A hierarchical model of goal directed navigation selects trajectories in a visual environment

Erdem, Uğur M., Milford, Michael, & Hasselmo, Michael E. (2015) A hierarchical model of goal directed navigation selects trajectories in a visual environment. Neurobiology of Learning and Memory, 117, pp. 109-121.

View at publisher

Abstract

We have developed a Hierarchical Look-Ahead Trajectory Model (HiLAM) that incorporates the firing pattern of medial entorhinal grid cells in a planning circuit that includes interactions with hippocampus and prefrontal cortex. We show the model’s flexibility in representing large real world environments using odometry information obtained from challenging video sequences. We acquire the visual data from a camera mounted on a small tele-operated vehicle. The camera has a panoramic field of view with its focal point approximately 5 cm above the ground level, similar to what would be expected from a rat’s point of view. Using established algorithms for calculating perceptual speed from the apparent rate of visual change over time, we generate raw dead reckoning information which loses spatial fidelity over time due to error accumulation. We rectify the loss of fidelity by exploiting the loop-closure detection ability of a biologically inspired, robot navigation model termed RatSLAM. The rectified motion information serves as a velocity input to the HiLAM to encode the environment in the form of grid cell and place cell maps. Finally, we show goal directed path planning results of HiLAM in two different environments, an indoor square maze used in rodent experiments and an outdoor arena more than two orders of magnitude larger than the indoor maze. Together these results bridge for the first time the gap between higher fidelity bio-inspired navigation models (HiLAM) and more abstracted but highly functional bio-inspired robotic mapping systems (RatSLAM), and move from simulated environments into real-world studies in rodent-sized arenas and beyond.

Impact and interest:

0 citations in Scopus
9 citations in Web of Science®
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

36 since deposited on 05 Aug 2014
29 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 74664
Item Type: Journal Article
Refereed: Yes
Keywords: Navigation, Path planning, Grid cell, Place cell, Hippocampus, SLAM, RatSLAM
DOI: 10.1016/j.nlm.2014.07.003
ISSN: 1074-7427
Divisions: Current > QUT Faculties and Divisions > Science & Engineering Faculty
Funding:
Copyright Owner: Copyright 2014 Elsevier Inc.
Copyright Statement: This is the author’s version of a work that was accepted for publication in Neurobiology of Learning and Memory. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Neurobiology of Learning and Memory, Volume 117, January 2015, DOI: 10.1016/j.nlm.2014.07.003
Deposited On: 05 Aug 2014 00:45
Last Modified: 23 Jun 2017 15:21

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page