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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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Related in: MedlinePlus

Estimating initial pose using reverse replay of past self-motion estimates.(A) Uncertainty (blue particle cloud) during real-time localization or during reverse replay, showing the estimated pose (cyan arrow) and the true pose (red arrow) during a two-minute period initially disoriented. (B) Ip (median, IQR) and V(θ) are shown during real-time localization (black) or during reverse replay (red), and the corresponding Ip distributions at 30 s.
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pcbi-1003927-g005: Estimating initial pose using reverse replay of past self-motion estimates.(A) Uncertainty (blue particle cloud) during real-time localization or during reverse replay, showing the estimated pose (cyan arrow) and the true pose (red arrow) during a two-minute period initially disoriented. (B) Ip (median, IQR) and V(θ) are shown during real-time localization (black) or during reverse replay (red), and the corresponding Ip distributions at 30 s.

Mentions: A final prediction was that the true pose at the beginning of a disoriented trial can be recovered by replaying self-motion estimates in reverse. In real time, the initial pose estimate was uniformly distributed over the arena in all directions. Following a period of localization, the final pose estimate was treated as the initial pose estimate of the same trajectory replayed in reverse, in an ‘offline’ manner. Fig. 5 shows that following reverse replay, pose estimates were substantially improved from real-time pose estimates during initial localization, which were optimal at the time. Assuming that a sequence of self-motion estimates can be stored and retrieved later, this simple strategy can significantly improve a past pose estimate retrospectively. Alternatively, an ‘online’ backward inference procedure can also be used to achieve retrospective localization for a chosen time, without storing self-motion estimates (Fig. S5, Text S1 – Modelling and Analysis, Text S1 - Supporting Results). The ability to accurately recover the starting pose implies that homing is possible using only idiothetic sensory cues, even when initially disoriented. In principle, direct homing can occur after an indefinite period of time, since both current pose and initial pose (‘home’) can be determined.


Estimating location without external cues.

Cheung A - PLoS Comput. Biol. (2014)

Estimating initial pose using reverse replay of past self-motion estimates.(A) Uncertainty (blue particle cloud) during real-time localization or during reverse replay, showing the estimated pose (cyan arrow) and the true pose (red arrow) during a two-minute period initially disoriented. (B) Ip (median, IQR) and V(θ) are shown during real-time localization (black) or during reverse replay (red), and the corresponding Ip distributions at 30 s.
© Copyright Policy
Related In: Results  -  Collection

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

pcbi-1003927-g005: Estimating initial pose using reverse replay of past self-motion estimates.(A) Uncertainty (blue particle cloud) during real-time localization or during reverse replay, showing the estimated pose (cyan arrow) and the true pose (red arrow) during a two-minute period initially disoriented. (B) Ip (median, IQR) and V(θ) are shown during real-time localization (black) or during reverse replay (red), and the corresponding Ip distributions at 30 s.
Mentions: A final prediction was that the true pose at the beginning of a disoriented trial can be recovered by replaying self-motion estimates in reverse. In real time, the initial pose estimate was uniformly distributed over the arena in all directions. Following a period of localization, the final pose estimate was treated as the initial pose estimate of the same trajectory replayed in reverse, in an ‘offline’ manner. Fig. 5 shows that following reverse replay, pose estimates were substantially improved from real-time pose estimates during initial localization, which were optimal at the time. Assuming that a sequence of self-motion estimates can be stored and retrieved later, this simple strategy can significantly improve a past pose estimate retrospectively. Alternatively, an ‘online’ backward inference procedure can also be used to achieve retrospective localization for a chosen time, without storing self-motion estimates (Fig. S5, Text S1 – Modelling and Analysis, Text S1 - Supporting Results). The ability to accurately recover the starting pose implies that homing is possible using only idiothetic sensory cues, even when initially disoriented. In principle, direct homing can occur after an indefinite period of time, since both current pose and initial pose (‘home’) can be determined.

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