Path integration in large-scale space and with novel geometries: Comparing vector addition and encoding-error models
Jazyk angličtina Země Spojené státy americké Médium electronic-ecollection
Typ dokumentu časopisecké články, Research Support, U.S. Gov't, Non-P.H.S.
PubMed
32379824
PubMed Central
PMC7244182
DOI
10.1371/journal.pcbi.1007489
PII: PCOMPBIOL-D-19-01761
Knihovny.cz E-zdroje
- MeSH
- chůze fyziologie MeSH
- dospělí MeSH
- lidé MeSH
- orientace fyziologie MeSH
- podněty MeSH
- propriocepce fyziologie MeSH
- prostorová navigace fyziologie MeSH
- teoretické modely MeSH
- vnímání prostoru fyziologie MeSH
- výpočetní biologie metody MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- Research Support, U.S. Gov't, Non-P.H.S. MeSH
Path integration is thought to rely on vestibular and proprioceptive cues yet most studies in humans involve primarily visual input, providing limited insight into their respective contributions. We developed a paradigm involving walking in an omnidirectional treadmill in which participants were guided on two sides of a triangle and then found their back way to origin. In Experiment 1, we tested a range of different triangle types while keeping the distance of the unguided side constant to determine the influence of spatial geometry. Participants overshot the angle they needed to turn and undershot the distance they needed to walk, with no consistent effect of triangle type. In Experiment 2, we manipulated distance while keeping angle constant to determine how path integration operated over both shorter and longer distances. Participants underestimated the distance they needed to walk to the origin, with error increasing as a function of the walked distance. To attempt to account for our findings, we developed configural-based computational models involving vector addition, the second of which included terms for the influence of past trials on the current one. We compared against a previously developed configural model of human path integration, the Encoding-Error model. We found that the vector addition models captured the tendency of participants to under-encode guided sides of the triangles and an influence of past trials on current trials. Together, our findings expand our understanding of body-based contributions to human path integration, further suggesting the value of vector addition models in understanding these important components of human navigation.
3rd Faculty of Medicine Charles University Ruská Prague Czech Republic
Center for Neuroscience University of California Davis Davis California United States of America
Cognitive Science Program University of Arizona Tucson Arizona United States of America
Evelyn McKnight Brain Institute University of Arizona Tucson Arizona United States of America
Psychology Department University of Arizona Tucson Arizona United States of America
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