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Sequence memory is an essential attribute of natural and artificial intelligence that enables agents to encode, store, and retrieve complex sequences of stimuli and actions. Computational models of sequence memory have been proposed where…

Neural and Evolutionary Computing · Computer Science 2023-11-06 Hamza Tahir Chaudhry , Jacob A. Zavatone-Veth , Dmitry Krotov , Cengiz Pehlevan

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

The standard model of memory consolidation foresees that memories are initially recorded in the hippocampus, while features that capture higher-level generalisations of data are created in the cortex, where they are stored for a possibly…

Neurons and Cognition · Quantitative Biology 2017-06-20 Alessandro Fontana

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

During sleep, the hippocampus recapitulates neuronal patterns corresponding to behavioral trajectories during previous experiences. This hippocampal replay supports the formation of long-term memories. Yet, whether replay originates within…

Neurons and Cognition · Quantitative Biology 2022-05-06 Adrien Peyrache

Grid cells in the medial entorhinal cortex (MEC) of the mammalian brain exhibit a strikingly regular hexagonal firing field over space. These cells are learned after birth and are thought to support spatial navigation but also more abstract…

Neurons and Cognition · Quantitative Biology 2024-10-07 Mufeng Tang , Helen Barron , Rafal Bogacz

During sleep and awake rest, the hippocampus replays sequences of place cells that have been activated during prior experiences. These have been interpreted as a memory consolidation process, but recent results suggest a possible…

Artificial Intelligence · Computer Science 2018-08-14 Lise Aubin , Mehdi Khamassi , Benoît Girard

The standard Hopfield model for associative neural networks accounts for biological Hebbian learning and acts as the harmonic oscillator for pattern recognition, however its maximal storage capacity is $\alpha \sim 0.14$, far from the…

Neural and Evolutionary Computing · Computer Science 2018-10-30 Alberto Fachechi , Elena Agliari , Adriano Barra

We solve the dynamics of Hopfield-type neural networks which store sequences of patterns, close to saturation. The asymmetry of the interaction matrix in such models leads to violation of detailed balance, ruling out an equilibrium…

Disordered Systems and Neural Networks · Physics 2015-06-25 A. During , A. C. C. Coolen , D. Sherrington

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

Fascinating and puzzling phenomena, such as landmark vector cells, splitter cells, and event-specific representations to name a few, are regularly discovered in the hippocampus. Without a unifying principle that can explain these divergent…

Neurons and Cognition · Quantitative Biology 2022-12-06 Rajkumar Vasudeva Raju , J. Swaroop Guntupalli , Guangyao Zhou , Miguel Lázaro-Gredilla , Dileep George

Deep learning has seen remarkable developments over the last years, many of them inspired by neuroscience. However, the main learning mechanism behind these advances - error backpropagation - appears to be at odds with neurobiology. Here,…

Neurons and Cognition · Quantitative Biology 2018-10-29 João Sacramento , Rui Ponte Costa , Yoshua Bengio , Walter Senn

Recent works have highlighted the need for a new dynamical paradigm in the modeling of brain function and evolution. Specifically, these models should incorporate non-constant and asymmetric synaptic weights $T_{ij}$ in the neuron-neuron…

Neurons and Cognition · Quantitative Biology 2025-11-03 Franco Cardin , Alberto Lovison , Amos Maritan , Aram Megighian

Learning features invariant to arbitrary transformations in the data is a requirement for any recognition system, biological or artificial. It is now widely accepted that simple cells in the primary visual cortex respond to features while…

Neural and Evolutionary Computing · Computer Science 2020-12-14 Jayanta K. Dutta , Bonny Banerjee

We analyze a variant of the Hopfield model that incorporates an unlearning mechanism based on spin correlations in the high-temperature regime. In the large system limit where extensively many patterns are stored, we employ the replica…

Disordered Systems and Neural Networks · Physics 2026-02-10 Shuta Takeuchi , Takashi Takahashi , Yoshiyuki Kabashima

In this work, we present a mathematical model for cyclic and sequential patterns of brain activity, combining heteroclinic dynamics with discrete neural-field models. We first show that spatial-discrete neural-field equations with…

Dynamical Systems · Mathematics 2026-05-05 M Virginia Bolelli , Luca Greco , Dario Prandi

Place cells in the hippocampus are active when an animal visits a certain location (referred to as a place field) within an environment. Grid cells in the medial entorhinal cortex (MEC) respond at multiple locations, with firing fields that…

Neurons and Cognition · Quantitative Biology 2018-05-17 David M. Schwartz , O. Ozan Koyluoglu

Recent experimental observations have shown that the reactivation of hippocampal place cells (PC) during sleep or immobility depicts trajectories that can go around barriers and can flexibly adapt to a changing maze layout. Such…

Neurons and Cognition · Quantitative Biology 2022-09-20 Yuanxiang Gao

We present a hidden Markov model that describes variation in an animal's position associated with varying levels of activity in action potential spike trains of individual place cell neurons. The model incorporates a coarse-graining of…

Applications · Statistics 2014-12-22 Marc Box , Matt W. Jones , Nick Whiteley

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