Simulation-based Inference of Developmental EEG Maturation with the Spectral Graph Model
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866914896951640064 |
|---|---|
| author | Bernardo, Danilo Xie, Xihe Verma, Parul Kim, Jonathan Liu, Virginia Numis, Adam L. Wu, Ye Glass, Hannah C. Yap, Pew-Thian Nagarajan, Srikantan S. Raj, Ashish |
| author_facet | Bernardo, Danilo Xie, Xihe Verma, Parul Kim, Jonathan Liu, Virginia Numis, Adam L. Wu, Ye Glass, Hannah C. Yap, Pew-Thian Nagarajan, Srikantan S. Raj, Ashish |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_02524 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Simulation-based Inference of Developmental EEG Maturation with the Spectral Graph Model Bernardo, Danilo Xie, Xihe Verma, Parul Kim, Jonathan Liu, Virginia Numis, Adam L. Wu, Ye Glass, Hannah C. Yap, Pew-Thian Nagarajan, Srikantan S. Raj, Ashish Neurons and Cognition 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. |
| title | Simulation-based Inference of Developmental EEG Maturation with the Spectral Graph Model |
| topic | Neurons and Cognition |
| url | https://arxiv.org/abs/2405.02524 |