Bayesian priors in estimates of object location in virtual reality
Abstract We investigated the category bias in spatial memory, which reveals the influence of a region (i.e., a spatial category) on memory for specific locations within the region’s bounds. The standard approach to investigating the category bias employs a static dot-in-circle task, in which observe...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Sampaio, Cristina [verfasserIn] Jones, Maria [verfasserIn] Engelbertson, Alexander [verfasserIn] Williams, Michael [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020 |
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| Schlagwörter: |
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| Anmerkung: |
© The Psychonomic Society, Inc. 2020 |
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| Übergeordnetes Werk: |
Enthalten in: Psychonomic bulletin & review - New York, NY : Springer, 1994, 27(2020), 6 vom: 06. Aug., Seite 1309-1316 |
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| Übergeordnetes Werk: |
volume:27 ; year:2020 ; number:6 ; day:06 ; month:08 ; pages:1309-1316 |
| Links: |
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| DOI / URN: |
10.3758/s13423-020-01782-z |
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| Katalog-ID: |
SPR042202051 |
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| 245 | 1 | 0 | |a Bayesian priors in estimates of object location in virtual reality |
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| 520 | |a Abstract We investigated the category bias in spatial memory, which reveals the influence of a region (i.e., a spatial category) on memory for specific locations within the region’s bounds. The standard approach to investigating the category bias employs a static dot-in-circle task, in which observers indicate the location of a single dot from memory after a brief interval. The agreement in the literature is that these location estimates result from Bayesian principles; however, the priors in the dot-in-circle task are geometric prototypes (the central angular value of each quadrant and two-thirds of the radius from the center of the circle to its circumference). These geometric prototypes are not “true” priors in that they are not pre-existing statistical likelihoods of a target’s location before other evidence is considered. In this paper, we tested the category bias with items for which informative priors exist (e.g., a vase, which is expected to be in the center of a table) and found that people favor them over geometric prototypes for estimating angular but not radial target positions. Our work contributes to the literature by showing that localizing common everyday objects in a circular space is not restricted to the use of cues intrinsic to the space. This is important because the majority of the empirical data on the category bias derives from locating targets that have little to no semantic information. | ||
| 650 | 4 | |a Spatial memory |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Category-adjustment model |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Category bias |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Spatial memory bias |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Spatial cognition |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Virtual environment |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Jones, Maria |e verfasserin |4 aut | |
| 700 | 1 | |a Engelbertson, Alexander |e verfasserin |4 aut | |
| 700 | 1 | |a Williams, Michael |e verfasserin |4 aut | |
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10.3758/s13423-020-01782-z doi (DE-627)SPR042202051 (SPR)s13423-020-01782-z-e DE-627 ger DE-627 rakwb eng 610 150 ASE 77.99 bkl Sampaio, Cristina verfasserin aut Bayesian priors in estimates of object location in virtual reality 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Psychonomic Society, Inc. 2020 Abstract We investigated the category bias in spatial memory, which reveals the influence of a region (i.e., a spatial category) on memory for specific locations within the region’s bounds. The standard approach to investigating the category bias employs a static dot-in-circle task, in which observers indicate the location of a single dot from memory after a brief interval. The agreement in the literature is that these location estimates result from Bayesian principles; however, the priors in the dot-in-circle task are geometric prototypes (the central angular value of each quadrant and two-thirds of the radius from the center of the circle to its circumference). These geometric prototypes are not “true” priors in that they are not pre-existing statistical likelihoods of a target’s location before other evidence is considered. In this paper, we tested the category bias with items for which informative priors exist (e.g., a vase, which is expected to be in the center of a table) and found that people favor them over geometric prototypes for estimating angular but not radial target positions. Our work contributes to the literature by showing that localizing common everyday objects in a circular space is not restricted to the use of cues intrinsic to the space. This is important because the majority of the empirical data on the category bias derives from locating targets that have little to no semantic information. Spatial memory (dpeaa)DE-He213 Category-adjustment model (dpeaa)DE-He213 Category bias (dpeaa)DE-He213 Spatial memory bias (dpeaa)DE-He213 Spatial cognition (dpeaa)DE-He213 Virtual environment (dpeaa)DE-He213 Jones, Maria verfasserin aut Engelbertson, Alexander verfasserin aut Williams, Michael verfasserin aut Enthalten in Psychonomic bulletin & review New York, NY : Springer, 1994 27(2020), 6 vom: 06. Aug., Seite 1309-1316 (DE-627)324827121 (DE-600)2031311-1 1531-5320 nnns volume:27 year:2020 number:6 day:06 month:08 pages:1309-1316 https://dx.doi.org/10.3758/s13423-020-01782-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 77.99 ASE AR 27 2020 6 06 08 1309-1316 |
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10.3758/s13423-020-01782-z doi (DE-627)SPR042202051 (SPR)s13423-020-01782-z-e DE-627 ger DE-627 rakwb eng 610 150 ASE 77.99 bkl Sampaio, Cristina verfasserin aut Bayesian priors in estimates of object location in virtual reality 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Psychonomic Society, Inc. 2020 Abstract We investigated the category bias in spatial memory, which reveals the influence of a region (i.e., a spatial category) on memory for specific locations within the region’s bounds. The standard approach to investigating the category bias employs a static dot-in-circle task, in which observers indicate the location of a single dot from memory after a brief interval. The agreement in the literature is that these location estimates result from Bayesian principles; however, the priors in the dot-in-circle task are geometric prototypes (the central angular value of each quadrant and two-thirds of the radius from the center of the circle to its circumference). These geometric prototypes are not “true” priors in that they are not pre-existing statistical likelihoods of a target’s location before other evidence is considered. In this paper, we tested the category bias with items for which informative priors exist (e.g., a vase, which is expected to be in the center of a table) and found that people favor them over geometric prototypes for estimating angular but not radial target positions. Our work contributes to the literature by showing that localizing common everyday objects in a circular space is not restricted to the use of cues intrinsic to the space. This is important because the majority of the empirical data on the category bias derives from locating targets that have little to no semantic information. Spatial memory (dpeaa)DE-He213 Category-adjustment model (dpeaa)DE-He213 Category bias (dpeaa)DE-He213 Spatial memory bias (dpeaa)DE-He213 Spatial cognition (dpeaa)DE-He213 Virtual environment (dpeaa)DE-He213 Jones, Maria verfasserin aut Engelbertson, Alexander verfasserin aut Williams, Michael verfasserin aut Enthalten in Psychonomic bulletin & review New York, NY : Springer, 1994 27(2020), 6 vom: 06. Aug., Seite 1309-1316 (DE-627)324827121 (DE-600)2031311-1 1531-5320 nnns volume:27 year:2020 number:6 day:06 month:08 pages:1309-1316 https://dx.doi.org/10.3758/s13423-020-01782-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 77.99 ASE AR 27 2020 6 06 08 1309-1316 |
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10.3758/s13423-020-01782-z doi (DE-627)SPR042202051 (SPR)s13423-020-01782-z-e DE-627 ger DE-627 rakwb eng 610 150 ASE 77.99 bkl Sampaio, Cristina verfasserin aut Bayesian priors in estimates of object location in virtual reality 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Psychonomic Society, Inc. 2020 Abstract We investigated the category bias in spatial memory, which reveals the influence of a region (i.e., a spatial category) on memory for specific locations within the region’s bounds. The standard approach to investigating the category bias employs a static dot-in-circle task, in which observers indicate the location of a single dot from memory after a brief interval. The agreement in the literature is that these location estimates result from Bayesian principles; however, the priors in the dot-in-circle task are geometric prototypes (the central angular value of each quadrant and two-thirds of the radius from the center of the circle to its circumference). These geometric prototypes are not “true” priors in that they are not pre-existing statistical likelihoods of a target’s location before other evidence is considered. In this paper, we tested the category bias with items for which informative priors exist (e.g., a vase, which is expected to be in the center of a table) and found that people favor them over geometric prototypes for estimating angular but not radial target positions. Our work contributes to the literature by showing that localizing common everyday objects in a circular space is not restricted to the use of cues intrinsic to the space. This is important because the majority of the empirical data on the category bias derives from locating targets that have little to no semantic information. Spatial memory (dpeaa)DE-He213 Category-adjustment model (dpeaa)DE-He213 Category bias (dpeaa)DE-He213 Spatial memory bias (dpeaa)DE-He213 Spatial cognition (dpeaa)DE-He213 Virtual environment (dpeaa)DE-He213 Jones, Maria verfasserin aut Engelbertson, Alexander verfasserin aut Williams, Michael verfasserin aut Enthalten in Psychonomic bulletin & review New York, NY : Springer, 1994 27(2020), 6 vom: 06. Aug., Seite 1309-1316 (DE-627)324827121 (DE-600)2031311-1 1531-5320 nnns volume:27 year:2020 number:6 day:06 month:08 pages:1309-1316 https://dx.doi.org/10.3758/s13423-020-01782-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 77.99 ASE AR 27 2020 6 06 08 1309-1316 |
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10.3758/s13423-020-01782-z doi (DE-627)SPR042202051 (SPR)s13423-020-01782-z-e DE-627 ger DE-627 rakwb eng 610 150 ASE 77.99 bkl Sampaio, Cristina verfasserin aut Bayesian priors in estimates of object location in virtual reality 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Psychonomic Society, Inc. 2020 Abstract We investigated the category bias in spatial memory, which reveals the influence of a region (i.e., a spatial category) on memory for specific locations within the region’s bounds. The standard approach to investigating the category bias employs a static dot-in-circle task, in which observers indicate the location of a single dot from memory after a brief interval. The agreement in the literature is that these location estimates result from Bayesian principles; however, the priors in the dot-in-circle task are geometric prototypes (the central angular value of each quadrant and two-thirds of the radius from the center of the circle to its circumference). These geometric prototypes are not “true” priors in that they are not pre-existing statistical likelihoods of a target’s location before other evidence is considered. In this paper, we tested the category bias with items for which informative priors exist (e.g., a vase, which is expected to be in the center of a table) and found that people favor them over geometric prototypes for estimating angular but not radial target positions. Our work contributes to the literature by showing that localizing common everyday objects in a circular space is not restricted to the use of cues intrinsic to the space. This is important because the majority of the empirical data on the category bias derives from locating targets that have little to no semantic information. Spatial memory (dpeaa)DE-He213 Category-adjustment model (dpeaa)DE-He213 Category bias (dpeaa)DE-He213 Spatial memory bias (dpeaa)DE-He213 Spatial cognition (dpeaa)DE-He213 Virtual environment (dpeaa)DE-He213 Jones, Maria verfasserin aut Engelbertson, Alexander verfasserin aut Williams, Michael verfasserin aut Enthalten in Psychonomic bulletin & review New York, NY : Springer, 1994 27(2020), 6 vom: 06. Aug., Seite 1309-1316 (DE-627)324827121 (DE-600)2031311-1 1531-5320 nnns volume:27 year:2020 number:6 day:06 month:08 pages:1309-1316 https://dx.doi.org/10.3758/s13423-020-01782-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 77.99 ASE AR 27 2020 6 06 08 1309-1316 |
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10.3758/s13423-020-01782-z doi (DE-627)SPR042202051 (SPR)s13423-020-01782-z-e DE-627 ger DE-627 rakwb eng 610 150 ASE 77.99 bkl Sampaio, Cristina verfasserin aut Bayesian priors in estimates of object location in virtual reality 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Psychonomic Society, Inc. 2020 Abstract We investigated the category bias in spatial memory, which reveals the influence of a region (i.e., a spatial category) on memory for specific locations within the region’s bounds. The standard approach to investigating the category bias employs a static dot-in-circle task, in which observers indicate the location of a single dot from memory after a brief interval. The agreement in the literature is that these location estimates result from Bayesian principles; however, the priors in the dot-in-circle task are geometric prototypes (the central angular value of each quadrant and two-thirds of the radius from the center of the circle to its circumference). These geometric prototypes are not “true” priors in that they are not pre-existing statistical likelihoods of a target’s location before other evidence is considered. In this paper, we tested the category bias with items for which informative priors exist (e.g., a vase, which is expected to be in the center of a table) and found that people favor them over geometric prototypes for estimating angular but not radial target positions. Our work contributes to the literature by showing that localizing common everyday objects in a circular space is not restricted to the use of cues intrinsic to the space. This is important because the majority of the empirical data on the category bias derives from locating targets that have little to no semantic information. Spatial memory (dpeaa)DE-He213 Category-adjustment model (dpeaa)DE-He213 Category bias (dpeaa)DE-He213 Spatial memory bias (dpeaa)DE-He213 Spatial cognition (dpeaa)DE-He213 Virtual environment (dpeaa)DE-He213 Jones, Maria verfasserin aut Engelbertson, Alexander verfasserin aut Williams, Michael verfasserin aut Enthalten in Psychonomic bulletin & review New York, NY : Springer, 1994 27(2020), 6 vom: 06. Aug., Seite 1309-1316 (DE-627)324827121 (DE-600)2031311-1 1531-5320 nnns volume:27 year:2020 number:6 day:06 month:08 pages:1309-1316 https://dx.doi.org/10.3758/s13423-020-01782-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 77.99 ASE AR 27 2020 6 06 08 1309-1316 |
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The standard approach to investigating the category bias employs a static dot-in-circle task, in which observers indicate the location of a single dot from memory after a brief interval. The agreement in the literature is that these location estimates result from Bayesian principles; however, the priors in the dot-in-circle task are geometric prototypes (the central angular value of each quadrant and two-thirds of the radius from the center of the circle to its circumference). These geometric prototypes are not “true” priors in that they are not pre-existing statistical likelihoods of a target’s location before other evidence is considered. In this paper, we tested the category bias with items for which informative priors exist (e.g., a vase, which is expected to be in the center of a table) and found that people favor them over geometric prototypes for estimating angular but not radial target positions. Our work contributes to the literature by showing that localizing common everyday objects in a circular space is not restricted to the use of cues intrinsic to the space. 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Sampaio, Cristina |
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Sampaio, Cristina ddc 610 bkl 77.99 misc Spatial memory misc Category-adjustment model misc Category bias misc Spatial memory bias misc Spatial cognition misc Virtual environment Bayesian priors in estimates of object location in virtual reality |
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610 150 ASE 77.99 bkl Bayesian priors in estimates of object location in virtual reality Spatial memory (dpeaa)DE-He213 Category-adjustment model (dpeaa)DE-He213 Category bias (dpeaa)DE-He213 Spatial memory bias (dpeaa)DE-He213 Spatial cognition (dpeaa)DE-He213 Virtual environment (dpeaa)DE-He213 |
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bayesian priors in estimates of object location in virtual reality |
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Bayesian priors in estimates of object location in virtual reality |
| abstract |
Abstract We investigated the category bias in spatial memory, which reveals the influence of a region (i.e., a spatial category) on memory for specific locations within the region’s bounds. The standard approach to investigating the category bias employs a static dot-in-circle task, in which observers indicate the location of a single dot from memory after a brief interval. The agreement in the literature is that these location estimates result from Bayesian principles; however, the priors in the dot-in-circle task are geometric prototypes (the central angular value of each quadrant and two-thirds of the radius from the center of the circle to its circumference). These geometric prototypes are not “true” priors in that they are not pre-existing statistical likelihoods of a target’s location before other evidence is considered. In this paper, we tested the category bias with items for which informative priors exist (e.g., a vase, which is expected to be in the center of a table) and found that people favor them over geometric prototypes for estimating angular but not radial target positions. Our work contributes to the literature by showing that localizing common everyday objects in a circular space is not restricted to the use of cues intrinsic to the space. This is important because the majority of the empirical data on the category bias derives from locating targets that have little to no semantic information. © The Psychonomic Society, Inc. 2020 |
| abstractGer |
Abstract We investigated the category bias in spatial memory, which reveals the influence of a region (i.e., a spatial category) on memory for specific locations within the region’s bounds. The standard approach to investigating the category bias employs a static dot-in-circle task, in which observers indicate the location of a single dot from memory after a brief interval. The agreement in the literature is that these location estimates result from Bayesian principles; however, the priors in the dot-in-circle task are geometric prototypes (the central angular value of each quadrant and two-thirds of the radius from the center of the circle to its circumference). These geometric prototypes are not “true” priors in that they are not pre-existing statistical likelihoods of a target’s location before other evidence is considered. In this paper, we tested the category bias with items for which informative priors exist (e.g., a vase, which is expected to be in the center of a table) and found that people favor them over geometric prototypes for estimating angular but not radial target positions. Our work contributes to the literature by showing that localizing common everyday objects in a circular space is not restricted to the use of cues intrinsic to the space. This is important because the majority of the empirical data on the category bias derives from locating targets that have little to no semantic information. © The Psychonomic Society, Inc. 2020 |
| abstract_unstemmed |
Abstract We investigated the category bias in spatial memory, which reveals the influence of a region (i.e., a spatial category) on memory for specific locations within the region’s bounds. The standard approach to investigating the category bias employs a static dot-in-circle task, in which observers indicate the location of a single dot from memory after a brief interval. The agreement in the literature is that these location estimates result from Bayesian principles; however, the priors in the dot-in-circle task are geometric prototypes (the central angular value of each quadrant and two-thirds of the radius from the center of the circle to its circumference). These geometric prototypes are not “true” priors in that they are not pre-existing statistical likelihoods of a target’s location before other evidence is considered. In this paper, we tested the category bias with items for which informative priors exist (e.g., a vase, which is expected to be in the center of a table) and found that people favor them over geometric prototypes for estimating angular but not radial target positions. Our work contributes to the literature by showing that localizing common everyday objects in a circular space is not restricted to the use of cues intrinsic to the space. This is important because the majority of the empirical data on the category bias derives from locating targets that have little to no semantic information. © The Psychonomic Society, Inc. 2020 |
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| container_issue |
6 |
| title_short |
Bayesian priors in estimates of object location in virtual reality |
| url |
https://dx.doi.org/10.3758/s13423-020-01782-z |
| remote_bool |
true |
| author2 |
Jones, Maria Engelbertson, Alexander Williams, Michael |
| author2Str |
Jones, Maria Engelbertson, Alexander Williams, Michael |
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| doi_str |
10.3758/s13423-020-01782-z |
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2024-07-04T01:14:54.319Z |
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|
| score |
7.40018 |