Synchronous Firing Research Articles

Use-dependent facilitation of electrical transmission involves changes to postsynaptic K+ current.

Activity-dependent modulation of electrical transmission typically involves Ca2+ influx acting directly on gap junctions or initiating Ca2+-dependent pathways that in turn modulate coupling. We now describe short-term use-dependent facilitation of electrical transmission between bag cell neurons from the hermaphroditic snail, Aplysia californica, that is instead mediated by changes in postsynaptic responsiveness. Bag cell neurons secrete reproductive hormone during a synchronous afterdischarge of action potentials coordinated by electrical coupling. Here, recordings from pairs of coupled bag cell neurons in culture showed that nonjunctional currents influence electrical transmission in a dynamic manner. Under a dual whole cell voltage-clamp, the junctional current was linear and largely voltage-independent, while in current-clamp, the coupling coefficient was similar regardless of the extent of presynaptic hyperpolarization. Moreover, a train stimulus of action potential-like waveforms, in a voltage-clamped presynaptic neuron, elicited electrotonic potentials, in a current-clamped postsynaptic neuron, that facilitated over time when delivered at a frequency approximating the afterdischarge. Junctional current remained constant over the train stimulus, as did postsynaptic voltage-gated Ca2+ current. However, postsynaptic voltage-gated K+ current underwent cumulative inactivation, suggesting that K+ current run-down facilitates the electrotonic potential by boosting the response to successive junctional currents. Accordingly, preventing run-down by blocking postsynaptic K+ channels occluded facilitation. Finally, stimulation of bursts in coupled pairs resulted in synchronous firing, where active neurons could recruit silent partners through short-term use-dependent facilitation. Thus, potentiation of electrical transmission may promote synchrony in bag cell neurons and, by extension, reproductive function.NEW & NOTEWORTHY The understanding of how activity can facilitate electrical transmission is incomplete. We found that electrotonic potentials between electrically coupled neuroendocrine bag cell neurons facilitated in a use-dependent fashion. Rather than changes to the junctional current, facilitation was associated with cumulative inactivation of postsynaptic K+ current, presumably augmenting responsiveness. When made to burst, neurons synchronized their spiking, in part by use-dependent facilitation bringing quiescent cells to the threshold. Facilitation may foster en masse firing and neurosecretion.

EEG synchrony reflects closure of jabberwocky noun phrases but not predictable pseudoword sequences.

Successful language comprehension requires the combination of individual words into larger linguistic units. In the present minimal-phrase study, we used electroencephalography (EEG) to investigate whether syntactic combination is indexed by changes in neural synchrony, while testing for both token-based and type-based effects. To do this, we analyzed inter-trial phase coherence (ITPC) elicited by reading two item (words or pseudowords) phrases that were either unifiable or non-unifiable. Results indicated that type-based unifiable phrases elicited increased ITPC relative to all other conditions in the frequency band corresponding to the rate of phrases (.5Hz) but not the rate of words (1Hz). Conversely, we observed a complementary pattern for the N400, which was more sensitive to token-based effects. These findings provide evidence that the combination of single words into larger syntactic structures may be indexed by the synchronous firing of assemblies of neurons oscillating at the rate of phrases during reading.

An Improved HVDC Synchronous Firing Control Method Based on Order Switching and Phase Compensation

Synchronous reference frame phase-locked loop (SRF-PLL) is adopted in high-voltage direct current (HVDC) synchronous firing control to output the synchronous phase. The synchronous performance directly affects the accuracy of the firing pulse, and even affects whether the inverter can successfully commutate during AC asymmetric faults. Therefore, an improved HVDC synchronous firing control method based on order switching and phase compensation is proposed in this paper. The improved SRF-PLL has the functions of extracting the fundamental frequency positive sequence (FFPS) phase and switching the order. When the fault detection detects that a fault has occurred, PLL is converted from the second-order system to the first-order system, so as to shorten the out-of-lock time and make it quickly enter the resynchronization. Then, for the phase shift of commutation voltages caused by fault, the zero-crossing sampling method is used to detect the change of the commutation voltage phases, and the synchronous phase of each commutation voltage is compensated selectively. Finally, the improved method is tested in CIGRE HVDC benchmark model and Three Gorges-Shanghai (3GS) DC project model, respectively. The results show that the improved method has better effect on suppressing commutation failure.

Ligand-gated mechanisms leading to ictogenesis in focal epileptic disorders

We review here the neuronal mechanisms that cause seizures in focal epileptic disorders and, specifically, those involving limbic structures that are known to be implicated in human mesial temporal lobe epilepsy. In both epileptic patients and animal models, the initiation of focal seizures - which are most often characterized by a low-voltage fast onset EEG pattern - is presumably dependent on the synchronous firing of GABA-releasing interneurons that, by activating post-synaptic GABAA receptors, cause large increases in extracellular [K+] through the activation of the co-transporter KCC2. A similar mechanism may contribute to seizure maintenance; accordingly, inhibiting KCC2 activity transforms seizure activity into a continuous pattern of short-lasting epileptiform discharges. It has also been found that interactions between different areas of the limbic system modulate seizure occurrence by controlling extracellular [K+] homeostasis. In line with this view, low-frequency electrical or optogenetic activation of limbic networks restrain seizure generation, an effect that may also involve the activation of GABAB receptors and activity-dependent changes in epileptiform synchronization. Overall, these findings highlight the paradoxical role of GABAA signaling in both focal seizure generation and maintenance, emphasize the efficacy of low-frequency activation in abating seizures, and provide experimental evidence explaining the poor efficacy of antiepileptic drugs designed to augment GABAergic function in controlling seizures in focal epileptic disorders.

Blockage of STAT3 during epileptogenesis prevents GABAergic loss and imprinting of the epileptic state.

Epilepsy, characterized by recurrent unprovoked seizures resulting from a wide variety of causes, is one of the world's most prominent neurological disabilities. Seizures, which are an expression of neuronal network dysfunction, occur in a positive feedback loop of concomitant factors, including neuro-inflammatory responses, where seizures generate more seizures. Among other pathways involved in inflammatory responses, the JAK/STAT signalling pathway has been proposed to participate in epilepsy. Here, we tested an in vitro model of temporal lobe epilepsy, with the hypothesis that acute blockage of STAT3-phosphorylation during epileptogenesis would prevent structural damage in the hippocampal circuitry and the imprinting of both neural epileptic activity and inflammatory glial states. We performed calcium imaging of spontaneous circuit dynamics in organotypic hippocampal slices previously exposed to epileptogenic conditions through the blockage of GABAergic synaptic transmission. Epileptogenic conditions lead to epileptic dynamics imprinted on circuits in terms of increased neuronal firing and circuit synchronization, increased correlated activity in neuronal pairs and decreased complexity in synchronization patterns. Acute blockage of the STAT3-phosphorylation during epileptogenesis prevented the imprinting of epileptic activity patterns, general cell loss, loss of GABAergic neurons and the persistence of reactive glial states. This work provides mechanistic evidence that blocking the STAT3 signalling pathway during epileptogenesis can prevent patho-topological persistent reorganization of neuro-glial circuits.

Synchronization of pacemaker cell firing underlies autonomic modulation of beating intervals and their variability in a numerical model of heterogeneous SA node tissue.

The normal heart beats regularly but not metronomically. It is initiated by pacemaker cells within the sinoatrial node (SAN), an extremely heterogeneous cellular network. The functional role of SAN cell heterogeneity remains unknown. Here we investigated the problem in a SAN tissue model comprised of 2025 single cell models. Each cell model features a coupled operation of the Ca and membrane clocks. We modeled tissue heterogeneity by varying the ICaL conductance (gCaL) and SR Ca pumping (Pup). In our simulations heterogeneous cells interacted in tissue and acquired new properties: while cells in isolation had all rhythmic or no firing, cells firing irregular APs emerged in local cell communities with similar properties. The heart rate is naturally increased via β-adrenergic receptors (βAR) and decreased via cholinergic receptors (ChR) in the SAN. βAR stimulation increased the rate and synchronization of AP firing of individual cell models within the SAN tissue, whereas ChR stimulation decreased the rate and synchronization of AP firing. The number of firing cells increased in βAR stimulation to 99% from 80%, and the average cycle length of the SAN decreased by ∼20%. Meanwhile the standard deviation of the cycle length decreased by a multiple of 25, reflecting a much higher level of synchronization. During ChR stimulation, the number of firing cells remained almost unchanged, but the average AP cycle length increased by almost 20%. The standard deviation also increased by a multiple of 2, demonstrating the higher level of desynchronization. The number of cells with emergent irregular APs firing was substantially greater under ChR stimulation than BAR stimulation, indicating importance of these cells as an intrinsic source of heart rate variability at various conditions.

Consciousness: Matter or EMF?

Conventional theories of consciousness (ToCs) that assume that the substrate of consciousness is the brain's neuronal matter fail to account for fundamental features of consciousness, such as the binding problem. Field ToC's propose that the substrate of consciousness is the brain's best accounted by some kind of field in the brain. Electromagnetic (EM) ToCs propose that the conscious field is the brain's well-known EM field. EM-ToCs were first proposed only around 20 years ago primarily to account for the experimental discovery that synchronous neuronal firing was the strongest neural correlate of consciousness (NCC). Although EM-ToCs are gaining increasing support, they remain controversial and are often ignored by neurobiologists and philosophers and passed over in most published reviews of consciousness. In this review I examine EM-ToCs against established criteria for distinguishing between ToCs and demonstrate that they outperform all conventional ToCs and provide novel insights into the nature of consciousness as well as a feasible route toward building artificial consciousnesses.

Intermittency properties in a temporal lobe epilepsy model

Neuronal synchronization is important for communication between brain regions and plays a key role in learning. However, changes in connectivity can lead to hyper-synchronized states related to epileptic seizures that occur intermittently with asynchronous states. The activity-regulated cytoskeleton-associated protein (ARC) is related to synaptic alterations which can lead to epilepsy. Induction of status epilepticus in rodent models causes the appearance of intense ARC immunoreactive neurons (IAINs), which present a higher number of connections and conductance intensity than non-IAINs. This alteration might contribute to abnormal epileptic seizure activity. In this work, we investigated how IAINs connectivity influences the firing pattern and synchronization in neural networks. Firstly, we showed the appearance of synchronized burst patterns due to the emergence of IAINs. Second, we described how the increase of IAINs connectivity favors the appearance of intermittent up and down activities associated with synchronous bursts and asynchronous spikes, respectively. Once the intermittent activity was properly characterized, we applied the optogenetics control of the high synchronous activities in the intermittent regime. To do this, we considered that 1% of neurons were transfected and became photosensitive. We observed that optogenetics methods to control synchronized burst patterns are effective when IAINs are chosen as photosensitive, but not effective in non-IAINs. Therefore, our analyses suggest that IAINs play a pivotal role in both the generation and suppression of highly synchronized activities.

Chimeralike oscillation modes in excitable scale-free networks

A topological mechanism of the emergence of chimeralike oscillation modes (CLOMs) consisting of coherent synchronous firings and incoherent nonsynchronous oscillations is proposed in excitable scale-free networks (ESFNs). It is revealed that the topology heterogeneity of the network is responsible for forming and maintaining the CLOM in the ESFN, which is definitely different from the mechanism of the normal oscillation mode (NOM) possessing only a single dynamical mode in homogeneous excitable systems. An effective-driving approach is proposed, which provides a criterion for the formation of the CLOM in excitable complex networks. Our contributions may shed light on a perspective of CLOMs in complex systems, and can help us understand competitions and self-organizations of NOM and CLOM in excitable systems with topological homogeneity and heterogeneity.

Measuring Neuronal Network Activity Using HumanInduced Neuronal Cells.

Synchronous firing of neurons, often referred to as "network activity" or "network bursting," is an indication of amature and synaptically connected network of neurons. We previously reported this phenomenon in 2D human neuronal in vitro models (McSweeney et al. iScience 25:105187, 2022). Using induced neurons (iNs) differentiated from human pluripotent stem cells (hPSCs) coupled with high-density microelectrodes arrays (HD-MEAs), we probed the underlying patterns of neuronal activity and found irregularities in network signaling across mutant states (McSweeney et al. iScience 25:105187, 2022). Here, we describe methods for plating cortical excitatory iNs differentiated from hPSCs on top of HD-MEAsand culturing iNs to maturity, examples of representative human wild-type Ngn2-iN data, and troubleshooting tips and tricks for the experimenter interested in integrating HD-MEAs into one's research approach.

Motor unit synchronization and firing rate correlate with the fractal dimension of the surface EMG: A validation study

The fractal dimension (FD) of the surface electromyographic (EMG) signal has been reported to be influenced by changes in the firing rate and synchronization of motor units. The purpose of this study was to validate these relations during experimental signals.Thirteen healthy subjects (12 men and 1 woman) performed an isometric knee extension at 5 % of their maximal voluntary contraction for 300 s. Intramuscular and surface EMG signal were recorded concurrently from the vastus medialis obliquus. Synchronization and firing rate were calculated from the decomposed intramuscular EMG signal, while FD was estimated using the box-counting method. The first and last 50 s of contractions were considered during the correlation analyses.FD was negatively related to the level of motor unit synchronization (rs = −0.30; p < 0.05) and positively correlated with firing rate (rs = 0.25; p < 0.01) when all data were pooled. FD was correlated with firing rate only during the initial 50 s of contraction (rs = 0.52; p < 0.001).FD of the sEMG signal is a parameter mostly related to the firing rate when fatigue does not develop and may be considered as an index of performance fatigability during sustained or at the end of prolonged contractions at very low forces. Indeed, FD cannot be considered as an exclusive index of motor unit synchronization during fatiguing contractions, but rather as largely related to central factors.

Firing behavior of single motor units of the tibialis anterior in human walking as non-invasively revealed by HDsEMG decomposition

Objective. Investigation of the firing behavior of motor units (MUs) provides essential neuromuscular control information because MUs are the smallest organizational component of the neuromuscular system. The MUs activated during human infants’ leg movements and rodent locomotion, mainly controlled by the spinal central pattern generator (CPG), show highly synchronous firing. In addition to spinal CPGs, the cerebral cortex is involved in neuromuscular control during walking in human adults. Based on the difference in the neural control mechanisms of locomotion between rodent, human infants and adults, MU firing behavior during adult walking probably has some different features from the other populations. However, so far, the firing activity of MUs in human adult walking has been largely unknown due to technical issues. Approach. Recent technical advances allow noninvasive investigation of MU firing by high-density surface electromyogram (HDsEMG) decomposition. We investigated the MU firing behavior of the tibialis anterior (TA) muscle during walking at a slow speed by HDsEMG decomposition. Main results. We found recruitment threshold modulation of MU between walking and steady isometric contractions. Doublet firings, and gait phase-specific firings were also observed during walking. We also found high MU synchronization during walking over a wide range of frequencies, probably including cortical and spinal CPG-related components. The amount of MU synchronization was modulated between the gait phases and motor tasks. These results suggest that the central nervous system flexibly controls MU firing to generate appropriate force of TA during human walking. Significance. This study revealed the MU behavior during walking at a slow speed and demonstrated the feasibility of noninvasive investigation of MUs during dynamic locomotor tasks, which will open new frontiers for the study of neuromuscular systems in the fields of neuroscience and biomedical engineering.

Upper and lower limb muscle sympathetic responses to contralateral exercise in healthy humans: A pilot study.

Muscle sympathetic nerve activity (MSNA) is similar between limbs at rest, although a subset of MSNA bursts do demonstrate limb-specific discharge. Whether limb differences in MSNA synchronicity are present during exercise remains controversial. We concurrently measured MSNA from the radial and fibular nerves at rest and during rhythmic handgrip (RHG), static handgrip (SHG), and post-exercise circulatory occlusion (PECO). MSNA burst frequency and incidence were similar between nerve sites during all conditions. Synchronous bursts resulted in larger increases in sympathetic-blood pressure transduction compared to isolated bursts (∆+3.6±2.1 vs. +2.3±2.4mmHg, P=0.01). The proportion of bursts firing synchronously between nerves at rest was slightly increased during RHG ([rest vs. exercise; mean±SD] 45.3±7.1 vs. 61.6±7.2%) and similar during SHG (56.2±7.2 vs. 54±10.6%). In contrast, burst firing synchronicity increased during PECO (83.8±12.4%) alongside larger burst amplitudes. Inter-limb differences in resting MSNA are preserved during handgrip exercise, whereas isolated metaboreflex activation results in greater burst synchronization between limbs.

Oscillations support short latency co-firing of neurons during human episodic memory formation.

Theta and gamma oscillations in the medial temporal lobe are suggested to play a critical role for human memory formation via establishing synchrony in neural assemblies. Arguably, such synchrony facilitates efficient information transfer between neurons and enhances synaptic plasticity, both of which benefit episodic memory formation. However, to date little evidence exists from humans that would provide direct evidence for such a specific role of theta and gamma oscillations for episodic memory formation. Here, we investigate how oscillations shape the temporal structure of neural firing during memory formation in the medial temporal lobe. We measured neural firing and local field potentials in human epilepsy patients via micro-wire electrode recordings to analyze whether brain oscillations are related to co-incidences of firing between neurons during successful and unsuccessful encoding of episodic memories. The results show that phase-coupling of neurons to faster theta and gamma oscillations correlates with co-firing at short latencies (~20-30 ms) and occurs during successful memory formation. Phase-coupling at slower oscillations in these same frequency bands, in contrast, correlates with longer co-firing latencies and occurs during memory failure. Thus, our findings suggest that neural oscillations play a role for the synchronization of neural firing in the medial temporal lobe during the encoding of episodic memories.

Neural synchrony in cortical networks: mechanisms and implications for neural information processing and coding.

Synchronization of neuronal discharges on the millisecond scale has long been recognized as a prevalent and functionally important attribute of neural activity. In this article, I review classical concepts and corresponding evidence of the mechanisms that govern the synchronization of distributed discharges in cortical networks and relate those mechanisms to their possible roles in coding and cognitive functions. To accommodate the need for a selective, directed synchronization of cells, I propose that synchronous firing of distributed neurons is a natural consequence of spike-timing-dependent plasticity (STDP) that associates cells repetitively receiving temporally coherent input: the “synchrony through synaptic plasticity” hypothesis. Neurons that are excited by a repeated sequence of synaptic inputs may learn to selectively respond to the onset of this sequence through synaptic plasticity. Multiple neurons receiving coherent input could thus actively synchronize their firing by learning to selectively respond at corresponding temporal positions. The hypothesis makes several predictions: first, the position of the cells in the network, as well as the source of their input signals, would be irrelevant as long as their input signals arrive simultaneously; second, repeating discharge patterns should get compressed until all or some part of the signals are synchronized; and third, this compression should be accompanied by a sparsening of signals. In this way, selective groups of cells could emerge that would respond to some recurring event with synchronous firing. Such a learned response pattern could further be modulated by synchronous network oscillations that provide a dynamic, flexible context for the synaptic integration of distributed signals. I conclude by suggesting experimental approaches to further test this new hypothesis.

Synchronous firing of dorsal horn neurons at the origin of dorsal root reflexes in naïve and paw-inflamed mice.

Spinal interneurons located in the dorsal horn induce primary afferent depolarization (PAD) controlling the excitability of the afferent’s terminals. Following inflammation, PAD may reach firing threshold contributing to maintain inflammation and pain. Our aim was to study the collective behavior of dorsal horn neurons, its relation to backfiring of primary afferents and the effects of a peripheral inflammation in this system. Experiments were performed on slices of spinal cord obtained from naïve adult mice or mice that had suffered an inflammatory pretreatment. Simultaneous recordings from groups of dorsal horn neurons and primary afferents were obtained and machine-learning methodology was used to analyze effective connectivity between them. Dorsal horn recordings showed grouping of spontaneous action potentials from different neurons in “population bursts.” These occurred at irregular intervals and were formed by action potentials from all classes of neurons recorded. Compared to naïve, population bursts from treated animals concentrated more action potentials, had a faster onset and a slower decay. Population bursts were disrupted by perfusion of picrotoxin and held a strong temporal correlation with backfiring of afferents. Effective connectivity analysis allowed pinpointing specific neurons holding pre- or post-synaptic relation to the afferents. Many of these neurons had an irregular fast bursting pattern of spontaneous firing. We conclude that population bursts contain action potentials from neurons presynaptic to the afferents which are likely to control their excitability. Peripheral inflammation may enhance synchrony in these neurons, increasing the chance of triggering action potentials in primary afferents and contributing toward central sensitization.

Superposed recurrence plots for reconstructing a common input applied to neurons.

In the brain, common inputs play an important role in eliciting synchronous firing in the assembly of neurons. However, common inputs are usually unknown to observers. If an unobserved common input can be reconstructed only from outputs, it would be beneficial to the understanding of communication in the brain. Thus, we have developed a method for reconstructing a common input only from output firing rates of uncoupled neuron models. To this end, we propose a superposed recurrence plot (SRP) comprising points determined by using a union of points at each pixel among multiple recurrence plots. The SRP method can reconstruct a common input when using various types of neurons with different firing rate baselines, even when using uncoupled neuron models that exhibit chaotic responses. The SRP method robustly reconstructs the common input applied to the neuron models when we select adequate time windows to calculate the firing rates in accordance with the width of the fluctuations. These results suggest that certain information is embedded in the firing rate. These findings could be a possible basis for analyzing whole-brain communication utilizing rate coding.

Deep learning-based feature extraction for prediction and interpretation of sharp-wave ripples in the rodent hippocampus.

Local field potential (LFP) deflections and oscillations define hippocampal sharp-wave ripples (SWRs), one of the most synchronous events of the brain. SWRs reflect firing and synaptic current sequences emerging from cognitively relevant neuronal ensembles. While spectral analysis have permitted advances, the surge of ultra-dense recordings now call for new automatic detection strategies. Here, we show how one-dimensional convolutional networks operating over high-density LFP hippocampal recordings allowed for automatic identification of SWR from the rodent hippocampus. When applied without retraining to new datasets and ultra-dense hippocampus-wide recordings, we discovered physiologically relevant processes associated to the emergence of SWR, prompting for novel classification criteria. To gain interpretability, we developed a method to interrogate the operation of the artificial network. We found it relied in feature-based specialization, which permit identification of spatially segregated oscillations and deflections, as well as synchronous population firing typical of replay. Thus, using deep learning-based approaches may change the current heuristic for a better mechanistic interpretation of these relevant neurophysiological events.

&lt;i&gt;Corrigendum to&lt;/i&gt;: Regional drought synchronised historical fires in dry forests of the Montane Cordillera Ecozone, Canada

Understanding climate as a driver of low- to moderate-severity fires in the Montane Cordillera Ecozone of Canada is a priority given predicted and observed increases in frequency and severity of large fires due to climate change. We characterised historical fire-climate associations using 14 crossdated fire-scar records and tree-ring proxy reconstructions of summer drought and annual precipitation from the region. We compared fire-climate associations among years when fires burned in multiple study areas. From 1746 to 1945, there were 32 years with moderate fire synchrony in which four to six study areas recorded fire. During four high fire synchrony years, 7 to 10 study areas recorded fire. Below-average annual precipitation and summer drought synchronised fires, whereas infrequent years of high fire synchrony were preceded by a wet summer. After 1945, decreased fire occurrence and synchrony reflects fire exclusion, suppression and climatic variation. Global climate change manifests as blocking high-pressure ridges that superimpose on longer fire-seasons and increased droughts. Combined, they make dry forests increasingly susceptible to synchronous fires, which are difficult to suppress as observed during the record-breaking 2017, 2018 and 2021 fire seasons in British Columbia.

Patterns of synchronization in 2D networks of inhibitory neurons.

Neural firing in many inhibitory networks displays synchronous assembly or clustered firing, in which subsets of neurons fire synchronously, and these subsets may vary with different inputs to, or states of, the network. Most prior analytical and computational modeling of such networks has focused on 1D networks or 2D networks with symmetry (often circular symmetry). Here, we consider a 2D discrete network model on a general torus, where neurons are coupled to two or more nearest neighbors in three directions (horizontal, vertical, and diagonal), and allow different coupling strengths in all directions. Using phase model analysis, we establish conditions for the stability of different patterns of clustered firing behavior in the network. We then apply our results to study how variation of network connectivity and the presence of heterogeneous coupling strengths influence which patterns are stable. We confirm and supplement our results with numerical simulations of biophysical inhibitory neural network models. Our work shows that 2D networks may exhibit clustered firing behavior that cannot be predicted as a simple generalization of a 1D network, and that heterogeneity of coupling can be an important factor in determining which patterns are stable.