dc.contributor.author | Koutsou, Achilleas | en |
dc.contributor.author | Christodoulou, Chris C. | en |
dc.contributor.author | Bugmann, G. | en |
dc.contributor.author | Kanev, J. | en |
dc.creator | Koutsou, Achilleas | en |
dc.creator | Christodoulou, Chris C. | en |
dc.creator | Bugmann, G. | en |
dc.creator | Kanev, J. | en |
dc.date.accessioned | 2019-11-13T10:40:47Z | |
dc.date.available | 2019-11-13T10:40:47Z | |
dc.date.issued | 2012 | |
dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/54297 | |
dc.description.abstract | In this letter, we aim to measure the relative contribution of coincidence detection and temporal integration to the firing of spikes of a simple neuron model. To this end, we develop a method to infer the degree of synchrony in an ensemble of neurons whose firing drives a single postsynaptic cell. This is accomplished by studying the effects of synchronous inputs on the membrane potential slope of the neuron and estimating the degree of response-relevant input synchrony, which determines the neuron's operational mode. The measure is calculated using the normalized slope of the membrane potential prior to the spikes fired by a neuron, and we demonstrate that it is able to distinguish between the two operational modes. By applying this measure to the membrane potential time course of a leaky integrate-and-fire neuron with the partial somatic reset mechanism, which has been shown to be the most likely candidate to reflect the mechanism used in the brain for reproducing the highly irregular firing at high rates, we show that the partial reset model operates as a temporal integrator of incoming excitatory postsynaptic potentials and that coincidence detection is not necessary for producing such high irregular firing. © 2012 Massachusetts Institute of Technology. | en |
dc.source | Neural computation | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84871902872&doi=10.1162%2fNECO_a_00323&partnerID=40&md5=11c3578fbe2bd82f58635456666a71ca | |
dc.subject | article | en |
dc.subject | human | en |
dc.subject | Humans | en |
dc.subject | Time Factors | en |
dc.subject | biological model | en |
dc.subject | Animals | en |
dc.subject | animal | en |
dc.subject | physiology | en |
dc.subject | time | en |
dc.subject | computer simulation | en |
dc.subject | Neurons | en |
dc.subject | artificial neural network | en |
dc.subject | Neural Networks (Computer) | en |
dc.subject | nerve cell | en |
dc.subject | Membrane Potentials | en |
dc.subject | mathematics | en |
dc.subject | Models, Neurological | en |
dc.subject | membrane potential | en |
dc.title | Distinguishing the causes of firing with themembrane potential slope | en |
dc.type | info:eu-repo/semantics/article | |
dc.identifier.doi | 10.1162/NECO_a_00323 | |
dc.description.volume | 24 | |
dc.description.issue | 9 | |
dc.description.startingpage | 2318 | |
dc.description.endingpage | 2345 | |
dc.author.faculty | 002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences | |
dc.author.department | Τμήμα Πληροφορικής / Department of Computer Science | |
dc.type.uhtype | Article | en |
dc.description.notes | <p>Cited By :3</p> | en |
dc.source.abbreviation | Neural Comp. | en |
dc.contributor.orcid | Christodoulou, Chris C. [0000-0001-9398-5256] | |
dc.gnosis.orcid | 0000-0001-9398-5256 | |