TY  - CONF
AU  - Pronold, Jari
AU  - van Meegen, Alexander
AU  - Shimoura, Renan
AU  - Vollenbröker, Hannah
AU  - Senden, Mario
AU  - Hilgetag, C. C.
AU  - Bakker, Rembrandt
AU  - van Albada, Sacha
TI  - Multi-scale Spiking Network Model of Human Cerebral Cortex
M1  - FZJ-2025-02699
PY  - 2025
AB  - Data-driven models at cellular resolution exist for various brain regions, yet few for human cortex. We present a comprehensive point-neuron network model of a human cortical hemisphere that integrates diverse experimental data into a unified framework bridging cellular and network scales [1]. Like a previous large-scale spiking model of macaque cortex [2,3], our work investigates how resting-state activity emerges in cortical networks.The model represents one hemisphere via the Desikan-Killiany parcellation (34 areas), with each area implemented as a 1 mm² microcircuit that distinguishes cortical layers. It aggregates multimodal data, including electron microscopy for synapse density, cytoarchitecture from the von Economo atlas [4], DTI-based connectivity [5], and local connection probabilities from the Potjans-Diesmann microcircuit [6]. Human neuron morphologies [7] guide layer-specific inter-area connectivity. The full-density model, comprising 3.47 million leaky integrate-and-fire neurons and 42.8 billion synapses, was simulated using NEST on the JURECA-DC supercomputer.Simulations show that equal strength for local and inter-area synapses yields asynchronous irregular activity that deviates from experimental observations. When inter-area connections are strengthened relative to local synapses, both microscopic spiking statistics from human medial frontal cortex and macroscopic resting-state fMRI correlations are reproduced [8]. In the latter scenario, consistent with empirical findings during visual imagery [9], sustained activity flows primarily from parietal through occipital and temporal to frontal areas.This open-source model enables systematic exploration of structure-dynamics relationships. Future work may leverage the Julich-Brain Atlas to refine the parcellation and incorporate detailed cytoarchitectural and receptor data [10]. The model code is available at https://github.com/INM-6/human-multi-area-model.
T2  - IAS Retreat 2025
CY  - 27 May 2025 - 27 May 2025, Jülich (Germany)
Y2  - 27 May 2025 - 27 May 2025
M2  - Jülich, Germany
LB  - PUB:(DE-HGF)24
DO  - DOI:10.34734/FZJ-2025-02699
UR  - https://juser.fz-juelich.de/record/1042899
ER  -