-based connectivity analysis between intractable mesial temporal lobe epilepsy (MTLE) patients and benign epilepsy with centrotemporal spikes (BECT). Resting state fMRI imaging data were collected for 14 MTLE patients, 12 BECT patients and 16 healthy controls (HCs). Independent component analysis (ICA) was performed to identify the cortical functional networks. Subcortical nuclei of interest were extracted from the Harvard-Oxford probability atlas. Network-based statistics were used to detect functional connectivity (FC) alterations across intranetworks and internetworks, including the connectivity between cortical networks and subcortical nuclei. Compared with HCs, MTLE patients showed significant lower activity between the connectivity of cortical networks and subcortical nuclei (especially hippocampus) and lower internetwork FC involving the lateral temporal lobe; BECT patients showed normal cortical-subcortical FC with hyperconnectivity between cortical networks. Together, cortical-subcortical hypoconnectivity in MTLE suggested a low efficiency and collaborative network pattern, and this might be relevant to the final decompensatory state and the intractable prognosis. Conversely, cortical-subcortical region with normal connectivity remained well in global cooperativity, and compensatory internetwork hyperconnectivity caused by widespread cortical abnormal discharge, which might account for the self-limited clinical outcome in BECT. Based on the fMRI functional network study, different brain network patterns might provide a better explanation of mechanisms in different types of epilepsy.

Hippocampal astrocytic neogenin regulating glutamate uptake, a critical pathway for preventing epileptic response

Epilepsy, a common neurological disorder, is featured with recurrent seizures. Its underlying pathological mechanisms remain elusive. Here, we provide evidence for loss of neogenin (NEO1), a coreceptor for multiple ligands, including netrins and bone morphological proteins, in the development of epilepsy. NEO1 is reduced in hippocampi from patients with epilepsy based on transcriptome and proteomic analyses. Neo1 knocking out (KO) in mouse brains displays elevated epileptiform spikes and seizure susceptibility. These phenotypes were undetectable in mice, with selectively depleted NEO1 in excitatory (NeuroD6-Cre⁺) or inhibitory (parvalbumin⁺) neurons, but present in mice with specific hippocampal astrocytic Neo1 KO. Additionally, neurons in hippocampal dentate gyrus, a vulnerable region in epilepsy, in mice with astrocyte-specific Neo1 KO show reductions in inhibitory synaptic vesicles and the frequency of miniature inhibitory postsynaptic current(mIPSC), but increase of the duration of miniature excitatory postsynaptic current and tonic NMDA receptor currents, suggesting impairments in both GABAergic transmission and extracellular glutamate clearance. Further proteomic and cell biological analyses of cell-surface proteins identified GLAST, a glutamate-aspartate transporter that is marked reduced in Neo1 KO astrocytes and the hippocampus. NEO1 interacts with GLAST and promotes GLAST surface distribution in astrocytes. Expressing NEO1 or GLAST in Neo1 KO astrocytes in the hippocampus abolishes the epileptic phenotype. Taken together, these results uncover an unrecognized pathway of NEO1-GLAST in hippocampal GFAP⁺ astrocytes, which is critical for GLAST surface distribution and function, and GABAergic transmission, unveiling NEO1 as a valuable therapeutic target to protect the brain from epilepsy.

Predictive value of functional MRI and EEG in epilepsy diagnosis after a first seizure

It is often difficult to predict seizure recurrence in subjects who have suffered a first-ever epileptic seizure. In this study, the predictive value of physiological signals measured using Electroencephalography (EEG) and functional MRI (fMRI) is assessed. In particular those patients developing epilepsy (i.e. a second unprovoked seizure) that were initially evaluated as having a low risk of seizure recurrence are of interest. In total, 26 epilepsy patients, of which 8 were initially evaluated as having a low risk of seizure recurrence (i.e. converters), and 17 subjects with only a single seizure were included. All subjects underwent routine EEG as well as fMRI measurements. For diagnostic classification, features related to the temporal dynamics were determined for both the processed EEG and fMRI data. Subsequently, a logistic regression classifier was trained on epilepsy and first-seizure subjects. The trained model was tested using the clinically relevant converters group. The sensitivity, specificity, and AUC (mean ± SD) of the regression model including metrics from both modalities were 74 ± 19%, 82 ± 18%, and 0.75 ± 0.12, respectively. Positive and negative predictive values (mean ± SD) of the regression model with both EEG and fMRI features are 84 ± 14% and 78 ± 12%. Moreover, this EEG/fMRI model showed significant improvements compared to the clinical diagnosis, whereas the models using metrics from either EEG or fMRI do not reach significance (p > 0.05). Temporal metrics computationally derived from EEG and fMRI time signals may clinically aid and synergistically improve the predictive value in a first-seizure sample.

The relationship between neuromagnetic activity and cognitive function in benign childhood epilepsy with centrotemporal spikes

PURPOSE

Our aim was to explore the pathophysiological mechanism of cognitive function changes in early untreated children with benign childhood epilepsy with centrotemporal spikes (BECTS).

METHODS

Magnetoencephalography (MEG) was performed in 33 children with BECTS and 18 healthy children. Wechsler Intelligence Scale for Children, fourth edition (WISC-IV) was used to divide children with BECTS into two groups. Normal cognitive function was defined as a full-scale intelligence quotient (FSIQ) of >80, while decreased cognitive function was defined as a FSIQ of <80. Accumulated source imaging was used to evaluate the neuromagnetic source activity in multifrequency bands.

RESULTS

Of the 33 patients with early untreated BECTS, a total of 17 had a FSIQ of <80 and 16 had FSIQ of >80. The course of epilepsy and number of seizures in the FSIQ <80 group were higher than that in the FSIQ >80 group. Our MEG results showed that in the 4-8 Hz frequency band, both patient groups had inactivation of the posterior cingulate cortex (PCC) region compared with the healthy control group. In the 30-80 Hz frequency band, the FSIQ <80 group showed inactivation of the PCC region compared with both the healthy control group and the FSIQ >80 group. In the 80-250 Hz frequency band, the FSIQ <80 group had inactivated of the medial frontal cortex (MFC) region compared with the healthy control group. In the 30-80 Hz frequency band, the strength of neuromagnetic source in patients with BECTS with FSIQ <80 was higher than that in the FSIQ >80 group and the healthy control group.

CONCLUSIONS

The magnetic source inactivation of the MFC and PCC regions during the interictal time may be the reason for cognitive decline in early untreated children with BECTS. Children with BECTS with cognitive decline had a longer course of epilepsy and more seizures. The magnetic source localization in the 4-8 Hz frequency band may be a new imaging marker for the diagnosis of new BECTS.

ADHD and ADHD-related neural networks in benign epilepsy with centrotemporal spikes: A systematic review

BACKGROUND

Attention-deficit/hyperactivity disorder (ADHD) and benign epilepsy with centrotemporal spikes (BECTS or rolandic epilepsy) present with a very high level of comorbidity. We aimed to review the existing literature focusing on two aspects: the possible role of epileptic activity in the damage of ADHD-related neural networks and the clinical approach to patients presenting with both conditions.

MATERIAL AND METHODS

A systematic review was performed using Sapienza Library System and PubMed. The following search terms have been considered: attention networks, ADHD, attention systems, rolandic epilepsy, benign epilepsy with centrotemporal spikes, centrotemporal spikes epilepsy, and focal epilepsy in children. The target population consisted of patients under 18 years of age diagnosed with either BECTS and ADHD or healthy controls.

RESULTS

Nine case-control and cohort studies have been selected. The reported prevalence of ADHD in patients with BECTS was around 60%. No clinical correlation was found between the medical records and the presence of ADHD in patients with BECTS, if not due to febrile convulsion (FC). One study showed higher levels of bilateral discharges in patients with severe ADHD. The negative influence of the age at onset of seizures was demonstrated on attention but not on intelligence quotient (IQ). Moreover, the frequency of seizures and the occurrence of discharges during nonrapid eye movement (NREM) sleep were correlated to attention impairment. From a neurobiological point of view, functional connectivity in patients with BECTS and ADHD appears to be disrupted. Two studies reported a specific impairment in selective visual attention, while one study underlined a decreased activation of the dorsal attention network (DAN). Two different studies found that patients with BECTS and comorbid ADHD presented with altered thickness in their magnetic resonance imaging (MRI) scans in the cortical and subcortical regions (including the frontal lobes, lingual-fusiform cortex, cuneus and precuneus, limbic area and pericalcarine cortex among others). This might explain the cognitive and behavioral symptoms such as poor selective visual attention, speech disturbance, and impulsivity.

CONCLUSIONS

Despite BECTS being considered to have a relative benign course, many studies have documented cognitive and/or behavioral problems in patients diagnosed with this type of epilepsy. In particular, children affected by rolandic epilepsy should receive a complete neuropsychological evaluation at seizure onset considering the high rate of comorbidity with ADHD. A further investigation of the common pathogenic substrate is desirable to better orientate the clinical and therapeutic interventions applied.

Frequency-Dependent Interictal Neuromagnetic Activities in Children With Benign Epilepsy With Centrotemporal Spikes: A Magnetoencephalography (MEG) Study

Objective: This study aimed to investigate interictal neuromagnetic activities in the low- to high-frequency ranges in patients with benign epilepsy with centrotemporal spikes (BECTS), especially those without interictal epileptiform discharges (IEDs).

Methods: We studied 21 clinically-diagnosed BECTS patients and 11 age-matched healthy controls (HC) using high-sampling magnetoencephalography (MEG). Neuromagnetic sources were assessed with accumulated source imaging (ASI). The MEG data were analyzed in seven frequency bands. The MEG recordings distinguished BECTS without IEDs (n = 10) from those with IEDs (n = 11) and HC (n = 11).

Results: At 1–4 Hz, the neuromagnetic activities in healthy subjects tended to locate at the precuneus/posterior cingulate, while those of the BECTS patients without IEDs tended to locate at the medial frontal cortex (MFC) compared to BECTS patients with IEDs. The MEG source imaging at 30–80 Hz revealed that BECTS patients without IEDs had higher occurrences of interictal brain activity in the medial temporal lobe (MTL) compared to controls and the brain activity strength seemed to be weaker. There was a significant correlation between the source strength of the interictal gamma oscillations of BECTS patients without IEDs and the duration of epilepsy.

Conclusions: IEDs might disrupt the default mode network (DMN). Aberrant brain activities in BECTS patients without IEDs were associated with cognitive areas of the brain. The strength of gamma oscillations in the chronic epilepsy state reflected the duration of BECTS.

Significance: MEG could reveal the aberrant neural activities in BECTS patients during the interictal period, and such abnormality is frequency-dependent. Gamma oscillations could be used to identify BECTS patients without IEDs.

Desynchronization of temporal lobe theta-band activity during effective anterior thalamus deep brain stimulation in epilepsy

BACKGROUND

Bilateral cyclic high frequency deep brain stimulation (DBS) of the anterior nucleus of the thalamus (ANT) reduces the seizure count in a subset of patients with epilepsy. Detecting stimulation-induced alterations of pathological brain networks may help to unravel the underlying physiological mechanisms related to effective stimulation delivery and optimize target engagement.

METHODS

We acquired 64-channel electroencephalography during ten ANT-DBS cycles (145 ​Hz, 90 ​μs, 3-5 ​V) of 1-min ON followed by 5-min OFF stimulation to detect changes in cortical activity related to seizure reduction. The study included 14 subjects (three responders, four non-responders, and seven healthy controls). Mixed-model ANOVA tests were used to compare differences in cortical activity between subgroups both ON and OFF stimulation, while investigating frequency-specific effects for the seizure onset zones.

RESULTS

ANT-DBS had a widespread desynchronization effect on cortical theta and alpha band activity in responders, but not in non-responders. Time domain analysis showed that the stimulation induced reduction in theta-band activity was temporally linked to the stimulation period. Moreover, stimulation induced theta-band desynchronization in the temporal lobe channels correlated significantly with the therapeutic response. Responders to ANT-DBS and healthy-controls had an overall lower level of theta-band activity compared to non-responders.

CONCLUSION

This study demonstrated that temporal lobe channel theta-band desynchronization may be a predictive physiological hallmark of therapeutic response to ANT-DBS and may be used to improve the functional precision of this intervention by verifying implantation sites, calibrating stimulation contacts, and possibly identifying treatment responders prior to implantation.

Effect of interictal epileptiform discharges on EEG-based functional connectivity networks

OBJECTIVE

Functional connectivity networks (FCNs) based on interictal electroencephalography (EEG) can identify pathological brain networks associated with epilepsy. FCNs are altered by interictal epileptiform discharges (IEDs), but it is unknown whether this is due to the morphology of the IED or the underlying pathological activity. Therefore, we characterized the impact of IEDs on the FCN through simulations and EEG analysis.

METHODS

We introduced simulated IEDs to sleep EEG recordings of eight healthy controls and analyzed the effect of IED amplitude and rate on the FCN. We then generated FCNs based on epochs with and without IEDs and compared them to the analogous FCNs from eight subjects with infantile spasms (IS), based on 1340 visually marked IEDs. Differences in network structure and strength were assessed.

RESULTS

IEDs in IS subjects caused increased connectivity strength but no change in network structure. In controls, simulated IEDs with physiological amplitudes and rates did not alter network strength or structure.

CONCLUSIONS

Increases in connectivity strength in IS subjects are not artifacts caused by the interictal spike waveform and may be related to the underlying pathophysiology of IS.

SIGNIFICANCE

Dynamic changes in EEG-based FCNs during IEDs may be valuable for identification of pathological networks associated with epilepsy.

Abnormal dynamics of functional connectivity density in children with benign epilepsy with centrotemporal spikes

Converging evidence has shown the link between benign epilepsy with centrotemporal spikes (BECTS) and abnormal functional connectivity among distant brain regions. However, prior research in BECTS has not examined the dynamic changes in functional connectivity as networks form. We combined functional connectivity density (FCD) mapping and sliding windows correlation analyses, to fully capture the functional dynamics in patients with respect to the presence of interictal epileptic discharges (IEDs). Resting-state fMRI was performed in 43 BECTS patients and 28 healthy controls (HC). Patients were further classified into two subgroups, namely, IED (n = 20) and non-IED (n = 23) depending on the simultaneous EEG-fMRI recordings. The global dynamic FCD (dFCD) was measured using sliding window correlation. Then we quantified dFCD variability using their standard deviation. Compared with HC, patients with and without IEDs both showed invariable dFCD (decreased) among the orbital fontal cortex, anterior cingulate cortex and striatum, as well as variable dFCD (increased) in the posterior default mode network (P < 0.05, AlphaSim corrected). Correlation analysis indicated that the variable dFCD in precuneus was related to seizure onset age (P < 0.05, uncorrected). BECTS with IEDs showed variable dFCD in regions related to the typical seizure semiology. The abnormal patterns of fluctuating FCD in BECTS suggest that both active and chronic epileptic state may contribute to altered dynamics of functional connectivity associated with cognitive disturbances and developmental alterations. These findings highlight the importance of considering fluctuating dynamic neural communication among brain systems to deepen our understanding of epilepsy diseases.

Epilepsy syndromes of childhood with sleep activation: Insights from functional imaging

In epilepsy syndromes of childhood with sleep activation, defined as the spectrum of epileptic conditions going from classical benign childhood epilepsy with centrotemporal spikes (BECTS) to epileptic encephalopathy (EE) with continuous spike and waves during slow-wave sleep (CSWS) including Landau-Kleffner syndrome (LKS), a lot of functional imaging studies have been performed so far, leading to results that are not always consistent, related to the technique of neuroimaging performed and to the variability of the clinical phenotype. Most consistent findings are, depending of the method used, activations or increased regional glucose metabolism in the epileptogenic regions, and deactivations, hypometabolism or decreased functional connectivity in cortical regions that belong to the default mode network. Functional changes are either transitory, temporally related to the occurrence of interictal epileptiform discharges (IED), or permanent, persisting across IED-free periods. Some studies have shown that the more severe phenotype, i.e. EE with CSWS, displays the more profound functional disturbances. Taken together, functional imaging studies support the concept that IED impact cognition in epilepsy syndromes of childhood with sleep activation. However, the precise chronology between the occurrence of IED and the functional disturbances, the neuropsychological correlates of the functional disturbances, and the effects of the anti-epileptic treatments on IED, functional disturbances and cognition need to be further studied.

A 65-nm CMOS Lossless Bio-Signal Compression Circuit With 250 FemtoJoule Performance Per Bit

A 65 nm CMOS integrated circuit implementation of a bio-physiological signal compression device is presented, reporting exceptionally low power, and extremely low silicon area cost, relative to state-of-the-art. A novel 'xor-log2-sub-band' data compression scheme is evaluated, achieving modest compression, but with very low resource cost. With the intent to design the 'simplest useful compression algorithm', the outcome is demonstrated to be very favourable where power must be saved by trading off compression effort against data storage capacity, or data transmission power, even where more complex algorithms can deliver higher compression ratios. A VLSI design and fabricated Integrated Circuit implementation are presented, and estimated performance gains and efficiency measures for various bio-medical use-cases are given. Power costs as low as 1.2 pJ per sample-bit are suggested for a 10 kSa/s data-rate, whilst utilizing a power-gating scenario, and dropping to 250 fJ/bit at continuous conversion data-rates of 5 MSa/sec. This is achieved with a diminutive circuit area of 155 um². Both power and area appear to be state-of-the-art in terms of compression versus resource cost, and this yields benefit for system optimization.

Functional and Structural Network Disorganizations in Typical Epilepsy With Centro-Temporal Spikes and Impact on Cognitive Neurodevelopment

Epilepsy with Centrotemporal Spikes (ECTS) is the most common form of self-limited focal epilepsy. The pathophysiological mechanisms by which ECTS induces neuropsychological impairment in 15-30% of affected children remain unclear. The objective of this study is to review the current state of knowledge concerning the brain structural and functional changes that may be involved in cognitive dysfunctions in ECTS. Structural brain imaging suggests the presence of subtle neurodevelopmental changes over the epileptogenic zone and over distant regions in ECTS. This structural remodeling likely occurs prior to the diagnosis and evolves over time, especially in patients with cognitive impairment, suggesting that the epileptogenic processes might interfere with the dynamics of the brain development and/or the normal maturation processes. Functional brain imaging demonstrates profound disorganization accentuated by interictal epileptic spikes (IES) in the epileptogenic zone and in remote networks in ECTS. Over the epileptogenic zone, the literature demonstrates changes in term of neuronal activity and synchronization, which are effective several hundred milliseconds before the IES. In the same time window, functional changes are also observed in bilateral distant networks, notably in the frontal and temporal lobes. Effective connectivity demonstrates that the epileptogenic zone constitutes the key area at the origin of IES propagation toward distant cortical regions, including frontal areas. Altogether, structural and functional network disorganizations, in terms of: (i) power spectral values, (ii) functional and effective connectivity, are likely to participate in the cognitive impairment commonly reported in children with ECTS. These results suggest a central and causal role of network disorganizations related to IES in the neuropsychological impairment described in ECTS children.

Changes in background electroencephalographic activity in benign childhood epilepsy with centrotemporal spikes after oxcarbazepine treatment: a standardized low-resolution brain electromagnetic tomography (sLORETA) study

Background

Several neuroimaging studies have reported neurophysiological alterations in patients with benign childhood epilepsy with centrotemporal spikes (BCECTS). However, reported outcomes have been inconsistent, and the progression of these changes in the brain remains unresolved. Moreover, background electroencephalography (EEG) in cases of BCECTS has not been performed often.

Methods

We investigated background EEG activity changes after six months of oxcarbazepine treatment to better understand the neurophysiological alterations and progression that occur in BCECTS. In 18 children with BCECTS, non-parametric statistical analyses using standardized low resolution brain electromagnetic tomography (sLORETA) were performed to compare the current density distribution of four frequency bands (delta, theta, alpha, and beta) between untreated and treated conditions.

Results

Background EEG activity for the delta frequency band was significantly decreased in the fronto-temporal and limbic regions of the left hemisphere after oxcarbazepine treatment (threshold log-F-ratio = ±2.729, P < 0.01). The maximum current density difference was found in the parahippocampal gyrus of the left limbic lobe (Montreal Neurological Institute coordinate [x, y, z = 25, − 20, − 10], Brodmann area 28) (log-F-ratio = 3.081, P < 0.01).

Conclusions

Our results indicate the involvement of the fronto-temporal and limbic cortices in BCECTS, and limbic lobe involvement, including the parahippocampal gyrus, was noted. In addition to evidence of the involvement of the fronto-temporal and limbic cortices in BCECTS, this study also found that an antiepileptic drug could reduce the delta frequency activity of the background EEG in these regions.

Trait related sensorimotor deficits in people who stutter: An EEG investigation of μ rhythm dynamics during spontaneous fluency

Stuttering is associated with compromised sensorimotor control (i.e., internal modeling) across the dorsal stream and oscillations of EEG mu (μ) rhythms have been proposed as reliable indices of anterior dorsal stream processing. The purpose of this study was to compare μ rhythm oscillatory activity between (PWS) and matched typically fluent speakers (TFS) during spontaneously fluent overt and covert speech production tasks. Independent component analysis identified bilateral μ components from 24/27 PWS and matched TFS that localized over premotor cortex. Time-frequency analysis of the left hemisphere μ clusters demonstrated significantly reduced μ-α and μ-β ERD (pCLUSTER < 0.05) in PWS across the time course of overt and covert speech production, while no group differences were found in the right hemisphere in any condition. Results were interpreted through the framework of State Feedback Control. They suggest that weak forward modeling and evaluation of sensory feedback across the time course of speech production characterizes the trait related sensorimotor impairment in PWS. This weakness is proposed to represent an underlying sensorimotor instability that may predispose the speech of PWS to breakdown.

The focal alteration and causal connectivity in children with new-onset benign epilepsy with centrotemporal spikes

The aim of the current study was to find the epileptic focus and examine its causal relationship to other brain regions in children with new-onset benign childhood epilepsy with centrotemporal spikes (BECTS). Resting-state functional magnetic resonance imaging (fMRI) was performed in 66 children with BECTS and 37 matched control children. We compared the amplitude of low frequency fluctuation (ALFF) signals between the two groups to find the potential epileptogenic zone (EZ), then used Granger causality analysis (GCA) to explore the causal effects of EZ on the whole brain. Children with BECTS had significantly increased ALFF in the right Broca’s area, and decreased ALFF in bilateral fusiform gyrus. The patients also showed increased driving effect from the EZ in Broca’s area to the right prefrontal lobe, and decreased effects to the frontal lobe and posterior parts of the language network. The causal effect on left Wernicke’s area negatively correlated with verbal IQ (VIQ) score. Our research on new-onset BECTS patients illustrates a possible compensatory mechanism in the language network at early stages of BECTS, and the negative correlation of GCA and VIQ suggest the disturbance of epileptiform activity on language. These findings shed light on the mechanisms of and language dysfunction in BECTS.

Quantitative EEG findings and response to treatment with antiepileptic medications in children with epilepsy

BACKGROUND

Epilepsy is a common chronic disorder in pediatric neurology. Nowadays, a variety of antiepileptic drugs (AEDs) are available. A scientific method designed to evaluate the effectiveness of AEDs in the early stage of treatment has not been reported.

PURPOSE

In this study, we try to use quantitative EEG (QEEG) analysis as a biomarker to evaluate therapeutic effectiveness.

METHODS

20 epileptic children were enrolled in this study. Participants were classified as effective if they achieved a reduction in seizure frequency over 50%. Ineffective was defined as a reduction in seizure frequency less than 50%. Eleven participants were placed in the effective group, the remaining 9 participants were placed in the ineffective group. EEG segments before and after 1-3months of antiepileptic drugs start/change were analyzed and compared by QEEG analysis. The follow-up EEG segments after the 2nd examinations were used to test the accuracy of the analytic results.

RESULTS

Six crucial EEG feature descriptors were selected for classifying the effective and ineffective groups. Significantly increased RelPowAlpha_avg_AVG, RelPowAlpha_snr_AVG, HjorthM_avg_AVG, and DecorrTime_snr_AVG values were found in the effective group as compared to the ineffective group. On the contrary, there were significantly decreases in DecorrTime_std_AVG, and Wavelet_db4_EnergyBand_5_avg_AVG values in the effective group as compared to the ineffective group. The analyses yielded a precision rate of 100%. When the follow-up EEG segments were used to test the analytic results, the accuracy was 83.3%.

CONCLUSION

The developed method is a useful tool in analyzing the effectiveness of antiepileptic drugs. This method may assist pediatric neurologists in evaluating the efficacy of AEDs and making antiepileptic drug adjustments when managing epileptic patients in the early stage.

Identifying neural drivers of benign childhood epilepsy with centrotemporal spikes

Epilepsy is a neurological disorder characterized by abnormal electrical discharges in a group of brain cells. Benign childhood epilepsy, which affect children under the age of 12 years, has been reported to contribute to the cognitive impairment of these children, even in the absence of structural abnormalities. Functional connectivity models have been applied to provide a deeper understanding of the processes that control and regulate interictal activity of benign childhood epilepsy. These studies have shown regions of increased connectivity and activity, particularly at the epileptic zone, which is usually the central region around the sensorimotor cortex, and in the immediate regions surrounding the zone and reduced activity in distant regions, such as the frontal lobe and temporal regions. The present study was designed to identify the neural drivers involved in the initiation and propagation of epileptic activity and the causal relationships between brain regions with increased and decreased connectivity and functional activity. We used three different models to identify neural drivers and casual connectivity with dynamic causal modelling (DCM) of EEG data. All models showed that the central region, the source of the epileptic activity, is the major driver of the brain network during interictal discharges. Other regions include the temporoparietal junction and temporal pole. The central region also had influence on the frontal and contralateral hemisphere, which might explain the cognitive deficits observed in these patients.

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The epileptic source is the major driver of the brain network

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Other drivers include the temporoparietal junction and temporal pole

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Epileptic source had influence on the frontal region which might explain the cognitive deficits

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The right epileptic region drives the left hemisphere during interictal epileptic discharges

EEG Mu (µ) rhythm spectra and oscillatory activity differentiate stuttering from non-stuttering adults

Stuttering is linked to sensorimotor deficits related to internal modeling mechanisms. This study compared spectral power and oscillatory activity of EEG mu (μ) rhythms between persons who stutter (PWS) and controls in listening and auditory discrimination tasks. EEG data were analyzed from passive listening in noise and accurate (same/different) discrimination of tones or syllables in quiet and noisy backgrounds. Independent component analysis identified left and/or right μ rhythms with characteristic alpha (α) and beta (β) peaks localized to premotor/motor regions in 23 of 27 people who stutter (PWS) and 24 of 27 controls. PWS produced μ spectra with reduced β amplitudes across conditions, suggesting reduced forward modeling capacity. Group time-frequency differences were associated with noisy conditions only. PWS showed increased μ-β desynchronization when listening to noise and early in discrimination events, suggesting evidence of heightened motor activity that might be related to forward modeling deficits. PWS also showed reduced μ-α synchronization in discrimination conditions, indicating reduced sensory gating. Together these findings indicate spectral and oscillatory analyses of μ rhythms are sensitive to stuttering. More specifically, they can reveal stuttering-related sensorimotor processing differences in listening and auditory discrimination that also may be influenced by basal ganglia deficits.

Local and Distant Dysregulation of Synchronization Around Interictal Spikes in BECTS

Objective: High Density electroencephalography (HD EEG) is the reference non-invasive technique to investigate the dynamics of neuronal networks in Benign Epilepsy with Centro-Temporal Spikes (BECTS). Analysis of local dynamic changes surrounding Interictal Epileptic Spikes (IES) might improve our knowledge of the mechanisms that propel neurons to the hypersynchronization of IES in BECTS. Transient distant changes in the dynamics of neurons populations may also interact with neuronal networks involved in various functions that are impaired in BECTS patients.

Methods: HD EEG (64 electrodes) of eight well-characterized BECTS patients (8 males; mean age: 7.2 years, range: 5–9 years) were analyzed. Unilateral IES were selected in 6 patients. They were bilateral and independent in 2 other patients. This resulted in a total of 10 groups of IES. Time-frequency analysis was performed on HD EEG epochs around the peak of the IES (±1000 ms), including phase-locked and non-phase-locked activities to the IES. The time frequency analyses were calculated for the frequencies between 4 and 200 Hz.

Results: Time-frequency analysis revealed two patterns of dysregulation of the synchronization between neuronal networks preceding and following hypersynchronization of interictal spikes (±400 ms) in the epileptogenic zone. Dysregulation consists of either desynchronization (n = 6) or oscillating synchronization (n = 4) (4–50 Hz) surrounding the IES. The 2 patients with bilateral IES exhibited only local desynchronization whatever the IES considered. Distant desynchronization in low frequencies within the same window occurs simultaneously in bilateral frontal, temporal and occipital areas (n = 7).

Significance: Using time-frequency analysis of HD EEG data in a well-defined population of BECTS, we demonstrated repeated complex changes in the dynamics of neuronal networks not only during, but also, before and after the IES. In the epileptogenic zone, our results found more complex reorganization of the local network than initially thought. In line with previous results obtained at a microscopic or macroscopic level, these changes suggested the variability strategies of neuronal assemblies to raise IES. Distant changes from the epileptogenic zone in desynchronization observed in the same time window suggested interactions between larger embedded networks and opened new avenues about their possible role in the underlying mechanism leading to cognitive deficits.

Childhood epilepsies: What should a pediatrician know?

Seizures in children are among the most common neurological disorders. A pediatrician should know how to approach a child who presents with a seizure. This review will focus on points that are important in the evaluation of children who have experienced seizures. A comprehensive and neurologically focused framework for history taking and a thorough clinical examination are the cornerstones in diagnosing and managing seizures. This article reviews the clinical approach to the diagnosis, investigation, and management of epilepsy in children, excluding neonatal seizures. A pediatrician should also be aware of common epilepsy syndromes that occur in children such as Benign Childhood Epilepsy with Centro-Temporal Spikes, and childhood absence epilepsy.

EEG Resting State Functional Connectivity Analysis in Children with Benign Epilepsy with Centrotemporal Spikes

In this study, we investigated changes in functional connectivity (FC) of the brain networks in patients with benign epilepsy with centrotemporal spikes (BECTS) compared to healthy controls using high-density EEG data collected under eyes-closed resting state condition. EEG source reconstruction was performed with exact Low Resolution Electromagnetic Tomography (eLORETA). We investigated FC between 84 Brodmann areas using lagged phase synchronization (LPS) in four frequency bands (δ, θ, α, and β). We further computed the network degree, clustering coefficient and efficiency. Compared to controls, patients displayed higher θ and α and lower β LPS values. In these frequency bands, patients were also characterized by less well ordered brain networks exhibiting higher global degrees and efficiencies and lower clustering coefficients. In the β band, patients exhibited reduced functional segregation and integration due to loss of both local and long-distance functional connections. These findings suggest that benign epileptic brain networks might be functionally disrupted due to their altered functional organization especially in the α and β frequency bands.