Dissociating frontoparietal brain networks with neuroadaptive Bayesian optimization
The unique contributions of different frontoparietal networks (FPNs) in cognition remains unclear. Here, authors use neuroadaptive Bayesian optimization to identify cognitive tasks that segregate dorsal and ventral FPNs and reveal complex many-to-many mappings between cognitive tasks and FPNs.
Guardado en:
Autores principales: | Romy Lorenz, Ines R. Violante, Ricardo Pio Monti, Giovanni Montana, Adam Hampshire, Robert Leech |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2018
|
Materias: | |
Acceso en línea: | https://doaj.org/article/e82b555ea3a2440696a1a1ae12917310 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Transcriptional Correlates of Chronic Alcohol Neuroadaptation in Drosophila Larvae
por: Amanda Anqueira-González, et al.
Publicado: (2021) -
Mathematical learning deficits originate in early childhood from atypical development of a frontoparietal brain network.
por: Ulrike Kuhl, et al.
Publicado: (2021) -
Dynamic network coding of working-memory domains and working-memory processes
por: Eyal Soreq, et al.
Publicado: (2019) -
Frontoparietal network resilience is associated with protection against cognitive decline in Parkinson’s disease
por: Arianna D. Cascone, et al.
Publicado: (2021) -
Neuroimaging evidence for a network sampling theory of individual differences in human intelligence test performance
por: Eyal Soreq, et al.
Publicado: (2021)