Quantitative differences in developmental profiles of spontaneous activity in cortical and hippocampal cultures

Graphene Microelectrode Arrays, 4D Structured Illumination Microscopy, and a Machine Learning Spike Sorting Algorithm Permit the Analysis of Ultrastructural Neuronal Changes During Neuronal Signaling in a Model of Niemann-Pick Disease Type C

Simultaneously recording network activity and ultrastructural changes of the synapse is essential for advancing understanding of the basis of neuronal functions. However, the rapid millisecond-scale fluctuations in neuronal activity and the subtle sub-diffraction resolution changes of synaptic morphology pose significant challenges to this endeavor. Here, specially designed graphene microelectrode arrays (G-MEAs) are used, which are compatible with high spatial resolution imaging across various scales as well as permit high temporal resolution electrophysiological recordings to address these challenges. Furthermore, alongside G-MEAs, an easy-to-implement machine learning algorithm is developed to efficiently process the large datasets collected from MEA recordings. It is demonstrated that the combined use of G-MEAs, machine learning (ML) spike analysis, and 4D structured illumination microscopy (SIM) enables monitoring the impact of disease progression on hippocampal neurons which are treated with an intracellular cholesterol transport inhibitor mimicking Niemann-Pick disease type C (NPC), and show that synaptic boutons, compared to untreated controls, significantly increase in size, leading to a loss in neuronal signaling capacity.

Biphasic response of human iPSC-derived neural network activity following exposure to a sarin-surrogate nerve agent

Organophosphorus nerve agents (OPNA) are hazardous environmental exposures to the civilian population and have been historically weaponized as chemical warfare agents (CWA). OPNA exposure can lead to several neurological, sensory, and motor symptoms that can manifest into chronic neurological illnesses later in life. There is still a large need for technological advancement to better understand changes in brain function following OPNA exposure. The human-relevant in vitro multi-electrode array (MEA) system, which combines the MEA technology with human stem cell technology, has the potential to monitor the acute, sub-chronic, and chronic consequences of OPNA exposure on brain activity. However, the application of this system to assess OPNA hazards and risks to human brain function remains to be investigated. In a concentration-response study, we have employed a human-relevant MEA system to monitor and detect changes in the electrical activity of engineered neural networks to increasing concentrations of the sarin surrogate 4-nitrophenyl isopropyl methylphosphonate (NIMP). We report a biphasic response in the spiking (but not bursting) activity of neurons exposed to low (i.e., 0.4 and 4 μM) versus high concentrations (i.e., 40 and 100 μM) of NIMP, which was monitored during the exposure period and up to 6 days post-exposure. Regardless of the NIMP concentration, at a network level, communication or coordination of neuronal activity decreased as early as 60 min and persisted at 24 h of NIMP exposure. Once NIMP was removed, coordinated activity was no different than control (0 μM of NIMP). Interestingly, only in the high concentration of NIMP did coordination of activity at a network level begin to decrease again at 2 days post-exposure and persisted on day 6 post-exposure. Notably, cell viability was not affected during or after NIMP exposure. Also, while the catalytic activity of AChE decreased during NIMP exposure, its activity recovered once NIMP was removed. Gene expression analysis suggests that human iPSC-derived neurons and primary human astrocytes resulted in altered genes related to the cell's interaction with the extracellular environment, its intracellular calcium signaling pathways, and inflammation, which could have contributed to how neurons communicated at a network level.

Modeling mTORopathy-related epilepsy in cultured murine hippocampal neurons using the multi-electrode array

The mechanistic target of rapamycin complex 1 (mTORC1) signaling pathway is a ubiquitous cellular pathway. mTORopathies, a group of disorders characterized by hyperactivity of the mTORC1 pathway, illustrate the prominent role of the mTOR pathway in disease pathology, often profoundly affecting the central nervous system. One of the most debilitating symptoms of mTORopathies is drug-resistant epilepsy, emphasizing the urgent need for a deeper understanding of disease mechanisms to develop novel anti-epileptic drugs. In this study, we explored the multiwell Multi-electrode array (MEA) system as a tool to identify robust network activity parameters in an approach to model mTORopathy-related epilepsy in vitro. To this extent, we cultured mouse primary hippocampal neurons on the multiwell MEA to identify robust network activity phenotypes in mTORC1-hyperactive neuronal networks. mTOR-hyperactivity was induced either through deletion of Tsc1 or overexpression of a constitutively active RHEB variant identified in patients, RHEBp.P37L. mTORC1 dependency of the phenotypes was assessed using rapamycin, and vigabatrin was applied to treat epilepsy-like phenotypes. We show that hyperactivity of the mTORC1 pathway leads to aberrant network activity. In both the Tsc1-KO and RHEB-p.P37L models, we identified changes in network synchronicity, rhythmicity, and burst characteristics. The presence of these phenotypes is prevented upon early treatment with the mTORC1-inhibitor rapamycin. Application of rapamycin in mature neuronal cultures could only partially rescue the network activity phenotypes. Additionally, treatment with the anti-epileptic drug vigabatrin reduced network activity and restored burst characteristics. Taken together, we showed that mTORC1-hyperactive neuronal cultures on the multiwell MEA system present reliable network activity phenotypes that can be used as an assay to explore the potency of new drug treatments targeting epilepsy in mTORopathy patients and may give more insights into the pathophysiological mechanisms underlying epilepsy in these patients.

MEA-NAP compares microscale functional connectivity, topology, and network dynamics in organoid or monolayer neuronal cultures

Microelectrode array (MEA) recordings are commonly used to compare firing and burst rates in neuronal cultures. MEA recordings can also reveal microscale functional connectivity, topology, and network dynamics-patterns seen in brain networks across spatial scales. Network topology is frequently characterized in neuroimaging with graph theoretical metrics. However, few computational tools exist for analyzing microscale functional brain networks from MEA recordings. Here, we present a MATLAB MEA network analysis pipeline (MEA-NAP) for raw voltage time-series acquired from single- or multi-well MEAs. Applications to 3D human cerebral organoids or 2D human-derived or murine cultures reveal differences in network development, including topology, node cartography, and dimensionality. MEA-NAP incorporates multi-unit template-based spike detection, probabilistic thresholding for determining significant functional connections, and normalization techniques for comparing networks. MEA-NAP can identify network-level effects of pharmacologic perturbation and/or disease-causing mutations and, thus, can provide a translational platform for revealing mechanistic insights and screening new therapeutic approaches.

Spatiotemporal analysis of 3D human iPSC-derived neural networks using a 3D multi-electrode array

While there is a growing appreciation of three-dimensional (3D) neural tissues (i.e., hydrogel-based, organoids, and spheroids), shown to improve cellular health and network activity to mirror brain-like activity in vivo, functional assessment using current electrophysiology techniques (e.g., planar multi-electrode arrays or patch clamp) has been technically challenging and limited to surface measurements at the bottom or top of the 3D tissue. As next-generation MEAs, specifically 3D MEAs, are being developed to increase the spatial precision across all three dimensions (X, Y, Z), development of improved computational analytical tools to discern region-specific changes within the Z dimension of the 3D tissue is needed. In the present study, we introduce a novel computational analytical pipeline to analyze 3D neural network activity recorded from a "bottom-up" 3D MEA integrated with a 3D hydrogel-based tissue containing human iPSC-derived neurons and primary astrocytes. Over a period of ~6.5 weeks, we describe the development and maturation of 3D neural activity (i.e., features of spiking and bursting activity) within cross sections of the 3D tissue, based on the vertical position of the electrode on the 3D MEA probe, in addition to network activity (identified using synchrony analysis) within and between cross sections. Then, using the sequential addition of postsynaptic receptor antagonists, bicuculline (BIC), 2-amino-5-phosphonovaleric acid (AP-5), and 6-cyano-5-nitroquinoxaline-2,3-dione (CNQX), we demonstrate that networks within and between cross sections of the 3D hydrogel-based tissue show a preference for GABA and/or glutamate synaptic transmission, suggesting differences in the network composition throughout the neural tissue. The ability to monitor the functional dynamics of the entire 3D reconstructed neural tissue is a critical bottleneck; here we demonstrate a computational pipeline that can be implemented in studies to better interpret network activity within an engineered 3D neural tissue and have a better understanding of the modeled organ tissue.

Emergent structural and functional properties of hippocampal multi-cellular aggregates

Hippocampal neural networks are distinctly capable of integrating multi-modal sensory inputs to drive memory formation. Neuroscientific investigations using simplified in vitro models have greatly relied on planar (2D) neuronal cultures made from dissociated tissue. While these models have served as simple, cost-effective, and high-throughput tools for examining various morphological and electrophysiological characteristics of hippocampal networks, 2D cultures fail to reconstitute critical elements of the brain microenvironment that may be necessary for the emergence of sophisticated integrative network properties. To address this, we utilized a forced aggregation technique to generate high-density (>100,000 cells/mm³) multi-cellular three-dimensional aggregates using rodent embryonic hippocampal tissue. We contrasted the emergent structural and functional properties of aggregated (3D) and dissociated (2D) cultures over 28 days in vitro (DIV). Hippocampal aggregates displayed robust axonal fasciculation across large distances and significant neuronal polarization, i.e., spatial segregation of dendrites and axons, at earlier time points compared to dissociated cultures. Moreover, we found that astrocytes in aggregate cultures self-organized into non-overlapping quasi-domains and developed highly stellate morphologies resembling astrocyte structures in vivo. We maintained cultures on multi-electrode arrays (MEAs) to assess spontaneous electrophysiological activity for up to 28 DIV. We found that 3D networks of aggregated cultures developed highly synchronized networks and with high burstiness by 28 DIV. We also demonstrated that dual-aggregate networks became active by 7 DIV, in contrast to single-aggregate networks which became active and developed synchronous bursting activity with repeating motifs by 14 DIV. Taken together, our findings demonstrate that the high-density, multi-cellular, 3D microenvironment of hippocampal aggregates supports the recapitulation of emergent biofidelic morphological and functional properties. Our findings suggest that neural aggregates may be used as segregated, modular building blocks for the development of complex, multi-nodal neural network topologies.

Emerging Activity Patterns and Synaptogenesis in Dissociated Hippocampal Cultures

Cultures of dissociated hippocampal neurons display a stereotypical development of network activity patterns within the first three weeks of maturation. During this process, network connections develop and the associated spiking patterns range from increasing levels of activity in the first two weeks to regular bursting activity in the third week of maturation. Characterization of network structure is important to examine the mechanisms underlying the emergent functional organization of neural circuits. To accomplish this, confocal microscopy techniques have been used and several automated synapse quantification algorithms based on (co)localization of synaptic structures have been proposed recently. However, these approaches suffer from the arbitrary nature of intensity thresholding and the lack of correction for random-chance colocalization. To address this problem, we developed and validated an automated synapse quantification algorithm that requires minimal operator intervention. Next, we applied our approach to quantify excitatory and inhibitory synaptogenesis using confocal images of dissociated hippocampal neuronal cultures captured at 5, 8, 14 and 20 days in vitro, the time period associated with the development of distinct neuronal activity patterns. As expected, we found that synaptic density increased with maturation, coinciding with increasing spiking activity in the network. Interestingly, the third week of the maturation exhibited a reduction in excitatory synaptic density suggestive of synaptic pruning that coincided with the emergence of regular bursting activity in the network.

Electrophysiological Activity of Primary Cortical Neuron-Glia Mixed Cultures

Neuroinflammation plays a central role in many neurological disorders, ranging from traumatic brain injuries to neurodegeneration. Electrophysiological activity is an essential measure of neuronal function, which is influenced by neuroinflammation. In order to study neuroinflammation and its electrophysiological fingerprints, there is a need for in vitro models that accurately capture the in vivo phenomena. In this study, we employed a new tri-culture of primary rat neurons, astrocytes, and microglia in combination with extracellular electrophysiological recording techniques using multiple electrode arrays (MEAs) to determine the effect of microglia on neural function and the response to neuroinflammatory stimuli. Specifically, we established the tri-culture and its corresponding neuron-astrocyte co-culture (lacking microglia) counterpart on custom MEAs and monitored their electrophysiological activity for 21 days to assess culture maturation and network formation. As a complementary assessment, we quantified synaptic puncta and averaged spike waveforms to determine the difference in excitatory to inhibitory neuron ratio (E/I ratio) of the neurons. The results demonstrate that the microglia in the tri-culture do not disrupt neural network formation and stability and may be a better representation of the in vivo rat cortex due to its more similar E/I ratio as compared to more traditional isolated neuron and neuron-astrocyte co-cultures. In addition, only the tri-culture displayed a significant decrease in both the number of active channels and spike frequency following pro-inflammatory lipopolysaccharide exposure, highlighting the critical role of microglia in capturing electrophysiological manifestations of a representative neuroinflammatory insult. We expect the demonstrated technology to assist in studying various brain disease mechanisms.

Nanomaterial-based microelectrode arrays for in vitro bidirectional brain-computer interfaces: a review

A bidirectional in vitro brain-computer interface (BCI) directly connects isolated brain cells with the surrounding environment, reads neural signals and inputs modulatory instructions. As a noninvasive BCI, it has clear advantages in understanding and exploiting advanced brain function due to the simplified structure and high controllability of ex vivo neural networks. However, the core of ex vivo BCIs, microelectrode arrays (MEAs), urgently need improvements in the strength of signal detection, precision of neural modulation and biocompatibility. Notably, nanomaterial-based MEAs cater to all the requirements by converging the multilevel neural signals and simultaneously applying stimuli at an excellent spatiotemporal resolution, as well as supporting long-term cultivation of neurons. This is enabled by the advantageous electrochemical characteristics of nanomaterials, such as their active atomic reactivity and outstanding charge conduction efficiency, improving the performance of MEAs. Here, we review the fabrication of nanomaterial-based MEAs applied to bidirectional in vitro BCIs from an interdisciplinary perspective. We also consider the decoding and coding of neural activity through the interface and highlight the various usages of MEAs coupled with the dissociated neural cultures to benefit future developments of BCIs.

Spikebench: An open benchmark for spike train time-series classification

Modern well-performing approaches to neural decoding are based on machine learning models such as decision tree ensembles and deep neural networks. The wide range of algorithms that can be utilized to learn from neural spike trains, which are essentially time-series data, results in the need for diverse and challenging benchmarks for neural decoding, similar to the ones in the fields of computer vision and natural language processing. In this work, we propose a spike train classification benchmark, based on open-access neural activity datasets and consisting of several learning tasks such as stimulus type classification, animal's behavioral state prediction, and neuron type identification. We demonstrate that an approach based on hand-crafted time-series feature engineering establishes a strong baseline performing on par with state-of-the-art deep learning-based models for neural decoding. We release the code allowing to reproduce the reported results.

Influence of microchannel geometry on device performance and electrophysiological recording fidelity during long-term studies of connected neural populations

Compartmentalized microfluidic neural cell culture platforms, which physically separate axons from the neural soma using a series of microchannels, have been used for studying a wide range of pathological conditions and basic neuroscience questions. While each study has different experimental needs, the fundamental design of these devices has largely remained unchanged and a systematic study to establish long-term neural cultures in this format is lacking. Here, we investigate the influence of microchannel geometry and cell seeding density on device performance particularly in the context of long-term studies of synaptically-connected, yet fluidically-isolated neural populations of neurons and glia. Of the different experimental parameters, the microchannel height was the principal determinant of device performance, where the other parameters offer additional degrees of freedom in customizing such devices for specific applications. We condense the effects of these parameters into design rules and demonstrate their utility in engineering a microfluidic neural culture platform with integrated microelectrode arrays. The engineered device successfully recorded from primary rat cortical cells for 59 days in vitro with more than on order of magnitude enhancement in signal-to-noise ratio in the microchannels.

Developmental depression-to-facilitation shift controls excitation-inhibition balance

Changes in the short-term dynamics of excitatory synapses over development have been observed throughout cortex, but their purpose and consequences remain unclear. Here, we propose that developmental changes in synaptic dynamics buffer the effect of slow inhibitory long-term plasticity, allowing for continuously stable neural activity. Using computational modeling we demonstrate that early in development excitatory short-term depression quickly stabilises neural activity, even in the face of strong, unbalanced excitation. We introduce a model of the commonly observed developmental shift from depression to facilitation and show that neural activity remains stable throughout development, while inhibitory synaptic plasticity slowly balances excitation, consistent with experimental observations. Our model predicts changes in the input responses from phasic to phasic-and-tonic and more precise spike timings. We also observe a gradual emergence of short-lasting memory traces governed by short-term plasticity development. We conclude that the developmental depression-to-facilitation shift may control excitation-inhibition balance throughout development with important functional consequences.

Using computational modelling this study proposes that the commonly observed depression-to-facilitation shift across development controls excitation-inhibition balance in the brain.

The dual action of glioma-derived exosomes on neuronal activity: synchronization and disruption of synchrony

Seizures represent a frequent symptom in gliomas and significantly impact patient morbidity and quality of life. Although the pathogenesis of tumor-related seizures is not fully understood, accumulating evidence indicates a key role of the peritumoral microenvironment. Brain cancer cells interact with neurons by forming synapses with them and by releasing exosomes, cytokines, and other small molecules. Strong interactions among neurons often lead to the synchronization of their activity. In this paper, we used an in vitro model to investigate the role of exosomes released by glioma cell lines and by patient-derived glioma stem cells (GSCs). The addition of exosomes released by U87 glioma cells to neuronal cultures at day in vitro (DIV) 4, when neurons are not yet synchronous, induces synchronization. At DIV 7-12 neurons become highly synchronous, and the addition of the same exosomes disrupts synchrony. By combining Ca²⁺ imaging, electrical recordings from single neurons with patch-clamp electrodes, substrate-integrated microelectrode arrays, and immunohistochemistry, we show that synchronization and de-synchronization are caused by the combined effect of (i) the formation of new neuronal branches, associated with a higher expression of Arp3, (ii) the modification of synaptic efficiency, and (iii) a direct action of exosomes on the electrical properties of neurons, more evident at DIV 7-12 when the threshold for spike initiation is significantly reduced. At DIV 7-12 exosomes also selectively boost glutamatergic signaling by increasing the number of excitatory synapses. Remarkably, de-synchronization was also observed with exosomes released by glioma-associated stem cells (GASCs) from patients with low-grade glioma but not from patients with high-grade glioma, where a more variable outcome was observed. These results show that exosomes released from glioma modify the electrical properties of neuronal networks and that de-synchronization caused by exosomes from low-grade glioma can contribute to the neurological pathologies of patients with brain cancers.

Dose-dependent consequences of sub-chronic fentanyl exposure on neuron and glial co-cultures

Fentanyl is one of the most common opioid analgesics administered to patients undergoing surgery or for chronic pain management. While the side effects of chronic fentanyl abuse are recognized (e.g., addiction, tolerance, impairment of cognitive functions, and inhibit nociception, arousal, and respiration), it remains poorly understood what and how changes in brain activity from chronic fentanyl use influences the respective behavioral outcome. Here, we examined the functional and molecular changes to cortical neural network activity following sub-chronic exposure to two fentanyl concentrations, a low (0.01 μM) and high (10 μM) dose. Primary rat co-cultures, containing cortical neurons, astrocytes, and oligodendrocyte precursor cells, were seeded in wells on either a 6-well multi-electrode array (MEA, for electrophysiology) or a 96-well tissue culture plate (for serial endpoint bulk RNA sequencing analysis). Once networks matured (at 28 days in vitro), co-cultures were treated with 0.01 or 10 μM of fentanyl for 4 days and monitored daily. Only high dose exposure to fentanyl resulted in a decline in features of spiking and bursting activity as early as 30 min post-exposure and sustained for 4 days in cultures. Transcriptomic analysis of the complex cultures after 4 days of fentanyl exposure revealed that both the low and high dose induced gene expression changes involved in synaptic transmission, inflammation, and organization of the extracellular matrix. Collectively, the findings of this in vitro study suggest that while neuroadaptive changes to neural network activity at a systems level was detected only at the high dose of fentanyl, transcriptomic changes were also detected at the low dose conditions, suggesting that fentanyl rapidly elicits changes in plasticity.

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.

Comparative microelectrode array data of the functional development of hPSC-derived and rat neuronal networks

We present a dataset of microelectrode array (MEA) recordings from human pluripotent stem cell (hPSC)-derived and rat embryonic cortical neurons during their in vitro maturation. The data were prepared to assess extracellularly recorded spontaneous activity and to compare the functional development of these neuronal networks. In addition to recordings of spontaneous activity, we provide pharmacological responses of hPSC-derived and rat cortical cultures at their mature stage. Together with the recorded electrode raw data, we share the analysis code to form a comprehensive dataset including spike times, spike waveforms, burst activity and network synchronization metrics calculated with two different connectivity estimators. Moreover, we provide the analysis code that produced the key scientific findings published previously with this dataset. This large dataset enables investigation of the functional aspects of maturing cortical neuronal networks and provides substantial parameters to assess the differences and similarities between hPSC-derived and rat cortical networks in vitro. This publicly available dataset will be beneficial, especially for experimental and computational neuroscientists.

MT5-MMP promotes neuroinflammation, neuronal excitability and Aβ production in primary neuron/astrocyte cultures from the 5xFAD mouse model of Alzheimer’s disease

Background

Membrane-type matrix metalloproteinase 5 (MT5-MMP) deficiency in the 5xFAD mouse model of Alzheimer's disease (AD) reduces brain neuroinflammation and amyloidosis, and prevents deficits in synaptic activity and cognition in prodromal stages of the disease. In addition, MT5-MMP deficiency prevents interleukin-1 beta (IL-1β)-mediated inflammation in the peripheral nervous system. In this context, we hypothesized that the MT5-MMP/IL-1β tandem could regulate nascent AD pathogenic events in developing neural cells shortly after the onset of transgene activation.

Methods

To test this hypothesis, we used 11–14 day in vitro primary cortical cultures from wild type, MT5-MMP−/−, 5xFAD and 5xFAD/MT5-MMP−/− mice, and evaluated the impact of MT5-MMP deficiency and IL-1β treatment for 24 h, by performing whole cell patch-clamp recordings, RT-qPCR, western blot, gel zymography, ELISA, immunocytochemistry and adeno-associated virus (AAV)-mediated transduction.

Results

5xFAD cells showed higher levels of MT5-MMP than wild type, concomitant with higher basal levels of inflammatory mediators. Moreover, MT5-MMP-deficient cultures had strong decrease of the inflammatory response to IL-1β, as well as decreased stability of recombinant IL-1β. The levels of amyloid beta peptide (Aβ) were similar in 5xFAD and wild-type cultures, and IL-1β treatment did not affect Aβ levels. Instead, the absence of MT5-MMP significantly reduced Aβ by more than 40% while sparing APP metabolism, suggesting altogether no functional crosstalk between IL-1β and APP/Aβ, as well as independent control of their levels by MT5-MMP. The lack of MT5-MMP strongly downregulated the AAV-induced neuronal accumulation of the C-terminal APP fragment, C99, and subsequently that of Aβ. Finally, MT5-MMP deficiency prevented basal hyperexcitability observed in 5xFAD neurons, but not hyperexcitability induced by IL-1β treatment.

Conclusions

Neuroinflammation and hyperexcitability precede Aβ accumulation in developing neural cells with nascent expression of AD transgenes. MT5-MMP deletion is able to tune down basal neuronal inflammation and hyperexcitability, as well as APP/Aβ metabolism. In addition, MT5-MMP deficiency prevents IL-1β-mediated effects in brain cells, except hyperexcitability. Overall, this work reinforces the idea that MT5-MMP is at the crossroads of pathogenic AD pathways that are already incipiently activated in developing neural cells, and that targeting MT5-MMP opens interesting therapeutic prospects.

The Association between Hypoxia-Induced Low Activity and Apoptosis Strongly Resembles That between TTX-Induced Silencing and Apoptosis

In the penumbra of a brain infarct, neurons initially remain structurally intact, but perfusion is insufficient to maintain neuronal activity at physiological levels. Improving neuronal recovery in the penumbra has large potential to advance recovery of stroke patients, but penumbral pathology is incompletely understood, and treatments are scarce. We hypothesize that low activity in the penumbra is associated with apoptosis and thus contributes to irreversible neuronal damage. We explored the putative relationship between low neuronal activity and apoptosis in cultured neurons exposed to variable durations of hypoxia or TTX. We combined electrophysiology and live apoptosis staining in 42 cultures, and compared effects of hypoxia and TTX silencing in terms of network activity and apoptosis. Hypoxia rapidly reduced network activity, but cultures showed limited apoptosis during the first 12 h. After 24 h, widespread apoptosis had occurred. This was associated with full activity recovery observed upon reoxygenation within 12 h, but not after 24 h. Similarly, TTX exposure strongly reduced activity, with full recovery upon washout within 12 h, but not after 24 h. Mean temporal evolution of apoptosis in TTX-treated cultures was the same as in hypoxic cultures. These results suggest that prolonged low activity may be a common factor in the pathways towards apoptosis.

Early prediction of developing spontaneous activity in cultured neuronal networks

Synchronization and bursting activity are intrinsic electrophysiological properties of in vivo and in vitro neural networks. During early development, cortical cultures exhibit a wide repertoire of synchronous bursting dynamics whose characterization may help to understand the parameters governing the transition from immature to mature networks. Here we used machine learning techniques to characterize and predict the developing spontaneous activity in mouse cortical neurons on microelectrode arrays (MEAs) during the first three weeks in vitro. Network activity at three stages of early development was defined by 18 electrophysiological features of spikes, bursts, synchrony, and connectivity. The variability of neuronal network activity during early development was investigated by applying k-means and self-organizing map (SOM) clustering analysis to features of bursts and synchrony. These electrophysiological features were predicted at the third week in vitro with high accuracy from those at earlier times using three machine learning models: Multivariate Adaptive Regression Splines, Support Vector Machines, and Random Forest. Our results indicate that initial patterns of electrical activity during the first week in vitro may already predetermine the final development of the neuronal network activity. The methodological approach used here may be applied to explore the biological mechanisms underlying the complex dynamics of spontaneous activity in developing neuronal cultures.

Culture of Rat Primary Cortical Cells for Microelectrode Array (MEA) Recordings to Screen for Acute and Developmental Neurotoxicity

Neurotoxicity testing of chemicals, drug candidates, and environmental pollutants still relies on extensive in vivo studies that are very costly, time-consuming, and ethically debated due to the large number of animals typically used. Currently, rat primary cortical cultures are widely used for in vitro neurotoxicity studies, as they closely resemble the in vitro brain with respect to the diversity of cell types, their physiological functions, and the pathological processes that they undergo. Common in vitro assays for neurotoxicity screening often focus on very target-specific endpoints such as morphological, biochemical, or electrophysiological changes, and such narrow focus can hamper translation and interpretation. Microelectrode array (MEA) recordings provide a non-invasive platform for extracellular recording of electrical activity of cultured neuronal cells, thereby enabling the evaluation of changes in neuronal (network) function as a sensitive and integrated endpoint for neurotoxicity screening. Here, we describe an in vitro approach for assessing changes in neuronal network function as a measure for neurotoxicity, using rat primary cortical cultures grown on MEAs. We provide a detailed protocol for the culture of rat primary cortical cells, and describe several experimental procedures to address acute, subchronic, and chronic exposure scenarios. We additionally describe the steps for processing and analyzing MEA and cell viability data. © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Isolation and culture of rat primary cortical cells on 48-well MEA plates Support Protocol 1: Pretreatment and washing of 48-well MEA plates before first use or for re-use Support Protocol 2: Coating of 48-well MEA plates with 0.1% PEI solution Basic Protocol 2: MEA measurements during acute exposure Alternate Protocol 1: MEA measurements during subchronic exposure Alternate Protocol 2: MEA measurements during chronic exposure Support Protocol 3: Determination of cell viability after MEA experiments Basic Protocol 3: MEA data processing Basic Protocol 4: Analyzing MEA experiments after acute and subchronic exposure Alternate Protocol 3: Analyzing MEA experiments after chronic exposure.

Presenilin-Deficient Neurons and Astrocytes Display Normal Mitochondrial Phenotypes

Presenilin 1 (PS1) and Presenilin 2 (PS2) are predominantly known as the catalytic subunits of the γ-secretase complex that generates the amyloid-β (Aβ) peptide, the major constituent of the senile plaques found in the brain of Alzheimer's disease (AD) patients. Apart from their role in γ-secretase activity, a growing number of cellular functions have been recently attributed to PSs. Notably, PSs were found to be enriched in mitochondria-associated membranes (MAMs) where mitochondria and endoplasmic reticulum (ER) interact. PS2 was more specifically reported to regulate calcium shuttling between these two organelles by controlling the formation of functional MAMs. We have previously demonstrated in mouse embryonic fibroblasts (MEF) an altered mitochondrial morphology along with reduced mitochondrial respiration and increased glycolysis in PS2-deficient cells (PS2KO). This phenotype was restored by the stable re-expression of human PS2. Still, all these results were obtained in immortalized cells, and one bottom-line question is to know whether these observations hold true in central nervous system (CNS) cells. To that end, we carried out primary cultures of PS1 knockdown (KD), PS2KO, and PS1KD/PS2KO (PSdKO) neurons and astrocytes. They were obtained from the same litter by crossing PS2 heterozygous; PS1 floxed (PS2+/-; PS1flox/flox) animals. Genetic downregulation of PS1 was achieved by lentiviral expression of the Cre recombinase in primary cultures. Strikingly, we did not observe any mitochondrial phenotype in PS1KD, PS2KO, or PSdKO primary cultures in basal conditions. Mitochondrial respiration and membrane potential were similar in all models, as were the glycolytic flux and NAD+/NADH ratio. Likewise, mitochondrial morphology and content was unaltered by PS expression. We further investigated the differences between results we obtained here in primary nerve cells and those previously reported in MEF cell lines by analyzing PS2KO primary fibroblasts. We found no mitochondrial dysfunction in this model, in line with observations in PS2KO primary neurons and astrocytes. Together, our results indicate that the mitochondrial phenotype observed in immortalized PS2-deficient cell lines cannot be extrapolated to primary neurons, astrocytes, and even to primary fibroblasts. The PS-dependent mitochondrial phenotype reported so far might therefore be the consequence of a cell immortalization process and should be critically reconsidered regarding its relevance to AD.

Functional and transcriptional characterization of complex neuronal co-cultures

Brain-on-a-chip systems are designed to simulate brain activity using traditional in vitro cell culture on an engineered platform. It is a noninvasive tool to screen new drugs, evaluate toxicants, and elucidate disease mechanisms. However, successful recapitulation of brain function on these systems is dependent on the complexity of the cell culture. In this study, we increased cellular complexity of traditional (simple) neuronal cultures by co-culturing with astrocytes and oligodendrocyte precursor cells (complex culture). We evaluated and compared neuronal activity (e.g., network formation and maturation), cellular composition in long-term culture, and the transcriptome of the two cultures. Compared to simple cultures, neurons from complex co-cultures exhibited earlier synapse and network development and maturation, which was supported by localized synaptophysin expression, up-regulation of genes involved in mature neuronal processes, and synchronized neural network activity. Also, mature oligodendrocytes and reactive astrocytes were only detected in complex cultures upon transcriptomic analysis of age-matched cultures. Functionally, the GABA antagonist bicuculline had a greater influence on bursting activity in complex versus simple cultures. Collectively, the cellular complexity of brain-on-a-chip systems intrinsically develops cell type-specific phenotypes relevant to the brain while accelerating the maturation of neuronal networks, important features underdeveloped in traditional cultures.

Distinct regulation of bioenergetics and translation by group I mGluR and NMDAR

Neuronal activity is responsible for the high energy consumption in the brain. However, the cellular mechanisms draining ATP upon the arrival of a stimulus are yet to be explored systematically at the post-synapse. Here, we provide evidence that a significant fraction of ATP is consumed upon glutamate stimulation to energize mGluR-induced protein synthesis. We find that both mGluR and NMDAR alter protein synthesis and ATP consumption with distinct kinetics at the synaptic-dendritic compartments. While mGluR activation leads to a rapid and sustained reduction in neuronal ATP levels, NMDAR activation has no immediate impact on the same. ATP consumption correlates inversely with the kinetics of protein synthesis for both receptors. We observe a persistent elevation in protein synthesis within 5 minutes of mGluR activation and a robust inhibition of the same within 2 minutes of NMDAR activation, assessed by the phosphorylation status of eEF2 and metabolic labeling. However, a delayed protein synthesis-dependent ATP expenditure ensues after 15 minutes of NMDAR stimulation. We identify a central role for AMPK in the correlation between protein synthesis and ATP consumption. AMPK is dephosphorylated and inhibited upon mGluR activation, while it is phosphorylated upon NMDAR activation. Perturbing AMPK activity disrupts receptor-specific modulations of eEF2 phosphorylation and protein synthesis. Our observations, therefore, demonstrate that the regulation of the AMPK-eEF2 signaling axis by glutamate receptors alters neuronal protein synthesis and bioenergetics.

Modeling the temporal network dynamics of neuronal cultures

Neurons form complex networks that evolve over multiple time scales. In order to thoroughly characterize these networks, time dependencies must be explicitly modeled. Here, we present a statistical model that captures both the underlying structural and temporal dynamics of neuronal networks. Our model combines the class of Stochastic Block Models for community formation with Gaussian processes to model changes in the community structure as a smooth function of time. We validate our model on synthetic data and demonstrate its utility on three different studies using in vitro cultures of dissociated neurons.

Certain ortho-hydroxylated brominated ethers are promiscuous kinase inhibitors that impair neuronal signaling and neurodevelopmental processes

The developing nervous system is remarkably sensitive to environmental signals, including disruptive toxins, such as polybrominated diphenyl ethers (PBDEs). PBDEs are an environmentally pervasive class of brominated flame retardants whose neurodevelopmental toxicity mechanisms remain largely unclear. Using dissociated cortical neurons from embryonic Rattus norvegicus, we found here that chronic exposure to 6-OH-BDE-47, one of the most prevalent hydroxylated PBDE metabolites, suppresses both spontaneous and evoked neuronal electrical activity. On the basis of our previous work on mitogen-activated protein kinase (MAPK)/extracellular signal-related kinase (ERK) (MEK) biology and our observation that 6-OH-BDE-47 is structurally similar to kinase inhibitors, we hypothesized that certain hydroxylated PBDEs mediate neurotoxicity, at least in part, by impairing the MEK-ERK axis of MAPK signal transduction. We tested this hypothesis on three experimental platforms: 1) in silico, where modeling ligand-protein docking suggested that 6-OH-BDE-47 is a promiscuous ATP-competitive kinase inhibitor; 2) in vitro in dissociated neurons, where 6-OH-BDE-47 and another specific hydroxylated BDE metabolite similarly impaired phosphorylation of MEK/ERK1/2 and activity-induced transcription of a neuronal immediate early gene; and 3) in vivo in Drosophila melanogaster, where developmental exposures to 6-OH-BDE-47 and a MAPK inhibitor resulted in offspring displaying similarly increased frequency of mushroom-body β-lobe midline crossing, a metric of axonal guidance. Taken together, our results support that certain ortho-hydroxylated PBDE metabolites are promiscuous kinase inhibitors and can cause disruptions of critical neurodevelopmental processes, including neuronal electrical activity, pre-synaptic functions, MEK-ERK signaling, and axonal guidance.

Illuminating Relationships Between the Pre- and Post-synapse

Excitatory synapses in the mammalian cortex are highly diverse, both in terms of their structure and function. However, relationships between synaptic features indicate they are highly coordinated entities. Imaging techniques, that enable physiology at the resolution of individual synapses to be investigated, have allowed the presynaptic activity level of the synapse to be related to postsynaptic function. This approach has revealed that neuronal activity induces the pre- and post-synapse to be functionally correlated and that subsets of synapses are more susceptible to certain forms of synaptic plasticity. As presynaptic function is often examined in isolation from postsynaptic properties, the effect it has on the post-synapse is not fully understood. However, since postsynaptic receptors at excitatory synapses respond to release of glutamate, it follows that they may be differentially regulated depending on the frequency of its release. Therefore, examining postsynaptic properties in the context of presynaptic function may be a useful way to approach a broad range of questions on synaptic physiology. In this review, we focus on how optophysiology tools have been utilized to study relationships between the pre- and the post-synapse. Multiple imaging techniques have revealed correlations in synaptic properties from the submicron to the dendritic level. Optical tools together with advanced imaging techniques are ideally suited to illuminate this area further, due to the spatial resolution and control they allow.

A flexible 3-dimensional microelectrode array for in vitro brain models

Three-dimensional (3D) in vitro models have become increasingly popular as systems to study cell-cell and cell-ECM interactions dependent on the spatial, mechanical, and chemical cues within the environment of the tissue, which is limited in traditional two-dimensional (2D) models. Although electrophysiological recordings of neuronal action potentials through 2D microelectrode arrays (MEAs) are a common and trusted method of evaluating neuronal function, network communication, and response to chemicals and biologicals, there are currently limited options for measuring electrophysiological activity from many locations simultaneously throughout a 3D network of neurons in vitro. Here, we have developed a thin-film, 3D flexible microelectrode array (3DMEA) that non-invasively interrogates a 3D culture of neurons and can accommodate 256 channels of recording or stimulation. Importantly, the 3DMEA is straightforward to fabricate and integrates with standard commercially available electrophysiology hardware. Polyimide probe arrays were microfabricated on glass substrates and mechanically actuated to collectively lift the arrays into a vertical position, relying solely on plastic deformation of their base hinge regions to maintain vertical alignment. Human induced pluripotent stem cell (hiPSC)-derived neurons and astrocytes were entrapped in a collagen-based hydrogel and seeded onto the 3DMEA, enabling growth of suspended cells in the matrix and the formation and maturation of a neural network around the 3DMEA probes. The 3DMEA supported the growth of functional neurons in 3D with action potential spike and burst activity recorded over 45 days in vitro. This platform is an important step in facilitating noninvasive electrophysiological characterization of 3D networks of electroactive cells in vitro.

Functional characterization of human pluripotent stem cell-derived cortical networks differentiated on laminin-521 substrate: comparison to rat cortical cultures

Human pluripotent stem cell (hPSC)-derived neurons provide exciting opportunities for in vitro modeling of neurological diseases and for advancing drug development and neurotoxicological studies. However, generating electrophysiologically mature neuronal networks from hPSCs has been challenging. Here, we report the differentiation of functionally active hPSC-derived cortical networks on defined laminin-521 substrate. We apply microelectrode array (MEA) measurements to assess network events and compare the activity development of hPSC-derived networks to that of widely used rat embryonic cortical cultures. In both of these networks, activity developed through a similar sequence of stages and time frames; however, the hPSC-derived networks showed unique patterns of bursting activity. The hPSC-derived networks developed synchronous activity, which involved glutamatergic and GABAergic inputs, recapitulating the classical cortical activity also observed in rodent counterparts. Principal component analysis (PCA) based on spike rates, network synchronization and burst features revealed the segregation of hPSC-derived and rat network recordings into different clusters, reflecting the species-specific and maturation state differences between the two networks. Overall, hPSC-derived neural cultures produced with a defined protocol generate cortical type network activity, which validates their applicability as a human-specific model for pharmacological studies and modeling network dysfunctions.

High-Density Electrical Recording and Impedance Imaging With a Multi-Modal CMOS Multi-Electrode Array Chip

Multi-electrode arrays, both active or passive, emerged as ideal technologies to unveil intricated electrophysiological dynamics of cells and tissues. Active MEAs, designed using complementary metal oxide semiconductor technology (CMOS), stand over passive devices thanks to the possibility of achieving single-cell resolution, the reduced electrode size, the reduced crosstalk and the higher functionality and portability. Nevertheless, most of the reported CMOS MEA systems mainly rely on a single operational modality, which strongly hampers the applicability range of a single device. This can be a limiting factor considering that most biological and electrophysiological dynamics are often based on the synergy of multiple and complex mechanisms acting from different angles on the same phenomena. Here, we designed a CMOS MEA chip with 16,384 titanium nitride electrodes, 6 independent operational modalities and 1,024 parallel recording channels for neuro-electrophysiological studies. Sixteen independent active areas are patterned on the chip surface forming a 4 × 4 matrix, each one including 1,024 electrodes. Electrodes of four different sizes are present on the chip surface, ranging from 2.5 × 3.5 μm² up to 11 × 11.0 μm², with 15 μm pitch. In this paper, we exploited the impedance monitoring and voltage recording modalities not only to monitor the growth and development of primary rat hippocampal neurons, but also to assess their electrophysiological activity over time showing a mean spike amplitude of 144.8 ± 84.6 μV. Fixed frequency (1 kHz) and high sampling rate (30 kHz) impedance measurements were used to evaluate the cellular adhesion and growth on the chip surface. Thanks to the high-density configuration of the electrodes, as well as their dimension and pitch, the chip can appreciate the evolutions of the cell culture morphology starting from the moment of the seeding up to mature culture conditions. The measurements were confirmed by fluorescent staining. The effect of the different electrode sizes on the spike amplitudes and noise were also discussed. The multi-modality of the presented CMOS MEA allows for the simultaneous assessment of different physiological properties of the cultured neurons. Therefore, it can pave the way both to answer complex fundamental neuroscience questions as well as to aid the current drug-development paradigm.

Tissue-specific extracellular matrix accelerates the formation of neural networks and communities in a neuron-glia co-culture on a multi-electrode array

The brain’s extracellular matrix (ECM) is a macromolecular network composed of glycosaminoglycans, proteoglycans, glycoproteins, and fibrous proteins. In vitro studies often use purified ECM proteins for cell culture coatings, however these may not represent the molecular complexity and heterogeneity of the brain’s ECM. To address this, we compared neural network activity (over 30 days in vitro) from primary neurons co-cultured with glia grown on ECM coatings from decellularized brain tissue (bECM) or MaxGel, a non-tissue-specific ECM. Cells were grown on a multi-electrode array (MEA) to enable noninvasive long-term interrogation of neuronal networks. In general, the presence of ECM accelerated the formation of networks without affecting the inherent network properties. However, specific features of network activity were dependent on the type of ECM: bECM enhanced network activity over a greater region of the MEA whereas MaxGel increased network burst rate associated with robust synaptophysin expression. These differences in network activity were not attributable to cellular composition, glial proliferation, or astrocyte phenotypes, which remained constant across experimental conditions. Collectively, the addition of ECM to neuronal cultures represents a reliable method to accelerate the development of mature neuronal networks, providing a means to enhance throughput for routine evaluation of neurotoxins and novel therapeutics.

Discovering the pharmacodynamics of conolidine and cannabidiol using a cultured neuronal network based workflow

Determining the mechanism of action (MOA) of novel or naturally occurring compounds mostly relies on assays tailored for individual target proteins. Here we explore an alternative approach based on pattern matching response profiles obtained using cultured neuronal networks. Conolidine and cannabidiol are plant-derivatives with known antinociceptive activity but unknown MOA. Application of conolidine/cannabidiol to cultured neuronal networks altered network firing in a highly reproducible manner and created similar impact on network properties suggesting engagement with a common biological target. We used principal component analysis (PCA) and multi-dimensional scaling (MDS) to compare network activity profiles of conolidine/cannabidiol to a series of well-studied compounds with known MOA. Network activity profiles evoked by conolidine and cannabidiol closely matched that of ω-conotoxin CVIE, a potent and selective Cav2.2 calcium channel blocker with proposed antinociceptive action suggesting that they too would block this channel. To verify this, Cav2.2 channels were heterologously expressed, recorded with whole-cell patch clamp and conolidine/cannabidiol was applied. Remarkably, conolidine and cannabidiol both inhibited Cav2.2, providing a glimpse into the MOA that could underlie their antinociceptive action. These data highlight the utility of cultured neuronal network-based workflows to efficiently identify MOA of drugs in a highly scalable assay.

Application of Microelectrode Array Approaches to Neurotoxicity Testing and Screening

Neurotoxicity can be defined by the ability of a drug or chemical to alter the physiology, biochemistry, or structure of the nervous system in a manner that may negatively impact the health or function of the individual. Electrophysiological approaches have been utilized to study the mechanisms underlying neurotoxic actions of drugs and chemicals for over 50 years, and in more recent decades, high-throughput patch-clamp approaches have been utilized by the pharmaceutical industry for drug development. The use of microelectrode array recordings to study neural network electrophysiology is a relatively newer approach, with commercially available systems becoming available only in the early 2000s. However, MEAs have been rapidly adopted as a useful approach for neurotoxicity testing. In this chapter, I will review the use of MEA approaches as they have been applied to the field of neurotoxicity testing, especially as they have been applied to the need to screen large numbers of chemicals for neurotoxicity and developmental neurotoxicity. In addition, I will also identify challenges for the field that when addressed will improve the utility of MEA approaches for toxicity testing.

Burst Detection Methods

'Bursting', defined as periods of high-frequency firing of a neuron separated by periods of quiescence, has been observed in various neuronal systems, both in vitro and in vivo. It has been associated with a range of neuronal processes, including efficient information transfer and the formation of functional networks during development, and has been shown to be sensitive to genetic and pharmacological manipulations. Accurate detection of periods of bursting activity is thus an important aspect of characterising both spontaneous and evoked neuronal network activity. A wide variety of computational methods have been developed to detect periods of bursting in spike trains recorded from neuronal networks. In this chapter, we review several of the most popular and successful of these methods.

The Probability of Neurotransmitter Release Governs AMPA Receptor Trafficking via Activity-Dependent Regulation of mGluR1 Surface Expression

A major mechanism contributing to synaptic plasticity involves alterations in the number of AMPA receptors (AMPARs) expressed at synapses. Hippocampal CA1 synapses, where this process has been most extensively studied, are highly heterogeneous with respect to their probability of neurotransmitter release, P(r). It is unknown whether there is any relationship between the extent of plasticity-related AMPAR trafficking and the initial P(r) of a synapse. To address this question, we induced metabotropic glutamate receptor (mGluR) dependent long-term depression (mGluR-LTD) and assessed AMPAR trafficking and P(r) at individual synapses, using SEP-GluA2 and FM4-64, respectively. We found that either pharmacological or synaptic activation of mGluR1 reduced synaptic SEP-GluA2 in a manner that depends upon P(r); this process involved an activity-dependent reduction in surface mGluR1 that selectively protects high-P(r) synapses from synaptic weakening. Consequently, the extent of postsynaptic plasticity can be pre-tuned by presynaptic activity.

Evaluation of in vitro neuronal platforms as surrogates for in vivo whole brain systems

Quantitatively benchmarking similarities and differences between the in vivo central nervous system and in vitro neuronal cultures can qualify discrepancies in functional responses and establish the utility of in vitro platforms. In this work, extracellular electrophysiology responses of cortical neurons in awake, freely-moving animals were compared to in vitro cultures of dissociated cortical neurons. After exposure to two well-characterized drugs, atropine and ketamine, a number of key points were observed: (1) significant differences in spontaneous firing activity for in vivo and in vitro systems, (2) similar response trends in single-unit spiking activity after exposure to atropine, and (3) greater sensitivity to the effects of ketamine in vitro. While in vitro cultures of dissociated cortical neurons may be appropriate for many types of pharmacological studies, we demonstrate that for some drugs, such as ketamine, this system may not fully capture the responses observed in vivo. Understanding the functionality associated with neuronal cultures will enhance the relevance of electrophysiology data sets and more accurately frame their conclusions. Comparing in vivo and in vitro rodent systems will provide the critical framework necessary for developing and interpreting in vitro systems using human cells that strive to more closely recapitulate human in vivo function and response.

Slow-Wave Recordings From Micro-Sized Neural Clusters Using Multiwell Type Microelectrode Arrays

OBJECTIVE

The use of microelectrode array (MEA) recordings is a very effective neurophysiological method because it is able to continuously and noninvasively obtain the spatiotemporal information of electrical activity from many neurons constituting a neural network. Very recently, studies have been published that used MEAs for the measurement of a low-frequency component of electrical activity as an indicator of diverse activity of cultured neurons. The occurrence of low-frequency activities has electrophysiological information that does not include the information from fast spikes. However, there is no in vitro experimental model suitable for measuring the low-frequency activities (slow-waves) for further study.

METHODS

Neural clusters consisting of dozens of neurons were placed directly onto each electrode of an MEA from which fast spikes and slow-waves were measured.

RESULTS

We obtained sufficient data on the early development patterns of the slow-waves and the spikes measured from many independent neural clusters confirming that the slow-waves occurred first before the emergence of the spikes in the neural clusters. We also showed that changes in the occurrence frequency of the slow-waves for synaptic blockers were measured from a large number of independent cultures.

CONCLUSION

Microsized neural cluster arrays, which can be combined with conventional MEAs, are suitable for multiple simultaneous recordings of slow-waves.

SIGNIFICANCE

Our technology provides a simple but useful method to study the generation of a low-frequency component of the electrical activity in cultured neural networks that are not yet well known as well as to expand the use of conventional MEAs.

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

Human induced pluripotent stem cell-derived neurons are promising for use in toxicity evaluations in nonclinical studies. The multi-electrode array (MEA) assay is used in such evaluation systems because it can measure the electrophysiological function of a neural network noninvasively and with high throughput. Synchronized burst firing (SBF) is the main analytic parameter of pharmacological effects in MEA data, but an accurate method for detecting SBFs has not been established. In this study, we present a 4-step method that accurately detects a target SBF confirmed by the researcher's interpretation of a raster plot. This method calculates one set parameter per step, in the following order: the inter-spike interval (ISI), the number of spikes in an SBF, the inter-SBF interval, and the number of spikes in an SBF again. We found that the 4-step method is advantageous over the conventional method because it determines the preferable duration of an SBF, accurately distinguishes continuous SBFs, detects weak SBFs, and avoids false detection of SBFs. We found also that pharmacological evaluations involving SBF analysis may differ depending on whether the 4-step or conventional threshold method is used. This 4-step method may contribute to improving the accuracy of drug toxicity and efficacy evaluations using human induced pluripotent stem cell-derived neurons.

Controlled placement of multiple CNS cell populations to create complex neuronal cultures

In vitro brain-on-a-chip platforms hold promise in many areas including: drug discovery, evaluating effects of toxicants and pathogens, and disease modelling. A more accurate recapitulation of the intricate organization of the brain in vivo may require a complex in vitro system including organization of multiple neuronal cell types in an anatomically-relevant manner. Most approaches for compartmentalizing or segregating multiple cell types on microfabricated substrates use either permanent physical surface features or chemical surface functionalization. This study describes a removable insert that successfully deposits neurons from different brain areas onto discrete regions of a microelectrode array (MEA) surface, achieving a separation distance of 100 μm. The regional seeding area on the substrate is significantly smaller than current platforms using comparable placement methods. The non-permanent barrier between cell populations allows the cells to remain localized and attach to the substrate while the insert is in place and interact with neighboring regions after removal. The insert was used to simultaneously seed primary rodent hippocampal and cortical neurons onto MEAs. These cells retained their morphology, viability, and function after seeding through the cell insert through 28 days in vitro (DIV). Co-cultures of the two neuron types developed processes and formed integrated networks between the different MEA regions. Electrophysiological data demonstrated characteristic bursting features and waveform shapes that were consistent for each neuron type in both mono- and co-culture. Additionally, hippocampal cells co-cultured with cortical neurons showed an increase in within-burst firing rate (p = 0.013) and percent spikes in bursts (p = 0.002), changes that imply communication exists between the two cell types in co-culture. The cell seeding insert described in this work is a simple but effective method of separating distinct neuronal populations on microfabricated devices, and offers a unique approach to developing the types of complex in vitro cellular environments required for anatomically-relevant brain-on-a-chip devices.

Fast wide-volume functional imaging of engineered in vitro brain tissues

The need for in vitro models that mimic the human brain to replace animal testing and allow high-throughput screening has driven scientists to develop new tools that reproduce tissue-like features on a chip. Three-dimensional (3D) in vitro cultures are emerging as an unmatched platform that preserves the complexity of cell-to-cell connections within a tissue, improves cell survival, and boosts neuronal differentiation. In this context, new and flexible imaging approaches are required to monitor the functional states of 3D networks. Herein, we propose an experimental model based on 3D neuronal networks in an alginate hydrogel, a tunable wide-volume imaging approach, and an efficient denoising algorithm to resolve, down to single cell resolution, the 3D activity of hundreds of neurons expressing the calcium sensor GCaMP6s. Furthermore, we implemented a 3D co-culture system mimicking the contiguous interfaces of distinct brain tissues such as the cortical-hippocampal interface. The analysis of the network activity of single and layered neuronal co-cultures revealed cell-type-specific activities and an organization of neuronal subpopulations that changed in the two culture configurations. Overall, our experimental platform represents a simple, powerful and cost-effective platform for developing and monitoring living 3D layered brain tissue on chip structures with high resolution and high throughput.

Inferring structural connectivity using Ising couplings in models of neuronal networks

Functional connectivity metrics have been widely used to infer the underlying structural connectivity in neuronal networks. Maximum entropy based Ising models have been suggested to discount the effect of indirect interactions and give good results in inferring the true anatomical connections. However, no benchmarking is currently available to assess the performance of Ising couplings against other functional connectivity metrics in the microscopic scale of neuronal networks through a wide set of network conditions and network structures. In this paper, we study the performance of the Ising model couplings to infer the synaptic connectivity in in silico networks of neurons and compare its performance against partial and cross-correlations for different correlation levels, firing rates, network sizes, network densities, and topologies. Our results show that the relative performance amongst the three functional connectivity metrics depends primarily on the network correlation levels. Ising couplings detected the most structural links at very weak network correlation levels, and partial correlations outperformed Ising couplings and cross-correlations at strong correlation levels. The result was consistent across varying firing rates, network sizes, and topologies. The findings of this paper serve as a guide in choosing the right functional connectivity tool to reconstruct the structural connectivity.

Euchromatin histone methyltransferase 1 regulates cortical neuronal network development

Heterozygous mutations or deletions in the human Euchromatin histone methyltransferase 1 (EHMT1) gene cause Kleefstra syndrome, a neurodevelopmental disorder that is characterized by autistic-like features and severe intellectual disability (ID). Neurodevelopmental disorders including ID and autism may be related to deficits in activity-dependent wiring of brain circuits during development. Although Kleefstra syndrome has been associated with dendritic and synaptic defects in mice and Drosophila, little is known about the role of EHMT1 in the development of cortical neuronal networks. Here we used micro-electrode arrays and whole-cell patch-clamp recordings to investigate the impact of EHMT1 deficiency at the network and single cell level. We show that EHMT1 deficiency impaired neural network activity during the transition from uncorrelated background action potential firing to synchronized network bursting. Spontaneous bursting and excitatory synaptic currents were transiently reduced, whereas miniature excitatory postsynaptic currents were not affected. Finally, we show that loss of function of EHMT1 ultimately resulted in less regular network bursting patterns later in development. These data suggest that the developmental impairments observed in EHMT1-deficient networks may result in a temporal misalignment between activity-dependent developmental processes thereby contributing to the pathophysiology of Kleefstra syndrome.

Editor's Highlight: Evaluation of a Microelectrode Array-Based Assay for Neural Network Ontogeny Using Training Set Chemicals

Thousands of compounds in the environment have not been characterized for developmental neurotoxicity (DNT) hazard. To address this issue, methods to screen compounds rapidly for DNT hazard evaluation are necessary and are being developed for key neurodevelopmental processes. In order to develop an assay for network formation, this study evaluated effects of a training set of chemicals on network ontogeny by measuring spontaneous electrical activity in neural networks grown on microelectrode arrays (MEAs). Rat (0-24 h old) primary cortical cells were plated in 48 well-MEA plates and exposed to 6 compounds: acetaminophen, bisindolylmaleimide-1 (Bis-1), domoic acid, mevastatin, sodium orthovanadate, and loperamide for a period of 12 days. Spontaneous network activity was recorded on days 2, 5, 7, 9, and 12 and viability was assessed using the Cell Titer Blue assay on day 12. Network activity (e.g. mean firing rate [MFR], burst rate [BR], etc), increased between days 5 and 12. Random Forest analysis indicated that across all compounds and times, temporal correlation of firing patterns (r), MFR, BR, number of active electrodes and % of spikes in a burst were the most influential parameters in separating control from treated wells. All compounds except acetaminophen (≤ 30 µM) caused concentration-related effects on one or more of these parameters. Domoic acid and sodium orthovanadate altered several of these parameters in the absence of cytotoxicity. Although cytotoxicity was observed with Bis1, mevastatin, and loperamide, some parameters were affected by these compounds at concentrations below those resulting in cytotoxicity. These results demonstrate that this assay may be suitable for screening of compounds for DNT hazard identification.

Characterization of Early Cortical Neural Network Development in Multiwell Microelectrode Array Plates

We examined neural network ontogeny using microelectrode array (MEA) recordings made in multiwell MEA (mwMEA) plates over the first 12 days in vitro (DIV). In primary cortical cultures, action potential spiking activity developed rapidly between DIV 5 and 12. Spiking was sporadic and unorganized at early DIV, and became progressively more organized with time, with bursting parameters, synchrony, and network bursting increasing between DIV 5 and 12. We selected 12 features to describe network activity; principal components analysis using these features demonstrated segregation of data by age at both the well and plate levels. Using random forest classifiers and support vector machines, we demonstrated that four features (coefficient of variation [CV] of within-burst interspike interval, CV of interburst interval, network spike rate, and burst rate) could predict the age of each well recording with >65% accuracy. When restricting the classification to a binary decision, accuracy improved to as high as 95%. Further, we present a novel resampling approach to determine the number of wells needed for comparing different treatments. Overall, these results demonstrate that network development on mwMEA plates is similar to development in single-well MEAs. The increased throughput of mwMEAs will facilitate screening drugs, chemicals, or disease states for effects on neurodevelopment.

A comparison of computational methods for detecting bursts in neuronal spike trains and their application to human stem cell-derived neuronal networks

We provide an unbiased quantitative assessment of eight existing methods for identifying bursts in neuronal spike trains. We reveal limitations in a number of commonly used burst detection techniques and provide recommendations for the best practice for accurate identification of bursts using existing techniques. An analysis of the ontogeny of bursting activity in a novel data set of recordings from human induced pluripotent stem cell-derived neuronal networks, using the highest-performing burst detectors from our study, is also presented.

Accurate identification of bursting activity is an essential element in the characterization of neuronal network activity. Despite this, no one technique for identifying bursts in spike trains has been widely adopted. Instead, many methods have been developed for the analysis of bursting activity, often on an ad hoc basis. Here we provide an unbiased assessment of the effectiveness of eight of these methods at detecting bursts in a range of spike trains. We suggest a list of features that an ideal burst detection technique should possess and use synthetic data to assess each method in regard to these properties. We further employ each of the methods to reanalyze microelectrode array (MEA) recordings from mouse retinal ganglion cells and examine their coherence with bursts detected by a human observer. We show that several common burst detection techniques perform poorly at analyzing spike trains with a variety of properties. We identify four promising burst detection techniques, which are then applied to MEA recordings of networks of human induced pluripotent stem cell-derived neurons and used to describe the ontogeny of bursting activity in these networks over several months of development. We conclude that no current method can provide “perfect” burst detection results across a range of spike trains; however, two burst detection techniques, the MaxInterval and logISI methods, outperform compared with others. We provide recommendations for the robust analysis of bursting activity in experimental recordings using current techniques.

Canalization of genetic and pharmacological perturbations in developing primary neuronal activity patterns

The function of the nervous system depends on the integrity of synapses and the patterning of electrical activity in brain circuits. The rapid advances in genome sequencing reveal a large number of mutations disrupting synaptic proteins, which potentially result in diseases known as synaptopathies. However, it is also evident that every normal individual carries hundreds of potentially damaging mutations. Although genetic studies in several organisms show that mutations can be masked during development by a process known as canalization, it is unknown if this occurs in the development of the electrical activity in the brain. Using longitudinal recordings of primary cultured neurons on multi-electrode arrays from mice carrying knockout mutations we report evidence of canalization in development of spontaneous activity patterns. Phenotypes in the activity patterns in young cultures from mice lacking the Gria1 subunit of the AMPA receptor were ameliorated as cultures matured. Similarly, the effects of chronic pharmacological NMDA receptor blockade diminished as cultures matured. Moreover, disturbances in activity patterns by simultaneous disruption of Gria1 and NMDA receptors were also canalized by three weeks in culture. Additional mutations and genetic variations also appeared to be canalized to varying degrees. These findings indicate that neuronal network canalization is a form of nervous system plasticity that provides resilience to developmental disruption.

This article is part of the Special Issue entitled ‘Synaptopathy – from Biology to Therapy’.

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Development of network activity in cultures with synaptic mutations was recorded.

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Synchronous burst firing with theta periodicity was observed as cultures matured.

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Gria1 deletion and chronic NMDA-R blockade disrupted network activity patterns.

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Dlg2 knockout disrupted network activity, other synaptic genes had minimal effects.

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Network activity phenotypes early in development were canalized as cultures matured.