ArticleFrontiers in neuroanatomy2014
Generation of dense statistical connectomes from sparse morphological data.
Article in Frontiers in neuroanatomy, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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36 citing papers in PubMed, 59 citations in OpenAlex.
- An in silico framework for dissecting the mechanistic origins of in vivo recorded neuronal activity.PLoS computational biology · 2026Article
- Network-neuron interactions underlying sensory responses of layer 5 pyramidal tract neurons in barrel cortex.PLoS computational biology · 2024Article
- Cell-type-specific inhibitory circuitry from a connectomic census of mouse visual cortex.bioRxiv : the preprint server for biology · 2024Article
- Review
- Simulation-based inference for efficient identification of generative models in computational connectomics.PLoS computational biology · 2023Article
- Translating single-neuron axonal reconstructions into meso-scale connectivity statistics in the mouse somatosensory thalamus.Frontiers in neuroinformatics · 2023Article
- Circuit-selective cell-autonomous regulation of inhibition in pyramidal neurons by Ste20-like kinase.Cell reports · 2022Article
- Structured sampling of olfactory input by the fly mushroom body.Current biology : CB · 2022Article
- The impact of neuron morphology on cortical network architecture.Cell reports · 2022Article
- Statistical Emulation of Neural Simulators: Application to Neocortical L2/3 Large Basket Cells.Frontiers in big data · 2022Article
- Neural anatomy and optical microscopy (NAOMi) simulation for evaluating calcium imaging methods.Journal of neuroscience methods · 2021Article
- Cellular connectomes as arbiters of local circuit models in the cerebral cortex.Nature communications · 2021Article
- Database of literature derived cellular measurements from the murine basal ganglia.Scientific data · 2020Article
- Anatomy and Physiology of Macaque Visual Cortical Areas V1, V2, and V5/MT: Bases for Biologically Realistic Models.Cerebral cortex (New York, N.Y. : 1991) · 2020Review
- An efficient analytical reduction of detailed nonlinear neuron models.Nature communications · 2020Article
- Article
- MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images.Frontiers in neuroanatomy · 2018Article
- 3D reconstruction and standardization of the rat facial nucleus for precise mapping of vibrissal motor networks.Neuroscience · 2018Article
- Human Cortical Pyramidal Neurons: From Spines to Spikes via Models.Frontiers in cellular neuroscience · 2018Article
- Rich cell-type-specific network topology in neocortical microcircuitry.Nature neuroscience · 2017Article
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sensory-evoked signal flow, at cellular and network levels, is primarily determined by the synaptic wiring of the underlying neuronal circuitry. Measurements of synaptic innervation, connection probabilities and subcellular organization of synaptic inputs are thus among the most active fields of research in contemporary neuroscience. Methods to measure these quantities range from electrophysiological recordings over reconstructions of dendrite-axon overlap at light-microscopic levels to dense circuit reconstructions of small volumes at electron-microscopic resolution. However, quantitative and complete measurements at subcellular resolution and mesoscopic scales to obtain all local and long-range synaptic in/outputs for any neuron within an entire brain region are beyond present methodological limits. Here, we present a novel concept, implemented within an interactive software environment called NeuroNet, which allows (i) integration of sparsely sampled (sub)cellular morphological data into an accurate anatomical reference frame of the brain region(s) of interest, (ii) up-scaling to generate an average dense model of the neuronal circuitry within the respective brain region(s) and (iii) statistical measurements of synaptic innervation between all neurons within the model. We illustrate our approach by generating a dense average model of the entire rat vibrissal cortex, providing the required anatomical data, and illustrate how to measure synaptic innervation statistically. Comparing our results with data from paired recordings in vitro and in vivo, as well as with reconstructions of synaptic contact sites at light- and electron-microscopic levels, we find that our in silico measurements are in line with previous results.
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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.