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The spatial responses of many of the cells recorded in all layers of rodent medial entorhinal cortex (mEC) show a triangular grid pattern, and once established might be based in part on path-integration mechanisms. Grid axes are tightly…

Neurons and Cognition · Quantitative Biology 2012-03-20 Bailu Si , Emilio Kropff , Alessandro Treves

Fourier-like summation of several grid cell modules with different spatial frequencies in the medial entorhinal cortex (MEC) has long been proposed to form the contours of place firing fields. Recent experiments largely, but not completely,…

Neurons and Cognition · Quantitative Biology 2019-10-15 Taiping Zeng , XiaoLi Li , Bailu Si

Encoding the distance between locations in space is essential for accurate navigation. Grid cells, a functional class of neurons in medial entorhinal cortex, are believed to support this computation. However, existing theories of how…

Neurons and Cognition · Quantitative Biology 2025-11-12 Pritipriya Dasbehera , Akshunna S. Dogra , William T. Redman

The hippocampus has been associated with both spatial cognition and episodic memory formation, but integrating these functions into a unified framework remains challenging. Here, we demonstrate that forming discrete memories of visual…

Artificial Intelligence · Computer Science 2024-05-24 Adrian F. Amil , Ismael T. Freire , Paul F. M. J. Verschure

The entorhinal-hippocampal circuit plays a critical role in higher brain functions, especially spatial cognition. Grid cells in the medial entorhinal cortex (MEC) periodically fire with different grid spacing and orientation, which makes a…

Neurons and Cognition · Quantitative Biology 2019-10-11 Taiping Zeng , XiaoLi Li , Bailu Si

Grid cells play a principal role in enabling mammalian cognitive representations of ambient environments. The key property of these cells -- the regular arrangement of their firing fields -- is commonly viewed as means for establishing…

Neurons and Cognition · Quantitative Biology 2022-08-30 Yuri Dabaghian

The hippocampal formation is thought to learn spatial maps of environments, and in many models this learning process consists of forming a sensory association for each location in the environment. This is inefficient, akin to learning a…

Artificial Intelligence · Computer Science 2021-07-02 Marcus Lewis

Understanding spatial location and relationships is a fundamental capability for modern artificial intelligence systems. Insights from human spatial cognition provide valuable guidance in this domain. Neuroscientific discoveries have…

Neural and Evolutionary Computing · Computer Science 2024-09-17 Boyang Li , Yulin Wu , Nuoxian Huang , Wenjia Zhang

Hippocampal neurons track positions of self, others, and gaze direction. However, it is unclear how their respective neural codes differ enough to avoid confusion while allowing for abstraction. We recorded from populations of hippocampal…

Place cells in the rat hippocampus play a key role in creating the animal's internal representation of the world. During active navigation, these cells spike only in discrete locations, together encoding a map of the environment.…

Neurons and Cognition · Quantitative Biology 2016-03-22 Yuri Dabaghian

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

The human brain possesses the extraordinary capability to contextualize the information it receives from our environment. The entorhinal-hippocampal plays a critical role in this function, as it is deeply engaged in memory processing and…

Artificial Intelligence · Computer Science 2023-07-06 Paul Stoewer , Achim Schilling , Andreas Maier , Patrick Krauss

It is widely accepted that the hippocampal place cells' spiking activity produces a cognitive map of space. However, many details of this representation's physiological mechanism remain unknown. For example, it is believed that the place…

Neurons and Cognition · Quantitative Biology 2015-09-08 A. Babichev , D. Ji , F. Memoli , Y. Dabaghian

How does the mind organize thoughts? The hippocampal-entorhinal complex is thought to support domain-general representation and processing of structural knowledge of arbitrary state, feature and concept spaces. In particular, it enables the…

Artificial Intelligence · Computer Science 2022-02-24 Paul Stoewer , Christian Schlieker , Achim Schilling , Claus Metzner , Andreas Maier , Patrick Krauss

Can neural networks learn goal-directed behaviour using similar strategies to the brain, by combining the relationships between the current state of the organism and the consequences of future actions? Recent work has shown that recurrent…

Neurons and Cognition · Quantitative Biology 2021-01-21 Justin Jude , Matthias H. Hennig

Many recent models study the downstream projection from grid cells to place cells, while recent data has pointed out the importance of the feedback projection. We thus asked how grid cells are affected by the nature of the input from the…

Neurons and Cognition · Quantitative Biology 2015-07-16 Yedidyah Dordek , Ron Meir , Dori Derdikman

Many learning problems involve symmetries, and while invariance can be built into neural architectures, it can also emerge implicitly when training on group-structured data. We study this phenomenon in classical Hopfield networks and show…

Machine Learning · Computer Science 2026-01-21 Michael Murray , Tenzin Chan , Kedar Karhadker , Christopher J. Hillar

Hippocampal place cells can encode spatial locations of an animal in physical or task-relevant spaces. We simulated place cell populations that encoded either Euclidean- or graph-based positions of a rat navigating to goal nodes in a maze…

Neurons and Cognition · Quantitative Biology 2022-11-17 Thibault Niederhauser , Adam Lester , Nina Miolane , Khanh Dao Duc , Manu S. Madhav

The brain encodes spacial structure through a combinatorial code of neural activity. Experiments suggest such codes correspond to convex areas of the subject's environment. We present an intrinsic condition that implies a neural code may…

Combinatorics · Mathematics 2016-10-20 Robert Williams

This paper deals with differentiable dynamical models congruent with neural process theories that cast brain function as the hierarchical refinement of an internal generative model explaining observations. Our work extends existing…

Machine Learning · Computer Science 2021-12-10 André Ofner , Sebastian Stober