Sleep, oscillations, and epilepsy.

Sleep and wake are defined through physiological and behavioral criteria and can be typically separated into non-rapid eye movement (NREM) sleep stages N1, N2, and N3, rapid eye movement (REM) sleep, and wake. Sleep and wake states are not homogenous in time. Their properties vary during the night and day cycle. Given that brain activity changes as a function of NREM, REM, and wake during the night and day cycle, are seizures more likely to occur during NREM, REM, or wake at a specific time? More generally, what is the relationship between sleep-wake cycles and epilepsy? We will review specific examples from clinical data and results from experimental models, focusing on the diversity and heterogeneity of these relationships. We will use a top-down approach, starting with the general architecture of sleep, followed by oscillatory activities, and ending with ionic correlates selected for illustrative purposes, with respect to seizures and interictal spikes. The picture that emerges is that of complexity; sleep disruption and pathological epileptic activities emerge from reorganized circuits. That different circuit alterations can occur across patients and models may explain why sleep alterations and the timing of seizures during the sleep-wake cycle are patient-specific.

Derailment of Sleep Homeostatic Plasticity Affects the Most Plastic Brain Systems and Carries the Risk of Epilepsy.

Although a critical link between non-rapid eye movement (NREM) sleep and epilepsy has long been suspected, the interconnecting mechanisms have remained obscure. However, recent advances in sleep research have provided some clues. Sleep homeostatic plasticity is now recognized as an engine of the synaptic economy and a feature of the brain's ability to adapt to changing demands. This allows epilepsy to be understood as a cost of brain plasticity. On the one hand, plasticity is a force for development, but on the other it opens the possibility of epileptic derailment. Here, we provide a summary of the phenomena that link sleep and epilepsy. The concept of "system epilepsy", or epilepsy as a network disease, is introduced as a general approach to understanding the major epilepsy syndromes, i.e., epilepsies building upon functional brain networks. We discuss how epileptogenesis results in certain major epilepsies following the derailment of NREM sleep homeostatic plasticity. Post-traumatic epilepsy is presented as a general model for this kind of epileptogenesis.

Ionic and synaptic mechanisms of seizure generation and epileptogenesis.

The biophysical mechanisms underlying epileptogenesis and the generation of seizures remain to be better understood. Among many factors triggering epileptogenesis are traumatic brain injury breaking normal synaptic homeostasis and genetic mutations disrupting ionic concentration homeostasis. Impairments in these mechanisms, as seen in various brain diseases, may push the brain network to a pathological state characterized by increased susceptibility to unprovoked seizures. Here, we review recent computational studies exploring the roles of ionic concentration dynamics in the generation, maintenance, and termination of seizures. We further discuss how ionic and synaptic homeostatic mechanisms may give rise to conditions which prime brain networks to exhibit recurrent spontaneous seizures and epilepsy.

New class of reduced computationally efficient neuronal models for large-scale simulations of brain dynamics.

During slow-wave sleep, brain electrical activity is dominated by the slow (< 1 Hz) electroencephalogram (EEG) oscillations characterized by the periodic transitions between active (or Up) and silent (or Down) states in the membrane voltage of the cortical and thalamic neurons. Sleep slow oscillation is believed to play critical role in consolidation of recent memories. Past computational studies, based on the Hodgkin-Huxley type neuronal models, revealed possible intracellular and network mechanisms of the neuronal activity during sleep, however, they failed to explore the large-scale cortical network dynamics depending on collective behavior in the large populations of neurons. In this new study, we developed a novel class of reduced discrete time spiking neuron models for large-scale network simulations of wake and sleep dynamics. In addition to the spiking mechanism, the new model implemented nonlinearities capturing effects of the leak current, the Ca2+ dependent K+ current and the persistent Na+ current that were found to be critical for transitions between Up and Down states of the slow oscillation. We applied the new model to study large-scale two-dimensional cortical network activity during slow-wave sleep. Our study explained traveling wave dynamics and characteristic synchronization properties of transitions between Up and Down states of the slow oscillation as observed in vivo in recordings from cats. We further predict a critical role of synaptic noise and slow adaptive currents for spike sequence replay as found during sleep related memory consolidation.

Methodological standards and functional correlates of depth in vivo electrophysiological recordings in control rodents. A TASK1-WG3 report of the AES/ILAE Translational Task Force of the ILAE.

This paper is a result of work of the AES/ILAE Translational Task Force of the International League Against Epilepsy. The aim is to provide acceptable standards and interpretation of results of electrophysiological depth recordings in vivo in control rodents.

Moderate Cortical Cooling Eliminates Thalamocortical Silent States during Slow Oscillation.

Reduction in temperature depolarizes neurons by a partial closure of potassium channels but decreases the vesicle release probability within synapses. Compared with cooling, neuromodulators produce qualitatively similar effects on intrinsic neuronal properties and synapses in the cortex. We used this similarity of neuronal action in ketamine-xylazine-anesthetized mice and non-anesthetized mice to manipulate the thalamocortical activity. We recorded cortical electroencephalogram/local field potential (LFP) activity and intracellular activities from the somatosensory thalamus in control conditions, during cortical cooling and on rewarming. In the deeply anesthetized mice, moderate cortical cooling was characterized by reversible disruption of the thalamocortical slow-wave pattern rhythmicity and the appearance of fast LFP spikes, with frequencies ranging from 6 to 9 Hz. These LFP spikes were correlated with the rhythmic IPSP activities recorded within the thalamic ventral posterior medial neurons and with depolarizing events in the posterior nucleus neurons. Similar cooling of the cortex during light anesthesia rapidly and reversibly eliminated thalamocortical silent states and evoked thalamocortical persistent activity; conversely, mild heating increased thalamocortical slow-wave rhythmicity. In the non-anesthetized head-restrained mice, cooling also prevented the generation of thalamocortical silent states. We conclude that moderate cortical cooling might be used to manipulate slow-wave network activity and induce neuromodulator-independent transition to activated states. Significance statement: In this study, we demonstrate that moderate local cortical cooling of lightly anesthetized or naturally sleeping mice disrupts thalamocortical slow oscillation and induces the activated local field potential pattern. Mild heating has the opposite effect; it increases the rhythmicity of thalamocortical slow oscillation. Our results demonstrate that slow oscillation can be influenced by manipulations to the properties of cortical neurons without changes in neuromodulation.

Modeling of Age-Dependent Epileptogenesis by Differential Homeostatic Synaptic Scaling.

Homeostatic synaptic plasticity (HSP) has been implicated in the development of hyperexcitability and epileptic seizures following traumatic brain injury (TBI). Our in vivo experimental studies in cats revealed that the severity of TBI-mediated epileptogenesis depends on the age of the animal. To characterize mechanisms of these differences, we studied the properties of the TBI-induced epileptogenesis in a biophysically realistic cortical network model with dynamic ion concentrations. After deafferentation, which was induced by dissection of the afferent inputs, there was a reduction of the network activity and upregulation of excitatory connections leading to spontaneous spike-and-wave type seizures. When axonal sprouting was implemented, the seizure threshold increased in the model of young but not the older animals, which had slower or unidirectional homeostatic processes. Our study suggests that age-related changes in the HSP mechanisms are sufficient to explain the difference in the likelihood of seizure onset in young versus older animals. Significance statement: Traumatic brain injury (TBI) is one of the leading causes of intractable epilepsy. Likelihood of developing epilepsy and seizures following severe brain trauma has been shown to increase with age. Specific mechanisms of TBI-related epileptogenesis and how these mechanisms are affected by age remain to be understood. We test a hypothesis that the failure of homeostatic synaptic regulation, a slow negative feedback mechanism that maintains neural activity within a physiological range through activity-dependent modulation of synaptic strength, in older animals may augment TBI-induced epileptogenesis. Our results provide new insight into understanding this debilitating disorder and may lead to novel avenues for the development of effective treatments of TBI-induced epilepsy.

Global intracellular slow-wave dynamics of the thalamocortical system.

It is widely accepted that corticothalamic neurons recruit the thalamus in slow oscillation, but global slow-wave thalamocortical dynamics have never been experimentally shown. We analyzed intracellular activities of neurons either from different cortical areas or from a variety of specific and nonspecific thalamic nuclei in relation to the phase of global EEG signal in ketamine-xylazine anesthetized mice. We found that, on average, slow-wave active states started off within frontal cortical areas as well as higher-order and intralaminar thalamus (posterior and parafascicular nuclei) simultaneously. Then, the leading edge of active states propagated in the anteroposterior/lateral direction over the cortex at ∼40 mm/s. The latest structure we recorded within the slow-wave cycle was the anterior thalamus, which followed active states of the retrosplenial cortex. Active states from different cortical areas tended to terminate simultaneously. Sensory thalamic ventral posterior medial and lateral geniculate nuclei followed cortical active states with major inhibitory and weak tonic-like "modulator" EPSPs. In these nuclei, sharp-rising, large-amplitude EPSPs ("drivers") were not modulated by cortical slow waves, suggesting their origin in ascending pathways. The thalamic active states in other investigated nuclei were composed of depolarization: some revealing "driver"- and "modulator"-like EPSPs, others showing "modulator"-like EPSPs only. We conclude that sensory thalamic nuclei follow the propagating cortical waves, whereas neurons from higher-order thalamic nuclei display "hub dynamics" and thus may contribute to the generation of cortical slow waves.

The impact of cortical deafferentation on the neocortical slow oscillation.

Slow oscillation is the main brain rhythm observed during deep sleep in mammals. Although several studies have demonstrated its neocortical origin, the extent of the thalamic contribution is still a matter of discussion. Using electrophysiological recordings in vivo on cats and computational modeling, we found that the local thalamic inactivation or the complete isolation of the neocortical slabs maintained within the brain dramatically reduced the expression of slow and fast oscillations in affected cortical areas. The slow oscillation began to recover 12 h after thalamic inactivation. The slow oscillation, but not faster activities, nearly recovered after 30 h and persisted for weeks in the isolated slabs. We also observed an increase of the membrane potential fluctuations recorded in vivo several hours after thalamic inactivation. Mimicking this enhancement in a network computational model with an increased postsynaptic activity of long-range intracortical afferents or scaling K(+) leak current, but not several other Na(+) and K(+) intrinsic currents was sufficient for recovering the slow oscillation. We conclude that, in the intact brain, the thalamus contributes to the generation of cortical active states of the slow oscillation and mediates its large-scale synchronization. Our study also suggests that the deafferentation-induced alterations of the sleep slow oscillation can be counteracted by compensatory intracortical mechanisms and that the sleep slow oscillation is a fundamental and intrinsic state of the neocortex.

Neocortical inhibitory activities and long-range afferents contribute to the synchronous onset of silent states of the neocortical slow oscillation.

During slow-wave sleep, neurons of the thalamocortical network are engaged in a slow oscillation (<1 Hz), which consists of an alternation between the active and the silent states. Several studies have provided insights on the transition from the silent, which are essentially periods of disfacilitation, to the active states. However, the conditions leading to the synchronous onset of the silent state remain elusive. We hypothesized that a synchronous input to local inhibitory neurons could contribute to the transition to the silent state in the cat suprasylvian gyrus during natural sleep and under ketamine-xylazine anesthesia. After partial and complete deafferentation of the cortex, we found that the silent state onset was more variable among remote sites. We found that the transition to the silent state was preceded by a reduction in excitatory postsynaptic potentials and firing probability in cortical neurons. We tested the impact of chloride-mediated inhibition in the silent-state onset. We uncovered a long-duration (100-300 ms) inhibitory barrage occurring about 250 ms before the silent state onset in 3-6% of neurons during anesthesia and in 12-15% of cases during natural sleep. These inhibitory activities caused a decrease in cortical firing that reduced the excitatory drive in the neocortical network. That chain reaction of disfacilitation ends up on the silent state. Electrical stimuli could trigger a network silent state with a maximal efficacy in deep cortical layers. We conclude that long-range afferents to the neocortex and chloride-mediated inhibition play a role in the initiation of the silent state.

Regulation of AMPA and NMDA receptor-mediated EPSPs in dendritic trees of thalamocortical cells.

Two main excitatory synapses are formed at the dendritic arbor of first-order nuclei thalamocortical (TC) neurons. Ascending sensory axons primarily establish contacts at large proximal dendrites, whereas descending corticothalamic fibers form synapses on thin distal dendrites. With the use of a multicomparment computational model based on fully reconstructed TC neurons from the ventroposterolateral nucleus of the cat, we compared local responses at the site of stimulation as well as somatic responses induced by both α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR)- and N-methyl-D-aspartate receptor (NMDAR)-mediated currents. We found that AMPAR-mediated responses, when synapses were located at proximal dendrites, induced a larger depolarization at the level of soma, whereas NMDAR-mediated responses were more efficient for synapses located at distal dendrites. The voltage transfer and transfer impedance were higher for NMDAR than for AMPAR activation at any location. For both types of synaptic current and for both input locations at the dendritic arbor, somatic responses were characterized by a low variability despite the large variability found in local responses in dendrites. The large neurons had overall smaller somatic responses than small neurons, but this relation was not found in local dendritic responses. We conclude that in TC cells, the dendritic location of small synaptic inputs does not play a major role in the amplitude of a somatic response, but the size of the neuron does. The variability of response amplitude between cells was much larger than the variability within cells. This suggests possible functional segregation of TC neurons of different size.

Local origin of slow EEG waves during sleep.

Neuronal activity mediating EEG slow waves consists of synchronous alternation of intracellular active and silent states. Recent data demonstrate that each active state of a sleep slow wave originates in a particular cortical location and propagate to involve other cortical areas. Preferential sites of origin of these waves are: the frontal cortex in adult humans, the associative cortex in cats and the somatosensory cortex in mice. In the site of origin of these slow waves any neuron can initiate a particular cycle, however there are neuronal groups with high likelihood of triggering a particular cycle. In epileptic patients, these neurons are mostly located in superficial layers, but in healthy experimental animals, populations ofintrinsically bursting neurons with a high probability of triggering spontaneous active states have been found in deeper cortical layers.

Respiration organizes gamma synchrony in the prefronto-thalamic network.

Multiple cognitive operations are associated with the emergence of gamma oscillations in the medial prefrontal cortex (mPFC) although little is known about the mechanisms that control this rhythm. Using local field potential recordings from cats, we show that periodic bursts of gamma recur with 1 Hz regularity in the wake mPFC and are locked to the exhalation phase of the respiratory cycle. Respiration organizes long-range coherence in the gamma band between the mPFC and the nucleus reuniens the thalamus (Reu), linking the prefrontal cortex and the hippocampus. In vivo intracellular recordings of the mouse thalamus reveal that respiration timing is propagated by synaptic activity in Reu and likely underlies the emergence of gamma bursts in the prefrontal cortex. Our findings highlight breathing as an important substrate for long-range neuronal synchronization across the prefrontal circuit, a key network for cognitive operations.

Properties of slow oscillation during slow-wave sleep and anesthesia in cats.

Deep anesthesia is commonly used as a model of slow-wave sleep (SWS). Ketamine-xylazine anesthesia reproduces the main features of sleep slow oscillation: slow, large-amplitude waves in field potential, which are generated by the alternation of hyperpolarized and depolarized states of cortical neurons. However, direct quantitative comparison of field potential and membrane potential fluctuations during natural sleep and anesthesia is lacking, so it remains unclear how well the properties of sleep slow oscillation are reproduced by the ketamine-xylazine anesthesia model. Here, we used field potential and intracellular recordings in different cortical areas in the cat to directly compare properties of slow oscillation during natural sleep and ketamine-xylazine anesthesia. During SWS cortical activity showed higher power in the slow/delta (0.1-4 Hz) and spindle (8-14 Hz) frequency range, whereas under anesthesia the power in the gamma band (30-100 Hz) was higher. During anesthesia, slow waves were more rhythmic and more synchronous across the cortex. Intracellular recordings revealed that silent states were longer and the amplitude of membrane potential around transition between active and silent states was bigger under anesthesia. Slow waves were mostly uniform across cortical areas under anesthesia, but in SWS, they were most pronounced in associative and visual areas but smaller and less regular in somatosensory and motor cortices. We conclude that, although the main features of the slow oscillation in sleep and anesthesia appear similar, multiple cellular and network features are differently expressed during natural SWS compared with ketamine-xylazine anesthesia.

Corticothalamic feedback controls sleep spindle duration in vivo.

Spindle oscillations are commonly observed during stage 2 of non-rapid eye movement sleep. During sleep spindles, the cerebral cortex and thalamus interact through feedback connections. Both initiation and termination of spindle oscillations are thought to originate in the thalamus based on thalamic recordings and computational models, although some in vivo results suggest otherwise. Here, we have used computer modeling and in vivo multisite recordings from the cortex and the thalamus in cats to examine the involvement of the cortex in spindle oscillations. We found that although the propagation of spindles depended on synaptic interaction within the thalamus, the initiation and termination of spindle sequences critically involved corticothalamic influences.

Interneuron-mediated inhibition synchronizes neuronal activity during slow oscillation.

The signature of slow-wave sleep in the electroencephalogram (EEG) is large-amplitude fluctuation of the field potential, which reflects synchronous alternation of activity and silence across cortical neurons. While initiation of the active cortical states during sleep slow oscillation has been intensively studied, the biological mechanisms which drive the network transition from an active state to silence remain poorly understood. In the current study, using a combination of in vivo electrophysiology and thalamocortical network simulation, we explored the impact of intrinsic and synaptic inhibition on state transition during sleep slow oscillation. We found that in normal physiological conditions, synaptic inhibition controls the duration and the synchrony of active state termination. The decline of interneuron-mediated inhibition led to asynchronous downward transition across the cortical network and broke the regular slow oscillation pattern. Furthermore, in both in vivo experiment and computational modelling, we revealed that when the level of synaptic inhibition was reduced significantly, it led to a recovery of synchronized oscillations in the form of seizure-like bursting activity. In this condition, the fast active state termination was mediated by intrinsic hyperpolarizing conductances. Our study highlights the significance of both intrinsic and synaptic inhibition in manipulating sleep slow rhythms.

Brain states in freely behaving marmosets.

STUDY OBJECTIVES: We evaluated common marmosets as a perspective animal model to study human sleep and wake states. METHODS: Using wireless neurologger recordings, we performed longitudinal multichannel local field potential (LFP) cortical, hippocampal, neck muscle, and video recordings in three freely behaving marmosets. The brain states were formally identified using self-organizing maps. RESULTS: Marmosets were generally awake during the day with occasional 1-2 naps, and they slept during the night. Major electrographic patterns fall in five clearly distinguished categories: wakefulness, drowsiness, light and deep NREM sleep, and REM. Marmosets typically had 14-16 sleep cycles per night, with either gradually increasing or relatively low, but stable delta power within the cycle. Overall, the delta power decreased throughout the night sleep. Marmosets demonstrated prominent high amplitude somatosensory mu-rhythm (10-15 Hz), accompanied with neocortical ripples, and alternated with occipital alpha rhythm (10-15 Hz). NREM sleep was characterized with the presence of high amplitude slow waves, sleep spindles and ripples in neocortex, and sharp-wave-ripple complexes in CA1. Light and deep stages differed in levels of delta and sigma power and muscle tone. REM sleep was defined with low muscle tone and activated LFP with predominant beta-activity and rare spindle-like or mu-like events. CONCLUSIONS: Multiple features of sleep-wake state distribution and electrographic patterns associated with behavioral states in marmosets closely match human states, although marmoset have shorter sleep cycles. This demonstrates that marmosets represent an excellent model to study origin of human electrographical rhythms and brain states.

Synaptic impairment induced by paroxysmal ionic conditions in neocortex.

PURPOSE: Seizures are associated with a reduction in extracellular Ca²(+) concentration ([Ca²(+) ](o) ) and an increase in extracellular K(+) concentration ([K(+) ](o) ). The long-range synchrony observed between distant electrodes during seizures is weak. We hypothesized that changes in extracellular ionic conditions during seizures are sufficient to alter synaptic neuronal responses and synchrony in the neocortex. METHODS: We obtained in vivo and in vitro electrophysiologic recordings combined with microstimulation from cat/rat neocortical neurons during seizures and seizure-like ionic conditions. In vitro the [K(+) ](o) was 2.8, 6.25, 8.0, and 12 mm and the [Ca²(+) ](o) was 1.2 and 0.6 mm. KEY FINDINGS: During seizures recorded in vivo, we observed abolition of evoked synaptic responses. In vitro, the membrane potential of both regular-spiking and fast-spiking neurons was depolarized in high [K(+) ](o) conditions and hyperpolarized in high [Ca²(+) ](o) conditions. During high [K(+) ](o) conditions, changes in [Ca²(+) ](o) did not affect membrane potential. The synaptic responsiveness of both regular-spiking and fast-spiking neurons was reduced during seizure-like ionic conditions. A reduction in [Ca²(+) ](o) to 0.6 mm increased failure rates but did not abolish responses. However, an increase in [K(+) ](o) to 12 mm abolished postsynaptic responses, which depended on a blockade in axonal spike propagation. SIGNIFICANCE: We conclude that concomitant changes in [K(+) ](o) and [Ca²(+) ](o) observed during seizures contribute largely to the alterations of synaptic neuronal responses and to the decrease in long-range synchrony during neocortical seizures.

Origin of active states in local neocortical networks during slow sleep oscillation.

Slow-wave sleep is characterized by spontaneous alternations of activity and silence in corticothalamic networks, but the causes of transition from silence to activity remain unknown. We investigated local mechanisms underlying initiation of activity, using simultaneous multisite field potential, multiunit recordings, and intracellular recordings from 2 to 4 nearby neurons in naturally sleeping or anesthetized cats. We demonstrate that activity may start in any neuron or recording location, with tens of milliseconds delay in other cells and sites. Typically, however, activity originated at deep locations, then involved some superficial cells, but appeared later in the middle of the cortex. Neuronal firing was also found to begin, after the onset of active states, at depths that correspond to cortical layer V. These results support the hypothesis that switch from silence to activity is mediated by spontaneous synaptic events, whereby any neuron may become active first. Due to probabilistic nature of activity onset, the large pyramidal cells from deep cortical layers, which are equipped with the most numerous synaptic inputs and large projection fields, are best suited for switching the whole network into active state.