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Estimation of the synaptic input under a single cell model

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dc.contributor.author Hajimoradkhani, Mohammad Mahdi
dc.date.accessioned 2021-11-18T10:16:29Z
dc.date.available 2021-11-18T10:16:29Z
dc.date.issued 2021
dc.identifier.uri http://hdl.handle.net/10230/49011
dc.description Treball de fi de grau en Bioinformàtica. Curs 2020-2021
dc.description Tutor: Antoni Guillamon Grabolosa
dc.description.abstract In this project, a series of simulations are prepared using the Morris-Lecar model, and a set of mathematical theories and transformations are applied which lead to the result that a neuronal dynamical system’s electrical behaviour is equivalent when electrical inputs vary in short and long time intervals; as well as the result that the total synaptic input can be accurately estimated. However, the current solutions to the open problem of estimating the excitatory and inhibitory synaptic inputs, which are components of the total synaptic input, remain inaccurate.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.rights This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 license
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other Treball de fi de grau – Curs 2020-2021
dc.title Estimation of the synaptic input under a single cell model
dc.type info:eu-repo/semantics/bachelorThesis
dc.subject.keyword Computational neuroscience
dc.subject.keyword Dynamical systems
dc.subject.keyword Estimation of synaptic input
dc.subject.keyword Single cell neuron model
dc.rights.accessRights info:eu-repo/semantics/openAccess


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