Network synchronization in hippocampal neurons

Criticality and universality in neuronal cultures during "up" and "down" states

The brain can be seen as a self-organized dynamical system that optimizes information processing and storage capabilities. This is supported by studies across scales, from small neuronal assemblies to the whole brain, where neuronal activity exhibits features typically associated with phase transitions in statistical physics. Such a critical state is characterized by the emergence of scale-free statistics as captured, for example, by the sizes and durations of activity avalanches corresponding to a cascading process of information flow. Another phenomenon observed during sleep, under anesthesia, and in in vitro cultures, is that cortical and hippocampal neuronal networks alternate between "up" and "down" states characterized by very distinct firing rates. Previous theoretical work has been able to relate these two concepts and proposed that only up states are critical whereas down states are subcritical, also indicating that the brain spontaneously transitions between the two. Using high-speed high-resolution calcium imaging recordings of neuronal cultures, we test this hypothesis here by analyzing the neuronal avalanche statistics in populations of thousands of neurons during "up" and "down" states separately. We find that both "up" and "down" states can exhibit scale-free behavior when taking into account their intrinsic time scales. In particular, the statistical signature of "down" states is indistinguishable from those observed previously in cultures without "up" states. We show that such behavior can not be explained by network models of non-conservative leaky integrate-and-fire neurons with short-term synaptic depression, even when realistic noise levels, spatial network embeddings, and heterogeneous populations are taken into account, which instead exhibits behavior consistent with previous theoretical models. Similar differences were also observed when taking into consideration finite-size scaling effects, suggesting that the intrinsic dynamics and self-organization mechanisms of these cultures might be more complex than previously thought. In particular, our findings point to the existence of different mechanisms of neuronal communication, with different time scales, acting during either high-activity or low-activity states, potentially requiring different plasticity mechanisms.

Bi-allelic NRXN1α deletion in microglia derived from iPSC of an autistic patient increases interleukin-6 production and impairs supporting function on neuronal networking

Autism spectrum disorder (ASD) is a set of heterogeneous neurodevelopmental conditions, with a highly diverse genetic hereditary component, including altered neuronal circuits, that has an impact on communication skills and behaviours of the affected individuals. Beside the recognised role of neuronal alterations, perturbations of microglia and the associated neuroinflammatory processes have emerged as credible contributors to aetiology and physiopathology of ASD. Mutations in NRXN1, a member of the neurexin family of cell-surface receptors that bind neuroligin, have been associated to ASD. NRXN1 is known to be expressed by neurons where it facilitates synaptic contacts, but it has also been identified in glial cells including microglia. Asserting the impact of ASD-related genes on neuronal versus microglia functions has been challenging. Here, we present an ASD subject-derived induced pluripotent stem cells (iPSC)-based in vitro system to characterise the effects of the ASD-associated NRXN1 gene deletion on neurons and microglia, as well as on the ability of microglia to support neuronal circuit formation and function. Using this approach, we demonstrated that NRXN1 deletion, impacting on the expression of the alpha isoform (NRXN1α), in microglia leads to microglial alterations and release of IL6, a pro-inflammatory interleukin associated with ASD. Moreover, microglia bearing the NRXN1α-deletion, lost the ability to support the formation of functional neuronal networks. The use of recombinant IL6 protein on control microglia-neuron co-cultures or neutralizing antibody to IL6 on their NRXN1α-deficient counterparts, supported a direct contribution of IL6 to the observed neuronal phenotype. Altogether, our data suggest that, in addition to neurons, microglia are also negatively affected by NRXN1α-deletion, and this significantly contributes to the observed neuronal circuit aberrations.

The vitals for steady nucleation maps of spontaneous spiking coherence in autonomous two-dimensional neuronal networks

Thin pancake-like neuronal networks cultured on top of a planar microelectrode array have been extensively tried out in neuroengineering, as a substrate for the mobile robot's control unit, i.e., as a cyborg's brain. Most of these attempts failed due to intricate self-organizing dynamics in the neuronal systems. In particular, the networks may exhibit an emergent spatial map of steady nucleation sites ("n-sites") of spontaneous population spikes. Being unpredictable and independent of the surface electrode locations, the n-sites drastically change local ability of the network to generate spikes. Here, using a spiking neuronal network model with generative spatially-embedded connectome, we systematically show in simulations that the number, location, and relative activity of spontaneously formed n-sites ("the vitals") crucially depend on the samplings of three distributions: (1) the network distribution of neuronal excitability, (2) the distribution of connections between neurons of the network, and (3) the distribution of maximal amplitudes of a single synaptic current pulse. Moreover, blocking the dynamics of a small fraction (about 4%) of non-pacemaker neurons having the highest excitability was enough to completely suppress the occurrence of population spikes and their n-sites. This key result is explained theoretically. Remarkably, the n-sites occur taking into account only short-term synaptic plasticity, i.e., without a Hebbian-type plasticity. As the spiking network model used in this study is strictly deterministic, all simulation results can be accurately reproduced. The model, which has already demonstrated a very high richness-to-complexity ratio, can also be directly extended into the three-dimensional case, e.g., for targeting peculiarities of spiking dynamics in cerebral (or brain) organoids. We recommend the model as an excellent illustrative tool for teaching network-level computational neuroscience, complementing a few benchmark models.

Gap-junction-mediated bioelectric signaling required for slow muscle development and function in zebrafish

Bioelectric signaling, intercellular communication facilitated by membrane potential and electrochemical coupling, is emerging as a key regulator of animal development. Gap junction (GJ) channels can mediate bioelectric signaling by creating a fast, direct pathway between cells for the movement of ions and other small molecules. In vertebrates, GJ channels are formed by a highly conserved transmembrane protein family called the connexins. The connexin gene family is large and complex, creating challenges in identifying specific connexins that create channels within developing and mature tissues. Using the embryonic zebrafish neuromuscular system as a model, we identify a connexin conserved across vertebrate lineages, gjd4, which encodes the Cx46.8 protein, that mediates bioelectric signaling required for slow muscle development and function. Through mutant analysis and in vivo imaging, we show that gjd4/Cx46.8 creates GJ channels specifically in developing slow muscle cells. Using genetics, pharmacology, and calcium imaging, we find that spinal-cord-generated neural activity is transmitted to developing slow muscle cells, and synchronized activity spreads via gjd4/Cx46.8 GJ channels. Finally, we show that bioelectrical signal propagation within the developing neuromuscular system is required for appropriate myofiber organization and that disruption leads to defects in behavior. Our work reveals a molecular basis for GJ communication among developing muscle cells and reveals how perturbations to bioelectric signaling in the neuromuscular system may contribute to developmental myopathies. Moreover, this work underscores a critical motif of signal propagation between organ systems and highlights the pivotal role of GJ communication in coordinating bioelectric signaling during development.

The neuronal basis of human creativity

Human creativity is a powerful cognitive ability underlying all uniquely human cultural and scientific advancement. However, the neuronal basis of this creative ability is unknown. Here, I propose that slow, spontaneous fluctuations in neuronal activity, also known as "resting state" fluctuations, constitute a universal mechanism underlying all facets of human creativity. Support for this hypothesis is derived from experiments that directly link spontaneous fluctuations and verbal creativity. Recent experimental and modeling advances in our understanding of the spontaneous fluctuations offer an explanation for the diversity and innovative nature of creativity, which is derived from a unique integration of random, neuronal noise on the one hand with individually specified, deterministic information acquired through learning, expertise training, and hereditary traits. This integration between stochasticity and order leads to a process that offers, on the one hand, original, unexpected outcomes but, on the other hand, endows these outcomes with knowledge-based meaning and significance.

Influence of microgravity on spontaneous calcium activity of primary hippocampal neurons grown in microfluidic chips

The influence of variations of gravity, either hypergravity or microgravity, on the brain of astronauts is a major concern for long journeys in space, to the Moon or to Mars, or simply long-duration missions on the ISS (International Space Station). Monitoring brain activity, before and after ISS missions already demonstrated important and long term effects on the brains of astronauts. In this study, we focus on the influence of gravity variations at the cellular level on primary hippocampal neurons. A dedicated setup has been designed and built to perform live calcium imaging during parabolic flights. During a CNES (Centre National d'Etudes Spatiales) parabolic flight campaign, we were able to observe and monitor the calcium activity of 2D networks of neurons inside microfluidic devices during gravity changes over different parabolas. Our preliminary results clearly indicate a modification of the calcium activity associated to variations of gravity.

Effect of adaptation functions and multilayer topology on synchronization

This study investigates the synchronization of globally coupled Kuramoto oscillators in monolayer and multilayer configurations. The interactions are taken to be pairwise, whose strength adapts with the instantaneous synchronization order parameter. The route to synchronization is analytically investigated using the Ott-Antonsen ansatz for two broad classes of adaptation functions that capture a wide range of transition scenarios. The formulation is subsequently extended to adaptively coupled multilayer configurations, using which a wider range of transition scenarios is uncovered for a bilayer model with cross-adaptive interlayer interactions.

Gap junction mediated bioelectric coordination is required for slow muscle development, organization, and function

Bioelectrical signaling, intercellular communication facilitated by membrane potential and electrochemical coupling, is emerging as a key regulator of animal development. Gap junction (GJ) channels can mediate bioelectric signaling by creating a fast, direct pathway between cells for the movement of ions and other small molecules. In vertebrates, GJ channels are formed by a highly conserved transmembrane protein family called the Connexins. The connexin gene family is large and complex, presenting a challenge in identifying the specific Connexins that create channels within developing and mature tissues. Using the embryonic zebrafish neuromuscular system as a model, we identify a connexin conserved across vertebrate lineages, gjd4, which encodes the Cx46.8 protein, that mediates bioelectric signaling required for appropriate slow muscle development and function. Through a combination of mutant analysis and in vivo imaging we show that gjd4/Cx46.8 creates GJ channels specifically in developing slow muscle cells. Using genetics, pharmacology, and calcium imaging we find that spinal cord generated neural activity is transmitted to developing slow muscle cells and synchronized activity spreads via gjd4/Cx46.8 GJ channels. Finally, we show that bioelectrical signal propagation within the developing neuromuscular system is required for appropriate myofiber organization, and that disruption leads to defects in behavior. Our work reveals the molecular basis for GJ communication among developing muscle cells and reveals how perturbations to bioelectric signaling in the neuromuscular system_may contribute to developmental myopathies. Moreover, this work underscores a critical motif of signal propagation between organ systems and highlights the pivotal role played by GJ communication in coordinating bioelectric signaling during development.

Modular architecture facilitates noise-driven control of synchrony in neuronal networks

High-level information processing in the mammalian cortex requires both segregated processing in specialized circuits and integration across multiple circuits. One possible way to implement these seemingly opposing demands is by flexibly switching between states with different levels of synchrony. However, the mechanisms behind the control of complex synchronization patterns in neuronal networks remain elusive. Here, we use precision neuroengineering to manipulate and stimulate networks of cortical neurons in vitro, in combination with an in silico model of spiking neurons and a mesoscopic model of stochastically coupled modules to show that (i) a modular architecture enhances the sensitivity of the network to noise delivered as external asynchronous stimulation and that (ii) the persistent depletion of synaptic resources in stimulated neurons is the underlying mechanism for this effect. Together, our results demonstrate that the inherent dynamical state in structured networks of excitable units is determined by both its modular architecture and the properties of the external inputs.

Revealing Low Amplitude Signals of Neuroendocrine Cells through Disordered Silicon Nanowires-Based Microelectrode Array

Today, the key methodology to study in vitro or in vivo electrical activity in a population of electrogenic cells, under physiological or pathological conditions, is by using microelectrode array (MEA). While significant efforts have been devoted to develop nanostructured MEAs for improving the electrophysiological investigation in neurons and cardiomyocytes, data on the recording of the electrical activity from neuroendocrine cells with MEA technology are scarce owing to their weaker electrical signals. Disordered silicon nanowires (SiNWs) for developing a MEA that, combined with a customized acquisition board, successfully capture the electrical signals generated by the corticotrope AtT-20 cells as a function of the extracellular calcium (Ca2+ ) concentration are reported. The recorded signals show a shape that clearly resembles the action potential waveform by suggesting a natural membrane penetration of the SiNWs. Additionally, the generation of synchronous signals observed under high Ca2+ content indicates the occurrence of a collective behavior in the AtT-20 cell population. This study extends the usefulness of MEA technology to the investigation of the electrical communication in cells of the pituitary gland, crucial in controlling several essential human functions, and provides new perspectives in recording with MEA the electrical activity of excitable cells.

Mathematical Model of Synaptic Long-Term Potentiation as a Bistability in a Chain of Biochemical Reactions with a Positive Feedback

Nitric oxide (NO) is involved in synaptic long-term potentiation (LTP) by multiple signaling pathways. Here, we show that LTP of synaptic transmission can be explained as a feature of signal transduction-bistable behavior in a chain of biochemical reactions with positive feedback, formed by diffusion of NO to the presynaptic site and facilitating the release of glutamate (Glu). The dynamics of Glu, calcium (Ca²⁺) and NO is described by a system of nonlinear reaction-diffusion equations with modified Michaelis-Menten (MM) kinetics. Numerical investigation reveals that the chain of biochemical reactions analyzed can exhibit a bistable behavior under physiological conditions when production of Glu is described by MM kinetics and decay of NO is modeled by means of two enzymatic pathways with different kinetic properties. Our finding extends understanding of the role of NO in LTP: a short high-intensity stimulus is "memorized" as a long-lasting elevation of NO concentration. The conclusions obtained by analysis of the chain of biochemical reactions describing LTP can be generalized to other chains of interactions or for creating the logical elements for biological computers.

Loss of neuron network coherence induced by virus-infected astrocytes: a model study

Coherent activations of brain neuron networks underlie many physiological functions associated with various behavioral states. These synchronous fluctuations in the electrical activity of the brain are also referred to as brain rhythms. At the cellular level, rhythmicity can be induced by various mechanisms of intrinsic oscillations in neurons or the network circulation of excitation between synaptically coupled neurons. One specific mechanism concerns the activity of brain astrocytes that accompany neurons and can coherently modulate synaptic contacts of neighboring neurons, synchronizing their activity. Recent studies have shown that coronavirus infection (Covid-19), which enters the central nervous system and infects astrocytes, can cause various metabolic disorders. Specifically, Covid-19 can depress the synthesis of astrocytic glutamate and gamma-aminobutyric acid. It is also known that in the post-Covid state, patients may suffer from symptoms of anxiety and impaired cognitive functions. We propose a mathematical model of a spiking neuron network accompanied by astrocytes capable of generating quasi-synchronous rhythmic bursting discharges. The model predicts that if the release of glutamate is depressed, normal burst rhythmicity will suffer dramatically. Interestingly, in some cases, the failure of network coherence may be intermittent, with intervals of normal rhythmicity, or the synchronization can disappear.

Pharmacologically targeting transient receptor potential channels for seizures and epilepsy: Emerging preclinical evidence of druggability

As one of the most prevalent and disabling brain disorders, epilepsy is characterized by spontaneous seizures that result from aberrant, excessive hyperactivity of a group of highly synchronized brain neurons. Remarkable progress in epilepsy research and treatment over the first two decades of this century led to a dramatical expansion in the third-generation antiseizure drugs (ASDs). However, there are still over 30% of patients suffering from seizures resistant to the current medications, and the broad unbearable adversative effects of ASDs significantly impair the quality of life in about 40% of individuals affected by the disease. Prevention of epilepsy in those who are at high risks is another major unmet medical need, given that up to 40% of epilepsy patients are believed to have acquired causes. Therefore, it is important to identify novel drug targets that can facilitate the discovery and development of new therapies engaging unprecedented mechanisms of action that might overcome these significant limitations. Also over the last two decades, calcium signaling has been increasingly recognized as a key contributory factor in epileptogenesis of many aspects. The intracellular calcium homeostasis involves a variety of calcium-permeable cation channels, the most important of which perhaps are the transient receptor potential (TRP) ion channels. This review focuses on recent exciting advances in understanding of TRP channels in preclinical models of seizure disorders. We also provide emerging insights into the molecular and cellular mechanisms of TRP channels-engaged epileptogenesis that might lead to new antiseizure therapies, epilepsy prevention and modification, and even a cure.

Expression of the primate-specific LINC00473 RNA in mouse neurons promotes excitability and CREB-regulated transcription

The LINC00473 (Lnc473) gene has previously been shown to be associated with cancer and psychiatric disorders. Its expression is elevated in several types of tumors and decreased in the brains of patients diagnosed with schizophrenia or major depression. In neurons, Lnc473 transcription is strongly responsive to synaptic activity, suggesting a role in adaptive, plasticity-related mechanisms. However, the function of Lnc473 is largely unknown. Here, using a recombinant adeno-associated viral vector, we introduced a primate-specific human Lnc473 RNA into mouse primary neurons. We show that this resulted in a transcriptomic shift comprising downregulation of epilepsy-associated genes and a rise in cAMP response element binding protein (CREB) activity, which was driven by augmented CREB-regulated transcription coactivator 1 (CRTC1) nuclear localization. Moreover, we demonstrate that ectopic Lnc473 expression increased neuronal excitability as well as network excitability. These findings suggest that primates may possess a lineage-specific activity-dependent modulator of CREB-regulated neuronal excitability.

Synchronization of phase oscillators on complex hypergraphs

We study the effect of structured higher-order interactions on the collective behavior of coupled phase oscillators. By combining a hypergraph generative model with dimensionality reduction techniques, we obtain a reduced system of differential equations for the system's order parameters. We illustrate our framework with the example of a hypergraph with hyperedges of sizes 2 (links) and 3 (triangles). For this case, we obtain a set of two coupled nonlinear algebraic equations for the order parameters. For strong values of coupling via triangles, the system exhibits bistability and explosive synchronization transitions. We find conditions that lead to bistability in terms of hypergraph properties and validate our predictions with numerical simulations. Our results provide a general framework to study the synchronization of phase oscillators in hypergraphs, and they can be extended to hypergraphs with hyperedges of arbitrary sizes, dynamic-structural correlations, and other features.

Flexibility of in vitro cortical circuits influences resilience from microtrauma

Background

Small clusters comprising hundreds to thousands of neurons are an important level of brain architecture that correlates single neuronal properties to fulfill brain function, but the specific mechanisms through which this scaling occurs are not well understood. In this study, we developed an in vitro experimental platform of small neuronal circuits (islands) to probe the importance of structural properties for their development, physiology, and response to microtrauma.

Methods

Primary cortical neurons were plated on a substrate patterned to promote attachment in clusters of hundreds of cells (islands), transduced with GCaMP6f, allowed to mature until 10-13 days in vitro (DIV), and monitored with Ca²⁺ as a non-invasive proxy for electrical activity. We adjusted two structural factors-island size and cellular density-to evaluate their role in guiding spontaneous activity and network formation in neuronal islands.

Results

We found cellular density, but not island size, regulates of circuit activity and network function in this system. Low cellular density islands can achieve many states of activity, while high cellular density biases islands towards a limited regime characterized by low rates of activity and high synchronization, a property we summarized as "flexibility." The injury severity required for an island to lose activity in 50% of its population was significantly higher in low-density, high flexibility islands.

Conclusion

Together, these studies demonstrate flexible living cortical circuits are more resilient to microtrauma, providing the first evidence that initial circuit state may be a key factor to consider when evaluating the consequences of trauma to the cortex.

Plasticity impairment alters community structure but permits successful pattern separation in a hippocampal network model

Patients who suffer from traumatic brain injury (TBI) often complain of learning and memory problems. Their symptoms are principally mediated by the hippocampus and the ability to adapt to stimulus, also known as neural plasticity. Therefore, one plausible injury mechanism is plasticity impairment, which currently lacks comprehensive investigation across TBI research. For these studies, we used a computational network model of the hippocampus that includes the dentate gyrus, CA3, and CA1 with neuron-scale resolution. We simulated mild injury through weakened spike-timing-dependent plasticity (STDP), which modulates synaptic weights according to causal spike timing. In preliminary work, we found functional deficits consisting of decreased firing rate and broadband power in areas CA3 and CA1 after STDP impairment. To address structural changes with these studies, we applied modularity analysis to evaluate how STDP impairment modifies community structure in the hippocampal network. We also studied the emergent function of network-based learning and found that impaired networks could acquire conditioned responses after training, but the magnitude of the response was significantly lower. Furthermore, we examined pattern separation, a prerequisite of learning, by entraining two overlapping patterns. Contrary to our initial hypothesis, impaired networks did not exhibit deficits in pattern separation with either population- or rate-based coding. Collectively, these results demonstrate how a mechanism of injury that operates at the synapse regulates circuit function.

TRPC channels as emerging targets for seizure disorders

Epilepsy is characterized by seizures of diverse types that affect about 1-2% of the population worldwide. Current antiseizure medications are unsatisfactory, as they merely provide symptomatic relief, are ineffective in about one-third of patients, and cause unbearable adverse effects. Transient receptor potential canonical (TRPC) channels are a group of nonselective cation channels involved in many physiological functions. In this review, we provide an overview of recent preclinical studies using both genetic and pharmacological strategies that reveal these receptor-operated calcium-permeable channels may also play fundamental roles in many aspects of epileptic seizures. We also propose that TRPC channels represent appealing targets for epilepsy treatment, with a goal of helping to advance the discovery and development of new antiseizure and/or antiepileptogenic therapies.

Is the forming of neuronal network activity in human-induced pluripotent stem cells important for the detection of drug-induced seizure risks?

BACKGROUND

Functional network activity is a characteristic for neuronal cells, and the complexity of the network activity represents the necessary substrate to support complex brain functions. Drugs that drastically increase the neuronal network activity may have a potential higher risk for seizures in human. Although there has been some recent considerable progress made using cultures from different types of human-induced pluripotent stem cell (hiPSC) derived neurons, one of the primary limitations is the lack of - or very low - network activity.

METHOD

In the present study, we investigated whether the limited neuronal network activity in commercial hiPSC-neurons (CNS.4U®) is capable of detecting drug-induced potential seizure risks. Therefore, we compared the hiPSC-results to those in rat primary neurons with known high neuronal network activity in vitro.

RESULTS

Gene expression and electrical activity from in vitro developing neuronal networks were assessed at multiple time-points. Transcriptomes of 7, 28, and 50 days in vitro were analyzed and compared to those from human brain tissues. Data from measurements of electrical activity using multielectrode arrays (MEAs) indicate that neuronal networks matured gradually over time, albeit in hiPSC this developed slower than rat primary cultures. The response of neuronal networks to neuronal active reference drugs modulating glutamatergic, acetylcholinergic and GABAergic pathways could be detected in both hiPSC-neurons and rat primary neurons. However, in comparison, GABAergic responses were limited in hiPSC-neurons.

CONCLUSION

Overall, despite a slower network development and lower network activity, CNS.4U® hiPSC-neurons can be used to detect drug induced changes in neuronal network activity, as shown by well-known seizurogenic drugs (affecting e.g., the Glycine receptor and Na⁺ channel). However, lower sensitivity to GABA antagonists has been observed.

Self-organization of in vitro neuronal assemblies drives to complex network topology

Activity-dependent self-organization plays an important role in the formation of specific and stereotyped connectivity patterns in neural circuits. By combining neuronal cultures, and tools with approaches from network neuroscience and information theory, we can study how complex network topology emerges from local neuronal interactions. We constructed effective connectivity networks using a transfer entropy analysis of spike trains recorded from rat embryo dissociated hippocampal neuron cultures between 6 and 35 days in vitro to investigate how the topology evolves during maturation. The methodology for constructing the networks considered the synapse delay and addressed the influence of firing rate and population bursts as well as spurious effects on the inference of connections. We found that the number of links in the networks grew over the course of development, shifting from a segregated to a more integrated architecture. As part of this progression, three significant aspects of complex network topology emerged. In agreement with previous in silico and in vitro studies, a small-world architecture was detected, largely due to strong clustering among neurons. Additionally, the networks developed in a modular topology, with most modules comprising nearby neurons. Finally, highly active neurons acquired topological characteristics that made them important nodes to the network and integrators of modules. These findings leverage new insights into how neuronal effective network topology relates to neuronal assembly self-organization mechanisms.

Coupling of in vitro Neocortical-Hippocampal Coculture Bursts Induces Different Spike Rhythms in Individual Networks

Brain-state alternation is important for long-term memory formation. Each brain state can be identified with a specific process in memory formation, e.g., encoding during wakefulness or consolidation during sleeping. The hippocampal-neocortical dialogue was proposed as a hypothetical framework for systems consolidation, which features different cross-frequency couplings between the hippocampus and distributed neocortical regions in different brain states. Despite evidence supporting this hypothesis, little has been reported about how information is processed with shifts in brain states. To address this gap, we developed an in vitro neocortical-hippocampal coculture model to study how activity coupling can affect connections between coupled networks. Neocortical and hippocampal neurons were cultured in two different compartments connected by a micro-tunnel structure. The network activity of the coculture model was recorded by microelectrode arrays underlying the substrate. Rhythmic bursting was observed in the spontaneous activity and electrical evoked responses. Rhythmic bursting activity in one compartment could couple to that in the other via axons passing through the micro-tunnels. Two types of coupling patterns were observed: slow-burst coupling (neocortex at 0.1–0.5 Hz and hippocampus at 1 Hz) and fast burst coupling (neocortex at 20–40 Hz and hippocampus at 4–10 Hz). The network activity showed greater synchronicity in the slow-burst coupling, as indicated by changes in the burstiness index. Network synchronicity analysis suggests the presence of different information processing states under different burst activity coupling patterns. Our results suggest that the hippocampal-neocortical coculture model possesses multiple modes of burst activity coupling between the cortical and hippocampal parts. With the addition of external stimulation, the neocortical-hippocampal network model we developed can elucidate the influence of state shifts on information processing.

Amyloid Beta Oligomers-Induced Ca2+ Entry Pathways: Role of Neuronal Networks, NMDA Receptors and Amyloid Channel Formation

The molecular basis of amyloid toxicity in Alzheimer’s disease (AD) remains controversial. Amyloid β (Aβ) oligomers promote Ca2+ influx, mitochondrial Ca2+ overload and apoptosis in hippocampal neurons in vivo and in vitro, but the primary Ca2+ entry pathways are unclear. We studied Ca2+ entry pathways induced by Aβ oligomers in rat hippocampal and cerebellar neurons. Aβ oligomers induce Ca2+ entry in neurons. Ca2+ responses to Aβ oligomers are large after synaptic networking and prevented by blockers of synaptic transmission. In contrast, in neurons devoid of synaptic connections, Ca2+ responses to Aβ oligomers are small and prevented only by blockers of amyloid channels (NA7) and NMDA receptors (MK801). A combination of NA7 and MK801 nearly abolished Ca2+ responses. Non-neuronal cells bearing NMDA receptors showed Ca2+ responses to oligomers, whereas cells without NMDA receptors did not exhibit Ca2+ responses. The expression of subunits of the NMDA receptor NR1/ NR2A and NR1/NR2B in HEK293 cells lacking endogenous NMDA receptors restored Ca2+ responses to NMDA but not to Aβ oligomers. We conclude that Aβ oligomers promote Ca2+ entry via amyloid channels and NMDA receptors. This may recruit distant neurons intertwisted by synaptic connections, spreading excitation and recruiting further NMDA receptors and voltage-gated Ca2+ channels, leading to excitotoxicity and neuron degeneration in AD.

Mechanistic insights into ultrasonic neurostimulation of disconnected neurons using single short pulses

Ultrasonic neurostimulation is a potentially potent noninvasive therapy, whose mechanism has yet to be elucidated. We designed a system capable of applying ultrasound with minimal reflections to neuronal cultures. Synaptic transmission was pharmacologically controlled, eliminating network effects, enabling examination of single-cell processes. Short single pulses of low-intensity ultrasound were applied, and time-locked responses were examined using calcium imaging. Low-pressure (0.35MPa) ultrasound directly stimulated ∼20% of pharmacologically disconnected neurons, regardless of membrane poration. Stimulation was resistant to the blockade of several purinergic receptor and mechanosensitive ion channel types. Stimulation was blocked, however, by suppression of action potentials. Surprisingly, even extremely short (4μs) pulses were effective, stimulating ∼8% of the neurons. Lower-pressure pulses (0.35MPa) were less effective than higher-pressure ones (0.65MPa). Attrition effects dominated, with no indication of compromised viability. Our results detract from theories implicating cavitation, heating, non-transient membrane pores >1.5nm, pre-synaptic release, or gradual effects. They implicate a post-synaptic mechanism upstream of the action potential, and narrow down the list of possible targets involved.

Postweaning positive modulation of α5GABAA receptors improves autism-like features in prenatal valproate rat model in a sex-specific manner

Autism spectrum disorder (ASD), as a common neurodevelopmental disorder that encompasses impairments in social communication and interaction, as well as repetitive and restrictive behavior, still awaits an effective treatment strategy. The involvement of GABAergic neurotransmission, and especially a deficit of GABA_A receptors that contain the α5 subunits, were implicated in pathogenesis of ASD. Therefore, we tested MP-III-022, a positive allosteric modulator (PAM) selective for α5GABAA receptors, in Wistar rats prenatally exposed to valproic acid, as an animal model useful for studying ASD. Postweaning rats of both sexes were treated for 7 days with vehicle or MP-III-022 at two doses pharmacokinetically determined as selective, and thereafter tested in a behavioral battery (social interaction test, elevated plus maze, spontaneous locomotor activity, and standard and reverse Morris water maze). Additional rats were used for establishing a primary neuronal culture and performing calcium imaging, and determination of hippocampal mRNA levels of GABRA5, NKCC1, and KCC2. MP-III-022 prevented impairments in many parameters connected with social, repetitive and restrictive behavioral domains. The lower and higher dose was more effective in males and females, respectively. Intriguingly, MP-III-022 elicited certain changes in control animals similar to those manifested in valproate animals themselves. Behavioral results were mirrored in GABA switch and spontaneous neuronal activity, assessed with calcium imaging, and also in expression changes of three genes analyzed. Our data support a role of α5GABAA receptors in pathophysiology of ASD, and suggest a potential application of selective PAMs in its treatment, that needs to be researched in a sex-specific manner. LAY SUMMARY: In rats prenatally exposed to valproate as a model of autism, a modulator of α5GABAA receptors ameliorated social, repetitive and restrictive impairments, and, intriguingly, elicited certain autism-like changes in control rats. Behavioral results were mirrored in GABA switch and spontaneous neuronal activity, and partly in gene expression changes. This shows a role of α5GABAA receptors in pathophysiology of ASD, and a potential application of their selective modulators in its treatment.

Multielectrode Arrays for Functional Phenotyping of Neurons from Induced Pluripotent Stem Cell Models of Neurodevelopmental Disorders

In vitro multielectrode array (MEA) systems are increasingly used as higher-throughput platforms for functional phenotyping studies of neurons in induced pluripotent stem cell (iPSC) disease models. While MEA systems generate large amounts of spatiotemporal activity data from networks of iPSC-derived neurons, the downstream analysis and interpretation of such high-dimensional data often pose a significant challenge to researchers. In this review, we examine how MEA technology is currently deployed in iPSC modeling studies of neurodevelopmental disorders. We first highlight the strengths of in vitro MEA technology by reviewing the history of its development and the original scientific questions MEAs were intended to answer. Methods of generating patient iPSC-derived neurons and astrocytes for MEA co-cultures are summarized. We then discuss challenges associated with MEA data analysis in a disease modeling context, and present novel computational methods used to better interpret network phenotyping data. We end by suggesting best practices for presenting MEA data in research publications, and propose that the creation of a public MEA data repository to enable collaborative data sharing would be of great benefit to the iPSC disease modeling community.

Noninvasive inference methods for interaction and noise intensities of coupled oscillators using only spike time data

Identifying interactions is essential for understanding self-organized systems because they are a source of order, function, and complexity. However, distinguishing interaction and noise effect is generally difficult because they both critically affect the stability of an ordered state. We propose methods that enable us to simultaneously infer both interaction and noise intensities. Our methods use only the time series of periodic events such as spike time data and do not require any external stimuli. Moreover, it is not necessary to assume a function form to fit. We numerically demonstrate that our methods yield reasonable inference even for a relatively short time series. These features are particularly beneficial for application in biological and chemical complex systems.

Measurements of interaction intensity are generally achieved by observing responses to perturbations. In biological and chemical systems, external stimuli tend to deteriorate their inherent nature, and thus, it is necessary to develop noninvasive inference methods. In this paper, we propose theoretical methods to infer coupling strength and noise intensity simultaneously in two well-synchronized noisy oscillators through observations of spontaneously fluctuating events such as neural spikes. A phase oscillator model is applied to derive formulae relating each of the parameters to spike time statistics. Using these formulae, each parameter is inferred from a specific set of statistics. We verify these methods using the FitzHugh–Nagumo model as well as the phase model. Our methods do not require external perturbations and thus can be applied to various experimental systems.

All-Optical Electrophysiology in hiPSC-Derived Neurons With Synthetic Voltage Sensors

Voltage imaging and “all-optical electrophysiology” in human induced pluripotent stem cell (hiPSC)-derived neurons have opened unprecedented opportunities for high-throughput phenotyping of activity in neurons possessing unique genetic backgrounds of individual patients. While prior all-optical electrophysiology studies relied on genetically encoded voltage indicators, here, we demonstrate an alternative protocol using a synthetic voltage sensor and genetically encoded optogenetic actuator that generate robust and reproducible results. We demonstrate the functionality of this method by measuring spontaneous and evoked activity in three independent hiPSC-derived neuronal cell lines with distinct genetic backgrounds.

Spontaneous, synchronous zinc spikes oscillate with neural excitability and calcium spikes in primary hippocampal neuron culture

Zinc has been suggested to act as an intracellular signaling molecule due to its regulatory effects on numerous protein targets including enzymes, transcription factors, ion channels, neurotrophic factors, and postsynaptic scaffolding proteins. However, intracellular zinc concentration is tightly maintained at steady levels under natural physiological conditions. Dynamic changes in intracellular zinc concentration have only been detected in certain types of cells that are exposed to pathologic stimuli or upon receptor ligand binding. Unlike calcium, the ubiquitous signaling metal ion that can oscillate periodically and spontaneously in various cells, spontaneous zinc oscillations have never been reported. In this work, we made the novel observation that the developing neurons generated spontaneous and synchronous zinc spikes in primary hippocampal cultures using a fluorescent zinc sensor, FluoZin-3. Blocking of glutamate receptor-dependent calcium influx depleted the zinc spikes, suggesting that these zinc spikes were driven by the glutamate-mediated spontaneous neural excitability and calcium spikes that have been characterized in early developing neurons. Simultaneous imaging of calcium or pH together with zinc, we uncovered that a downward pH spike was evoked with each zinc spike and this transient cellular acidification occurred downstream of calcium spikes but upstream of zinc spikes. Our results suggest that spontaneous, synchronous zinc spikes were generated through calcium influx-induced cellular acidification, which liberates zinc from intracellular zinc binding ligands. Given that changes in zinc concentration can modulate activities of proteins essential for synapse maturation and neuronal differentiation, these zinc spikes might act as important signaling roles in neuronal development.

Unpredictable Oscillations for Hopfield-Type Neural Networks with Delayed and Advanced Arguments

This is the first time that the method for the investigation of unpredictable solutions of differential equations has been extended to unpredictable oscillations of neural networks with a generalized piecewise constant argument, which is delayed and advanced. The existence and exponential stability of the unique unpredictable oscillation are proven. According to the theory, the presence of unpredictable oscillations is strong evidence for Poincaré chaos. Consequently, the paper is a contribution to chaos applications in neuroscience. The model is inspired by chaotic time-varying stimuli, which allow studying the distribution of chaotic signals in neural networks. Unpredictable inputs create an excitation wave of neurons that transmit chaotic signals. The technique of analysis includes the ideas used for differential equations with a piecewise constant argument. The results are illustrated by examples and simulations. They are carried out in MATLAB Simulink to demonstrate the simplicity of the diagrammatic approaches.

Asymmetry underlies stability in power grids

Behavioral homogeneity is often critical for the functioning of network systems of interacting entities. In power grids, whose stable operation requires generator frequencies to be synchronized-and thus homogeneous-across the network, previous work suggests that the stability of synchronous states can be improved by making the generators homogeneous. Here, we show that a substantial additional improvement is possible by instead making the generators suitably heterogeneous. We develop a general method for attributing this counterintuitive effect to converse symmetry breaking, a recently established phenomenon in which the system must be asymmetric to maintain a stable symmetric state. These findings constitute the first demonstration of converse symmetry breaking in real-world systems, and our method promises to enable identification of this phenomenon in other networks whose functions rely on behavioral homogeneity.

Synaptic communication mediates the assembly of a self-organizing circuit that controls reproduction

Migration of gonadotropin-releasing hormone (GnRH) neurons from their birthplace in the nasal placode to their hypothalamic destination is critical for vertebrate reproduction and species persistence. While their migration mode as individual GnRH neurons has been extensively studied, the role of GnRH-GnRH cell communication during migration remains largely unexplored. Here, we show in awake zebrafish larvae that migrating GnRH neurons pause at the nasal-forebrain junction and form clusters that act as interhemisphere neuronal ensembles. Within the ensembles, GnRH neurons create an isolated, spontaneously active circuit that is internally wired through monosynaptic glutamatergic synapses into which newborn GnRH neurons integrate before entering the brain. This initial phase of integration drives a phenotypic switch, which is essential for GnRH neurons to properly migrate toward their hypothalamic destination. Together, these experiments reveal a critical step for reproduction, which depends on synaptic communication between migrating GnRH neurons.

Interstitial ions: A key regulator of state-dependent neural activity?

Throughout the nervous system, ion gradients drive fundamental processes. Yet, the roles of interstitial ions in brain functioning is largely forgotten. Emerging literature is now revitalizing this area of neuroscience by showing that interstitial cations (K+, Ca2+ and Mg2+) are not static quantities but change dynamically across states such as sleep and locomotion. In turn, these state-dependent changes are capable of sculpting neuronal activity; for example, changing the local interstitial ion composition in the cortex is sufficient for modulating the prevalence of slow-frequency neuronal oscillations, or potentiating the gain of visually evoked responses. Disturbances in interstitial ionic homeostasis may also play a central role in the pathogenesis of central nervous system diseases. For example, impairments in K+ buffering occur in a number of neurodegenerative diseases, and abnormalities in neuronal activity in disease models disappear when interstitial K+ is normalized. Here we provide an overview of the roles of interstitial ions in physiology and pathology. We propose the brain uses interstitial ion signaling as a global mechanism to coordinate its complex activity patterns, and ion homeostasis failure contributes to central nervous system diseases affecting cognitive functions and behavior.

Coherent Dynamics Enhanced by Uncorrelated Noise

Synchronization is a widespread phenomenon observed in physical, biological, and social networks, which persists even under the influence of strong noise. Previous research on oscillators subject to common noise has shown that noise can actually facilitate synchronization, as correlations in the dynamics can be inherited from the noise itself. However, in many spatially distributed networks, such as the mammalian circadian system, the noise that different oscillators experience can be effectively uncorrelated. Here, we show that uncorrelated noise can in fact enhance synchronization when the oscillators are coupled. Strikingly, our analysis also shows that uncorrelated noise can be more effective than common noise in enhancing synchronization. We first establish these results theoretically for phase and phase-amplitude oscillators subject to either or both additive and multiplicative noise. We then confirm the predictions through experiments on coupled electrochemical oscillators. Our findings suggest that uncorrelated noise can promote rather than inhibit coherence in natural systems and that the same effect can be harnessed in engineered systems.

Channels to consciousness: a possible role of gap junctions in consciousness

The neurophysiological basis of consciousness is still unknown and one of the most challenging questions in the field of neuroscience and related disciplines. We propose that consciousness is characterized by the maintenance of mental representations of internal and external stimuli for the execution of cognitive operations. Consciousness cannot exist without working memory, and it is likely that consciousness and working memory share the same neural substrates. Here, we present a novel psychological and neurophysiological framework that explains the role of consciousness for cognition, adaptive behavior, and everyday life. A hypothetical architecture of consciousness is presented that is organized as a system of operation and storage units named platforms that are controlled by a consciousness center (central executive/online platform). Platforms maintain mental representations or contents, are entrusted with different executive functions, and operate at different levels of consciousness. The model includes conscious-mode central executive/online and mental time travel platforms and semiconscious steady-state and preconscious standby platforms. Mental representations or contents are represented by neural circuits and their support cells (astrocytes, oligodendrocytes, etc.) and become conscious when neural circuits reverberate, that is, fire sequentially and continuously with relative synchronicity. Reverberatory activity in neural circuits may be initiated and maintained by pacemaker cells/neural circuit pulsars, enhanced electronic coupling via gap junctions, and unapposed hemichannel opening. The central executive/online platform controls which mental representations or contents should become conscious by recruiting pacemaker cells/neural network pulsars, the opening of hemichannels, and promoting enhanced neural circuit coupling via gap junctions.

Astrocytic Regulation of Synchronous Bursting in Cortical Cultures: From Local to Global

Synchronous bursting (SB) is ubiquitous in neuronal networks and independent of network structure. Although it is known to be driven by glutamatergic neurotransmissions, its underlying mechanism remains unclear. Recent studies show that local glutamate recycle by astrocytes affects nearby neuronal activities, which indicate that the local dynamics might also be the origin of SBs in networks. We investigated the effects of local glutamate dynamics on SBs in both cultures developed on multielectrode array (MEA) systems and a tripartite synapse simulation. Local glutamate uptake by astrocytes was altered by pharmacological targeting of GLT-1 glutamate transporters, whereas neuronal firing activities and synaptic glutamate level was simultaneously monitored with MEA and astrocyte-specific glutamate sensors (intensity-based glutamate-sensing fluorescent reporter), respectively. Global SB properties were significantly altered on targeting GLT-1. Detailed simulation of a network with astrocytic glutamate uptake and recycle mechanisms, conforming with the experimental observations, shows that astrocytes function as a slow negative feedback to neuronal activities in the network. SB in the network can be realized as an alternation between positive and negative feedback in the neurons and astrocytes, respectively. An understanding of glutamate trafficking dynamics is of general application to explain how astrocyte malfunction can result in pathological seizure-like phenomena in neuronal systems.

Lipid-Bilayer-Supported 3D Printing of Human Cerebral Cortex Cells Reveals Developmental Interactions

Current understanding of human brain development is rudimentary due to suboptimal in vitro and animal models. In particular, how initial cell positions impact subsequent human cortical development is unclear because experimental spatial control of cortical cell arrangement is technically challenging. 3D cell printing provides a rapid customized approach for patterning. However, it has relied on materials that do not represent the extracellular matrix (ECM) of brain tissue. Therefore, in the present work, a lipid-bilayer-supported printing technique is developed to 3D print human cortical cells in the soft, biocompatible ECM, Matrigel. Printed human neural stem cells (hNSCs) show high viability, neural differentiation, and the formation of functional, stimulus-responsive neural networks. By using prepatterned arrangements of neurons and astrocytes, it is found that hNSC process outgrowth and migration into cell-free matrix and into astrocyte-containing matrix are similar in extent. However, astrocytes enhance the later developmental event of axon bundling. Both young and mature neurons migrate into compartments containing astrocytes; in contrast, astrocytes do not migrate into neuronal domains signifying nonreciprocal chemorepulsion. Therefore, precise prepatterning by 3D printing allows the construction of natural and unnatural patterns that yield important insights into human cerebral cortex development.

Suppression of hypersynchronous network activity in cultured cortical neurons using an ultrasoft silicone scaffold

The spontaneous activity pattern of cortical neurons in dissociated culture is characterized by burst firing that is highly synchronized among a wide population of cells. The degree of synchrony, however, is excessively higher than that in cortical tissues. Here, we employed polydimethylsiloxane (PDMS) elastomers to establish a novel system for culturing neurons on a scaffold with an elastic modulus resembling brain tissue, and investigated the effect of the scaffold's elasticity on network activity patterns in cultured rat cortical neurons. Using whole-cell patch clamp to assess the scaffold effect on the development of synaptic connections, we found that the amplitude of excitatory postsynaptic current, as well as the frequency of spontaneous transmissions, was reduced in neuronal networks grown on an ultrasoft PDMS with an elastic modulus of 0.5 kPa. Furthermore, the ultrasoft scaffold was found to suppress neural correlations in the spontaneous activity of the cultured neuronal network. The dose of GsMTx-4, an antagonist of stretch-activated cation channels (SACs), required to reduce the generation of the events below 1.0 event per min on PDMS substrates was lower than that for neurons on a glass substrate. This suggests that the difference in the baseline level of SAC activation is a molecular mechanism underlying the alteration in neuronal network activity depending on scaffold stiffness. Our results demonstrate the potential application of PDMS with biomimetic elasticity as cell-culture scaffold for bridging the in vivo-in vitro gap in neuronal systems.

Neuronal Degeneration Impairs Rhythms Between Connected Microcircuits

Synchronization of neural activity across brain regions is critical to processes that include perception, learning, and memory. After traumatic brain injury (TBI), neuronal degeneration is one possible effect and can alter communication between neural circuits. Consequently, synchronization between neurons may change and can contribute to both lasting changes in functional brain networks and cognitive impairment in patients. However, fundamental principles relating exactly how TBI at the cellular scale affects synchronization of mesoscale circuits are not well understood. In this work, we use computational networks of Izhikevich integrate-and-fire neurons to study synchronized, oscillatory activity between clusters of neurons, which also adapt according to spike-timing-dependent plasticity (STDP). We study how the connections within and between these neuronal clusters change as unidirectional connections form between the two neuronal populations. In turn, we examine how neuronal deletion, intended to mimic the temporary or permanent loss of neurons in the mesoscale circuit, affects these dynamics. We determine synchronization of two neuronal circuits requires very modest connectivity between these populations; approximately 10% of neurons projecting from one circuit to another circuit will result in high synchronization. In addition, we find that synchronization level inversely affects the strength of connection between neuronal microcircuits - moderately synchronized microcircuits develop stronger intercluster connections than do highly synchronized circuits. Finally, we find that highly synchronized circuits are largely protected against the effects of neuronal deletion but may display changes in frequency properties across circuits with targeted neuronal loss. Together, our results suggest that strongly and weakly connected regions differ in their inherent resilience to damage and may serve different roles in a larger network.

Molecular Mechanisms of REM Sleep

Rapid-eye movement (REM) sleep is a paradoxical sleep state characterized by brain activity similar to wakefulness, rapid-eye-movement, and lack of muscle tone. REM sleep is a fundamental brain function, evolutionary conserved across species, including human, mouse, bird, and even reptiles. The physiological importance of REM sleep is highlighted by severe sleep disorders incurred by a failure in REM sleep regulation. Despite the intense interest in the mechanism of REM sleep regulation, the molecular machinery is largely left to be investigated. In models of REM sleep regulation, acetylcholine has been a pivotal component. However, even newly emerged techniques such as pharmacogenetics and optogenetics have not fully clarified the function of acetylcholine either at the cellular level or neural-circuit level. Recently, we discovered that the G_q type muscarinic acetylcholine receptor genes, Chrm1 and Chrm3, are essential for REM sleep. In this review, we develop the perspective of current knowledge on REM sleep from a molecular viewpoint. This should be a starting point to clarify the molecular and cellular machinery underlying REM sleep regulation and will provide insights to explore physiological functions of REM sleep and its pathological roles in REM-sleep-related disorders such as depression, PTSD, and neurodegenerative diseases.

Critical synchronization dynamics of the Kuramoto model on connectome and small world graphs

The hypothesis, that cortical dynamics operates near criticality also suggests, that it exhibits universal critical exponents which marks the Kuramoto equation, a fundamental model for synchronization, as a prime candidate for an underlying universal model. Here, we determined the synchronization behavior of this model by solving it numerically on a large, weighted human connectome network, containing 836733 nodes, in an assumed homeostatic state. Since this graph has a topological dimension d < 4, a real synchronization phase transition is not possible in the thermodynamic limit, still we could locate a transition between partially synchronized and desynchronized states. At this crossover point we observe power-law–tailed synchronization durations, with τ_t ≃ 1.2(1), away from experimental values for the brain. For comparison, on a large two-dimensional lattice, having additional random, long-range links, we obtain a mean-field value: τ_t ≃ 1.6(1). However, below the transition of the connectome we found global coupling control-parameter dependent exponents 1 < τ_t ≤ 2, overlapping with the range of human brain experiments. We also studied the effects of random flipping of a small portion of link weights, mimicking a network with inhibitory interactions, and found similar results. The control-parameter dependent exponent suggests extended dynamical criticality below the transition point.

Emergence of spatially periodic diffusive waves in small-world neuronal networks

It has been observed in experiment that the anatomical structure of neuronal networks in the brain possesses the feature of small-world networks. Yet how the small-world structure affects network dynamics remains to be fully clarified. Here we study the dynamics of a class of small-world networks consisting of pulse-coupled integrate-and-fire (I&F) neurons. Under stochastic Poisson drive, we find that the activity of the entire network resembles diffusive waves. To understand its underlying mechanism, we analyze the simplified regular-lattice network consisting of firing-rate-based neurons as an approximation to the original I&F small-world network. We demonstrate both analytically and numerically that, with strongly coupled connections, in the absence of noise, the activity of the firing-rate-based regular-lattice network spatially forms a static grating pattern that corresponds to the spatial distribution of the firing rate observed in the I&F small-world neuronal network. We further show that the spatial grating pattern with different phases comprise the continuous attractor of both the I&F small-world and firing-rate-based regular-lattice network dynamics. In the presence of input noise, the activity of both networks is perturbed along the continuous attractor, which gives rise to the diffusive waves. Our numerical simulations and theoretical analysis may potentially provide insights into the understanding of the generation of wave patterns observed in cortical networks.

Role of Human-Induced Pluripotent Stem Cell-Derived Spinal Cord Astrocytes in the Functional Maturation of Motor Neurons in a Multielectrode Array System

The ability to generate human‐induced pluripotent stem cell (hiPSC)‐derived neural cells displaying region‐specific phenotypes is of particular interest for modeling central nervous system biology in vitro. We describe a unique method by which spinal cord hiPSC‐derived astrocytes (hiPSC‐A) are cultured with spinal cord hiPSC‐derived motor neurons (hiPSC‐MN) in a multielectrode array (MEA) system to record electrophysiological activity over time. We show that hiPSC‐A enhance hiPSC‐MN electrophysiological maturation in a time‐dependent fashion. The sequence of plating, density, and age in which hiPSC‐A are cocultured with MN, but not their respective hiPSC line origin, are factors that influence neuronal electrophysiology. When compared to coculture with mouse primary spinal cord astrocytes, we observe an earlier and more robust electrophysiological maturation in the fully human cultures, suggesting that the human origin is relevant to the recapitulation of astrocyte/motor neuron crosstalk. Finally, we test pharmacological compounds on our MEA platform and observe changes in electrophysiological activity, which confirm hiPSC‐MN maturation. These findings are supported by immunocytochemistry and real‐time PCR studies in parallel cultures demonstrating human astrocyte mediated changes in the structural maturation and protein expression profiles of the neurons. Interestingly, this relationship is reciprocal and coculture with neurons influences astrocyte maturation as well. Taken together, these data indicate that in a human in vitro spinal cord culture system, astrocytes support hiPSC‐MN maturation in a time‐dependent and species‐specific manner and suggest a closer approximation of in vivo conditions. stem cells translational medicine2019;8:1272&1285

We describe a fully human, spinal cord‐specific, coculture platform with human‐induced pluripotent stem cell‐derived motor neurons and astrocytes for multielectrode array recording. We show that human‐induced pluripotent stem cell‐derived motor neurons/human‐induced pluripotent stem cell‐derived astrocytes bidirectional morphological and molecular maturation is reflected by electrophysiological recordings with multielectrode array recording.

Novel roles of ER stress in repressing neural activity and seizures through Mdm2- and p53-dependent protein translation

Seizures can induce endoplasmic reticulum (ER) stress, and sustained ER stress contributes to neuronal death after epileptic seizures. Despite the recent debate on whether inhibiting ER stress can reduce neuronal death after seizures, whether and how ER stress impacts neural activity and seizures remain unclear. In this study, we discovered that the acute ER stress response functions to repress neural activity through a protein translation-dependent mechanism. We found that inducing ER stress promotes the expression and distribution of murine double minute-2 (Mdm2) in the nucleus, leading to ubiquitination and down-regulation of the tumor suppressor p53. Reduction of p53 subsequently maintains protein translation, before the onset of translational repression seen during the latter phase of the ER stress response. Disruption of Mdm2 in an Mdm2 conditional knockdown (cKD) mouse model impairs ER stress-induced p53 down-regulation, protein translation, and reduction of neural activity and seizure severity. Importantly, these defects in Mdm2 cKD mice were restored by both pharmacological and genetic inhibition of p53 to mimic the inactivation of p53 seen during ER stress. Altogether, our study uncovered a novel mechanism by which neurons respond to acute ER stress. Further, this mechanism plays a beneficial role in reducing neural activity and seizure severity. These findings caution against inhibition of ER stress as a neuroprotective strategy for seizures, epilepsies, and other pathological conditions associated with excessive neural activity.

One-third of epilepsy patients respond poorly to current anti-epileptic drugs. Thus, there is an urgent need to characterize cellular behavior during seizures, and the corresponding molecular mechanisms in order to develop better therapies. Seizures are known to induce ER stress but how the ER stress response functions to modulate seizure activity is unknown. Our study provides evidence to demonstrate a novel and beneficial role for the ER stress response in reducing neural activity and seizure severity. Mechanistically, we found that these beneficial effects are mediated by elevated protein translation, which is triggered by the activation of Mdm2-p53 signaling, during the early ER stress response. Our findings suggest that therapeutic attempts to reduce ER stress in epilepsies may result in worsening seizure activity and therefore caution against inhibition of ER stress as a neuroprotective strategy for epilepsies.

Klotho deficiency affects the spine morphology and network synchronization of neurons

Klotho-deficient mice rapidly develop cognitive impairment and show some evidence of the onset of neurodegeneration. However, it is impossible to investigate the long-term consequences on the brain because of the dramatic shortening of lifespan caused by systemic klotho deficiency. As klotho expression is downregulated with advancing organismal age, understanding the mechanisms of klotho action is important for developing novel strategies to support healthy brain aging. Previously, we reported that klotho-deficient mice show enhanced long-term potentiation prior to the onset of cognitive impairment. To inform this unusual phenotype, herein, we examined neuronal structure and in vitro synaptic function. Our results indicate that klotho deficiency causes the population of dendritic spines to shift towards increased head diameter and decreased length consistent with mature, mushroom type spines. Multi-electrode array recordings from klotho-deficient neurons show increased synchronous firing and activity changes reflective of increased neuronal network activity. Supplementation of the neuronal growth media with recombinant shed klotho corrected some but not all of the activity changes caused by klotho deficiency. Last, in vivo we found that klotho-deficient mice have a decreased latency to induced seizure activity. Together these data show that klotho-deficient memory impairments are underpinned by structural and functional changes that may preclude ongoing normal cognition.

Next Generation Networks: Featuring the Potential Role of Emerging Applications in Translational Oncology

Nowadays, networks are pervasively used as examples of models suitable to mathematically represent and visualize the complexity of systems associated with many diseases, including cancer. In the cancer context, the concept of network entropy has guided many studies focused on comparing equilibrium to disequilibrium (i.e., perturbed) conditions. Since these conditions reflect both structural and dynamic properties of network interaction maps, the derived topological characterizations offer precious support to conduct cancer inference. Recent innovative directions have emerged in network medicine addressing especially experimental omics approaches integrated with a variety of other data, from molecular to clinical and also electronic records, bioimaging etc. This work considers a few theoretically relevant concepts likely to impact the future of applications in personalized/precision/translational oncology. The focus goes to specific properties of networks that are still not commonly utilized or studied in the oncological domain, and they are: controllability, synchronization and symmetry. The examples here provided take inspiration from the consideration of metastatic processes, especially their progression through stages and their hallmark characteristics. Casting these processes into computational frameworks and identifying network states with specific modular configurations may be extremely useful to interpret or even understand dysregulation patterns underlying cancer, and associated events (onset, progression) and disease phenotypes.

Null model exhibiting synchronized dynamics in uncoupled oscillators

The phenomenon of phase synchronization of oscillatory systems, arising out of feedback coupling is ubiquitous across physics and biology. In noisy, complex systems, one generally observes transient epochs of synchronization followed by nonsynchronous dynamics. How does one guarantee that the observed transient epochs of synchronization are arising from an underlying feedback mechanism and not from some peculiar statistical properties of the system? This question is particularly important for complex biological systems, where the search for a nonexistent feedback mechanism may turn out to be an enormous waste of resources. In this article, we propose a null model for synchronization, motivated by expectations on the dynamical behavior of biological systems, to provide a quantitative measure of the confidence with which one can infer the existence of a feedback mechanism based on observation of transient synchronized behavior. We demonstrate the application of our null model to the phenomenon of gait synchronization in free-swimming nematodes, Caenorhabditis elegans.

The emergence of synchrony in networks of mutually inferring neurons

This paper considers the emergence of a generalised synchrony in ensembles of coupled self-organising systems, such as neurons. We start from the premise that any self-organising system complies with the free energy principle, in virtue of placing an upper bound on its entropy. Crucially, the free energy principle allows one to interpret biological systems as inferring the state of their environment or external milieu. An emergent property of this inference is synchronisation among an ensemble of systems that infer each other. Here, we investigate the implications of neuronal dynamics by simulating neuronal networks, where each neuron minimises its free energy. We cast the ensuing ensemble dynamics in terms of inference and show that cardinal behaviours of neuronal networks - both in vivo and in vitro - can be explained by this framework. In particular, we test the hypotheses that (i) generalised synchrony is an emergent property of free energy minimisation; thereby explaining synchronisation in the resting brain: (ii) desynchronisation is induced by exogenous input; thereby explaining event-related desynchronisation and (iii) structure learning emerges in response to causal structure in exogenous input; thereby explaining functional segregation in real neuronal systems.

Modeling breathing rhythms

Computational models are helping researchers to understand how certain properties of neurons contribute to respiratory rhythms.