Synchronous Firing Research Articles

Mefloquine-induced conformational shift in Cx36 N-terminal helix leading to channel closure mediated by lipid bilayer

Connexin 36 (Cx36) forms interneuronal gap junctions, establishing electrical synapses for rapid synaptic transmission. In disease conditions, inhibiting Cx36 gap junction channels (GJCs) is beneficial, as it prevents abnormal synchronous neuronal firing and apoptotic signal propagation, mitigating seizures and progressive cell death. Here, we present cryo-electron microscopy structures of human Cx36 GJC in complex with known channel inhibitors, such as mefloquine, arachidonic acid, and 1-hexanol. Notably, these inhibitors competitively bind to the binding pocket of the N-terminal helices (NTH), inducing a conformational shift from the pore-lining NTH (PLN) state to the flexible NTH (FN) state. This leads to the obstruction of the channel pore by flat double-layer densities of lipids. These studies elucidate the molecular mechanisms of how Cx36 GJC can be modulated by inhibitors, providing valuable insights into potential therapeutic applications.

Influences of short-term and long-term plasticity of memristive synapse on firing activity of neuronal network

Abstract Synaptic plasticity can greatly affect the firing behavior of neural networks, and it specifically refers to changes in the strength, morphology, and function of synaptic connections. In this paper, a novel memristor model, which can be configured as a volatile and nonvolatile memristor by adjusting its internal parameter, is proposed to mimic the short-term and long-term synaptic plasticity. Then, a bi-neuron network model, with the proposed memristor serving as a coupling synapse and the external electromagnetic radiation being emulated by the flux-controlled memristors, is established to elucidate the effects of short-term and long-term synaptic plasticity on firing activity of the neuron network. The resultant 7D neuron network has no equilibrium point and its hidden dynamical behavior is revealed by phase diagram, time series, bifurcation diagram, Lyapunov exponent spectrum and two-dimensional dynamic map. Our results show the short-term and long-term plasticity can induce different bifurcation scenarios when the coupling strength increases. In addition, memristor synaptic plasticity has a great influence on the distribution of firing patterns in the parameter space. More interestingly, when exploring the synchronous firing behavior of two neurons, the two neurons can gradually achieve phase synchronization as the coupling strength increases along the opposite directions under two different memory attributes. Finally, a microcontroller-based hardware system is implemented to verify the numerical simulation results.

Transition and bifurcation mechanism of firing activities in memristor synapse-coupled Hindmarsh–Rose bi-neuron model

Memristor, especially the locally active one, is widely used in emulating the synapse-inspired activities in neural networks, in which the connection between memristor properties and neuronal electrical activities requires further investigation. In this paper, a bi-neuron model is constructed by bi-directionally connecting a locally active memristor between the membrane potentials of two deterministic 3D HR neuron models. Complex spiking/bursting firing activities and their transitions are disclosed under different memristor control parameters. The bifurcation mechanisms of the revealed synchronous and asynchronous firing activities are explored inside each individual neuron by taking the externally input state variables as modulation parameters. These results demonstrate the crucial effect of the locally active memristor synapse on firing activities of its coupled network. FPGA-based digital circuit experiment is finally performed to verify the numerical results. This research is beneficial to understanding, control and application of firing activities in neural networks.

Neuron configuration enhances the synchronization dynamics in ring networks with heterogeneous firing patterns

Neuron synchronization is fundamental for brain dynamics. While several efforts have been made to understand neuron coupling between tonic and bursting neurons, the position of neurons in a neural network and its relationship with synchronization is not fully understood. This work investigates the impact of neuronal heterogeneity on firing pattern transitions and synchronization in networks comprising tonic and bursting neurons. Using the Huber-Braun model, we explore two configurations: one with neurons grouped closely and another with maximal separation. Our findings reveal that while increased coupling strength generally promotes synchronization, the specific mix of neuron types and their spatial configuration crucially modulate both synchronization and firing pattern transitions, leading to phenomena such as cluster synchronization and global phase synchrony. The results indicate that the configuration with maximal separation and with mostly bursting neurons synchronizes more quickly. Firing pattern transitions are also configuration-dependent. For example, in the network with half tonic and half bursting, the configuration grouped closely undergoes diverse complex dynamics transition in the synchronized state, while the other configuration synchronize with chaotic bursting dynamics. Behaviors like cluster synchronization are observed in this network. The study underscores the significance of considering neuronal heterogeneity in understanding network dynamics.

Estradiol elicits distinct firing patterns in arcuate nucleus kisspeptin neurons of females through altering ion channel conductances.

Hypothalamic kisspeptin (Kiss1) neurons are vital for pubertal development and reproduction. Arcuate nucleus Kiss1 (Kiss1ARH) neurons are responsible for the pulsatile release of Gonadotropin-releasing Hormone (GnRH). In females, the behavior of Kiss1ARH neurons, expressing Kiss1, Neurokinin B (NKB), and Dynorphin (Dyn), varies throughout the ovarian cycle. Studies indicate that 17β-estradiol (E2) reduces peptide expression but increases Vglut2 mRNA and glutamate neurotransmission in these neurons, suggesting a shift from peptidergic to glutamatergic signaling. To investigate this shift, we combined transcriptomics, electrophysiology, and mathematical modeling. Our results demonstrate that E2 treatment upregulates the mRNA expression of voltage-activated calcium channels, elevating the whole-cell calcium current and that contribute to high-frequency burst firing. Additionally, E2 treatment decreased the mRNA levels of Canonical Transient Receptor Potential (TPRC) 5 and G protein-coupled K+ (GIRK) channels. When TRPC5 channels in Kiss1ARH neurons were deleted using CRISPR, the slow excitatory postsynaptic potential (sEPSP) was eliminated. Our data enabled us to formulate a biophysically realistic mathematical model of the Kiss1ARH neuron, suggesting that E2 modifies ionic conductances in Kiss1ARH neurons, enabling the transition from high frequency synchronous firing through NKB-driven activation of TRPC5 channels to a short bursting mode facilitating glutamate release. In a low E2 milieu, synchronous firing of Kiss1ARH neurons drives pulsatile release of GnRH, while the transition to burst firing with high, preovulatory levels of E2 would facilitate the GnRH surge through its glutamatergic synaptic connection to preoptic Kiss1 neurons.

Histone variant macroH2A1 regulates synchronous firing of replication origins in the inactive X chromosome.

MacroH2A has been linked to transcriptional silencing, cell identity, and is a hallmark of the inactive X chromosome (Xi). However, it remains unclear whether macroH2A plays a role in DNA replication. Using knockdown/knockout cells for each macroH2A isoform, we show that macroH2A-containing nucleosomes slow down replication progression rate in the Xi reflecting the higher nucleosome stability. Moreover, macroH2A1, but not macroH2A2, regulates the number of nano replication foci in the Xi, and macroH2A1 downregulation increases DNA loop sizes corresponding to replicons. This relates to macroH2A1 regulating replicative helicase loading during G1 by interacting with it. We mapped this interaction to a phenylalanine in macroH2A1 that is not conserved in macroH2A2 and the C-terminus of Mcm3 helicase subunit. We propose that macroH2A1 enhances the licensing of pre-replication complexes via DNA helicase interaction and loading onto the Xi.

Neuromodulatory Compensation of Cortical Neural Activity on Electrodeposited Pt/Ir Modified Microelectrode Arrays for Temperature Transients.

Temperature has a profound influence on various neuromodulation processes and has emerged as a focal point. However, the effects of acute environmental temperature fluctuations on cultured cortical networks have been inadequately elucidated. To bridge this gap, we have developed a brain-on-a-chip platform integrating cortical networks and electrodeposited Pt/Ir modified microelectrode arrays (MEAs) with 3D-printed bear-shaped triple chambers, facilitating control of temperature transients. This innovative system administers thermal stimuli while concurrently monitoring neuronal activity, including spikes and local field potentials, from 60 microelectrodes (diameter: 30 μm; impedance: 9.34 ± 1.37 kΩ; and phase delay: -45.26 ± 2.85°). Temperature transitions of approximately ±10 °C/s were applied to cortical networks on MEAs via in situ perfusion within the triple chambers. Subsequently, we examined the spatiotemporal dynamics of the brain-on-a-chip under temperature regulation at both the group level (neuronal population) and their interactions (network dynamics) and the individual level (cellular activity). Specifically, we found that after the temperature reduction neurons enhanced the overall information transmission efficiency of the network through synchronous firing to compensate for the decreased efficiency of single-cell level information transmission, in contrast to temperature elevation. By leveraging the integration of high-performance MEAs with perfusion chambers, this investigation provides a comprehensive understanding of the impact of temperature on the spatiotemporal dynamics of neural networks, thereby facilitating future exploration of the intricate interplay between temperature and brain function.

Regulation of spike propagation in feedforward neural networks through short-term synaptic plasticity

Both factors, multilayer Feedforward Neural Networks (FFNs) and short-term synaptic plasticity (STP), are considered crucial in the transmission and processing of neural signals. In this study, a 10-layer FFN was constructed to study the impact of STP on neuronal activity propagation. Neurons within the same layer do not have direct connections; instead, neurons between adjacent layers are randomly connected with a specific probability. The findings indicate that synaptic plasticity can regulate the network’s firing rate, synchronization, and output firing rate gain. Notably, short-term facilitation (STF) allows the network to exhibit high-pass filtering, while short-term depression (STD) achieves low-pass filtering. Combining STF and STD synapses in the FFN broadens the range of input firing rates effectively transmitted by the network. Increasing the proportion of STD-dominated synapses enhances the gain of low firing rate signals but reduces the gain of high firing rate signals. Adjusting the mix of synapses enables the network to implement bandpass filtering and control firing rate gain. These results underscore the effectiveness of modulating short-term synaptic plasticity in regulating neural activity propagation in FFNs.

Specialized connectivity of molecular layer interneuron subtypes leads to disinhibition and synchronous inhibition of cerebellar Purkinje cells

Molecular layer interneurons (MLIs) account for approximately 80% of the inhibitory interneurons in the cerebellar cortex and are vital to cerebellar processing. MLIs are thought to primarily inhibit Purkinje cells (PCs) and suppress the plasticity of synapses onto PCs. MLIs also inhibit, and are electrically coupled to, other MLIs, but the functional significance of these connections is not known. Here, we find that two recently recognized MLI subtypes, MLI1 and MLI2, have a highly specialized connectivity that allows them to serve distinct functional roles. MLI1s primarily inhibit PCs, are electrically coupled to each other, fire synchronously with other MLI1s on the millisecond timescale invivo, and synchronously pause PC firing. MLI2s are not electrically coupled, primarily inhibit MLI1s and disinhibit PCs, and are well suited to gating cerebellar-dependent behavior and learning. The synchronous firing of electrically coupled MLI1s and disinhibition provided by MLI2s require a major re-evaluation of cerebellar processing.

Purinergic Signalling Mediates Aberrant Excitability of Developing Neuronal Circuits in the Fmr1 Knockout Mouse Model.

Neuronal hyperexcitability within developing cortical circuits is a common characteristic of several heritable neurodevelopmental disorders, including Fragile X Syndrome (FXS), intellectual disability and autism spectrum disorders (ASD). While this aberrant circuitry is typically studied from a neuron-centric perspective, glial cells secrete soluble factors that regulate both neurite extension and synaptogenesis during development. The nucleotide-mediated purinergic signalling system is particularly instrumental in facilitating these effects. We recently reported that within a FXS animal model, theFmr1 KO mouse, the purinergic signalling system is upregulated in cortical astrocytes leading to altered secretion of synaptogenic and plasticity-related proteins. In this study, we examined whether elevated astrocyte purinergic signalling also impacts neuronal morphology and connectivity of Fmr1 KO cortical neurons. Here, we found that conditioned media from primary Fmr1 KO astrocytes was sufficient to enhance neurite extension and complexity of both wildtype and Fmr1 KO neurons to a similar degree as UTP-mediated outgrowth. Significantly enhanced firing was also observed in Fmr1 KO neuron-astrocyte co-cultures grown on microelectrode arrays but was associated with large deficits in firing synchrony. The selective P2Y2 purinergic receptor antagonist AR-C 118925XX effectively normalized much of the aberrant Fmr1 KO activity, designating P2Y2 as a potential therapeutic target in FXS. These results not only demonstrate the importance of astrocyte soluble factors in the development of neural circuitry, but also show that P2Y purinergic receptors play a distinct role in pathological FXS neuronal activity.

GABAergic interneuron diversity and organization are crucial for the generation of human-specific functional neural networks in cerebral organoids.

This mini review investigates the importance of GABAergic interneurons for the network function of human-induced pluripotent stem cells (hiPSC)-derived brain organoids. The presented evidence suggests that the abundance, diversity and three-dimensional cortical organization of GABAergic interneurons are the primary elements responsible for the creation of synchronous neuronal firing patterns. Without intricate inhibition, coupled oscillatory patterns cannot reach a sufficient complexity to transfer spatiotemporal information constituting physiological network function. Furthermore, human-specific brain network function seems to be mediated by a more complex and interconnected inhibitory structure that remains developmentally flexible for a longer period when compared to rodents. This suggests that several characteristics of human brain networks cannot be captured by rodent models, emphasizing the need for model systems like organoids that adequately mimic physiological human brain function in vitro.

Spike synchrony as a measure of Gestalt structure

The function of spike synchrony is debatable: some researchers view it as a mechanism for binding perceptual features, others – as a byproduct of brain activity. We argue for an alternative computational role: synchrony can estimate the prior probability of incoming stimuli. In V1, this can be achieved by comparing input with previously acquired visual experience, which is encoded in plastic horizontal intracortical connections. V1 connectivity structure can encode the acquired visual experience in the form of its aggregate statistics. Since the aggregate statistics of natural images tend to follow the Gestalt principles, we can assume that V1 is more often exposed to Gestalt-like stimuli, and this is manifested in its connectivity structure. At the same time, the connectivity structure has an impact on spike synchrony in V1. We used a spiking model with V1-like connectivity to demonstrate that spike synchrony reflects the Gestalt structure of the stimulus. We conducted simulation experiments with three Gestalt laws: proximity, similarity, and continuity, and found substantial differences in firing synchrony for stimuli with varying degrees of Gestalt-likeness. This allows us to conclude that spike synchrony indeed reflects the Gestalt structure of the stimulus, which can be interpreted as a mechanism for prior probability estimation.

Learning and Neural Activity: Beyond Localization

Learning is classified into two types: "classical conditioning," which modifies simple reflexes, and "operant conditioning," which modifies complex voluntary behaviors. The neural circuits underlying these two types differ significantly. During the learning process of operant conditioning tasks, various changes in firing rate and firing synchrony of neurons can be observed across multiple brain regions. Additionally, neuronal firing rate and synchrony in several brain regions can be voluntarily controlled through operant conditioning. Consequently, it is evident that neurons in widespread brain regions have the potential for plastic changes to facilitate learning. It may be suggested that the learning of complex voluntary behaviors is underlined by widespread dynamic changes in neural activity and is not restricted to only a few brain regions.

Brain-Region-Specific Genes Form the Major Pathways Featuring Their Basic Functional Role: Their Implication in Animal Chronic Stress Model.

The analysis of RNA-Sec data from murine bulk tissue samples taken from five brain regions associated with behavior and stress response was conducted. The focus was on the most contrasting brain region-specific genes (BRSG) sets in terms of their expression rates. These BRSGs are identified as genes with a distinct outlying (high) expression rate in a specific region compared to others used in the study. The analysis suggested that BRSG sets form non-randomly connected compact gene networks, which correspond to the major neuron-mediated functional processes or pathways in each brain region. The number of BRSGs and the connection rate were found to depend on the heterogeneity and coordinated firing rate of neuron types in each brain region. The most connected pathways, along with the highest BRSG number, were observed in the Striatum, referred to as Medium Spiny Neurons (MSNs), which make up 95% of neurons and exhibit synchronous firing upon dopamine influx. However, the Ventral Tegmental Area/Medial Raphe Nucleus (VTA/MRN) regions, although primarily composed of monoaminergic neurons, do not fire synchronously, leading to a smaller BRSG number. The Hippocampus (HPC) region, on the other hand, displays significant neuronal heterogeneity, with glutamatergic neurons being the most numerous and synchronized. Interestingly, the two monoaminergic regions involved in the study displayed a common BRSG subnetwork architecture, emphasizing their proximity in terms of axonal throughput specifics and high-energy metabolism rates. This finding suggests the concerted evolution of monoaminergic neurons, leading to unique adaptations at the genic repertoire scale. With BRSG sets, we were able to highlight the contrasting features of the three groups: control, depressive, and aggressive mice in the animal chronic stress model. Specifically, we observed a decrease in serotonergic turnover in both the depressed and aggressive groups, while dopaminergic emission was high in both groups. There was also a notable absence of dopaminoceptive receptors on the postsynaptic membranes in the striatum in the depressed group. Additionally, we confirmed that neurogenesis BRSGs are specific to HPC, with the aggressive group showing attenuated neurogenesis rates compared to the control/depressive groups. We also confirmed that immune-competent cells like microglia and astrocytes play a crucial role in depressed phenotypes, including mitophagy-related gene Prkcd. Based on this analysis, we propose the use of BRSG sets as a suitable framework for evaluating case-control group-wise assessments of specific brain region gene pathway responses.

Stretch-Induced Injury Affects Cortical Neuronal Networks in a Time- and Severity-Dependent Manner.

Traumatic brain injury (TBI) is the leading cause of accident-related death and disability in the world and can lead to long-term neuropsychiatric symptoms, such as a decline in cognitive function and neurodegeneration. TBI includes primary and secondary injury, with head trauma and deformation of the brain caused by the physical force of the impact as primary injury, and cellular and molecular cascades that lead to cell death as secondary injury. Currently, there is no treatment for TBI-induced cell damage and neural circuit dysfunction in the brain, and thus, it is important to understand the underlying cellular mechanisms that lead to cell damage. In the current study, we use stretchable microelectrode arrays (sMEAs) to model the primary injury of TBI to study the electrophysiological effects of physically injuring cortical cells. We recorded electrophysiological activity before injury and then stretched the flexible membrane of the sMEAs to injure the cells to varying degrees. At 1, 24, and 72h post-stretch, we recorded activity to analyze differences in spike rate, Fano factor, burstlet rate, burstlet width, synchrony of firing, local network efficiency, and Q statistic. Our results demonstrate that mechanical injury changes the firing properties of cortical neuron networks in culture in a time- and severity-dependent manner. Our results suggest that changes to electrophysiological properties after stretch are dependent on the strength of synchronization between neurons prior to injury.

Implications of variable synaptic weights for rate and temporal coding of cerebellar outputs.

Purkinje cell (PC) synapses onto cerebellar nuclei (CbN) neurons allow signals from the cerebellar cortex to influence the rest of the brain. PCs are inhibitory neurons that spontaneously fire at high rates, and many PC inputs are thought to converge onto each CbN neuron to suppress its firing. It has been proposed that PCs convey information using a rate code, a synchrony and timing code, or both. The influence of PCs on CbN neuron firing was primarily examined for the combined effects of many PC inputs with comparable strengths, and the influence of individual PC inputs has not been extensively studied. Here, we find that single PC to CbN synapses are highly variable in size, and using dynamic clamp and modeling we reveal that this has important implications for PC-CbN transmission. Individual PC inputs regulate both the rate and timing of CbN firing. Large PC inputs strongly influence CbN firing rates and transiently eliminate CbN firing for several milliseconds. Remarkably, the refractory period of PCs leads to a brief elevation of CbN firing prior to suppression. Thus, individual PC-CbN synapses are suited to concurrently convey rate codes and generate precisely timed responses in CbN neurons. Either synchronous firing or synchronous pauses of PCs promote CbN neuron firing on rapid time scales for nonuniform inputs, but less effectively than for uniform inputs. This is a secondary consequence of variable input sizes elevating the baseline firing rates of CbN neurons by increasing the variability of the inhibitory conductance. These findings may generalize to other brain regions with highly variable inhibitory synapse sizes.

The Effect of Fire on Multiple Tree Species in the Eastern Deciduous Forest

Fire is a disturbance that serves to maintain the diverse mosaic of vegetation in the Eastern Deciduous Forest. However, our ability to reconstruct fire occurrence from hardwood tree scars still lags far behind our expertise in reconstructing fire history from conifers in the western United States. This study examines the fidelity of fire scaring in multiple tree species in the Big Oaks National Wildlife Refuge in Indiana, which is located in the central hardwood region of the Eastern Deciduous Forest. All 15 species, except for red oak, showed evidence of past fires, and most samples recorded multiple fire events. No fire scars were recorded in the latewood of the samples. Most of the fires scars occurred in the earlywood (May) suggesting the dormant season fires are likely associated with fires in March to April before the growing season begins. No synchronous fires were recorded across all sites, but fires occurred in 1981, 1982, 1984, 1985, and 1988 across multiple sites. This suggests that these were larger spreading fires. Establishment pulses were documented in association with fire events in 1981, 1984, and 1995, suggesting that fire may benefit the establishment or root sprouting of some hardwood species. Fourteen of the fifteen species that we sampled preserved fire scars, suggesting that the diverse suite of species in the Eastern Deciduous Forest is a viable sampling pool for examining fire history across this forest type.

Synchronization and firing mode transition of two neurons in a bilateral auditory system driven by a high–low frequency signal

The FitzHugh–Nagumo neuron circuit integrates a piezoelectric ceramic to form a piezoelectric sensing neuron, which can capture external sound signals and simulate the auditory neuron system. Two piezoelectric sensing neurons are coupled by a parallel circuit consisting of a Josephson junction and a linear resistor, and a binaural auditory system is established. Considering the non-singleness of external sound sources, the high–low frequency signal is used as the input signal to study the firing mode transition and synchronization of this system. It is found that the angular frequency of the high–low frequency signal is a key factor in determining whether the dynamic behaviors of two coupled neurons are synchronous. When they are in synchronization at a specific angular frequency, the changes in physical parameters of the input signal and the coupling strength between them will not destroy their synchronization. In addition, the firing mode of two coupled auditory neurons in synchronization is affected by the characteristic parameters of the high–low frequency signal rather than the coupling strength. The asynchronous dynamic behavior and variations in firing modes will harm the auditory system. These findings could help determine the causes of hearing loss and devise functional assistive devices for patients.

Ictal activity is sustained by the estrogen receptor β during the estrous cycle

Catamenial epilepsy, defined as a periodicity of seizure exacerbation during the menstrual cycle, affects up to 70 % of epileptic women. Seizures in these patients are often non-responsive to medication; however, our understanding of the relation between menstrual cycle and seizure generation (i.e. ictogenesis) remains limited. We employed here field potential recordings in the in vitro 4-aminopyridine model of epileptiform synchronization in female mice (P60–P130) and found that: (i) the estrous phase favors ictal activity in the entorhinal cortex; (ii) these ictal discharges display an onset pattern characterised by the presence of chirps that are thought to mirror synchronous interneuron firing; and (iii) blocking estrogen receptor β-mediated signaling reduces ictal discharge duration. Our findings indicate that the duration of 4AP-induced ictal discharges, in vitro, increases during the estrous phase, which corresponds to the human peri-ovulatory period. We propose that these effects are caused by the presumptive enhancement of interneuron excitability due to increased estrogen receptor β-mediated signaling.

How synaptic function controls critical transitions in spiking neuron networks: insight from a Kuramoto model reduction.

The dynamics of synaptic interactions within spiking neuron networks play a fundamental role in shaping emergent collective behavior. This paper studies a finite-size network of quadratic integrate-and-fire neurons interconnected via a general synaptic function that accounts for synaptic dynamics and time delays. Through asymptotic analysis, we transform this integrate-and-fire network into the Kuramoto-Sakaguchi model, whose parameters are explicitly expressed via synaptic function characteristics. This reduction yields analytical conditions on synaptic activation rates and time delays determining whether the synaptic coupling is attractive or repulsive. Our analysis reveals alternating stability regions for synchronous and partially synchronous firing, dependent on slow synaptic activation and time delay. We also demonstrate that the reduced microscopic model predicts the emergence of synchronization, weakly stable cyclops states, and non-stationary regimes remarkably well in the original integrate-and-fire network and its theta neuron counterpart. Our reduction approach promises to open the door to rigorous analysis of rhythmogenesis in networks with synaptic adaptation and plasticity.