RI: SMALL: Collaborative Research: Investigations of the Role of Dorsal versus Ventral Place and Grid Cells during Multi-Scale Spatial Navigation in Rats and Robots

点击翻译按钮获取中文摘要

Spatial navigation is a complex cognitive process that relies on robust and adaptive mechanisms to relate current and future spatial positions to specific locations in the environment. The goal of this project is to provide a better understanding of spatial navigation by integrating information obtained from experimental studies in rats, computational models, and experiments on robots that will test new hypotheses on how these mechanisms work. The hippocampus and medial entorhinal cortex (MEC) are major brain regions involved in mammalian spatial navigation. While the role of place cells in the hippocampus has been extensively studied, there are still many open questions on the functional role of MEC grid cells and their interaction with the hippocampal place cells. Of interest to this proposal is the recent finding that grid cells are organized in an orderly fashion along the dorso-ventral axis of the MEC, with dorsal grids being much more tightly spaced than ventral ones. The investigators hypothesize that this multiscale organization endows the navigation system with a coding mechanism that will inherently achieve robustness with respect to external perturbations such as obstacles or unexpected changes in visual cues. In order to evaluate this hypothesis the investigators will develop computational and robotic models while systematically performing experiments in rat in which the dorsal or ventral portions of MEC or hippocampus will be inactivated. They will introduce new types of mazes in which the spatial frequency of the trajectories will be controlled. This work will contribute to better spatial navigation in robotics by: (1) providing a robotic testbed to evaluate hypotheses on the role of the entorhinal cortex and (2) providing biologically plausible models for robust spatial navigation under uncertain and dynamic environments. These models will suggest alternatives to classical probabilistic methods commonly used in robot Simultaneous Localization And Mapping paradigms. This work will also contribute to studies of spatial navigation in rats by: (1) showing the usefulness of robots in providing a physical testbed beyond pure computational modeling, and (2) exploiting the shorter cycle of robot experimentation to produce maze configurations that are optimal for testing specific hypotheses in rat experiments.