Cellular-synaptic generation of sleep spindles, spike-and-wave discharges, and evoked thalamocortical responses in the neocortex of the rat

Cell-class-specific electric field entrainment of neural activity

Electric fields affect the activity of neurons and brain circuits, yet how this happens at the cellular level remains enigmatic. Lack of understanding of how to stimulate the brain to promote or suppress specific activity significantly limits basic research and clinical applications. Here, we study how electric fields impact subthreshold and spiking properties of major cortical neuronal classes. We find that neurons in the rodent and human cortex exhibit strong, cell-class-dependent entrainment that depends on stimulation frequency. Excitatory pyramidal neurons, with their slower spike rate, entrain to both slow and fast electric fields, while inhibitory classes like Pvalb and Sst (with their fast spiking) predominantly phase-lock to fast fields. We show that this spike-field entrainment is the result of two effects: non-specific membrane polarization occurring across classes and class-specific excitability properties. Importantly, these properties are present across cortical areas and species. These findings allow for the design of selective and class-specific neuromodulation.

Pathological and Physiological High-frequency Oscillations on Electroencephalography in Patients with Epilepsy

High-frequency oscillations (HFOs) encompass ripples (80 Hz-200 Hz) and fast ripples (200 Hz-600 Hz), serving as a promising biomarker for localizing the epileptogenic zone in epilepsy. Spontaneous fast ripples are always pathological, while ripples may be physiological or pathological. Distinguishing physiological from pathological ripples is important not only for designating epileptogenic brain regions, but also for investigations that study ripples in the context of memory encoding, consolidation, and recall in patients with epilepsy. Many studies have sought to identify distinguishing features between pathological and physiological ripples over the past two decades. Physiological and pathological ripples differ with respect to their spatial location, cellular mechanisms, morphology, and coupling with background electroencephalographic activity. Retrospective studies have demonstrated that differentiating between pathological and physiological ripples can improve surgical outcome prediction. In this review, we summarize the characteristics, differences, and applications of pathological and physiological HFOs and discuss strategies for their clinical translation.

Cell class-specific electric field entrainment of neural activity

Electric fields affect the activity of neurons and brain circuits, yet how this interaction happens at the cellular level remains enigmatic. Lack of understanding on how to stimulate the human brain to promote or suppress specific activity patterns significantly limits basic research and clinical applications. Here we study how electric fields impact the subthreshold and spiking properties of major cortical neuronal classes. We find that cortical neurons in rodent neocortex and hippocampus as well as human cortex exhibit strong and cell class-dependent entrainment that depends on the stimulation frequency. Excitatory pyramidal neurons with their typically slower spike rate entrain to slow and fast electric fields, while inhibitory classes like Pvalb and SST with their fast spiking predominantly phase lock to fast fields. We show this spike-field entrainment is the result of two effects: non-specific membrane polarization occurring across classes and class-specific excitability properties. Importantly, these properties of spike-field and class-specific entrainment are present in cells across cortical areas and species (mouse and human). These findings open the door to the design of selective and class-specific neuromodulation technologies.

Uncovering population contributions to the extracellular potential in the mouse visual system using Laminar Population Analysis

The local field potential (LFP), the low-frequency part of the extracellular potential, reflects transmembrane currents in the vicinity of the recording electrode. Thought mainly to stem from currents caused by synaptic input, it provides information about neural activity complementary to that of spikes, the output of neurons. However, the many neural sources contributing to the LFP, and likewise the derived current source density (CSD), can often make it challenging to interpret. Efforts to improve its interpretability have included the application of statistical decomposition tools like principal component analysis (PCA) and independent component analysis (ICA) to disentangle the contributions from different neural sources. However, their underlying assumptions of, respectively, orthogonality and statistical independence are not always valid for the various processes or pathways generating LFP. Here, we expand upon and validate a decomposition algorithm named Laminar Population Analysis (LPA), which is based on physiological rather than statistical assumptions. LPA utilizes the multiunit activity (MUA) and LFP jointly to uncover the contributions of different populations to the LFP. To perform the validation of LPA, we used data simulated with the large-scale, biophysically detailed model of mouse V1 developed by the Allen Institute. We find that LPA can identify laminar positions within V1 and the temporal profiles of laminar population firing rates from the MUA. We also find that LPA can estimate the salient current sinks and sources generated by feedforward input from the lateral geniculate nucleus (LGN), recurrent activity in V1, and feedback input from the lateromedial (LM) area of visual cortex. LPA identifies and distinguishes these contributions with a greater accuracy than the alternative statistical decomposition methods, PCA and ICA. Lastly, we also demonstrate the application of LPA on experimentally recorded MUA and LFP from 24 animals in the publicly available Visual Coding dataset. Our results suggest that LPA can be used both as a method to estimate positions of laminar populations and to uncover salient features in LFP/CSD contributions from different populations.

Suppression of absence seizures by using different stimulations in a reduced corticothalamic-basal ganglion-pedunculopontine nucleus model

Coupled neural network models are playing an increasingly important part in the modulation of absence seizures today. However, it is currently unclear how basal ganglia, corticothalamic network and pedunculopontine nucleus can coordinate with each other to develop a whole coupling circuit, theoretically. In addition, it is still difficult to select effective parameters of electrical stimulation on the regulation of absence seizures in clinical trials. Therefore, to develop a coupled model and reduce computation cost, a new model constructed by a simplified basal ganglion, two corticothalamic circuits and a pedunculopontine nucleus was proposed. Further, to seek better inhibition therapy, three electrical stimulations, high frequency stimulation (HFS), 1:0 coordinate reset stimulation (CRS) and 3:2 CRS, were applied to the thalamic reticular nucleus (RE) in the first corticothalamic circuit in the coupled model. The simulation results revealed that increasing the frequency and pulse width of an electrical stimulation within a certain range can also suppress seizures. Under the same parameters of electrical stimulation, the inhibitory effect of HFS on seizures was better than that of 1:0 CRS and 3:2 CRS. The research established a reduced corticothalamic-basal ganglion-pedunculopontine nucleus model, which lays a theoretical foundation for future optimal parameters selection of electrical stimulation. We hope that the findings will provide new insights into the role of theoretical models in absence seizures.

Uncovering circuit mechanisms of current sinks and sources with biophysical simulations of primary visual cortex

Local field potential (LFP) recordings reflect the dynamics of the current source density (CSD) in brain tissue. The synaptic, cellular, and circuit contributions to current sinks and sources are ill-understood. We investigated these in mouse primary visual cortex using public Neuropixels recordings and a detailed circuit model based on simulating the Hodgkin-Huxley dynamics of >50,000 neurons belonging to 17 cell types. The model simultaneously captured spiking and CSD responses and demonstrated a two-way dissociation: firing rates are altered with minor effects on the CSD pattern by adjusting synaptic weights, and CSD is altered with minor effects on firing rates by adjusting synaptic placement on the dendrites. We describe how thalamocortical inputs and recurrent connections sculpt specific sinks and sources early in the visual response, whereas cortical feedback crucially alters them in later stages. These results establish quantitative links between macroscopic brain measurements (LFP/CSD) and microscopic biophysics-based understanding of neuron dynamics and show that CSD analysis provides powerful constraints for modeling beyond those from considering spikes.

Visual cortical LFP in relation to the hippocampal theta rhythm in track running rats

Theta oscillations in the primary visual cortex (VC) have been observed during running tasks, but the mechanism behind their generation is not well understood. Some studies have suggested that theta in the VC is locally generated, while others have proposed that it is volume conducted from the hippocampus. The present study aimed to investigate the relationship between hippocampal and VC LFP dynamics. Analysis of power spectral density revealed that LFP in the VC was similar to that in the hippocampus, but with lower overall magnitude. As running velocity increased, both the power and frequency of theta and its harmonics increased in the VC, similarly to what is observed in the hippocampus. Current source density analysis triggered to theta did not identify distinct current sources and sinks in the VC, supporting the idea that theta in the VC is conducted from the adjacent hippocampus. Phase coupling between theta, its harmonics, and gamma is a notable feature in the hippocampus, particularly in the lacunosum moleculare. While some evidence of coupling between theta and its harmonics in the VC was found, bicoherence estimates did not reveal significant phase coupling between theta and gamma. Similar results were seen in the cross-region bicoherence analysis, where theta showed strong coupling with its harmonics with increasing velocity. Thus, theta oscillations observed in the VC during running tasks are likely due to volume conduction from the hippocampus.

Discriminating rapid eye movement sleep from wakefulness by analyzing high frequencies from single-channel EEG recordings in mice

Rapid eye movement sleep (REMS) is characterized by the appearance of fast, desynchronized rhythms in the cortical electroencephalogram (EEG), similar to wakefulness. The low electromyogram (EMG) amplitude during REMS distinguishes it from wakefulness; therefore, recording EMG signal seems to be imperative for discriminating between the two states. The present study evaluated the high frequency components of the EEG signal from mice (80-500 Hz) to support REMS detection during sleep scoring without an EMG signal and found a strong positive correlation between waking and the average power of 80-120 Hz, 120-200 Hz, 200-350 Hz and 350-500 Hz. A highly negative correlation was observed with REMS. Furthermore, our machine learning approach demonstrated that simple EEG time-series features are enough to discriminate REMS from wakefulness with sensitivity of roughly 98 percent and specificity of around 92 percent. Interestingly, assessing only the higher frequency bands (200-350 Hz as well as 350-500 Hz) gives significantly greater predictive power than assessing only the lower end of the EEG frequency spectrum. This paper proposes an approach that can detect subtle changes in REMS reliably, and future unsupervised sleep-scoring approaches could greatly benefit from it.

Brain State-Dependent Modulation of Thalamic Visual Processing by Cortico-Thalamic Feedback

The behavioral state of a mammal impacts how the brain responds to visual stimuli as early as in the dorsolateral geniculate nucleus of the thalamus (dLGN), the primary relay of visual information to the cortex. A clear example of this is the markedly stronger response of dLGN neurons to higher temporal frequencies of the visual stimulus in alert as compared with quiescent animals. The dLGN receives strong feedback from the visual cortex, yet whether this feedback contributes to these state-dependent responses to visual stimuli is poorly understood. Here, we show that in male and female mice, silencing cortico-thalamic feedback profoundly reduces state-dependent differences in the response of dLGN neurons to visual stimuli. This holds true for dLGN responses to both temporal and spatial features of the visual stimulus. These results reveal that the state-dependent shift of the response to visual stimuli in an early stage of visual processing depends on cortico-thalamic feedback.SIGNIFICANCE STATEMENT Brain state affects even the earliest stages of sensory processing. A clear example of this phenomenon is the change in thalamic responses to visual stimuli depending on whether the animal's brain is in an alert or quiescent state. Despite the radical impact that brain state has on sensory processing, the underlying circuits are still poorly understood. Here, we show that both the temporal and spatial response properties of thalamic neurons to visual stimuli depend on the state of the animal and, crucially, that this state-dependent shift relies on the feedback projection from visual cortex to thalamus.

Thalamic control of sensory processing and spindles in a biophysical somatosensory thalamoreticular circuit model of wakefulness and sleep

Thalamoreticular circuitry plays a key role in arousal, attention, cognition, and sleep spindles, and is linked to several brain disorders. A detailed computational model of mouse somatosensory thalamus and thalamic reticular nucleus has been developed to capture the properties of over 14,000 neurons connected by 6 million synapses. The model recreates the biological connectivity of these neurons, and simulations of the model reproduce multiple experimental findings in different brain states. The model shows that inhibitory rebound produces frequency-selective enhancement of thalamic responses during wakefulness. We find that thalamic interactions are responsible for the characteristic waxing and waning of spindle oscillations. In addition, we find that changes in thalamic excitability control spindle frequency and their incidence. The model is made openly available to provide a new tool for studying the function and dysfunction of the thalamoreticular circuitry in various brain states.

John EK, Potesta CV, Gallagher MJ, Macdonald RL, Zhou C. Sleep slow-wave oscillations trigger seizures in a genetic epilepsy model of Dravet syndrome

Sleep is the preferential period when epileptic spike-wave discharges appear in human epileptic patients, including genetic epileptic seizures such as Dravet syndrome with multiple mutations including SCN1A mutation and GABAA receptor γ2 subunit Gabrg2Q390X mutation in patients, which presents more severe epileptic symptoms in female patients than male patients. However, the seizure onset mechanism during sleep still remains unknown. Our previous work has shown that the sleep-like state-dependent homeostatic synaptic potentiation can trigger epileptic spike-wave discharges in one transgenic heterozygous Gabrg2+/Q390X knock-in mouse model.1 Here, using this heterozygous knock-in mouse model, we hypothesized that slow-wave oscillations themselves in vivo could trigger epileptic seizures. We found that epileptic spike-wave discharges in heterozygous Gabrg2+/Q390X knock-in mice exhibited preferential incidence during non-rapid eye movement sleep period, accompanied by motor immobility/facial myoclonus/vibrissal twitching and more frequent spike-wave discharge incidence appeared in female heterozygous knock-in mice than male heterozygous knock-in mice. Optogenetically induced slow-wave oscillations in vivo significantly increased epileptic spike-wave discharge incidence in heterozygous Gabrg2+/Q390X knock-in mice with longer duration of non-rapid eye movement sleep or quiet-wakeful states. Furthermore, suppression of slow-wave oscillation-related homeostatic synaptic potentiation by 4-(diethylamino)-benzaldehyde injection (i.p.) greatly attenuated spike-wave discharge incidence in heterozygous knock-in mice, suggesting that slow-wave oscillations in vivo did trigger seizure activity in heterozygous knock-in mice. Meanwhile, sleep spindle generation in wild-type littermates and heterozygous Gabrg2+/Q390X knock-in mice involved the slow-wave oscillation-related homeostatic synaptic potentiation that also contributed to epileptic spike-wave discharge generation in heterozygous Gabrg2+/Q390X knock-in mice. In addition, EEG spectral power of delta frequency (0.1-4 Hz) during non-rapid eye movement sleep was significantly larger in female heterozygous Gabrg2+/Q390X knock-in mice than that in male heterozygous Gabrg2+/Q390X knock-in mice, which likely contributes to the gender difference in seizure incidence during non-rapid eye movement sleep/quiet-wake states of human patients. Overall, all these results indicate that slow-wave oscillations in vivo trigger the seizure onset in heterozygous Gabrg2+/Q390X knock-in mice, preferentially during non-rapid eye movement sleep period and likely generate the sex difference in seizure incidence between male and female heterozygous Gabrg2+/Q390X knock-in mice.

Transcranial magnetic stimulation of the brain: What is stimulated? - A consensus and critical position paper

Transcranial (electro)magnetic stimulation (TMS) is currently the method of choice to non-invasively induce neural activity in the human brain. A single transcranial stimulus induces a time-varying electric field in the brain that may evoke action potentials in cortical neurons. The spatial relationship between the locally induced electric field and the stimulated neurons determines axonal depolarization. The induced electric field is influenced by the conductive properties of the tissue compartments and is strongest in the superficial parts of the targeted cortical gyri and underlying white matter. TMS likely targets axons of both excitatory and inhibitory neurons. The propensity of individual axons to fire an action potential in response to TMS depends on their geometry, myelination and spatial relation to the imposed electric field and the physiological state of the neuron. The latter is determined by its transsynaptic dendritic and somatic inputs, intrinsic membrane potential and firing rate. Modeling work suggests that the primary target of TMS is axonal terminals in the crown top and lip regions of cortical gyri. The induced electric field may additionally excite bends of myelinated axons in the juxtacortical white matter below the gyral crown. Neuronal excitation spreads ortho- and antidromically along the stimulated axons and causes secondary excitation of connected neuronal populations within local intracortical microcircuits in the target area. Axonal and transsynaptic spread of excitation also occurs along cortico-cortical and cortico-subcortical connections, impacting on neuronal activity in the targeted network. Both local and remote neural excitation depend critically on the functional state of the stimulated target area and network. TMS also causes substantial direct co-stimulation of the peripheral nervous system. Peripheral co-excitation propagates centrally in auditory and somatosensory networks, but also produces brain responses in other networks subserving multisensory integration, orienting or arousal. The complexity of the response to TMS warrants cautious interpretation of its physiological and behavioural consequences, and a deeper understanding of the mechanistic underpinnings of TMS will be critical for advancing it as a scientific and therapeutic tool.

Waveform detection by deep learning reveals multi-area spindles that are selectively modulated by memory load

Sleep is generally considered to be a state of large-scale synchrony across thalamus and neocortex; however, recent work has challenged this idea by reporting isolated sleep rhythms such as slow oscillations and spindles. What is the spatial scale of sleep rhythms? To answer this question, we adapted deep learning algorithms initially developed for detecting earthquakes and gravitational waves in high-noise settings for analysis of neural recordings in sleep. We then studied sleep spindles in non-human primate electrocorticography (ECoG), human electroencephalogram (EEG), and clinical intracranial electroencephalogram (iEEG) recordings in the human. Within each recording type, we find widespread spindles occur much more frequently than previously reported. We then analyzed the spatiotemporal patterns of these large-scale, multi-area spindles and, in the EEG recordings, how spindle patterns change following a visual memory task. Our results reveal a potential role for widespread, multi-area spindles in consolidation of memories in networks widely distributed across primate cortex.

The brain processes memories as we sleep, generating rhythms of electrical activity called ‘sleep spindles’. Sleep spindles were long thought to be a state where the entire brain was fully synchronized by this rhythm. This was based on EEG recordings, short for electroencephalogram, a technique that uses electrodes on the scalp to measure electrical activity in the outermost layer of the brain, the cortex. But more recent intracranial recordings of people undergoing brain surgery have challenged this idea and suggested that sleep spindles may not be a state of global brain synchronization, but rather localised to specific areas.

Mofrad et al. sought to clarify the extent to which spindles co-occur at multiple sites in the brain, which could shed light on how networks of neurons coordinate memory storage during sleep. To analyse highly variable brain wave recordings, Mofrad et al. adapted deep learning algorithms initially developed for detecting earthquakes and gravitational waves. The resulting algorithm, designed to more sensitively detect spindles amongst other brain activity, was then applied to a range of sleep recordings from humans and macaque monkeys.

The analyses revealed that widespread and complex patterns of spindle rhythms, spanning multiple areas in the cortex of the brain, actually appear much more frequently than previously thought. This finding was consistent across all the recordings analysed, even recordings under the skull, which provide the clearest window into brain circuits. Further analyses found that these multi-area spindles occurred more often in sleep after people had completed tasks that required holding many visual scenes in memory, as opposed to control conditions with fewer visual scenes.

In summary, Mofrad et al. show that neuroscientists had previously not appreciated the complex and dynamic patterns in this sleep rhythm. These patterns in sleep spindles may be able to adapt based on the demands needed for memory storage, and this will be the subject of future work. Moreover, the findings support the idea that sleep spindles help coordinate the consolidation of memories in brain circuits that stretch across the cortex. Understanding this mechanism may provide insights into how memory falters in aging and sleep-related diseases, such as Alzheimer’s disease. Lastly, the algorithm developed by Mofrad et al. stands to be a useful tool for analysing other rhythmic waveforms in noisy recordings.

Are High Frequency Oscillations in Scalp EEG Related to Age?

BACKGROUND

High-frequency oscillations (HFOs) have received much attention in recent years, particularly in the clinical context. In addition to their application as a marker for pathological changes in patients with epilepsy, HFOs have also been brought into context with several physiological mechanisms. Furthermore, recent studies reported a relation between an increase of HFO rate and age in invasive EEG recordings. The present study aimed to investigate whether this relation can be replicated in scalp-EEG.

METHODS

We recorded high-density EEG from 11 epilepsy patients at rest as well as during motor performance. Manual detection of HFOs was performed by two independent raters following a standardized protocol. Patients were grouped by age into younger (<25 years) and older (>50 years) participants.

RESULTS

No significant difference of HFO-rates was found between groups [U = 10.5, p = 0.429, r = 0.3].

CONCLUSIONS

Lack of replicability of the age effect of HFOs may be due to the local propagation patterns of age-related HFOs occurring in deep structures. However, limitations such as small sample size, decreased signal-to-noise ratio as compared to invasive recordings, as well as HFO-mimicking artifacts must be considered.

OUP accepted manuscript

Metabolism regulates neuronal activity and modulates the occurrence of epileptic seizures. Here, using two rodent models of absence epilepsy, we show that hypoglycaemia increases the occurrence of spike-wave seizures. We then show that selectively disrupting glycolysis in the thalamus, a structure implicated in absence epilepsy, is sufficient to increase spike-wave seizures. We propose that activation of thalamic AMP-activated protein kinase, a sensor of cellular energetic stress and potentiator of metabotropic GABA_B-receptor function, is a significant driver of hypoglycaemia-induced spike-wave seizures. We show that AMP-activated protein kinase augments postsynaptic GABA_B-receptor-mediated currents in thalamocortical neurons and strengthens epileptiform network activity evoked in thalamic brain slices. Selective thalamic AMP-activated protein kinase activation also increases spike-wave seizures. Finally, systemic administration of metformin, an AMP-activated protein kinase agonist and common diabetes treatment, profoundly increased spike-wave seizures. These results advance the decades-old observation that glucose metabolism regulates thalamocortical circuit excitability by demonstrating that AMP-activated protein kinase and GABA_B-receptor cooperativity is sufficient to provoke spike-wave seizures.

Nonrapid eye movement sleep characteristics and relations with motor, memory, and cognitive ability from infancy to preadolescence

Sleep plays a critical role in neural neurodevelopment. Hallmarks of sleep reflected in the electroencephalogram during nonrapid eye movement (NREM) sleep are associated with learning processes, cognitive ability, memory, and motor functioning. Research in adults is well-established; however, the role of NREM sleep in childhood is less clear. Growing evidence suggests the importance of two NREM sleep features: slow-wave activity and sleep spindles. These features may be critical for understanding maturational change and the functional role of sleep during development. Here, we review the literature on NREM sleep from infancy to preadolescence to provide insight into the network dynamics of the developing brain. The reviewed findings show distinct relations between topographical and maturational aspects of slow waves and sleep spindles; however, the direction and consistency of these relationships vary, and associations with cognitive ability remain unclear. Future research investigating the role of NREM sleep and development would benefit from longitudinal approaches, increased control for circadian and homeostatic influences, and in early childhood, studies recording daytime naps and overnight sleep to yield increased precision for detecting age-related change. Such evidence could help explicate the role of NREM sleep and provide putative physiological markers of neurodevelopment.

Decoding neurobiological spike trains using recurrent neural networks: a case study with electrophysiological auditory cortex recordings

Recent advancements in multielectrode methods and spike-sorting algorithms enable the in vivo recording of the activities of many neurons at a high temporal resolution. These datasets offer new opportunities in the investigation of the biological neural code, including the direct testing of specific coding hypotheses, but they also reveal the limitations of present decoder algorithms. Classical methods rely on a manual feature extraction step, resulting in a feature vector, like the firing rates of an ensemble of neurons. In this paper, we present a recurrent neural-network-based decoder and evaluate its performance on experimental and artificial datasets. The experimental datasets were obtained by recording the auditory cortical responses of rats exposed to sound stimuli, while the artificial datasets represent preset encoding schemes. The task of the decoder was to classify the action potential timeseries according to the corresponding sound stimuli. It is illustrated that, depending on the coding scheme, the performance of the recurrent-network-based decoder can exceed the performance of the classical methods. We also show how randomized copies of the training datasets can be used to reveal the role of candidate spike-train features. We conclude that artificial neural network decoders can be a useful alternative to classical population vector-based techniques in studies of the biological neural code.

LSD degrades hippocampal spatial representations and suppresses hippocampal-visual cortical interactions

Lysergic acid diethylamide (LSD) produces hallucinations, which are perceptions uncoupled from the external environment. How LSD alters neuronal activities in vivo that underlie abnormal perceptions is unknown. Here, we show that when rats run along a familiar track, hippocampal place cells under LSD reduce their firing rates, their directionality, and their interaction with visual cortical neurons. However, both hippocampal and visual cortical neurons temporarily increase firing rates during head-twitching, a behavioral signature of a hallucination-like state in rodents. When rats are immobile on the track, LSD enhances cortical firing synchrony in a state similar to the wakefulness-to-sleep transition, during which the hippocampal-cortical interaction remains dampened while hippocampal awake reactivation is maintained. Our results suggest that LSD suppresses hippocampal-cortical interactions during active behavior and during immobility, leading to internal hippocampal representations that are degraded and isolated from external sensory input. These effects may contribute to LSD-produced abnormal perceptions.

Spike and wave discharges and fast ripples during posttraumatic epileptogenesis

OBJECTIVE

The goal of the present study was to determine whether spike and wave discharges (SWDs) and SWDs with superimposed fast ripples (SWDFRs) could be biomarkers of posttraumatic epileptogenesis.

METHODS

Fluid percussion injury was conducted on 13-14-week old male Sprague Dawley rats. Immediately after traumatic brain injury (TBI), they were implanted with microelectrodes in the neocortex, hippocampus, and striatum bilaterally. Age-matched sham rats with the same electrode implantation montage acted as controls. Wideband brain electrical activity was recorded intermittently from Day 1 of TBI, and continued from 2 to 21 weeks after TBI. SWD and SWDFR analysis was performed during the first 2 weeks to investigate whether the occurrence of this pattern predicted development of epilepsy. The remaining 3-21 weeks were used for identifying which rats became epileptic (E+ group) and which did not (E- group).

RESULTS

The E+ group (n = 9) showed a significant increase in SWD rate in prefrontal cortex during Weeks 1 and 2 after TBI. The E- group showed a significant increase in SWD rate only in the second week. One hundred percent of rats in the E+ group displayed SWDFRs beginning from the first week after TBI. The SWDFR pattern was observed in all recorded brain areas: prefrontal and perilesional cortices, hippocampus, and striatum. None of rats in the E- group showed coexistence of fast ripples with SWDs.

SIGNIFICANCE

Occurrence of SWDFRs after TBI, but not an increase in the rate of SWDs, could be a noninvasive electroencephalographic biomarker of posttraumatic epileptogenesis.

Recommendations for Preclinical Testing of Treatments Against Alzheimer's Disease-Related Epileptiform Spikes in Transgenic Rodent Models

Recent evidence suggests that about 30%of patients with mild to moderate Alzheimer's disease (AD) without a known diagnosis of epilepsy may display epileptiform spikes during electroencephalographic (EEG) recordings. These abnormal discharges occur predominantly during sleep and may be associated with accelerated disease progression. Subclinical spikes may represent a relevant target for clinical drug interventions, and there is a clear unmet need for preclinical testing of novel disease modifying agents in suitable animal models. Transgenic rodent models of AD pathology exhibit various forms of epileptiform EEG activity related to the abnormal levels of amyloid species in the brain. Among them, large-amplitude cortical and hippocampal EEG spikes in mouse and rat AD models may be reminiscent of the subclinical epileptiform EEG spikes recorded in some AD patients. This article reports the recommendations of a multidisciplinary panel of experts on optimal EEG markers and experimental designs to measure and report epileptiform activities and their response to symptomatic and disease-modifying drugs in transgenic AD model rodents. These recommendations may harmonize future preclinical EEG studies in the drug discovery research and may increase the comparability of experimental outcomes and their translational clinical value.

Shared and unique features of mammalian sleep spindles - insights from new and old animal models

Sleep spindles are phasic events observed in mammalian non-rapid eye movement sleep. They are relevant today in the study of memory consolidation, sleep quality, mental health and ageing. We argue that our advanced understanding of their mechanisms has not exhausted the utility and need for animal model work. This is both because some topics, like cognitive ageing, have not yet been addressed sufficiently in comparative efforts and because the evolutionary history of this oscillation is still poorly understood. Comparisons across species often are either limited to referencing the classical cat and rodent models, or are over-inclusive, uncritically including reports of sleep spindles in rarely studied animals. In this review, we discuss the emergence of new (dog and sheep) models for sleep spindles and compare the strengths and shortcomings of new and old models based on the three validation criteria for animal models - face, predictive, and construct validity. We conclude that an emphasis on cognitive ageing might dictate the future of comparative sleep spindle studies, a development that is already becoming visible in studies on dogs. Moreover, reconstructing the evolutionary history of sleep spindles will require more stringent criteria for their identification, across more species. In particular, a stronger emphasis on construct and predictive validity can help verify if spindle-like events in other species are actual sleep spindles. Work in accordance with such stricter validation suggests that sleep spindles display more universally shared features, like defining frequency, than previously thought.

Shaping the slow waves of sleep: A systematic and integrative review of sleep slow wave modulation in humans using non-invasive brain stimulation

The experimental study of electroencephalographic slow wave sleep (SWS) stretches over more than half a century and has corroborated its importance for basic physiological processes, such as brain plasticity, metabolism and immune system functioning. Alterations of SWS in aging or pathological conditions suggest that modulating SWS might constitute a window for clinically relevant interventions. This work provides a systematic and integrative review of SWS modulation through non-invasive brain stimulation in humans. A literature search using PubMed, conducted in May 2020, identified 3220 studies, of which 82 fulfilled inclusion criteria. Three approaches have been adopted to modulate the macro- and microstructure of SWS, namely auditory, transcranial electrical and transcranial magnetic stimulation. Our current knowledge about the modulatory mechanisms, the space of stimulation parameters and the physiological and behavioral effects are reported and evaluated. The integration of findings suggests that sleep slow wave modulation bears the potential to promote our understanding of the functions of SWS and to develop new treatments for conditions of disrupted SWS.

Alterations of Neuronal Dynamics as a Mechanism for Cognitive Impairment in Epilepsy

Epilepsy is commonly associated with cognitive and behavioral deficits that dramatically affect the quality of life of patients. In order to identify novel therapeutic strategies aimed at reducing these deficits, it is critical first to understand the mechanisms leading to cognitive impairments in epilepsy. Traditionally, seizures and epileptiform activity in addition to neuronal injury have been considered to be the most significant contributors to cognitive dysfunction. In this review we however highlight the role of a new mechanism: alterations of neuronal dynamics, i.e. the timing at which neurons and networks receive and process neural information. These alterations, caused by the underlying etiologies of epilepsy syndromes, are observed in both animal models and patients in the form of abnormal oscillation patterns in unit firing, local field potentials, and electroencephalogram (EEG). Evidence suggests that such mechanisms significantly contribute to cognitive impairment in epilepsy, independently of seizures and interictal epileptiform activity. Therefore, therapeutic strategies directly targeting neuronal dynamics rather than seizure reduction may significantly benefit the quality of life of patients.

Graphene active sensor arrays for long-term and wireless mapping of wide frequency band epicortical brain activity

Graphene active sensors have demonstrated promising capabilities for the detection of electrophysiological signals in the brain. Their functional properties, together with their flexibility as well as their expected stability and biocompatibility have raised them as a promising building block for large-scale sensing neural interfaces. However, in order to provide reliable tools for neuroscience and biomedical engineering applications, the maturity of this technology must be thoroughly studied. Here, we evaluate the performance of 64-channel graphene sensor arrays in terms of homogeneity, sensitivity and stability using a wireless, quasi-commercial headstage and demonstrate the biocompatibility of epicortical graphene chronic implants. Furthermore, to illustrate the potential of the technology to detect cortical signals from infra-slow to high-gamma frequency bands, we perform proof-of-concept long-term wireless recording in a freely behaving rodent. Our work demonstrates the maturity of the graphene-based technology, which represents a promising candidate for chronic, wide frequency band neural sensing interfaces.

Insights on the role of external globus pallidus in controlling absence seizures

Absence epilepsy, characterized by transient loss of awareness and bilaterally synchronous 2-4 Hz spike and wave discharges (SWDs) on electroencephalography (EEG) during absence seizures, is generally believed to arise from abnormal interactions between the cerebral cortex (Ctx) and thalamus. Recent animal electrophysiological studies suggested that changing the neural activation level of the external globus pallidus (GPe) neurons can remarkably modify firing rates of the thalamic reticular nucleus (TRN) neurons through the GABAergic GPe-TRN pathway. However, the existing experimental evidence does not provide a clear answer as to whether the GPe-TRN pathway contributes to regulating absence seizures. Here, using a biophysically based mean-field model of the GPe-corticothalamic (GCT) network, we found that both directly decreasing the strength of the GPe-TRN pathway and inactivating GPe neurons can effectively suppress absence seizures. Also, the pallido-cortical pathway and the recurrent connection of GPe neurons facilitate the regulation of absence seizures through the GPe-TRN pathway. Specifically, in the controllable situation, enhancing the coupling strength of either of the two pathways can successfully terminate absence seizures. Moreover, the competition between the GPe-TRN and pallido-cortical pathways may lead to the GPe bidirectionally controlling absence seizures, and this bidirectional control manner can be significantly modulated by the Ctx-TRN pathway. Importantly, when the strength of the Ctx-TRN pathway is relatively strong, the bidirectional control of absence seizures by changing GPe neural activities can be observed at both weak and strong strengths of the pallido-cortical pathway.These findings suggest that the GPe-TRN pathway may have crucial functional roles in regulating absence seizures, which may provide a testable hypothesis for further experimental studies and new perspectives on the treatment of absence epilepsy.

Reconsidering Network Mechanisms in Absence Seizures: Unhitching the Wave Cart From the Spike Horse

[Box: see text]

Reliable induction of sleep spindles with intracranial electrical pulse stimulation

Neocortical sleep spindles have been shown to occur more frequently following a memory task, suggesting that a method to increase spindle activity could improve memory processing. Stimulation of the neocortex can elicit a slow oscillation (SO) and a spindle, but the feasibility of this method to boost SO and spindles over time has not been tested. In rats with implanted neocortical electrodes, stimulation during slow wave sleep significantly increased SO and spindle rates compared to control rest periods before and after the stimulation session. Coordination between hippocampal sharp-wave ripples and spindles also increased. These effects were reproducible across five consecutive days of testing, demonstrating the viability of this method to increase SO and spindles.

The laminar profile of sleep spindles in humans

Sleep spindles are functionally important NREM sleep EEG oscillations which are generated in thalamocortical, corticothalamic and possibly cortico-cortical circuits. Previous hypotheses suggested that slow and fast spindles or spindles with various spatial extent may be generated in different circuits with various cortical laminar innervation patterns. We used NREM sleep EEG data recorded from four human epileptic patients undergoing presurgical electrophysiological monitoring with subdural electrocorticographic grids (ECoG) and implanted laminar microelectrodes penetrating the cortex (IME). The position of IMEs within cortical layers was confirmed using postsurgical histological reconstructions. Many spindles detected on the IME occurred only in one layer and were absent from the ECoG, but with increasing amplitude simultaneous detection in other layers and on the ECoG became more likely. ECoG spindles were in contrast usually accompanied by IME spindles. Neither IME nor ECoG spindle cortical profiles were strongly associated with sleep spindle frequency or globality. Multiple-unit and single-unit activity during spindles, however, was heterogeneous across spindle types, but also across layers and patients. Our results indicate that extremely local spindles may occur in any cortical layer, but co-occurrence at other locations becomes likelier with increasing amplitude and the relatively large spindles detected on ECoG channels have a stereotypical laminar profile. We found no compelling evidence that different spindle types are associated with different laminar profiles, suggesting that they are generated in cortical and thalamic circuits with similar cortical innervation patterns. Local neuronal activity is a stronger candidate mechanism for driving functional differences between spindles subtypes.

A role for spindles in the onset of rapid eye movement sleep

Sleep spindle generation classically relies on an interplay between the thalamic reticular nucleus (TRN), thalamo-cortical (TC) relay cells and cortico-thalamic (CT) feedback during non-rapid eye movement (NREM) sleep. Spindles are hypothesized to stabilize sleep, gate sensory processing and consolidate memory. However, the contribution of non-sensory thalamic nuclei in spindle generation and the role of spindles in sleep-state regulation remain unclear. Using multisite thalamic and cortical LFP/unit recordings in freely behaving mice, we show that spike-field coupling within centromedial and anterodorsal (AD) thalamic nuclei is as strong as for TRN during detected spindles. We found that spindle rate significantly increases before the onset of rapid eye movement (REM) sleep, but not wakefulness. The latter observation is consistent with our finding that enhancing spontaneous activity of TRN cells or TRN-AD projections using optogenetics increase spindle rate and transitions to REM sleep. Together, our results extend the classical TRN-TC-CT spindle pathway to include non-sensory thalamic nuclei and implicate spindles in the onset of REM sleep.

During NREM sleep, spindles emerge from thalamocortical interactions. Here the authors carry out multisite thalamic and cortical recordings in freely behaving mice, to investigate the role of other non-classical thalamic sites in sleep spindle generation.

Assessment of Sleep, K-Complexes, and Sleep Spindles in a T21 Light-Dark Cycle

Circadian rhythm misalignment has a deleterious impact on the brain and the body. In rats, exposure to a 21-hour day length impairs hippocampal dependent memory. Sleep, and particularly K-complexes and sleep spindles in the cortex, have been hypothesized to be involved in memory consolidation. Altered K-complexes, sleep spindles, or interaction between the cortex and hippocampus could be a mechanism for the memory consolidation failure but has yet to be assessed in any circadian misalignment paradigm. In the current study, continuous local field potential recordings from five rats were used to assess the changes in aspects of behavior and sleep, including wheel running activity, quiet wakefulness, motionless sleep, slow wave sleep, REM sleep, K-complexes and sleep spindles, in rats exposed to six consecutive days of a T21 light-dark cycle (L9:D12). Except for a temporal redistribution of sleep and activity during the T21, there were no changes in period, or total amount for any aspect of sleep or activity. These data suggest that the memory impairment elicited from 6 days of T21 exposure is likely not due to changes in sleep architecture. It remains possible that hippocampal plasticity is affected by experiencing light when subjective circadian phase is calling for dark. However, if there is a reduction in hippocampal plasticity, changes in sleep appear not to be driving this effect.

Impaired State-Dependent Potentiation of GABAergic Synaptic Currents Triggers Seizures in a Genetic Generalized Epilepsy Model

Epileptic activity in genetic generalized epilepsy (GGE) patients preferentially appears during sleep and its mechanism remains unknown. Here, we found that sleep-like slow-wave oscillations (0.5 Hz SWOs) potentiated excitatory and inhibitory synaptic currents in layer V cortical pyramidal neurons from wild-type (wt) mouse brain slices. In contrast, SWOs potentiated excitatory, but not inhibitory, currents in cortical neurons from a heterozygous (het) knock-in (KI) Gabrg2+Q/390X model of Dravet epilepsy syndrome. This created an imbalance between evoked excitatory and inhibitory currents to effectively prompt neuronal action potential firings. Similarly, physiologically similar up-/down-state induction (present during slow-wave sleep) in cortical neurons also potentiated excitatory synaptic currents within brain slices from wt and het KI mice. Moreover, this state-dependent potentiation of excitatory synaptic currents entailed some signaling pathways of homeostatic synaptic plasticity. Consequently, in het KI mice, in vivo SWO induction (using optogenetic methods) triggered generalized epileptic spike-wave discharges (SWDs), being accompanied by sudden immobility, facial myoclonus, and vibrissa twitching. In contrast, in wt littermates, SWO induction did not cause epileptic SWDs and motor behaviors. To our knowledge, this is the first mechanism to explain why epileptic SWDs preferentially happen during non rapid eye-movement sleep and quiet-wakefulness in human GGE patients.

Inter-channel phase differences during sleep spindles are altered in Veterans with PTSD

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We assessed the spatiotemporal dynamics of slow and fast spindles in PTSD.

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Inter-channel phase differences during slow spindles were reduced in PTSD.

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This effect was reproducible across nights and subsamples of the study population.

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The spatiotemporal dynamics of fast spindles was not altered in PTSD.

Sleep disturbances are common complaints in patients with post-traumatic stress disorder (PTSD). To date, however, objective markers of PTSD during sleep remain elusive. Sleep spindles are distinctive bursts of brain oscillatory activity during non-rapid eye movement (NREM) sleep and have been implicated in sleep protection and sleep-dependent memory processes. In healthy sleep, spindles observed in electroencephalogram (EEG) data are highly synchronized across different regions of the scalp. Here, we aimed to investigate whether the spatiotemporal synchronization patterns between EEG channels during sleep spindles, as quantified by the phase-locking value (PLV) and the mean phase difference (MPD), are altered in PTSD. Using high-density (64-channel) EEG data recorded from 78 combat-exposed Veteran men (31 with PTSD and 47 without PTSD) during two consecutive nights of sleep, we examined group differences in the PLV and MPD for slow (10–13 Hz) and fast (13–16 Hz) spindles separately. To evaluate the reproducibility of our findings, we set apart the first 47 consecutive participants (18 with PTSD) for the initial discovery and reserved the remaining 31 participants (13 with PTSD) for replication analysis. In the discovery analysis, compared to the non-PTSD group, the PTSD group showed smaller MPDs during slow spindles between the frontal and centro-parietal channel pairs on both nights. We obtained reproducible results in the replication analysis in terms of statistical significance and effect size. The PLVs during slow or fast spindles did not significantly differ between groups. The reduced inter-channel phase difference during slow spindles in PTSD may reflect pathological changes in the underlying thalamocortical circuits. This novel finding, if independently validated, may prove useful in developing sleep-focused PTSD diagnostics and interventions.

Interactions Between Motor Thalamic Field Potentials and Single-Unit Spiking Are Correlated With Behavior in Rats

Field potential (FP) oscillations are believed to coordinate brain activity over large spatiotemporal scales, with specific features (e.g., phase and power) in discrete frequency bands correlated with motor output. Furthermore, complex correlations between oscillations in distinct frequency bands (phase-amplitude, amplitude-amplitude, and phase-phase coupling) are commonly observed. However, the mechanisms underlying FP-behavior correlations and cross-frequency coupling remain unknown. The thalamus plays a central role in generating many circuit-level neural oscillations, and single-unit activity in motor thalamus (Mthal) is correlated with behavioral output. We, therefore, hypothesized that motor thalamic spiking coordinates motor system FPs and underlies FP-behavior correlations. To investigate this possibility, we recorded wideband motor thalamic (Mthal) electrophysiology as healthy rats performed a two-alternative forced-choice task. Delta (1–4 Hz), beta (13–30 Hz), low gamma (30–70 Hz), and high gamma (70–200 Hz) power were strongly modulated by task performance. As in the cortex, the delta phase was correlated with beta/low gamma power and reaction time. Most interestingly, subpopulations of Mthal neurons defined by their relationship to the behavior exhibited distinct relationships with FP features. Specifically, neurons whose activity was correlated with action selection and movement speed were entrained to delta oscillations. Furthermore, changes in their activity anticipated power fluctuations in beta/low gamma bands. These complex relationships suggest mechanisms for commonly observed FP-FP and spike-FP correlations, as well as subcortical influences on motor output.

Response of spike-wave discharges in aged APP/PS1 Alzheimer model mice to antiepileptic, metabolic and cholinergic drugs

Epileptic nonconvulsive spike-wave discharges (SWDs) are commonly seen in amyloid plaque bearing transgenic mice but only rarely in their wild-type littermates. To shed light on their possible treatment options, we assessed the effect of drugs with variable and known mechanisms of action on the occurrence of SWDs in aged APPswe/PS1dE9 mice. The treatments included prototypic antiepileptic drugs (ethosuximide and levetiracetam), donepezil as the typical Alzheimer drug and atropine as an antagonistic effect, GABA_B antagonist CGP-35348, and alternate energy substrates beta-hydroxybutyrate (BHB), pyruvate and lactate on the occurrence of SWDs in aged APPswe/PS1dE9 mice. All agents were administered by single intraperitoneal injections at doses earlier documented to be effective and response was assessed by recording 3 h of video-EEG. Atropine at 25 mg/kg significantly decreased SWD occurrence in all behavioral states, and also resulted in altered frequency composition of SWDs and general EEG slowing during sleep. Ethosuximide at 200 mg/kg and levetiracetam at 75 mg/kg effectively suppressed SWDs only during a period of mixed behavioral states, but levetiracetam also increased SWDs in sleep. BHB at 1 g/kg decreased SWDs in sleep, while both pyruvate and lactate at the same dose tended to increase SWD number and total duration. Unexpectantly, donepezil at 0.3 mg/kg CGP-35348 at 100 mg/kg had no effect on SWDs. These findings call for re-evaluation of some prevailing theories on neural circuit alternations that underlie SWD generation and show the utility of APP/PS1 mice for testing potential new treatments for nonconvulsive epileptic activity related to Alzheimer pathology.

The (Un)Conscious Mouse as a Model for Human Brain Functions: Key Principles of Anesthesia and Their Impact on Translational Neuroimaging

In recent years, technical and procedural advances have brought functional magnetic resonance imaging (fMRI) to the field of murine neuroscience. Due to its unique capacity to measure functional activity non-invasively, across the entire brain, fMRI allows for the direct comparison of large-scale murine and human brain functions. This opens an avenue for bidirectional translational strategies to address fundamental questions ranging from neurological disorders to the nature of consciousness. The key challenges of murine fMRI are: (1) to generate and maintain functional brain states that approximate those of calm and relaxed human volunteers, while (2) preserving neurovascular coupling and physiological baseline conditions. Low-dose anesthetic protocols are commonly applied in murine functional brain studies to prevent stress and facilitate a calm and relaxed condition among animals. Yet, current mono-anesthesia has been shown to impair neural transmission and hemodynamic integrity. By linking the current state of murine electrophysiology, Ca2+ imaging and fMRI of anesthetic effects to findings from human studies, this systematic review proposes general principles to design, apply and monitor anesthetic protocols in a more sophisticated way. The further development of balanced multimodal anesthesia, combining two or more drugs with complementary modes of action helps to shape and maintain specific brain states and relevant aspects of murine physiology. Functional connectivity and its dynamic repertoire as assessed by fMRI can be used to make inferences about cortical states and provide additional information about whole-brain functional dynamics. Based on this, a simple and comprehensive functional neurosignature pattern can be determined for use in defining brain states and anesthetic depth in rest and in response to stimuli. Such a signature can be evaluated and shared between labs to indicate the brain state of a mouse during experiments, an important step toward translating findings across species.

A Systematic Review of Closed-Loop Feedback Techniques in Sleep Studies-Related Issues and Future Directions

Advances in computer processing technology have enabled researchers to analyze real-time brain activity and build real-time closed-loop paradigms. In many fields, the effectiveness of these closed-loop protocols has proven to be better than that of the simple open-loop paradigms. Recently, sleep studies have attracted much attention as one possible application of closed-loop paradigms. To date, several studies that used closed-loop paradigms have been reported in the sleep-related literature and recommend a closed-loop feedback system to enhance specific brain activity during sleep, which leads to improvements in sleep's effects, such as memory consolidation. However, to the best of our knowledge, no report has reviewed and discussed the detailed technical issues that arise in designing sleep closed-loop paradigms. In this paper, we reviewed the most recent reports on sleep closed-loop paradigms and offered an in-depth discussion of some of their technical issues. We found 148 journal articles strongly related with 'sleep and stimulation' and reviewed 20 articles on closed-loop feedback sleep studies. We focused on human sleep studies conducting any modality of feedback stimulation. Then we introduced the main component of the closed-loop system and summarized several open-source libraries, which are widely used in closed-loop systems, with step-by-step guidelines for closed-loop system implementation for sleep. Further, we proposed future directions for sleep research with closed-loop feedback systems, which provide some insight into closed-loop feedback systems.

Spatial resolution of local field potential signals in macaque V4

OBJECTIVE

An important challenge for the development of cortical visual prostheses is to generate spatially localized percepts of light, using artificial stimulation. Such percepts are called phosphenes, and the goal of prosthetic applications is to generate a pattern of phosphenes that matches the structure of the retinal image. A preliminary step in this process is to understand how the spatial positions of phosphene-like visual stimuli are encoded in the distributed activity of cortical neurons. The spatial resolution with which the distributed responses discriminate positions puts a limit on the capability of visual prosthesis devices to induce phosphenes at multiple positions. While most previous prosthetic devices have targeted the primary visual cortex, the extrastriate cortex has the advantage of covering a large part of the visual field with a smaller amount of cortical tissue, providing the possibility of a more compact implant. Here, we studied how well ensembles of Local Field Potentials (LFPs) and Multiunit activity (MUA) responses from extrastriate cortical visual area V4 of a behaving macaque monkey can discriminate between two-dimensional spatial positions.

APPROACH

We used support vector machines (SVM) to determine the capabilities of LFPs and MUA to discriminate responses to phosphene-like stimuli (probes) at different spatial separations. We proposed a selection strategy based on the combined responses of multiple electrodes and used the linear learning weights to find the minimum number of electrodes for fine and coarse discriminations. We also measured the contribution of correlated trial-to-trial variability in the responses to the discrimination performance for MUA and LFP.

MAIN RESULTS

We found that despite the large receptive field sizes in V4, the combined responses from multiple sites, whether MUA or LFP, are capable of fine and coarse discrimination of positions. Our electrode selection procedure significantly increased discrimination performance while reducing the required number of electrodes. Analysis of noise correlations in MUA and LFP responses showed that noise correlations in LFPs carry more information about spatial positions.

SIGNIFICANCE

This study determined the coding strategy for fine discrimination, suggesting that spatial positions could be well localized with patterned stimulation in extrastriate area V4. It also provides a novel approach to build a compact prosthesis with relatively few electrodes, which has the potential advantage of reducing tissue damage in real applications.

Developmental abnormalities in cortical GABAergic system in mice lacking mGlu3 metabotropic glutamate receptors

Polymorphic variants of the gene encoding for metabotropic glutamate receptor 3 (mGlu3) are linked to schizophrenia. Because abnormalities of cortical GABAergic interneurons lie at the core of the pathophysiology of schizophrenia, we examined whether mGlu3 receptors influence the developmental trajectory of cortical GABAergic transmission in the postnatal life. mGlu3^-/- mice showed robust changes in the expression of interneuron-related genes in the prefrontal cortex (PFC), including large reductions in the expression of parvalbumin (PV) and the GluN1 subunit of NMDA receptors. The number of cortical cells enwrapped by perineuronal nets was increased in mGlu3^-/- mice, suggesting that mGlu3 receptors shape the temporal window of plasticity of PV⁺ interneurons. Electrophysiological measurements of GABA_A receptor-mediated responses revealed a more depolarized reversal potential of GABA currents in the somata of PFC pyramidal neurons in mGlu3^-/- mice at postnatal d 9 associated with a reduced expression of the K⁺/Cl^- symporter. Finally, adult mGlu3^-/- mice showed lower power in electroencephalographic rhythms at 1-45 Hz in quiet wakefulness as compared with their wild-type counterparts. These findings suggest that mGlu3 receptors have a strong impact on the development of cortical GABAergic transmission and cortical neural synchronization mechanisms corroborating the concept that genetic variants of mGlu3 receptors may predispose to psychiatric disorders.-Imbriglio, T., Verhaeghe, R., Martinello, K., Pascarelli, M. T., Chece, G., Bucci, D., Notartomaso, S., Quattromani, M., Mascio, G., Scalabrì, F., Simeone, A., Maccari, S., Del Percio, C., Wieloch, T., Fucile, S., Babiloni, C., Battaglia, G., Limatola, C., Nicoletti, F., Cannella, M. Developmental abnormalities in cortical GABAergic system in mice lacking mGlu3 metabotropic glutamate receptors.

Cortical activation in generalized seizures

OBJECTIVE

Patients with generalized epilepsy exhibit different epileptiform events including asymptomatic interictal spikes (IS), absence seizures with spike-wave discharges (SWDs), and myoclonic seizures (MS). Our objective was to determine the spatiotemporal patterns of cortical activation in SWDs, IS, and MS in the Gabra1^+/A322D juvenile myoclonic epilepsy mouse.

METHODS

We fabricated affordable, flexible high-density electroencephalography (HdEEG) arrays and recorded spontaneous SWD, IS, and MS with video/HdEEG. We determined differences among the events in amplitude spectral density (ASD) in the δ/θ/α/β/γ frequency bands at baseline (3.5-4.0 seconds before the first spike time, t₀ ) and the prespike period (0.1-0.5 seconds before t₀ ), and we elucidated the spatiotemporal activation during the t₀ spike.

RESULTS

All three events had an increase in ASD between baseline and prespike in at least one frequency band. During prespike, MS had the largest δ-band ASD, but SWD had the greatest α/β/γ band ASD. For all three events, the ASD was largest in the anterior regions. The t₀ spike voltage was also greatest in the anterior regions for all three events and IS and MS had larger voltages than SWD. From 7.5 to 17.5 msec after t₀ , MS had greater voltage than IS and SWD, and maximal voltage was in the posterior parietal region.

SIGNIFICANCE

Changes in spectral density from baseline to prespike indicate that none of these generalized events are instantaneous or entirely unpredictable. Prominent engagement of anterior cortical regions during prespike and at t₀ suggest that common anterior neural circuits participate in each event. Differences in prespike ASD signify that although the events may engage similar brain regions, they may arise from distinct proictal states with different neuronal activity or connectivity. Prolonged activation of the posterior parietal area in MS suggests that posterior circuits contribute to the myoclonic jerk. Together, these findings identify brain regions and processes that could be specifically targeted for further recording and modulation.

Electrophysiological monitoring of inhibition in mammalian species, from rodents to humans

GABAergic interneurons constitute a highly diverse family of neurons that play a critical role in cortical functions. Due to their prominent role in cortical network dynamics, genetic, developmental, or other dysfunctions in GABAergic neurons have been linked to neurological disorders such as epilepsy. Thus, it is crucial to investigate the interaction of these various neurons and to develop methods to specifically and directly monitor inhibitory activity in vivo. While research in small mammals has benefited from a wealth of recent technological development, bridging the gap to large mammals and humans remains a challenge. This is of particular interest since single neuron monitoring with intracranial electrodes in epileptic patients is developing quickly, opening new avenues for understanding the role of different cell types in epilepsy. Here, we review currently available techniques that monitor inhibitory activity in the brain and the respective validations in rodents. Finally, we discuss the future developments of these techniques and how knowledge from animal research can be translated to the study of neuronal circuit dynamics in the human brain.

The Effects of NMDA Receptor Blockade on Sensory-Evoked Responses in Superficial Layers of the Rat Barrel Cortex

Transmission of excitation from L4 to L2/3 is a part of a canonical circuit of cortical sensory signal processing. While synapses from L4 to L2/3 are mediated by both AMPA and NMDA glutamate receptors, previous studies suggested that sensory-evoked excitation of neurons in supragranular layers is almost entirely mediated by NMDA receptors. Here, we readdressed this question using extracellular recordings of sensory-evoked potentials (SEPs) and multiple unit activity (MUA) in the rat barrel cortex. We found that blockade of NMDA receptors using the selective antagonist dAPV profoundly inhibited the late part of L2/3 SEP, the associated sink, and MUA response but did not affect its initial part. Our results indicate that both non-NMDA and NMDA receptors are involved in sensory signal transmission from L4 to L2/3. While non-NMDA receptors mediate fast transmission of sensory signals, NMDA-Rs are importantly involved in the generation of the late phase of the sensory-evoked response in supragranular layers.

Spatial neuronal synchronization and the waveform of oscillations: Implications for EEG and MEG

Neuronal oscillations are ubiquitous in the human brain and are implicated in virtually all brain functions. Although they can be described by a prominent peak in the power spectrum, their waveform is not necessarily sinusoidal and shows rather complex morphology. Both frequency and temporal descriptions of such non-sinusoidal neuronal oscillations can be utilized. However, in non-invasive EEG/MEG recordings the waveform of oscillations often takes a sinusoidal shape which in turn leads to a rather oversimplified view on oscillatory processes. In this study, we show in simulations how spatial synchronization can mask non-sinusoidal features of the underlying rhythmic neuronal processes. Consequently, the degree of non-sinusoidality can serve as a measure of spatial synchronization. To confirm this empirically, we show that a mixture of EEG components is indeed associated with more sinusoidal oscillations compared to the waveform of oscillations in each constituent component. Using simulations, we also show that the spatial mixing of the non-sinusoidal neuronal signals strongly affects the amplitude ratio of the spectral harmonics constituting the waveform. Finally, our simulations show how spatial mixing can affect the strength and even the direction of the amplitude coupling between constituent neuronal harmonics at different frequencies. Validating these simulations, we also demonstrate these effects in real EEG recordings. Our findings have far reaching implications for the neurophysiological interpretation of spectral profiles, cross-frequency interactions, as well as for the unequivocal determination of oscillatory phase.

Sensory Specializations of Mormyrid Fish Are Associated with Species Differences in Electric Signal Localization Behavior

The ability to localize communication signals plays a fundamental role in social interactions. For signal localization to take place, the sensory system of the receiver must extract information about distance and direction to the sender from physical characteristics of the signal. In many sensory systems, information from multiple peripheral receptors must be integrated by central sensory pathways to determine the sender location. Here, we asked whether evolutionary divergence in the electrosensory and visual systems of mormyrid fish is associated with signal localization behavior. In mormyrids, differences in the distribution of electroreceptors on the surface of the skin are associated with differences in the midbrain exterolateral nucleus (EL). Species with electroreceptors clustered in three rosettes on both sides of the head have a small and undifferentiated EL. In contrast, EL is enlarged and subdivided into anterior (ELa) and posterior (ELp) regions in species that have electroreceptors broadly -distributed throughout the body. Interestingly, species with EL and clustered electroreceptors also have larger visual systems and higher visual acuity than species with ELa/ELp and broadly distributed electroreceptors. Species with broadly distributed electroreceptors and ELa/ELp approached a simulated conspecific by following the curved electric field lines generated by the electrosensory stimulus. In contrast, a species with small EL and clustered electroreceptors, but an enlarged visual system, followed shorter and straighter paths to the stimulus source. In the central electrosensory system, evoked field potentials in response to stimuli delivered from the left versus the right differed more in EL than in ELa/ELp. Our results suggest that signal localization behavior is associated with differences in sensory specializations. We propose that the distribution of electroreceptors on the body affects the ability of individuals to align parallel to electric field lines and maintain such alignment while approaching the signal source. The spatial resolution of sensory information relayed from the periphery to the midbrain in species with clustered electroreceptors may allow for gross, but not fine, processing of sender location. Furthermore, visual information may play an important role in localizing signaling individuals in species with small EL and clustered electroreceptors. In line with previous studies, we suggest that the physiological and behavioral differences associated with signal localization reflect adaptations to different habitats and social environments.

Sensory coding is impaired in rat absence epilepsy

KEY POINTS

Absence epilepsy is characterized by the occurrence of spike-and-wave discharges concomitant with an alteration of consciousness and is associated with cognitive comorbidities. In a genetic model of absence epilepsy in the rat, the genetic absence epilepsy rat from Strasbourg (GAERS), spike-and-wave discharges are shown to be initiated in the barrel field primary somatosensory cortex that codes whisker-related information, therefore playing an essential role in the interactions of rodents with their environment. Sensory-information processing is impaired in the epileptic barrel field primary somatosensory cortex of GAERS, with a delayed sensory-evoked potential and a duplicated neuronal response to whisker stimulation in in vivo extracellular recordings. Yet, GAERS present no defaults of performance in a texture discrimination task, suggesting the existence of a compensatory mechanism within the epileptic neuronal network. The results of the present study indicate that physiological primary functions are processed differently in an epileptic cortical network.

ABSTRACT

Several neurodevelopmental pathologies are associated with disorganized cortical circuits that may alter primary functions such as sensory processes. In the present study, we investigated whether the function of a cortical area is altered in the seizure onset zone of absence epilepsy, a prototypical form of childhood genetic epilepsy associated with cognitive impairments. We first combined in vivo multichannel electrophysiological recordings and histology to precisely localize the seizure onset zone in the genetic absence epilepsy rat from Strasbourg (GAERS). We then investigated the functionality of this epileptic zone using extracellular silicon probe recordings of sensory-evoked local field potentials and multi-unit activity, as well as a behavioural test of texture discrimination. We show that seizures in this model are initiated in the barrel field part of the primary somatosensory cortex and are associated with high-frequency oscillations. In this cortex, we found an increased density of parvalbumin-expressing interneurons in layer 5 in GAERS compared to non-epileptic Wistar rats. Its functional investigation revealed that sensory abilities of GAERS are not affected in a texture-discrimination task, whereas the intracortical processing of sensory-evoked information is delayed and duplicated. Altogether, these results suggest that absence seizures are associated with an increase of parvalbumin-inhibitory neurons, which may promote the functional relationship between epileptic oscillations and high-frequency activities. Our findings suggest that cortical circuits operate differently in the epileptic onset zone and may adapt to maintain their ability to process highly specialized information.

High-frequency oscillations and focal seizures in epileptic rodents

High-pass filtering (> 80 Hz) of EEG signals has enabled neuroscientists to analyze high-frequency oscillations (HFOs; i.e., ripples: 80-200 Hz and fast ripples: 250-500 Hz) in epileptic patients presenting with focal seizures and in animal models mimicking this condition. Evidence obtained from these studies indicate that HFOs mirror pathological network activity that may initiate and sustain ictogenesis and epileptogenesis. HFOs are observed in temporal lobe regions of epileptic animals during interictal periods but they also occur before seizure onset and during the ictal period, suggesting that they can pinpoint to the mechanisms of seizure generation. Accordingly, ripples and fast ripples predominate during two specific seizure onset patterns termed low-voltage fast and hypersynchronous, respectively. In this review we will: (i) summarize these experimental studies; (ii) consider the evolution of HFOs over time during epileptogenesis; (iii) address data obtained with optogenetic stimulating procedures both in vitro and in vivo, and (iv) take into account the impact of anti-epileptic drugs on HFOs. We expect these findings to contribute to understanding the neuronal mechanisms leading to ictogenesis and epileptogenesis thus leading to the development of mechanistically targeted anti-epileptic strategies.