Functional Connectivity-Based Parcellation of the Thalamus: An Unsupervised Clustering Method and Its Validity Investigation.
Brain Connect
; 5(10): 620-30, 2015 Dec.
Article
em En
| MEDLINE
| ID: mdl-26106821
Node definition or delineating how the brain is parcellated into individual functionally related regions is the first step to accurately map the human connectome. As a result, parcellation of the human brain has drawn considerable attention in the field of neuroscience. The thalamus is known as a relay in the human brain, with its nuclei sending fibers to the cortical and subcortical regions. Functional magnetic resonance imaging techniques offer a way to parcellate the thalamus in vivo based on its connectivity properties. However, the parcellations from previous studies show that both the number and the distribution of thalamic subdivisions vary with different cortical segmentation methods. In this study, we used an unsupervised clustering method that does not rely on a priori information of the cortical segmentation to parcellate the thalamus. Instead, this approach is based on the intrinsic resting-state functional connectivity profiles of the thalamus with the whole brain. A series of cluster solutions were obtained, and an optimal solution was determined. Furthermore, the validity of our parcellation was investigated through the following: (1) identifying specific resting-state connectivity patterns of thalamic parcels with different brain networks and (2) investigating the task activation and psychophysiological interactions of specific thalamic clusters during 8-Hz flashing checkerboard stimulation with simultaneous finger tapping. Together, the current study provides a reliable parcellation of the thalamus and enhances our understating of thalamic. Furthermore, the current study provides a framework for parcellation that could be potentially extended to other subcortical and cortical regions.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Tálamo
/
Processamento de Imagem Assistida por Computador
Tipo de estudo:
Clinical_trials
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Prognostic_studies
Limite:
Adult
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Female
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Humans
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Male
Idioma:
En
Revista:
Brain Connect
Ano de publicação:
2015
Tipo de documento:
Article
País de afiliação:
China