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Visual exploration of large multidimensional datasets has seen tremendous progress in recent years, allowing users to express rich data queries that produce informative visual summaries, all in real time. Techniques based on data cubes are…

In this lecture I will present some models of neural networks that have been developed in the recent years. The aim is to construct neural networks which work as associative memories. Different attractors of the network will be identified…

Condensed Matter · Physics 2008-02-03 Giorgio Parisi

Visual attention is a mechanism closely intertwined with vision and memory. Top-down information influences visual processing through attention. We designed a neural network model inspired by aspects of human visual attention. This model…

Computer Vision and Pattern Recognition · Computer Science 2025-06-09 Ruoyang Hu , Robert A. Jacobs

Reverse engineering the brain is proving difficult, perhaps impossible. While many believe that this is just a matter of time and effort, a different approach might help. Here, we describe a very simple idea which explains the power of the…

Neural and Evolutionary Computing · Computer Science 2015-12-17 Fergal Byrne

In this paper, we review recent approaches for explaining concepts in neural networks. Concepts can act as a natural link between learning and reasoning: once the concepts are identified that a neural learning system uses, one can integrate…

Artificial Intelligence · Computer Science 2024-05-06 Jae Hee Lee , Sergio Lanza , Stefan Wermter

In this paper, we present a neural network system related to about memory and recall that consists of one neuron group (the "cue ball") and a one-layer neural net (the "recall net"). This system realizes the bidirectional memorization…

Neural and Evolutionary Computing · Computer Science 2022-10-11 Hiroshi Inazawa

Neuronal circuits of the cerebral cortex are the structural basis of mammalian cognition. The same qualitative components and connectivity motifs are repeated across functionally specialized cortical areas and mammalian species, suggesting…

Neurons and Cognition · Quantitative Biology 2025-07-04 Arno Granier , Katharina A Wilmes , Mihai A Petrovici , Walter Senn

Structured internal representations (cognitive maps) shape cognition, from imagining the future and counterfactual past, to transferring knowledge to new settings. Our understanding of how such representations are formed and maintained in…

Neurons and Cognition · Quantitative Biology 2024-10-07 Matthew M Nour , Yunzhe Liu , Mohamady El-Gaby , Robert A McCutcheon , Raymond J Dolan

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

We consider a living organism as an observer of the evolution of its environment recording sensory information about the state space X of the environment in real time. Sensory information is sampled and then processed on two levels. On the…

Artificial Intelligence · Computer Science 2010-03-22 Dan Guralnik

This paper describes some biologically-inspired processes that could be used to build the sort of networks that we associate with the human brain. New to this paper, a 'refined' neuron will be proposed. This is a group of neurons that by…

Artificial Intelligence · Computer Science 2018-02-06 Kieran Greer

Mammalian brains span about 4 orders of magnitude in cortical volume and have to operate in different environments that require diverse behavioral skills. Despite these geometric and behavioral diversities, the examination of cerebral…

Neurons and Cognition · Quantitative Biology 2014-05-19 Jan Karbowski

Over the last few decades, a lot of progress has been made in understanding different aspects of the brain's ability to form abstract representations, but a specific mechanism for how they are created and used remains to emerge. Here, we…

Neurons and Cognition · Quantitative Biology 2020-03-02 Prashant C. Raju

At the intersection of computation and cognitive science, graph theory is utilized as a formalized description of complex relationships and structures. Traditional graph models are often static, lacking dynamic and autonomous behavioral…

Neurons and Cognition · Quantitative Biology 2024-06-11 Hui Wei , Chenyue Feng , Jianning Zhang

Memories in the brain are separated in two categories: short-term and long-term memories. Long-term memories remain for a lifetime, while short-term ones exist from a few milliseconds to a few minutes. Within short-term memory studies,…

Neural and Evolutionary Computing · Computer Science 2014-11-26 Julien Hubert , Takashi Ikegami

When someone mentions the name of a known person we immediately recall her face and possibly many other traits. This is because we possess the so-called associative memory, that is the ability to correlate different memories to the same…

Neurons and Cognition · Quantitative Biology 2010-08-26 Yuriy V. Pershin , Massimiliano Di Ventra

Neural codes allow the brain to represent, process, and store information about the world. Combinatorial codes, comprised of binary patterns of neural activity, encode information via the collective behavior of populations of neurons. A…

Neurons and Cognition · Quantitative Biology 2016-12-22 Carina Curto , Elizabeth Gross , Jack Jeffries , Katherine Morrison , Mohamed Omar , Zvi Rosen , Anne Shiu , Nora Youngs

Cognition is supported by neurophysiological processes that occur both in local anatomical neighborhoods and in distributed large-scale circuits. Recent evidence from network control theory suggests that white matter pathways linking…

Neurons and Cognition · Quantitative Biology 2016-06-30 John D. Medaglia , Shi Gu , Fabio Pasqualetti , Rebecca L. Ashare , Caryn Lerman , Joseph Kable , Danielle S. Bassett

There are a number of ways to procedurally generate interesting three-dimensional shapes, and a method where a cellular neural network is combined with a mesh growth algorithm is presented here. The aim is to create a shape from a genetic…

Neural and Evolutionary Computing · Computer Science 2016-03-30 Hugo Martay

This paper describes a process for combining patterns and features, to guide a search process and make predictions. It is based on the functionality that a human brain might have, which is a highly distributed network of simple neuronal…

Artificial Intelligence · Computer Science 2021-01-05 Kieran Greer