Extracting BOLD signals based on time-constrained multiset canonical correlation analysis for brain functional network estimation and classification.
Brain Res
; 1775: 147745, 2022 01 15.
Article
em En
| MEDLINE
| ID: mdl-34864043
ABSTRACT
Brain functional network (BFN), usually estimated from blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI), has been proven to be a powerful tool to study the organization of the brain and discover biomarkers for diagnosis of brain disorders. Prior to BFN estimation and classification, extracting representative BOLD signals from brain regions of interest (ROIs) is a critical step. Traditional extraction methods include averaging, peaking operation and dimensionality reduction, often leading to signal cancellation and information loss. In this paper, we propose a novel method, namely time-constrained multiset canonical correlation analysis (TMCCA), to extract representative BOLD signals for subsequent BFN estimation and classification. Different from traditional methods that equally treat all BOLD signals in a ROI, the proposed method assigns weights to different BOLD signals, and learns the optimal weights to make the extracted representative signals jointly maximize the multiple correlations between ROIs. Importantly, time-constraint is incorporated into our proposed method, which can effectively encode nonlinear relationship among BOLD signals. To evaluate the effectiveness of the proposed method, the extracted BOLD signals is used to estimate BFN and, in turn, identify brain disorders, including mild cognitive impairment (MCI) and autistic spectrum disorder (ASD). Experimental results demonstrate that our proposed TMCCA can lead to better performance than traditional methods.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Encéfalo
/
Rede Nervosa
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
Brain Res
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
China
País de publicação:
HOLANDA
/
HOLLAND
/
NETHERLANDS
/
NL
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PAISES BAJOS
/
THE NETHERLANDS