ICC   25427
INSTITUTO DE INVESTIGACION EN CIENCIAS DE LA COMPUTACION
Unidad Ejecutora - UE
congresos y reuniones científicas
Título:
Brain connectivity predicts performance in different domains of cognitive function in preschoolers
Autor/es:
PRATS, L.; FRACCHIA, C.; LIPINA S.J.; KAMIENKOWSKI JE; FRAIMAN D; SIGMAN, M.; PIETTO LM; HERMIDA M.J.
Lugar:
Buenos Aires
Reunión:
Congreso; 2 nd FALAN Congress (Federation of Latin American and Caribbean Neuroscience Societies); 2016
Institución organizadora:
Federation of Latin American and Caribbean Neuroscience Societies
Resumen:
Brain networks have been extensively explored mostly in adults but also during development. These networks were defined on the basis of several measures of similarity between brain regions? activity from fMRI, MEG and EEG. In adults, it has been shown how different networks are related with different cognitive functions for instance the fronto-parietal network with top-down control. These functional networks initially found during the performance of a related cognitive task, also appears to be still coherent at rest. During development, several lines of research explore when and how these networks arose. Interestingly, these studies typically explored linear correlations with age, while many plastic processes during first years of life depends nonlinearly on the age. Few studies focus on resting state EEG functional connectivity. A major difference between this technique and fMRI is the opportunity to focus on different time scales or frequency bands, and thus target different brain processes. They found significant differences in several frequency bands from 5 to 11 years using graph theory measures such as the characteristic path length, weight dispersion, and the modularity and homogeneity of the network. These results also supported the general picture of segregation and integration drawn from the fMRI studies. The relation between resting state activity with the performance in different tasks (in separatesessions) were started to be investigated in the last decade using mainly fMRI in adults, but also EEG. These studies investigated how measures of network function acquired at rest predicts subsequent performance in a perceptual or working memory task or acquisition of a newmotor skills. Extending these results to children could shed light on how learning different abilities and acquiring capacities shapes their brain.The present work was aimed to study how different cognitive control functions are represented in the brain networks, and particularly to explore the associations between resting-state connectivitypatterns and the children?s cognitive abilities measured in separate sessions (i.e Vocabulary and Matrices from the K-BIT test and a Stroop-like task).