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Cognitive problem-solving benefits from cognitive maps aiding navigation and planning. Previous studies revealed that cognitive maps for physical space navigation involve hippocampal (HC) allocentric codes, while cognitive maps for abstract…

Neurons and Cognition · Quantitative Biology 2024-07-30 Toon Van de Maele , Bart Dhoedt , Tim Verbelen , Giovanni Pezzulo

Hippocampal cognitive map---a neuronal representation of the spatial environment---is broadly discussed in the computational neuroscience literature for decades. More recent studies point out that hippocampus plays a major role in producing…

Neurons and Cognition · Quantitative Biology 2017-10-18 Andrey Babichev , Yuri Dabaghian

A recurrent neural network model storing multiple spatial maps, or ``charts'', is analyzed. A network of this type has been suggested as a model for the origin of place cells in the hippocampus of rodents. The extremely diluted and fully…

Disordered Systems and Neural Networks · Physics 2009-10-31 Francesco P. Battaglia , Alessandro Treves

Semantic representations can be framed as a structured, dynamic knowledge space through which humans navigate to retrieve and manipulate meaning. To investigate how humans traverse this geometry, we introduce a framework that represents…

Computation and Language · Computer Science 2026-04-15 Felipe D. Toro-Hernández , Jesuino Vieira Filho , Rodrigo M. Cabral-Carvalho

Human mobility in cities is shaped not only by visible structures such as highways, rivers, and parks but also by invisible barriers rooted in socioeconomic segregation, uneven access to amenities, and administrative divisions. Yet…

Computers and Society · Computer Science 2025-07-01 Guangyuan Weng , Minsuk Kim , Yong-Yeol Ahn , Esteban Moro

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

This paper investigates the conformal isometry hypothesis as a potential explanation for the hexagonal periodic patterns in grid cell response maps. We posit that grid cell activities form a high-dimensional vector in neural space, encoding…

Neurons and Cognition · Quantitative Biology 2025-02-28 Dehong Xu , Ruiqi Gao , Wen-Hao Zhang , Xue-Xin Wei , Ying Nian Wu

We show that a model of the hippocampus introduced recently by Scarpetta, Zhaoping & Hertz ([2002] Neural Computation 14(10):2371-96), explains the theta phase precession phenomena. In our model, the theta phase precession comes out as a…

Neurons and Cognition · Quantitative Biology 2007-05-23 Silvia Scarpetta , Maria Marinaro

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 in the entorhinal cortex encode the position of an animal in its environment using spatially periodic tuning curves of varying periodicity. Recent experiments established that these cells are functionally organized in discrete…

Neurons and Cognition · Quantitative Biology 2016-01-13 Noga Weiss Mosheiff , Haggai Agmon , Avraham Moriel , Yoram Burak

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 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

Place-cell networks, typically forced to pairwise synaptic interactions, are widely studied as models of cognitive maps: such models, however, share a severely limited storage capacity, scaling linearly with network size and with a very…

Disordered Systems and Neural Networks · Physics 2025-11-24 Adriano Barra , Martino S. Centonze , Michela Marra Solazzo , Daniele Tantari

Place embeddings generated from human mobility trajectories have become a popular method to understand the functionality of places. Place embeddings with high spatial resolution are desirable for many applications, however, downscaling the…

Machine Learning · Computer Science 2020-02-07 Toru Shimizu , Takahiro Yabe , Kota Tsubouchi

Multi-electrode arrays covering several square millimeters of neural tissue provide simultaneous access to population signals such as extracellular potentials and spiking activity of one hundred or more individual neurons. The…

Neurons and Cognition · Quantitative Biology 2024-11-11 Johanna Senk , Espen Hagen , Sacha J. van Albada , Markus Diesmann

To navigate a space, the brain makes an internal representation of the environment using different cells such as place cells, grid cells, head direction cells, border cells, and speed cells. All these cells, along with sensory inputs,…

Robotics · Computer Science 2026-04-17 Hibatallah Meliani , Khadija Slimani , Samira Khoulji

We introduce a new neural architecture and an unsupervised algorithm for learning invariant representations from temporal sequence of images. The system uses two groups of complex cells whose outputs are combined multiplicatively: one that…

Neural and Evolutionary Computing · Computer Science 2010-06-03 Karo Gregor , Yann LeCun

Neural computation is associated with the emergence, reconfiguration and dissolution of cell assemblies in the context of varying oscillatory states. Here, we describe the complex spatio-temporal dynamics of cell assemblies through temporal…

Neurons and Cognition · Quantitative Biology 2020-01-20 Nicola Pedreschi , Christophe Bernard , Wesley Clawson , Pascale Quilichini , Alain Barrat , Demian Battaglia

We present an embedding of stochastic optimal control problems, of the so called path integral form, into reproducing kernel Hilbert spaces. Using consistent, sample based estimates of the embedding leads to a model free, non-parametric…

Machine Learning · Computer Science 2012-08-14 Konrad Rawlik , Marc Toussaint , Sethu Vijayakumar

Many imaging techniques for biological systems -- like fixation of cells coupled with fluorescence microscopy -- provide sharp spatial resolution in reporting locations of individuals at a single moment in time but also destroy the dynamics…

Subcellular Processes · Quantitative Biology 2024-05-15 Christopher E. Miles , Scott A. McKinley , Fangyuan Ding , Richard B. Lehoucq