Synchronous Firing Research Articles

Intrathecal delivery of BDNF to the lumbar spinal cord modulates lumbar interneurons activity in a feline model of spinal cord injury.

In the present study, we examined the correlations between the recovery of stepping obtained with intrathecal BDNF delivery to the lumbar spinal cord and the firing of the lumbar spinal interneurons in a feline model of SCI. In-vivo extracellular recordings of spinal neurons were conducted using two 64-channel microelectrode arrays inserted in the intermediate zone of the L3-L7 segments of cats spinalized at the T11-T12 level that received either saline or BDNF delivered intrathecally to the lumbar cisterna via an implanted minipump. Interneuronal activity was explored in terms of averaged neuronal firing properties and in terms of spike train interactions. With respect to averaged neuronal firing properties, we observed a significant increase in firing frequency in BNDF-treated animals and a similar distribution of the units' preferred phase of firing relative to the step cycle between the groups. With respect to spike train interactions, we observed higher synchrony of firing in BDNF-treated animals as well as less dependency on the unit's past firing. Studies conducted in feline models of complete spinal cord injury (SCI) show a gradual recovery of hindlimb stepping after intensive treadmill training. Similarly, delivery of neurotrophins such as Brain Derived Neurotrophic Factor (BDNF) or Neurotrophin-3 (NT-3) to the injury site via cellular transplant or via implantable mini-pump to the lumbar cisterna has been shown to promote recovery of locomotor behavior in the absence of locomotor training. The results from this study suggest that BDNF treatment sets the overall population in a state of high excitability, which along with higher synchrony and ensemble-dependent behavior, allows for the proper integration of cutaneous and proprioceptive input resulting in treadmill locomotor recovery after SCI.

Fast activity chirp patterns in focal seizures from patients and animal models.

Time-frequency analysis of focal seizure electroencephalographic signals performed with depth electrodes in human temporal lobe structures has revealed the occurrence at onset of oscillations at approximately 30-100 Hz that feature a monotonic rapid decay in frequency content. This seizure onset pattern, referred to as chirp, has been identified as a highly specific and sensitive marker of focal seizures that are characterized by low-voltage fast activity. We report that this chirp pattern is also observed in animal models of temporal lobe epilepsy in both invivo and invitro preparations. We propose here that chirps mirror the involvement of synchronous interneuron firing that is known to represent a specific cellular mechanism leading to the initiation of focal seizures, in particular those characterized by low-voltage fast activity.

Human driven climate change increased the likelihood of the 2023 record area burned in Canada

In 2023, wildfires burned 15 million hectares in Canada, more than doubling the previous record. These wildfires caused a record number of evacuations, unprecedented air quality impacts across Canada and the northeastern United States, and substantial strain on fire management resources. Using climate models, we show that human-induced climate change significantly increased the likelihood of area burned at least as large as in 2023 across most of Canada, with more than two-fold increases in the east and southwest. The long fire season was more than five times as likely and the large areas across Canada experiencing synchronous extreme fire weather were also much more likely due to human influence on the climate. Simulated emissions from the 2023 wildfire season were eight times their 1985-2022 mean. With continued warming, the likelihood of extreme fire seasons is projected to increase further in the future, driving additional impacts on health, society, and ecosystems.

Limbic system synaptic dysfunctions associated with prion disease onset

Misfolding of normal prion protein (PrPC) to pathological isoforms (prions) causes prion diseases (PrDs) with clinical manifestations including cognitive decline and mood-related behavioral changes. Cognition and mood are linked to the neurophysiology of the limbic system. Little is known about how the disease affects the synaptic activity in brain parts associated with this system. We hypothesize that the dysfunction of synaptic transmission in the limbic regions correlates with the onset of reduced cognition and behavioral deficits. Here, we studied how prion infection in mice disrupts the synaptic function in three limbic regions, the hippocampus, hypothalamus, and amygdala, at a pre-clinical stage (mid-incubation period) and early clinical onset. PrD caused calcium flux dysregulation associated with lesser spontaneous synchronous neuronal firing and slowing neural oscillation at the pre-clinical stage in the hippocampal CA1, ventral medial hypothalamus, and basolateral amygdala (BLA). At clinical onset, synaptic transmission and synaptic plasticity became significantly disrupted. This correlated with a substantial depletion of the soluble prion protein, loss of total synapses, abnormal neurotransmitter levels and synaptic release, decline in synaptic vesicle recycling, and cytoskeletal damage. Further, the amygdala exhibited distinct disease-related changes in synaptic morphology and physiology compared with the other regions, but generally to a lesser degree, demonstrating how different rates of damage in the limbic system influence the evolution of clinical disease. Overall, PrD causes synaptic damage in three essential limbic regions starting at a preclinical stage and resulting in synaptic plasticity dysfunction correlated with early disease signs. Therapeutic drugs that alleviate these early neuronal dysfunctions may significantly delay clinical onset.

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 Slc17a6 (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 that contributes 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/SaCas9, the slow excitatory postsynaptic potential was eliminated. Our data enabled us to formulate a biophysically realistic mathematical model of Kiss1ARH neurons, suggesting that E2 modifies ionic conductances in these 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.

Synchronous firing transition between different regions of brain neural networks enhanced by Hamiltonian energy

Synchronous firing transition between different regions of brain neural networks enhanced by Hamiltonian energy

Dynamics and synchronization of the Morris-Lecar model with field coupling subject to electromagnetic excitation

In this study, we extend the Morris-Lecar (M-L) neuron model to design a neuronal network model with field effects. Using Lyapunov theory and the master stability function to evaluate the stability of synchronous manifolds. The Hamilton energy function of a single neuron is derived using Helmholtz's theorem to equivalently describe its internal field energy, and bioelectric activities are analyzed in conjunction with synchronization error functions. A comprehensive analysis was conducted using various numerical methods, including time series diagrams, bifurcation diagrams, two-parameter plane synchronization error diagrams, and similarity function diagrams. The observations indicate that variations in conductivity and equilibrium potential directly impact the firing patterns and synchronization states of neurons. In various coupling methods, an increase in coupling strength induces different degrees of oscillation within the coupled system. The effects of three coupling methods on the synchronization of the neuronal network are examined using spatiotemporal evolution diagrams and energy evolution diagrams. Global synchronization error and synchronization factors are introduced to quantify the level of synchrony. Numerical results indicate that an appropriate coupling strength and ionic conductance enhance network synchrony. Numerical results indicate that appropriate coupling strength promotes network synchrony. The insights gained from this study contribute to providing a more coherent framework for constructing neuronal network models under field-coupled conditions, thereby enhancing the understanding of fundamental principles in neuroscience and offering new perspectives for the treatment and rehabilitation of neurological disorders.

Gap Junctions in Different Neuronal Groups Exert Different Effects on Sharp Wave-ripples of a Neuronal Network in CA1

Abstract Gap junctions are indispensable for achieving brain functions. The direct coupling between neurons connected by gap junctions may contribute to synchronization of neuronal firing and emergence of sharp wave-ripples(SWR), which affect brain functions such as memory consolidation. However, considering the heterogeneity of excitatory and inhibitory neurons, it is not quite clear whether gap junctions have the same effect on the emergence of SWR in network activity in different neuron types. In order to explore the above problems, we constructed a neuronal network located in CA1 region of hippocampus, which contains excitatory pyramidal cells, PV+BCs and axo-axonic cells. Taking into account diverse connections between neurons and properties of neurons, we investigated effects of gap junctions on SWR in different kinds of neuronal populations in the constructed network with chemical synaptic connections by neurodynamical modeling. Numerical results show that gap junctions within pyramidal neurons and PV+BCs promote the emergence of SWR, whereas gap junctions within axo-axonic cells suppress it. At the same time, it is revealed that gap junctions in axo-axonic cells play a dominant role in modulating SWR. We hope that these findings provide some inspiration for studies on neuronal heterogeneity and the enhancement of synchronicity of oscillations by gap junctions.

Firing dynamics and coupling synchronization of memristive EMR-based Chaivlo neuron utilizing equivalent energy approach.

Firing dynamics and its energy property of neuron are crucial for exploring the mechanism of intricate information processing within the nervous system. However, the energy analysis of discrete neuron is significantly lacking in comparison to the vast literature and mature theory available on continuous neuron, thereby necessitating a focused effort in this underexplored realm. In this paper, we introduce a Chaivlo neuron map by employing a flux-controlled memristor to simulate electromagnetic radiation (EMR), and a detailed analysis of its firing dynamics is conducted based on an equivalent Hamiltonian energy approach. Our observations reveal that a range of energy-based firing behaviors, such as spike firing, coexistence firing, mixed-mode firing, and chaotic bursting firing, can be induced by EMR and injected current. To delve deeper into the synchronous firing dynamics, we establish a Chaivlo network by electrically coupling two memristive EMR-based Chaivlo neurons. Subsequently, we experimentally evaluate the synchronization behavior of this network by quantifying both the synchronization factor and the average difference of equivalent Hamiltonian energy. Our findings conclusively demonstrate that both EMR and coupling strength positively contribute to the network's synchronization ability.

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 seven-dimensional (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 (2D) 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.