Homeostatic synaptic plasticity can explain post-traumatic epileptogenesis in chronically isolated neocortex

Understanding epileptogenesis from molecules to network alteration

Epilepsy is characterized by recurrent seizures. Following an initial insult, a latent period precedes the onset of spontaneous seizures, a process referred to as epileptogenesis. This period plays a critical role in halting the progression toward epilepsy before the onset of abnormal molecular and network alterations. In this study, the fundamental concepts of epileptogenesis as well as the associated molecular and cellular targets are reviewed.

Progressive Circuit Hyperexcitability in Mouse Neocortical Slice Cultures with Increasing Duration of Activity Silencing

Forebrain neurons deprived of activity become hyperactive when activity is restored. Rebound activity has been linked to spontaneous seizures in vivo following prolonged activity blockade. Here, we measured the time course of rebound activity and the contributing circuit mechanisms using calcium imaging, synaptic staining, and whole-cell patch clamp in organotypic slice cultures of mouse neocortex. Calcium imaging revealed hypersynchronous activity increasing in intensity with longer periods of deprivation. While activity partially recovered 3 d after slices were released from 5 d of deprivation, they were less able to recover after 10 d of deprivation. However, even after the longer period of deprivation, activity patterns eventually returned to baseline levels. The degree of deprivation-induced rebound was age-dependent, with the greatest effects occurring when silencing began in the second week. Pharmacological blockade of NMDA receptors indicated that hypersynchronous rebound activity did not require activation of Hebbian plasticity. In single-neuron recordings, input resistance roughly doubled with a concomitant increase in intrinsic excitability. Synaptic imaging of pre- and postsynaptic proteins revealed dramatic reductions in the number of presumptive synapses with a larger effect on inhibitory than excitatory synapses. Putative excitatory synapses colocalizing PSD-95 and Bassoon declined by 39 and 56% following 5 and 10 d of deprivation, but presumptive inhibitory synapses colocalizing gephyrin and VGAT declined by 55 and 73%, respectively. The results suggest that with prolonged deprivation, a progressive reduction in synapse number is accompanied by a shift in the balance between excitation and inhibition and increased cellular excitability.

Hidden hearing loss: Fifteen years at a glance

Hearing loss affects approximately 18% of the population worldwide. Hearing difficulties in noisy environments without accompanying audiometric threshold shifts likely affect an even larger percentage of the global population. One of the potential causes of hidden hearing loss is cochlear synaptopathy, the loss of synapses between inner hair cells (IHC) and auditory nerve fibers (ANF). These synapses are the most vulnerable structures in the cochlea to noise exposure or aging. The loss of synapses causes auditory deafferentation, i.e., the loss of auditory afferent information, whose downstream effect is the loss of information that is sent to higher-order auditory processing stages. Understanding the physiological and perceptual effects of this early auditory deafferentation might inform interventions to prevent later, more severe hearing loss. In the past decade, a large body of work has been devoted to better understand hidden hearing loss, including the causes of hidden hearing loss, their corresponding impact on the auditory pathway, and the use of auditory physiological measures for clinical diagnosis of auditory deafferentation. This review synthesizes the findings from studies in humans and animals to answer some of the key questions in the field, and it points to gaps in knowledge that warrant more investigation. Specifically, recent studies suggest that some electrophysiological measures have the potential to function as indicators of hidden hearing loss in humans, but more research is needed for these measures to be included as part of a clinical test battery.

VX-765 Alleviates Circadian Rhythm Disorder in a Rodent Model of Traumatic Brain Injury Plus Hemorrhagic Shock and Resuscitation

Severe traumatic brain injury (TBI) can result in persistent complications, including circadian rhythm disorder, that substantially affect not only the injured people, but also the mood and social interactions with the family and the community. Pyroptosis in GFAP-positive astrocytes plays a vital role in inflammatory changes post-TBI. We determined whether VX-765, a low molecular weight caspase-1 inhibitor, has potential therapeutic value against astrocytic inflammation and pyroptosis in a rodent model of TBI plus hemorrhagic shock and resuscitation (HSR). A weight-drop plus bleeding and refusion model was used to establish traumatic exposure in rats. VX-765 (50 mg/kg) was injected via the femoral vein after resuscitation. Wheel-running activity was assessed, brain magnetic resonance images were evaluated, the expression of pyroptosis-associated molecules including cleaved caspase-1, gasdermin D (GSDMD), and interleukin-18 (IL-18) in astrocytes in the region of anterior hypothalamus, were explored 30 days post-trauma. VX-765-treated rats had significant improvement in circadian rhythm disorder, decreased mean diffusivity (MD) and mean kurtosis (MK), increased fractional anisotropy (FA), an elevated number and branches of astrocytes, and lower cleaved caspase-1, GSDMD, and IL-18 expression in astrocytes than TBI + HSR-treated rats. These results demonstrated that inhibition of pyroptosis-associated astrocytic activations in the anterior hypothalamus using VX-765 may ameliorate circadian rhythm disorder after trauma. In conclusion, we suggest that interventions targeting caspase-1-induced astrocytic pyroptosis by VX-765 are promising strategies to alleviate circadian rhythm disorder post-TBI.

Self-limited childhood epilepsies are disorders of the perisylvian communication system, carrying the risk of progress to epileptic encephalopathies-Critical review

"Sleep plasticity is a double-edged sword: a powerful machinery of neural build-up, with a risk to epileptic derailment." We aimed to review the types of self-limited focal epilepsies..."i.e. keep as two separate paragraphs" We aimed to review the types of self-limited focal epilepsies: (1) self-limited focal childhood epilepsy with centrotemporal spikes, (2) atypical Rolandic epilepsy, and (3) electrical status epilepticus in sleep with mental consequences, including Landau-Kleffner-type acquired aphasia, showing their spectral relationship and discussing the debated topics. Our endeavor is to support the system epilepsy concept in this group of epilepsies, using them as models for epileptogenesis in general. The spectral continuity of the involved conditions is evidenced by several features: language impairment, the overarching presence of centrotemporal spikes and ripples (with changing electromorphology across the spectrum), the essential timely and spatial independence of interictal epileptic discharges from seizures, NREM sleep relatedness, and the existence of the intermediate-severity "atypical" forms. These epilepsies might be the consequences of a genetically determined transitory developmental failure, reflected by widespread neuropsychological symptoms originating from the perisylvian network that have distinct time and space relations from secondary epilepsy itself. The involved epilepsies carry the risk of progression to severe, potentially irreversible encephalopathic forms.

Modelling homeostatic plasticity in the auditory cortex results in neural signatures of tinnitus

Tinnitus is a clinical condition where a sound is perceived without an external sound source. Homeostatic plasticity (HSP), serving to increase neural activity as compensation for the reduced input to the auditory pathway after hearing loss, has been proposed as a mechanism underlying tinnitus. In support, animal models of tinnitus show evidence of increased neural activity after hearing loss, including increased spontaneous and sound-driven firing rate, as well as increased neural noise throughout the auditory processing pathway. Bridging these findings to human tinnitus, however, has proven to be challenging. Here we implement hearing loss-induced HSP in a Wilson-Cowan Cortical Model of the auditory cortex to predict how homeostatic principles operating at the microscale translate to the meso- to macroscale accessible through human neuroimaging. We observed HSP-induced response changes in the model that were previously proposed as neural signatures of tinnitus, but that have also been reported as correlates of hearing loss and hyperacusis. As expected, HSP increased spontaneous and sound-driven responsiveness in hearing-loss affected frequency channels of the model. We furthermore observed evidence of increased neural noise and the appearance of spatiotemporal modulations in neural activity, which we discuss in light of recent human neuroimaging findings. Our computational model makes quantitative predictions that require experimental validation, and may thereby serve as the basis of future human studies of hearing loss, tinnitus, and hyperacusis.

Putative roles for homeostatic plasticity in epileptogenesis

Homeostatic plasticity allows neural circuits to maintain an average activity level while preserving the ability to learn new associations and efficiently transmit information. This dynamic process usually protects the brain from excessive activity, like seizures. However, in certain contexts, homeostatic plasticity might produce seizures, either in response to an acute provocation or more chronically as a driver of epileptogenesis. Here, we review three seizure conditions in which homeostatic plasticity likely plays an important role: acute drug withdrawal seizures, posttraumatic or disconnection epilepsy, and cyclic seizures. Identifying the homeostatic mechanisms active at different stages of development and in different circuits could allow better targeting of therapies, including determining when neuromodulation might be most effective, proposing ways to prevent epileptogenesis, and determining how to disrupt the cycle of recurring seizure clusters.

Synaptic Integration in CA1 Pyramidal Neurons Is Intact despite Deficits in GABAergic Transmission in the Scn1a Haploinsufficiency Mouse Model of Dravet Syndrome

Mutations of SCN1A, which encodes the voltage-gated sodium channel Nav1.1, can cause epilepsy disorders such as Dravet syndrome (DS) that are comorbid with wide-ranging neurologic dysfunction. Many studies suggest that Nav1.1 haploinsufficiency causes forebrain GABAergic interneuron hypoexcitability, while pyramidal neuron physiology is mostly unaltered, and that this serves as a primary cell physiology phenotype linking mutation to disease. We hypothesized that deficits in inhibition would alter synaptic integration during activation of the hippocampal microcircuit, thus disrupting cellular information processing and leading to seizures and cognitive deficits. We tested this hypothesis using ex vivo whole-cell recordings from CA1 pyramidal neurons in a heterozygous Scn1a knock-out mouse model and wild-type (WT) littermates, measuring responses to single and patterned synaptic stimulation and spontaneous synaptic activity. Overall, our experiments reveal a surprising normalcy of excitatory and inhibitory synaptic temporal integration in the hippocampus of Scn1a haploinsufficient mice. While miniature IPSCs and feedforward inhibition and were decreased, we did not identify a pattern or frequency of input that caused a failure of synaptic inhibition. We further show that reduced GABA release probability and subsequent reduced short-term depression may act to overcome deficits in inhibition normalizing input/output functions in the Scn1a haploinsufficient hippocampus. These experiments show that CA1 pyramidal neuron synaptic processing is surprisingly robust, even during decreased interneuron function, and more complex circuit activity is likely required to reveal altered function in the hippocampal microcircuit.

Heterogeneous CaMKII-Dependent Synaptic Compensations in CA1 Pyramidal Neurons From Acute Hippocampal Slices

Prolonged changes in neural activity trigger homeostatic synaptic plasticity (HSP) allowing neuronal networks to operate within functional ranges. Cell-wide or input-specific adaptations can be induced by pharmacological or genetic manipulations of activity, and by sensory deprivation. Reactive functional changes caused by deafferentation may partially share mechanisms with HSP. Acute hippocampal slices are a suitable model to investigate relatively rapid (hours) modifications occurring after denervation and explore the underlying mechanisms. As during slicing many afferents are cut, we conducted whole-cell recordings of miniature excitatory postsynaptic currents (mEPSCs) in CA1 pyramidal neurons to evaluate changes over the following 12 h. As Schaffer collaterals constitute a major glutamatergic input to these neurons, we also dissected CA3. We observed an average increment in mEPSCs amplitude and a decrease in decay time, suggesting synaptic AMPA receptor upregulation and subunit content modifications. Sorting mEPSC by rise time, a correlate of synapse location along dendrites, revealed amplitude raises at two separate domains. A specific frequency increase was observed in the same domains and was accompanied by a global, unspecific raise. Amplitude and frequency increments were lower at sites initially more active, consistent with local compensatory processes. Transient preincubation with a specific Ca2+/calmodulin-dependent kinase II (CaMKII) inhibitor either blocked or occluded amplitude and frequency upregulation in different synapse populations. Results are consistent with the concurrent development of different known CaMKII-dependent HSP processes. Our observations support that deafferentation causes rapid and diverse compensations resembling classical slow forms of adaptation to inactivity. These results may contribute to understand fast-developing homeostatic or pathological events after brain injury.

A feedback control principle common to several biological and engineered systems

Feedback control is used by many distributed systems to optimize behaviour. Traditional feedback control algorithms spend significant resources to constantly sense and stabilize a continuous control variable of interest, such as vehicle speed for implementing cruise control, or body temperature for maintaining homeostasis. By contrast, discrete-event feedback (e.g. a server acknowledging when data are successfully transmitted, or a brief antennal interaction when an ant returns to the nest after successful foraging) can reduce costs associated with monitoring a continuous variable; however, optimizing behaviour in this setting requires alternative strategies. Here, we studied parallels between discrete-event feedback control strategies in biological and engineered systems. We found that two common engineering rules-additive-increase, upon positive feedback, and multiplicative-decrease, upon negative feedback, and multiplicative-increase multiplicative-decrease-are used by diverse biological systems, including for regulating foraging by harvester ant colonies, for maintaining cell-size homeostasis, and for synaptic learning and adaptation in neural circuits. These rules support several goals of these systems, including optimizing efficiency (i.e. using all available resources); splitting resources fairly among cooperating agents, or conversely, acquiring resources quickly among competing agents; and minimizing the latency of responses, especially when conditions change. We hypothesize that theoretical frameworks from distributed computing may offer new ways to analyse adaptation behaviour of biology systems, and in return, biological strategies may inspire new algorithms for discrete-event feedback control in engineering.

A Correspondence Between Normalization Strategies in Artificial and Biological Neural Networks

A fundamental challenge at the interface of machine learning and neuroscience is to uncover computational principles that are shared between artificial and biological neural networks. In deep learning, normalization methods such as batch normalization, weight normalization, and their many variants help to stabilize hidden unit activity and accelerate network training, and these methods have been called one of the most important recent innovations for optimizing deep networks. In the brain, homeostatic plasticity represents a set of mechanisms that also stabilize and normalize network activity to lie within certain ranges, and these mechanisms are critical for maintaining normal brain function. In this article, we discuss parallels between artificial and biological normalization methods at four spatial scales: normalization of a single neuron's activity, normalization of synaptic weights of a neuron, normalization of a layer of neurons, and normalization of a network of neurons. We argue that both types of methods are functionally equivalent-that is, both push activation patterns of hidden units toward a homeostatic state, where all neurons are equally used-and we argue that such representations can improve coding capacity, discrimination, and regularization. As a proof of concept, we develop an algorithm, inspired by a neural normalization technique called synaptic scaling, and show that this algorithm performs competitively against existing normalization methods on several data sets. Overall, we hope this bidirectional connection will inspire neuroscientists and machine learners in three ways: to uncover new normalization algorithms based on established neurobiological principles; to help quantify the trade-offs of different homeostatic plasticity mechanisms used in the brain; and to offer insights about how stability may not hinder, but may actually promote, plasticity.

Neurodegeneration exposes firing rate dependent effects on oscillation dynamics in computational neural networks

Traumatic brain injury (TBI) can lead to neurodegeneration in the injured circuitry, either through primary structural damage to the neuron or secondary effects that disrupt key cellular processes. Moreover, traumatic injuries can preferentially impact subpopulations of neurons, but the functional network effects of these targeted degeneration profiles remain unclear. Although isolating the consequences of complex injury dynamics and long-term recovery of the circuit can be difficult to control experimentally, computational networks can be a powerful tool to analyze the consequences of injury. Here, we use the Izhikevich spiking neuron model to create networks representative of cortical tissue. After an initial settling period with spike-timing-dependent plasticity (STDP), networks developed rhythmic oscillations similar to those seen in vivo. As neurons were sequentially removed from the network, population activity rate and oscillation dynamics were significantly reduced. In a successive period of network restructuring with STDP, network activity levels returned to baseline for some injury levels and oscillation dynamics significantly improved. We next explored the role that specific neurons have in the creation and termination of oscillation dynamics. We determined that oscillations initiate from activation of low firing rate neurons with limited structural inputs. To terminate oscillations, high activity excitatory neurons with strong input connectivity activate downstream inhibitory circuitry. Finally, we confirm the excitatory neuron population role through targeted neurodegeneration. These results suggest targeted neurodegeneration can play a key role in the oscillation dynamics after injury.

Sleep and Epilepsy Link by Plasticity

We aimed to explore the link between NREM sleep and epilepsy. Based on human and experimental data we propose that a sleep-related epileptic transformation of normal neurological networks underlies epileptogenesis. Major childhood epilepsies as medial temporal lobe epilepsy (MTLE), absence epilepsy (AE) and human perisylvian network (PN) epilepsies - made us good models to study. These conditions come from an epileptic transformation of the affected functional systems. This approach allows a system-based taxonomy instead of the outworn generalized-focal classification. MTLE links to the memory-system, where epileptic transformation results in a switch of normal sharp wave-ripples to epileptic spikes and pathological high frequency oscillations, compromising sleep-related memory consolidation. Absence epilepsy (AE) and juvenile myoclonic epilepsy (JME) belong to the corticothalamic system. The burst-firing mode of NREM sleep normally producing sleep-spindles turns to an epileptic working mode ejecting bilateral synchronous spike-waves. There seems to be a progressive transition from AE to JME. Shared absences and similar bilateral synchronous discharges show the belonging of the two conditions, while the continuous age windows - AE affecting schoolchildren, JME the adolescents - and the increased excitability in JME compared to AE supports the notion of progression. In perisylvian network epilepsies - idiopathic focal childhood epilepsies and electrical status epilepticus in sleep including Landau-Kleffner syndrome - centrotemporal spikes turn epileptic, with the potential to cause cognitive impairment. Postinjury epilepsies modeled by the isolated cortex model highlight the shared way of epileptogenesis suggesting the derailment of NREM sleep-related homeostatic plasticity as a common step. NREM sleep provides templates for plasticity derailing to epileptic variants under proper conditions. This sleep-origin explains epileptiform discharges' link and similarity with NREM sleep slow oscillations, spindles and ripples. Normal synaptic plasticity erroneously overgrowing homeostatic processes may derail toward an epileptic working-mode manifesting the involved system's features. The impact of NREM sleep is unclear in epileptogenesis occurring in adolescence and adulthood, when plasticity is lower. The epileptic process interferes with homeostatic synaptic plasticity and may cause cognitive impairment. Its type and degree depends on the affected network's function. We hypothesize a vicious circle between sleep end epilepsy. The epileptic derailment of normal plasticity interferes with sleep cognitive functions. Sleep and epilepsy interconnect by the pathology of plasticity.

Homeostatic Plasticity in Epilepsy

In the healthy brain, neuronal excitability and synaptic strength are homeostatically regulated to keep neuronal network activity within physiological boundaries. Epilepsy is characterized by episodes of highly synchronized firing across in widespread neuronal populations, due to a failure in regulation of network activity. Here we consider epilepsy as a failure of homeostatic plasticity or as a maladaptive response to perturbations in the activity. How homeostatic compensation is involved in epileptogenic processes or in the chronic phase of epilepsy, is still debated. Although several theories have been proposed, there is relatively little experimental evidence to evaluate them. In this perspective, we will discuss recent results that shed light on the potential role of homeostatic plasticity in epilepsy. First, we will present some recent insights on how homeostatic compensations are probably active before and during epileptogenesis and how their actions are temporally regulated and closely dependent on the progression of pathology. Then, we will consider the dual role of transcriptional regulation during epileptogenesis, and finally, we will underline the importance of homeostatic plasticity in the context of therapeutic interventions for epilepsy. While classic pharmacological interventions may be counteracted by the epileptic brain to maintain its potentially dysfunctional set point, novel therapeutic approaches may provide the neuronal network with the tools necessary to restore its physiological balance.

Homeostatic activity regulation as a mechanism underlying the effect of brain stimulation

Hyperexcitability of the neural network often occurs after brain injuries or degeneration and is a key pathophysiological feature in certain neurological diseases such as epilepsy, neuropathic pain, and tinnitus. Although the standard approach of pharmacological treatments is to directly suppress the hyperexcitability through reducing excitation or enhancing inhibition, different techniques for stimulating brain activity are often used to treat refractory neurological conditions. However, it is unclear why stimulating brain activity would be effective for controlling hyperexcitability. Recent studies suggest that the pathogenesis in these disorders exhibits a transition from an initial activity loss after acute injury or progressive neurodegeneration to subsequent development of hyperexcitability. This process mimics homeostatic activity regulation and may contribute to developing network hyperexcitability that underlies neurological symptoms. This hypothesis also predicts that stimulating brain activity should be effective in reducing hyperexcitability due to homeostatic activity regulation and in relieving symptoms. Here we review current evidence of homeostatic plasticity in the development of hyperexcitability in some neurological diseases and the effects of brain stimulation. The homeostatic plasticity hypothesis may provide new insights into the pathophysiology of neurological diseases and may guide the use of brain stimulation techniques for treating them.

Ionic and synaptic mechanisms of seizure generation and epileptogenesis

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

Cortical stimulation for treatment of neurological disorders of hyperexcitability: a role of homeostatic plasticity

Hyperexcitability of neural network is a key neurophysiological mechanism in several neurological disorders including epilepsy, neuropathic pain, and tinnitus. Although standard paradigm of pharmacological management of them is to suppress this hyperexcitability, such as having been exemplified by the use of certain antiepileptic drugs, their frequent refractoriness to drug treatment suggests likely different pathophysiological mechanism. Because the pathogenesis in these disorders exhibits a transition from an initial activity loss after injury or sensory deprivation to subsequent hyperexcitability and paroxysmal discharges, this process can be regarded as a process of functional compensation similar to homeostatic plasticity regulation, in which a set level of activity in neural network is maintained after injury-induced activity loss through enhanced network excitability. Enhancing brain activity, such as cortical stimulation that is found to be effective in relieving symptoms of these disorders, may reduce such hyperexcitability through homeostatic plasticity mechanism. Here we review current evidence of homeostatic plasticity in the mechanism of acquired epilepsy, neuropathic pain, and tinnitus and the effects and mechanism of cortical stimulation. Establishing a role of homeostatic plasticity in these disorders may provide a theoretical basis on their pathogenesis as well as guide the development and application of therapeutic approaches through electrically or pharmacologically stimulating brain activity for treating these disorders.

Gabapentin Prevents Progressive Increases in Excitatory Connectivity and Epileptogenesis Following Neocortical Trauma

Neocortical injury initiates a cascade of events, some of which result in maladaptive epileptogenic reorganization of surviving neural circuits. Research focused on molecular and organizational changes that occur following trauma may reveal processes that underlie human post-traumatic epilepsy (PTE), a common and unfortunate consequence of traumatic brain injury. The latency between injury and development of PTE provides an opportunity for prophylactic intervention, once the key underlying mechanisms are understood. In rodent neocortex, injury to pyramidal neurons promotes axonal sprouting, resulting in increased excitatory circuitry that is one important factor promoting epileptogenesis. We used laser-scanning photostimulation of caged glutamate and whole-cell recordings in in vitro slices from injured neocortex to assess formation of new excitatory synapses, a process known to rely on astrocyte-secreted thrombospondins (TSPs), and to map the distribution of maladaptive circuit reorganization. We show that this reorganization is centered principally in layer V and associated with development of epileptiform activity. Short-term blockade of the synaptogenic effects of astrocyte-secreted TSPs with gabapentin (GBP) after injury suppresses the new excitatory connectivity and epileptogenesis for at least 2 weeks. Results reveal that aberrant circuit rewiring is progressive in vivo and provide further rationale for prophylactic anti-epileptogenic use of gabapentinoids following cortical trauma.

Role of KCC2-dependent potassium efflux in 4-Aminopyridine-induced Epileptiform synchronization

A balance between excitation and inhibition is necessary to maintain stable brain network dynamics. Traditionally, seizure activity is believed to arise from the breakdown of this delicate balance in favor of excitation with loss of inhibition. Surprisingly, recent experimental evidence suggests that this conventional view may be limited, and that inhibition plays a prominent role in the development of epileptiform synchronization. Here, we explored the role of the KCC2 co-transporter in the onset of inhibitory network-induced seizures. Our experiments in acute mouse brain slices, of either sex, revealed that optogenetic stimulation of either parvalbumin- or somatostatin-expressing interneurons induced ictal discharges in rodent entorhinal cortex during 4-aminopyridine application. These data point to a proconvulsive role of GABAA receptor signaling that is independent of the inhibitory input location (i.e., dendritic vs. somatic). We developed a biophysically realistic network model implementing dynamics of ion concentrations to explore the mechanisms leading to inhibitory network-induced seizures. In agreement with experimental results, we found that stimulation of the inhibitory interneurons induced seizure-like activity in a network with reduced potassium A-current. Our model predicts that interneuron stimulation triggered an increase of interneuron firing, which was accompanied by an increase in the intracellular chloride concentration and a subsequent KCC2-dependent gradual accumulation of the extracellular potassium promoting epileptiform ictal activity. When the KCC2 activity was reduced, stimulation of the interneurons was no longer able to induce ictal events. Overall, our study provides evidence for a proconvulsive role of GABAA receptor signaling that depends on the involvement of the KCC2 co-transporter.

Enhancing excitatory activity of somatosensory cortex alleviates neuropathic pain through regulating homeostatic plasticity

Central sensitization and network hyperexcitability of the nociceptive system is a basic mechanism of neuropathic pain. We hypothesize that development of cortical hyperexcitability underlying neuropathic pain may involve homeostatic plasticity in response to lesion-induced somatosensory deprivation and activity loss, and can be controlled by enhancing cortical activity. In a mouse model of neuropathic pain, in vivo two-photon imaging and patch clamp recording showed initial loss and subsequent recovery and enhancement of spontaneous firings of somatosensory cortical pyramidal neurons. Unilateral optogenetic stimulation of cortical pyramidal neurons both prevented and reduced pain-like behavior as detected by bilateral mechanical hypersensitivity of hindlimbs, but corpus callosotomy eliminated the analgesic effect that was ipsilateral, but not contralateral, to optogenetic stimulation, suggesting involvement of inter-hemispheric excitatory drive in this effect. Enhancing activity by focally blocking cortical GABAergic inhibition had a similar relieving effect on the pain-like behavior. Patch clamp recordings from layer V pyramidal neurons showed that optogenetic stimulation normalized cortical hyperexcitability through changing neuronal membrane properties and reducing frequency of excitatory postsynaptic events. We conclude that development of neuropathic pain involves abnormal homeostatic activity regulation of somatosensory cortex, and that enhancing cortical excitatory activity may be a novel strategy for preventing and controlling neuropathic pain.

Multi-layer network utilizing rewarded spike time dependent plasticity to learn a foraging task

Neural networks with a single plastic layer employing reward modulated spike time dependent plasticity (STDP) are capable of learning simple foraging tasks. Here we demonstrate advanced pattern discrimination and continuous learning in a network of spiking neurons with multiple plastic layers. The network utilized both reward modulated and non-reward modulated STDP and implemented multiple mechanisms for homeostatic regulation of synaptic efficacy, including heterosynaptic plasticity, gain control, output balancing, activity normalization of rewarded STDP and hard limits on synaptic strength. We found that addition of a hidden layer of neurons employing non-rewarded STDP created neurons that responded to the specific combinations of inputs and thus performed basic classification of the input patterns. When combined with a following layer of neurons implementing rewarded STDP, the network was able to learn, despite the absence of labeled training data, discrimination between rewarding patterns and the patterns designated as punishing. Synaptic noise allowed for trial-and-error learning that helped to identify the goal-oriented strategies which were effective in task solving. The study predicts a critical set of properties of the spiking neuronal network with STDP that was sufficient to solve a complex foraging task involving pattern classification and decision making.

This study explores how intelligent behavior emerges from the basic principles known at the cellular level of biological neuronal network dynamics. Compared to the approaches used in the artificial intelligence community, we applied biologically realistic modeling of neuronal dynamics and plasticity. The building blocks of the model are spiking neurons, spike-time dependent plasticity (STDP) and homeostatic rules, known experimentally, which are shown to play a fundamental role in both keeping the network stable and capable of continous learning. Our study predicts that a combination of these principles makes possible a foraging behavior in a previously unknown environment, including pattern classification to distinct between environment shapes which are rewarded and those which are punished and decision making to select the optimal strategy to acquire the maximal number of the rewarded elements. To solve this complex task we used multi-layer neuronal processing that implemented pattern generalization by unsupervised STDP at the earlier processing step, as commonly observed in the animal and human sensory processing, followed by reinforcement learning at the later steps. In the model, the intelligent behavior emerged spontaneously due to the network organization implementing both local unsupervised plasticity and reward feedback resulting from a successful behavior in the environment.

Mechanisms underlying different onset patterns of focal seizures

Focal seizures are episodes of pathological brain activity that appear to arise from a localised area of the brain. The onset patterns of focal seizure activity have been studied intensively, and they have largely been distinguished into two types-low amplitude fast oscillations (LAF), or high amplitude spikes (HAS). Here we explore whether these two patterns arise from fundamentally different mechanisms. Here, we use a previously established computational model of neocortical tissue, and validate it as an adequate model using clinical recordings of focal seizures. We then reproduce the two onset patterns in their most defining properties and investigate the possible mechanisms underlying the different focal seizure onset patterns in the model. We show that the two patterns are associated with different mechanisms at the spatial scale of a single ECoG electrode. The LAF onset is initiated by independent patches of localised activity, which slowly invade the surrounding tissue and coalesce over time. In contrast, the HAS onset is a global, systemic transition to a coexisting seizure state triggered by a local event. We find that such a global transition is enabled by an increase in the excitability of the "healthy" surrounding tissue, which by itself does not generate seizures, but can support seizure activity when incited. In our simulations, the difference in surrounding tissue excitability also offers a simple explanation of the clinically reported difference in surgical outcomes. Finally, we demonstrate in the model how changes in tissue excitability could be elucidated, in principle, using active stimulation. Taken together, our modelling results suggest that the excitability of the tissue surrounding the seizure core may play a determining role in the seizure onset pattern, as well as in the surgical outcome.

Using Biophysical Models to Understand the Effect of tDCS on Neurorehabilitation: Searching for Optimal Covariates to Enhance Poststroke Recovery

Stroke is a leading cause of worldwide disability, and up to 75% of survivors suffer from some degree of arm paresis. Recently, rehabilitation of stroke patients has focused on recovering motor skills by taking advantage of use-dependent neuroplasticity, where high-repetition of goal-oriented movement is at times combined with non-invasive brain stimulation, such as transcranial direct current stimulation (tDCS). Merging the two approaches is thought to provide outlasting clinical gains, by enhancing synaptic plasticity and motor relearning in the motor cortex primary area. However, this general approach has shown mixed results across the stroke population. In particular, stroke location has been found to correlate with the likelihood of success, which suggests that different patients might require different protocols. Understanding how motor rehabilitation and stimulation interact with ongoing neural dynamics is crucial to optimize rehabilitation strategies, but it requires theoretical and computational models to consider the multiple levels at which this complex phenomenon operate. In this work, we argue that biophysical models of cortical dynamics are uniquely suited to address this problem. Specifically, biophysical models can predict treatment efficacy by introducing explicit variables and dynamics for damaged connections, changes in neural excitability, neurotransmitters, neuromodulators, plasticity mechanisms, and repetitive movement, which together can represent brain state, effect of incoming stimulus, and movement-induced activity. In this work, we hypothesize that effects of tDCS depend on ongoing neural activity and that tDCS effects on plasticity may be also related to enhancing inhibitory processes. We propose a model design for each step of this complex system, and highlight strengths and limitations of the different modeling choices within our approach. Our theoretical framework proposes a change in paradigm, where biophysical models can contribute to the future design of novel protocols, in which combined tDCS and motor rehabilitation strategies are tailored to the ongoing dynamics that they interact with, by considering the known biophysical factors recruited by such protocols and their interaction.

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.

Mechanisms of homeostatic plasticity in the excitatory synapse

Brain development, sensory information processing, and learning and memory processes depend on Hebbian forms of synaptic plasticity, and on the remodeling and pruning of synaptic connections. Neurons in networks implicated in these processes carry out their functions while facing constant perturbation; homeostatic responses are therefore required to maintain neuronal activity within functional ranges for proper brain function. Here, we will review in vitro and in vivo studies demonstrating that several mechanisms underlie homeostatic plasticity of excitatory synapses, and identifying participant molecular players. Emerging evidence suggests a link between disrupted homeostatic synaptic plasticity and neuropsychiatric and neurologic disorders. Hebbian forms of synaptic plasticity, such as long-term potentiation (LTP), induce long-lasting changes in synaptic strength, which can be destabilizing and drive activity to saturation. Conversely, homeostatic plasticity operates to compensate for prolonged activity changes, stabilizing neuronal firing within a dynamic physiological range. We review mechanisms underlying homeostatic plasticity, and address how neurons integrate distinct forms of plasticity for proper brain function. This article is part of a mini review series: "Synaptic Function and Dysfunction in Brain Diseases".

Chronic Posttraumatic Epilepsy following Neocortical Undercut Lesion in Mice

Posttraumatic epilepsy (PTE) usually develops in a small percentage of patients of traumatic brain injury after a varying latent period. Modeling this chronic neurological condition in rodents is time consuming and inefficient, which constitutes a significant obstacle in studying its mechanism and discovering novel therapeutics for its prevention and treatment. Partially isolated neocortex, or undercut, is known to induce cortical hyperexcitability and epileptiform activity in vitro, and has been used extensively for studying the neurophysiological mechanism of posttraumatic epileptogenesis. However, whether the undercut lesion in rodents causes chronic epileptic seizures has not been systematically characterized. Here we used a miniature telemetry system to continuously monitor electroencephalography (EEG) in adult C57BL mice for up to 3 months after undercut surgery. We found that 50% of animals developed spontaneous seizures between 16–50 days after injury. The mean seizure duration was 8.9±3.6 seconds, and the average seizure frequency was 0.17±0.17 times per day. There was no progression in seizure frequency and duration over the recording period. Video monitoring revealed behavioral arrests and clonic limb movement during seizure attacks. A pentylenetetrazol (PTZ) test further showed increased seizure susceptibility in the undercut mice. We conclude that undercut lesion in mice is a model of chronic PTE that involves spontaneous epileptic seizures.

Astrocyte Hypertrophy Contributes to Aberrant Neurogenesis after Traumatic Brain Injury

Traumatic brain injury (TBI) is a widespread epidemic with severe cognitive, affective, and behavioral consequences. TBIs typically result in a relatively rapid inflammatory and neuroinflammatory response. A major component of the neuroinflammatory response is astrocytes, a type of glial cell in the brain. Astrocytes are important in maintaining the integrity of neuronal functioning, and it is possible that astrocyte hypertrophy after TBIs might contribute to pathogenesis. The hippocampus is a unique brain region, because neurogenesis persists in adults. Accumulating evidence supports the functional importance of these newborn neurons and their associated astrocytes. Alterations to either of these cell types can influence neuronal functioning. To determine if hypertrophied astrocytes might negatively influence immature neurons in the dentate gyrus, astrocyte and newborn neurons were analyzed at 30 days following a TBI in mice. The results demonstrate a loss of radial glial-like processes extending through the granule cell layer after TBI, as well as ectopic growth and migration of immature dentate neurons. The results further show newborn neurons in close association with hypertrophied astrocytes, suggesting a role for the astrocytes in aberrant neurogenesis. Future studies are needed to determine the functional significance of these alterations to the astrocyte/immature neurons after TBI.

Transition from Initial Hypoactivity to Hyperactivity in Cortical Layer V Pyramidal Neurons after Traumatic Brain Injury In Vivo

Traumatic brain injury (TBI) often results in structural damage and a loss of neurons that is commonly accompanied by early changes in neuronal electrical activity. Loss of neuronal activity has been hypothesized to contribute to post-traumatic epileptogenesis through the regulation of homeostatic plasticity. The existence of activity loss in cortical neurons after TBI and its subsequent transition into hyperactivity over time is not well characterized, however, particularly in models of TBI in vivo. In the current study, changes in neuronal activity in the primary motor cortex after moderate controlled cortical impact (CCI) in mice were studied using a single-unit recording technique in vivo. Recordings were made at different time points after CCI from cortical layer V pyramidal neurons that were within 1-2 mm from the anterior edge of the injured foci. Within 1-4 h after CCI, the frequency of spontaneous single-unit activity depressed significantly, with the mean firing frequency decreasing from 2.59 ± 0.18 Hz in the sham group to 1.05 ± 0.20 Hz of the injured group. The firing frequencies recovered to the normal level at 1 day and 7 days post-CCI, but became significantly higher at 3 days and 14 days post-CCI. The results suggest that TBI caused initial loss of activity in neurons of the perilesional cortical region, which was followed by compensatory recovery and enhancement of activity. These time-dependent changes in neuronal activity may contribute to the development of hyperexcitability through homeostatic activity regulation.

In vivo models of cortical acquired epilepsy

The neocortex is the site of origin of several forms of acquired epilepsy. Here we provide a brief review of experimental models that were recently developed to study neocortical epileptogenesis as well as some major results obtained with these methods. Most of neocortical seizures appear to be nocturnal and it is known that neuronal activities reveal high levels of synchrony during slow-wave sleep. Therefore, we start the review with a description of mechanisms of neuronal synchronization and major forms of synchronized normal and pathological activities. Then, we describe three experimental models of seizures and epileptogenesis: ketamine-xylazine anesthesia as feline seizure triggered factor, cortical undercut as cortical penetrating wound model and neocortical kindling. Besides specific technical details describing these models we also provide major features of pathological brain activities recorded during epileptogenesis and seizures. The most common feature of all models of neocortical epileptogenesis is the increased duration of network silent states that up-regulates neuronal excitability and eventually leads to epilepsy.

Modeling of Age-Dependent Epileptogenesis by Differential Homeostatic Synaptic Scaling

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

Excitatory/Inhibitory Balance and Circuit Homeostasis in Autism Spectrum Disorders

Autism spectrum disorders (ASDs) and related neurological disorders are associated with mutations in many genes affecting the ratio between neuronal excitation and inhibition. However, understanding the impact of these mutations on network activity is complicated by the plasticity of these networks, making it difficult in many cases to separate initial deficits from homeostatic compensation. Here we explore the contrasting evidence for primary defects in inhibition or excitation in ASDs and attempt to integrate the findings in terms of the brain's ability to maintain functional homeostasis.

Evolution of Network Synchronization during Early Epileptogenesis Parallels Synaptic Circuit Alterations

In secondary epilepsy, a seizure-prone neural network evolves during the latent period between brain injury and the onset of spontaneous seizures. The nature of the evolution is largely unknown, and even its completeness at the onset of seizures has recently been challenged by measures of gradually decreasing intervals between subsequent seizures. Sequential calcium imaging of neuronal activity, in the pyramidal cell layer of mouse hippocampal in vitro preparations, during early post-traumatic epileptogenesis demonstrated rapid increases in the fraction of neurons that participate in interictal activity. This was followed by more gradual increases in the rate at which individual neurons join each developing seizure, the pairwise correlation of neuronal activities as a function of the distance separating the pair, and network-wide measures of functional connectivity. These data support the continued evolution of synaptic connectivity in epileptic networks beyond the latent period: early seizures occur when recurrent excitatory pathways are largely polysynaptic, while ongoing synaptic remodeling after the onset of epilepsy enhances intranetwork connectivity as well as the onset and spread of seizure activity.

Homeostatic role of heterosynaptic plasticity: models and experiments

Homosynaptic Hebbian-type plasticity provides a cellular mechanism of learning and refinement of connectivity during development in a variety of biological systems. In this review we argue that a complimentary form of plasticity-heterosynaptic plasticity-represents a necessary cellular component for homeostatic regulation of synaptic weights and neuronal activity. The required properties of a homeostatic mechanism which acutely constrains the runaway dynamics imposed by Hebbian associative plasticity have been well-articulated by theoretical and modeling studies. Such mechanism(s) should robustly support the stability of operation of neuronal networks and synaptic competition, include changes at non-active synapses, and operate on a similar time scale to Hebbian-type plasticity. The experimentally observed properties of heterosynaptic plasticity have introduced it as a strong candidate to fulfill this homeostatic role. Subsequent modeling studies which incorporate heterosynaptic plasticity into model neurons with Hebbian synapses (utilizing an STDP learning rule) have confirmed its ability to robustly provide stability and competition. In contrast, properties of homeostatic synaptic scaling, which is triggered by extreme and long lasting (hours and days) changes of neuronal activity, do not fit two crucial requirements for a hypothetical homeostatic mechanism needed to provide stability of operation in the face of on-going synaptic changes driven by Hebbian-type learning rules. Both the trigger and the time scale of homeostatic synaptic scaling are fundamentally different from those of the Hebbian-type plasticity. We conclude that heterosynaptic plasticity, which is triggered by the same episodes of strong postsynaptic activity and operates on the same time scale as Hebbian-type associative plasticity, is ideally suited to serve a homeostatic role during on-going synaptic plasticity.

Neocortical focus: experimental view

All brain normal or pathological activities occur in one of the states of vigilance: wake, slow-wave sleep, or REM sleep. Neocortical seizures preferentially occur during slow-wave sleep. We provide a description of neuronal behavior and mechanisms mediating such a behavior within neocortex taking place in natural states of vigilance as well as during seizures pointing to similarities and differences exhibited during sleep and seizures. A concept of epileptic focus is described using a model of cortical undercut, because in that model, the borders of the focus are well defined. In this model, as in other models of acquired epilepsy, the main factor altering excitability is deafferentation, which upregulates neuronal excitability that promotes generation of seizures. Periods of disfacilitation recorded during slow-wave sleep further upregulate neuronal excitability. It appears that the state of neurons and neuronal network in the epileptic focus produced by deafferentation are such that seizures cannot be generated there. Instead, seizures always start around the perimeter of the undercut cortex. Therefore, we define these areas as the seizure focus. In this zone, neuronal connectivity and excitability are moderately enhanced, lowering the threshold for seizure generation.

Astrocyte roles in traumatic brain injury

Astrocytes sense changes in neural activity and extracellular space composition. In response, they exert homeostatic mechanisms critical for maintaining neural circuit function, such as buffering neurotransmitters, modulating extracellular osmolarity and calibrating neurovascular coupling. In addition to upholding normal brain activities, astrocytes respond to diverse forms of brain injury with heterogeneous and progressive changes of gene expression, morphology, proliferative capacity and function that are collectively referred to as reactive astrogliosis. Traumatic brain injury (TBI) sets in motion complex events in which noxious mechanical forces cause tissue damage and disrupt central nervous system (CNS) homeostasis, which in turn trigger diverse multi-cellular responses that evolve over time and can lead either to neural repair or secondary cellular injury. In response to TBI, astrocytes in different cellular microenvironments tune their reactivity to varying degrees of axonal injury, vascular disruption, ischemia and inflammation. Here we review different forms of TBI-induced astrocyte reactivity and the functional consequences of these responses for TBI pathobiology. Evidence regarding astrocyte contribution to post-traumatic tissue repair and synaptic remodeling is examined, and the potential for targeting specific aspects of astrogliosis to ameliorate TBI sequelae is considered.

Maladaptive neural synchrony in tinnitus: origin and restoration

Tinnitus is the conscious perception of sound heard in the absence of physical sound sources external or internal to the body, reflected in aberrant neural synchrony of spontaneous or resting-state brain activity. Neural synchrony is generated by the nearly simultaneous firing of individual neurons, of the synchronization of membrane-potential changes in local neural groups as reflected in the local field potentials, resulting in the presence of oscillatory brain waves in the EEG. Noise-induced hearing loss, often resulting in tinnitus, causes a reorganization of the tonotopic map in auditory cortex and increased spontaneous firing rates and neural synchrony. Spontaneous brain rhythms rely on neural synchrony. Abnormal neural synchrony in tinnitus appears to be confined to specific frequency bands of brain rhythms. Increases in delta-band activity are generated by deafferented/deprived neuronal networks resulting from hearing loss. Coordinated reset (CR) stimulation was developed in order to specifically counteract such abnormal neuronal synchrony by desynchronization. The goal of acoustic CR neuromodulation is to desynchronize tinnitus-related abnormal delta-band oscillations. CR neuromodulation does not require permanent stimulus delivery in order to achieve long-lasting desynchronization or even a full-blown anti-kindling but may have cumulative effects, i.e., the effect of different CR epochs separated by pauses may accumulate. Unlike other approaches, acoustic CR neuromodulation does not intend to reduce tinnitus-related neuronal activity by employing lateral inhibition. The potential efficacy of acoustic CR modulation was shown in a clinical proof of concept trial, where effects achieved in 12 weeks of treatment delivered 4–6 h/day persisted through a preplanned 4-week therapy pause and showed sustained long-term effects after 10 months of therapy, leading to 75% responders.

Electrogenic properties of the Na⁺/K⁺ ATPase control transitions between normal and pathological brain states

Ionic concentrations fluctuate significantly during epileptic seizures. In this study, using a combination of in vitro electrophysiology, computer modeling, and dynamical systems analysis, we demonstrate that changes in the potassium and sodium intra- and extracellular ion concentrations ([K(+)] and [Na(+)], respectively) during seizure affect the neuron dynamics by modulating the outward Na(+)/K(+) pump current. First, we show that an increase of the outward Na(+)/K(+) pump current mediates termination of seizures when there is a progressive increase in the intracellular [Na(+)]. Second, we show that the Na(+)/K(+) pump current is crucial in maintaining the stability of the physiological network state; a reduction of this current leads to the onset of seizures via a positive-feedback loop. We then present a novel dynamical mechanism for bursting in neurons with a reduced Na(+)/K(+) pump. Overall, our study demonstrates the profound role of the current mediated by Na(+)/K(+) ATPase on the stability of neuronal dynamics that was previously unknown.

Acute and chronic efficacy of bumetanide in an in vitro model of posttraumatic epileptogenesis

BACKGROUND

Seizures triggered by acute injuries to the developing brain respond poorly to first-line medications that target the inhibitory chloride-permeable GABAA receptor. Neuronal injury is associated with profound increases in cytoplasmic chloride ([Cl(-)]i) resulting in depolarizing GABA signaling, higher seizure propensity and limited efficacy of GABAergic anticonvulsants. The Na(+)-K(+)-2Cl(-) (NKCC1) cotransporter blocker bumetanide reduces [Cl(-)]i and causes more negative GABA equilibrium potential in injured neurons. We therefore tested both the acute and chronic efficacy of bumetanide on early posttraumatic ictal-like epileptiform discharges and epileptogenesis.

METHODS

Acute hippocampal slices were used as a model of severe traumatic brain injury and posttraumatic epileptogenesis. Hippocampal slices were then incubated for 3 weeks. After a 1-week latent period, slice cultures developed chronic spontaneous ictal-like discharges. The anticonvulsant and anti-epileptogenic efficacy of bumetanide, phenobarbital, and the combination of these drugs was studied.

RESULTS

Bumetanide reduced the frequency and power of early posttraumatic ictal-like discharges in vitro and enhanced the anticonvulsant efficacy of phenobarbital. Continuous 2-3 weeks administration of bumetanide as well as phenobarbital in combination with bumetanide failed to prevent posttraumatic ictal-like discharges and epileptogenesis.

CONCLUSIONS

Our data demonstrate a persistent contribution of NKCC1 cotransport in posttraumatic ictal-like activity, presumably as a consequence of chronic alterations in neuronal chloride homeostasis and GABA-mediated inhibition. New strategies for more effective reduction in posttraumatic and seizure-induced [Cl(-)]i accumulation could provide the basis for effective treatments for posttraumatic epileptogenesis and the resultant seizures.

Homeostatic control of presynaptic neurotransmitter release

It is well established that the active properties of nerve and muscle cells are stabilized by homeostatic signaling systems. In organisms ranging from Drosophila to humans, neurons restore baseline function in the continued presence of destabilizing perturbations by rebalancing ion channel expression, modifying neurotransmitter receptor surface expression and trafficking, and modulating neurotransmitter release. This review focuses on the homeostatic modulation of presynaptic neurotransmitter release, termed presynaptic homeostasis. First, we highlight criteria that can be used to define a process as being under homeostatic control. Next, we review the remarkable conservation of presynaptic homeostasis at the Drosophila, mouse, and human neuromuscular junctions and emerging parallels at synaptic connections in the mammalian central nervous system. We then highlight recent progress identifying cellular and molecular mechanisms. We conclude by reviewing emerging parallels between the mechanisms of homeostatic signaling and genetic links to neurological disease.

Homeostatic structural plasticity can account for topology changes following deafferentation and focal stroke

After brain lesions caused by tumors or stroke, or after lasting loss of input (deafferentation), inter- and intra-regional brain networks respond with complex changes in topology. Not only areas directly affected by the lesion but also regions remote from the lesion may alter their connectivity—a phenomenon known as diaschisis. Changes in network topology after brain lesions can lead to cognitive decline and increasing functional disability. However, the principles governing changes in network topology are poorly understood. Here, we investigated whether homeostatic structural plasticity can account for changes in network topology after deafferentation and brain lesions. Homeostatic structural plasticity postulates that neurons aim to maintain a desired level of electrical activity by deleting synapses when neuronal activity is too high and by providing new synaptic contacts when activity is too low. Using our Model of Structural Plasticity, we explored how local changes in connectivity induced by a focal loss of input affected global network topology. In accordance with experimental and clinical data, we found that after partial deafferentation, the network as a whole became more random, although it maintained its small-world topology, while deafferentated neurons increased their betweenness centrality as they rewired and returned to the homeostatic range of activity. Furthermore, deafferentated neurons increased their global but decreased their local efficiency and got longer tailed degree distributions, indicating the emergence of hub neurons. Together, our results suggest that homeostatic structural plasticity may be an important driving force for lesion-induced network reorganization and that the increase in betweenness centrality of deafferentated areas may hold as a biomarker for brain repair.

Fragility in dynamic networks: application to neural networks in the epileptic cortex

Epilepsy is a network phenomenon characterized by atypical activity at the neuronal and population levels during seizures, including tonic spiking, increased heterogeneity in spiking rates, and synchronization. The etiology of epilepsy is unclear, but a common theme among proposed mechanisms is that structural connectivity between neurons is altered. It is hypothesized that epilepsy arises not from random changes in connectivity, but from specific structural changes to the most fragile nodes or neurons in the network. In this letter, the minimum energy perturbation on functional connectivity required to destabilize linear networks is derived. Perturbation results are then applied to a probabilistic nonlinear neural network model that operates at a stable fixed point. That is, if a small stimulus is applied to the network, the activation probabilities of each neuron respond transiently but eventually recover to their baseline values. When the perturbed network is destabilized, the activation probabilities shift to larger or smaller values or oscillate when a small stimulus is applied. Finally, the structural modifications to the neural network that achieve the functional perturbation are derived. Simulations of the unperturbed and perturbed networks qualitatively reflect neuronal activity observed in epilepsy patients, suggesting that the changes in network dynamics due to destabilizing perturbations, including the emergence of an unstable manifold or a stable limit cycle, may be indicative of neuronal or population dynamics during seizure. That is, the epileptic cortex is always on the brink of instability and minute changes in the synaptic weights associated with the most fragile node can suddenly destabilize the network to cause seizures. Finally, the theory developed here and its interpretation of epileptic networks enables the design of a straightforward feedback controller that first detects when the network has destabilized and then applies linear state feedback control to steer the network back to its stable state.

Krüppel mediates the selective rebalancing of ion channel expression

Ion channel gene expression can vary substantially among neurons of a given type, even though neuron-type-specific firing properties remain stable and reproducible. The mechanisms that modulate ion channel gene expression and stabilize neural firing properties are unknown. In Drosophila, we demonstrate that loss of the Shal potassium channel induces the compensatory rebalancing of ion channel expression including, but not limited to, the enhanced expression and function of Shaker and slowpoke. Using genomic and network modeling approaches combined with genetic and electrophysiological assays, we demonstrate that the transcription factor Krüppel is necessary for the homeostatic modulation of Shaker and slowpoke expression. Remarkably, Krüppel induction is specific to the loss of Shal, not being observed in five other potassium channel mutants that cause enhanced neuronal excitability. Thus, homeostatic signaling systems responsible for rebalancing ion channel expression can be selectively induced after the loss or impairment of a specific ion channel.

The impact of cortical deafferentation on the neocortical slow oscillation

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

Hippocampus, hippocampal sclerosis and epilepsy

Hippocampal sclerosis (HS) is considered one of the major pathogenic factors of drug-resistant temporal lobe epilepsy. HS is characterized by selective loss of pyramidal neurons - especially of sectors CA1 and CA3 of the hippocampus - pathological proliferation of interneuron networks, and severe glia reaction. These changes occur in the course of long-term and complex epileptogenesis. The authors, on the basis of a review of the literature and own experience, present the pathomechanisms leading to hippocampal sclerosis and epileptogenesis, including various morphological and functional elements of this structure of the brain and pharmacological possibilities of preventing these processes.

Traumatic Brain Injury Causes a Tacrolimus-Sensitive Increase in Non-Convulsive Seizures in a Rat Model of Post-Traumatic Epilepsy

Epilepsy is a significant but potentially preventable complication of traumatic brain injury (TBI). Previous research in animal models of acquired epilepsy has implicated the calcium-sensitive phosphatase, calcineurin. In addition, our lab recently found that calcineurin activity in the rat hippocampus increases acutely after lateral TBI. Here we use a calcineurin inhibitor test whether an acute increase in calcineurin activity is necessary for the development of late post-traumatic seizures. Adult rats were administered the calcineurin inhibitor Tacrolimus (5mg/kg; i.p.) 1 hour after lateral fluid percussion TBI and then monitored by video-electrocorticography (video-ECoG) for spontaneous seizure activity 5 weeks or 33 weeks later. At 5 weeks post-TBI, we observed epileptiform activity on the video-ECoG of brain injured rats but no seizures. By 33 weeks post-TBI though, nearly all injured rats exhibited spontaneous seizures, including convulsive seizures which were infrequent but lasted minutes (18% of injured rats), and non-convulsive seizures which were frequent but lasted tens of seconds (94% of injured rats). We also identified non-convulsive seizures in a smaller subset of control and sham TBI rats (56%), reminiscent of idiopathic seizures described in other rats strains. Non-convulsive seizures in the brain injured rats, however, were four-times more frequent and two-times longer lasting than in their uninjured littermates. Interestingly, rats administered Tacrolimus acutely after TBI showed significantly fewer non-convulsive seizures than untreated rats, but a similar degree of cortical atrophy. The data thus indicate that administration of Tacrolimus acutely after TBI suppressed non-convulsive seizures months later.

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.