Detection of synchronized burst firing in cultured human induced pluripotent stem cell-derived neurons using a 4-step method

Exploring Kainic Acid-Induced Alterations in Circular Tripartite Networks with Advanced Analysis Tools

Brain activity implies the orchestrated functioning of interconnected brain regions. Typical in vitro models aim to mimic the brain using single human pluripotent stem cell-derived neuronal networks. However, the field is constantly evolving to model brain functions more accurately through the use of new paradigms, e.g., brain-on-a-chip models with compartmentalized structures and integrated sensors. These methods create novel data requiring more complex analysis approaches. The previously introduced circular tripartite network concept models the connectivity between spatially diverse neuronal structures. The model consists of a microfluidic device allowing axonal connectivity between separated neuronal networks with an embedded microelectrode array to record both local and global electrophysiological activity patterns in the closed circuitry. The existing tools are suboptimal for the analysis of the data produced with this model. Here, we introduce advanced tools for synchronization and functional connectivity assessment. We used our custom-designed analysis to assess the interrelations between the kainic acid (KA)-exposed proximal compartment and its nonexposed distal neighbors before and after KA. Novel multilevel circuitry bursting patterns were detected and analyzed in parallel with the inter- and intracompartmental functional connectivity. The effect of KA on the proximal compartment was captured, and the spread of this effect to the nonexposed distal compartments was revealed. KA induced divergent changes in bursting behaviors, which may be explained by distinct baseline activity and varied intra- and intercompartmental connectivity strengths. The circular tripartite network concept combined with our developed analysis advances importantly both face and construct validity in modeling human epilepsy in vitro.

Calcium-Dependent Hyperexcitability in Human Stem Cell-Derived Rett Syndrome Neuronal Networks

Background

Mutations in MECP2 predominantly cause Rett syndrome and can be modeled in vitro using human stem cell-derived neurons. Patients with Rett syndrome have signs of cortical hyperexcitability, such as seizures. Human stem cell-derived MECP2 null excitatory neurons have smaller soma size and reduced synaptic connectivity but are also hyperexcitable due to higher input resistance. Paradoxically, networks of MECP2 null neurons show a decrease in the frequency of network bursts consistent with a hypoconnectivity phenotype. Here, we examine this issue.

Methods

We reanalyzed multielectrode array data from 3 isogenic MECP2 cell line pairs recorded over 6 weeks (n = 144). We used a custom burst detection algorithm to analyze network events and isolated a phenomenon that we termed reverberating super bursts (RSBs). To probe potential mechanisms of RSBs, we conducted pharmacological manipulations using bicuculline, EGTA-AM, and DMSO on 1 cell line (n = 34).

Results

RSBs, often misidentified as single long-duration bursts, consisted of a large-amplitude initial burst followed by several high-frequency, low-amplitude minibursts. Our analysis revealed that MECP2 null networks exhibited increased frequency of RSBs, which produced increased bursts compared with isogenic controls. Bicuculline or DMSO treatment did not affect RSBs. EGTA-AM selectively eliminated RSBs and rescued network burst dynamics.

Conclusions

During early development, MECP2 null neurons are hyperexcitable and produce hyperexcitable networks. This may predispose them to the emergence of hypersynchronic states that potentially translate into seizures. Network hyperexcitability depends on asynchronous neurotransmitter release that is likely driven by presynaptic Ca2+ and can be rescued by EGTA-AM to restore typical network dynamics.

Evaluation of neurotoxicity for pesticide-related compounds in human iPS cell-derived neurons using microelectrode array

In vivo evaluations of chemicals in neurotoxicity have certain limitations due to the considerable time and cost required, necessity of extrapolation from rodents to humans, and limited information on toxicity mechanisms. To address this issue, the development of in vitro test methods using new approach methodologies (NAMs) is important to evaluate the chemicals in neurotoxicity. Microelectrode array (MEA) allows the assessment of changes in neural network activity caused by compound administration. However, studies on compound evaluation criteria are scarce. In this study, we evaluated the impact of pesticides on neural activity using MEA measurements of human iPSC-derived neurons. A principal component analysis was performed on the electrical physiological parameters obtained by MEA measurements, and the influence of excessive neural activity due to compound addition was defined using the standard deviation of neural activity with solvent addition as the reference. By using known seizurogenic compounds as positive controls for neurotoxicity in MEA and evaluating pesticides with insufficient verification of their neurotoxicity in humans, we demonstrated that these pesticides exhibit neurotoxicity in humans. In conclusion, our data suggest that the neurotoxicity evaluation method in human iPSC neurons using MEA measurements could be one of the in vitro neurotoxicity test methods that could replace animal experiments.

An integrated approach for early in vitro seizure prediction utilizing hiPSC neurons and human ion channel assays

Seizure liability remains a significant cause of attrition throughout drug development. Advances in stem cell biology coupled with an increased understanding of the role of ion channels in seizure offer an opportunity for a new paradigm in screening. We assessed the activity of 15 pro-seizurogenic compounds (7 CNS active therapies, 4 GABA receptor antagonists, and 4 other reported seizurogenic compounds) using automated electrophysiology against a panel of 14 ion channels (Nav1.1, Nav1.2, Nav1.6, Kv7.2/7.3, Kv7.3/7.5, Kv1.1, Kv4.2, KCa4.1, Kv2.1, Kv3.1, KCa1.1, GABA α1β2γ2, nicotinic α4β2, NMDA 1/2A). These were selected based on linkage to seizure in genetic/pharmacological studies. Fourteen compounds demonstrated at least one "hit" against the seizure panel and 11 compounds inhibited 2 or more ion channels. Next, we assessed the impact of the 15 compounds on electrical signaling using human-induced pluripotent stem cell neurons in microelectrode array (MEA). The CNS active therapies (amoxapine, bupropion, chlorpromazine, clozapine, diphenhydramine, paroxetine, quetiapine) all caused characteristic changes to electrical activity in key parameters indicative of seizure such as network burst frequency and duration. The GABA antagonist picrotoxin increased all parameters, but the antibiotics amoxicillin and enoxacin only showed minimal changes. Acetaminophen, included as a negative control, caused no changes in any of the parameters assessed. Overall, pro-seizurogenic compounds showed a distinct fingerprint in the ion channel/MEA panel. These studies highlight the potential utility of an integrated in vitro approach for early seizure prediction to provide mechanistic information and to support optimal drug design in early development, saving time and resources.

Verification of the seizure liability of compounds based on their in vitro functional activity in cultured rat cortical neurons and co-cultured human iPSC-derived neurons with astrocytes and in vivo extrapolation to cerebrospinal fluid concentration

Methodical screening of safe and efficient drug candidate compounds is crucial for drug development. A high-throughput and accurate compound evaluation method targeting the central nervous system can be developed using in vitro neural networks. In particular, an evaluation system based on a human-derived neural network that can act as an alternative to animal experiments is desirable to avoid interspecific differences. A microelectrode array (MEA) is one such evaluation system, and can measure in vitro neural activity; however, studies on compound evaluation criteria and in vitro to in vivo extrapolation are scarce. In this study, we identified the parameters that can eliminate the effects of solvents from neural activity data obtained using MEA allow for accurate compound evaluation. Additionally, we resolved the issue associated with compound evaluation criteria during MEA using principal component analysis by considering the neuronal activity exceeding standard deviation (SD) of the solvent as indicator of seizurogenic potential. Overall, 10 seizurogenic compounds and three negative controls were assessed using MEA-based co-cultured human-induced pluripotent stem cell-derived neurons and astrocytes, and primary rat cortical neurons. In addition, we determined rat cerebrospinal fluid (CSF) concentrations during tremor and convulsion in response to exposure to test compounds. To characterize the in vitro to in vivo extrapolation and species differences, we compared the concentrations at which neuronal activity exceeding the SD range of the solvent was detectable using the MEA system and rat CSF concentration.

Neuroprotective Potential of L-Glutamate Transporters in Human Induced Pluripotent Stem Cell-Derived Neural Cells against Excitotoxicity

Human induced pluripotent stem cell (hiPSC)-derived neural cells have started to be used in safety/toxicity tests at the preclinical stage of drug development. As previously reported, hiPSC-derived neurons exhibit greater tolerance to excitotoxicity than those of primary cultures of rodent neurons; however, the underlying mechanisms remain unknown. We here investigated the functions of L-glutamate (L-Glu) transporters, the most important machinery to maintain low extracellular L-Glu concentrations, in hiPSC-derived neural cells. We also clarified the contribution of respective L-Glu transporter subtypes. At 63 days in vitro (DIV), we detected neuronal circuit functions in hiPSC-derived neural cells by a microelectrode array system (MEA). At 63 DIV, exposure to 100 μM L-Glu for 24 h did not affect the viability of neural cells. 100 µM L-Glu in the medium decreased to almost 0 μM in 60 min. Pharmacological inhibition of excitatory amino acid transporter 1 (EAAT1) and EAAT2 suppressed almost 100% of L-Glu decrease. In the presence of this inhibitor, 100 μM L-Glu dramatically decreased cell viability. These results suggest that in hiPSC-derived neural cells, EAAT1 and EAAT2 are the predominant L-Glu transporters, and their uptake potentials are the reasons for the tolerance of hiPSC-derived neurons to excitotoxicity.

Large-Area Field Potential Imaging Having Single Neuron Resolution Using 236 880 Electrodes CMOS-MEA Technology

The electrophysiological technology having a high spatiotemporal resolution at the single-cell level and noninvasive measurements of large areas provide insights on underlying neuronal function. Here, a complementary metal-oxide semiconductor (CMOS)-microelectrode array (MEA) is used that uses 236 880 electrodes each with an electrode size of 11.22 × 11.22 µm and 236 880 covering a wide area of 5.5 × 5.9 mm in presenting a detailed and single-cell-level neural activity analysis platform for brain slices, human iPS cell-derived cortical networks, peripheral neurons, and human brain organoids. Propagation pattern characteristics between brain regions changes the synaptic propagation into compounds based on single-cell time-series patterns, classification based on single DRG neuron firing patterns and compound responses, axonal conduction characteristics and changes to anticancer drugs, and network activities and transition to compounds in brain organoids are extracted. This detailed analysis of neural activity at the single-cell level using the CMOS-MEA provides a new understanding of the basic mechanisms of brain circuits in vitro and ex vivo, on human neurological diseases for drug discovery, and compound toxicity assessment.

A functional neuron maturation device provides convenient application on microelectrode array for neural network measurement

BACKGROUND

Microelectrode array (MEA) systems are valuable for in vitro assessment of neurotoxicity and drug efficiency. However, several difficulties such as protracted functional maturation and high experimental costs hinder the use of MEA analysis requiring human induced pluripotent stem cells (hiPSCs). Neural network functional parameters are also needed for in vitro to in vivo extrapolation.

METHODS

In the present study, we produced a cost effective nanofiber culture platform, the SCAD device, for long-term culture of hiPSC-derived neurons and primary peripheral neurons. The notable advantage of SCAD device is convenient application on multiple MEA systems for neuron functional analysis.

RESULTS

We showed that the SCAD device could promote functional maturation of cultured hiPSC-derived neurons, and neurons responded appropriately to convulsant agents. Furthermore, we successfully analyzed parameters for in vitro to in vivo extrapolation, i.e., low-frequency components and synaptic propagation velocity of the signal, potentially reflecting neural network functions from neurons cultured on SCAD device. Finally, we measured the axonal conduction velocity of peripheral neurons.

CONCLUSIONS

Neurons cultured on SCAD devices might constitute a reliable in vitro platform to investigate neuron functions, drug efficacy and toxicity, and neuropathological mechanisms by MEA.

Responses to antibiotics in human iPSC-derived neurons based on the clinical antibiotic-associated encephalopathy classification

Antibiotic-associated encephalopathy (AAE) is a central nervous system disorder caused by antibiotics administration and classified into three types based on clinical symptoms. Type 1 AAE causes seizures and myoclonus, type 2 causes psychiatric symptoms, and type 3 is characterized by cerebellar ataxia. In this study, we investigated whether the electrical activity of in vitro human iPSC-derived neurons to antibiotics could be classified based on the 3 types of AAEs classified by clinical symptoms. Glutamatergic, GABAergic neurons and astrocytes differentiated from human iPS cells were seeded on micro-electrode array (MEA). The cumulative administration of 13 different antimicrobials detected changes in neural activity that differed according to AAE type. Next, we classified the antimicrobials by principal component analysis (PCA) and confirmed the AAE type of each agent. We found that Types 1-3 AAE agents were distributed separately. The classification of antibiotics depending on electrophysiological response characteristics was consistent with the clinical practice classification of AAEs. In conclusion, the combination of electrophysiological responses of human iPS cell-derived neural networks measured by MEA plus multivariate analysis methods will effectively detect and classify antibiotics developmental risks.

Long-term morphological and functional dynamics of human stem cell-derived neuronal networks on high-density micro-electrode arrays

Comprehensive electrophysiological characterizations of human induced pluripotent stem cell (hiPSC)-derived neuronal networks are essential to determine to what extent these in vitro models recapitulate the functional features of in vivo neuronal circuits. High-density micro-electrode arrays (HD-MEAs) offer non-invasive recording with the best spatial and temporal resolution possible to date. For 3 months, we tracked the morphology and activity features of developing networks derived from a transgenic hiPSC line in which neurogenesis is inducible by neurogenic transcription factor overexpression. Our morphological data revealed large-scale structural changes from homogeneously distributed neurons in the first month to the formation of neuronal clusters over time. This led to a constant shift in position of neuronal cells and clusters on HD-MEAs and corresponding changes in spatial distribution of the network activity maps. Network activity appeared as scarce action potentials (APs), evolved as local bursts with longer duration and changed to network-wide synchronized bursts with higher frequencies but shorter duration over time, resembling the emerging burst features found in the developing human brain. Instantaneous firing rate data indicated that the fraction of fast spiking neurons (150–600 Hz) increases sharply after 63 days post induction (dpi). Inhibition of glutamatergic synapses erased burst features from network activity profiles and confirmed the presence of mature excitatory neurotransmission. The application of GABAergic receptor antagonists profoundly changed the bursting profile of the network at 120 dpi. This indicated a GABAergic switch from excitatory to inhibitory neurotransmission during circuit development and maturation. Our results suggested that an emerging GABAergic system at older culture ages is involved in regulating spontaneous network bursts. In conclusion, our data showed that long-term and continuous microscopy and electrophysiology readouts are crucial for a meaningful characterization of morphological and functional maturation in stem cell-derived human networks. Most importantly, assessing the level and duration of functional maturation is key to subject these human neuronal circuits on HD-MEAs for basic and biomedical applications.

Raster plots machine learning to predict the seizure liability of drugs and to identify drugs

In vitro microelectrode array (MEA) assessment using human induced pluripotent stem cell (iPSC)-derived neurons holds promise as a method of seizure and toxicity evaluation. However, there are still issues surrounding the analysis methods used to predict seizure and toxicity liability as well as drug mechanisms of action. In the present study, we developed an artificial intelligence (AI) capable of predicting the seizure liability of drugs and identifying drugs using deep learning based on raster plots of neural network activity. The seizure liability prediction AI had a prediction accuracy of 98.4% for the drugs used to train it, classifying them correctly based on their responses as either seizure-causing compounds or seizure-free compounds. The AI also made concentration-dependent judgments of the seizure liability of drugs that it was not trained on. In addition, the drug identification AI implemented using the leave-one-sample-out scheme could distinguish among 13 seizure-causing compounds as well as seizure-free compound responses, with a mean accuracy of 99.9 ± 0.1% for all drugs. These AI prediction models are able to identify seizure liability concentration-dependence, rank the level of seizure liability based on the seizure liability probability, and identify the mechanism of the action of compounds. This holds promise for the future of in vitro MEA assessment as a powerful, high-accuracy new seizure liability prediction method.

Principal Component Analysis to Distinguish Seizure Liability of Drugs in Human iPS Cell-Derived Neurons

Screening for drug discovery targeting the central nervous system requires the establishment of efficient and highly accurate toxicity test methods that can reduce costs and time while maintaining high throughput using the function of an in vitro neural network. In particular, an evaluation system using a human-derived neural network is desirable in terms of species difference. Despite the attention the microelectrode array (MEA) is attracting among the evaluation systems that can measure in vitro neural activity, an effective analysis method for evaluation of toxicity and mechanism of action has not yet been established. Here we established analytical parameters and multivariate analysis method capable of detecting seizure liability of drugs using MEA measurement of human iPS cell-derived neurons. Using the spike time series data of all drugs, we established periodicity as a new analytical parameter. Periodicity has facilitated the detection of responses to seizurogenic drugs, previously difficult to detect with conventional analytical parameters. By constructing a multivariate analytical method that identifies a parameter set that achieves an arbitrary condition, we found that the parameter set comprising total spikes, maximum frequency, inter maximum frequency interval, coefficient of variance of inter maximum frequency interval, and periodicity can uniformly detect the seizure liability of seizurogenic drugs with different mechanisms of action. Seizurogenic drugs were suggested to increase the regularity of the network burst in MEA measurements in human iPS cell-derived neurons.

Variant-specific changes in persistent or resurgent sodium current in SCN8A-related epilepsy patient-derived neurons

Missense variants in the SCN8A voltage-gated sodium channel gene are linked to early-infantile epileptic encephalopathy type 13, also known as SCN8A-related epilepsy. These patients exhibit a wide spectrum of intractable seizure types, severe developmental delay, movement disorders, and elevated risk of sudden unexpected death in epilepsy. The mechanisms by which SCN8A variants lead to epilepsy are poorly understood, although heterologous expression systems and mouse models have demonstrated altered sodium current properties. To investigate these mechanisms using a patient-specific model, we generated induced pluripotent stem cells from three patients with missense variants in SCN8A: p.R1872>L (Patient 1); p.V1592>L (Patient 2); and p.N1759>S (Patient 3). Using small molecule differentiation into excitatory neurons, induced pluripotent stem cell-derived neurons from all three patients displayed altered sodium currents. Patients 1 and 2 had elevated persistent current, while Patient 3 had increased resurgent current compared to controls. Neurons from all three patients displayed shorter axon initial segment lengths compared to controls. Further analyses focused on one of the patients with increased persistent sodium current (Patient 1) and the patient with increased resurgent current (Patient 3). Excitatory cortical neurons from both patients had prolonged action potential repolarization. Using doxycycline-inducible expression of the neuronal transcription factors neurogenin 1 and 2 to synchronize differentiation of induced excitatory cortical-like neurons, we investigated network activity and response to pharmacotherapies. Both small molecule differentiated and induced patient neurons displayed similar abnormalities in action potential repolarization. Patient induced neurons showed increased burstiness that was sensitive to phenytoin, currently a standard treatment for SCN8A-related epilepsy patients, or riluzole, an FDA-approved drug used in amyotrophic lateral sclerosis and known to block persistent and resurgent sodium currents, at pharmacologically relevant concentrations. Patch-clamp recordings showed that riluzole suppressed spontaneous firing and increased the action potential firing threshold of patient-derived neurons to more depolarized potentials. Two of the patients in this study were prescribed riluzole off-label. Patient 1 had a 50% reduction in seizure frequency. Patient 3 experienced an immediate and dramatic seizure reduction with months of seizure freedom. An additional patient with a SCN8A variant in domain IV of Nav1.6 (p.V1757>I) had a dramatic reduction in seizure frequency for several months after starting riluzole treatment, but then seizures recurred. Our results indicate that patient-specific neurons are useful for modelling SCN8A-related epilepsy and demonstrate SCN8A variant-specific mechanisms. Moreover, these findings suggest that patient-specific neuronal disease modelling offers a useful platform for discovering precision epilepsy therapies.

Can We Panelize Seizure?

Seizure liability remains a significant cause of attrition in drug discovery and development, leading to loss of competitiveness, delays, and increased costs. Current detection methods rely on observations made in in vivo studies intended to support clinical trials, such as tremors or other abnormal movements. These signs could be missed or misinterpreted; thus, definitive confirmation of drug-induced seizure requires a follow-up electroencephalogram study. There has been progress in in vivo detection of seizure using automated video systems that record and analyze animal movements. Nonetheless, it would be preferable to have earlier prediction of seizurogenic risk that could be used to eliminate liabilities early in discovery while there are options for medicinal chemists making potential new drugs. Attrition due to cardiac adverse events has benefited from routine early screening; could we reduce attrition due to seizure using a similar approach? Specifically, microelectrode arrays could be used to detect potential seizurogenic signals in stem-cell-derived neurons. In addition, there is clear evidence implicating neuronal voltage-gated and ligand-gated ion channels, GPCRs and transporters in seizure. Interactions with surrounding glial cells during states of stress or inflammation can also modulate ion channel function in neurons, adding to the challenge of seizure prediction. It is timely to evaluate the opportunity to develop an in vitro assessment of seizure linked to a panel of ion channel assays that predict seizure, with the aim of influencing structure-activity relationship at the design stage and eliminating compounds predicted to be associated with pro-seizurogenic state.

Cortical neurons derived from human pluripotent stem cells lacking FMRP display altered spontaneous firing patterns

BACKGROUND

Fragile X syndrome (FXS), a neurodevelopmental disorder, is a leading monogenetic cause of intellectual disability and autism spectrum disorder. Notwithstanding the extensive studies using rodent and other pre-clinical models of FXS, which have provided detailed mechanistic insights into the pathophysiology of this disorder, it is only relatively recently that human stem cell-derived neurons have been employed as a model system to further our understanding of the pathophysiological events that may underlie FXS. Our study assesses the physiological properties of human pluripotent stem cell-derived cortical neurons lacking fragile X mental retardation protein (FMRP).

METHODS

Electrophysiological whole-cell voltage- and current-clamp recordings were performed on two control and three FXS patient lines of human cortical neurons derived from induced pluripotent stem cells. In addition, we also describe the properties of an isogenic pair of lines in one of which FMR1 gene expression has been silenced.

RESULTS

Neurons lacking FMRP displayed bursts of spontaneous action potential firing that were more frequent but shorter in duration compared to those recorded from neurons expressing FMRP. Inhibition of large conductance Ca²⁺-activated K⁺ currents and the persistent Na⁺ current in control neurons phenocopies action potential bursting observed in neurons lacking FMRP, while in neurons lacking FMRP pharmacological potentiation of voltage-dependent Na⁺ channels phenocopies action potential bursting observed in control neurons. Notwithstanding the changes in spontaneous action potential firing, we did not observe any differences in the intrinsic properties of neurons in any of the lines examined. Moreover, we did not detect any differences in the properties of miniature excitatory postsynaptic currents in any of the lines.

CONCLUSIONS

Pharmacological manipulations can alter the action potential burst profiles in both control and FMRP-null human cortical neurons, making them appear like their genetic counterpart. Our studies indicate that FMRP targets that have been found in rodent models of FXS are also potential targets in a human-based model system, and we suggest potential mechanisms by which activity is altered.

L-type voltage-gated calcium channel regulation of in vitro human cortical neuronal networks

The combination of in vitro multi-electrode arrays (MEAs) and the neuronal differentiation of stem cells offers the capability to study human neuronal networks from patient or engineered human cell lines. Here, we use MEA-based assays to probe synaptic function and network interactions of hiPSC-derived neurons. Neuronal network behaviour first emerges at approximately 30 days of culture and is driven by glutamate neurotransmission. Over a further 30 days, inhibitory GABAergic signalling shapes network behaviour into a synchronous regular pattern of burst firing activity and low activity periods. Gene mutations in L-type voltage gated calcium channel subunit genes are strongly implicated as genetic risk factors for the development of schizophrenia and bipolar disorder. We find that, although basal neuronal firing rate is unaffected, there is a dose-dependent effect of L-type voltage gated calcium channel inhibitors on synchronous firing patterns of our hiPSC-derived neural networks. This demonstrates that MEA assays have sufficient sensitivity to detect changes in patterns of neuronal interaction that may arise from hypo-function of psychiatric risk genes. Our study highlights the utility of in vitro MEA based platforms for the study of hiPSC neural network activity and their potential use in novel compound screening.

Impact of Sleep-Wake-Associated Neuromodulators and Repetitive Low-Frequency Stimulation on Human iPSC-Derived Neurons

The cross-regional neurons in the brainstem, hypothalamus, and thalamus regulate the central nervous system, including the cerebral cortex, in a sleep–wake cycle-dependent manner. A characteristic brain wave, called slow wave, of about 1 Hz is observed during non-REM sleep, and the sleep homeostasis hypothesis proposes that the synaptic connection of a neural network is weakened during sleep. In the present study, in vitro human induced pluripotent stem cell (iPSC)-derived neurons, we investigated the responses to the neuromodulator known to be involved in sleep–wake regulation. We also determined whether long-term depression (LTD)-like phenomena could be induced by 1 Hz low-frequency stimulation (LFS), which is within the range of the non-REM sleep slow wave. A dose-dependent increase was observed in the number of synchronized burst firings (SBFs) when 0.1–1000 nM of serotonin, acetylcholine, histamine, orexin, or noradrenaline, all with increased extracellular levels during wakefulness, was administered to hiPSC-derived dopaminergic (DA) neurons. The number of SBFs repeatedly increased up to 5 h after 100 nM serotonin administration, inducing a 24-h rhythm cycle. Next, in human iPSC-derived glutamate neurons, 1 Hz LFS was administered four times for 15 min every 90 min. A significant reduction in both the number of firings and SBFs was observed in the 15 min immediately after LFS. Decreased frequency of spontaneous activity and recovery over time were repeatedly observed. Furthermore, we found that LFS attenuates synaptic connections, and particularly attenuates the strong connections in the neuronal network, and does not cause uniform attenuation. These results suggest sleep–wake states can be mimicked by cyclic neuromodulator administration and show that LTD-like phenomena can be induced by LFS in vitro human iPSC-derived neurons. These results could be applied in studies on the mechanism of slow waves during sleep or in an in vitro drug efficacy evaluation depending on sleep–wake state.

In vitro Models for Seizure-Liability Testing Using Induced Pluripotent Stem Cells

The brain is the most complex organ in the body, controlling our highest functions, as well as regulating myriad processes which incorporate the entire physiological system. The effects of prospective therapeutic entities on the brain and central nervous system (CNS) may potentially cause significant injury, hence, CNS toxicity testing forms part of the “core battery” of safety pharmacology studies. Drug-induced seizure is a major reason for compound attrition during drug development. Currently, the rat ex vivo hippocampal slice assay is the standard option for seizure-liability studies, followed by primary rodent cultures. These models can respond to diverse agents and predict seizure outcome, yet controversy over the relevance, efficacy, and cost of these animal-based methods has led to interest in the development of human-derived models. Existing platforms often utilize rodents, and so lack human receptors and other drug targets, which may produce misleading data, with difficulties in inter-species extrapolation. Current electrophysiological approaches are typically used in a low-throughput capacity and network function may be overlooked. Human-derived induced pluripotent stem cells (iPSCs) are a promising avenue for neurotoxicity testing, increasingly utilized in drug screening and disease modeling. Furthermore, the combination of iPSC-derived models with functional techniques such as multi-electrode array (MEA) analysis can provide information on neuronal network function, with increased sensitivity to neurotoxic effects which disrupt different pathways. The use of an in vitro human iPSC-derived neural model for neurotoxicity studies, combined with high-throughput techniques such as MEA recordings, could be a suitable addition to existing pre-clinical seizure-liability testing strategies.

Toxicological evaluation of convulsant and anticonvulsant drugs in human induced pluripotent stem cell-derived cortical neuronal networks using an MEA system

Functional evaluation assays using human induced pluripotent stem cell (hiPSC)-derived neurons can predict the convulsion toxicity of new drugs and the neurological effects of antiepileptic drugs. However, differences in responsiveness depending on convulsant type and antiepileptic drugs, and an evaluation index capable of comparing in vitro responses with in vivo responses are not well known. We observed the difference in synchronized burst patterns in the epileptiform activities induced by pentylentetrazole (PTZ) and 4-aminopryridine (4-AP) with different action mechanisms using multi-electrode arrays (MEAs); we also observed that 100 µM of the antiepileptic drug phenytoin suppressed epileptiform activities induced by PTZ, but increased those induced by 4-AP. To compare in vitro results with in vivo convulsive responses, frequency analysis of below 250 Hz, excluding the spike component, was performed. The in vivo convulsive firing enhancement of the high γ wave and β wave component were observed remarkably in in vitro hiPSC-derived neurons with astrocytes in co-culture. MEA measurement of hiPSC-derived neurons in co-culture with astrocytes and our analysis methods, including frequency analysis, appear effective for predicting convulsion toxicity, side effects, and their mechanism of action as well as the comparison of convulsions induced in vivo.