Networks Of Excitatory Neurons Research Articles

HCN1 hyperpolarization-activated cyclic nucleotide–gated channels enhance evoked GABA release from parvalbumin-positive interneurons

Hyperpolarization-activated, cyclic nucleotide-gated (HCN) channels generate the cationic Ih current in neurons and regulate the excitability of neuronal networks. The function of HCN channels depends, in part, on their subcellular localization. Of the four HCN isoforms (HCN1-4), HCN1 is strongly expressed in the dendrites of pyramidal neurons (PNs) in hippocampal area CA1 but also in presynaptic terminals of parvalbumin-positive interneurons (PV+ INs), which provide strong inhibitory control over hippocampal activity. Yet, little is known about how HCN1 channels in these cells regulate the evoked release of the inhibitory transmitter GABA from their axon terminals. Here, we used genetic, optogenetic, electrophysiological, and imaging techniques to investigate how the electrophysiological properties of PV+ INs are regulated by HCN1, including how HCN1 activity at presynaptic terminals regulates the release of GABA onto PNs in CA1. We found that application of HCN1 pharmacological blockers reduced the amplitude of the inhibitory postsynaptic potential recorded from CA1 PNs in response to selective optogenetic stimulation of PV+ INs. Homozygous HCN1 knockout mice also show reduced IPSCs in postsynaptic cells. Finally, two-photon imaging using genetically encoded fluorescent calcium indicators revealed that HCN1 blockers reduced the probability that an extracellular electrical stimulating pulse evoked a Ca2+ response in individual PV+ IN presynaptic boutons. Taken together, our results show that HCN1 channels in the axon terminals of PV+ interneurons facilitate GABAergic transmission in the hippocampal CA1 region.

Transcriptomic cell-type specificity of local cortical circuits.

Complex neocortical functions rely on networks of diverse excitatory and inhibitory neurons. While local connectivity rules between major neuronal subclasses have been established, the specificity of connections at the level of transcriptomic subtypes remains unclear. We introduce single transcriptome assisted rabies tracing (START), a method combining monosynaptic rabies tracing and single-nuclei RNA sequencing to identify transcriptomic cell types, providing inputs to defined neuron populations. We employ START to transcriptomically characterize inhibitory neurons providing monosynaptic input to 5 different layer-specific excitatory cortical neuron populations in mouse primary visual cortex (V1). At the subclass level, we observe results consistent with findings from prior studies that resolve neuronal subclasses using antibody staining, transgenic mouse lines, and morphological reconstruction. With improved neuronal subtype granularity achieved with START, we demonstrate transcriptomic subtype specificity of inhibitory inputs to various excitatory neuron subclasses. These results establish local connectivity rules at the resolution of transcriptomic inhibitory cell types.

The recovery of parabolic avalanches in spatially subsampled neuronal networks at criticality

Scaling relationships are key in characterizing complex systems at criticality. In the brain, they are evident in neuronal avalanches—scale-invariant cascades of neuronal activity quantified by power laws. Avalanches manifest at the cellular level as cascades of neuronal groups that fire action potentials simultaneously. Such spatiotemporal synchronization is vital to theories on brain function yet avalanche synchronization is often underestimated when only a fraction of neurons is observed. Here, we investigate biases from fractional sampling within a balanced network of excitatory and inhibitory neurons with all-to-all connectivity and critical branching process dynamics. We focus on how mean avalanche size scales with avalanche duration. For parabolic avalanches, this scaling is quadratic, quantified by the scaling exponent, χ = 2, reflecting rapid spatial expansion of simultaneous neuronal firing over short durations. However, in networks sampled fractionally, χ is significantly lower. We demonstrate that applying temporal coarse-graining and increasing a minimum threshold for coincident firing restores χ = 2, even when as few as 0.1% of neurons are sampled. This correction crucially depends on the network being critical and fails for near sub- and supercritical branching dynamics. Using cellular 2-photon imaging, our approach robustly identifies χ = 2 over a wide parameter regime in ongoing neuronal activity from frontal cortex of awake mice. In contrast, the common ‘crackling noise’ approach fails to determine χ under similar sampling conditions at criticality. Our findings overcome scaling bias from fractional sampling and demonstrate rapid, spatiotemporal synchronization of neuronal assemblies consistent with scale-invariant, parabolic avalanches at criticality.

TauP301L disengages from the proteosome core complex and neurogranin coincident with enhanced neuronal network excitability

Tauopathies are characterised by the pathological accumulation of misfolded tau. The emerging view is that toxic tau species drive synaptic dysfunction and potentially tau propagation before measurable neurodegeneration is evident, but the underlying molecular events are not well defined. Human non-mutated 0N4R tau (tauWT) and P301L mutant 0N4R tau (tauP301L) were expressed in mouse primary cortical neurons using adeno-associated viruses to monitor early molecular changes and synaptic function before the onset of neuronal loss. In this model tauP301L was differentially phosphorylated relative to tauwt with a notable increase in phosphorylation at ser262. Affinity purification - mass spectrometry combined with tandem mass tagging was used to quantitatively compare the tauWT and tauP301L interactomes. This revealed an enrichment of tauP301L with ribosomal proteins but a decreased interaction with the proteasome core complex and reduced tauP301L degradation. Differences in the interaction of tauP301L with members of a key synaptic calcium-calmodulin signalling pathway were also identified, most notably, increased association with CaMKII but reduced association with calcineurin and the candidate AD biomarker neurogranin. Decreased association of neurogranin to tauP301L corresponded with the appearance of enhanced levels of extracellular neurogranin suggestive of potential release or leakage from synapses. Finally, analysis of neuronal network activity using micro-electrode arrays showed that overexpression of tauP301L promoted basal hyperexcitability coincident with these changes in the tau interactome and implicating tau in specific early alterations in synaptic function.

A mean-field model of gamma-frequency oscillations in networks of excitatory and inhibitory neurons.

Gamma oscillations are widely seen in the cerebral cortex in different states of the wake-sleep cycle and are thought to play a role in sensory processing and cognition. Here, we study the emergence of gamma oscillations at two levels, in networks of spiking neurons, and a mean-field model. At the network level, we consider two different mechanisms to generate gamma oscillations and show that they are best seen if one takes into account the synaptic delay between neurons. At the mean-field level, we show that, by introducing delays, the mean-field can also produce gamma oscillations. The mean-field matches the mean activity of excitatory and inhibitory populations of the spiking network, as well as their oscillation frequencies, for both mechanisms. This mean-field model of gamma oscillations should be a useful tool to investigate large-scale interactions through gamma oscillations in the brain.

Emergent properties in a V1-inspired network of Hodgkin–Huxley neurons

This article is devoted to the theoretical and numerical analysis of a network of excitatory and inhibitory neurons of Hodgkin–Huxley (HH) type, for which the topology is inspired by that of a single local layer of visual cortex V1. Our model relies on recent work in this area and thus combines a stochastic drive – which may be interpreted as an ambient drive for each neuron – with recurrent inputs resulting from the network activity. After a review of the dynamics of a single HH equation for both the deterministic and the stochastically driven case, we proceed to an analysis of the network. This analysis reveals emergent properties of the system such as partial synchronization and synchronization (defined here as a state of the network for which all the neurons spike within a short interval of time), correlation between excitatory and inhibitory conductances, and oscillations in the Gamma-band frequency. The collective behavior enumerated herein is observed when the input-amplitude parameter SEE measuring excitatory-to-excitatory coupling (recurrent excitation) increases to within a certain range. Of note, our work indicates a distinct mechanism for obtaining the emergent properties, some of which have been classically observed. As a consequence our article contributes to the understanding of how assemblies of inhibitory and excitatory cells interact together to produce rhythms in the network. It also aims to bring problems from neuroscience to the realm of mathematics, where they can be analyzed rigorously.

Transcranial Magnetic and Transcutaneous Spinal Cord Electrical Stimulation a Stroke-Patients Walking Correction: Blinded Clinical Randomised Study

INTRODUCTION. The impairment of motor system function due to stroke often leads to patients’ dependence on external assistance. The technique of rhythmic transcranial magnetic stimulation (rTMS) is now widely used in the restoration of impaired central nervous system (CNS) function. In recent years, there has been information about the use of transcutaneous electrical spinal cord stimulation (TSCS) in the correction of motor functions in CNS disorders of various genesis.
 AIM. To evaluate the possibilities of combined use of transcranial magnetic and transcutaneous electrical stimulation of the spinal cord in the correction of locomotor functions in patients after ischemic stroke.
 MATERIALS AND METHODS. The conducted blind clinical randomized study involved patients who had an ischemic stroke. Study participants were randomly divided into control (n = 12) and experimental (n = 9) groups. Patients in the control group received standardized neurorehabilitation techniques. The participants of the experimental group were offered standardized neurorehabilitation techniques combined with rTMS and TSCS. High-frequency rTMS was performed in the projection of the sensory-motor cortex on the side of the lesion, in the area of innervation of the lower limb. During TSCS, a stimulating electrode was placed between Th11–Th12, indifferent electrodes were placed in the region of the iliac crests, and the lumbar enlargement of the spinal cord was stimulated. The dynamics of neurological deficit was assessed using the rehabilitation routing scale, the Rivermead mobility index, the Berg balance scale, and a six-point scale for assessing muscle strength. The excitability of the neural networks of the spinal cord was determined using TSCS at the T11–T12 level, with electromyographic recording of the evoked motor responses of the muscles of the lower extremities.
 RESULTS AND DISCUSSION. The combined use of rTMS and TSCS in the rehabilitation of patients in the acute period after ischemic stroke leads to an increase in the excitability of neuronal networks of the lumbar thickening of the spinal cord, a decrease in the activation thresholds of the RF, BF, TA and GM muscles of the affected limb (by 7.7 ma, 18.3 ma, 24.8 ma and 14.2 ma, respectively). Inclusion of rTMS and TSCS in the rehabilitation course leads to a significant improvement in the rehabilitation routing scale (by 2 points), Rivermead mobility index (by 5.8 points), statokinetic control functions (balance-Berg by 12 points) and an increase in lower limb muscle strength (flexors by 5.1 points, extensors by 6.2 points).
 CONCLUSION. The use of rTMS and TSCS can be used as an additional effect within the framework of rehabilitation measures in the acute period after ischemic stroke.

Epilepsy is more than a simple seizure disorder: Causal relationships between epilepsy and its comorbidities

This review draws connections between the pathogenesis of canine epilepsy and its most commonly recognised comorbidities: cognitive impairment (CI), attention deficit hyperactivity disorder (ADHD)-like behaviour, fear and anxiety. Uni/bidirectional causalities and the possibility of a common aetiology triggering both epilepsy and the associated diseases are considered. Research on this topic is sparse in dogs, so information has been gathered and assessed from human and laboratory animal studies. Anatomical structures, functional connections, disrupted neurotransmission and neuroinflammatory processes collectively serve as a common foundation for epilepsy and its comorbidities. Specific anatomical structures, especially parts of the limbic system, such as the amygdala and the hippocampus, are involved in generating seizures, as well as cognitive- and behavioural disorders. Furthermore, disturbances in inhibitory and excitatory neurotransmission influence neuronal excitability and networks, leading to underlying brain dysfunction. Functional magnetic resonance imaging (fMRI), interictal epileptiform discharges (IEDs), and electroencephalography (EEG) have demonstrated functional brain connections that are related to the emergence of both epilepsy and its various comorbidities. Neuroinflammatory processes can either cause or be a consequence of seizures, and inflammatory mediators, oxidative stress and mitochondrial dysfunction, can equally evoke mood disorders. The extensive relationships contributing to the development and progression of seizures and comorbid cognitive and behavioural conditions illustrate the complexity of the disease that is epilepsy.

Rescue of sharp wave-ripples and prevention of network hyperexcitability in the ventral but not the dorsal hippocampus of a rat model of fragile X syndrome.

Fragile X syndrome (FXS) is a genetic neurodevelopmental disorder characterized by intellectual disability and is related to autism. FXS is caused by mutations of the fragile X messenger ribonucleoprotein 1 gene (Fmr1) and is associated with alterations in neuronal network excitability in several brain areas including hippocampus. The loss of fragile X protein affects brain oscillations, however, the effects of FXS on hippocampal sharp wave-ripples (SWRs), an endogenous hippocampal pattern contributing to memory consolidation have not been sufficiently clarified. In addition, it is still not known whether dorsal and ventral hippocampus are similarly affected by FXS. We used a Fmr1 knock-out (KO) rat model of FXS and electrophysiological recordings from the CA1 area of adult rat hippocampal slices to assess spontaneous and evoked neural activity. We find that SWRs and associated multiunit activity are affected in the dorsal but not the ventral KO hippocampus, while complex spike bursts remain normal in both segments of the KO hippocampus. Local network excitability increases in the dorsal KO hippocampus. Furthermore, specifically in the ventral hippocampus of KO rats we found an increased effectiveness of inhibition in suppressing excitation and an upregulation of α1GABAA receptor subtype. These changes in the ventral KO hippocampus are accompanied by a striking reduction in its susceptibility to induced epileptiform activity. We propose that the neuronal network specifically in the ventral segment of the hippocampus is reorganized in adult Fmr1-KO rats by means of balanced changes between excitability and inhibition to ensure normal generation of SWRs and preventing at the same time derailment of the neural activity toward hyperexcitability.

Retinoic acid regulation of homoeostatic synaptic plasticity and its relationship to cognitive disorders.

There is increasing interest in retinoic acid (RA) as a regulator of the complex biological processes underlying the cognitive functions performed by the brain. The importance of RA in brain function is underlined by the brain's high efficiency in converting vitamin A into RA. One crucial action of RA in the brain is dependent on RA receptor α (RARα) transport out of the nucleus, where it no longer regulates transcription but carries out non-genomic functions. RARα, when localised in the cytoplasm, particularly in neuronal dendrites, acts as a translational suppressor. It regulates protein translation as a crucial part of the mechanism maintaining homoeostatic synaptic plasticity, which is characterised by neuronal changes necessary to restore and balance the excitability of neuronal networks after perturbation events. Under normal conditions of neurotransmission, RARα without ligand suppresses the translation of proteins. When neural activity is reduced, RA synthesis is stimulated, and RA signalling via RARα derepresses the translation of proteins and synergistically with the fragile X mental retardation protein allows the synthesis of Ca2+ permeable α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors that re-establish normal levels of synaptic activity. Homoeostatic synaptic plasticity underlies many cognitive processes, so its impairment due to dysregulation of RA signalling may be involved in neurodevelopmental disorders such as autism, which is also associated with FMRP. A full understanding of RA signalling control of homoeostatic synaptic plasticity may point to treatments.

SCN1A-deficient excitatory neuronal networks display mutation-specific phenotypes.

Dravet syndrome is a severe epileptic encephalopathy, characterized by (febrile) seizures, behavioural problems and developmental delay. Eighty per cent of patients with Dravet syndrome have a mutation in SCN1A, encoding Nav1.1. Milder clinical phenotypes, such as GEFS+ (generalized epilepsy with febrile seizures plus), can also arise from SCN1A mutations. Predicting the clinical phenotypic outcome based on the type of mutation remains challenging, even when the same mutation is inherited within one family. This clinical and genetic heterogeneity adds to the difficulties of predicting disease progression and tailoring the prescription of anti-seizure medication. Understanding the neuropathology of different SCN1A mutations may help to predict the expected clinical phenotypes and inform the selection of best-fit treatments. Initially, the loss of Na+-current in inhibitory neurons was recognized specifically to result in disinhibition and consequently seizure generation. However, the extent to which excitatory neurons contribute to the pathophysiology is currently debated and might depend on the patient clinical phenotype or the specific SCN1A mutation. To examine the genotype-phenotype correlations of SCN1A mutations in relation to excitatory neurons, we investigated a panel of patient-derived excitatory neuronal networks differentiated on multi-electrode arrays. We included patients with different clinical phenotypes, harbouring various SCN1A mutations, along with a family in which the same mutation led to febrile seizures, GEFS+ or Dravet syndrome. We hitherto describe a previously unidentified functional excitatory neuronal network phenotype in the context of epilepsy, which corresponds to seizurogenic network prediction patterns elicited by proconvulsive compounds. We found that excitatory neuronal networks were affected differently, depending on the type of SCN1A mutation, but did not segregate according to clinical severity. Specifically, loss-of-function mutations could be distinguished from missense mutations, and mutations in the pore domain could be distinguished from mutations in the voltage sensing domain. Furthermore, all patients showed aggravated neuronal network responses at febrile temperatures compared with controls. Finally, retrospective drug screening revealed that anti-seizure medication affected GEFS+ patient- but not Dravet patient-derived neuronal networks in a patient-specific and clinically relevant manner. In conclusion, our results indicate a mutation-specific excitatory neuronal network phenotype, which recapitulates the foremost clinically relevant features, providing future opportunities for precision therapies.

Adult-Born Granule Cells Contribute to Dentate Gyrus Circuit Reorganization after Traumatic Brain Injury.

Post-traumatic epilepsy (PTE) is a serious consequence of traumatic brain injury (TBI). PTE develops following a latent postinjury period during which alterations in neuronal network excitability are thought to occur, leading to the development of recurrent and unprovoked seizures. In particular,

Chaotic dynamics in spatially distributed neuronal networks generate population-wide shared variability.

Neural activity in the cortex is highly variable in response to repeated stimuli. Population recordings across the cortex demonstrate that the variability of neuronal responses is shared among large groups of neurons and concentrates in a low dimensional space. However, the source of the population-wide shared variability is unknown. In this work, we analyzed the dynamical regimes of spatially distributed networks of excitatory and inhibitory neurons. We found chaotic spatiotemporal dynamics in networks with similar excitatory and inhibitory projection widths, an anatomical feature of the cortex. The chaotic solutions contain broadband frequency power in rate variability and have distance-dependent and low-dimensional correlations, in agreement with experimental findings. In addition, rate chaos can be induced by globally correlated noisy inputs. These results suggest that spatiotemporal chaos in cortical networks can explain the shared variability observed in neuronal population responses.

Unitary synaptic responses of parvalbumin interneurons evoked by excitatory neurons in the mouse barrel cortex.

The mammalian cortex integrates and processes information to transform sensory inputs into perceptions and motor outputs. These operations are performed by networks of excitatory and inhibitory neurons distributed through the cortical layers. Parvalbumin interneurons (PVIs) are the most abundant type of inhibitory cortical neuron. With axons projecting within and between layers, PVIs supply feedforward and feedback inhibition to control and modulate circuit function. Distinct populations of excitatory neurons recruit different PVI populations, but the specializations of these synapses are poorly understood. Here, we targeted a genetically encoded hybrid voltage sensor to PVIs and used fluorescence imaging in mouse somatosensory cortex slices to record their voltage changes. Stimulating a single visually identified excitatory neuron with small-tipped theta-glass electrodes depolarized multiple PVIs, and a common threshold suggested that stimulation elicited unitary synaptic potentials in response to a single excitatory neuron. Excitatory neurons depolarized PVIs in multiple layers, with the most residing in the layer of the stimulated neuron. Spiny stellate cells depolarized PVIs more strongly than pyramidal cells by up to 77%, suggesting a greater role for stellate cells in recruiting PVI inhibition and controlling cortical computations. Response half-width also varied between different excitatory inputs. These results demonstrate functional differences between excitatory synapses on PVIs.

CASK loss of function differentially regulates neuronal maturation and synaptic function in human induced cortical excitatory neurons

SummaryLoss-of-function (LOF) mutations in CASK cause severe developmental phenotypes, including microcephaly with pontine and cerebellar hypoplasia, X-linked intellectual disability, and autism. Unraveling the pathological mechanisms of CASK-related disorders has been challenging owing to limited human cellular models to study the dynamic roles of this molecule during neuronal maturation and synapse development. Here, we investigate cell-autonomous functions of CASK in cortical excitatory induced neurons (iNs) generated from CASK knockout (KO) isogenic human embryonic stem cells (hESCs) using gene expression, morphometrics, and electrophysiology. While immature CASK KO iNs show robust neuronal outgrowth, mature CASK KO iNs display severe defects in synaptic transmission and synchronized network activity without compromising neuronal morphology and synapse numbers. In the developing human cortical excitatory neurons, CASK functions to promote both structural integrity and establishment of cortical excitatory neuronal networks. These results lay the foundation for future studies identifying suppressors of such phenotypes relevant to human patients.

Regimes and mechanisms of transient amplification in abstract and biological neural networks.

Neuronal networks encode information through patterns of activity that define the networks’ function. The neurons’ activity relies on specific connectivity structures, yet the link between structure and function is not fully understood. Here, we tackle this structure-function problem with a new conceptual approach. Instead of manipulating the connectivity directly, we focus on upper triangular matrices, which represent the network dynamics in a given orthonormal basis obtained by the Schur decomposition. This abstraction allows us to independently manipulate the eigenspectrum and feedforward structures of a connectivity matrix. Using this method, we describe a diverse repertoire of non-normal transient amplification, and to complement the analysis of the dynamical regimes, we quantify the geometry of output trajectories through the effective rank of both the eigenvector and the dynamics matrices. Counter-intuitively, we find that shrinking the eigenspectrum’s imaginary distribution leads to highly amplifying regimes in linear and long-lasting dynamics in nonlinear networks. We also find a trade-off between amplification and dimensionality of neuronal dynamics, i.e., trajectories in neuronal state-space. Networks that can amplify a large number of orthogonal initial conditions produce neuronal trajectories that lie in the same subspace of the neuronal state-space. Finally, we examine networks of excitatory and inhibitory neurons. We find that the strength of global inhibition is directly linked with the amplitude of amplification, such that weakening inhibitory weights also decreases amplification, and that the eigenspectrum’s imaginary distribution grows with an increase in the ratio between excitatory-to-inhibitory and excitatory-to-excitatory connectivity strengths. Consequently, the strength of global inhibition reveals itself as a strong signature for amplification and a potential control mechanism to switch dynamical regimes. Our results shed a light on how biological networks, i.e., networks constrained by Dale’s law, may be optimised for specific dynamical regimes.

Modeling cortical synaptic effects of anesthesia and their cholinergic reversal.

General anesthetics work through a variety of molecular mechanisms while resulting in the common end point of sedation and loss of consciousness. Generally, the administration of common anesthetics induces reduction in synaptic excitation while promoting synaptic inhibition. Exogenous modulation of the anesthetics’ synaptic effects can help determine the neuronal pathways involved in anesthesia. For example, both animal and human studies have shown that exogenously induced increases in acetylcholine in the brain can elicit wakeful-like behavior despite the continued presence of the anesthetic. However, the underlying mechanisms of anesthesia reversal at the cellular level have not been investigated. Here we apply a computational model of a network of excitatory and inhibitory neurons to simulate the network-wide effects of anesthesia, due to changes in synaptic inhibition and excitation, and their reversal by cholinergic activation through muscarinic receptors. We use a differential evolution algorithm to fit model parameters to match measures of spiking activity, neuronal connectivity, and network dynamics recorded in the visual cortex of rodents during anesthesia with desflurane in vivo. We find that facilitating muscarinic receptor effects of acetylcholine on top of anesthetic-induced synaptic changes predicts the reversal of anesthetic suppression of neurons’ spiking activity, functional connectivity, as well as pairwise and population interactions. Thus, our model predicts a specific neuronal mechanism for the cholinergic reversal of anesthesia consistent with experimental behavioral observations.

Mechanism of carbachol-induced 40 Hz gamma oscillations and the effects of NMDA activation on oscillatory dynamics in a model of the CA3 subfield of the hippocampus

Gamma oscillations are a prominent feature of various neural systems, including the CA3 subfield of the hippocampus. In CA3, in vitro carbachol application induces ∼40 Hz gamma oscillations in the network of glutamatergic excitatory pyramidal neurons (PNs) and local GABAergic inhibitory neurons (INs). Activation of NMDA receptors within CA3 leads to an increase in the frequency of carbachol-induced oscillations to ∼60 Hz, a broadening of the distribution of individual oscillation cycle frequencies, and a decrease in the time lag between PN and IN spike bursts. In this work, we develop a biophysical integrate-and-fire model of the CA3 subfield, we show that the dynamics of our model are in concordance with physiological observations, and we provide computational support for the hypothesis that the ‘E-I’ mechanism is responsible for the emergence of ∼40 Hz gamma oscillations in the absence of NMDA activation. We then incorporate NMDA receptors into our CA3 model, and we show that our model exhibits the increase in gamma oscillation frequency, broadening of the cycle frequency distribution, and decrease in the time lag between PN and IN spike bursts observed experimentally. Remarkably, we find an inverse relationship in our model between the net NMDA current delivered to PNs and INs in an oscillation cycle and cycle frequency. Furthermore, we find a disparate effect of NMDA receptors on PNs versus INs – we show that NMDA receptors on INs tend to increase oscillation frequency, while NMDA receptors on PNs tend to slightly decrease or not affect oscillation frequency. We find that these observations can be explained if NMDA activity above a threshold level causes a shift in the mechanism underlying gamma oscillations; in the absence of NMDA receptors, the ‘E-I’ mechanism is primarily responsible for the generation of gamma oscillations (at 40 Hz), while when NMDA receptors are active, the mechanism of gamma oscillations shifts to the ‘I-I’ mechanism, and we argue that within the ‘I-I’ regime (which displays a higher baseline oscillation frequency of ∼60 Hz), slight changes in the level of NMDA activity are inversely related to cycle frequency.

A Research on the Role and Mechanism of N-Methyl-D-Aspartate Receptors in the Effects of Silver Nanoparticles on the Electrical Excitability of Hippocampal Neuronal Networks

The purpose of this paper is to explore the role and mechanism of N-Methyl-D-Aspartate (NMDA) receptors in the effects of silver nanoparticles (SNPs) on the electrical excitability of hippocampal neuronal networks. First, the cytotoxicity of different concentrations of SNPs was evaluated and screened by MTT experiment, then the Voltage Threshold Measurement Method (VTMM) was employed to study the effects of SNPs on the electrical excitability of hippocampal neuronal networks under non-cytotoxic (5 μM) and cytotoxic (100 μM) concentrations after different action times. The role of NMDA receptors in the effects of SNPs on the electrical excitability of hippocampal neuronal networks was investigated through the NMDA receptor antagonist MK-801. Then, the effects of SNPs on the number of NMDA receptors and the Ca2+ content in hippocampal neurons were further investigated, and the relationship between these changes and neuronal networks electrical excitability was discussed. The results of voltage threshold (VTh) test showed that non-cytotoxic 5 μM SNPs has an excitatory effect on hippocampal neuronal networks, while the effect of cytotoxic 100 μM SNPs gradually changed from excitatory to inhibitory with the extension of action time. It was found that SNPs could increase the electrical excitability of neuronal networks by activating NMDA receptors through the experiments with MK-801 antagonists. Moreover, the fluorescent staining experiments showed that the activation of NMDA receptors by SNPs can lead to an increase in the intracellular Ca2+ content, and then trigger a negative feedback regulation mechanism of neurons between the number of NMDA receptors and intracellular Ca2+ content. The high Ca2+ content in neurons can also decrease neurons’ cell viability, which in turn leads to changes in the electrical excitability of the neuronal networks.

Interlayer Connectivity Affects the Coherence Resonance and Population Activity Patterns in Two-Layered Networks of Excitatory and Inhibitory Neurons.

The firing patterns of neuronal populations often exhibit emergent collective oscillations, which can display substantial regularity even though the dynamics of individual elements is very stochastic. One of the many phenomena that is often studied in this context is coherence resonance, where additional noise leads to improved regularity of spiking activity in neurons. In this work, we investigate how the coherence resonance phenomenon manifests itself in populations of excitatory and inhibitory neurons. In our simulations, we use the coupled FitzHugh-Nagumo oscillators in the excitable regime and in the presence of neuronal noise. Formally, our model is based on the concept of a two-layered network, where one layer contains inhibitory neurons, the other excitatory neurons, and the interlayer connections represent heterotypic interactions. The neuronal activity is simulated in realistic coupling schemes in which neurons within each layer are connected with undirected connections, whereas neurons of different types are connected with directed interlayer connections. In this setting, we investigate how different neurophysiological determinants affect the coherence resonance. Specifically, we focus on the proportion of inhibitory neurons, the proportion of excitatory interlayer axons, and the architecture of interlayer connections between inhibitory and excitatory neurons. Our results reveal that the regularity of simulated neural activity can be increased by a stronger damping of the excitatory layer. This can be accomplished with a higher proportion of inhibitory neurons, a higher fraction of inhibitory interlayer axons, a stronger coupling between inhibitory axons, or by a heterogeneous configuration of interlayer connections. Our approach of modeling multilayered neuronal networks in combination with stochastic dynamics offers a novel perspective on how the neural architecture can affect neural information processing and provide possible applications in designing networks of artificial neural circuits to optimize their function via noise-induced phenomena.