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It is now widely accepted that one of the roles of the hippocampus is to maintain episodic spatial representations, while parallel striatal pathways contribute to both declarative and procedural value computations by encoding different…

Neurons and Cognition · Quantitative Biology 2014-12-10 Fabian Chersi

Current theories suggest that adaptive decision-making necessitates the interaction between multiple decision-making systems. The computational definitions of different models of decision-making suggest interactions with task demands and…

Neurons and Cognition · Quantitative Biology 2023-07-28 Ugurcan Mugan , Seiichiro Amemiya , Paul S. Regier , A. David Redish

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

In the mammalian brain, newly acquired memories depend on the hippocampus for maintenance and recall, but over time the neocortex takes over these functions, rendering memories hippocampus-independent. The process responsible for this…

Neurons and Cognition · Quantitative Biology 2021-07-02 Peter Helfer , Thomas R. Shultz

Autonomous navigation in complex and partially observable environments remains a central challenge in robotics. Several bio-inspired models of mapping and navigation based on place cells in the mammalian hippocampus have been proposed. This…

Neural and Evolutionary Computing · Computer Science 2026-01-08 Bekarys Dukenbaev , Andrew Gerstenslager , Alexander Johnson , Ali A. Minai

The brain has a great capacity for computation and efficient resolution of complex problems, far surpassing modern computers. Neuromorphic engineering seeks to mimic the basic principles of the brain to develop systems capable of achieving…

In the mammalian brain newly acquired memories depend on the hippocampus for maintenance and recall, but over time these functions are taken over by the neocortex through a process called systems consolidation. However, reactivation of a…

Neurons and Cognition · Quantitative Biology 2019-03-29 Peter Helfer , Thomas R. Shultz

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

The discovery of place cells and other spatially modulated neurons in the hippocampal complex of rodents has been crucial to elucidating the neural basis of spatial cognition. More recently, the replay of neural sequences encoding…

Neurons and Cognition · Quantitative Biology 2023-01-18 Adedapo Alabi , Dieter Vanderelst , Ali Minai

Hippocampal place and time cells encode spatial and temporal aspects of experience. Both have the same neural substrate, but have been modeled as having different functions and mechanistic origins, place cells as continuous attractors, and…

Neurons and Cognition · Quantitative Biology 2026-04-02 Qiaorong S. Yu , Zhaoze Wang , Vijay Balasubramanian

Hippocampal reverse replay is thought to contribute to learning, and particularly reinforcement learning, in animals. We present a computational model of learning in the hippocampus that builds on a previous model of the…

Neurons and Cognition · Quantitative Biology 2021-02-25 Matthew T. Whelan , Tony J. Prescott , Eleni Vasilaki

The spiking activity of the hippocampal place cells plays a key role in producing and sustaining an internalized representation of the ambient space---a cognitive map. These cells do not only exhibit location-specific spiking during…

Neurons and Cognition · Quantitative Biology 2018-11-05 Andrey Babichev , Dmitriy Morozov , Yuri Dabaghian

In this paper we explain the strikingly regular activity of the 'grid' cells in rodent dorsal medial entorhinal cortex (dMEC) and the spatially localized activity of the hippocampal place cells in CA3 and CA1 by assuming that the…

Neurons and Cognition · Quantitative Biology 2008-04-22 Andras Lorincz , Melinda Kiszlinger , Gabor Szirtes

Topological data analyses are rapidly turning into key tools for quantifying large volumes of neurobiological data, e.g., for organizing the spiking outputs of large neuronal ensembles and thus gaining insights into the information produced…

Neurons and Cognition · Quantitative Biology 2019-09-18 Yuri Dabaghian

The spiking activity of principal cells in mammalian hippocampus encodes an internalized neuronal representation of the ambient space---a cognitive map. Once learned, such a map enables the animal to navigate a given environment for a long…

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

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

Spatial navigation in mammals is based on building a mental representation of their environment---a cognitive map. However, both the nature of this cognitive map and its underpinning in neural structures and activity remains vague. A key…

Neurons and Cognition · Quantitative Biology 2016-03-22 A. Babichev , S. Cheng , Yu. Dabaghian

Memory is inherently entangled with prediction and planning. Flexible behavior in biological and artificial agents depends on the interplay of learning from the past and predicting the future in ever-changing environments. This chapter…

Artificial Intelligence · Computer Science 2024-02-21 Ida Momennejad

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

State of the art deep reinforcement learning algorithms take many millions of interactions to attain human-level performance. Humans, on the other hand, can very quickly exploit highly rewarding nuances of an environment upon first…

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