ArticleJournal of neurophysiology2023
Stimulation-mediated reverse engineering of silent neural networks.
Article in Journal of neurophysiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
4 citing papers in PubMed.
- Acute DOI exposure drives cortical hyperexcitability and functional network remodeling.bioRxiv : the preprint server for biology · 2026Article
- Deriving connectivity from spiking activity in detailed models of large-scale cortical microcircuits.iScience · 2026Article
- Magnetic Detection of Neural Activity by Nanocoil Transducers.Nano letters · 2024Article
- Inference of network connectivity from temporally binned spike trains.Journal of neuroscience methods · 2024Article
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Authors and funding
4 authors.
Funding
Abstract
Reconstructing connectivity of neuronal networks from single-cell activity is essential to understanding brain function, but the challenge of deciphering connections from populations of silent neurons has been largely unmet. We demonstrate a protocol for deriving connectivity of simulated silent neuronal networks using stimulation combined with a supervised learning algorithm, which enables inferring connection weights with high fidelity and predicting spike trains at the single-spike and single-cell levels with high accuracy. We apply our method on rat cortical recordings fed through a circuit of heterogeneously connected leaky integrate-and-fire neurons firing at typical lognormal distributions and demonstrate improved performance during stimulation for multiple subpopulations. These testable predictions about the number and protocol of the required stimulations are expected to enhance future efforts for deriving neuronal connectivity and drive new experiments to better understand brain function.
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Registered trials
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