Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Farzaneh Shayegh"'
Publikováno v:
Journal of Medical Signals and Sensors, Vol 14, Iss 8, Pp 24-24 (2024)
Unlike other functional integration methods that examine the relationship and correlation between two channels, effective connection reports the direct effect of one channel on another and expresses their causal relationship. In this article, we inve
Externí odkaz:
https://doaj.org/article/75b57316347a4726b7a53525bbcf760e
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-15 (2022)
Abstract Due to the increasing prevalence of chronic kidney disease and its high mortality rate, study of risk factors affecting the progression of the disease is of great importance. Here in this work, we aim to develop a framework for using machine
Externí odkaz:
https://doaj.org/article/5b9755f794b3447e83ba253af86f29c2
Publikováno v:
Frontiers in Systems Neuroscience, Vol 16 (2023)
IntroductionCan we apply graph representation learning algorithms to identify autism spectrum disorder (ASD) patients within a large brain imaging dataset? ASD is mainly identified by brain functional connectivity patterns. Attempts to unveil the com
Externí odkaz:
https://doaj.org/article/c190e646078346ee870c0371b2dafb57
Autor:
Farzaneh Shayegh, Jean-Jacques Bellanger, Saied Sadri, Rasoul Amirfattahi, Karim Ansari-Asl, Lotfi Senhadji
Publikováno v:
Journal of Medical Signals and Sensors, Vol 3, Iss 1, Pp 2-14 (2013)
Neural mass models are computational nonlinear models that simulate the activity of a population of neurons as an average neuron, in such a way that different inhibitory post-synaptic potential and excitatory post-synaptic potential signals could be
Externí odkaz:
https://doaj.org/article/1d449810f90e49adaea11743567abe1a
Publikováno v:
The Journal of The Textile Institute. :1-12
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::38200050cfcebbad04a0f5370a6c7190
https://doi.org/10.1080/00405000.2022.2149498
https://doi.org/10.1080/00405000.2022.2149498
Publikováno v:
Journal of theoretical biology. 506
Nowadays, numerous studies have investigated the modeling of efficient neural encoding processes in the retina of the eye to encode the sensory data. Retina, as the innermost coat of the eye, is the first and the most important area of the visual neu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bf9ee7164d2b51d4efbc6b07dfcbf859
https://pubmed.ncbi.nlm.nih.gov/32738265
https://pubmed.ncbi.nlm.nih.gov/32738265
Publikováno v:
International Journal of Neural Systems. 31:2050073
In contrast to the previous artificial neural networks (ANNs), spiking neural networks (SNNs) work based on temporal coding approaches. In the proposed SNN, the number of neurons, neuron models, encoding method, and learning algorithm design are desc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::13bc714f645a49bc9038a2121da55d90
https://doi.org/10.1142/s0129065720500732
https://doi.org/10.1142/s0129065720500732
Autor:
Jean-Jacques Bellanger, Farzaneh Shayegh, Karim Ansari-Asl, S. Sadri, Rasoul Amirfattahi, Lotfi Senhadji
Publikováno v:
Network: Computation in Neural Systems. 25:139-167
In this paper, a model-based approach is presented to quantify the effective synchrony between hippocampal areas from depth-EEG signals. This approach is based on the parameter identification procedure of a realistic Multi-Source/Multi-Channel (MSMC)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::92fcb6ccbb8f2f2e963bf6204c78143e
https://doi.org/10.3109/0954898x.2014.940409
https://doi.org/10.3109/0954898x.2014.940409
Publikováno v:
Computer Methods and Programs in Biomedicine. 113:323-337
In order to predict epileptic seizures many precursory features, extracted from the EEG signals, have been introduced. Before checking out the performance of features in detection of pre-seizure state, it is required to see whether these features are
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dfcc9e9c961cd9dc7333c64ffbe3ed3c
https://doi.org/10.1016/j.cmpb.2013.08.014
https://doi.org/10.1016/j.cmpb.2013.08.014
Publikováno v:
Journal of Computational Neuroscience. 36:39-53
By assuming the brain as a multi-stable system, different scenarios have been introduced for transition from normal to epileptic state. But, the path through which this transition occurs is under debate. In this paper a stochastic model for seizure g
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::515d87b177ef7d4dbe3a13274263b4b6
https://doi.org/10.1007/s10827-013-0457-5
https://doi.org/10.1007/s10827-013-0457-5