首页|State-sensitive convolutional sparse coding for potential biomarker identification in brain signals

State-sensitive convolutional sparse coding for potential biomarker identification in brain signals

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The identification of prototypical waveforms,such as sleep spindles and epileptic spikes,is crucial for the diagnosis of neurological disorders.These prototypical waveforms are usually recurrently presented in certain brain states,serving as potential biomarkers for clinical evaluations.Convolutional sparse coding(CSC)approaches have demonstrated strength in identifying recurrent patterns in time-series.However,existing CSC approaches do not explicitly explore state-specific patterns,making it difficult to identify state-related biomarkers.To address this problem,we propose state-sensitive CSC to learn state-specific prototypical waveforms.Specifically,we model signals of a certain state with specific waveforms that only appear frequently in this state and background waveforms that are independent of states.Based on this,state-sensitive CSC separates state-specific waveforms from background ones explicitly by incorporating incoherence constraints into optimizations.Experiments with epilepsy brain signals demonstrate that our approach can effectively identify prototypical waveforms in pre-ictal states,providing potential biomarkers for seizure prediction.Our approach provides a promising tool for automatic biomarker candidate identification.

convolutional sparse codingprototypical waveformsstate-specific dictionarybiomarker iden-tificationneural signal processing

Puli WANG、Yu QI、Gang PAN

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College of Computer Science and Technology,Zhejiang University,Hangzhou 310000,China

State Key Laboratory of Brain-Machine Intelligence,Zhejiang University,Hangzhou 310000,China

MOE Frontier Science Center for Brain Science and Brain-machine Integration,Zhejiang University,Hangzhou 310000,China

Affiliated Mental Health Center & Hangzhou Seventh People's Hospital,Zhejiang University School of Medicine,Hangzhou 310000,China

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STI 2030 Major ProjectsNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaKey R&D Program of Zhejiang

2021ZD0200400U190920261925603622762282023C03001

2024

10.1007/s11432-023-3876-1

中国科学:信息科学(英文版)
中国科学院

中国科学:信息科学(英文版)

CSTPCDEI
影响因子：0.715
ISSN：1674-733X
年,卷(期)：2024.67(5)
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