Sparse Spike Feature Learning to Recognize Traceable Interictal Epileptiform Spikes - Université de Picardie Jules Verne
Article Dans Une Revue International Journal of Neural Systems Année : 2024

Sparse Spike Feature Learning to Recognize Traceable Interictal Epileptiform Spikes

Chenchen Cheng
Yunbo Shi
Yan Liu
Bo You
Yuanfeng Zhou
Yakang Dai

Résumé

Interictal epileptiform spikes (spikes) and epileptogenic focus are strongly correlated. However, partial spikes are insensitive to epileptogenic focus, which restricts epilepsy neurosurgery. Therefore, identifying spike subtypes that are strongly associated with epileptogenic focus (traceable spikes) could facilitate their use as reliable signal sources for accurately tracing epileptogenic focus. However, the sparse firing phenomenon in the transmission of intracranial neuronal discharges leads to differences within spikes that cannot be observed visually. Therefore, neuro-electro-physiologists are unable to identify traceable spikes that could accurately locate epileptogenic focus. Herein, we propose a novel sparse spike feature learning method to recognize traceable spikes and extract discrimination information related to epileptogenic focus. First, a multilevel eigensystem feature representation was determined based on a multilevel feature representation module to express the intrinsic properties of a spike. Second, the sparse feature learning module expressed the sparse spike multi-domain context feature representation to extract sparse spike feature representations. Among them, a sparse spike encoding strategy was implemented to effectively simulate the sparse firing phenomenon for the accurate encoding of the activity of intracranial neurosources. The sensitivity of the proposed method was 97.1%, demonstrating its effectiveness and significant efficiency relative to other state-of-the-art methods.

Domaines

Neurosciences
Fichier non déposé

Dates et versions

hal-04822365 , version 1 (06-12-2024)

Identifiants

Citer

Chenchen Cheng, Yunbo Shi, Yan Liu, Bo You, Yuanfeng Zhou, et al.. Sparse Spike Feature Learning to Recognize Traceable Interictal Epileptiform Spikes. International Journal of Neural Systems, 2024, ⟨10.1142/S0129065724500710⟩. ⟨hal-04822365⟩

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