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Simulation-based Inference of Developmental EEG Maturation with the Spectral Graph Model

D Bernardo, X Xie, P Verma, J Kim, V Liu, Y Wu… - arXiv preprint arXiv …, 2024 - arxiv.org
Quantitative Biology paper q-bio.NC Suggest

… In this study, we utilize simulation-based inference with the spectral graph model (SBI-SGM) to model EEG spectral maturation and infer population-based trajectories of …

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BibTeX

@article{2405.02524v3,
Author        = {Danilo Bernardo and Xihe Xie and Parul Verma and Jonathan Kim and Virginia Liu and Adam L. Numis and Ye Wu and Hannah C. Glass and Pew-Thian Yap and Srikantan S. Nagarajan and Ashish Raj},
Title         = {Simulation-based Inference of Developmental EEG Maturation with the
  Spectral Graph Model},
Eprint        = {2405.02524v3},
DOI           = {10.1038/s42005-024-01748-w},
ArchivePrefix = {arXiv},
PrimaryClass  = {q-bio.NC},
Abstract      = {The spectral content of macroscopic neural activity evolves throughout
development, yet how this maturation relates to underlying brain network
formation and dynamics remains unknown. Here, we assess the developmental
maturation of electroencephalogram spectra via Bayesian model inversion of the
spectral graph model, a parsimonious whole-brain model of spatiospectral neural
activity derived from linearized neural field models coupled by the structural
connectome. Simulation-based inference was used to estimate age-varying
spectral graph model parameter posterior distributions from
electroencephalogram spectra spanning the developmental period. This
model-fitting approach accurately captures observed developmental
electroencephalogram spectral maturation via a neurobiologically consistent
progression of key neural parameters: long-range coupling, axonal conduction
speed, and excitatory:inhibitory balance. These results suggest that the
spectral maturation of macroscopic neural activity observed during typical
development is supported by age-dependent functional adaptations in localized
neural dynamics and their long-range coupling across the macroscopic structural
network.},
Year          = {2024},
Month         = {May},
Note          = {Commun Phys 7, 255 (2024)},
Url           = {http://arxiv.org/abs/2405.02524v3},
File          = {2405.02524v3.pdf}
}

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