Neurons derived from human induced Pluripotent Stem Cells (hiPSCs) provide a promising new tool for studying neurological disorders. In the past decade, many protocols for differentiating hiPSCs into neurons have been developed. However, these protocols are often slow with high variability, low reproducibility, and low efficiency. In addition, the neurons obtained with these protocols are often immature and lack adequate functional activity both at the single-cell and network levels unless the neurons are cultured for several months. Partially due to these limitations, the functional properties of hiPSC-derived neuronal networks are still not well characterized. Here, we adapt a recently published protocol that describes production of human neurons from hiPSCs by forced expression of the transcription factor neurogenin-2. This protocol is rapid (yielding mature neurons within 3 weeks) and efficient, with nearly 100% conversion efficiency of transduced cells (>95% of DAPI-positive cells are MAP2 positive). Furthermore, the protocol yields a homogeneous population of excitatory neurons that would allow the investigation of cell-type specific contributions to neurological disorders. We modified the original protocol by generating stably transduced hiPSC cells, giving us explicit control over the total number of neurons. These cells are then used to generate hiPSC-derived neuronal networks on micro-electrode arrays. In this way, the spontaneous electrophysiological activity of hiPSC-derived neuronal networks can be measured and characterized, while retaining interexperimental consistency in terms of cell density. The presented protocol is broadly applicable, especially for mechanistic and pharmacological studies on human neuronal networks.
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http://dx.doi.org/10.3791/54900 | DOI Listing |
Sci Rep
January 2025
School of Chemical, Petroleum and Gas Engineering, Iran University of Science and Technology, P.O. Box: 16765-163, Tehran, Iran.
In this study, Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) were developed to estimate the equilibrium solubility and partial pressure of CO in blended aqueous solutions of diisopropanolamine (DIPA) and 2-amino-2-methylpropanol (AMP). In this study, several key parameters were analyzed to understand the behavior of the aqueous DIPA/AMP system for CO capture. Including DIPA (9-21 wt%), AMP (9-21 wt%), temperature (323.
View Article and Find Full Text PDFEMBO J
January 2025
Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, 450000, Henan, China.
The carboxyl terminus of Hsc70-interacting protein (CHIP) is pivotal for managing misfolded and aggregated proteins via chaperone networks and degradation pathways. In a preclinical rodent model of CHIP-related ataxia, we observed that CHIP mutations lead to increased levels of phosphodiesterase 9A (PDE9A), whose role in this context remains poorly understood. Here, we investigated the molecular mechanisms underlying the role of PDE9A in CHIP-related ataxia and demonstrated that CHIP binds to PDE9A, facilitating its polyubiquitination and autophagic degradation.
View Article and Find Full Text PDFBrain Struct Funct
January 2025
Behavioral Neuroscience Laboratory, Department of Psychology, Boğaziçi University, Bebek, 34342, Istanbul, Turkey.
Theta oscillations of the mammalian amygdala are associated with processing, encoding and retrieval of aversive memories. In the hippocampus, the power of the network theta oscillation is modulated by basal forebrain (BF) GABAergic projections. Here, we combine anatomical and computational approaches to investigate if similar BF projections to the amygdaloid complex provide an analogous modulation of local network activity.
View Article and Find Full Text PDFPLoS Comput Biol
January 2025
Electrical and Computer Engineering Department, Concordia University, Montreal, Canada.
Astrocytes critically shape whole-brain structure and function by forming extensive gap junctional networks that intimately and actively interact with neurons. Despite their importance, existing computational models of whole-brain activity ignore the roles of astrocytes while primarily focusing on neurons. Addressing this oversight, we introduce a biophysical neural mass network model, designed to capture the dynamic interplay between astrocytes and neurons via glutamatergic and GABAergic transmission pathways.
View Article and Find Full Text PDFBiological memory networks are thought to store information by experience-dependent changes in the synaptic connectivity between assemblies of neurons. Recent models suggest that these assemblies contain both excitatory and inhibitory neurons (E/I assemblies), resulting in co-tuning and precise balance of excitation and inhibition. To understand computational consequences of E/I assemblies under biologically realistic constraints we built a spiking network model based on experimental data from telencephalic area Dp of adult zebrafish, a precisely balanced recurrent network homologous to piriform cortex.
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