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Animal navigation research posits that organisms build and maintain internal spatial representations, or maps, of their environment. We ask if machines -- specifically, artificial intelligence (AI) navigation agents -- also build implicit…

Artificial Intelligence · Computer Science 2023-02-01 Erik Wijmans , Manolis Savva , Irfan Essa , Stefan Lee , Ari S. Morcos , Dhruv Batra

Discussions of the hippocampus often focus on place cells, but many neurons are not place cells in any given environment. Here we describe the collective activity in such mixed populations, treating place and non-place cells on the same…

Neurons and Cognition · Quantitative Biology 2019-01-01 Leenoy Meshulam , Jeffrey L. Gauthier , Carlos D. Brody , David W. Tank , William Bialek

Robotic and animal mapping systems share many challenges and characteristics: they must function in a wide variety of environmental conditions, enable the robot or animal to navigate effectively to find food or shelter, and be…

Robotics · Computer Science 2017-12-25 Litao Yu , Adam Jacobson , Michael Milford

The hippocampus and the striatum support episodic and procedural memory, respectively, and "place" and "response" learning within spatial navigation. Recently this dichotomy has been linked to "model-based" and "model-free" reinforcement…

Neurons and Cognition · Quantitative Biology 2018-02-05 Chersi Fabian , Burgess Neil

A variety of behaviors like spatial navigation or bodily motion can be formulated as graph traversal problems through cognitive maps. We present a neural network model which can solve such tasks and is compatible with a broad range of…

Neural and Evolutionary Computing · Computer Science 2021-10-12 Henry Powell , Mathias Winkel , Alexander V. Hopp , Helmut Linde

Simultaneous localisation and mapping (SLAM) algorithms are commonly used in robotic systems for learning maps of novel environments. Brains also appear to learn maps, but the mechanisms are not known and it is unclear how to infer these…

Robotics · Computer Science 2024-02-02 Kipp Freud , Nathan Lepora , Matt W. Jones , Cian O'Donnell

The hippocampus encodes space through a striking gradient of place field sizes along its dorsal-ventral axis, yet the principles generating this continuous gradient from discrete grid cell inputs remain debated. We propose a unified…

Neurons and Cognition · Quantitative Biology 2025-06-06 Shujun Zhou , Guozhang Chen

Learning and recognition is a fundamental process performed in many robot operations such as mapping and localization. The majority of approaches share some common characteristics, such as attempting to extract salient features, landmarks…

Robotics · Computer Science 2017-07-21 Adam Jacobson , Walter Scheirer , Michael Milford

The grid firing patterns are thought to provide an efficient intrinsic metric capable of supporting universal spatial metric for mammalian spatial navigation in all environments. However, whether spatial representations of grid cells in the…

Neurons and Cognition · Quantitative Biology 2019-10-14 Taiping Zeng , XiaoLi Li , Bailu Si

To solve a navigation task based on experiences, we need a mechanism to associate places with objects and to recall them along the course of action. In a reward-oriented task, if the route to a reward location is simulated in mind after…

Neurons and Cognition · Quantitative Biology 2024-10-28 Hiroki Nakagawa , Katsumi Tateno , Kensuke Takada , Takashi Morie

Animals flexibly change their behavior depending on context. It is reported that the hippocampus is one of the most prominent regions for contextual behaviors, and its sequential activity shows context dependency. However, how such…

Neurons and Cognition · Quantitative Biology 2026-03-19 Yoshiki Ito , Taro Toyoizumi

Efficient path planning and navigation is critical for animals, robotics, logistics and transportation. We study a model in which spatial navigation problems can rapidly be solved in the brain by parallel mental exploration of alternative…

Neurons and Cognition · Quantitative Biology 2012-05-03 Filip Ponulak , John J. Hopfield

The grid cells (GCs) of the medial entorhinal cortex (MEC) and place cells (PCs) of the hippocampus are key elements of the brain network for the metric representation of space. Currently, any of the existing theoretical models can explain…

Neurons and Cognition · Quantitative Biology 2015-07-01 Andrey Stepanyuk

In the past decade, the cell-type specific connectivity and activity of local cortical networks have been characterized experimentally to some detail. In parallel, modeling has been established as a tool to relate network structure to…

Neurons and Cognition · Quantitative Biology 2011-06-29 Tobias C. Potjans , Markus Diesmann

Pyramidal cells that emit spikes when the animal is at specific locations of the environment are known as "place cells": these neurons are thought to provide an internal representation of space via "cognitive maps". Here, we consider the…

Disordered Systems and Neural Networks · Physics 2024-08-27 Martino Salomone Centonze , Alessandro Treves , Elena Agliari , Adriano Barra

Grid cells in the entorhinal cortex of mammalian brains exhibit striking hexagon grid firing patterns in their response maps as the animal (e.g., a rat) navigates in a 2D open environment. In this paper, we study the emergence of the…

Neurons and Cognition · Quantitative Biology 2024-02-21 Dehong Xu , Ruiqi Gao , Wen-Hao Zhang , Xue-Xin Wei , Ying Nian Wu

Memory replay may be key to learning in biological brains, which manage to learn new tasks continually without catastrophically interfering with previous knowledge. On the other hand, artificial neural networks suffer from catastrophic…

Machine Learning · Computer Science 2022-01-06 Haitz Sáez de Ocáriz Borde

The hippocampal-entorhinal complex plays a major role in the organization of memory and thought. The formation of and navigation in cognitive maps of arbitrary mental spaces via place and grid cells can serve as a representation of memories…

Neurons and Cognition · Quantitative Biology 2022-10-31 Paul Stoewer , Achim Schilling , Andreas Maier , Patrick Krauss

A common approach to interpreting spiking activity is based on identifying the firing fields---regions in physical or configuration spaces that elicit responses of neurons. Common examples include hippocampal place cells that fire at…

Neurons and Cognition · Quantitative Biology 2021-08-10 D. Akhtiamov , A. G. Cohn , Y. Dabaghian

Growing neuropsychological and neurophysiological evidence suggests that the visual cortex uses parts-based representations to encode, store and retrieve relevant objects. In such a scheme, objects are represented as a set of spatially…

Neurons and Cognition · Quantitative Biology 2015-03-13 Jenia Jitsev , Christoph von der Malsburg