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Estimating location without external cues.

Cheung A - PLoS Comput. Biol. (2014)

Bottom Line: Surprisingly, localization does not require the sensing of any external cue, including the boundary.Optimal localization performance was found to depend on arena shape, arena size, local and global rotational asymmetry, and the structure of the path taken during localization.Based on these results, experiments are suggested to identify if and where information fusion occurs in the mammalian spatial memory system.

View Article: PubMed Central - PubMed

Affiliation: The University of Queensland, Queensland Brain Institute, Brisbane, Queensland, Australia.

ABSTRACT
The ability to determine one's location is fundamental to spatial navigation. Here, it is shown that localization is theoretically possible without the use of external cues, and without knowledge of initial position or orientation. With only error-prone self-motion estimates as input, a fully disoriented agent can, in principle, determine its location in familiar spaces with 1-fold rotational symmetry. Surprisingly, localization does not require the sensing of any external cue, including the boundary. The combination of self-motion estimates and an internal map of the arena provide enough information for localization. This stands in conflict with the supposition that 2D arenas are analogous to open fields. Using a rodent error model, it is shown that the localization performance which can be achieved is enough to initiate and maintain stable firing patterns like those of grid cells, starting from full disorientation. Successful localization was achieved when the rotational asymmetry was due to the external boundary, an interior barrier or a void space within an arena. Optimal localization performance was found to depend on arena shape, arena size, local and global rotational asymmetry, and the structure of the path taken during localization. Since allothetic cues including visual and boundary contact cues were not present, localization necessarily relied on the fusion of idiothetic self-motion cues and memory of the boundary. Implications for spatial navigation mechanisms are discussed, including possible relationships with place field overdispersion and hippocampal reverse replay. Based on these results, experiments are suggested to identify if and where information fusion occurs in the mammalian spatial memory system.

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Other properties affecting idiothetic localization.(A) Ip (median, IQR) and V(θ) during idiothetic localization (left) by a 7×15 cm elliptic navigating agent (black), during random (blue) or thigmotactic (red) movements in an egg arena. The thigmotactic movement strategy resulted a higher  (right, Wilcoxon test, p = 1.3×10−200) and lower V(θ) (κ-test, p<10−16) at 48 minutes, and faster Ip rise kinetics (random t90 = 13:25; thigmotactic t90 = 2:46). An example trajectory is shown for each movement strategy (grey). See also Video S3. (B) Idiothetic localization following linear arena expansion. Simulated grids partially rescaled with the expansion of the test arena, assuming the standard kite boundary in memory. The optimal scaling factors determined by the normalized firing field are shown together with the true arena scale factor (parentheses). See also Table S1. (C) Median Ip and V(θ) functions (left), and Ip(48) distributions (right) are shown for the four arenas in (B). Ip functions were calculated using the test arena.
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pcbi-1003927-g004: Other properties affecting idiothetic localization.(A) Ip (median, IQR) and V(θ) during idiothetic localization (left) by a 7×15 cm elliptic navigating agent (black), during random (blue) or thigmotactic (red) movements in an egg arena. The thigmotactic movement strategy resulted a higher (right, Wilcoxon test, p = 1.3×10−200) and lower V(θ) (κ-test, p<10−16) at 48 minutes, and faster Ip rise kinetics (random t90 = 13:25; thigmotactic t90 = 2:46). An example trajectory is shown for each movement strategy (grey). See also Video S3. (B) Idiothetic localization following linear arena expansion. Simulated grids partially rescaled with the expansion of the test arena, assuming the standard kite boundary in memory. The optimal scaling factors determined by the normalized firing field are shown together with the true arena scale factor (parentheses). See also Table S1. (C) Median Ip and V(θ) functions (left), and Ip(48) distributions (right) are shown for the four arenas in (B). Ip functions were calculated using the test arena.

Mentions: A third prediction was that the centre of a finite-sized navigating agent need not reach the arena boundary, if it used an internal model of its own perimeter. This was demonstrated using an elliptic agent using both random and thigmotactic (wall following) trajectories (Fig. 4A). Accuracy was significantly improved by using a thigmotactic movement strategy, demonstrating trajectory-dependence of localization performance.


Estimating location without external cues.

Cheung A - PLoS Comput. Biol. (2014)

Other properties affecting idiothetic localization.(A) Ip (median, IQR) and V(θ) during idiothetic localization (left) by a 7×15 cm elliptic navigating agent (black), during random (blue) or thigmotactic (red) movements in an egg arena. The thigmotactic movement strategy resulted a higher  (right, Wilcoxon test, p = 1.3×10−200) and lower V(θ) (κ-test, p<10−16) at 48 minutes, and faster Ip rise kinetics (random t90 = 13:25; thigmotactic t90 = 2:46). An example trajectory is shown for each movement strategy (grey). See also Video S3. (B) Idiothetic localization following linear arena expansion. Simulated grids partially rescaled with the expansion of the test arena, assuming the standard kite boundary in memory. The optimal scaling factors determined by the normalized firing field are shown together with the true arena scale factor (parentheses). See also Table S1. (C) Median Ip and V(θ) functions (left), and Ip(48) distributions (right) are shown for the four arenas in (B). Ip functions were calculated using the test arena.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4214594&req=5

pcbi-1003927-g004: Other properties affecting idiothetic localization.(A) Ip (median, IQR) and V(θ) during idiothetic localization (left) by a 7×15 cm elliptic navigating agent (black), during random (blue) or thigmotactic (red) movements in an egg arena. The thigmotactic movement strategy resulted a higher (right, Wilcoxon test, p = 1.3×10−200) and lower V(θ) (κ-test, p<10−16) at 48 minutes, and faster Ip rise kinetics (random t90 = 13:25; thigmotactic t90 = 2:46). An example trajectory is shown for each movement strategy (grey). See also Video S3. (B) Idiothetic localization following linear arena expansion. Simulated grids partially rescaled with the expansion of the test arena, assuming the standard kite boundary in memory. The optimal scaling factors determined by the normalized firing field are shown together with the true arena scale factor (parentheses). See also Table S1. (C) Median Ip and V(θ) functions (left), and Ip(48) distributions (right) are shown for the four arenas in (B). Ip functions were calculated using the test arena.
Mentions: A third prediction was that the centre of a finite-sized navigating agent need not reach the arena boundary, if it used an internal model of its own perimeter. This was demonstrated using an elliptic agent using both random and thigmotactic (wall following) trajectories (Fig. 4A). Accuracy was significantly improved by using a thigmotactic movement strategy, demonstrating trajectory-dependence of localization performance.

Bottom Line: Surprisingly, localization does not require the sensing of any external cue, including the boundary.Optimal localization performance was found to depend on arena shape, arena size, local and global rotational asymmetry, and the structure of the path taken during localization.Based on these results, experiments are suggested to identify if and where information fusion occurs in the mammalian spatial memory system.

View Article: PubMed Central - PubMed

Affiliation: The University of Queensland, Queensland Brain Institute, Brisbane, Queensland, Australia.

ABSTRACT
The ability to determine one's location is fundamental to spatial navigation. Here, it is shown that localization is theoretically possible without the use of external cues, and without knowledge of initial position or orientation. With only error-prone self-motion estimates as input, a fully disoriented agent can, in principle, determine its location in familiar spaces with 1-fold rotational symmetry. Surprisingly, localization does not require the sensing of any external cue, including the boundary. The combination of self-motion estimates and an internal map of the arena provide enough information for localization. This stands in conflict with the supposition that 2D arenas are analogous to open fields. Using a rodent error model, it is shown that the localization performance which can be achieved is enough to initiate and maintain stable firing patterns like those of grid cells, starting from full disorientation. Successful localization was achieved when the rotational asymmetry was due to the external boundary, an interior barrier or a void space within an arena. Optimal localization performance was found to depend on arena shape, arena size, local and global rotational asymmetry, and the structure of the path taken during localization. Since allothetic cues including visual and boundary contact cues were not present, localization necessarily relied on the fusion of idiothetic self-motion cues and memory of the boundary. Implications for spatial navigation mechanisms are discussed, including possible relationships with place field overdispersion and hippocampal reverse replay. Based on these results, experiments are suggested to identify if and where information fusion occurs in the mammalian spatial memory system.

Show MeSH
Related in: MedlinePlus