Human Neuronal Networks Research Articles

Huntingtin lowering impairs the maturation and synchronized synaptic activity of human cortical neuronal networks derived from induced pluripotent stem cells

Despite growing descriptions of wild-type Huntingtin (wt-HTT) roles in both adult brain function and, more recently, development, several clinical trials are exploring HTT-lowering approaches that target both wt-HTT and the mutant isoform (mut-HTT) responsible for Huntington's disease (HD). This non-selective targeting is based on the autosomal dominant inheritance of HD, supporting the idea that mut-HTT exerts its harmful effects through a toxic gain-of-function or a dominant-negative mechanism. However, the precise amount of wt-HTT needed for healthy neurons in adults and during development remains unclear. In this study, we address this question by examining how wt-HTT loss affects human neuronal network formation, synaptic maturation, and homeostasis in vitro. Our findings establish a role of wt-HTT in the maturation of dendritic arborization and the acquisition of network-wide synchronized activity by human cortical neuronal networks modeled in vitro. Interestingly, the network synchronization defects only became apparent when more than two-thirds of the wt-HTT protein was depleted. Our study underscores the critical need to precisely understand wt-HTT role in neuronal health. It also emphasizes the potential risks of excessive wt-HTT loss associated with non-selective therapeutic approaches targeting both wt- and mut-HTT isoforms in HD patients.

Human tripartite cortical network model for temporal assessment of alpha-synuclein aggregation and propagation in Parkinson’s Disease

Previous studies have shown that aggregated alpha-synuclein (α-s) protein, a key pathological marker of Parkinson’s disease (PD), can propagate between cells, thus participating in disease progression. This prion-like propagation has been widely studied using in vivo and in vitro models, including rodent and human cell cultures. In this study, our focus was on temporal assessment of functional changes during α-s aggregation and propagation in human induced pluripotent stem cell (hiPSC)-derived neuronal cultures and in engineered networks. Here, we report an engineered circular tripartite human neuronal network model in a microfluidic chip integrated with microelectrode arrays (MEAs) as a platform to study functional markers during α-s aggregation and propagation. We observed progressive aggregation of α-s in conventional neuronal cultures and in the exposed (proximal) compartments of circular tripartite networks following exposure to preformed α-s fibrils (PFF). Furthermore, aggregated forms propagated to distal compartments of the circular tripartite networks through axonal transport. We observed impacts of α-s aggregation on both the structure and function of neuronal cells, such as in presynaptic proteins, mitochondrial motility, calcium oscillations and neuronal activity. The model enabled an assessment of the early, middle, and late phases of α-s aggregation and its propagation during a 13-day follow-up period. While our temporal analysis suggested a complex interplay of structural and functional changes during the in vitro propagation of α-s aggregates, further investigation is required to elucidate the underlying mechanisms. Taken together, this study demonstrates the technical potential of our introduced model for conducting in-depth analyses for revealing such mechanisms.

DeePhys: A machine learning–assisted platform for electrophysiological phenotyping of human neuronal networks

Reproducible functional assays to study invitro neuronal networks represent an important cornerstone in the quest to develop physiologically relevant cellular models of human diseases. Here, we introduce DeePhys, a MATLAB-based analysis tool for data-driven functional phenotyping of invitro neuronal cultures recorded by high-density microelectrode arrays. DeePhys is a modular workflow that offers a range of techniques to extract features from spike-sorted data, allowing for the examination of functional phenotypes both at the individual cell and network levels, as well as across development. In addition, DeePhys incorporates the capability to integrate novel features and to use machine-learning-assisted approaches, which facilitates a comprehensive evaluation of pharmacological interventions. To illustrate its practical application, we apply DeePhys to human induced pluripotent stem cell-derived dopaminergic neurons obtained from both patients and healthy individuals and showcase how DeePhys enables phenotypic screenings.

Using graph theory to analyze human brain neuronal networks – a novel approach to investigate neuronal crosstalk.

Using graph theory to analyze human brain neuronal networks – a novel approach to investigate neuronal crosstalk.

Investigating the reliability of the evoked response in human iPSCs-derived neuronal networks coupled to micro-electrode arrays

In vitro models of neuronal networks have emerged as a potent instrument for gaining deeper insights into the intricate mechanisms governing the human brain. Notably, the integration of human-induced pluripotent stem cells (hiPSCs) with micro-electrode arrays offers a means to replicate and dissect both the structural and functional elements of the human brain within a controlled in vitro environment. Given that neuronal communication relies on the emission of electrical (and chemical) stimuli, the employment of electrical stimulation stands as a mean to comprehensively interrogate neuronal assemblies, to better understand their inherent electrophysiological dynamics. However, the establishment of standardized stimulation protocols for cultures derived from hiPSCs is still lacking, thereby hindering the precise delineation of efficacious parameters to elicit responses. To fill this gap, the primary objective of this study resides in delineating effective parameters for the electrical stimulation of hiPSCs-derived neuronal networks, encompassing the determination of voltage amplitude and stimulation frequency able to evoke reliable and stable responses. This study represents a stepping-stone in the exploration of efficacious stimulation parameters, thus broadening the electrophysiological activity profiling of neural networks sourced from human-induced pluripotent stem cells.

Understanding the molecular mechanisms of TDP‐43 neurotoxicity in ALS and FTD to inspire targeted therapies

AbstractALS and FTD are fatal and incurable neurodegenerative diseases, characterized by accumulation of pathologic forms of RNA‐binding proteins, predominantly TDP‐43. The functional consequences and potential neurotoxic effects of the highly heterogeneous TDP‐43 aggregates observed in postmortem brains are debated. Combining structural protein analysis with cellular systems we uncovered a novel and unexpected mechanism that counteracts pathologic aggregation of TDP‐43. More recently, we described two distinct mechanisms of aggregation resulting in either nuclear of cytoplasmic TDP‐43 aggregates, resembling the neuropathological heterogeneity described in FTD patients and potentially unravels the origins of heterogeneous pathological species occurring in TDP‐43 proteinopathies. We also showed that FTD heterogeneity is associated with alternate pathological TDP‐43 conformations, reminiscent of prion strains. We used advanced microscopy techniques to explore the differences in the physical and seeding properties between these pathological TDP‐43 aggregates. We found that the subcellular environment and organization of TDP‐43 aggregates differs in patient brains in a subtype‐specific manner. When isolated and introduced in cells, these distinct TDP‐43 assemblies triggered neoaggregate formation with seeding potencies and morphologies that mimicked human brain pathology. To study neurodegeneration phenotypes in human neurons, we developed a new methodology for generating human neuronal networks with remarkable maturity, longevity and reproducibility. Combining high density multielectron arrays and single cell RNA sequencing, we demonstrated the potential of these cultures for modeling neurodegeneration. In this new model, we identified novel RNA targets of TDP‐43, which we found abnormally accumulated in neurons with TDP‐43 pathology in human brains of ALS and FTD patients. The implications of these studies for understanding the mechanisms of neurodegeneration and inspiring therapeutic approaches will be discussed.

Deepening the role of excitation/inhibition balance in human iPSCs-derived neuronal networks coupled to MEAs during long-term development

Objective. The purpose of this study is to investigate whether and how the balance between excitation and inhibition (‘E/I balance’) influences the spontaneous development of human-derived neuronal networks in vitro. To achieve that goal, we performed a long-term (98 d) characterization of both homogeneous (only excitatory or inhibitory neurons) and heterogeneous (mixed neuronal types) cultures with controlled E/I ratios (i.e. E:I 0:100, 25:75, 50:50, 75:25, 100:0) by recording their electrophysiological activity using micro-electrode arrays. Approach. Excitatory and inhibitory neurons were derived from human induced pluripotent stem cells (hiPSCs). We realized five different configurations by systematically varying the glutamatergic and GABAergic percentages. Main results. We successfully built both homogeneous and heterogeneous neuronal cultures from hiPSCs finely controlling the E/I ratios; we were able to maintain them for up to 3 months. Homogeneity differentially impacted purely inhibitory (no bursts) and purely excitatory (few bursts) networks, deviating from the typical traits of heterogeneous cultures (burst dominated). Increased inhibition in heterogeneous cultures strongly affected the duration and organization of bursting and network bursting activity. Spike-based functional connectivity and image-based deep learning analysis further confirmed all the above. Significance. Healthy neuronal activity is controlled by a well-defined E/I balance whose alteration could lead to the onset of neurodevelopmental disorders like schizophrenia or epilepsy. Most of the commonly used in vitro models are animal-derived or too simplified and thus far from the in vivo human condition. In this work, by performing a long-term study of hiPSCs-derived neuronal networks obtained from healthy human subjects, we demonstrated the feasibility of a robust in vitro model which can be further exploited for investigating pathological conditions where the E/I balance is impaired.

An in silico and invitro human neuronal network model reveals cellular mechanisms beyond NaV1.1 underlying Dravet syndrome.

Human induced pluripotent stem cell (hiPSC)-derived neuronal networks on multi-electrode arrays (MEAs) provide a unique phenotyping tool to study neurological disorders. However, it is difficult to infer cellular mechanisms underlying these phenotypes. Computational modeling can utilize the rich dataset generated by MEAs, and advance understanding of disease mechanisms. However, existing models lack biophysical detail, or validation and calibration to relevant experimental data. We developed a biophysical in silico model that accurately simulates healthy neuronal networks on MEAs. To demonstrate the potential of our model, we studied neuronal networks derived from a Dravet syndrome (DS) patient with a missense mutation in SCN1A, encoding sodium channel NaV1.1. Our in silico model revealed that sodium channel dysfunctions were insufficient to replicate the invitro DS phenotype, and predicted decreased slow afterhyperpolarization and synaptic strengths. We verified these changes in DS patient-derived neurons, demonstrating the utility of our insilico model to predict disease mechanisms.

Analyzing bursting synchronization in structural connectivity matrix of a human brain under external pulsed currents

Cognitive tasks in the human brain are performed by various cortical areas located in the cerebral cortex. The cerebral cortex is separated into different areas in the right and left hemispheres. We consider one human cerebral cortex according to a network composed of coupled subnetworks with small-world properties. We study the burst synchronization and desynchronization in a human neuronal network under external periodic and random pulsed currents. With and without external perturbations, the emergence of bursting synchronization is observed. Synchronization can contribute to the processing of information, however, there are evidences that it can be related to some neurological disorders. Our results show that synchronous behavior can be suppressed by means of external pulsed currents.

344Laser bioprinting of human iPSC-derived neural stem cells and neurons: Effect on cell survival, multipotency, differentiation, and neuronal activity.

Generation of human neuronal networks by three-dimensional (3D) bioprinting is promising for drug testing and hopefully will allow for the understanding of cellular mechanisms in brain tissue. The application of neural cells derived from human induced-pluripotent stem cells (hiPSCs) is an obvious choice, since hiPSCs provide access to cells unlimited in number and cell types that could be generated by differentiation. The questions in this regard include which neuronal differentiation stage is optimal for printing of such networks, and to what extent the addition of other cell types, especially astrocytes, supports network formation. These aspects are the focus of the present study, in which we applied a laser-based bioprinting technique and compared hiPSC-derived neural stem cells (NSCs) with neuronal differentiated NSCs, with and without the inclusion of co-printed astrocytes. In this study, we investigated in detail the effects of cell types, printed droplet size, and duration of differentiation before and after printing on viability, as well as proliferation, stemness, differentiation potential, formation of dendritic extensions and synapses, and functionality of the generated neuronal networks. We found a significant dependence of cell viability after dissociation on differentiation stage, but no impact of the printing process. Moreover, we observed a dependence of the abundance of neuronal dendrites on droplet size, a marked difference between printed cells and normal cell culture in terms of further differentiation of the cells, especially differentiation into astrocytes, as well as neuronal network formation and activity. Notably, there was a clear effect of admixed astrocytes on NSCs but not on neurons.

Multimodal monitoring of human cortical organoids implanted in mice reveal functional connection with visual cortex

Human cortical organoids, three-dimensional neuronal cultures, are emerging as powerful tools to study brain development and dysfunction. However, whether organoids can functionally connect to a sensory network in vivo has yet to be demonstrated. Here, we combine transparent microelectrode arrays and two-photon imaging for longitudinal, multimodal monitoring of human cortical organoids transplanted into the retrosplenial cortex of adult mice. Two-photon imaging shows vascularization of the transplanted organoid. Visual stimuli evoke electrophysiological responses in the organoid, matching the responses from the surrounding cortex. Increases in multi-unit activity (MUA) and gamma power and phase locking of stimulus-evoked MUA with slow oscillations indicate functional integration between the organoid and the host brain. Immunostaining confirms the presence of human-mouse synapses. Implantation of transparent microelectrodes with organoids serves as a versatile in vivo platform for comprehensive evaluation of the development, maturation, and functional integration of human neuronal networks within the mouse brain.

Propagation of Distinct α-Synuclein Strains Within Human Reconstructed Neuronal Network and Associated Neuronal Dysfunctions.

Aggregated alpha-synuclein (α-Syn) in neurons is a hallmark of Parkinson's disease (PD) and other synucleinopathies. Recent advances (1) in the production and purification of synthetic assemblies of α-Syn, (2) in the design and production of microfluidic devices allowing the construction of oriented and compartmentalized neuronal network on a chip, and (3) in the differentiation of human pluripotent stem cells (hPSCs) into specific neuronal subtypes now allow the study of cellular and molecular determinants of the prion-like properties of α-Syn in vitro. Here, we described the methods we used to reconstruct a cortico-cortical human neuronal network in microfluidic devices and how to take advantage of this cellular model to characterize (1) the prion-like properties of different α-Syn strains and (2) the neuronal dysfunctions and the alterations associated with the exposure to α-Syn strains or the nucleation of endogenous α-Syn protein in vitro.

Development of a platform to investigate long-term potentiation in human iPSC-derived neuronal networks.

SummaryImpairment of long-term potentiation (LTP) is a common feature of many pre-clinical models of neurological disorders; however, studies in humans are limited by the inaccessibility of the brain. Human induced pluripotent stem cells (hiPSCs) provide a unique opportunity to study LTP in disease-specific genetic backgrounds. Here we describe a multi-electrode array (MEA)-based assay to investigate chemically induced LTP (cLTP) across entire networks of hiPSC-derived midbrain dopaminergic (DA) and cortical neuronal populations that lasts for days, allowing studies of the late phases of LTP and enabling detection of associated molecular changes. We show that cLTP on midbrain DA neuronal networks is largely independent of the N-methyl-D-aspartate receptor (NMDAR) and partially dependent on brain-derived neurotrophic factor (BDNF). Finally, we describe activity-regulated gene expression induced by cLTP. This cLTP-MEA assay platform will enable phenotype discovery and higher-throughput analyses of synaptic plasticity on hiPSC-derived neurons.

Practical guide for preparation, computational reconstruction and analysis of 3D human neuronal networks in control and ischaemic conditions.

ABSTRACTTo obtain commensurate numerical data of neuronal network morphology in vitro, network analysis needs to follow consistent guidelines. Important factors in successful analysis are sample uniformity, suitability of the analysis method for extracting relevant data and the use of established metrics. However, for the analysis of 3D neuronal cultures, there is little coherence in the analysis methods and metrics used in different studies. Here, we present a framework for the analysis of neuronal networks in 3D. First, we selected a hydrogel that supported the growth of human pluripotent stem cell-derived cortical neurons. Second, we tested and compared two software programs for tracing multi-neuron images in three dimensions and optimized a workflow for neuronal analysis using software that was considered highly suitable for this purpose. Third, as a proof of concept, we exposed 3D neuronal networks to oxygen-glucose deprivation- and ionomycin-induced damage and showed morphological differences between the damaged networks and control samples utilizing the proposed analysis workflow. With the optimized workflow, we present a protocol for preparing, challenging, imaging and analysing 3D human neuronal cultures.

Analysis of Comprehensive Artificial Neural Network Computer Media Aided Construction of Economic Forecasting Model

As a complex system engineering, economic forecasting involves many fields and disciplines, and its accuracy largely depends on the selected forecasting method and forecasting model. The construction of the traditional economic prediction model mainly depends on the theories of economic statistics and metrology, which cannot meet the prediction needs of the new era. ANN model has a more flexible nonlinear quality and learning mode so that it can effectively adapt to the prediction scenario of a nonlinear economic system. ANN is an abstract model of the human brain neuronal network based on the information-processing perspective and composed of different networks to achieve a specific representation of logical strategies. ANN’s self-learning function, associative storage function, and the ability to find optimal solutions at high speed have led to its in-depth application and research in an increasing number of fields. In addition, ANN research work has continued to advance, has made great progress in many fields represented by economic forecasting, has successfully solved many practical problems, showing a more intelligent adaptation in the field of economics, and therefore has an important research value. Based on this, this paper first analyzes the economic system prediction, then studies the ANN medium model and learning algorithm, and finally verifies the effectiveness of the ANN economic prediction model integrating computer medium.

A defined human-specific platform for modeling neuronal network stimulation in vitro and in silico

BackgroundTranscription factor-based forward programming enables the efficient generation of forebrain excitatory and inhibitory neurons from human pluripotent stem cells (hPSCs). This provides an opportunity to study stimulation-response patterns in highly defined neuronal networks in a controlled and customizable in vitro environment. New methodCell populations composed of defined ratios of excitatory and inhibitory neurons were generated by forward programming genome-edited human hPSCs carrying the inducible transcription factors NGN2 and ASCL1/DLX2, respectively. These populations were cultured on multi-electrode arrays (MEAs), and population responses elicited by distinct spatial and temporal stimulation patterns were analyzed. In parallel, in silico network models fed with neuronal parameters obtained from the in vitro cultures were developed to explore potential mechanisms underlying experimental observations. ResultsNeuronal cultures developed network-level electrophysiological activities with pronounced synchronized network bursts (NBs), which responded to synaptic modulators. Interestingly, local electrical pulse stimulation at frequencies ≤ 0.2 Hz reliably elicited NBs, while frequencies of ≥ 1 Hz yielded no homogeneous responses, but only sporadic NBs. In contrast, multi-site stimulation at the same frequency could elicit NBs robustly. Data from computational models suggest that this phenomenon can be explained by exhaustion and presynaptic functional paralysis of targeted circuits by high-frequency local stimulation. Comparison with existing methodsCompared to hPSC-derived neurons generated solely by small molecule treatment, forward-programmed excitatory and inhibitory neurons enable the composition of highly confectionized networks. In silico simulation of induced biological network responses can be directly used to devise and validate mechanistic hypotheses underlying the recorded network dynamics. ConclusionsThe present study demonstrates the prospect of the iPSC technology for conducting personalized in vitro studies of human neuronal networks and their responses to electric stimuli. It also illustrates how the combined use of biological and in silico neuronal networks can support the development of mechanistic hypotheses underlying network responses to specific stimuli.

Impaired Functional Connectivity Underlies Fragile X Syndrome.

Fragile X syndrome (FXS), the most common form of inherited intellectual disability, is caused by a developmentally regulated silencing of the FMR1 gene, but its effect on human neuronal network development and function is not fully understood. Here, we isolated isogenic human embryonic stem cell (hESC) subclones—one with a full FX mutation and one that is free of the mutation (control) but shares the same genetic background—differentiated them into induced neurons (iNs) by forced expression of NEUROG-1, and compared the functional properties of the derived neuronal networks. High-throughput image analysis demonstrates that FX-iNs have significantly smaller cell bodies and reduced arborizations than the control. Both FX- and control-neurons can discharge repetitive action potentials, and FX neuronal networks are also able to generate spontaneous excitatory synaptic currents with slight differences from the control, demonstrating that iNs generate more mature neuronal networks than the previously used protocols. MEA analysis demonstrated that FX networks are hyperexcitable with significantly higher spontaneous burst-firing activity compared to the control. Most importantly, cross-correlation analysis enabled quantification of network connectivity to demonstrate that the FX neuronal networks are significantly less synchronous than the control, which can explain the origin of the development of intellectual dysfunction associated with FXS.

Regenerating the Injured Spinal Cord at the Chronic Phase by Engineered iPSCs-Derived 3D Neuronal Networks.

Cell therapy using induced pluripotent stem cell‐derived neurons is considered a promising approach to regenerate the injured spinal cord (SC). However, the scar formed at the chronic phase is not a permissive microenvironment for cell or biomaterial engraftment or for tissue assembly. Engineering of a functional human neuronal network is now reported by mimicking the embryonic development of the SC in a 3D dynamic biomaterial‐based microenvironment. Throughout the in vitro cultivation stage, the system's components have a synergistic effect, providing appropriate cues for SC neurogenesis. While the initial biomaterial supported efficient cell differentiation in 3D, the cells remodeled it to provide an inductive microenvironment for the assembly of functional SC implants. The engineered tissues are characterized for morphology and function, and their therapeutic potential is investigated, revealing improved structural and functional outcomes after acute and chronic SC injuries. Such technology is envisioned to be translated to the clinic to rewire human injured SC.

Transcriptome Dynamics of Human Neuronal Differentiation From iPSC.

The generation and use of induced pluripotent stem cells (iPSCs) in order to obtain all differentiated adult cell morphologies without requiring embryonic stem cells is one of the most important discoveries in molecular biology. Among the uses of iPSCs is the generation of neuron cells and organoids to study the biological cues underlying neuronal and brain development, in addition to neurological diseases. These iPSC-derived neuronal differentiation models allow us to examine the gene regulatory factors involved in such processes. Among these regulatory factors are long non-coding RNAs (lncRNAs), genes that are transcribed from the genome and have key biological functions in establishing phenotypes, but are frequently not included in studies focusing on protein coding genes. Here, we provide a comprehensive analysis and overview of the coding and non-coding transcriptome during multiple stages of the iPSC-derived neuronal differentiation process using RNA-seq. We identify previously unannotated lncRNAs via genome-guided de novo transcriptome assembly, and the distinct characteristics of the transcriptome during each stage, including differentially expressed and stage specific genes. We further identify key genes of the human neuronal differentiation network, representing novel candidates likely to have critical roles in neurogenesis using coexpression network analysis. Our findings provide a valuable resource for future studies on neuronal differentiation.

Human stem cell-derived GABAergic neurons functionally integrate into human neuronal networks

Gamma-aminobutyric acid (GABA)-releasing interneurons modulate neuronal network activity in the brain by inhibiting other neurons. The alteration or absence of these cells disrupts the balance between excitatory and inhibitory processes, leading to neurological disorders such as epilepsy. In this regard, cell-based therapy may be an alternative therapeutic approach. We generated light-sensitive human embryonic stem cell (hESC)-derived GABAergic interneurons (hdIN) and tested their functionality. After 35 days in vitro (DIV), hdINs showed electrophysiological properties and spontaneous synaptic currents comparable to mature neurons. In co-culture with human cortical neurons and after transplantation (AT) into human brain tissue resected from patients with drug-resistant epilepsy, light-activated channelrhodopsin-2 (ChR2) expressing hdINs induced postsynaptic currents in human neurons, strongly suggesting functional efferent synapse formation. These results provide a proof-of-concept that hESC-derived neurons can integrate and modulate the activity of a human host neuronal network. Therefore, this study supports the possibility of precise temporal control of network excitability by transplantation of light-sensitive interneurons.