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Percolation theory concerns the emergence of connected clusters that percolate through a networked system. Previous studies ignored the effect that a node outside the percolating cluster may actively induce its inside neighbours to exit the…

Statistical Mechanics · Physics 2013-09-12 Jin-Hua Zhao , Hai-Jun Zhou , Yang-Yu Liu

We generalize the theory of k-core percolation on complex networks to k-core percolation on multiplex networks, where k=(k_a, k_b, ...). Multiplex networks can be defined as networks with a set of vertices but different types of edges, a,…

Disordered Systems and Neural Networks · Physics 2014-10-08 N. Azimi-Tafreshi , J. Gomez-Gardenes , S. N. Dorogovtsev

The $k$-core percolation is a fundamental structural transition in complex networks. Through the analysis of the size jump behaviors of $k$-core in the evolution process of networks, we confirm that $k$-core percolation is continuous phase…

Statistical Mechanics · Physics 2017-10-10 Yong Zhu , Xiaosong Chen

We analyse perception and memory, using mathematical models for knowledge graphs and tensors, to gain insights into the corresponding functionalities of the human mind. Our discussion is based on the concept of propositional sentences…

Artificial Intelligence · Computer Science 2020-02-11 Volker Tresp , Sahand Sharifzadeh , Dario Konopatzki , Yunpu Ma

Spatiotemporal flows of neural activity, such as traveling waves, have been observed throughout the brain since the earliest recordings; yet there is still little consensus on their functional role. Recent experiments and models have linked…

Neurons and Cognition · Quantitative Biology 2026-02-03 T. Anderson Keller , Lyle Muller , Terrence J. Sejnowski , Max Welling

Consciousness spans macroscopic experience and microscopic neuronal activity, yet linking these scales remains challenging. Prevailing theories, such as Integrated Information Theory, focus on a single scale, overlooking how causal power…

Neurons and Cognition · Quantitative Biology 2025-09-16 Zhipeng Wang , Yingqi Rong , Kaiwei Liu , Mingzhe Yang , Jiang Zhang , Jing He

Concept learning is a fundamental aspect of human cognition and plays a critical role in mental processes such as categorization, reasoning, memory, and decision-making. Researchers across various disciplines have shown consistent interest…

Artificial Intelligence · Computer Science 2024-01-15 Yuwei Wang , Yi Zeng

Brain function emerges from coordinated activity across anatomically connected regions, where structural connectivity (SC) -- the network of white matter pathways - provides the physical substrate for functional connectivity (FC) -- the…

Neurons and Cognition · Quantitative Biology 2025-07-09 Sam Frank Kelemen , Joaquín Gõni , Sérgio Pequito , Arian Ashourvan

Decoding sensory experiences from neural activity to reconstruct human-perceived visual stimuli and semantic content remains a challenge in neuroscience and artificial intelligence. Despite notable progress in current brain decoding models,…

Neurons and Cognition · Quantitative Biology 2025-10-13 Feihan Feng , Jingxin Nie

A cognitive architecture aimed at cumulative learning must provide the necessary information and control structures to allow agents to learn incrementally and autonomously from their experience. This involves managing an agent's goals as…

Artificial Intelligence · Computer Science 2021-12-06 Hugo Latapie , Ozkan Kilic , Kristinn R. Thorisson , Pei Wang , Patrick Hammer

Functional theories of consciousness, based on emergence of conscious experiences from the execution of a particular function by an insentient brain, face the hard problem of consciousness of explaining why the insentient brain should…

Neurons and Cognition · Quantitative Biology 2025-04-29 Danko D. Georgiev

The Tensor Brain (TB) has been introduced as a computational model for perception and memory. This paper provides an overview of the TB model, incorporating recent developments and insights into its functionality. The TB is composed of two…

Artificial Intelligence · Computer Science 2024-12-31 Volker Tresp , Hang Li

Machine learning models can inherit hidden behavioral traits through innocuous public interfaces, a phenomenon known as subliminal learning. Here we extend this framework to quantum models and study two distillation pathways: an auxiliary…

Quantum Physics · Physics 2026-05-29 Shi-Xin Zhang , Yu-Qin Chen

We develop the theory of the k-core (bootstrap) percolation on uncorrelated random networks with arbitrary degree distributions. We show that the k-core percolation is an unusual, hybrid phase transition with a jump emergence of the k-core…

Statistical Mechanics · Physics 2009-11-11 A. V. Goltsev , S. N. Dorogovtsev , J. F. F. Mendes

The origin and development of consciousness is poorly understood. Although it is clearly a naturalistic phenomenon evolved through Darwinian evolution, explaining it in terms of physicochemical, neural, or symbolic mechanisms remains…

Neurons and Cognition · Quantitative Biology 2014-10-20 J. H. van Hateren

Brain perceptual rivalry, exemplified by auditory stream segregation of competing tones (A_, B__, ABA_), serves as a core mechanism of brain perception formation. While increasingly recognized as determining by neural connections rather…

Neurons and Cognition · Quantitative Biology 2025-03-10 Yuxuan Wu , Jinling Gao , Xiaona Fang , Jin Wang

Understanding the human brain remains the Holy Grail in biomedical science, and arguably in all of the sciences. Our brains represent the most complex systems in the world (and some contend the universe) comprising nearly one hundred…

Quantitative Methods · Quantitative Biology 2016-02-03 Sean L. Simpson , Paul J. Laurienti

The brain's structural connectome supports signal propagation between neuronal elements, shaping diverse coactivation patterns that can be captured as functional connectivity. While the link between structure and function remains an ongoing…

Neurons and Cognition · Quantitative Biology 2022-07-11 Yaqian Yang , Zhiming Zheng , Longzhao Liu , Hongwei Zheng , Yi Zhen , Yi Zheng , Xin Wang , Shaoting Tang

The secrecy problem in the state-dependent cognitive interference channel is considered in this paper. In our model, there are a primary and a secondary (cognitive) transmitter-receiver pairs, in which the cognitive transmitter has the…

Information Theory · Computer Science 2016-05-19 Hamid G. Bafghi , Babak Seyfe , Mahtab Mirmohseni , Mohammad Reza Aref

Emerging evidence shows that the modular organization of the human brain allows for better and efficient cognitive performance. Many of these cognitive functions are very fast and occur in subsecond time scale such as the visual object…

Neurons and Cognition · Quantitative Biology 2018-08-01 J. Rizkallah , P. Benquet , A. Kabbara , O. Dufor , F. Wendling , M. Hassan