Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Sevgi Şengül Ayan"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract The impact of emotions on human behavior is substantial, and the ability to recognize people's feelings has a wide range of practical applications including education. Here, the methods and tools of education are being calibrated according t
Externí odkaz:
https://doaj.org/article/3fa7f82ea7be42969d2e5b8c9c6cc822
Publikováno v:
Entropy, Vol 22, Iss 4, p 387 (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 dependencies from data which are
Externí odkaz:
https://doaj.org/article/9850f17d304c474096e7f91a00718a81
Autor:
Deniz Gençağa, Sevgi Şengül Ayan
Publikováno v:
Proceedings, Vol 33, Iss 1, p 2 (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 the statistical dependencies
Externí odkaz:
https://doaj.org/article/610bec3449754fac8f85b0334cbefbce
A Pilot Study of Ion Current Estimation by Artificial Neural Network from Action Potential Waveforms
Experiments using conventional experimental approaches to capture the dynamics of ion channels are not always feasible, and even when possible and feasible, some can be time-consuming. In this work, the ionic current-time dynamics during cardiac acti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::519bd9f8d84762640c96ac40a65aff1a
https://doi.org/10.21203/rs.3.rs-1900433/v1
https://doi.org/10.21203/rs.3.rs-1900433/v1
Autor:
Sevgi Şengül Ayan, Ahmet Kürşad Sırcan
Publikováno v:
Channels
article-version (VoR) Version of Record
article-version (VoR) Version of Record
Mathematical models for the action potential (AP) generation of the electrically excitable cells including the heart are involved different mechanisms including the voltage-dependent currents with nonlinear time- and voltage-gating properties. From t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cb470bb577786cc39a463d6052427014
https://doi.org/10.1080/19336950.2021.1940628
https://doi.org/10.1080/19336950.2021.1940628
Autor:
Sevgi Şengül Ayan, Uğur Dalaman, Ahmet Kurt, Mohamedou Abewa, Ahmet Kürşad Sırcan, Nazmi Yaras
Publikováno v:
European Biophysics Journal. 49:323-342
Mathematical action potential (AP) modeling is a well-established but still-developing area of research to better understand physiological and pathological processes. In particular, changes in AP mechanisms in the isoproterenol (ISO) -induced hypertr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::64c1df2dab9346ae9276fe6fc7749aa4
https://doi.org/10.1007/s00249-020-01439-8
https://doi.org/10.1007/s00249-020-01439-8
The patch-clamp technique is a significant tool in current electrophysiology research, especially in cardiovascular diseases, because it can capture electrical activity of the heart from cardiomyocytes. It is challenging to classify action potential
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::763500ab956c11d90b23da08c1836f26
http://hdl.handle.net/20.500.12566/1377
http://hdl.handle.net/20.500.12566/1377
Autor:
Deniz Gençağa, Sevgi Şengül Ayan
Publikováno v:
Volume: 4, Issue: 3 208-216
International Advanced Researches and Engineering Journal
International Advanced Researches and Engineering Journal
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 between the neuronal populati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::42d99da9be14d9f7e36c1606a7bfdfdc
https://dergipark.org.tr/tr/pub/iarej/issue/57908/747142
https://dergipark.org.tr/tr/pub/iarej/issue/57908/747142
Publikováno v:
Entropy, Vol 22, Iss 387, p 387 (2020)
Entropy
Volume 22
Issue 4
Entropy
Volume 22
Issue 4
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 dependencies from data which are
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9e2ec81e6a78c4d1f0843f1c8b68c40b
http://hdl.handle.net/20.500.12566/788
http://hdl.handle.net/20.500.12566/788