Micro Three-Dimensional Neuronal Cultures Generate Developing Cortex-Like Activity Patterns

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.

3D models of glioblastoma interaction with cortical cells

Introduction: Glioblastoma (GBM) invasiveness and ability to infiltrate deep into the brain tissue is a major reason for the poor patient prognosis for this type of brain cancer. Behavior of glioblastoma cells, including their motility, and expression of invasion-promoting genes such as matrix metalloprotease-2 (MMP2), are strongly influenced by normal cells found in the brain parenchyma. Cells such as neurons may also be influenced by the tumor, as many glioblastoma patients develop epilepsy. In vitro models of glioblastoma invasiveness are used to supplement animal models in a search for better treatments, and need to combine capability for high-throughput experiments with capturing bidirectional interactions between GBM and brain cells.

Methods: In this work, two 3D in vitro models of GBM-cortical interactions were investigated. A matrix-free model was created by co-culturing GBM and cortical spheroids, and a matrix-based model was created by embedding cortical cells and a GBM spheroid in Matrigel.

Results: Rapid GBM invasion occurred in the matrix-based model, and was enhanced by the presence of cortical cells. Little invasion occurred in the matrix-free model. In both types of models, presence of GBM cells resulted in a significant increase in paroxysmal neuronal activity.

Discussion: Matrix-based model may be better suited for studying GBM invasion in an environment that includes cortical cells, while matrix-free model may be useful in investigation of tumor-associated epilepsy.

Advances in Recapitulating Alzheimer's Disease Phenotypes Using Human Induced Pluripotent Stem Cell-Based In Vitro Models

Alzheimer's disease (AD) is an incurable neurodegenerative disorder and the leading cause of death among older individuals. Available treatment strategies only temporarily mitigate symptoms without modifying disease progression. Recent studies revealed the multifaceted neurobiology of AD and shifted the target of drug development. Established animal models of AD are mostly tailored to yield a subset of disease phenotypes, which do not recapitulate the complexity of sporadic late-onset AD, the most common form of the disease. The use of human induced pluripotent stem cells (HiPSCs) offers unique opportunities to fill these gaps. Emerging technology allows the development of disease models that recapitulate a brain-like microenvironment using patient-derived cells. These models retain the individual's unraveled genetic background, yielding clinically relevant disease phenotypes and enabling cost-effective, high-throughput studies for drug discovery. Here, we review the development of various HiPSC-based models to study AD mechanisms and their application in drug discovery.

Label-free monitoring of 3D cortical neuronal growth in vitro using optical diffraction tomography

The highly complex central nervous systems of mammals are often studied using three-dimensional (3D) in vitro primary neuronal cultures. A coupled confocal microscopy and immunofluorescence labeling are widely utilized for visualizing the 3D structures of neurons. However, this requires fixation of the neurons and is not suitable for monitoring an identical sample at multiple time points. Thus, we propose a label-free monitoring method for 3D neuronal growth based on refractive index tomograms obtained by optical diffraction tomography. The 3D morphology of the neurons was clearly visualized, and the developmental processes of neurite outgrowth in 3D spaces were analyzed for individual neurons.

Efficient and Accurate Computational Model of Neuron with Spike Frequency Adaptation

Simplified models of neurons are widely used in computational investigations of large networks. One of the most important performance metrics of simplified models is their accuracy in reproducing action potential (spike) timing. In this article, we developed a simple, computationally efficient neuron model by modifying the adaptive exponential integrate and fire (AdEx) model [1] with sigmoid afterhyperpolarization current (Sigmoid AHP). Our model can precisely match the spike times and spike frequency adaptation of cortical pyramidal neurons. The accuracy was similar to a more complex two compartment biophysically realistic model of the same neurons. This work provides a simplified neuronal model with improved spike timing accuracy for use in modeling of large neural networks.Clinical Relevance- Accurate and computationally efficient single neuron model will enable large network modeling of brain regions involved in neurological and psychiatric disorders and may lead to a better understanding of the disorder mechanisms.

Microdevice for directional axodendritic connectivity between micro 3D neuronal cultures

Neuronal cultures are widely used in neuroscience research. However, the randomness of circuits in conventional cultures prevents accurate in vitro modeling of cortical development and of the pathogenesis of neurological and psychiatric disorders. A basic feature of cortical circuits that is not captured in standard cultures of dissociated cortical cells is directional connectivity. In this work, a polydimethylsiloxane (PDMS)-based device that achieves directional connectivity between micro 3D cultures is demonstrated. The device consists of through-holes for micro three-dimensional (μ3D) clusters of cortical cells connected by microtrenches for axon and dendrite guidance. The design of the trenches relies in part on the concept of axonal edge guidance, as well as on the novel concept of specific dendrite targeting. This replicates dominant excitatory connectivity in the cortex, enables the guidance of the axon after it forms a synapse in passing (an "en passant" synapse), and ensures that directional selectivity is preserved over the lifetime of the culture. The directionality of connections was verified morphologically and functionally. Connections were dependent on glutamatergic synapses. The design of this device has the potential to serve as a building block for the reconstruction of more complex cortical circuits in vitro.