Dataset Information

Distinct Topographical Patterns of Spike-Wave Discharge in Transgenic and Pharmacologically Induced Absence Seizure Models.

ABSTRACT: Absence seizures (AS) are generalized non-convulsive seizures characterized by a brief loss of consciousness and spike-and-wave discharges (SWD) in an electroencephalogram (EEG). A number of animal models have been developed to explain the mechanisms of AS, and thalamo-cortical networks are considered to be involved. However, the cortical foci have not been well described in mouse models of AS. This study aims to use a high density EEG in pathophysiologically different AS models to compare the spatiotemporal patterns of SWDs. We used two AS models: a pharmacologically induced model (gamma-hydroxybutyric acid, GHB model) and a transgenic model (phospholipase beta4 knock-out, PLCβ4 model). The occurrences of SWDs were confirmed by thalamic recordings. The topographical analysis of SWDs showed that the onset and propagation patterns were markedly distinguishable between the two models. In the PLCβ4 model, the foci were located within the somatosensory cortex followed by propagation to the frontal cortex, whereas in the GHB model, a majority of SWDs was initiated in the prefrontal cortex followed by propagation to the posterior cortex. In addition, in the GHB model, foci were also observed in other cortical areas. This observation indicates that different cortical networks are involved in the generation of SWDs across the two models.

SUBMITTER: Lee S

PROVIDER: S-EPMC6751861 | biostudies-other | 2019 Aug

REPOSITORIES: biostudies-other

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Distinct Topographical Patterns of Spike-Wave Discharge in Transgenic and Pharmacologically Induced Absence Seizure Models.

Lee Soojung S Hwang Eunjin E Lee Mina M Choi Jee Hyun JH

Experimental neurobiology 20190801 4

Absence seizures (AS) are generalized non-convulsive seizures characterized by a brief loss of consciousness and spike-and-wave discharges (SWD) in an electroencephalogram (EEG). A number of animal models have been developed to explain the mechanisms of AS, and thalamo-cortical networks are considered to be involved. However, the cortical foci have not been well described in mouse models of AS. This study aims to use a high density EEG in pathophysiologically different AS models to compare the s ...[more]

PMID: 31495076

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Project description:IntroductionDifferent studies have investigated by means of EEG-fMRI coregistration the brain networks related to generalized spike-and-wave discharges (GSWD) in patients with idiopathic generalized epilepsy (IGE). These studies revealed a widespread GSWD-related neural network that involves the thalamus and regions of the default mode network. In this study we investigated which brain regions are critically involved in the termination of absence seizures (AS) in a group of IGE patients.MethodsEighteen patients (6 male; mean age 25 years) with AS were included in the EEG-fMRI study. Functional data were acquired at 3T with continuous simultaneous video-EEG recording. Event-related analysis was performed with SPM8 software, using the following regressors: (1) GSWD onset and duration; (2) GSWD offset. Data were analyzed at single-subject and at group level with a second level random effect analysis.ResultsA mean of 17 events for patient was recorded (mean duration of 4.2 sec). Group-level analysis related to GSWD onset respect to rest confirmed previous findings revealing thalamic activation and a precuneus/posterior cingulate deactivation. At GSWD termination we observed a decrease in BOLD signal over the bilateral dorsolateral frontal cortex respect to the baseline (and respect to GSWD onset). The contrast GSWD offset versus onset showed a BOLD signal increase over the precuneus-posterior cingulate region bilaterally. Parametric correlations between electro-clinical variables and BOLD signal at GSWD offset did not reveal significant effects.ConclusionThe role of the decreased neural activity of lateral prefrontal cortex at GSWD termination deserve future investigations to ascertain if it has a role in promoting the discharge offset, as well as in the determination of the cognitive deficits often present in patients with AS. The increased BOLD signal at precuneal/posterior cingulate cortex might reflect the recovery of neural activity in regions that are "suspended" during spike and waves activity, as previously hypothesized.

Project description:ObjectiveManual detection of spike-wave discharges (SWDs) from electroencephalography (EEG) records is time intensive, costly, and subject to inconsistencies/biases. In addition, manual scoring often omits information on SWD confidence/intensity, which may be important for the investigation of mechanistic-based research questions. Our objective is to develop an automated method for the detection of SWDs in a mouse model of absence epilepsy that is focused on the characteristics of human scoring of preselected events to establish a confidence-based, continuous-valued scoring.MethodsWe develop a support vector machine (SVM)-based algorithm for the automated detection of SWDs in the γ2R43Q mouse model of absence epilepsy. The algorithm first identifies putative SWD events using frequency- and amplitude-based peak detection. Four humans scored a set of 2500 putative events identified by the algorithm. Then, using predictors calculated from the wavelet transform of each event and the labels from human scoring, we trained an SVM to classify (SWD/nonSWD) and assign confidence scores to each event identified from 60, 24-hour EEG records. We provide a detailed assessment of intra- and interrater scoring that demonstrates advantages of automated scoring.ResultsThe algorithm scored SWDs along a continuum that is highly correlated with human confidence and that allows us to more effectively characterize ambiguous events. We demonstrate that events along our scoring continuum are temporally and proportionately correlated with abrupt changes in spectral power bands relevant to normal behavioral states including sleep.SignificanceAlthough there are automated and semi-automated methods for the detection of SWDs in humans and rats, we contribute to the need for continued development of SWD detection in mice. Our results demonstrate the value of viewing detection of SWDs as a continuous classification problem to better understand "ground truth" in SWD detection (ie, the most reliable features agreed upon by humans that also correlate with objective physiologic measures).

Dataset Information

Distinct Topographical Patterns of Spike-Wave Discharge in Transgenic and Pharmacologically Induced Absence Seizure Models.

Publications

Distinct Topographical Patterns of Spike-Wave Discharge in Transgenic and Pharmacologically Induced Absence Seizure Models.

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