Now showing items 1-6 of 6

    • Analysis of parameter changes of a neuronal network model using transfer entropy 

      Şengül Ayan, Sevgi; Gençağa, Deniz (International Advanced Researches and Engineering Journal, 2020)
      Understanding the dynamics of coupled neurons is one of the fundamental problems in the analysis of neuronal model dynamics. The transfer entropy (TE) method is one of the primary analyses to explore the information flow ...
    • Confounding factor analysis for vocal fold oscillations 

      Gençağa, Deniz (MDPI, 2023)
      This paper provides a methodology to better understand the relationships between different aspects of vocal fold motion, which are used as features in machine learning-based approaches for detecting respiratory infections ...
    • Effects of neuronal noise on neural communication 

      Gençağa, Deniz; Şengül Ayan, Sevgi (Proceedings, 2019)
      In this work, we propose an approach to better understand the effects of neuronal noise on neural communication systems. Here, we extend the fundamental Hodgkin-Huxley (HH) model by adding synaptic couplings to represent ...
    • Statistical approaches for the analysis of dependency among neurons under noise 

      Gençağa, Deniz; Şengül Ayan, Sevgi; Farnoudkia, Hajar; Okuyucu, Serdar (MDPI, 2020)
      Neuronal noise is a major factor affecting the communication between coupled neurons. In this work, we propose a statistical toolset to infer the coupling between two neurons under noise. We estimate these statistical ...
    • Transfer entropy 

      Gençağa, Deniz (MDPI AG, 2018)
      Statistical relationships among the variables of a complex system reveal a lot about its physical behavior. Therefore, identification of the relevant variables and characterization of their interactions are crucial for a ...
    • Transfer entropy 

      Gençağa, Deniz (MDPI, 2018)