ArticleCerebral cortex (New York, N.Y. : 1991)2024
Multi-scale spiking network model of human cerebral cortex.
Article in Cerebral cortex (New York, N.Y. : 1991), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- A brain-constrained neural model of cognition and language with NEST: transitioning from the Felix framework.Cognitive neurodynamics · 2026Article
- Mechanistic corticostriatal circuit model predicts learning-dependent fMRI dynamics and individual reward bias in humans.bioRxiv : the preprint server for biology · 2026Article
- Measurement of electrochemical brain activity with fast-scan cyclic voltammetry during functional magnetic resonance imaging.Nature protocols · 2026Review
- A Framework Integrating Spiking Cortical Circuit Modeling and Simulation-Based Inference to Probe Biomarkers of Cortical Dysfunction in Alzheimer's Disease.Interdisciplinary sciences, computational life sciences · 2026Article
- Building on models-a perspective for computational neuroscience.Cerebral cortex (New York, N.Y. : 1991) · 2025Article
- Layered structure of cortex explains reversal dynamics in bistable perception.Scientific reports · 2025Article
- A Python toolbox for neural circuit parameter inference.NPJ systems biology and applications · 2025Article
- Article
- The architecture of the human default mode network explored through cytoarchitecture, wiring and signal flow.Nature neuroscience · 2025Article
- Article
- Stitcher: A Surface Reconstruction Tool for Highly Gyrified Brains.Neuroinformatics · 2024Article
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Authors and funding
8 authors.
Funding
Abstract
Although the structure of cortical networks provides the necessary substrate for their neuronal activity, the structure alone does not suffice to understand the activity. Leveraging the increasing availability of human data, we developed a multi-scale, spiking network model of human cortex to investigate the relationship between structure and dynamics. In this model, each area in one hemisphere of the Desikan-Killiany parcellation is represented by a $1\,\mathrm{mm^{2}}$ column with a layered structure. The model aggregates data across multiple modalities, including electron microscopy, electrophysiology, morphological reconstructions, and diffusion tensor imaging, into a coherent framework. It predicts activity on all scales from the single-neuron spiking activity to the area-level functional connectivity. We compared the model activity with human electrophysiological data and human resting-state functional magnetic resonance imaging (fMRI) data. This comparison reveals that the model can reproduce aspects of both spiking statistics and fMRI correlations if the inter-areal connections are sufficiently strong. Furthermore, we study the propagation of a single-spike perturbation and macroscopic fluctuations through the network. The open-source model serves as an integrative platform for further refinements and future in silico studies of human cortical structure, dynamics, and function.
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Registered trials
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