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Using max entropy ratio of recurrence plot to measure electrocorticogram changes in epilepsy patients

Author

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  • Yan, Jiaqing
  • Wang, Yinghua
  • Ouyang, Gaoxiang
  • Yu, Tao
  • Li, Xiaoli

Abstract

A maximum entropy ratio (MER) method is firstly adapted to investigate the high-dimensional Electrocorticogram (ECoG) data from epilepsy patients. MER is a symbolic analysis approach for the detection of recurrence domains of complex dynamical systems from time series. Data were chosen from eight patients undergoing pre-surgical evaluation for drug-resistant temporal lobe epilepsy. MERs for interictal and ictal data were calculated and compared. A statistical test was performed to evaluate the ability of MER to separate the interictal state from the ictal state. MER showed significant changes from the interictal state into the ictal state, where MER was low at the ictal state and is significantly different with that at the interictal state. These suggest that MER is able to separate the ictal state from the interictal state based on ECoG data. It has the potential of detecting the transition between normal brain activity and the ictal state.

Suggested Citation

  • Yan, Jiaqing & Wang, Yinghua & Ouyang, Gaoxiang & Yu, Tao & Li, Xiaoli, 2016. "Using max entropy ratio of recurrence plot to measure electrocorticogram changes in epilepsy patients," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 109-116.
    • Handle: RePEc:eee:phsmap:v:443:y:2016:i:c:p:109-116
    DOI: 10.1016/j.physa.2015.09.069
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    Cited by:

    1. Xu, Mengjia & Shang, Pengjian & Lin, Aijing, 2017. "Multiscale recurrence quantification analysis of order recurrence plots," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 381-389.
    2. Chen, Yuan & Lin, Aijing, 2022. "Order pattern recurrence for the analysis of complex systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    3. Yang, Chuanzuo & Luan, Guoming & Liu, Zhao & Wang, Qingyun, 2019. "Dynamical analysis of epileptic characteristics based on recurrence quantification of SEEG recordings," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 507-515.

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