Cargando…
Topological data analysis for revealing dynamic brain reconfiguration in MEG data
In recent years, the focus of the functional connectivity community has shifted from stationary approaches to the ones that include temporal dynamics. Especially, non-invasive electrophysiological data (magnetoencephalography/electroencephalography (MEG/EEG)) with high temporal resolution and good s...
Autores principales: | Duman, Ali Nabi, Tatar, Ahmet E. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10363343/ https://www.ncbi.nlm.nih.gov/pubmed/37489123 http://dx.doi.org/10.7717/peerj.15721 |
Ejemplares similares
-
Uncovering Dynamic Brain Reconfiguration in MEG Working Memory n-Back Task Using Topological Data Analysis
por: Duman, Ali Nabi, et al.
Publicado: (2019) -
Bayesian analysis of phase data in EEG and MEG
por: Dimmock, Sydney, et al.
Publicado: (2023) -
MEG and EEG data analysis with MNE-Python
por: Gramfort, Alexandre, et al.
Publicado: (2013) -
BrainWave: A Matlab Toolbox for Beamformer Source Analysis of MEG Data
por: Jobst, Cecilia, et al.
Publicado: (2018) -
The Impact of the Geometric Correction Scheme on MEG Functional Topology at Rest
por: Della Penna, Stefania, et al.
Publicado: (2019)