Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Yael Tugendhaft"'
Autor:
Shiri Hodassman, Yuval Meir, Karin Kisos, Itamar Ben-Noam, Yael Tugendhaft, Amir Goldental, Roni Vardi, Ido Kanter
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-14 (2022)
Abstract Real-time sequence identification is a core use-case of artificial neural networks (ANNs), ranging from recognizing temporal events to identifying verification codes. Existing methods apply recurrent neural networks, which suffer from traini
Externí odkaz:
https://doaj.org/article/4266cd1315b9494db5cfa0b387bde045
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-12 (2022)
Abstract Synaptic plasticity is a long-lasting core hypothesis of brain learning that suggests local adaptation between two connecting neurons and forms the foundation of machine learning. The main complexity of synaptic plasticity is that synapses a
Externí odkaz:
https://doaj.org/article/415b2555da004e2e96a94405fa2f0b0d
Publikováno v:
Physical review. E. 105(1-1)
Refractoriness is a fundamental property of excitable elements, such as neurons, indicating the probability for re-excitation in a given time-lag, and is typically linked to the neuronal hyperpolarization following an evoked spike. Here we measured t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::33209832453385cb0fa21c9bf128532f
https://pubmed.ncbi.nlm.nih.gov/35193251
https://pubmed.ncbi.nlm.nih.gov/35193251
Refractory periods are an unavoidable feature of excitable elements, resulting in necessary time-lags for re-excitation. Herein, we measure neuronal absolute refractory periods (ARPs) in synaptic blocked neuronal cultures. In so doing, we show that t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::41670599b6a2a2f1d3c84772ef8be65e
Autor:
Roni Vardi, Shira Sardi, Shiri Hodassman, Yuval Meir, Yael Tugendhaft, Ido Kanter, Amir Goldental
Publikováno v:
Scientific Reports
Scientific Reports, Vol 10, Iss 1, Pp 1-1 (2020)
Scientific Reports, Vol 10, Iss 1, Pp 1-1 (2020)
Attempting to imitate the brain's functionalities, researchers have bridged between neuroscience and artificial intelligence for decades; however, experimental neuroscience has not directly advanced the field of machine learning (ML). Here, using neu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1bce5b0fbdd4928f536dbd17b4ad9e5e
http://europepmc.org/articles/PMC7271123
http://europepmc.org/articles/PMC7271123
Autor:
Yael Tugendhaft, Shira Sardi, Shiri Hodassman, Amir Goldental, Ido Kanter, Roni Vardi, Yuval Meir
Publikováno v:
Scientific Reports
Scientific Reports, Vol 10, Iss 1, Pp 1-10 (2020)
Scientific Reports, Vol 10, Iss 1, Pp 1-10 (2020)
Attempting to imitate the brain functionalities, researchers have bridged between neuroscience and artificial intelligence for decades; however, experimental neuroscience has not directly advanced the field of machine learning. Here, using neuronal c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::af342a6d1ad44bc21ad19ae1de7f1c1c
http://europepmc.org/articles/PMC7181840
http://europepmc.org/articles/PMC7181840
Publikováno v:
ACS chemical neuroscience. 9(6)
Experimental and theoretical results reveal a new underlying mechanism for fast brain learning process, dendritic learning, as opposed to the misdirected research in neuroscience over decades, which is based solely on slow synaptic plasticity. The pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5b099f34ddaf28f6776c23ff593500b5
https://pubmed.ncbi.nlm.nih.gov/29727167
https://pubmed.ncbi.nlm.nih.gov/29727167