Cohort-level brain mapping: learning cognitive atoms to single out specialized regions.
Inf Process Med Imaging
; 23: 438-49, 2013.
Article
en En
| MEDLINE
| ID: mdl-24683989
Functional Magnetic Resonance Imaging (fMRI) studies map the human brain by testing the response of groups of individuals to carefully-crafted and contrasted tasks in order to delineate specialized brain regions and networks. The number of functional networks extracted is limited by the number of subject-level contrasts and does not grow with the cohort. Here, we introduce a new group-level brain mapping strategy to differentiate many regions reflecting the variety of brain network configurations observed in the population. Based on the principle of functional segregation, our approach singles out functionally-specialized brain regions by learning group-level functional profiles on which the response of brain regions can be represented sparsely. We use a dictionary-learning formulation that can be solved efficiently with on-line algorithms, scaling to arbitrary large datasets. Importantly, we model inter-subject correspondence as structure imposed in the estimated functional profiles, integrating a structure-inducing regularization with no additional computational cost. On a large multi-subject study, our approach extracts a large number of brain networks with meaningful functional profiles.
Buscar en Google
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Algoritmos
/
Encéfalo
/
Mapeo Encefálico
/
Reconocimiento de Normas Patrones Automatizadas
/
Inteligencia Artificial
/
Imagen por Resonancia Magnética
/
Interpretación de Imagen Asistida por Computador
/
Red Nerviosa
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
Inf Process Med Imaging
Asunto de la revista:
DIAGNOSTICO POR IMAGEM
/
INFORMATICA MEDICA
Año:
2013
Tipo del documento:
Article
Pais de publicación:
Alemania