Role of mossy fiber sprouting and mossy cell loss in hyperexcitability: a network model of the dentate gyrus incorporating cell types and axonal topography

Synaptic Plasticity and Excitation-Inhibition Balance in the Dentate Gyrus: Insights from In Vivo Recordings in Neuroligin-1, Neuroligin-2, and Collybistin Knockouts

The hippocampal dentate gyrus plays a role in spatial learning and memory and is thought to encode differences between similar environments. The integrity of excitatory and inhibitory transmission and a fine balance between them is essential for efficient processing of information. Therefore, identification and functional characterization of crucial molecular players at excitatory and inhibitory inputs is critical for understanding the dentate gyrus function. In this minireview, we discuss recent studies unraveling molecular mechanisms of excitatory/inhibitory synaptic transmission, long-term synaptic plasticity, and dentate granule cell excitability in the hippocampus of live animals. We focus on the role of three major postsynaptic proteins localized at excitatory (neuroligin-1) and inhibitory synapses (neuroligin-2 and collybistin). In vivo recordings of field potentials have the advantage of characterizing the effects of the loss of these proteins on the input-output function of granule cells embedded in a network with intact connectivity. The lack of neuroligin-1 leads to deficient synaptic plasticity and reduced excitation but normal granule cell output, suggesting unaltered excitation-inhibition ratio. In contrast, the lack of neuroligin-2 and collybistin reduces inhibition resulting in a shift towards excitation of the dentate circuitry.

Model-Based Analysis of Electrode Placement and Pulse Amplitude for Hippocampal Stimulation

Objective:

The ideal form of a neural-interfacing device is highly dependent upon the anatomy of the region with which it is meant to interface. Multiple-electrode arrays provide a system which can be adapted to various neural geometries. Computational models of stimulating systems have proven useful for evaluating electrode placement and stimulation protocols, but have yet to be adequately adapted to the unique features of the hippocampus.

Methods:

As an approach to understanding potential memory restorative devices, an Admittance Method-NEURON model was constructed to predict the direct and synaptic response of a region of the rat dentate gyrus to electrical stimulation of the perforant path.

Results:

A validation of estimated local field potentials against experimental recordings is performed and results of a bi-linear electrode placement and stimulation amplitude parameter search are presented.

Conclusion:

The parametric analysis presented herein suggests that stimulating electrodes placed between the lateral and medial perforant path, near the crest of the dentate gyrus, yield a larger relative population response to given stimuli.

Significance:

Beyond deepening understanding of the hippocampal tissue system, establishment of this model provides a method to evaluate candidate stimulating devices and protocols.

Excitatory Synaptic Input to Hilar Mossy Cells under Basal and Hyperexcitable Conditions

Hilar mossy cells (HMCs) in the hippocampus receive glutamatergic input from dentate granule cells (DGCs) via mossy fibers (MFs) and back-projections from CA3 pyramidal neuron collateral axons. Many fundamental features of these excitatory synapses have not been characterized in detail despite their potential relevance to hippocampal cognitive processing and epilepsy-induced adaptations in circuit excitability. In this study, we compared pre- and postsynaptic parameters between MF and CA3 inputs to HMCs in young and adult mice of either sex and determined the relative contributions of the respective excitatory inputs during in vitro and in vivo models of hippocampal hyperexcitability. The two types of excitatory synapses both exhibited a modest degree of short-term plasticity, with MF inputs to HMCs exhibiting lower paired-pulse (PP) and frequency facilitation than was described previously for MF–CA3 pyramidal cell synapses. MF–HMC synapses exhibited unitary excitatory synaptic currents (EPSCs) of larger amplitude, contained postsynaptic kainate receptors, and had a lower NMDA/AMPA receptor ratio compared to CA3–HMC synapses. Pharmacological induction of hippocampal hyperexcitability in vitro transformed the abundant but relatively weak CA3–HMC connections to very large amplitude spontaneous bursts of compound EPSCs (cEPSCs) in young mice (∼P20) and, to a lesser degree, in adult mice (∼P70). CA3–HMC cEPSCs were also observed in slices prepared from mice with spontaneous seizures several weeks after intrahippocampal kainate injection. Strong excitation of HMCs during synchronous CA3 activity represents an avenue of significant excitatory network generation back to DGCs and might be important in generating epileptic networks.

Converging early responses to brain injury pave the road to epileptogenesis

Epilepsy, characterized by recurrent seizures and abnormal electrical activity in the brain, is one of the most prevalent brain disorders. Over two million people in the United States have been diagnosed with epilepsy and 3% of the general population will be diagnosed with it at some point in their lives. While most developmental epilepsies occur due to genetic predisposition, a class of "acquired" epilepsies results from a variety of brain insults. A leading etiological factor for epilepsy that is currently on the rise is traumatic brain injury (TBI), which accounts for up to 20% of all symptomatic epilepsies. Remarkably, the presence of an identified early insult that constitutes a risk for development of epilepsy provides a therapeutic window in which the pathological processes associated with brain injury can be manipulated to limit the subsequent development of recurrent seizure activity and epilepsy. Recent studies have revealed diverse pathologies, including enhanced excitability, activated immune signaling, cell death, and enhanced neurogenesis within a week after injury, suggesting a period of heightened adaptive and maladaptive plasticity. An integrated understanding of these processes and their cellular and molecular underpinnings could lead to novel targets to arrest epileptogenesis after trauma. This review attempts to highlight and relate the diverse early changes after trauma and their role in development of epilepsy and suggests potential strategies to limit neurological complications in the injured brain.

T2N as a new tool for robust electrophysiological modeling demonstrated for mature and adult-born dentate granule cells

Compartmental models are the theoretical tool of choice for understanding single neuron computations. However, many models are incomplete, built ad hoc and require tuning for each novel condition rendering them of limited usability. Here, we present T2N, a powerful interface to control NEURON with Matlab and TREES toolbox, which supports generating models stable over a broad range of reconstructed and synthetic morphologies. We illustrate this for a novel, highly detailed active model of dentate granule cells (GCs) replicating a wide palette of experiments from various labs. By implementing known differences in ion channel composition and morphology, our model reproduces data from mouse or rat, mature or adult-born GCs as well as pharmacological interventions and epileptic conditions. This work sets a new benchmark for detailed compartmental modeling. T2N is suitable for creating robust models useful for large-scale networks that could lead to novel predictions. We discuss possible T2N application in degeneracy studies.

Resveratrol for Easing Status Epilepticus Induced Brain Injury, Inflammation, Epileptogenesis, and Cognitive and Memory Dysfunction-Are We There Yet?

Status epilepticus (SE) is a medical emergency exemplified by self-sustaining, unceasing seizures or swiftly recurring seizure events with no recovery between seizures. The early phase after SE event is associated with neurodegeneration, neuroinflammation, and abnormal neurogenesis in the hippocampus though the extent of these changes depends on the severity and duration of seizures. In many instances, over a period, the initial precipitating injury caused by SE leads to temporal lobe epilepsy (TLE), typified by spontaneous recurrent seizures, cognitive, memory and mood impairments associated with chronic inflammation, reduced neurogenesis, abnormal synaptic reorganization, and multiple molecular changes in the hippocampus. While antiepileptic drugs are efficacious for terminating or greatly reducing seizures in most cases of SE, they have proved ineffective for easing SE-induced epileptogenesis and TLE. Despite considerable advances in elucidating SE-induced multiple cellular, electrophysiological, and molecular changes in the brain, efficient strategies that prevent SE-induced TLE development are yet to be discovered. This review critically confers the efficacy and promise of resveratrol, a phytoalexin found in the skin of red grapes, for easing SE-induced neurodegeneration, neuroinflammation, aberrant neurogenesis, and for restraining the evolution of SE-induced brain injury into a chronic epileptic state typified by spontaneous recurrent seizures, and learning, memory, and mood impairments.

Place field detection using grid-based clustering in a large-scale computational model of the rat dentate gyrus

Place cells are neurons in the hippocampus that are sensitive to location within an environment. Simulations of a large-scale, computational model of the rat dentate gyrus using grid cell input have been performed resulting in granule cells that express multiple place fields. The typical method of detecting place fields using a global threshold on this data is unreliable as the characteristics of the place fields from a single neuron can be highly variable. A grid-based implementation of DENCLUE has been developed to calculate local thresholds to identify each place field. An adaptive binning algorithm used to smooth the rate maps was combined with the DENCLUE implementation to adaptively choose the size of the smoothing kernel and reduce the number of free parameters of the total algorithm. A sensitivity analysis was performed using the threshold parameter to demonstrate the robustness of using local thresholds as opposed to using a single global threshold in detecting the place fields resulting from the large-scale simulation. The analysis supports the use of applying local thresholds for place field detection and will be used to further investigate the role of granule cells in hippocampal function.

Interleukin-1 Receptor in Seizure Susceptibility after Traumatic Injury to the Pediatric Brain

Epilepsy after pediatric traumatic brain injury (TBI) is associated with poor quality of life. This study aimed to characterize post-traumatic epilepsy in a mouse model of pediatric brain injury, and to evaluate the role of interleukin-1 (IL-1) signaling as a target for pharmacological intervention. Male mice received a controlled cortical impact or sham surgery at postnatal day 21, approximating a toddler-aged child. Mice were treated acutely with an IL-1 receptor antagonist (IL-1Ra; 100 mg/kg, s.c.) or vehicle. Spontaneous and evoked seizures were evaluated from video-EEG recordings. Behavioral assays tested for functional outcomes, postmortem analyses assessed neuropathology, and brain atrophy was detected by ex vivo magnetic resonance imaging. At 2 weeks and 3 months post-injury, TBI mice showed an elevated seizure response to the convulsant pentylenetetrazol compared with sham mice, associated with abnormal hippocampal mossy fiber sprouting. A robust increase in IL-1β and IL-1 receptor were detected after TBI. IL-1Ra treatment reduced seizure susceptibility 2 weeks after TBI compared with vehicle, and a reduction in hippocampal astrogliosis. In a chronic study, IL-1Ra-TBI mice showed improved spatial memory at 4 months post-injury. At 5 months, most TBI mice exhibited spontaneous seizures during a 7 d video-EEG recording period. At 6 months, IL-1Ra-TBI mice had fewer evoked seizures compared with vehicle controls, coinciding with greater preservation of cortical tissue. Findings demonstrate this model's utility to delineate mechanisms underlying epileptogenesis after pediatric brain injury, and provide evidence of IL-1 signaling as a mediator of post-traumatic astrogliosis and seizure susceptibility.SIGNIFICANCE STATEMENT Epilepsy is a common cause of morbidity after traumatic brain injury in early childhood. However, a limited understanding of how epilepsy develops, particularly in the immature brain, likely contributes to the lack of efficacious treatments. In this preclinical study, we first demonstrate that a mouse model of traumatic injury to the pediatric brain reproduces many neuropathological and seizure-like hallmarks characteristic of epilepsy. Second, we demonstrate that targeting the acute inflammatory response reduces cognitive impairments, the degree of neuropathology, and seizure susceptibility, after pediatric brain injury in mice. These findings provide evidence that inflammatory cytokine signaling is a key process underlying epilepsy development after an acquired brain insult, which represents a feasible therapeutic target to improve quality of life for survivors.

Axonal sprouting in commissurally projecting parvalbumin-expressing interneurons

Previous research has shown that in vivo on-demand optogenetic stimulation of inhibitory interneurons expressing parvalbumin (PV) is sufficient to suppress seizures in a mouse model of temporal lobe epilepsy (TLE). Surprisingly, this intervention was capable of suppressing seizures when PV-expressing interneurons were stimulated ipsilateral or contralateral to the presumed seizure focus, raising the possibility of commissural inhibition in TLE. There are mixed reports regarding commissural PV interneuron projections in the healthy hippocampus, and it was previously unknown whether these connections would be maintained or modified following the network reorganization associated with TLE. Using retrograde labeling and viral vector technology in both sexes and the intrahippocampal kainate mouse model of TLE, we therefore examined these issues. Our results reveal that healthy controls possess a population of commissurally projecting hippocampal PV interneurons. Two weeks post kainate injection, we observed a slight, but not statistically significant decrease in retrogradely labeled PV interneurons in the hippocampus contralateral to kainate and tracer injection. By 6 months post kainate, however, there was a significant increase in retrogradely labeled PV interneurons, suggesting commissural inhibitory axonal sprouting. Using viral green fluorescent protein expression selectively in PV neurons, we demonstrated sprouting of commissural PV projections in the dentate gyrus of the kainate-injected hippocampus 6 months post kainate. These findings indicate that PV interneurons supply direct inhibition to the contralateral hippocampus and undergo sprouting in a mouse model of TLE. © 2017 Wiley Periodicals, Inc.

Inflammation in epileptogenesis after traumatic brain injury

Background

Epilepsy is a common and debilitating consequence of traumatic brain injury (TBI). Seizures contribute to progressive neurodegeneration and poor functional and psychosocial outcomes for TBI survivors, and epilepsy after TBI is often resistant to existing anti-epileptic drugs. The development of post-traumatic epilepsy (PTE) occurs in a complex neurobiological environment characterized by ongoing TBI-induced secondary injury processes. Neuroinflammation is an important secondary injury process, though how it contributes to epileptogenesis, and the development of chronic, spontaneous seizure activity, remains poorly understood. A mechanistic understanding of how inflammation contributes to the development of epilepsy (epileptogenesis) after TBI is important to facilitate the identification of novel therapeutic strategies to reduce or prevent seizures.

Body

We reviewed previous clinical and pre-clinical data to evaluate the hypothesis that inflammation contributes to seizures and epilepsy after TBI. Increasing evidence indicates that neuroinflammation is a common consequence of epileptic seizure activity, and also contributes to epileptogenesis as well as seizure initiation (ictogenesis) and perpetuation. Three key signaling factors implicated in both seizure activity and TBI-induced secondary pathogenesis are highlighted in this review: high-mobility group box protein-1 interacting with toll-like receptors, interleukin-1β interacting with its receptors, and transforming growth factor-β signaling from extravascular albumin. Lastly, we consider age-dependent differences in seizure susceptibility and neuroinflammation as mechanisms which may contribute to a heightened vulnerability to epileptogenesis in young brain-injured patients.

Conclusion

Several inflammatory mediators exhibit epileptogenic and ictogenic properties, acting on glia and neurons both directly and indirectly influence neuronal excitability. Further research is required to establish causality between inflammatory signaling cascades and the development of epilepsy post-TBI, and to evaluate the therapeutic potential of pharmaceuticals targeting inflammatory pathways to prevent or mitigate the development of PTE.

Dendrites of dentate gyrus granule cells contribute to pattern separation by controlling sparsity

The hippocampus plays a key role in pattern separation, the process of transforming similar incoming information to highly dissimilar, nonverlapping representations. Sparse firing granule cells (GCs) in the dentate gyrus (DG) have been proposed to undertake this computation, but little is known about which of their properties influence pattern separation. Dendritic atrophy has been reported in diseases associated with pattern separation deficits, suggesting a possible role for dendrites in this phenomenon. To investigate whether and how the dendrites of GCs contribute to pattern separation, we build a simplified, biologically relevant, computational model of the DG. Our model suggests that the presence of GC dendrites is associated with high pattern separation efficiency while their atrophy leads to increased excitability and performance impairments. These impairments can be rescued by restoring GC sparsity to control levels through various manipulations. We predict that dendrites contribute to pattern separation as a mechanism for controlling sparsity. © 2016 The Authors Hippocampus Published by Wiley Periodicals, Inc.

Interneuronal mechanisms of hippocampal theta oscillations in a full-scale model of the rodent CA1 circuit

The hippocampal theta rhythm plays important roles in information processing; however, the mechanisms of its generation are not well understood. We developed a data-driven, supercomputer-based, full-scale (1:1) model of the rodent CA1 area and studied its interneurons during theta oscillations. Theta rhythm with phase-locked gamma oscillations and phase-preferential discharges of distinct interneuronal types spontaneously emerged from the isolated CA1 circuit without rhythmic inputs. Perturbation experiments identified parvalbumin-expressing interneurons and neurogliaform cells, as well as interneuronal diversity itself, as important factors in theta generation. These simulations reveal new insights into the spatiotemporal organization of the CA1 circuit during theta oscillations.

Interneuronal mechanisms of hippocampal theta oscillations in a full-scale model of the rodent CA1 circuit

The hippocampal theta rhythm plays important roles in information processing; however, the mechanisms of its generation are not well understood. We developed a data-driven, supercomputer-based, full-scale (1:1) model of the rodent CA1 area and studied its interneurons during theta oscillations. Theta rhythm with phase-locked gamma oscillations and phase-preferential discharges of distinct interneuronal types spontaneously emerged from the isolated CA1 circuit without rhythmic inputs. Perturbation experiments identified parvalbumin-expressing interneurons and neurogliaform cells, as well as interneuronal diversity itself, as important factors in theta generation. These simulations reveal new insights into the spatiotemporal organization of the CA1 circuit during theta oscillations.

DOI:http://dx.doi.org/10.7554/eLife.18566.001

Interplay between excitability type and distributions of neuronal connectivity determines neuronal network synchronization

While the interplay between neuronal excitability properties and global properties of network topology is known to affect network propensity for synchronization, it is not clear how detailed characteristics of these properties affect spatiotemporal pattern formation. Here we study mixed networks, composed of neurons having type I and/or type II phase response curves, with varying distributions of local and random connections and show that not only average network properties, but also the connectivity distribution statistics, significantly affect network synchrony. Namely, we study networks with fixed networkwide properties, but vary the number of random connections that nodes project. We show that varying node excitability (type I vs type II) influences network synchrony most dramatically for systems with long-tailed distributions of the number of random connections per node. This indicates that a cluster of even a few highly rewired cells with a high propensity for synchronization can alter the degree of synchrony in the network as a whole. We show this effect generally on a network of coupled Kuramoto oscillators and investigate the impact of this effect more thoroughly in pulse-coupled networks of biophysical neurons.

Callosal dysfunction explains injury sequelae in a computational network model of axonal injury

Mild traumatic brain injury (mTBI) often results in neurobehavioral aberrations such as impaired attention and increased reaction time. Diffusion imaging and postmortem analysis studies suggest that mTBI primarily affects myelinated axons in white matter tracts. In particular, corpus callosum, mediating interhemispheric information exchange, has been shown to be affected in mTBI. Yet little is known about the mechanisms linking the injury of myelinated callosal axons to the neurobehavioral sequelae of mTBI. To address this issue, we devised and studied a large, biologically plausible neuronal network model of cortical tissue. Importantly, the model architecture incorporated intra- and interhemispheric organization, including myelinated callosal axons and distance-dependent axonal conduction delays. In the resting state, the intact model network exhibited several salient features, including alpha-band (8-12 Hz) collective activity with low-frequency irregular spiking of individual neurons. The network model of callosal injury captured several clinical observations, including 1) "slowing down" of the network rhythms, manifested as an increased resting-state theta-to-alpha power ratio, 2) reduced response to attention-like network stimulation, manifested as a reduced spectral power of collective activity, and 3) increased population response time in response to stimulation. Importantly, these changes were positively correlated with injury severity, supporting proposals to use neurobehavioral indices as biomarkers for determining the severity of injury. Our modeling effort helps to understand the role played by the injury of callosal myelinated axons in defining the neurobehavioral sequelae of mTBI.

Dysfunctional epileptic neuronal circuits and dysmorphic dendritic spines are mitigated by platelet-activating factor receptor antagonism

Temporal lobe epilepsy or limbic epilepsy lacks effective therapies due to a void in understanding the cellular and molecular mechanisms that set in motion aberrant neuronal network formations during the course of limbic epileptogenesis (LE). Here we show in in vivo rodent models of LE that the phospholipid mediator platelet-activating factor (PAF) increases in LE and that PAF receptor (PAF-r) ablation mitigates its progression. Synthetic PAF-r antagonists, when administered intraperitoneally in LE, re-establish hippocampal dendritic spine density and prevent formation of dysmorphic dendritic spines. Concomitantly, hippocampal interictal spikes, aberrant oscillations, and neuronal hyper-excitability, evaluated 15–16 weeks after LE using multi-array silicon probe electrodes implanted in the dorsal hippocampus, are reduced in PAF-r antagonist-treated mice. We suggest that over-activation of PAF-r signaling induces aberrant neuronal plasticity in LE and leads to chronic dysfunctional neuronal circuitry that mediates epilepsy.

Spike synchrony generated by modulatory common input through NMDA-type synapses

Common excitatory input to neurons increases their firing rates and the strength of the spike correlation (synchrony) between them. Little is known, however, about the synchronizing effects of modulatory common input. Here, we show that modulatory common input with the slow synaptic kinetics of N-methyl-d-aspartate (NMDA) receptors enhances firing rates and also produces synchrony. Tight synchrony (correlations on the order of milliseconds) always increases with modulatory strength. Unexpectedly, the relationship between strength of modulation and strength of loose synchrony (tens of milliseconds) is not monotonic: The strongest loose synchrony is obtained for intermediate modulatory amplitudes. This finding explains recent neurophysiological results showing that in cortical areas V1 and V2, presumed modulatory top-down input due to contour grouping increases (loose and tight) synchrony but that additional modulatory input due to top-down attention does not change tight synchrony and actually decreases loose synchrony. These neurophysiological findings are understood from our model of integrate-and-fire neurons under the assumption that contour grouping as well as attention lead to additive modulatory common input through NMDA-type synapses. In contrast, circuits with common projections through model α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors did not exhibit the paradoxical decrease of synchrony with increased input. Our results suggest that NMDA receptors play a critical role in top-down response modulation in the visual cortex.

Organization and control of epileptic circuits in temporal lobe epilepsy

When studying the pathological mechanisms of epilepsy, there are a seemingly endless number of approaches from the ultrastructural level-receptor expression by EM-to the behavioral level-comorbid depression in behaving animals. Epilepsy is characterized as a disorder of recurrent seizures, which are defined as "a transient occurrence of signs and/or symptoms due to abnormal excessive or synchronous neuronal activity in the brain" (Fisher et al., 2005). Such abnormal activity typically does not occur in a single isolated neuron; rather, it results from pathological activity in large groups-or circuits-of neurons. Here we choose to focus on two aspects of aberrant circuits in temporal lobe epilepsy: their organization and potential mechanisms to control these pathological circuits. We also look at two scales: microcircuits, ie, the relationship between individual neurons or small groups of similar neurons, and macrocircuits, ie, the organization of large-scale brain regions. We begin by summarizing the large body of literature that describes the stereotypical anatomical changes in the temporal lobe-ie, the anatomical basis of alterations in microcircuitry. We then offer a brief introduction to graph theory and describe how this type of mathematical analysis, in combination with computational neuroscience techniques and using parameters obtained from experimental data, can be used to postulate how microcircuit alterations may lead to seizures. We then zoom out and look at the changes which are seen over large whole-brain networks in patients and animal models, and finally we look to the future.

Role of Sodium Channels in Epilepsy

Voltage-gated sodium channels (VGSCs) are fundamentally important for the generation and coordinated transmission of action potentials throughout the nervous system. It is, therefore, unsurprising that they have been shown to play a central role in the genesis and alleviation of epilepsy. Genetic studies on patients with epilepsy have identified more than 700 mutations among the genes that encode for VGSCs attesting to their role in pathogenesis. Further, many common antiepileptic drugs act on VGSCs to suppress seizure activity. Here, we present an account of the role of VGSCs in epilepsy, both through their pathogenic dysfunction and as targets for pharmacotherapy.

Abnormal UP/DOWN Membrane Potential Dynamics Coupled with the Neocortical Slow Oscillation in Dentate Granule Cells during the Latent Phase of Temporal Lobe Epilepsy

The dentate gyrus, a major entry point to the hippocampus, gates (or filters) incoming information from the cortex. During sleep or anesthesia, the slow-wave oscillation (SWO) orchestrates hippocampus-neocortex communication, which is important for memory formation. The dentate gate is altered in temporal lobe epilepsy (TLE) early during epileptogenesis, which favors the propagation of pathological activities. Yet, whether the gating of physiological SWO by dentate granule cells (DGCs) is altered in TLE has remained unexplored. We combined intracellular recordings of membrane potential (V m) of DGCs and local field potential recordings of the SWO in parietal cortex in anesthetized rats early during epileptogenesis [post-status epilepticus (SE) rats]. As expected, in control rats, the V m of DGCs weakly and rarely oscillated in the SWO frequency range. In contrast, in post-SE rats, the V m of DGCs displayed strong and long-lasting SWO. In these cells, clear UP and DOWN states, in phase with the neocortical SWO, led to a bimodal V m distribution. In post-SE rats, the firing of DGCs was increased and more temporally modulated by the neocortical SWO. We conclude that UP/DOWN state dynamics dominate the V m of DGCs and firing early during epileptogenesis. This abnormally strong neocortical influence on the dynamics of DGCs may profoundly modify the hippocampus-neocortex dialogue during sleep and associated cognitive functions.

Computational Modeling of Adult Neurogenesis

The restriction of adult neurogenesis to only a handful of regions of the brain is suggestive of some shared requirement for this dramatic form of structural plasticity. However, a common driver across neurogenic regions has not yet been identified. Computational studies have been invaluable in providing insight into the functional role of new neurons; however, researchers have typically focused on specific scales ranging from abstract neural networks to specific neural systems, most commonly the dentate gyrus area of the hippocampus. These studies have yielded a number of diverse potential functions for new neurons, ranging from an impact on pattern separation to the incorporation of time into episodic memories to enabling the forgetting of old information. This review will summarize these past computational efforts and discuss whether these proposed theoretical functions can be unified into a common rationale for why neurogenesis is required in these unique neural circuits.

Spines slow down dendritic chloride diffusion and affect short-term ionic plasticity of GABAergic inhibition

Cl⁻ plays a crucial role in neuronal function and synaptic inhibition. However, the impact of neuronal morphology on the diffusion and redistribution of intracellular Cl⁻ is not well understood. The role of spines in Cl⁻ diffusion along dendritic trees has not been addressed so far. Because measuring fast and spatially restricted Cl⁻ changes within dendrites is not yet technically possible, we used computational approaches to predict the effects of spines on Cl⁻ dynamics in morphologically complex dendrites. In all morphologies tested, including dendrites imaged by super-resolution STED microscopy in live brain tissue, spines slowed down longitudinal Cl⁻ diffusion along dendrites. This effect was robust and could be observed in both deterministic as well as stochastic simulations. Cl⁻ extrusion altered Cl⁻ diffusion to a much lesser extent than the presence of spines. The spine-dependent slowing of Cl⁻ diffusion affected the amount and spatial spread of changes in the GABA reversal potential thereby altering homosynaptic as well as heterosynaptic short-term ionic plasticity at GABAergic synapses in dendrites. Altogether, our results suggest a fundamental role of dendritic spines in shaping Cl⁻ diffusion, which could be of relevance in the context of pathological conditions where spine densities and neural excitability are perturbed.

A general homeostatic principle following lesion induced dendritic remodeling

INTRODUCTION

Neuronal death and subsequent denervation of target areas are hallmarks of many neurological disorders. Denervated neurons lose part of their dendritic tree, and are considered "atrophic", i.e. pathologically altered and damaged. The functional consequences of this phenomenon are poorly understood.

RESULTS

Using computational modelling of 3D-reconstructed granule cells we show that denervation-induced dendritic atrophy also subserves homeostatic functions: By shortening their dendritic tree, granule cells compensate for the loss of inputs by a precise adjustment of excitability. As a consequence, surviving afferents are able to activate the cells, thereby allowing information to flow again through the denervated area. In addition, action potentials backpropagating from the soma to the synapses are enhanced specifically in reorganized portions of the dendritic arbor, resulting in their increased synaptic plasticity. These two observations generalize to any given dendritic tree undergoing structural changes.

CONCLUSIONS

Structural homeostatic plasticity, i.e. homeostatic dendritic remodeling, is operating in long-term denervated neurons to achieve functional homeostasis.

Interactions between Inhibitory Interneurons and Excitatory Associational Circuitry in Determining Spatio-Temporal Dynamics of Hippocampal Dentate Granule Cells: A Large-Scale Computational Study

This paper reports on findings from a million-cell granule cell model of the rat dentate gyrus that was used to explore the contributions of local interneuronal and associational circuits to network-level activity. The model contains experimentally derived morphological parameters for granule cells, which each contain approximately 200 compartments, and biophysical parameters for granule cells, basket cells, and mossy cells that were based both on electrophysiological data and previously published models. Synaptic input to cells in the model consisted of glutamatergic AMPA-like EPSPs and GABAergic-like IPSPs from excitatory and inhibitory neurons, respectively. The main source of input to the model was from layer II entorhinal cortical neurons. Network connectivity was constrained by the topography of the system, and was derived from axonal transport studies, which provided details about the spatial spread of axonal terminal fields, as well as how subregions of the medial and lateral entorhinal cortices project to subregions of the dentate gyrus. Results of this study show that strong feedback inhibition from the basket cell population can cause high-frequency rhythmicity in granule cells, while the strength of feedforward inhibition serves to scale the total amount of granule cell activity. Results furthermore show that the topography of local interneuronal circuits can have just as strong an impact on the development of spatio-temporal clusters in the granule cell population as the perforant path topography does, both sharpening existing clusters and introducing new ones with a greater spatial extent. Finally, results show that the interactions between the inhibitory and associational loops can cause high frequency oscillations that are modulated by a low-frequency oscillatory signal. These results serve to further illustrate the importance of topographical constraints on a global signal processing feature of a neural network, while also illustrating how rich spatio-temporal and oscillatory dynamics can evolve from a relatively small number of interacting local circuits.

A Voltage-Based STDP Rule Combined with Fast BCM-Like Metaplasticity Accounts for LTP and Concurrent "Heterosynaptic" LTD in the Dentate Gyrus In Vivo

Long-term potentiation (LTP) and long-term depression (LTD) are widely accepted to be synaptic mechanisms involved in learning and memory. It remains uncertain, however, which particular activity rules are utilized by hippocampal neurons to induce LTP and LTD in behaving animals. Recent experiments in the dentate gyrus of freely moving rats revealed an unexpected pattern of LTP and LTD from high-frequency perforant path stimulation. While 400 Hz theta-burst stimulation (400-TBS) and 400 Hz delta-burst stimulation (400-DBS) elicited substantial LTP of the tetanized medial path input and, concurrently, LTD of the non-tetanized lateral path input, 100 Hz theta-burst stimulation (100-TBS, a normally efficient LTP protocol for in vitro preparations) produced only weak LTP and concurrent LTD. Here we show in a biophysically realistic compartmental granule cell model that this pattern of results can be accounted for by a voltage-based spike-timing-dependent plasticity (STDP) rule combined with a relatively fast Bienenstock-Cooper-Munro (BCM)-like homeostatic metaplasticity rule, all on a background of ongoing spontaneous activity in the input fibers. Our results suggest that, at least for dentate granule cells, the interplay of STDP-BCM plasticity rules and ongoing pre- and postsynaptic background activity determines not only the degree of input-specific LTP elicited by various plasticity-inducing protocols, but also the degree of associated LTD in neighboring non-tetanized inputs, as generated by the ongoing constitutive activity at these synapses.

The vast majority of computational studies that model synaptic plasticity neglect the fact that in vivo neurons exhibit an ongoing spontaneous spiking which affects the dynamics of synaptic changes. Here we study how key components of learning mechanisms in the brain, namely spike timing-dependent plasticity and metaplasticity, interact with spontaneous activity in the input pathways of the neuron. Using biologically realistic simulations we show that ongoing background activity is a key determinant of the degree of long-term potentiation and long-term depression of synaptic transmission between nerve cells in the hippocampus of freely moving animals. This work helps better understand the computational rules which drive synaptic plasticity in vivo.

Microcircuits in Epilepsy: Heterogeneity and Hub Cells in Network Synchronization

Epilepsy is a complex disorder involving neurological alterations that lead to the pathological development of spontaneous, recurrent seizures. For decades, seizures were thought to be largely repetitive, and had been examined at the macrocircuit level using electrophysiological recordings. However, research mapping the dynamics of large neuronal populations has revealed that seizures are not simply recurrent bursts of hypersynchrony. Instead, it is becoming clear that seizures involve a complex interplay of different neurons and circuits. Herein, we will review studies examining microcircuit changes that may underlie network hyperexcitability, discussing observations from network theory, computational modeling, and optogenetics. We will delve into the idea of hub cells as pathological centers for seizure activity, and will explore optogenetics as a novel avenue to target and treat pathological circuits. Finally, we will conclude with a discussion on future directions in the field.

Functional Reduction in Cannabinoid-Sensitive Heterotypic Inhibition of Dentate Basket Cells in Epilepsy: Impact on Network Rhythms

Strong perisomatic inhibition by fast-spiking basket cells (FS-BCs) regulates dentate throughput. Homotypic FS-BC interconnections that support gamma oscillations, and heterotypic inputs from diverse groups of interneurons that receive extensive neurochemical regulation, together, shape FS-BC activity patterns. However, whether seizures precipitate functional changes in inhibitory networks and contribute to abnormal network activity in epilepsy is not known. In the first recordings from dentate interneuronal pairs in a model of temporal lobe epilepsy, we demonstrate that status epilepticus (SE) selectively compromises GABA release at synapses from dentate accommodating interneurons (AC-INs) to FS-BCs, while efficacy of homotypic FS-BC synapses is unaltered. The functional decrease in heterotypic cannabinoid receptor type 1 (CB₁R)-sensitive inhibition of FS-BCs resulted from enhanced baseline GABA_B-mediated suppression of synaptic release after SE. The frequency of CB₁R-sensitive inhibitory synaptic events in FS-BCs was depressed early after SE induction and remained reduced in epileptic rats. In biologically based simulations of heterogeneous inhibitory networks and excitatory-inhibitory cell networks, experimentally identified decrease in reliability of AC-IN to FS-BCs synaptic release reduced theta power and theta-gamma coupling and enhanced gamma coherence. Thus, the experimentally identified functional reduction in heterotypic inhibition of FS-BCs can contribute to compromised network oscillations in epilepsy and could precipitate memory and cognitive co-morbidities.

Future of seizure prediction and intervention: closing the loop

The ultimate goal of epilepsy therapies is to provide seizure control for all patients while eliminating side effects. Improved specificity of intervention through on-demand approaches may overcome many of the limitations of current intervention strategies. This article reviews the progress in seizure prediction and detection, potential new therapies to provide improved specificity, and devices to achieve these ends. Specifically, we discuss (1) potential signal modalities and algorithms for seizure detection and prediction, (2) closed-loop intervention approaches, and (3) hardware for implementing these algorithms and interventions. Seizure prediction and therapies maximize efficacy, whereas minimizing side effects through improved specificity may represent the future of epilepsy treatments.

A computational study on how theta modulated inhibition can account for the long temporal windows in the entorhinal-hippocampal loop

A recent experimental study (Mizuseki, Sirota, Pastalkova, & Buzsaki, 2009) has shown that the temporal delays between population activities in successive entorhinal and hippocampal anatomical stages are longer (about 70-80ms) than expected from axon conduction velocities and passive synaptic integration of feed-forward excitatory inputs. We investigate via computer simulations the mechanisms that give rise to such long temporal delays in the hippocampus structures. A model of the dentate gyrus (DG), CA3 and CA1 microcircuits is presented that uses biophysical representations of the major cell types including granule cells, CA3 and CA1 pyramidal cells (PCs) and six types of interneurons: basket cells (BCs), axo-axonic cells (AACs), bistratified cells (BSCs), oriens lacunosum-moleculare cells (OLMs), mossy cells (MCs) and hilar perforant path associated cells (HC). Inputs to the network came from the entorhinal cortex (EC) (layers 2 and 3) and the medial septum (MS). The model simulates accurately the timing of firing of different hippocampal cells with respect to the theta rhythm. The model shows that the experimentally reported long temporal delays in the DG, CA3 and CA1 hippocampal regions are due to theta modulated somatic and axonic inhibition. The model further predicts that the phase at which the CA1 PCs fire with respect to the theta rhythm is determined primarily by their increased dendritic excitability caused by the decrease of the axial resistance and the A-type K(+) conductance along their dendritic trunk. The model predicted latencies by which the DG, CA3 and CA1 principal cells fire are inline with the experimental evidence. Finally, the model proposes functional roles for the different inhibitory interneurons in the retrieval of the memory pattern by the DG, CA3 and CA1 networks. The model makes a number of predictions, which can be tested experimentally, thus leading to a better understanding of the biophysical computations in the hippocampus.

Topography-dependent spatio-temporal correlations in the entorhinal-dentate-CA3 circuit in a large-scale computational model of the Rat Hippocampus

The correlation due to different topographies was characterized in a large-scale, biologically-realistic, computational model of the rat hippocampus using a spatio-temporal correlation analysis. The effect of the topographical projection between the following subregions of the hippocampus was investigated: the entorhinal to dentate projection, the entorhinal to CA3 projection, and the mossy fiber to CA3 projection. Through this work, analysis was performed on the individual and combined effects of these projections on the activity of the principal neurons of the dentate gyrus and CA3. The simulations show that uncorrelated input transmitted through the entorhinal-to-dentate or entorhinal-to-CA3 projection causes spatio-temporally correlated activity in the principal neurons that manifest as spike clusters. However, if the mossy fiber system provides uncorrelated input to the CA3, then the CA3 activity remains uncorrelated. When considering the transfer of correlation through the dentate, this analysis suggests that the mossy fiber system do not imbue any correlation to the activity as it propagates from the granule cells of the dentate to the CA3. With the spatio-temporal correlation analysis, the influence of each topographical projection on the transfer of correlation can be investigated as additional subregions and neuron types are added to the large-scale model.

A portion of inhibitory neurons in human temporal lobe epilepsy are functionally upregulated: an endogenous mechanism for seizure termination

MAIN PROBLEM

Epilepsy is one of the more common neurological disorders. The medication is often ineffective to the patients suffering from intractable temporal lobe epilepsy (TLE). As their seizures are usually self-terminated, the elucidation of the mechanism underlying endogenous seizure termination will help to find a new strategy for epilepsy treatment. We aim to examine the role of inhibitory interneurons in endogenous seizure termination in TLE patients.

METHODS

Whole-cell recordings were conducted on inhibitory interneurons in seizure-onset cortices of intractable TLE patients and the temporal lobe cortices of nonseizure individuals. The intrinsic property of the inhibitory interneurons and the strength of their GABAergic synaptic outputs were measured. The quantitative data were introduced into the computer-simulated neuronal networks to figure out a role of these inhibitory units in the seizure termination.

RESULTS

In addition to functional downregulation, a portion of inhibitory interneurons in seizure-onset cortices were upregulated in encoding the spikes and controlling their postsynaptic neurons. A patch-like upregulation of inhibitory neurons in the local network facilitated seizure termination. The upregulations of both inhibitory neurons and their output synapses synergistically shortened seizure duration, attenuated seizure strength, and terminated seizure propagation.

CONCLUSION

Automatic seizure termination is likely due to the fact that a portion of the inhibitory neurons and synapses are upregulated in the seizure-onset cortices. This mechanism may create novel therapeutic strategies to treat intractable epilepsy, such as the simultaneous upregulation of cortical inhibitory neurons and their output synapses.

A detailed, conductance-based computer model of intrinsic sensory neurons of the gastrointestinal tract

Intrinsic sensory neurons (ISNs) of the enteric nervous system respond to stimuli such as muscle tension, muscle length, distortion of the mucosa, and the chemical content in the lumen. ISNs form recurrent networks that probably drive many intestinal motor patterns and reflexes. ISNs express a large number of voltage- and calcium-gated ion channels, some of which are modified by inflammation or repeated physiological stimuli, but how interactions between different ionic currents in ISNs produce both normal and pathological behaviors in the intestine remains unclear. We constructed a model of ISNs including voltage-gated sodium and potassium channels, N-type calcium channels, big conductance calcium-dependent potassium (BK) channels, calcium-dependent nonspecific cation channels (NSCa), intermediate conductance calcium-dependent potassium (IK) channels, hyperpolarization-activated cation (Ih) channels, and internal calcium dynamics. The model was based on data from the literature and our electrophysiological studies. The model reproduced responses to short or long depolarizing current pulses and responses to long hyperpolarizing current pulses. Sensitivity analysis showed that Ih, IK, NSCa, and BK have the largest influence on the number of action potentials observed during prolonged depolarizations. The model also predicts that changes to the voltage of activation for Ih have a large influence on excitability, but changes to the time constant of activation for Ih have a minor effect. Our model identifies how interactions between different iconic currents influence the excitability of ISNs and highlights an important role for Ih in enteric neuroplasticity resulting from disease.

Computational models of dentate gyrus with epilepsy-induced morphological alterations in granule cells

Temporal lobe epilepsy provokes a number of different morphological alterations in granule cells of the hippocampus dentate gyrus. These alterations may be associated with the hyperactivity and hypersynchrony found in the epileptic dentate gyrus, and their study requires the use of different kinds of approaches including computational modeling. Conductance-based models of both normal and epilepsy-induced morphologically altered granule cells have been used in the construction of network models of dentate gyrus to study the effects of these alterations on epilepsy. Here, we review these models and discuss their contributions to the understanding of the association between alterations in neuronal morphology and epilepsy in the dentate gyrus.

Specific binding of lacosamide to collapsin response mediator protein 2 (CRMP2) and direct impairment of its canonical function: implications for the therapeutic potential of lacosamide

The novel antiepileptic drug lacosamide (LCM; SPM927, Vimpat®) has been heralded as having a dual-mode of action through interactions with both the voltage-gated sodium channel and the neurite outgrowth-promoting collapsin response mediator protein 2 (CRMP2). Lacosamide's ability to dampen neuronal excitability through the voltage-gated sodium channel likely underlies its efficacy in attenuating the symptoms of epilepsy (i.e., seizures). While the role of CRMP2 in epilepsy has not been well studied, given the proposed involvement of circuit reorganization in epileptogenesis, the ability of lacosamide to alter CRMP2 function may prove disease modifying. Recently, however, the validity of lacosamide's interaction with CRMP2 has come under scrutiny. In this review, we address the contradictory reports concerning the binding of lacosamide to CRMP2 as well as the ability of lacosamide to directly impact CRMP2 function. Additionally, we address similarly the contradicting reports regarding the potential disease-modifying effect of lacosamide on the development and progression of epilepsy. As the vast majority of antiepileptic drugs influences only the symptoms of epilepsy, the ability to hinder disease progression would be a major breakthrough in efforts to cure or prevent this debilitating syndrome.

Combined role of seizure-induced dendritic morphology alterations and spine loss in newborn granule cells with mossy fiber sprouting on the hyperexcitability of a computer model of the dentate gyrus

Temporal lobe epilepsy strongly affects hippocampal dentate gyrus granule cells morphology. These cells exhibit seizure-induced anatomical alterations including mossy fiber sprouting, changes in the apical and basal dendritic tree and suffer substantial dendritic spine loss. The effect of some of these changes on the hyperexcitability of the dentate gyrus has been widely studied. For example, mossy fiber sprouting increases the excitability of the circuit while dendritic spine loss may have the opposite effect. However, the effect of the interplay of these different morphological alterations on the hyperexcitability of the dentate gyrus is still unknown. Here we adapted an existing computational model of the dentate gyrus by replacing the reduced granule cell models with morphologically detailed models coming from three-dimensional reconstructions of mature cells. The model simulates a network with 10% of the mossy fiber sprouting observed in the pilocarpine (PILO) model of epilepsy. Different fractions of the mature granule cell models were replaced by morphologically reconstructed models of newborn dentate granule cells from animals with PILO-induced Status Epilepticus, which have apical dendritic alterations and spine loss, and control animals, which do not have these alterations. This complex arrangement of cells and processes allowed us to study the combined effect of mossy fiber sprouting, altered apical dendritic tree and dendritic spine loss in newborn granule cells on the excitability of the dentate gyrus model. Our simulations suggest that alterations in the apical dendritic tree and dendritic spine loss in newborn granule cells have opposing effects on the excitability of the dentate gyrus after Status Epilepticus. Apical dendritic alterations potentiate the increase of excitability provoked by mossy fiber sprouting while spine loss curtails this increase.

Neurogenesis is currently a well known phenomenon in the adult brain, in special in some areas such as the subventricular zone and the dentate gyrus in the hippocampus, in which different endogenous and exogenous factors provoke cell proliferation. In the specific case of the dentate gyrus, granule cells proliferate exhibiting altered morphology after the induction of Status Epilepticus (SE) by pilocarpine (PILO). Several days after the injury the new cells show different morphological alterations, for example, in dendritic spines and branching patterns, as well as with the formation of axonal sprouting. The way in which these new cells are integrated into the hippocampus is still unknown with conflicting data in the literature. Here we used computer simulation to test if the activity of the dentate gyrus is affected by the presence of different proportions of new cells after PILO-induced SE. Our results show that the specific morphological alterations present in the granule cells in rats with PILO-induced SE may be responsible for increasing (mossy fiber sprouting) or decreasing (spine loss) the activity in the network. The imbalance between these effects may be manifest as an epileptiform network behavior.

Modern concepts of seizure modeling

Seizures are complex phenomena spanning multiple spatial and temporal scales, from ion dynamics to communication between brain regions, from milliseconds (spikes) to days (interseizure intervals). Because of the existence of such multiple scales, the experimental evaluation of the mechanisms underlying the initiation, propagation, and termination of epileptic seizures is a difficult problem. Theoretical models and numerical simulations provide new tools to investigate seizure mechanisms at multiple scales. In this chapter, we review different theoretical approaches and their contributions to our understanding of seizure mechanisms.

Abrupt and gradual transitions between low and hyperexcited firing frequencies in neuronal models with fast synaptic excitation: a comparative study

Hyperexcitability of neuronal networks is one of the hallmarks of epileptic brain seizure generation, and results from a net imbalance between excitation and inhibition that promotes excessive abnormal firing frequencies. The transition between low and high firing frequencies as the levels of recurrent AMPA excitation change can occur either gradually or abruptly. We used modeling, numerical simulations, and dynamical systems tools to investigate the biophysical and dynamic mechanisms that underlie these two identified modes of transition in recurrently connected neurons via AMPA excitation. We compare our results and demonstrate that these two modes of transition are qualitatively different and can be linked to different intrinsic properties of the participating neurons.

Seizure-induced alterations in fast-spiking basket cell GABA currents modulate frequency and coherence of gamma oscillation in network simulations

Gamma frequency oscillations have been proposed to contribute to memory formation and retrieval. Fast-spiking basket cells (FS-BCs) are known to underlie development of gamma oscillations. Fast, high amplitude GABA synapses and gap junctions have been suggested to contribute to gamma oscillations in FS-BC networks. Recently, we identified that, apart from GABAergic synapses, FS-BCs in the hippocampal dentate gyrus have GABAergic currents mediated by extrasynaptic receptors. Our experimental studies demonstrated two specific changes in FS-BC GABA currents following experimental seizures [Yu et al., J. Neurophysiol. 109, 1746 (2013)]: increase in the magnitude of extrasynaptic (tonic) GABA currents and a depolarizing shift in GABA reversal potential (E(GABA)). Here, we use homogeneous networks of a biophysically based model of FS-BCs to examine how the presence of extrasynaptic GABA conductance (g(GABA-extra)) and experimentally identified, seizure-induced changes in g(GABA-extra) and E(GABA) influence network activity. Networks of FS-BCs interconnected by fast GABAergic synapses developed synchronous firing in the dentate gamma frequency range (40-100 Hz). Systematic investigation revealed that the biologically realistic range of 30 to 40 connections between FS-BCs resulted in greater coherence in the gamma frequency range when networks were activated by Poisson-distributed dendritic synaptic inputs rather than by homogeneous somatic current injections, which were balanced for FS-BC firing frequency in unconnected networks. Distance-dependent conduction delay enhanced coherence in networks with 30-40 FS-BC interconnections while inclusion of gap junctional conductance had a modest effect on coherence. In networks activated by somatic current injections resulting in heterogeneous FS-BC firing, increasing g(GABA-extra) reduced the frequency and coherence of FS-BC firing when E(GABA) was shunting (-74 mV), but failed to alter average FS-BC frequency when E(GABA) was depolarizing (-54 mV). When FS-BCs were activated by biologically based dendritic synaptic inputs, enhancing g(GABA-extra) reduced the frequency and coherence of FS-BC firing when E(GABA) was shunting and increased average FS-BC firing when E(GABA) was depolarizing. Shifting E(GABA) from shunting to depolarizing potentials consistently increased network frequency to and above high gamma frequencies (>80 Hz). Since gamma oscillations may contribute to learning and memory processing [Fell et al., Nat. Neurosci. 4, 1259 (2001); Jutras et al., J. Neurosci. 29, 12521 (2009); Wang, Physiol. Rev. 90, 1195 (2010)], our demonstration that network oscillations are modulated by extrasynaptic inhibition in FS-BCs suggests that neuroactive compounds that act on extrasynaptic GABA receptors could impact memory formation by modulating hippocampal gamma oscillations. The simulation results indicate that the depolarized FS-BC GABA reversal, observed after experimental seizures, together with enhanced spillover extrasynaptic GABA currents are likely to promote generation of focal high frequency activity associated with epileptic networks.

Mechanisms of seizure propagation in 2-dimensional centre-surround recurrent networks

Understanding how seizures spread throughout the brain is an important problem in the treatment of epilepsy, especially for implantable devices that aim to avert focal seizures before they spread to, and overwhelm, the rest of the brain. This paper presents an analysis of the speed of propagation in a computational model of seizure-like activity in a 2-dimensional recurrent network of integrate-and-fire neurons containing both excitatory and inhibitory populations and having a difference of Gaussians connectivity structure, an approximation to that observed in cerebral cortex. In the same computational model network, alternative mechanisms are explored in order to simulate the range of seizure-like activity propagation speeds (0.1-100 mm/s) observed in two animal-slice-based models of epilepsy: (1) low extracellular [Formula: see text], which creates excess excitation and (2) introduction of gamma-aminobutyric acid (GABA) antagonists, which reduce inhibition. Moreover, two alternative connection topologies are considered: excitation broader than inhibition, and inhibition broader than excitation. It was found that the empirically observed range of propagation velocities can be obtained for both connection topologies. For the case of the GABA antagonist model simulation, consistent with other studies, it was found that there is an effective threshold in the degree of inhibition below which waves begin to propagate. For the case of the low extracellular [Formula: see text] model simulation, it was found that activity-dependent reductions in inhibition provide a potential explanation for the emergence of slowly propagating waves. This was simulated as a depression of inhibitory synapses, but it may also be achieved by other mechanisms. This work provides a localised network understanding of the propagation of seizures in 2-dimensional centre-surround networks that can be tested empirically.

High-dose rapamycin blocks mossy fiber sprouting but not seizures in a mouse model of temporal lobe epilepsy

PURPOSE

The role of granule cell axon (mossy fiber) sprouting in temporal lobe epileptogenesis is unclear and controversial. Rapamycin suppresses mossy fiber sprouting, but its reported effects on seizure frequency are mixed. The present study used high-dose rapamycin to more completely block mossy fiber sprouting and to measure the effect on seizure frequency.

METHODS

Mice were treated with pilocarpine to induce status epilepticus. Beginning 24 h later and continuing for 2 months, vehicle or rapamycin (10 mg/kg/day) was administered. Starting 1 month after status epilepticus, mice were monitored by video 9 h per day, every day, for 1 month to measure the frequency of spontaneous motor seizures. At the end of seizure monitoring, a subset of mice was prepared for anatomic analysis. Mossy fiber sprouting was measured as the proportion of the granule cell layer and molecular layer that displayed black labeling in Timm-stained sections.

KEY FINDINGS

Extensive mossy fiber sprouting developed in mice that experienced status epilepticus and were treated with vehicle. In rapamycin-treated mice, mossy fiber sprouting was blocked almost to the level of naive controls. Seizure frequency was similar in vehicle-treated and rapamycin-treated mice.

SIGNIFICANCE

These findings suggest that mossy fiber sprouting is not necessary for epileptogenesis in the mouse pilocarpine model. They also reveal that rapamycin does not have antiseizure or antiepileptogenic effects in this model.

Quantitative assessment of CA1 local circuits: knowledge base for interneuron-pyramidal cell connectivity

In this work, through a detailed literature review, data-mining, and extensive calculations, we provide a current, quantitative estimate of the cellular and synaptic constituents of the CA1 region of the rat hippocampus. Beyond estimating the cell numbers of GABAergic interneuron types, we calculate their convergence onto CA1 pyramidal cells and compare it with the known input synapses on CA1 pyramidal cells. The convergence calculation and comparison are also made for excitatory inputs to CA1 pyramidal cells. In addition, we provide a summary of the excitatory and inhibitory convergence onto interneurons. The quantitative knowledge base assembled and synthesized here forms the basis for data-driven, large-scale computational modeling efforts. Additionally, this work highlights specific instances where the available data are incomplete, which should inspire targeted experimental projects toward a more complete quantification of the CA1 neurons and their connectivity.

GABAergic transmission in temporal lobe epilepsy: the role of neurosteroids

Modification of GABAergic inhibition is an intensely investigated hypothesis guiding research into mechanisms underlying temporal lobe epilepsy (TLE). Seizures can be initiated by blocking γ amino butyric acid type A (GABAA receptors, GABARs), which mediate fast synaptic inhibition in the brain, and controlled by drugs that enhance their function. Derivatives of steroid hormones called neurosteroids are natural substances that physiologically enhance GABAR function and suppress seizures. GABAR structure, function, expression, assembly, and pharmacological properties are changed in the hippocampus of epileptic animals. These alterations render GABARs less sensitive to neurosteroid modulation, which may contribute to seizure susceptibility. Plasticity of GABARs could play a role in periodic exacerbation of seizures experienced by women with epilepsy, commonly referred to as catamenial epilepsy.

Network-specific mechanisms may explain the paradoxical effects of carbamazepine and phenytoin

PURPOSE

A common notion of the mechanism by which the antiepileptic drugs (AEDs) carbamazepine and phenytoin act is that they block sodium channels by binding preferentially to the inactivated state, thereby allowing normal neuronal firing while blocking ictal activity. However, these drugs have unpredictable efficacy and, in some cases, may exacerbate seizures. Previous studies have suggested that reducing sodium channel availability in the dentate gyrus (DG) paradoxically increases excitability. We used a biophysically detailed computer model of the DG to test the hypothesis that AEDs increase excitability by disproportionately reducing negative feedback mechanisms.

METHODS

We built a Markov model of sodium channel gating that reproduces responses to voltage clamp experiments in the presence of carbamazepine and phenytoin. We incorporated this validated Markov model into a biophysically realistic computer model of DG neurons and networks. Simulated drug concentrations were similar to those measured in cerebral spinal fluid in medicated patients. Single neuron models were stimulated with current injections, and networks were stimulated with perforant path synaptic input. In the network model, environmental effects were studied by introducing mossy fiber sprouting.

KEY FINDINGS

As expected, drugs reduced sodium channel availability, which in turn reduced action potential amplitude. This had only a small effect on action potential (AP) firing rate during brief (100 msec) current injections. Paradoxically, long current injections (2,500 msec) increased AP firing rates. This was caused by reduced calcium entry and consequently reduced activation of calcium activated potassium channels. It is important to note that the main determinant of drug effect was resting membrane potential (RMP) and not action potential firing rate. Binding of phenytoin and carbamazepine is slow and, thus drug effects are largely determined by the long term state of the RMP. This paradoxical AP firing increase was dependent on the unusually large calcium-activated potassium conductances expressed by DG granule cells. This predicts that drug efficacy in a given network will depend on the precise makeup of conductances in the network. RMP is expected to vary with the level of activity in the network. We simulated the effects of drugs on single shot stimulus responses in networks with mossy fiber sprouting and varied the RMP in all neurons as a model for network activity. For an RMP of -50 mV, representing an active network, drugs had no effect, or in some cases, increased excitability. Drugs had an increasingly larger inhibitory effect on network responses as RMP decreased. An important prediction is that drugs will be unable to block ictal activity invading an active network.

SIGNIFICANCE

Our key findings are that drug effects depend on both intrinsic properties of the network and its behavioral state. This may explain the paradoxical and unpredictable effects of some AEDs on seizure control in some patients.

The epilepsies: complex challenges needing complex solutions

It is widely accepted that epilepsies are complex syndromes due to their multi-factorial origins and manifestations. Different mathematical and computational descriptions use appropriate methods to address nonlinear relationships, chaotic behaviors and emergent properties. These theoretical approaches can be divided into two major categories: descriptive, such as flowcharts, graphs and other statistical analyses, and explicative, which include both realistic and abstract models. Although these modeling tools have brought great advances, a common framework to guide their design, implementation and evaluation, with the goal of future integration, is still needed. In the current review, we discuss two examples of complexity analysis that can be performed with epilepsy data: behavioral sequences of temporal lobe seizures and alterations in an experimental cellular model. We also highlight the importance of the creation of model repositories for the epileptology field and encourage the development of mathematical descriptions of complex systems, together with more accurate simulation techniques.

Spatially clustered neuronal assemblies comprise the microstructure of synchrony in chronically epileptic networks

Epilepsy is characterized by recurrent synchronizations of neuronal activity, which are both a cardinal clinical symptom and a debilitating phenomenon. Although the temporal dynamics of epileptiform synchronizations are well described at the macroscopic level using electrophysiological approaches, less is known about how spatially distributed microcircuits contribute to these events. It is important to understand the relationship between micro and macro network activity because the various mechanisms proposed to underlie the generation of such pathological dynamics are united by the assumption that epileptic activity is recurrent and hypersynchronous across multiple scales. However, quantitative analyses of epileptiform spatial dynamics with cellular resolution have been hampered by the difficulty of simultaneously recording from multiple neurons in lesioned, adult brain tissue. We have overcome this experimental limitation and used two-photon calcium imaging in combination with a functional clustering algorithm to uncover the functional network structure of the chronically epileptic dentate gyrus in the mouse pilocarpine model of temporal lobe epilepsy. We show that, under hyperexcitable conditions, slices from the epileptic dentate gyrus display recurrent interictal-like network events with a high diversity in the activity patterns of individual neurons. Analysis reveals that multiple functional clusters of spatially localized neurons comprise epileptic networks, and that network events are composed of the coactivation of variable subsets of these clusters, which show little repetition between events. Thus, these interictal-like recurrent macroscopic events are not necessarily recurrent when viewed at the microcircuit scale and instead display a patterned but variable structure.