Altered Static and Dynamic Spontaneous Neural Activity in Drug-Naïve and Drug-Receiving Benign Childhood Epilepsy With Centrotemporal Spikes

Abstract

The present study aims to investigate intrinsic abnormalities of brain and the effect of antiepileptic treatment on brain activity in Benign childhood epilepsy with centrotemporal spikes (BECTS). Twenty-six drug-naïve patients (DNP) and 22 drug-receiving patients (DRP) with BECTS were collected in this study. Static amplitude of low frequency fluctuation (sALFF) and dynamic ALFF (dALFF) were applied to resting-state fMRI data. Functional connectivity (FC) analysis was further performed for affected regions identified by static and dynamic analysis. One-way analysis of variance and post hoc statistical analyses were performed for between-group differences. Abnormal sALFF and dALFF values were correlated with clinical features of patients. Compared with healthy controls (HC), DNP group demonstrated alterations of sALFF and/or dALFF in medial prefrontal cortex (MPFC), supplementary motor areas (SMA), cerebellum, hippocampus, pallidum and cingulate cortex, in which the values were close to normal in DRP. Notably, sALFF and dALFF showed specific sensitivity in detecting abnormalities in basal ganglia and cerebellum. Additionally, DRP showed additional changes in precuneus, inferior temporal gyrus, superior frontal gyrus and occipital visual cortex. Compared with HC, the DNP showed increased FC in default network and motion-related networks, and the DRP showed decreased FC in default network. The MPFC, hippocampus, SMA, basal ganglia and cerebellum are indicated to be intrinsically affected regions and effective therapeutic targets. And the FC profiles of default and motion-related networks might be potential core indicators for clinical treatment. This study revealed potential neuromodulatory targets and helped understand pathomechanism of BECTS. Static and dynamic analyses should be combined to investigate neuropsychiatric disorders.

Impact of Antiepileptic Drugs on Cognition and Neuromagnetic Activity in Childhood Epilepsy With Centrotemporal Spikes: A Magnetoencephalography Study

“…This further supports the theory that neuromagnetic signals of different frequency bands represent distinct inherent physiological activities (Tenney et al, 2014;Tang et al, 2016;Zhang et al, 2020). In agreement with fMRI evidence based on amplitude of low frequency fluctuation (Jiang et al, 2020) and functional covariance connectivity (Jiang et al, 2019), our results suggest that AEDs have effects on brain regional activity and functional networks. The analysis of the magnetic source location exhibited that, after treatment, activation of PCC increased in multiple frequency bands, and the differences were evident in the 30-80 Hz frequency band.…”

“…First, the number of participants who completed the follow-up was less than expected, and the small sample size weakened the statistical power and the generalizability of the conclusions, to some extent. Meanwhile, this study design was not able to compare brain activity between untreated CECTS children and matched healthy controls, so while several previous studies have reported comparative results for this purpose among untreated children and healthy controls (Jiang et al, 2019(Jiang et al, , 2020Li et al, 2020b), we still cannot assert that all the cognitive improvements can be attributed to AEDs. Additionally, this study, limited by sample size, did not group the types of AEDs and the prognosis of the children, which can cause mixed effects.…”

“…To date, numerous studies have demonstrated that the restingstate brain activity of children with CECTS has been altered (McGinnity et al, 2017;Bourel-Ponchel et al, 2019;Zhang et al, 2020). On this basis, several studies based on functional magnetic resonance (fMRI) have further investigated brain alterations in CECTS during AEDs treatment, the results of which have shown that AEDs have an effect on functional connectivity (FC) (Jiang et al, 2019(Jiang et al, , 2020), and regional activity (Zhang et al, 2017(Zhang et al, , 2018. Unfortunately, these studies are all cross-sectional studies, rather than longitudinal follow-up studies, and lead to limited convincing results.…”

Dynamic Altered Amplitude of Low-Frequency Fluctuations in Patients With Major Depressive Disorder

“…Functional images were preprocessed using a software (Data Processing and Analysis for Brain Imaging toolbox; http://rfmri.org/DPABI ) ( 46 ). The main steps were included: (1) exclusion of the initial 10 volumes to ensure signal stability; (2) slice timing and realignment; (3) spatial normalization to the standard Montreal Neurological Institute (MNI 152) space and resampled to 3 × 3 × 3 mm 3 ; (4) spatial smoothing using a 6-mm full-width half-maximum Gaussian kernel; (5) detrending the BOLD signals to correct a linear trend; (6) regression out of the nuisance covariates including the averaged signals from global mean signals ( 22 , 28 , 30 , 47 ), cerebrospinal fluid signals, white matter signals, and Friston-24 head motion parameters; (7) temporal filtering (bandpass, 0.01–0.08 Hz) of BOLD signals; (8) to exclude the influence of head motion and ensure the contiguous time points, scrubbing with cubic spline interpolation was used; (9) additionally, to evaluate the head movement, we also calculate the mean frame-wise displacement (FD) ( 48 , 49 ). In the group-level analysis, we also used the mean FD as a covariate to reduce the impact of motion artifact in the fMRI signal.…”

More than just statics: Static and temporal dynamic changes in intrinsic brain activity in unilateral temporal lobe epilepsy

“…In a literature search of the aforementioned IBA dynamic indicators, most research on TLE was found to focus on dynamic FC studies ( Jiang et al, 2020 ; Li et al, 2022 ; Pang et al, 2022 ). However, the relevant studies which applied the other dynamic indicators, such as dALFF, dfALFF, dReHo, dDC, dVMHC and dGSCorr, in TLE patients could not be retrieved.…”