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Predicting direction detection thresholds for arbitrary translational acceleration profiles in the horizontal plane
In previous research, direction detection thresholds have been measured and successfully modeled by exposing participants to sinusoidal acceleration profiles of different durations. In this paper, we present measurements that reveal differences in thresholds depending not only on the duration of the...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Springer-Verlag
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3035781/ https://www.ncbi.nlm.nih.gov/pubmed/21234751 http://dx.doi.org/10.1007/s00221-010-2523-9 |
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author | Soyka, Florian Robuffo Giordano, Paolo Beykirch, Karl Bülthoff, Heinrich H. |
author_facet | Soyka, Florian Robuffo Giordano, Paolo Beykirch, Karl Bülthoff, Heinrich H. |
author_sort | Soyka, Florian |
collection | PubMed |
description | In previous research, direction detection thresholds have been measured and successfully modeled by exposing participants to sinusoidal acceleration profiles of different durations. In this paper, we present measurements that reveal differences in thresholds depending not only on the duration of the profile, but also on the actual time course of the acceleration. The measurements are further explained by a model based on a transfer function, which is able to predict direction detection thresholds for all types of acceleration profiles. In order to quantify a participant’s ability to detect the direction of motion in the horizontal plane, a four-alternative forced-choice task was implemented. Three types of acceleration profiles (sinusoidal, trapezoidal and triangular) were tested for three different durations (1.5, 2.36 and 5.86 s). To the best of our knowledge, this is the first study which varies both quantities (profile and duration) in a systematic way within a single experiment. The lowest thresholds were found for trapezoidal profiles and the highest for triangular profiles. Simulations for frequencies lower than the ones actually measured predict a change from this behavior: Sinusoidal profiles are predicted to yield the highest thresholds at low frequencies. This qualitative prediction is only possible with a model that is able to predict thresholds for different types of acceleration profiles. Our modeling approach represents an important advancement, because it allows for a more general and accurate description of perceptual thresholds for simple and complex translational motions. |
format | Text |
id | pubmed-3035781 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Springer-Verlag |
record_format | MEDLINE/PubMed |
spelling | pubmed-30357812011-03-16 Predicting direction detection thresholds for arbitrary translational acceleration profiles in the horizontal plane Soyka, Florian Robuffo Giordano, Paolo Beykirch, Karl Bülthoff, Heinrich H. Exp Brain Res Research Article In previous research, direction detection thresholds have been measured and successfully modeled by exposing participants to sinusoidal acceleration profiles of different durations. In this paper, we present measurements that reveal differences in thresholds depending not only on the duration of the profile, but also on the actual time course of the acceleration. The measurements are further explained by a model based on a transfer function, which is able to predict direction detection thresholds for all types of acceleration profiles. In order to quantify a participant’s ability to detect the direction of motion in the horizontal plane, a four-alternative forced-choice task was implemented. Three types of acceleration profiles (sinusoidal, trapezoidal and triangular) were tested for three different durations (1.5, 2.36 and 5.86 s). To the best of our knowledge, this is the first study which varies both quantities (profile and duration) in a systematic way within a single experiment. The lowest thresholds were found for trapezoidal profiles and the highest for triangular profiles. Simulations for frequencies lower than the ones actually measured predict a change from this behavior: Sinusoidal profiles are predicted to yield the highest thresholds at low frequencies. This qualitative prediction is only possible with a model that is able to predict thresholds for different types of acceleration profiles. Our modeling approach represents an important advancement, because it allows for a more general and accurate description of perceptual thresholds for simple and complex translational motions. Springer-Verlag 2011-01-14 2011 /pmc/articles/PMC3035781/ /pubmed/21234751 http://dx.doi.org/10.1007/s00221-010-2523-9 Text en © The Author(s) 2011 https://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. |
spellingShingle | Research Article Soyka, Florian Robuffo Giordano, Paolo Beykirch, Karl Bülthoff, Heinrich H. Predicting direction detection thresholds for arbitrary translational acceleration profiles in the horizontal plane |
title | Predicting direction detection thresholds for arbitrary translational acceleration profiles in the horizontal plane |
title_full | Predicting direction detection thresholds for arbitrary translational acceleration profiles in the horizontal plane |
title_fullStr | Predicting direction detection thresholds for arbitrary translational acceleration profiles in the horizontal plane |
title_full_unstemmed | Predicting direction detection thresholds for arbitrary translational acceleration profiles in the horizontal plane |
title_short | Predicting direction detection thresholds for arbitrary translational acceleration profiles in the horizontal plane |
title_sort | predicting direction detection thresholds for arbitrary translational acceleration profiles in the horizontal plane |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3035781/ https://www.ncbi.nlm.nih.gov/pubmed/21234751 http://dx.doi.org/10.1007/s00221-010-2523-9 |
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