TY  - JOUR
AU  - Pronold, Jari
AU  - van Meegen, Alexander
AU  - Shimoura, Renan O
AU  - Vollenbröker, Hannah
AU  - Senden, Mario
AU  - Hilgetag, Claus C
AU  - Bakker, Rembrandt
AU  - van Albada, Sacha J
TI  - Multi-Scale Spiking Network Model of Human Cerebral Cortex
JO  - Cerebral cortex
VL  - 34
IS  - 10
SN  - 1047-3211
CY  - Oxford
PB  - Oxford Univ. Press
M1  - FZJ-2024-05686
SP  - bhae409
PY  - 2024
AB  - 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 $mm^2$ 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.
LB  - PUB:(DE-HGF)16
C6  - 39428578
UR  - <Go to ISI:>//WOS:001336208500001
DO  - DOI:10.1093/cercor/bhae409
UR  - https://juser.fz-juelich.de/record/1031473
ER  -