ArticleScientific reports2021
Early prediction of developing spontaneous activity in cultured neuronal networks.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Pathological disruption of CELF2 shuttling causes neuronal hyperactivity, learning deficits, and seizures.The Journal of clinical investigation · 2026Article
- Behavior of neural networks in culture suggest that sporadic and genetic forms of Alzheimer's disease may not be equivalent.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Correlative voltage imaging and cryo-electron tomography bridge neuronal activity and molecular structure.Nature communications · 2025Article
- Targeting Kinin B1R Attenuates Hypertension Through AT1R-Dependent Mechanisms.Circulation research · 2025Article
- Article
- Machine learning and complex network analysis of drug effects on neuronal microelectrode biosensor data.Scientific reports · 2025Article
- Repetitive training enhances the pattern recognition capability of cultured neural networks.PLoS computational biology · 2025Article
- High-density multielectrode arrays bring cellular resolution to neuronal activity and network analyses of corticospinal motor neurons.Scientific reports · 2025Article
- Nanomagnetic Guidance Shapes the Structure-Function Relationship of Developing Cortical Networks.Nano letters · 2024Article
- Calcium-Dependent Hyperexcitability in Human Stem Cell-Derived Rett Syndrome Neuronal Networks.Biological psychiatry global open science · 2024Article
- Development of a new hazard scoring system in primary neuronal cell cultures for drug-induced acute neuronal toxicity identification in early drug discovery.Frontiers in pharmacology · 2024Article
- autoMEA: machine learning-based burst detection for multi-electrode array datasets.Frontiers in neuroscience · 2024Article
- Harnessing the potential of human induced pluripotent stem cells, functional assays and machine learning for neurodevelopmental disorders.Frontiers in neuroscience · 2024Review
- Nanomaterial-based microelectrode arrays for in vitro bidirectional brain-computer interfaces: a review.Microsystems & nanoengineering · 2023Review
- Calpain-Independent Intracellular Protease Activity Is Elevated in Excitotoxic Cortical Neurons Prior to Delayed Calcium Deregulation and Mitochondrial Dysfunction.Biomolecules · 2022Article
- Lightsheet optical tweezer (LOT) for optical manipulation of microscopic particles and live cells.Scientific reports · 2022Article
- Spontaneous Activity Predicts Survival of Developing Cortical Neurons.Frontiers in cell and developmental biology · 2022Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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