Poster (Other)

FZJ-2023-04363

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Multi-Scale Spiking Network Model of Human Cerebral Cortex

Pronold, J. ; Meegen, A. v. ; Vollenbröker, H. ; Shimoura, R. (Corresponding author)FZJ* ; Senden, M. ; Hilgetag, C. C. ; Bakker, R.FZJ* ; van Albada, S.FZJ*

2023

Abstract: Background: The structure of the brain plays a crucial role in shaping its activity. However, the link between structural connectivity and observed neuronal activity remains incompletely understood. Previous research utilizing a large-scale spiking network model of leaky integrate-and-fire neurons has addressed this question for macaque cortex [1,2]. Here, a similar framework is employed to investigate human cortex in a model that links the cortical network structure to the resting-state activity of neurons, populations, layers, and areas.Objectives: The objective of this study is to investigate the link between structural connectivity and observed neuronal activity in human cortex using a large-scale spiking network model, and to create a platform for multi-scale in silico studies of human cortex.Materials and Methods: The model includes all 34 areas in a single hemisphere of human cortex according to the Desikan-Killiany parcellation. Our approach integrates cortical data on architecture, morphology, and connectivity into a multi-scale framework for predicting neuron connections. Each cortical area is represented by a 1 $mm^2$ layered microcircuit adapted from [3] with the full density of neurons and synapses. Inter-area connectivity relies on diffusion tensor imaging data [4] and the determination of laminar patterns of synaptic connectivity takes into account human neuron morphology data [5]. The model comprises 4 million neurons and 50 billion synapses, simulated with the NEST simulator on the supercomputer JURECA-DC. Results and Conclusions: Simulations of the model with uniform synaptic weights reveal a state with asynchronous and irregular activity that deviates from experimental recordings in terms of spiking activity and inter-area functional connectivity. Increasing inter-area synapse strength enables the model to capture both microscopic and macroscopic resting-state activity of human cortex measured via electrophysiological recordings and fMRI [6]. Furthermore, the model reveals rapid propagation of the effects of a single-spike perturbation across the entire network. This suggests individual spikes play a role in fast sensory processing and behavioral responses in the cortical network. Overall, the model serves as a basis for the investigation of multi-scale structure-dynamics relationships in human cortex.

Note: References: [1] Schmidt M, Bakker R, Hilgetag CC, Diesmann M, van Albada SJ. Brain Struct Funct. 2018;223(3):1409–35.[2] Schmidt M, Bakker R, Shen K, Bezgin G, Diesmann M, et al. PLOS Comput Biol. 2018;14(10):e1006359.[3] Potjans TC, Diesmann M. Cerebral Cortex. 2014;24(3):785–806.[4] Van Essen DC, Smith SM, Barch DM, Behrens TE, Yacoub E, et al. Neuroimage. 2013;80:62–79[5] Mohan H, Verhoog MB, Doreswamy KK, Eyal G, Aardse R, et al. Cerebral Cortex. 2015;25(12):4839–53.[6] Minxha J, Adolphs R, Fusi S, Mamelak AN, Rutishauser U. Science. 2020;368(6498).

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Contributing Institute(s):

1. Computational and Systems Neuroscience (INM-6)
2. Theoretical Neuroscience (IAS-6)
3. Jara-Institut Brain structure-function relationships (INM-10)

Research Program(s):

1. 5231 - Neuroscientific Foundations (POF4-523) (POF4-523)
2. DFG project 313856816 - SPP 2041: Computational Connectomics (313856816) (313856816)
3. DFG project 347572269 - Heterogenität von Zytoarchitektur, Chemoarchitektur und Konnektivität in einem großskaligen Computermodell der menschlichen Großhirnrinde (347572269) (347572269)
4. HBP SGA3 - Human Brain Project Specific Grant Agreement 3 (945539) (945539)
5. Brain-Scale Simulations (jinb33_20220812) (jinb33_20220812)

Appears in the scientific report 2023

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