Modeling different regimes of bioelectrical activity in the brain in normal subjects and in "increased readiness" in a network of neuron-like elements

Desynchronous (low voltage fast activity), synchronous (high voltage slow waves) as well as convulsive brain activities were stimulated by a computer model of neuronal population. Network excitatory and inhibitory elements possessed fundamental dynamic properties of real neurones. Being independent both of the excitability of elements and of external influence efficacy, synchronous (desynchronous) network activity resulted from the increase (decrease) of the average power of "neuronal" interconnections which imitated mutual and recurrent excitation and inhibition. The inhibition efficacy being reduced as compared with excitation, synchronization of elements became intensified. As a consequence, the rhythmic activity amplitude increased and the appearance of self-sustained oscillations simulating convulsive activity was facilitated. The probable mechanism of EEG activation by virtue of the reduction of mutual and recurrent excitation and inhibition efficacy as well as the significance of inhibitory mechanism deficiency for epileptogenesis are discussed.     

In vitro study of newborn rat brain maturation: implication for sudden infant death syndrome.

We have used slice preparation from newborn rats to study the development of the nucleus tractus solitarius neuronal network and brain intracellular phosphorus metabolites. As shown previously on adults, the newborn preparation retains local excitatory and inhibitory synaptic connections and enables study of intrinsic electrical properties in the nucleus tractus solitarius. Electrophysiological investigation of inhibitory synaptic transmission demonstrated a maturational step at days 4-6 after birth. Nuclear magnetic resonance spectroscopy of brain slices revealed a metabolic maturation between postnatal days 11 and 17. Results emphasize the differential maturation steps during the postnatal development of rat central nervous system. Possibly, Sudden Infant Death Syndrome may result from the abnormal timing in the occurrence of these steps.     

A neural network model of reliably optimized spike transmission

We studied the detailed structure of a neuronal network model in which the spontaneous spike activity is correctly optimized to match the experimental data and discuss the reliability of the optimized spike transmission. Two stochastic properties of the spontaneous activity were calculated: the spike-count rate and synchrony size. The synchrony size, expected to be an important factor for optimization of spike transmission in the network, represents a percentage of observed coactive neurons within a time bin, whose probability approximately follows a power-law. We systematically investigated how these stochastic properties could matched to those calculated from the experimental data in terms of the log-normally distributed synaptic weights between excitatory and inhibitory neurons and synaptic background activity induced by the input current noise in the network model. To ensure reliably optimized spike transmission, the synchrony size as well as spike-count rate were simultaneously optimized. This required changeably balanced log-normal distributions of synaptic weights between excitatory and inhibitory neurons and appropriately amplified synaptic background activity. Our results suggested that the inhibitory neurons with a hub-like structure driven by intensive feedback from excitatory neurons were a key factor in the simultaneous optimization of the spike-count rate and synchrony size, regardless of different spiking types between excitatory and inhibitory neurons.     

Effects of phase on homeostatic spike rates

Recent experimental results by Talathi et al. (Neurosci Lett 455:145–149, 2009) showed a divergence in the spike rates of two types of population spike events, representing the putative activity of the excitatory and inhibitory neurons in the CA1 area of an animal model for temporal lobe epilepsy. The divergence in the spike rate was accompanied by a shift in the phase of oscillations between these spike rates leading to a spontaneous epileptic seizure. In this study, we propose a model of homeostatic synaptic plasticity which assumes that the target spike rate of populations of excitatory and inhibitory neurons in the brain is a function of the phase difference between the excitatory and inhibitory spike rates. With this model of homeostatic synaptic plasticity, we are able to simulate the spike rate dynamics seen experimentally by Talathi et al. in a large network of interacting excitatory and inhibitory neurons using two different spiking neuron models. A drift analysis of the spike rates resulting from the homeostatic synaptic plasticity update rule allowed us to determine the type of synapse that may be primarily involved in the spike rate imbalance in the experimental observation by Talathi et al. We find excitatory neurons, particularly those in which the excitatory neuron is presynaptic, have the most influence in producing the diverging spike rates and causing the spike rates to be anti-phase. Our analysis suggests that the excitatory neuronal population, more specifically the excitatory to excitatory synaptic connections, could be implicated in a methodology designed to control epileptic seizures.     

Development of gonadotropin-releasing hormone (GnRH) neuron regulation in the female rat

Summary 1. After reaching its final destination the GnRH neuronal network develops under the influence of both excitatory and inhibitory inputs.2. In the first 2 weeks of life, the immaturity of the GnRH neuronal system is reflected in sporadic unsynchronized bursts of the decapeptide, which determine the pattern of serum gonadotropin levels observed in female rats: high FSH levels and transient bursts of LH. The main inhibitory neuronal systems that operate in this period are the opioid and dopaminergic systems. A decrease in their inhibitory effectiveness may not be sufficient correctly to activate and synchronize the GnRH neuronal system.3. There is a concomitant increase in excitatory inputs, mainly noradrenaline, excitatory amino acids, and NPY, which increase the synthesis and release of GnRH at the beginning of the juvenile period and participate in the coupling of GnRH neural activity to the ongoing rhythmic activity of a hypothalamic circadian oscillator.4. The morphological changes of GnRH neurons which take place during the third and fourth weeks of life, and which are probably related to increasing estradiol levels, reflects the increasing complexity of the GnRH neuronal network, which establishes synaptic contacts to enable the expression of pulsatility and of the positive feedback of estradiol, both necessary components for the occurrence of puberty.     

Plasticity of GABAergic synapses in the neonatal rat hippocampus

While the development and plasticity of excitatory synaptic connections have been studied into detail, little is known about the development of inhibitory synapses. As proposed for excitatory synapses, recent studies have indicated that activity-dependent forms of synaptic plasticity, such as long-term potentiation and long-term depression, may play a role in the establishment of functional inhibitory synaptic connections. Here, I review these different forms of plasticity and focus on their possible role in the developing neuronal network.     

Influence of glutamate and GABA transport on brain excitatory/inhibitory balance

An optimally functional brain requires both excitatory and inhibitory inputs that are regulated and balanced. A perturbation in the excitatory/inhibitory balance—as is the case in some neurological disorders/diseases (e.g. traumatic brain injury Alzheimer’s disease, stroke, epilepsy and substance abuse) and disorders of development (e.g. schizophrenia, Rhett syndrome and autism spectrum disorder)—leads to dysfunctional signaling, which can result in impaired cognitive and motor function, if not frank neuronal injury. At the cellular level, transmission of glutamate and GABA, the principle excitatory and inhibitory neurotransmitters in the central nervous system control excitatory/inhibitory balance. Herein, we review the synthesis, release, and signaling of GABA and glutamate followed by a focused discussion on the importance of their transport systems to the maintenance of excitatory/inhibitory balance.     

The effect of early sensory experience on development of neuron functional properties in the area of vibrissal projection in the rat neocortex

The role of specific sensory inflow in the functional maturation of neurons in the area of vibrissal projections in the somatosensory cortex of rats was studied. Animals were subjected to bilateral trimming of whiskers during the first three weeks of postnatal ontogenesis. Quantitative and qualitative characteristics of neuronal responses were analyzed in the "lemniscal" layers IV and Vb and "paralemniscal" layer Va in junior (27-40 PN days) and elder (41-57 PN days) rats. The immediate effect of deafferentation in younger animals consisted in an increase in excitatory responses, which correlated with a deficit of inhibitory reactions. In animals subjected to vibrissectomy, atypical responses were observed in the "lemniscal" and "paralemniscal" layers. This effect may be caused by a derangement of distribution of thalamic afferents in the somatosensory cortex. Elder animals in vibrissectomized group displayed an increase in inhibitory reactions, i.e., the long-term effect of vibrissectomy is the actualization of inhibitory mechanisms.     

电刺激诱导大鼠海马癫痫电网络神经信息分析

探讨电刺激致海马(hippocampus,HPC)癫痫网络的神经信息特征和M型胆碱能受体阻断剂东莨菪碱(scopolamine)对该信息特征的调制作用。实验用雄性SD大鼠45只,体重150￣250g。急性强直电(60Hz,2s,0.4￣0.6mA)刺激右侧后背HPC(acutetetanizationoftherightposteriordorsalhippocampus,ATPDH),双电极同步记录同侧HPC网络和单个神经元电活动。分析癫痫发作样高频电振荡(ripple)功率谱(powerspec-trum)、尖波连续发放峰间间隔(interpeakinterval,IPI)和单位时间内平均频率(Hz),并同步分析单个神经元放电脉冲间隔(interspikeinterval,ISI)的变化特征。发现:(1)ATPDH诱导的HPC癫痫放电模式主要包括rip-ple和具有稳定频率特征的尖波样连续发放;(2)东莨菪碱(i.p.)可以提前ripple第1组分最大功率(μV2)与单个神经元原发性单位后放电最大ISI出现的时间,对最大ISI的作用更明显;(3)东莨菪碱可以部分再现重复施加ATPDH诱导出现巨大尖波连续发放IPI和神经元放电ISI平行发展特征。结果提示:M胆碱能受体阻断剂东莨菪碱可以同时调制HPC癫痫网络成员电场和细胞的瞬时编码信息;而成员电场ripple功率谱/连续尖波IPI和神经元放电ISI点分布的对比研究,可以用于分析癫痫网络瞬时编码信息和药物生物学效应。     

Evaluation of forms of cortical neuron response to acetylcholine

Analysis was carried out of the form of excitatory components of the reaction of 92 neurones in rats sensorimotor cortical area to electrophoretically applied acetylcholine. The used method of approximation of neuronal reaction form by two polynomes of the second degree allowed to identify one- and two-component types of responses to the transmitter. It is suggested that in genesis of the excitatory component of neuronal reaction to acetylcholine one or two types of cholinoreceptors may participate.     

Chaos and synchrony in a model of a hypercolumn in visual cortex

Neurons in cortical slices emit spikes or bursts of spikes regularly in response to a suprathreshold current injection. This behavior is in marked contrast to the behavior of cortical neurons in vivo, whose response to electrical or sensory input displays a strong degree of irregularity. Correlation measurements show a significant degree of synchrony in the temporal fluctuations of neuronal activities in cortex. We explore the hypothesis that these phenomena are the result of the synchronized chaos generated by the deterministic dynamics of local cortical networks. A model of a hypercolumn in the visual cortex is studied. It consists of two populations of neurons, one inhibitory and one excitatory. The dynamics of the neurons is based on a Hodgkin-Huxley type model of excitable voltage-clamped cells with several cellular and synaptic conductances. A slow potassium current is included in the dynamics of the excitatory population to reproduce the observed adaptation of the spike trains emitted by these neurons. The pattern of connectivity has a spatial structure which is correlated with the internal organization of hypercolumns in orientation columns. Numerical simulations of the model show that in an appropriate parameter range, the network settles in a synchronous chaotic state, characterized by a strong temporal variability of the neural activity which is correlated across the hypercolumn. Strong inhibitory feedback is essential for the stabilization of this state. These results show that the cooperative dynamics of large neuronal networks are capable of generating variability and synchrony similar to those observed in cortex. Auto-correlation and cross-correlation functions of neuronal spike trains are computed, and their temporal and spatial features are analyzed. In other parameter regimes, the network exhibits two additional states: synchronized oscillations and an asynchronous state. We use our model to study cortical mechanisms for orientation selectivity. It is shown that in a suitable parameter regime, when the input is not oriented, the network has a continuum of states, each representing an inhomogeneous population activity which is peaked at one of the orientation columns. As a result, when a weakly oriented input stimulates the network, it yields a sharp orientation tuning. The properties of the network in this regime, including the appearance of virtual rotations and broad stimulus-dependent cross-correlations, are investigated. The results agree with the predictions of the mean field theory which was previously derived for a simplified model of stochastic, two-state neurons. The relation between the results of the model and experiments in visual cortex are discussed.     

Optogenetic Delay of Status Epilepticus Onset in an In Vivo Rodent Epilepsy Model

Epilepsy is a devastating disease, currently treated with medications, surgery or electrical stimulation. None of these approaches is totally effective and our ability to control seizures remains limited and complicated by frequent side effects. The emerging revolutionary technique of optogenetics enables manipulation of the activity of specific neuronal populations in vivo with exquisite spatiotemporal resolution using light. We used optogenetic approaches to test the role of hippocampal excitatory neurons in the lithium-pilocarpine model of acute elicited seizures in awake behaving rats. Hippocampal pyramidal neurons were transduced in vivo with a virus carrying an enhanced halorhodopsin (eNpHR), a yellow light activated chloride pump, and acute seizure progression was then monitored behaviorally and electrophysiologically in the presence and absence of illumination delivered via an optical fiber. Inhibition of those neurons with illumination prior to seizure onset significantly delayed electrographic and behavioral initiation of status epilepticus, and altered the dynamics of ictal activity development. These results reveal an essential role of hippocampal excitatory neurons in this model of ictogenesis and illustrate the power of optogenetic approaches for elucidation of seizure mechanisms. This early success in controlling seizures also suggests future therapeutic avenues.     

Synchronization and sensitivity enhancement of the Hodgkin-Huxley neurons due to inhibitory inputs

Recent experimental results imply that inhibitory postsynaptic potentials can play a functional role in realizing synchronization of neuronal firing in the brain. In order to examine the relation between inhibition and synchronous firing of neurons theoretically, we analyze possible effects of synchronization and sensitivity enhancement caused by inhibitory inputs to neurons with a biologically realistic model of the Hodgkin-Huxley equations. The result shows that, after an inhibitory spike, the firing probability of a single postsynaptic neuron exposed to random excitatory background activity oscillates with time. The oscillation of the firing probability can be related to synchronous firing of neurons receiving an inhibitory spike simultaneously. Further, we show that when an inhibitory spike input precedes an excitatory spike input, the presence of such preceding inhibition raises the firing probability peak of the neuron after the excitatory input. The result indicates that an inhibitory spike input can enhance the sensitivity of the postsynaptic neuron to the following excitatory spike input. Two neural network models based on these effects on postsynaptic neurons caused by inhibitory inputs are proposed to demonstrate possible mechanisms of detecting particular spatiotemporal spike patterns. Received: 15 April 1999 /Accepted in revised form: 25 November 1999     

Network activity of "interneurons" and large cells of amygdala in active and passive rabbits

By plotting cross-correlation histograms differences were found in interaction of conjectural small "interneurons" and large principal cells of the central and basal amygdalar nuclei in negative emotional situations. The network activity of "nterneurons" was higher than in principal cells. "Interneurons" more frequently had excitatory and inhibitory input or output connections with neighbouring cells, latency of their connections with other cells was smaller than in principal neurons. Interaction of "interneurons" and principal cells differed in animals with active and passive behavioural strategy in negative emotional situations. As compared to active animals, in passive rabbits inhibitory connections to "interneurons" from other cells occurred more frequently, excitatory or inhibitory connections from "interneurons" to principal cells appeared more rare.     

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 , 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 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.     

Dynamics of the seizure states caused by the action of ligands of the inhibitory transmitter system, as a consequence of evolution of stochastic neuronal populations

A probabilistic model describing functioning of the elements of a neuronal population is suggested. The model includes subsystems: synaptically interconnected inhibitory and excitatory neurons. The probability of the occurrence of the intercellular signal at varying levels of the endogenous transmitter and the effects of exogenous ligands (agonists, antagonists, etc.) of the inhibitory (GABA_A) transmitter system is considered. Comparison of the computer simulation with the experimental data showed that their paroxysmal EEG activity recorded after applications of strychnine, corazol, bicuculline, or picrotoxin to the neocortical surface, as well as during seizures following intravenous administrations of these drugs, is characterized by a consequent mild and rigid loss of stability, followed by a decrease in the share of active neurons in the population. The reason for these phenomena is a periodical asynchronous decrease in the efficiency of excitatory and inhibitory intercellular signals in the neuronal population.     

Cortical network modeling: analytical methods for firing rates and some properties of networks of LIF neurons.

The circuitry of cortical networks involves interacting populations of excitatory (E) and inhibitory (I) neurons whose relationships are now known to a large extent. Inputs to E- and I-cells may have their origins in remote or local cortical areas. We consider a rudimentary model involving E- and I-cells. One of our goals is to test an analytic approach to finding firing rates in neural networks without using a diffusion approximation and to this end we consider in detail networks of excitatory neurons with leaky integrate-and-fire (LIF) dynamics. A simple measure of synchronization, denoted by S(q), where q is between 0 and 100 is introduced. Fully connected E-networks have a large tendency to become dominated by synchronously firing groups of cells, except when inputs are relatively weak. We observed random or asynchronous firing in such networks with diverse sets of parameter values. When such firing patterns were found, the analytical approach was often able to accurately predict average neuronal firing rates. We also considered several properties of E-E networks, distinguishing several kinds of firing pattern. Included were those with silences before or after periods of intense activity or with periodic synchronization. We investigated the occurrence of synchronized firing with respect to changes in the internal excitatory postsynaptic potential (EPSP) magnitude in a network of 100 neurons with fixed values of the remaining parameters. When the internal EPSP size was less than a certain value, synchronization was absent. The amount of synchronization then increased slowly as the EPSP amplitude increased until at a particular EPSP size the amount of synchronization abruptly increased, with S(5) attaining the maximum value of 100%. We also found network frequency transfer characteristics for various network sizes and found a linear dependence of firing frequency over wide ranges of the external afferent frequency, with non-linear effects at lower input frequencies. The theory may also be applied to sparsely connected networks, whose firing behaviour was found to change abruptly as the probability of a connection passed through a critical value. The analytical method was also found to be useful for a feed-forward excitatory network and a network of excitatory and inhibitory neurons.