Rhythmic activity in EEG and sleep in rats with absence epilepsy

Epileptic seizure clustering and accumulation at transition from activity to rest in GAERS rats

Knowing when seizures occur may help patients and can also provide insight into epileptogenesis mechanisms. We recorded seizures over periods of several days in the Genetic Absence Epileptic Rat from Strasbourg (GAERS) model of absence epilepsy, while we monitored behavioral activity with a combined head accelerometer (ACCEL), neck electromyogram (EMG), and electrooculogram (EOG). The three markers consistently discriminated between states of behavioral activity and rest. Both GAERS and control Wistar rats spent more time in rest (55-66%) than in activity (34-45%), yet GAERS showed prolonged continuous episodes of activity (23 vs. 18 min) and rest (34 vs. 30 min). On average, seizures lasted 13 s and were separated by 3.2 min. Isolated seizures were associated with a decrease in the power of the activity markers from steep for ACCEL to moderate for EMG and weak for EOG, with ACCEL and EMG power changes starting before seizure onset. Seizures tended to occur in bursts, with the probability of seizing significantly increasing around a seizure in a window of ±4 min. Furthermore, the seizure rate was strongly increased for several minutes when transitioning from activity to rest. These results point to mechanisms that control behavioral states as determining factors of seizure occurrence.

A simple and fast ANN-based method of studying slow-wave sleep microstructure in freely moving rats

Electroencephalography (EEG) is a common technique for measuring brain activity. Artificial Neuronal Networks (ANNs) can provide valuable insights into the brain dynamics of humans and animals. We built a simple and fast shallow ANN-based solution for sleep recognition in EEGs recorded in freely moving rats. The ANN was constructed using open-source software and truncated to one formula with empirically defined weight coefficients. The optimization of the ANN model's performance (i.e., post-processing) relied on a probability-related approach to sleep microstructure. This approach could be a good way to analyze large datasets. In the current dataset, the slow-wave sleep was recognized with the sensitivity of 0.91 and the specificity of 0.98. The optimal model performance achieved with minimum sleep duration of 80-90 s and sleep interruption of 14-18 s. Our results suggest the following fundamental issues. First, 14-18 s sleep interruptions might be the archetypal micro-arousals in rats. Second, slow-wave sleep in rats might be built up of a set of sleep "building blocks" lasting 80-90 s.

Alpha2 Adrenergic Modulation of Spike-Wave Epilepsy: Experimental Study of Pro-Epileptic and Sedative Effects of Dexmedetomidine

In the present report, we evaluated adrenergic mechanisms of generalized spike-wave epileptic discharges (SWDs), which are the encephalographic hallmarks of idiopathic generalized epilepsies. SWDs link to a hyper-synchronization in the thalamocortical neuronal activity. We unclosed some alpha2-adrenergic mechanisms of sedation and provocation of SWDs in rats with spontaneous spike-wave epilepsy (WAG/Rij and Wistar) and in control non-epileptic rats (NEW) of both sexes. Dexmedetomidine (Dex) was a highly selective alpha-2 agonist (0.003-0.049 mg/kg, i.p.). Injections of Dex did not elicit de novo SWDs in non-epileptic rats. Dex can be used to disclose the latent form of spike-wave epilepsy. Subjects with long-lasting SWDs at baseline were at high risk of absence status after activation of alpha2- adrenergic receptors. We create the concept of alpha1- and alpha2-ARs regulation of SWDs via modulation of thalamocortical network activity. Dex induced the specific abnormal state favorable for SWDs-"alpha2 wakefulness". Dex is regularly used in clinical practice. EEG examination in patients using low doses of Dex might help to diagnose the latent forms of absence epilepsy (or pathology of cortico-thalamo-cortical circuitry).

Sex Differences in Behavior and Learning Abilities in Adult Rats

Laboratory rats have excellent learning abilities and are often used in cognitive neuroscience research. The majority of rat studies are conducted on males, whereas females are usually overlooked. Here, we examined sex differences in behavior and tactile sensitivity in littermates during adulthood (5.8-7.6 months of age). We used a battery of behavioral tests, including the 2% sucrose preference test (positive motivation), a free-choice paradigm (T-maze, neutral situation), and associative fear-avoidance learning (negative motivation, aversive situation). Tactile perception was examined using the von Frey test (aversive situation). In two aversive situations (von Frey test and avoidance learning), females were examined during the diestrus stage of the estrous cycle, and ultrasonic vocalization was recorded in both sexes. It was found that (1) females, but not males, lost their body weight on the first day of the sucrose preference test, suggesting sex differences in their reaction to environmental novelty or in metabolic homeostasis; (2) the tactile threshold in females was lower than in males, and females less frequently emitted aversive ultrasonic calls; (3) in the avoidance learning task, around 26% of males (but no females) were not able to learn and experienced frizzing. Overall, the performance of associative fear-avoidance in males was worse than in females. In general, females demonstrated higher abilities of associative learning and less persistently emitted aversive ultrasonic calls.

Spike-Wave Seizures, NREM Sleep and Micro-Arousals in WAG/Rij Rats with Genetic Predisposition to Absence Epilepsy: Developmental Aspects

The current study was done in Wistar Albino Glaxo Rijswijk (WAG/Rij) rats, which are genetically prone to develop spontaneous spike-wave discharges (SWDs) and are widely used as a genetic model of absence epilepsy. Here, we examined functional links between sleep and spike-wave epilepsy in aging WAG/Rij rats using advanced techniques of EEG analysis. SWDs, periods of NREM sleep and micro-arousals were automatically detected in three-channel epidural EEG recorded in freely moving WAG/Rij rats consequently at the age 5, 7 and 9 months. We characterized the developmental profile of spike-wave epilepsy in drug-naïve WAG/Rij rats and defined three epi-phenotypes—severe, mild and minor epilepsy. Age-related changes of SWDs were associated with changes in NREM sleep. Several signs of NREM sleep fragmentation were defined in epileptic WAG/Rij rats. It seems that spike-wave epilepsy per se promotes micro-arousals during NREM sleep. However, subjects with a higher number of micro-arousals (and NREM sleep episodes) at the age of 5 months were characterized by a reduction of SWDs between 5 and 7 months of age.

Multimodal Autoencoder Predicts fNIRS Resting State From EEG Signals

In this work, we introduce a deep learning architecture for evaluation on multimodal electroencephalographic (EEG) and functional near-infrared spectroscopy (fNIRS) recordings from 40 epileptic patients. Long short-term memory units and convolutional neural networks are integrated within a multimodal sequence-to-sequence autoencoder. The trained neural network predicts fNIRS signals from EEG, sans a priori, by hierarchically extracting deep features from EEG full spectra and specific EEG frequency bands. Results show that higher frequency EEG ranges are predictive of fNIRS signals with the gamma band inputs dominating fNIRS prediction as compared to other frequency envelopes. Seed based functional connectivity validates similar patterns between experimental fNIRS and our model's fNIRS reconstructions. This is the first study that shows it is possible to predict brain hemodynamics (fNIRS) from encoded neural data (EEG) in the resting human epileptic brain based on power spectrum amplitude modulation of frequency oscillations in the context of specific hypotheses about how EEG frequency bands decode fNIRS signals.

Sleep Disturbances in Rats With Genetic Pre-disposition to Spike-Wave Epilepsy (WAG/Rij)

Wistar Albino Glaxo Rijswijk (WAG/Rij) rats are widely used in basic and pre-clinical studies as a valid genetic model of absence epilepsy. Adult WAG/Rij rats exhibit generalized 8–10-Hz spike-wave discharges (SWDs) in the electroencephalogram. SWDs are known to result from thalamocortical circuit dysfunction, and this implies an intimate relationship between slow-wave EEG activity, sleep spindles, and SWDs. The present mini review summarizes relevant research on sleep-related disturbances associated with spike-wave epilepsy in WAG/Rij rats in the domain of slow-wave sleep EEG and microarousals. It also discusses enhancement of the intermediate stage of sleep. In general, sleep EEG studies provide important information about epileptogenic processes related to spike-wave epilepsy.

Spike-wave seizures, slow-wave sleep EEG and morphology of substantia nigra pars compacta in WAG/Rij rats with genetic predisposition to absence epilepsy

Spike-wave discharges (SWDs) are EEG hallmarks of absence epilepsy, and they spontaneously appear in adult WAG/Rij rats. SWDs are known to be vigilance-dependent and are modulated by monoaminergic mechanisms. It is also known that loss of neurons in the center of the nigrostriatal dopamine system, substantia nigra pars compacta (SNc), is associated with a variety of sleep disorders. We hypothesized that a disorder of the nigrostriatal dopamine system described for WAG/Rij rats might facilitate generation of SWDs through changes in vigilance state and the quality of sleep. Our study was conducted in 'epileptic' and 'non-epileptic' phenotype (less than 1 SWDs per h). Analysis included (1) EEG examination, i.e., analysis of SWDs, rudimentary SWDs and slow wave sleep EEG and (2) microstructural examination of SNc, i.e., measuring its size and the number of neurons and glial cells. No differences in size and cellular content of SNc were found between 'epileptic' and 'non-epileptic' phenotypes. Meanwhile in 'epileptic' subjects, the number of SWDs correlated with the number of neurons in SNc (SWDs more frequently occurred in subjects with fewer neurons in SNc). Rudimentary SWDs were found in both phenotypes. No differences in number and duration of rudimentary SWDs were found between 'epileptic' and 'non-epileptic' phenotypes. Spike-wave EEG activity showed strong association with the number of neurons in SNc: subjects with fewer neurons in SNc were characterized by higher number of SWDs and longer rudimentary SWDs. In sum, our data suggested that intense epileptic EEG activity (in the form of SWDs and rudimentary SWDs) might lead to sleep disruption. However, the lack of direct correlations between sleep parameters and SWDs number indicated that the link between sleep features, SNc cellularity and spike-wave EEG activity could be more complex than we had expected.

Automatic wavelet-based assessment of behavioral sleep using multichannel electrocorticography in rats

PURPOSE

During the last decade, the reported prevalence of sleep-disordered breathing in adults has been rapidly increasing. Therefore, automatic methods of sleep assessment are of particular interest. In a framework of translational neuroscience, this study introduces a reliable automatic detection system of behavioral sleep in laboratory rats based on the signal recorded at the cortical surface without requiring electromyography.

METHODS

Experimental data were obtained in 16 adult male WAG/Rij rats at the age of 9 months. Electrocorticographic signals (ECoG) were recorded in freely moving rats during the entire day (22.5 ± 2.2 h). Automatic wavelet-based assessment of behavioral sleep (BS) was proposed. The performance of this wavelet-based method was validated in a group of rats with genetic predisposition to absence epilepsy (n=16) based on visual analysis of their behavior in simultaneously recorded video.

RESULTS

The accuracy of automatic sleep detection was 98% over a 24-h period. An automatic BS assessment method can be adjusted for detecting short arousals during sleep (microarousals) with various duration.

CONCLUSIONS

These findings suggest that automatic wavelet-based assessment of behavioral sleep can be used for assessment of sleep quality. Current analysis indicates a temporal relationship between microarousals, sleep, and epileptic discharges in genetically prone subjects.

Electro-Quasistatic Animal Body Communication for Untethered Rodent Biopotential Recording

Continuous multi-channel monitoring of biopotential signals is vital in understanding the body as a whole, facilitating accurate models and predictions in neural research. The current state of the art in wireless technologies for untethered biopotential recordings rely on radiative electromagnetic (EM) fields. In such transmissions, only a small fraction of this energy is received since the EM fields are widely radiated resulting in lossy inefficient systems. Using the body as a communication medium (similar to a 'wire') allows for the containment of the energy within the body, yielding order(s) of magnitude lower energy than radiative EM communication. In this work, we introduce Animal Body Communication (ABC), which utilizes the concept of using the body as a medium into the domain of untethered animal biopotential recording. This work, for the first time, develops the theory and models for animal body communication circuitry and channel loss. Using this theoretical model, a sub-inch[Formula: see text] [1″ × 1″ × 0.4″], custom-designed sensor node is built using off the shelf components which is capable of sensing and transmitting biopotential signals, through the body of the rat at significantly lower powers compared to traditional wireless transmissions. In-vivo experimental analysis proves that ABC successfully transmits acquired electrocardiogram (EKG) signals through the body with correlation [Formula: see text] when compared to traditional wireless communication modalities, with a 50[Formula: see text] reduction in power consumption.

Modulation in phase and frequency of neural oscillations during epileptiform activity induced by neonatal Zika virus infection in mice

Modulation of brain activity is one of the main mechanisms capable of demonstrating the synchronization dynamics of neural oscillations. In epilepsy, modulation is a key concept since seizures essentially result from neural hypersynchronization and hyperexcitability. In this study, we have introduced a time-dependent index based on the Kullback-Leibler divergence to quantify the effects of phase and frequency modulations of neural oscillations in neonatal mice exhibiting epileptiform activity induced by Zika virus (ZIKV) infection. Through this index, we demonstrate that fast oscillations (gamma and beta 2) are the more susceptible modulated rhythms in terms of phase, during seizures, whereas slow waves (delta and theta) mainly undergo changes in frequency. The index also allowed detection of specific patterns associated with the interdependent modulation of phase and frequency in neural activity. Furthermore, by comparing ZIKV modulations with the general computational model Epileptors, we verify different signatures related to the brain rhythms modulation in phase and frequency. These findings instigate new studies on the effects of ZIKV infection on neuronal networks from electrophysiological activities, and how different mechanisms can trigger epilepsy.

Slow-wave activity preceding the onset of 10-15-Hz sleep spindles and 5-9-Hz oscillations in electroencephalograms in rats with and without absence seizures

Cortico-thalamocortical networks generate sleep spindles and slow waves during non-rapid eye movement sleep, as well as paroxysmal spike-wave discharges (i.e. electroencephalogram manifestation of absence epilepsy) and 5-9-Hz oscillations in genetic rat models (i.e. pro-epileptic activity). Absence epilepsy is a disorder of the thalamocortical network. We tested a hypothesis that absence epilepsy associates with changes in the slow-wave activity before the onset of sleep spindles and pro-epileptic 5-9-Hz oscillations. The study was performed in the WAG/Rij genetic rat model of absence epilepsy and Wistar rats at the age of 9-12 months. Electroencephalograms were recorded with epidural electrodes from the anterior cortex. Sleep spindles (10-15 Hz), 5-9-Hz oscillations and their slow-wave (2-7 Hz) precursors were automatically detected and analysed using continuous wavelet transform. Subjects with electroencephalogram seizures (the "epileptic" phenotype) and without seizure activity (the "non-epileptic" phenotype) were identified in both strains. It was found that time-amplitude features of sleep spindles and 5-9-Hz oscillations were similar in both rat strains and in both phenotypes. Sleep spindles in "epileptic" rats were more often preceded by the slow-wave (~4 Hz) activity than in "non-epileptic" rats. The intrinsic frequency of slow-wave precursors of sleep spindles and 5-9-Hz oscillations in "epileptic" rats was 1-1.5 Hz higher than in "non-epileptic" rats. In general, our results indicated that absence epilepsy associated with: (a) the reinforcement of slow waves immediately prior to normal sleep spindles; and (b) weakening of amplitude growth in transition "slow wave → spindle/5-9-Hz oscillation".

Chronic pulmonary exposure to traffic-related fine particulate matter causes brain impairment in adult rats

BACKGROUND

Effects of air pollution on neurotoxicity and behavioral alterations have been reported. The objective of this study was to investigate the pathophysiology caused by particulate matter (PM) in the brain. We examined the effects of traffic-related particulate matter with an aerodynamic diameter of < 1 μm (PM₁), high-efficiency particulate air (HEPA)-filtered air, and clean air on the brain structure, behavioral changes, brainwaves, and bioreactivity of the brain (cortex, cerebellum, and hippocampus), olfactory bulb, and serum after 3 and 6 months of whole-body exposure in 6-month-old Sprague Dawley rats.

RESULTS

The rats were exposed to 16.3 ± 8.2 (4.7~ 68.8) μg/m³ of PM₁ during the study period. An MRI analysis showed that whole-brain and hippocampal volumes increased with 3 and 6 months of PM₁ exposure. A short-term memory deficiency occurred with 3 months of exposure to PM₁ as determined by a novel object recognition (NOR) task, but there were no significant changes in motor functions. There were no changes in frequency bands or multiscale entropy of brainwaves. Exposure to 3 months of PM₁ increased 8-isoporstance in the cortex, cerebellum, and hippocampus as well as hippocampal inflammation (interleukin (IL)-6), but not in the olfactory bulb. Systemic CCL11 (at 3 and 6 months) and IL-4 (at 6 months) increased after PM₁ exposure. Light chain 3 (LC3) expression increased in the hippocampus after 6 months of exposure. Spongiosis and neuronal shrinkage were observed in the cortex, cerebellum, and hippocampus (neuronal shrinkage) after exposure to air pollution. Additionally, microabscesses were observed in the cortex after 6 months of PM₁ exposure.

CONCLUSIONS

Our study first observed cerebral edema and brain impairment in adult rats after chronic exposure to traffic-related air pollution.

Chronic pulmonary exposure to traffic-related fine particulate matter causes brain impairment in adult rats

Background

Effects of air pollution on neurotoxicity and behavioral alterations have been reported. The objective of this study was to investigate the pathophysiology caused by particulate matter (PM) in the brain. We examined the effects of traffic-related particulate matter with an aerodynamic diameter of < 1 μm (PM₁), high-efficiency particulate air (HEPA)-filtered air, and clean air on the brain structure, behavioral changes, brainwaves, and bioreactivity of the brain (cortex, cerebellum, and hippocampus), olfactory bulb, and serum after 3 and 6 months of whole-body exposure in 6-month-old Sprague Dawley rats.

Results

The rats were exposed to 16.3 ± 8.2 (4.7~ 68.8) μg/m³ of PM₁ during the study period. An MRI analysis showed that whole-brain and hippocampal volumes increased with 3 and 6 months of PM₁ exposure. A short-term memory deficiency occurred with 3 months of exposure to PM₁ as determined by a novel object recognition (NOR) task, but there were no significant changes in motor functions. There were no changes in frequency bands or multiscale entropy of brainwaves. Exposure to 3 months of PM₁ increased 8-isoporstance in the cortex, cerebellum, and hippocampus as well as hippocampal inflammation (interleukin (IL)-6), but not in the olfactory bulb. Systemic CCL11 (at 3 and 6 months) and IL-4 (at 6 months) increased after PM₁ exposure. Light chain 3 (LC3) expression increased in the hippocampus after 6 months of exposure. Spongiosis and neuronal shrinkage were observed in the cortex, cerebellum, and hippocampus (neuronal shrinkage) after exposure to air pollution. Additionally, microabscesses were observed in the cortex after 6 months of PM₁ exposure.

Conclusions

Our study first observed cerebral edema and brain impairment in adult rats after chronic exposure to traffic-related air pollution.

Electronic supplementary material

The online version of this article (10.1186/s12989-018-0281-1) contains supplementary material, which is available to authorized users.

The pacemaker role of thalamic reticular nucleus in controlling spike-wave discharges and spindles

Absence epilepsy, characterized by 2-4 Hz spike-wave discharges (SWDs), can be caused by pathological interactions within the thalamocortical system. Cortical spindling oscillations are also demonstrated to involve the oscillatory thalamocortical rhythms generated by the synaptic circuitry of the thalamus and cortex. This implies that SWDs and spindling oscillations can share the common thalamocortical mechanism. Additionally, the thalamic reticular nucleus (RE) is hypothesized to regulate the onsets and propagations of both the epileptic SWDs and sleep spindles. Based on the proposed single-compartment thalamocortical neural field model, we firstly investigate the stimulation effect of RE on the initiations, terminations, and transitions of SWDs. It is shown that the activations and deactivations of RE triggered by single-pulse stimuli can drive the cortical subsystem to behave as the experimentally observed onsets and self-abatements of SWDs, as well as the transitions from 2-spike and wave discharges (2-SWDs) to SWDs. In particular, with increasing inhibition from RE to the specific relay nucleus (TC), rich transition behaviors in cortex can be obtained through the upstream projection path, RE→TC→Cortex. Although some of the complex dynamical patterns can be expected from the earlier single compartment thalamocortical model, the effect of brain network topology on the emergence of SWDs and spindles, as well as the transitions between them, has not been fully investigated. We thereby develop a spatially extended 3-compartment coupled network model with open-/closed-end connective configurations, to investigate the spatiotemporal effect of RE on the SWDs and spindles. Results show that the degrees of activations of RE₁ can induce the rich spatiotemporal evolution properties including the propagations from SWDs to spindles within different compartments and the transitions between them, through the RE₁→TC₁→Cortex₁ and Cortex₁→Cortex₂→Cortex₃ projecting paths, respectively. Overall, those results imply that RE possesses the pacemaker function in controlling SWDs and spindling oscillations, which computationally provide causal support for the involvement of RE in absence seizures and sleep spindles.