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Collective rhythmic dynamics from neurons is vital for cognitive functions such as memory formation but how neurons self-organize to produce such activity is not well understood. Attractor-based models have been successfully implemented as…

Neurons and Cognition · Quantitative Biology 2013-03-22 Mark Niedringhaus , Xin Chen , Katherine Conant , Rhonda Dzakpasu

Biocomputing technologies exploit biological communication mechanisms involving cell-cell signal propagation to perform computations. Researchers recently worked toward realising logic gates made by neurons to develop novel devices such as…

Emerging Technologies · Computer Science 2022-09-07 Giulio Basso , Michael Taynnan Barros

Memory information in the brain is commonly believed to be stored in the synapse. However, a recent groundbreaking electrophysiology research has raised the possibility that memory information may actually be stored inside the neuron…

Neurons and Cognition · Quantitative Biology 2021-01-26 James Tee , Desmond P. Taylor

Attractor neural network is an important theoretical scenario for modeling memory function in the hippocampus and in the cortex. In these models, memories are stored in the plastic recurrent connections of neural populations in the form of…

Neurons and Cognition · Quantitative Biology 2016-01-12 Alireza Alemi

The brain as an astonishingly remarkable device has been studied from various angles. It is now well known that neurons are the seat of all activities of the brain function. The dynamical properties pertaining to a single neuron and a…

Neurons and Cognition · Quantitative Biology 2007-05-23 I. Mitra

Autoassociative networks were proposed in the 80's as simplified models of memory function in the brain, using recurrent connectivity with hebbian plasticity to store patterns of neural activity that can be later recalled. This type of…

Disordered Systems and Neural Networks · Physics 2011-11-10 Emilio Kropff , Alessandro Treves

A model of associative memory is studied, which stores and reliably retrieves many more patterns than the number of neurons in the network. We propose a simple duality between this dense associative memory and neural networks commonly used…

Neural and Evolutionary Computing · Computer Science 2017-03-28 Dmitry Krotov , John J Hopfield

Intelligence necessitates memory. Without memory, humans fail to perform various nontrivial tasks such as reading novels, playing games or solving maths. As the ultimate goal of machine learning is to derive intelligent systems that learn…

Machine Learning · Computer Science 2021-07-06 Hung Le

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

The brain can reproduce memories from partial data; this ability is critical for memory recall. The process of memory recall has been studied using auto-associative networks such as the Hopfield model. This kind of model reliably converges…

Neurons and Cognition · Quantitative Biology 2016-05-18 James P. Roach , Leonard M Sander , Michal R. Zochowski

Humans excel at continually acquiring, consolidating, and retaining information from an ever-changing environment, whereas artificial neural networks (ANNs) exhibit catastrophic forgetting. There are considerable differences in the…

Neural and Evolutionary Computing · Computer Science 2023-04-17 Fahad Sarfraz , Elahe Arani , Bahram Zonooz

Modern Hopfield Neural Networks (HNNs), also known as Dense Associative Memories (DAMs), enhance the performance of simple recurrent neural networks by leveraging the nonlinearities in their energy functions. They have broad applications in…

Optics · Physics 2026-01-12 Khalid Musa , Santosh Kumar , Michael Katidis , Yu-Ping Huang

We introduce a novel approach to endowing neural networks with emergent, long-term, large-scale memory. Distinct from strategies that connect neural networks to external memory banks via intricately crafted controllers and hand-designed…

Machine Learning · Computer Science 2020-08-18 Tri Huynh , Michael Maire , Matthew R. Walter

This paper presents a neural network model (associative memory model) for memory and recall of images. In this model, only a single neuron can memorize multi-images and when that neuron is activated, it is possible to recall all the…

Neural and Evolutionary Computing · Computer Science 2025-10-09 Hiroshi Inazawa

The retrieval capabilities of associative neural networks can be impaired by different kinds of noise: the fast noise (which makes neurons more prone to failure), the slow noise (stemming from interference among stored memories), and…

Disordered Systems and Neural Networks · Physics 2020-12-10 Elena Agliari , Giordano De Marzo

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

Biological agents navigate complex environments by combining long-term memory of successful actions with short-term suppression of recently visited locations-a capability that remains difficult to replicate in artificial systems, especially…

In the brain, both neurons and glial cells work in conjunction with each other during information processing. Stimulation of neurons can cause calcium oscillations in astrocytes which in turn can affect neuronal calcium dynamics. The…

Neurons and Cognition · Quantitative Biology 2023-08-16 Bhanu Sharma , Spandan Kumar , Subhendu Ghosh , Vikram Singh

The ability to form memories is a basic feature of learning and accumulating knowledge. But where is memory information stored in the brain? Within the scientific research community, it is generally believed that memory information is…

Neurons and Cognition · Quantitative Biology 2024-03-28 Jie Zhang

Storage and retrieval of data in a computer memory plays a major role in system performance. Traditionally, computer memory organization is static - i.e., they do not change based on the application-specific characteristics in memory access…

Artificial Intelligence · Computer Science 2021-01-11 Prabuddha Chakraborty , Swarup Bhunia
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