ArticleScientific reports2022
A realistic morpho-anatomical connection strategy for modelling full-scale point-neuron microcircuits.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 14 citations in OpenAlex.
- Article
- Co-simulation framework combining a microscopically detailed point neuron model of the hippocampal CA1 region with the macroscopic high-resolution virtual brain model.Journal of computational neuroscience · 2026Article
- Visualization and simulation of full-scale point-neuron circuits via the Neural Circuit Visualizer web platform.Scientific reports · 2026Article
- A Computational Model of the Respiratory CPG for the Artificial Control of Breathing.Bioengineering (Basel, Switzerland) · 2025Article
- Large-Scale Mechanistic Models of Brain Circuits with Biophysically and Morphologically Detailed Neurons.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Review
- Modeling the impact of neuromorphological alterations in Down syndrome on fast neural oscillations.PLoS computational biology · 2024Article
- Multiscale modeling of neuronal dynamics in hippocampus CA1.Frontiers in computational neuroscience · 2024Article
- Long-Term Synaptic Plasticity Tunes the Gain of Information Channels through the Cerebellum Granular Layer.Biomedicines · 2022Article
- Towards the Simulation of a Realistic Large-Scale Spiking Network on a Desktop Multi-GPU System.Bioengineering (Basel, Switzerland) · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The modeling of extended microcircuits is emerging as an effective tool to simulate the neurophysiological correlates of brain activity and to investigate brain dysfunctions. However, for specific networks, a realistic modeling approach based on the combination of available physiological, morphological and anatomical data is still an open issue. One of the main problems in the generation of realistic networks lies in the strategy adopted to build network connectivity. Here we propose a method to implement a neuronal network at single cell resolution by using the geometrical probability volumes associated with pre- and postsynaptic neurites. This allows us to build a network with plausible connectivity properties without the explicit use of computationally intensive touch detection algorithms using full 3D neuron reconstructions. The method has been benchmarked for the mouse hippocampus CA1 area, and the results show that this approach is able to generate full-scale brain networks at single cell resolution that are in good agreement with experimental findings. This geometric reconstruction of axonal and dendritic occupancy, by effectively reflecting morphological and anatomical constraints, could be integrated into structured simulators generating entire circuits of different brain areas facilitating the simulation of different brain regions with realistic models.
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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.