ArticleCommunications biology2022
Deconvolution improves the detection and quantification of spike transmission gain from spike trains.
Article in Communications biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 17 citations in OpenAlex.
- Enriched experience increases reciprocal synaptic connectivity and coding sparsity in higher-order cortex.Science advances · 2026Article
- Engineering Neuronal Network Connectivity Through Precise and Scalable Electrical Modulation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Toward reliable machine learning models for neural circuit inference: A diagnostic study of CNNs on spike trains.PLoS computational biology · 2026Article
- Prefrontal cortex interneurons and their contributions to attention, working memory, and adaptive behavior.Progress in neurobiology · 2026Review
- Medial prefrontal cortex activity precedes dorsomedial striatum in need for change during history-based flexible behavior.iScience · 2025Article
- Advances in large-scale electrophysiology with high-density microelectrode arrays.Lab on a chip · 2025Review
- Enriched experience increases reciprocal synaptic connectivity and coding sparsity in higher-order cortex.bioRxiv : the preprint server for biology · 2025Article
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- Early synaptic dysfunction of striatal parvalbumin interneurons in a mouse model of Parkinson's disease.iScience · 2024Article
- Ensemble learning and ground-truth validation of synaptic connectivity inferred from spike trains.PLoS computational biology · 2024Article
- Wired together, change together: Spike timing modifies transmission in converging assemblies.Science advances · 2024Article
- Positive and biphasic extracellular waveforms correspond to return currents and axonal spikes.Communications biology · 2023Article
- Error correction and improved precision of spike timing in converging cortical networks.Cell reports · 2022Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Accurate detection and quantification of spike transmission between neurons is essential for determining neural network mechanisms that govern cognitive functions. Using point process and conductance-based simulations, we found that existing methods for determining neuronal connectivity from spike times are highly affected by burst spiking activity, resulting in over- or underestimation of spike transmission. To improve performance, we developed a mathematical framework for decomposing the cross-correlation between two spike trains. We then devised a deconvolution-based algorithm for removing effects of second-order spike train statistics. Deconvolution removed the effect of burst spiking, improving the estimation of neuronal connectivity yielded by state-of-the-art methods. Application of deconvolution to neuronal data recorded from hippocampal region CA1 of freely-moving mice produced higher estimates of spike transmission, in particular when spike trains exhibited bursts. Deconvolution facilitates the precise construction of complex connectivity maps, opening the door to enhanced understanding of the neural mechanisms underlying brain function.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.