Cargando…
Disentangling dynamic networks: Separated and joint expressions of functional connectivity patterns in time
Resting‐state functional connectivity (FC) is highly variable across the duration of a scan. Groups of coevolving connections, or reproducible patterns of dynamic FC (dFC), have been revealed in fluctuating FC by applying unsupervised learning techniques. Based on results from k‐means clustering and...
Autores principales: | Leonardi, Nora, Shirer, William R., Greicius, Michael D., Van De Ville, Dimitri |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6868958/ https://www.ncbi.nlm.nih.gov/pubmed/25081921 http://dx.doi.org/10.1002/hbm.22599 |
Ejemplares similares
-
Transient brain activity disentangles fMRI resting-state dynamics in terms of spatially and temporally overlapping networks
por: Karahanoğlu, Fikret Işik, et al.
Publicado: (2015) -
Disentangled Dynamic Deviation Transformer Networks for Multivariate Time Series Anomaly Detection
por: Wang, Chunzhi, et al.
Publicado: (2023) -
Disentangling Multispectral Functional Connectivity With Wavelets
por: Billings, Jacob C. W., et al.
Publicado: (2018) -
Sparse synaptic connectivity is required for decorrelation and pattern separation in feedforward networks
por: Cayco-Gajic, N. Alex, et al.
Publicado: (2017) -
Disentanglement Dynamics in Nonequilibrium Environments
por: Chen, Mingli, et al.
Publicado: (2022)