Cargando…
An Inverse-Linear Logistic Model of The Main Sequence
A model of the main sequence is proposed based on the logistic function. The model’s fit to the peak velocity-amplitude relation resembles an S curve, simultaneously allowing control of the curve’s asymptotes at very small and very large amplitudes, as well as its slope over the mid-amplitude range....
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Bern Open Publishing
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7166123/ https://www.ncbi.nlm.nih.gov/pubmed/33828660 http://dx.doi.org/10.16910/jemr.10.3.4 |
_version_ | 1783523509890187264 |
---|---|
author | Duchowski, Andrew T. Krejtz, Krzysztof Biele, Cezary Niedzielska, Anna Kiefer, Peter Giannopoulos, Ioannis Gehrer, Nina Schönenberg, Michael |
author_facet | Duchowski, Andrew T. Krejtz, Krzysztof Biele, Cezary Niedzielska, Anna Kiefer, Peter Giannopoulos, Ioannis Gehrer, Nina Schönenberg, Michael |
author_sort | Duchowski, Andrew T. |
collection | PubMed |
description | A model of the main sequence is proposed based on the logistic function. The model’s fit to the peak velocity-amplitude relation resembles an S curve, simultaneously allowing control of the curve’s asymptotes at very small and very large amplitudes, as well as its slope over the mid-amplitude range. The proposed inverse-linear logistic model is also able to express the linear relation of duration and amplitude. We demonstrate the utility and robustness of the model when fit to aggregate data at the smalland mid-amplitude ranges, namely when fitting microsaccades, saccades, and superposition of both. We are confident the model will suitably extend to the largeamplitude range of eye movements. |
format | Online Article Text |
id | pubmed-7166123 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Bern Open Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-71661232021-04-06 An Inverse-Linear Logistic Model of The Main Sequence Duchowski, Andrew T. Krejtz, Krzysztof Biele, Cezary Niedzielska, Anna Kiefer, Peter Giannopoulos, Ioannis Gehrer, Nina Schönenberg, Michael J Eye Mov Res Article A model of the main sequence is proposed based on the logistic function. The model’s fit to the peak velocity-amplitude relation resembles an S curve, simultaneously allowing control of the curve’s asymptotes at very small and very large amplitudes, as well as its slope over the mid-amplitude range. The proposed inverse-linear logistic model is also able to express the linear relation of duration and amplitude. We demonstrate the utility and robustness of the model when fit to aggregate data at the smalland mid-amplitude ranges, namely when fitting microsaccades, saccades, and superposition of both. We are confident the model will suitably extend to the largeamplitude range of eye movements. Bern Open Publishing 2017-05-29 /pmc/articles/PMC7166123/ /pubmed/33828660 http://dx.doi.org/10.16910/jemr.10.3.4 Text en This work is licensed under a Creative Commons Attribution 4.0 International License, (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Article Duchowski, Andrew T. Krejtz, Krzysztof Biele, Cezary Niedzielska, Anna Kiefer, Peter Giannopoulos, Ioannis Gehrer, Nina Schönenberg, Michael An Inverse-Linear Logistic Model of The Main Sequence |
title | An Inverse-Linear Logistic Model of The Main Sequence |
title_full | An Inverse-Linear Logistic Model of The Main Sequence |
title_fullStr | An Inverse-Linear Logistic Model of The Main Sequence |
title_full_unstemmed | An Inverse-Linear Logistic Model of The Main Sequence |
title_short | An Inverse-Linear Logistic Model of The Main Sequence |
title_sort | inverse-linear logistic model of the main sequence |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7166123/ https://www.ncbi.nlm.nih.gov/pubmed/33828660 http://dx.doi.org/10.16910/jemr.10.3.4 |
work_keys_str_mv | AT duchowskiandrewt aninverselinearlogisticmodelofthemainsequence AT krejtzkrzysztof aninverselinearlogisticmodelofthemainsequence AT bielecezary aninverselinearlogisticmodelofthemainsequence AT niedzielskaanna aninverselinearlogisticmodelofthemainsequence AT kieferpeter aninverselinearlogisticmodelofthemainsequence AT giannopoulosioannis aninverselinearlogisticmodelofthemainsequence AT gehrernina aninverselinearlogisticmodelofthemainsequence AT schonenbergmichael aninverselinearlogisticmodelofthemainsequence AT duchowskiandrewt inverselinearlogisticmodelofthemainsequence AT krejtzkrzysztof inverselinearlogisticmodelofthemainsequence AT bielecezary inverselinearlogisticmodelofthemainsequence AT niedzielskaanna inverselinearlogisticmodelofthemainsequence AT kieferpeter inverselinearlogisticmodelofthemainsequence AT giannopoulosioannis inverselinearlogisticmodelofthemainsequence AT gehrernina inverselinearlogisticmodelofthemainsequence AT schonenbergmichael inverselinearlogisticmodelofthemainsequence |