% IMPORTANT: The following is UTF-8 encoded. This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.
@INPROCEEDINGS{Pronold:1042899,
author = {Pronold, Jari and van Meegen, Alexander and Shimoura, Renan
and Vollenbröker, Hannah and Senden, Mario and Hilgetag, C.
C. and Bakker, Rembrandt and van Albada, Sacha},
title = {{M}ulti-scale {S}piking {N}etwork {M}odel of {H}uman
{C}erebral {C}ortex},
reportid = {FZJ-2025-02699},
year = {2025},
abstract = {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.},
month = {May},
date = {2025-05-27},
organization = {IAS Retreat 2025, Jülich (Germany),
27 May 2025 - 27 May 2025},
subtyp = {Other},
cin = {IAS-6},
cid = {I:(DE-Juel1)IAS-6-20130828},
pnm = {5231 - Neuroscientific Foundations (POF4-523) / HBP SGA3 -
Human Brain Project Specific Grant Agreement 3 (945539) /
EBRAINS 2.0 - EBRAINS 2.0: A Research Infrastructure to
Advance Neuroscience and Brain Health (101147319) / JL SMHB
- Joint Lab Supercomputing and Modeling for the Human Brain
(JL SMHB-2021-2027) / $HiRSE_PS$ - Helmholtz Platform for
Research Software Engineering - Preparatory Study
$(HiRSE_PS-20220812)$ / Brain-Scale Simulations
$(jinb33_20220812)$ / DFG project G:(GEPRIS)491111487 -
Open-Access-Publikationskosten / 2025 - 2027 /
Forschungszentrum Jülich (OAPKFZJ) (491111487)},
pid = {G:(DE-HGF)POF4-5231 / G:(EU-Grant)945539 /
G:(EU-Grant)101147319 / G:(DE-Juel1)JL SMHB-2021-2027 /
$G:(DE-Juel-1)HiRSE_PS-20220812$ /
$G:(DE-Juel1)jinb33_20220812$ / G:(GEPRIS)491111487},
typ = {PUB:(DE-HGF)24},
doi = {10.34734/FZJ-2025-02699},
url = {https://juser.fz-juelich.de/record/1042899},
}