Theoretical and Computational Neuroscience<\/p>\n
Author:<\/strong> Leandro Ezequiel Fernandez | Email:<\/strong> leandrofernandez671@gmail.com<\/p>\n Leandro E. Fernandez 1\u00b0<\/sup>, Agust\u00edn Carpio 1\u00b0<\/sup>, Jiamin Wu 2\u00b0<\/sup>, Marcelo Rozemberg 2\u00b0<\/sup>, Gabriel B. Mindlin 1\u00b0<\/sup><\/p>\n 1\u00b0 Dpto. de F\u00edsica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina & Instituto de F\u00edsica Interdisciplinaria y Aplicada, INFINA-CONICET, Buenos Aires, Argentina. The comprehension of neural networks emerges as a significant scientific endeavor, encompassing a diverse range of methodological approaches across various disciplines. At the heart of these networks lies a multitude of neuron models, reflecting the field’s inherent diversity.<\/p>\n In line with this pursuit, a recent significant advancement involves the creation of a novel ultra-compact electronic circuit that emulates the leaky integrate-and-fire dynamics. This novel development aligns harmoniously with the broader objective of understanding neural networks. By employing mathematical modeling to replicate experimental setups, we establish a structured pathway to comprehensively analyze and dissect the intricate system dynamics. This analytical framework not only reveals subtle insights beyond empirical observations but also provides a deeper grasp of the underlying principles at play.<\/p>\n Our mathematical model, rooted in the Morris-Lecar framework, adeptly reproduces experimental outcomes in a qualitative manner. Furthermore, it unfolds a diverse spectrum of dynamic behaviors, encompassing phenomena like bursting, single spiking, and periodic spiking. Beyond capturing the essence of neural behavior, this electronic neuron model emerges as a versatile tool for further exploration and enriched understanding, bridging the gap between theoretical insights and practical application.<\/p>\n","protected":false},"excerpt":{"rendered":" Author: Fernandez Leandro Ezequiel | email: leandrofernandez671@gmail.com | Theoretical and Computational Neuroscience<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[34],"tags":[28],"class_list":["post-2014","post","type-post","status-publish","format-standard","hentry","category-session-2","tag-theoretical-and-computational-neuroscience"],"_links":{"self":[{"href":"https:\/\/csan2023.saneurociencias.org.ar\/index.php\/wp-json\/wp\/v2\/posts\/2014","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/csan2023.saneurociencias.org.ar\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/csan2023.saneurociencias.org.ar\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/csan2023.saneurociencias.org.ar\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/csan2023.saneurociencias.org.ar\/index.php\/wp-json\/wp\/v2\/comments?post=2014"}],"version-history":[{"count":1,"href":"https:\/\/csan2023.saneurociencias.org.ar\/index.php\/wp-json\/wp\/v2\/posts\/2014\/revisions"}],"predecessor-version":[{"id":2185,"href":"https:\/\/csan2023.saneurociencias.org.ar\/index.php\/wp-json\/wp\/v2\/posts\/2014\/revisions\/2185"}],"wp:attachment":[{"href":"https:\/\/csan2023.saneurociencias.org.ar\/index.php\/wp-json\/wp\/v2\/media?parent=2014"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/csan2023.saneurociencias.org.ar\/index.php\/wp-json\/wp\/v2\/categories?post=2014"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/csan2023.saneurociencias.org.ar\/index.php\/wp-json\/wp\/v2\/tags?post=2014"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
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\n2\u00b0 Universit\u00e9 Paris-Saclay, CNRS Laboratoire de Physique des Solides, 91405, Orsay, France.<\/p>\n