Dynamic interactions determine partial thalamic quiescence in a computer network model of spike-and-wave seizures

Spike-and-wave discharges of absence seizures in a sleep waves-constrained corticothalamic model

AIMS

Recurrent network activity in corticothalamic circuits generates physiological and pathological EEG waves. Many computer models have simulated spike-and-wave discharges (SWDs), the EEG hallmark of absence seizures (ASs). However, these models either provided detailed simulated activity only in a selected territory (i.e., cortical or thalamic) or did not test whether their corticothalamic networks could reproduce the physiological activities that are generated by these circuits.

METHODS

Using a biophysical large-scale corticothalamic model that reproduces the full extent of EEG sleep waves, including sleep spindles, delta, and slow (<1 Hz) waves, here we investigated how single abnormalities in voltage- or transmitter-gated channels in the neocortex or thalamus led to SWDs.

RESULTS

We found that a selective increase in the tonic γ-aminobutyric acid type A receptor (GABA-A) inhibition of first-order thalamocortical (TC) neurons or a selective decrease in cortical phasic GABA-A inhibition is sufficient to generate ~4 Hz SWDs (as in humans) that invariably start in neocortical territories. Decreasing the leak conductance of higher-order TC neurons leads to ~7 Hz SWDs (as in rodent models) while maintaining sleep spindles at 7-14 Hz.

CONCLUSION

By challenging key features of current mechanistic views, this simulated ictal corticothalamic activity provides novel understanding of ASs and makes key testable predictions.

The Unexplored Territory of Neural Models: Potential Guides for Exploring the Function of Metabotropic Neuromodulation

The space of possible neural models is enormous and under-explored. Single cell computational neuroscience models account for a range of dynamical properties of membrane potential, but typically do not address network function. In contrast, most models focused on network function address the dimensions of excitatory weight matrices and firing thresholds without addressing the complexities of metabotropic receptor effects on intrinsic properties. There are many under-explored dimensions of neural parameter space, and the field needs a framework for representing what has been explored and what has not. Possible frameworks include maps of parameter spaces, or efforts to categorize the fundamental elements and molecules of neural circuit function. Here we review dimensions that are under-explored in network models that include the metabotropic modulation of synaptic plasticity and presynaptic inhibition, spike frequency adaptation due to calcium-dependent potassium currents, and afterdepolarization due to calcium-sensitive non-specific cation currents and hyperpolarization activated cation currents. Neuroscience research should more effectively explore possible functional models incorporating under-explored dimensions of neural function.

Simulation Neurotechnologies for Advancing Brain Research: Parallelizing Large Networks in NEURON

Large multiscale neuronal network simulations are of increasing value as more big data are gathered about brain wiring and organization under the auspices of a current major research initiative, such as Brain Research through Advancing Innovative Neurotechnologies. The development of these models requires new simulation technologies. We describe here the current use of the NEURON simulator with message passing interface (MPI) for simulation in the domain of moderately large networks on commonly available high-performance computers (HPCs). We discuss the basic layout of such simulations, including the methods of simulation setup, the run-time spike-passing paradigm, and postsimulation data storage and data management approaches. Using the Neuroscience Gateway, a portal for computational neuroscience that provides access to large HPCs, we benchmark simulations of neuronal networks of different sizes (500-100,000 cells), and using different numbers of nodes (1-256). We compare three types of networks, composed of either Izhikevich integrate-and-fire neurons (I&F), single-compartment Hodgkin-Huxley (HH) cells, or a hybrid network with half of each. Results show simulation run time increased approximately linearly with network size and decreased almost linearly with the number of nodes. Networks with I&F neurons were faster than HH networks, although differences were small since all tested cells were point neurons with a single compartment.

Generalized seizures in a neural field model with bursting dynamics

The mechanisms underlying generalized seizures are explored with neural field theory. A corticothalamic neural field model that has accounted for multiple brain activity phenomena and states is used to explore changes leading to pathological seizure states. It is found that absence seizures arise from instabilities in the system and replicate experimental studies in numerous animal models and clinical studies.

Seizure prediction in hippocampal and neocortical epilepsy using a model-based approach

OBJECTIVES

The aim of this study is to develop a model based seizure prediction method.

METHODS

A neural mass model was used to simulate the macro-scale dynamics of intracranial EEG data. The model was composed of pyramidal cells, excitatory and inhibitory interneurons described through state equations. Twelve model's parameters were estimated by fitting the model to the power spectral density of intracranial EEG signals and then integrated based on information obtained by investigating changes in the parameters prior to seizures. Twenty-one patients with medically intractable hippocampal and neocortical focal epilepsy were studied.

RESULTS

Tuned to obtain maximum sensitivity, an average sensitivity of 87.07% and 92.6% with an average false prediction rate of 0.2 and 0.15/h were achieved using maximum seizure occurrence periods of 30 and 50 min and a minimum seizure prediction horizon of 10s, respectively. Under maximum specificity conditions, the system sensitivity decreased to 82.9% and 90.05% and the false prediction rates were reduced to 0.16 and 0.12/h using maximum seizure occurrence periods of 30 and 50 min, respectively.

CONCLUSIONS

The spatio-temporal changes in the parameters demonstrated patient-specific preictal signatures that could be used for seizure prediction.

SIGNIFICANCE

The present findings suggest that the model-based approach may aid prediction of seizures.

Modeling Neural Activity

This paper provides an overview of different types of models for studying activity of nerve cells and their networks with a special emphasis on neural oscillations. One part describes the neuronal models based on the Hodgkin and Huxley formalism first described in the 1950s. It is discussed how further simplifications of this formalism enable mathematical analysis of the process of neural excitability. The focus of the paper’s second component is on network activity. Understanding network function is one of the important frontiers remaining in neuroscience. At present, experimental techniques can only provide global recordings or samples of the activity of the huge networks that form the nervous system. Models in neuroscience can therefore play a critical role by providing a framework for integration of necessarily incomplete datasets, thereby providing insight into the mechanisms of neural function. Network models can either explicitly contain individual network nodes that model the neurons, or they can be based on representations of compound population activity. The latter approach was pioneered by Wilson and Cowan in the 1970s. Finally I provide an overview and discuss how network models are employed in the study of neuronal network pathology such as epilepsy.

CONTROLLING SYNCHRONIZATION IN A NEURON-LEVEL POPULATION MODEL

We have studied coupled neural populations in an effort to understand basic mechanisms that maintain their normal synchronization level despite changes in the inter-population coupling levels. Towards this goal, we have incorporated coupling and internal feedback structures in a neuron-level population model from the literature. We study two forms of internal feedback — regulation of excitation, and compensation of excessive excitation with inhibition. We show that normal feedback actions quickly regulate/compensate an abnormally high coupling between the neural populations, whereas a pathology in these feedback actions can lead to abnormal synchronization and "seizure"-like high amplitude oscillations. We then develop an external control paradigm, termed feedback decoupling, as a robust synchronization control strategy. The external feedback decoupling controller acts to achieve the operational objective of maintaining normal-level synchronous behavior irrespective of the pathology in the internal feedback mechanisms. Results from such an analysis have an interesting physical interpretation and specific implications for the treatment of diseases such as epilepsy. The proposed remedy is consistent with a variety of recent observations in the human and animal epileptic brain, and with theories from nonlinear systems, adaptive systems, optimization, and neurophysiology.

Multiple firing patterns in deep dorsal horn neurons of the spinal cord: computational analysis of mechanisms and functional implications

Deep dorsal horn relay neurons (dDHNs) of the spinal cord are known to exhibit multiple firing patterns under the control of local metabotropic neuromodulation: tonic firing, plateau potential, and spontaneous oscillations. This work investigates the role of interactions between voltage-gated channels and the occurrence of different firing patterns and then correlates these two phenomena with their functional role in sensory information processing. We designed a conductance-based model using the NEURON software package, which successfully reproduced the classical features of plateau in dDHNs, including a wind-up of the neuronal response after repetitive stimulation. This modeling approach allowed us to systematically test the impact of conductance interactions on the firing patterns. We found that the expression of multiple firing patterns can be reproduced by changes in the balance between two currents (L-type calcium and potassium inward rectifier conductances). By investigating a possible generalization of the firing state switch, we found that the switch can also occur by varying the balance of any hyperpolarizing and depolarizing conductances. This result extends the control of the firing switch to neuromodulators or to network effects such as synaptic inhibition. We observed that the switch between the different firing patterns occurs as a continuous function in the model, revealing a particular intermediate state called the accelerating mode. To characterize the functional effect of a firing switch on information transfer, we used correlation analysis between a model of peripheral nociceptive afference and the dDHN model. The simulation results indicate that the accelerating mode was the optimal firing state for information transfer.

The properties of reticular thalamic neuron GABA(A) IPSCs of absence epilepsy rats lead to enhanced network excitability

Both human investigations and studies in animal models have suggested that abnormalities in GABA(A) receptor function have a potential role in the pathophysiology of absence seizures. Recently we showed that, prior to seizure onset, GABA(A) IPSCs in thalamic reticular (NRT) neurons of genetic absence epilepsy rats from Strasbourg (GAERS) had a 25% larger amplitude, a 40% faster decay and a 45% smaller paired-pulse depression than those of nonepileptic control (NEC) rats. By means of a novel mathematical description, the properties of both GAERS and NEC GABAergic synapses can be mimicked. These model synapses were then used in an NRT network model in order to investigate their potential impact on the neuronal firing patterns. Compared to NEC, GAERS NRT neurons show an overall increase in excitability and a higher frequency and regularity of firing in response to periodic input signals. Moreover, in response to randomly distributed stimuli, the GAERS but not the NEC model produces resonance between 7 and 9 Hz, the frequency range of spike-wave discharges in GAERS. The implications of these results for the epileptogenesis of absence seizures are discussed.

Seizure-like afterdischarges simulated in a model neuron

To explore non-synaptic mechanisms in paroxysmal discharges, we used a computer model of a simplified hippocampal pyramidal cell, surrounded by interstitial space and a "glial-endothelial" buffer system. Ion channels for Na+, K+, Ca2+ and Cl- ion antiport 3Na/Ca, and "active" ion pumps were represented in the neuron membrane. The glia had "leak" conductances and an ion pump. Fluxes, concentration changes and cell swelling were computed. The neuron was stimulated by injecting current. Afterdischarge (AD) followed stimulation if depolarization due to rising interstitial K+ concentration ([K+]o) activated persistent Na+ current (INa.P). AD was either simple or self-regenerating; either regular (tonic) or burst-type (clonic); and always self-limiting. Self-regenerating AD required sufficient INa.P to ensure re-excitation. Burst firing depended on activation of dendritic Ca2+ currents and Ca-dependent K+ current. Varying glial buffer function influenced [K+]o accumulation and afterdischarge duration. Variations in Na+ and K+ currents influenced the threshold and the duration of AD. The data show that high [K+]o and intrinsic membrane currents can produce the feedback of self-regenerating afterdischarges without synaptic input. The simulated discharge resembles neuron behavior during paroxysmal firing in living brain tissue.

propagation of seizure-like activity in a model of neocortex

SUMMARY

Seizures in pediatric epilepsy are often associated with spreading, repetitive bursting activity in neocortex. The authors examined onset and propagation of seizure-like activity using a computational model of cortical circuitry. The model includes two pyramidal cell types and four types of inhibitory interneurons. Each neuron is represented by a multicompartmental model with biophysically realistic ion channels. The authors determined the role of bursting neurons and found that their capability of driving network oscillations is most prominent in networks with either weak or relatively strong excitatory synaptic coupling. Synaptic coupling strength was varied in a separate set of simulations to examine its role in network bursting. Oscillations both between cortical layers (vertical oscillations) and between cortical areas (horizontal oscillations) emerge at moderate excitatory coupling strengths. For horizontal propagation, existence of a fast-conducting fiber system and its properties are critical. Seizure-like oscillatory activity may originate from single neurons or small networks, and that activity may propagate in two principal fashions: one that can be represented by a unidirectional (pacemaker)-type process and the other as multi- or bidirectional propagating waves. The frequency of the bursting patterns relates to underlying propagating activity that can either sustain or disrupt the ongoing oscillation.

Influence of norepinephrine on somatosensory neuronal responses in the rat thalamus: a combined modeling and in vivo multi-channel, multi-neuron recording study

Norepinephrine released within primary sensory circuits from locus coeruleus afferent fibers can produce a spectrum of modulatory actions on spontaneous or sensory-evoked activity of individual neurons. Within the ventral posterior medial thalamus, membrane currents modulated by norepinephrine have been identified. However, the relationship between the cellular effects of norepinephrine and the impact of norepinephrine release on populations of neurons encoding sensory signals is still open to question. To address this lacuna in understanding the net impact of the noradrenergic system on sensory signal processing, a computational model of the rat trigeminal somatosensory thalamus was generated. The effects of independent manipulation of different cellular actions of norepinephrine on simulated afferent input to the computational model were then examined. The results of these simulations aided in the design of in vivo neural ensemble recording experiments where sensory-driven responses of thalamic neurons were measured before and during locus coeruleus activation in waking animals. Together the simulated and experimental results reveal several key insights regarding the regulation of neural network operation by norepinephrine including: 1) cell-specific modulatory actions of norepinephrine, 2) mechanisms of norepinephrine action that can improve the tuning of the network and increase the signal-to-noise ratio of cellular responses in order to enhance network representation of salient stimulus features and 3) identification of the dynamic range of thalamic neuron function through which norepinephrine operates.

Starting and stopping mechanisms of absence epileptic seizures are revealed by hazard functions

We show that the hazard function provides useful information about the starting and the stopping mechanisms of absence epileptic seizures. The hazard function quantifies changes in the probability that an event (respectively, the starting and the stopping of a seizure) occurs in some small time interval given that it has not occurred yet. It informs us about changes in the concentration of endogenous substances that modulate the neuronal signalling properties of (parts of) the brain. In a pharmacological experiment, we used the hazard function to study the effect of a GABA-transaminase inhibitor (vigabatrin) on the starting and the stopping mechanisms of absence epileptic seizures in a genetic rat model of absence epilepsy (the WAG/Rij rat). This experiment showed that a high GABA level changed the stopping mechanism of the absence epileptic seizures, creating much better conditions for very long seizures to develop. With respect to the starting mechanism, it was found that both with a high and a low GABA level, there was evidence for a recovery mechanism that decreases the probability that a new seizure starts. Initially, this probability is larger with a high GABA level, but gradually it converges to the same constant baseline probability as in the condition with a low GABA level.

The Blue Brain Project

IBM's Blue Gene supercomputer allows a quantum leap in the level of detail at which the brain can be modelled. I argue that the time is right to begin assimilating the wealth of data that has been accumulated over the past century and start building biologically accurate models of the brain from first principles to aid our understanding of brain function and dysfunction.

Grouping of brain rhythms in corticothalamic systems

Different brain rhythms, with both low-frequency and fast-frequency, are grouped within complex wave-sequences. Instead of dissecting various frequency bands of the major oscillations that characterize the brain electrical activity during states of vigilance, it is conceptually more rewarding to analyze their coalescence, which is due to neuronal interactions in corticothalamic systems. This concept of unified brain rhythms does not only include low-frequency sleep oscillations but also fast (beta and gamma) activities that are not exclusively confined to brain-activated states, since they also occur during slow-wave sleep. The major factor behind this coalescence is the cortically generated slow oscillation that, through corticocortical and corticothalamic drives, is effective in grouping other brain rhythms. The experimental evidence for unified oscillations derived from simultaneous intracellular recordings of cortical and thalamic neurons in vivo, while recent studies in humans using global methods provided congruent results of grouping different types of slow and fast oscillatory activities. Far from being epiphenomena, spontaneous brain rhythms have an important role in synaptic plasticity. The role of slow-wave sleep oscillation in consolidating memory traces acquired during wakefulness is being explored in both experimental animals and human subjects. Highly synchronized sleep oscillations may develop into seizures that are generated intracortically and lead to inhibition of thalamocortical neurons, via activation of thalamic reticular neurons, which may explain the obliteration of signals from the external world and unconsciousness during some paroxysmal states.

Feedback Inhibition and Throughput Properties of an Integrate-and-Fire-or-Burst Network Model of Retinogeniculate Transmission

Computational modeling has played an important role in the dissection of the biophysical basis of rhythmic oscillations in thalamus that are associated with sleep and certain forms of epilepsy. In contrast, the dynamic filter properties of thalamic relay nuclei during states of arousal are not well understood. Here we present a modeling and simulation study of the throughput properties of the visually driven dorsal lateral geniculate nucleus (dLGN) in the presence of feedback inhibition from the perigeniculate nucleus (PGN). We employ thalamocortical (TC) and thalamic reticular (RE) versions of a minimal integrate-and-fire-or-burst type model and a one-dimensional, two-layered network architecture. Potassium leakage conductances control the neuromodulatory state of the network and eliminate rhythmic bursting in the presence of spontaneous input (i.e., wake up the network). The aroused dLGN/PGN network model is subsequently stimulated by spatially homogeneous spontaneous retinal input or spatio-temporally patterned input consistent with the activity of X-type retinal ganglion cells during full-field or drifting grating visual stimulation. The throughput properties of this visually-driven dLGN/PGN network model are characterized and quantified as a function of stimulus parameters such as contrast, temporal frequency, and spatial frequency. During low-frequency oscillatory full-field stimulation, feedback inhibition from RE neurons often leads to TC neuron burst responses, while at high frequency tonic responses dominate. Depending on the average rate of stimulation, contrast level, and temporal frequency of modulation, the TC and RE cell bursts may or may not be phase-locked to the visual stimulus. During drifting-grating stimulation, phase-locked bursts often occur for sufficiently high contrast so long as the spatial period of the grating is not small compared to the synaptic footprint length, i.e., the spatial scale of the network connectivity.

Sleep, epilepsy and thalamic reticular inhibitory neurons

Thalamic reticular neurons release the potent inhibitory neurotransmitter GABA and their main targets are thalamocortical neurons in the dorsal thalamus. This article focuses on two topics: (i) the role of thalamic reticular neurons in the initiation of spindles, a hallmark oscillation during early sleep stages; and (ii) the reticular-induced inhibition of thalamocortical neurons during cortically generated spike-wave seizures. Although hotly debated during the past decade, the idea of spindle generation by a network of GABAergic reticular neurons was recently supported by in vivo and in computo studies demonstrating interactions between inhibitory reticular neurons that lead to spindle sequences. During spike-wave seizures and electrical paroxysms of the Lennox-Gastaut type, which arise in the neocortex, reticular neurons are powerfully excited through corticofugal projections and they produce prolonged inhibitory postsynaptic potentials in thalamocortical neurons. Thus, GABAergic reticular neurons are crucial in the generation of some sleep rhythms, which produce synaptic plasticity, and in inhibiting external signals through thalamocortical neurons, which leads to unconsciousness during absence epilepsy.

Single-column thalamocortical network model exhibiting gamma oscillations, sleep spindles, and epileptogenic bursts

To better understand population phenomena in thalamocortical neuronal ensembles, we have constructed a preliminary network model with 3,560 multicompartment neurons (containing soma, branching dendrites, and a portion of axon). Types of neurons included superficial pyramids (with regular spiking [RS] and fast rhythmic bursting [FRB] firing behaviors); RS spiny stellates; fast spiking (FS) interneurons, with basket-type and axoaxonic types of connectivity, and located in superficial and deep cortical layers; low threshold spiking (LTS) interneurons, which contacted principal cell dendrites; deep pyramids, which could have RS or intrinsic bursting (IB) firing behaviors, and endowed either with nontufted apical dendrites or with long tufted apical dendrites; thalamocortical relay (TCR) cells; and nucleus reticularis (nRT) cells. To the extent possible, both electrophysiology and synaptic connectivity were based on published data, although many arbitrary choices were necessary. In addition to synaptic connectivity (by AMPA/kainate, NMDA, and GABA(A) receptors), we also included electrical coupling between dendrites of interneurons, nRT cells, and TCR cells, and--in various combinations--electrical coupling between the proximal axons of certain cortical principal neurons. Our network model replicates several observed population phenomena, including 1) persistent gamma oscillations; 2) thalamocortical sleep spindles; 3) series of synchronized population bursts, resembling electrographic seizures; 4) isolated double population bursts with superimposed very fast oscillations (>100 Hz, "VFO"); 5) spike-wave, polyspike-wave, and fast runs (about 10 Hz). We show that epileptiform bursts, including double and multiple bursts, containing VFO occur in rat auditory cortex in vitro, in the presence of kainate, when both GABA(A) and GABA(B) receptors are blocked. Electrical coupling between axons appears necessary (as reported previously) for persistent gamma and additionally plays a role in the detailed shaping of epileptogenic events. The degree of recurrent synaptic excitation between spiny stellate cells, and their tendency to fire throughout multiple bursts, also appears critical in shaping epileptogenic events.

Functional impact of alternative splicing of human T-type Cav3.3 calcium channels

Low-voltage-activated T-type (Cav3) Ca2+ channels produce low-threshold spikes that trigger burst firing in many neurons. The CACNA1I gene encodes the Cav3.3 isoform, which activates and inactivates much more slowly than the other Cav3 channels. These distinctive kinetic features, along with its brain-region-specific expression, suggest that Cav3.3 channels endow neurons with the ability to generate long-lasting bursts of firing. The human CACNA1I gene contains two regions of alternative splicing: variable inclusion of exon 9 and an alternative acceptor site within exon 33, which leads to deletion of 13 amino acids (Delta33). The goal of this study is to determine the functional consequences of these variations in the full-length channel. The cDNA encoding these regions were cloned using RT-PCR from human brain, and currents were recorded by whole cell patch clamp. Introduction of the Delta33 deletion slowed the rate of channel opening. Addition of exon 9 had little effect on kinetics, whereas its addition to Delta33 channels unexpectedly slowed both activation and inactivation kinetics. Modeling of neuronal firing showed that exon 9 or Delta33 alone reduced burst firing, whereas the combination enhanced firing. The major conclusions of this study are that the intracellular regions after repeats I and IV play a role in channel gating, that their effects are interdependent, suggesting a direct interaction, and that splice variation of Cav3.3 channels provides a mechanism for fine-tuning the latency and duration of low-threshold spikes.

Neocortical seizures: initiation, development and cessation

Different forms of electrical paroxysms in experimental animals mimic the patterns of absence seizures associated with spike-wave complexes at approximately 3 Hz and of Lennox-Gastaut seizures with spike-wave or polyspike-wave complexes at approximately 1.5-2.5 Hz, intermingled with fast runs at 10-20 Hz. Both these types of electrical seizures are preferentially generated during slow-wave sleep. Here, we challenge the hypothesis of a subcortical pacemaker that would account for suddenly generalized spike-wave seizures as well as the idea of an exclusive role of synaptic excitation in the generation of paroxysmal depolarizing components, and we focus on three points, based on multiple intracellular and field potential recordings in vivo that are corroborated by some clinical studies: (a) the role of neocortical bursting neurons, especially fast-rhythmic-bursting neurons, and of very fast oscillations (ripples, 80-200 Hz) in seizure initiation; (b) the cortical origin of both these types of electrical paroxysms, the synaptic propagation of seizures from one to other, local and distant, cortical sites, finally reaching the thalamus, where the synchronous cortical firing excites thalamic reticular inhibitory neurons and thus leads to steady hyperpolarization and phasic inhibitory postsynaptic potentials in a majority of thalamocortical neurons, which might explain the obliteration of signals from the external world and the unconsciousness during absence seizures; and (c) the cessation of seizures, whose cellular mechanisms have only begun to be investigated and remain an open avenue for research.

Dynamics of non-convulsive epileptic phenomena modeled by a bistable neuronal network

It is currently believed that the mechanisms underlying spindle oscillations are related to those that generate spike and wave (SW) discharges. The mechanisms of transition between these two types of activity, however, are not well understood. In order to provide more insight into the dynamics of the neuronal networks leading to seizure generation in a rat experimental model of absence epilepsy we developed a computational model of thalamo-cortical circuits based on relevant (patho)physiological data. The model is constructed at the macroscopic level since this approach allows to investigate dynamical properties of the system and the role played by different mechanisms in the process of seizure generation, both at short and long time scales. The main results are the following: (i) SW discharges represent dynamical bifurcations that occur in a bistable neuronal network; (ii) the durations of paroxysmal and normal epochs have exponential distributions, indicating that transitions between these two stable states occur randomly over time with constant probabilities; (iii) the probabilistic nature of the onset of paroxysmal activity implies that it is not possible to predict its occurrence; (iv) the bistable nature of the dynamical system allows that an ictal state may be aborted by a single counter-stimulus.

Interactions between membrane conductances underlying thalamocortical slow-wave oscillations

Neurons of the central nervous system display a broad spectrum of intrinsic electrophysiological properties that are absent in the traditional "integrate-and-fire" model. A network of neurons with these properties interacting through synaptic receptors with many time scales can produce complex patterns of activity that cannot be intuitively predicted. Computational methods, tightly linked to experimental data, provide insights into the dynamics of neural networks. We review this approach for the case of bursting neurons of the thalamus, with a focus on thalamic and thalamocortical slow-wave oscillations. At the single-cell level, intrinsic bursting or oscillations can be explained by interactions between calcium- and voltage-dependent channels. At the network level, the genesis of oscillations, their initiation, propagation, termination, and large-scale synchrony can be explained by interactions between neurons with a variety of intrinsic cellular properties through different types of synaptic receptors. These interactions can be altered by neuromodulators, which can dramatically shift the large-scale behavior of the network, and can also be disrupted in many ways, resulting in pathological patterns of activity, such as seizures. We suggest a coherent framework that accounts for a large body of experimental data at the ion-channel, single-cell, and network levels. This framework suggests physiological roles for the highly synchronized oscillations of slow-wave sleep.

Involvement of the thalamocortical system in epileptic loss of consciousness

Experiments on putative neuronal mechanisms underlying absence seizures as well as clinical observations are critically reviewed for their ability to explain apparent "loss of consciousness." It is argued that the initial defect in absences lies with corticothalamic (CT) neuronal mechanisms responsible for selective attention and/or planning for action, rather than with those establishing either the states or the contents of consciousness. Normally, rich thalamocortical (TC)-CT feedback loops regulate the flow of information to the cortex and help its neurons to organize themselves in discrete assemblies, which through high-frequency (>30 Hz) oscillations bind those distributed processes of the brain that are considered important, so that we are able to focus on what is needed from moment to moment and be aware of this fact. This ability is transiently lost in absence seizures, because large numbers of CT loops are recruited for seconds in much stronger, low-frequency ( approximately 3 Hz) oscillations of EPSP/IPSP sequences, which underlie electroencephalographic (EEG) spike-and-wave discharges (SWDs). These oscillations probably result from a transformation of the normal EEG rhythm of sleep spindles on an abnormal increase of cortical excitability that results in strong activation of inhibitory neurons in the cortex and in nucleus reticularis thalami. The strong general enhancement of CT feedback during SWDs may disallow the discrete feedback, which normally selects specific TC circuits for conscious perception and/or motor reaction. Such a mechanism of SWD generation allows variability in the extent to which different TC sectors are engaged in the SWD activity and thus explains the variable ability of some patients to respond during an absence, depending on the sensory modality examined.

Chaos in the brain: a short review alluding to epilepsy, depression, exercise and lateralization

Electroencephalograms (EEGs) reflect the electrical activity of the brain. Even when they are analyzed from healthy individuals, they manifest chaos in the nervous system. EEGs are likely to be produced by a nonlinear system, since a nonlinear system with at least 3 degrees of freedom (or state variables) may exhibit chaotic behavior. Furthermore, such systems can have multiple stable states governed by "chaotic" ("strange") attractors. A key feature of chaotic systems is the presence of an infinite number of unstable periodic fixed points, which are found in spontaneously active neuronal networks (e.g., epilepsy). The brain has chemicals called neurotransmitters that convey the information through the 10(16) synapses residing there. However, each of these neurotransmitters acts through various receptors and their numerous subtypes, thereby exhibiting complex interactions. Albeit in epilepsy the role of chaos and EEG findings are well proven, in another condition, i.e., depression, the role of chaos is slowly gaining ground. The multifarious roles of exercise, neurotransmitters and (cerebral) hemispheric lateralization, in the case of depression, are also being established. The common point of reference could be nonlinear dynamics. The purpose of this review is to study those nonlinear/chaotic interactions and point towards new theoretical models incorporating the oscillation caused by the same neurotransmitter acting on its different receptor subtypes. This may lead to a better understanding of brain neurodynamics in health and disease.

Impact of network activities on neuronal properties in corticothalamic systems

Data from in vivo and in vitro experiments are discussed to emphasize that synaptic activities in neocortex and thalamus have a decisive impact on intrinsic neuronal properties in intact-brain preparations under anesthesia and even more so during natural states of vigilance. Thus the firing patterns of cortical neuronal types are not inflexible but may change with the level of membrane potential and during periods rich in synaptic activity. The incidences of some cortical cell classes (defined by their responses to depolarizing current pulses) are different in isolated cortical slabs in vivo or in slices maintained in vitro compared with the intact cortex of naturally awake animals. Network activities, which include the actions of generalized modulatory systems, have a profound influence on the membrane potential, apparent input resistance, and backpropagation of action potentials. The analysis of various oscillatory types leads to the conclusion that in the intact brain, there are no "pure" rhythms, generated in simple circuits, but complex wave sequences (consisting of different, low- and fast-frequency oscillations) that result from synaptic interactions in corticocortical and corticothalamic neuronal loops under the control of activating systems arising in the brain stem core or forebrain structures. As an illustration, it is shown that the neocortex governs the synchronization of network or intrinsically generated oscillations in the thalamus. The rhythmic recurrence of spike bursts and spike trains fired by thalamic and cortical neurons during states of decreased vigilance may lead to plasticity processes in neocortical neurons. If these phenomena, which may contribute to the consolidation of memory traces, are not constrained by inhibitory processes, they induce seizures in which the neocortex initiates the paroxysms and controls their thalamic reflection. The results indicate that intact-brain preparations are necessary to investigate global brain functions such as behavioral states of vigilance and paroxysmal activities.

Brainstem activates paroxysmal discharge in human generalized epilepsy

In nine patients with generalized epilepsy of convulsive seizures, the excitability change of the brainstem was evaluated over the course of the interictal paroxysmal discharge (poly spike-and-wave complex, poly SWC). The evaluation was carried out by a sequential analysis of brainstem auditory evoked potentials (BAEPs) before and during one sequence of poly SWC. The characteristics of BAEPs, i.e. far-field evoked potentials, allowed the evaluation of the excitability change in the brainstem, which was not influenced by the cortical activity. The excitability in the ventral brainstem, measured with the parameters of wave-III, showed a biphasic fluctuation (deceleration--acceleration) before the onset of poly SWC (minima at -0.7+/-0.4 s). On the other hand, the excitability in the dorsal brainstem, measured with the parameters of wave-V, showed no significant difference over the course of poly SWC. The results suggest that the biphasic excitability change in the ventral brainstem is conveyed to the cortex through the ascending activating system. The excitability acceleration preceded by deceleration in the ventral brainstem probably synchronizes the cortical activity profoundly enough to produce poly SWC through the activation of intralaminar thalamic neurons.

Corticothalamic resonance, states of vigilance and mentation

During various states of vigilance, brain oscillations are grouped together through reciprocal connections between the neocortex and thalamus. The coherent activity in corticothalamic networks, under the control of brainstem and forebrain modulatory systems, requires investigations in intact-brain animals. During behavioral states associated with brain disconnection from the external world, the large-scale synchronization of low-frequency oscillations is accompanied by the inhibition of synaptic transmission through thalamocortical neurons. Despite the coherent oscillatory activity, on the functional side there is dissociation between the thalamus and neocortex during slow-wave sleep. While dorsal thalamic neurons undergo inhibitory processes due to the prolonged spike-bursts of thalamic reticular neurons, the cortex displays, periodically, a rich spontaneous activity and preserves the capacity to process internally generated signals that dominate the state of sleep. In vivo experiments using simultaneous intracellular recordings from thalamic and cortical neurons show that short-term plasticity processes occur after prolonged and rhythmic spike-bursts fired by thalamic and cortical neurons during slow-wave sleep oscillations. This may serve to support resonant phenomena and reorganize corticothalamic circuitry, determine which synaptic modifications, formed during the waking state, are to be consolidated and generate a peculiar kind of dreaming mentation. In contrast to the long-range coherent oscillations that occur at low frequencies during slow-wave sleep, the sustained fast oscillations that characterize alert states are synchronized over restricted territories and are associated with discrete and differentiated patterns of conscious events.

Spike-and-wave discharges of absence seizures as a transformation of sleep spindles: the continuing development of a hypothesis

OBJECTIVES

This review aims to offer a critical account of recent scientific developments relevant to the hypothesis which Pierre Gloor proposed in the 1970s for the generation of spike and wave discharges (SWDs) of primary generalized absence seizures.

RESULTS

According to this hypothesis SWDs develop in the same circuits, which normally generate sleep spindles, by an initially cortical transformation of one every two or more spindle waves to a 'spike' component of SWDs, while the next one or more spindle waves are eliminated and replaced by a slow negative wave. This hypothesis was based on experiments in feline generalized penicillin epilepsy showing the possibility of transition from spindles to SWDs, when cortical neurons become hyper-responsive to thalamocortical volleys, which normally induce spindles, and thus engage feedback cortical inhibition, rebound excitation, recurrent intracortical dissemination of excitation during the 'spike' and strong excitation of thalamus for further augmentation of a brain wide synchronous oscillation. In the 1980s, electrophysiological studies in vitro and in vivo revealed the basic features of spindle rhythm generation by neurons in nucleus reticularis thalami and thalamocortical-corticothalamic oscillatory reverberations.

CONCLUSIONS

In the light of this knowledge, experimental studies in several genetic and pharmacological animal models of absence seizures, clinical observations and theoretical studies in computer models have considered, tested, modified and challenged this hypothesis. It may still be found useful in the era of dynamic digital EEG analysis of SWDs and its current sources.

Intracellular study of excitability in the seizure-prone neocortex in vivo

The excitability of neocortical neurons from cat association areas 5-7 was investigated during spontaneously occurring seizures with spike-wave (SW) complexes at 2-3 Hz. We tested the antidromic and orthodromic responsiveness of neocortical neurons during the "spike" and "wave" components of SW complexes, and we placed emphasis on the dynamics of excitability changes from sleeplike patterns to seizures. At the resting membrane potential, an overwhelming majority of neurons displayed seizures over a depolarizing envelope. Cortical as well as thalamic stimuli triggered isolated paroxysmal depolarizing shifts (PDSs) that eventually developed into SW seizures. PDSs could also be elicited by cortical or thalamic volleys during the wave-related hyperpolarization of neurons, but not during the spike-related depolarization. The latencies of evoked excitatory postsynaptic potentials (EPSPs) progressively decreased, and their slope and depolarization surface increased, from the control period preceding the seizure to the climax of paroxysm. Before the occurrence of full-blown seizures, thalamic stimuli evoked PDSs arising from the postinhibitory rebound excitation, whereas cortical stimuli triggered PDSs immediately after the early EPSP. These data shed light on the differential excitability of cortical neurons during the spike and wave components of SW seizures, and on the differential effects of cortical and thalamic volleys leading to such paroxysms. We conclude that the wave-related hyperpolarization does not represent GABA-mediated inhibitory postsynaptic potentials (IPSPs), and we suggest that it is a mixture of disfacilitation and Ca(2+)-dependent K(+) currents, similar to the prolonged hyperpolarization of the slow sleep oscillation.

Non-linear analysis of intracranial human EEG in temporal lobe epilepsy

OBJECTIVE

Intracranial EEG recordings from patients suffering from medically intractable temporal lobe epilepsy were analyzed with the aim of characterizing the dynamics of EEG epochs recorded before and during a seizure and comparing the classification of the EEG epochs on the basis of visual inspection to the results of the numerical analysis.

METHODS

The stationarity of the selected EEGs was assessed qualitatively. The coarse-grained correlation dimension and coarse-grained correlation entropy were used for the non-linear characterization of the EEG epochs.

RESULTS

High-pass filtering was necessary in order to make the majority of the epochs appear stationarity beyond a time scale of about 2 s. It was found that the dimension of the ictal EEGs decreased with respect to the epochs containing ongoing (interictal) activity. The entropy of the ictal recordings however increased. A scaling of the entropy was applied and it was found that the scaled entropy of the ictal EEG decreased, consistent with the increased regularity of the ictal EEG. The coarse-grained quantities discriminated well between EEG epochs recorded prior to and during seizures at locations displaying ictal activity and classification improved by including the linear autocorrelation time in the analysis.

CONCLUSIONS

It is concluded that ictal and non-ictal EEG can be well distinguished on the basis of non-linear analysis. The results are in good agreement with the visual analysis.

Brainstem triggers absence seizures in human generalized epilepsy

Simultaneous analysis of brainstem auditory evoked potentials (BAEPs) with reference to electroencephalography (EEG) was designed to examine the brainstem function corresponding to the EEG event. With this method, we investigated the brainstem function pre- and during the paroxysmal discharge in human absence seizures classified as primary generalized epilepsy (PGE). Two types of functional change in the lower brainstem were revealed as parameters of wave-III components (amplitude and area) of BAEPs without significant change in the upper brainstem. One was long-range biphasic fluctuation (acceleration followed by abrupt deceleration with the maximum -6.4+/-3.2 s before the seizure onset), and the other was rhythmic oscillation with 3 Hz. The latter, synchronized with the cortical spike-and-wave complex, imposed on the descending slope of the former. One important point is that both preceded the onset of cortical paroxysmal discharge. The results reappraise the classical hypothesis of "centrencephalic system" on seizure generating mechanism in human PGE. The results prove the primary triggering role of the lower brainstem that is independent of sleep-related synchronizations. The method is applicable to other types of EEG event for the investigation of brainstem involvement.

Common dynamics in temporal lobe seizures and absence seizures

Similarities among the clinical features of complex partial temporal lobe seizures and absence (petit mal) seizures suggest shared underlying mechanisms, but dissimilar electrographic features of the two seizure types have cast doubt on common neuronal substrates. However, visual inspection and traditional approaches to quantitative analysis of the electroencephalogram and electrocorticogram, such as Fourier analysis, may not be appropriate to identify and characterize the highly non-linear mechanisms likely to underlie ictal events. We previously introduced a technique, non-linear autoregressive analysis, that is designed to identify non-linear dynamics in the electroencephalogram [Schiff N. D. et al. (1991) Society of Neuroscience 21st Annual Meeting, 638.6; Schiff N. D. et al. (1995) Biol. Cybern. 72, 519-526, 527-533]. The non-linear autoregressive analysis technique is aimed at describing seizure discharges as a disturbance of synchrony at the level of neuronal circuits. In absence seizures, we showed that non-linear autoregressive analysis revealed a consistent "fingerprint" of these non-linearities in 3/s discharges within and across patients. Here, we investigate the possibility that non-linear autoregressive modeling of seizure records from patients with temporal lobe epilepsy might reveal common circuit mechanisms when compared with the non-linear autoregressive analysis fingerprint of absence seizures. Electrocorticographic records of seizure activity were obtained in four patients who had received subdural grids or strips implanted in preparation for epilepsy surgery. Decomposition of the multichannel data recorded from these patients by principal component analysis revealed that at least three to five independent "generators" were required to model the data from each patient. Non-linear autoregressive analysis of these extracted generators revealed non-linear dynamics in two patients. In both patients, the temporal aspects of these non-linearities were similar to the characteristic non-linearities identified in the non-linear autoregressive analysis fingerprint of absence seizures. In particular, both patients showed a non-linear interaction of signals 90 ms in the past with signals 150 ms in the past. This was the most prominent interaction seen in all patients with absence seizures (typical and atypical). These results suggest that seizures from some patients with temporal lobe epilepsy may share common underlying circuit mechanisms with those of absence seizures. Physiological interpretations of these results are considered and proposed mechanisms are placed into the context of the alterations of consciousness seen in both epilepsies.

The induction of pain: an integrative review

The highly disagreeable sensation of pain results from an extraordinarily complex and interactive series of mechanisms integrated at all levels of the neuroaxis, from the periphery, via the dorsal horn to higher cerebral structures. Pain is usually elicited by the activation of specific nociceptors ('nociceptive pain'). However, it may also result from injury to sensory fibres, or from damage to the CNS itself ('neuropathic pain'). Although acute and subchronic, nociceptive pain fulfils a warning role, chronic and/or severe nociceptive and neuropathic pain is maladaptive. Recent years have seen a progressive unravelling of the neuroanatomical circuits and cellular mechanisms underlying the induction of pain. In addition to familiar inflammatory mediators, such as prostaglandins and bradykinin, potentially-important, pronociceptive roles have been proposed for a variety of 'exotic' species, including protons, ATP, cytokines, neurotrophins (growth factors) and nitric oxide. Further, both in the periphery and in the CNS, non-neuronal glial and immunecompetent cells have been shown to play a modulatory role in the response to inflammation and injury, and in processes modifying nociception. In the dorsal horn of the spinal cord, wherein the primary processing of nociceptive information occurs, N-methyl-D-aspartate receptors are activated by glutamate released from nocisponsive afferent fibres. Their activation plays a key role in the induction of neuronal sensitization, a process underlying prolonged painful states. In addition, upon peripheral nerve injury, a reduction of inhibitory interneurone tone in the dorsal horn exacerbates sensitized states and further enhance nociception. As concerns the transfer of nociceptive information to the brain, several pathways other than the classical spinothalamic tract are of importance: for example, the postsynaptic dorsal column pathway. In discussing the roles of supraspinal structures in pain sensation, differences between its 'discriminative-sensory' and 'affective-cognitive' dimensions should be emphasized. The purpose of the present article is to provide a global account of mechanisms involved in the induction of pain. Particular attention is focused on cellular aspects and on the consequences of peripheral nerve injury. In the first part of the review, neuronal pathways for the transmission of nociceptive information from peripheral nerve terminals to the dorsal horn, and therefrom to higher centres, are outlined. This neuronal framework is then exploited for a consideration of peripheral, spinal and supraspinal mechanisms involved in the induction of pain by stimulation of peripheral nociceptors, by peripheral nerve injury and by damage to the CNS itself. Finally, a hypothesis is forwarded that neurotrophins may play an important role in central, adaptive mechanisms modulating nociception. An improved understanding of the origins of pain should facilitate the development of novel strategies for its more effective treatment.

Spike-and-wave oscillations based on the properties of GABAB receptors

Neocortical and thalamic neurons are involved in the genesis of generalized spike-and-wave (SW) epileptic seizures. The cellular mechanism of SW involves complex interactions between intrinsic neuronal firing properties and multiple types of synaptic receptors, but because of the complexity of these interactions the exact details of this mechanism are unclear. In this paper these types of interactions were investigated by using biophysical models of thalamic and cortical neurons. It is shown first that, because of the particular activation properties of GABAB receptor-mediated responses, simulated field potentials can display SW waveforms if cortical pyramidal cells and interneurons generate prolonged discharges in synchrony, without any other assumptions. Here the "spike" component coincided with the synchronous firing, whereas the "wave" component was generated mostly by slow GABAB-mediated K+ currents. Second, the model suggests that intact thalamic circuits can be forced into a approximately 3 Hz oscillatory mode by corticothalamic feedback. Here again, this property was attributable to the characteristics of GABAB-mediated inhibition. Third, in the thalamocortical system this property can lead to generalized approximately 3 Hz oscillations with SW field potentials. The oscillation consisted of a synchronous prolonged firing in all cell types, interleaved with a approximately 300 msec period of neuronal silence, similar to experimental observations during SW seizures. This model suggests that SW oscillations can arise from thalamocortical loops in which the corticothalamic feedback indirectly evokes GABAB-mediated inhibition in the thalamus. This mechanism is shown to be consistent with a number of different experimental models, and experiments are suggested to test its consistency.

Spike-wave complexes and fast components of cortically generated seizures. IV. Paroxysmal fast runs in cortical and thalamic neurons

In the preceding papers of this series, we have analyzed the cellular patterns and synchronization of neocortical seizures occurring spontaneously or induced by electrical stimulation or cortical infusion of bicuculline under a variety of experimental conditions, including natural states of vigilance in behaving animals and acute preparations under different anesthetics. The seizures consisted of two distinct components: spike-wave (SW) or polyspike-wave (PSW) at 2-3 Hz and fast runs at 10-15 Hz. Because the thalamus is an input source and target of cortical neurons, we investigated here the seizure behavior of thalamic reticular (RE) and thalamocortical (TC) neurons, two major cellular classes that have often been implicated in the generation of paroxysmal episodes. We performed single and dual simultaneous intracellular recordings, in conjunction with multisite field potential and extracellular unit recordings, from neocortical areas and RE and/or dorsal thalamic nuclei under ketamine-xylazine and barbiturate anesthesia. Both components of seizures were analyzed, but emphasis was placed on the fast runs because of their recent investigation at the cellular level. 1) The fast runs occurred at slightly different frequencies and, therefore, were asynchronous in various cortical neuronal pools. Consequently, dorsal thalamic nuclei, although receiving convergent inputs from different neocortical areas involved in seizure, did not express strongly synchronized fast runs. 2) Both RE and TC cells were hyperpolarized during seizure episodes with SW/PSW complexes and relatively depolarized during the fast runs. As known, hyperpolarization of thalamic neurons deinactivates a low-threshold conductance that generates high-frequency spike bursts. Accordingly, RE neurons discharged prolonged high-frequency spike bursts in close time relation with the spiky component of cortical SW/PSW complexes, whereas they fired single action potentials, spike doublets, or triplets during the fast runs. In TC cells, the cortical fast runs were reflected as excitatory postsynaptic potentials appearing after short latencies that were compatible with monosynaptic activation through corticothalamic pathways. 3) The above data suggested the cortical origin of these seizures. To further test this hypothesis, we performed experiments on completely isolated cortical slabs from suprasylvian areas 5 or 7 and demonstrated that electrical stimulation within the slab induces seizures with fast runs and SW/PSW complexes, virtually identical to those elicited in intact-brain animals. The conclusion of all papers in this series is that complex seizure patterns, resembling those described at the electroencephalogram level in different forms of clinical seizures with SW/PSW complexes and, particularly, in the Lennox-Gastaut syndrome of humans, are generated in neocortex. Thalamic neurons reflect cortical events as a function of membrane potential in RE/TC cells and degree of synchronization in cortical neuronal networks.

Spike-wave complexes and fast components of cortically generated seizures. III. Synchronizing mechanisms

The intracortical and thalamocortical synchronization of spontaneously occurring or bicuculline-induced seizures, consisting of spike-wave (SW) or polyspike-wave (PSW) complexes at 2-3 Hz and fast runs at 10-15 Hz, was investigated in cats under ketamine-xylazine anesthesia. We used single and dual simultaneous intracellular recordings from cortical areas 5 and 7, and extracellular recordings of unit firing and field potentials from neocortical areas 5, 7, 17, 18, as well as related thalamic nuclei. The evolution of time delays between paroxysmal depolarizing events in single neurons or neuronal pools recorded from adjacent and distant sites was analyzed by using 1) sequential cross-correlations between field potentials, 2) averaged activities triggered by the spiky component of cortical SW/PSW complexes, and 3) time histograms between neuronal discharges. In all instances, the paroxysmal activities recorded from the dorsal thalamus lagged the onset of seizures in neocortex. The time lags between simultaneously impaled cortical neurons were significantly smaller during SW complexes than during the prior epochs of slow oscillation. During seizures, as during the slow oscillation, the intracortical synchrony was reduced with increased distance between different cortical sites. Dual intracellular recordings showed that, during the same seizure, time lags were not constant and, instead, reflected alternating precession of the recorded foci. After transection between areas 5 and 7, the intracortical synchrony was lost, but corticothalamocortical volleys could partially restore seizure synchrony. These data show that the neocortex leads the thalamus during SW/PSW seizures, that time lags between cortical foci are not static, and that thalamus may assist synchronization of SW/PSW seizures after disconnection of intracortical synaptic linkages.

Spike-wave complexes and fast components of cortically generated seizures. I. Role of neocortex and thalamus

We explored the relative contributions of cortical and thalamic neuronal networks in the generation of electrical seizures that include spike-wave (SW) and polyspike-wave (PSW) complexes. Seizures were induced by systemic or local cortical injections of bicuculline, a gamma-aminobutyric acid-A (GABAA) antagonist, in cats under barbiturate anesthesia. Field potentials and extracellular neuronal discharges were recorded through arrays of eight tungsten electrodes (0.4 or 1 mm apart) placed over the cortical suprasylvian gyrus and within the thalamus. 1) Systemic injections of bicuculline induced SW/PSW seizures in cortex, whereas spindle sequences continued to be present in the thalamus. 2) Cortical suprasylvian injection of bicuculline induced focal paroxysmal single spikes that developed into full-blown seizures throughout the suprasylvian cortex. The seizures were characterized by highly synchronized SW or PSW complexes at 2-4 Hz, interspersed with runs of fast (10-15 Hz) activity. The intracellular aspects of this complex pattern in different types of neocortical neurons are described in the following paper. Complete decortication abolished the seizure, leaving intact thalamic spindles. Injections of bicuculline in the cortex of athalamic cats resulted in similar components as those occurring with an intact thalamus. 3) Injection of bicuculline in the thalamus decreased the frequency of barbiturate spindles and increased the synchrony of spike bursts fired by thalamocortical and thalamic reticular cells but did not induce seizures. Decortication did not modify the effects of bicuculline injection in the thalamus. Our results indicate that the minimal substrate that is necessary for the production of seizures consisting of SW/PSW complexes and runs of fast activity is the neocortex.

Computer models of hippocampal circuit changes of the kindling model of epilepsy

Abnormalities in the organization of brain circuits may underlie many types of epilepsy. This hypothesis can best be evaluated in the case of temporal lobe epilepsy, where evidence of rewiring (synaptic reorganization) can be found in the dentate gyrus. Computer modeling of normal and reorganized dentate gyrus was used to understand the functional consequences of these structural changes. Hyperexcitability appeared to be largely limited by the powerful intrinsic adaptation characteristic of granule cells, the principal cells in this area. Combining disinhibition with new recurrent excitatory circuitry was necessary to produce repeated firing of these cells. Paradoxically, continuing regenerative activity was only seen with a large reduction in the strength of the inciting stimulus. Validation of these findings will require further physiological correlation.

Mechanisms and experimental models of seizure generation

Over the past year evidence has accumulated against the idea that seizures require re-entrant activity between spatially separate structures. Seizures in vivo typically do involve interconnected, spatially separate brain regions, but they often show no net phase lag around the putative circuit. In many cases seizure-like events can arise from localized regions such as the entorhinal cortex or hippocampus proper, through mechanisms that are starting to be identified.