Article
Neurosciences
Kotaro Mizuta, Junichi Nakai, Yasunori Hayashi, Masaaki Sato
Summary: The hippocampus stores spatial and non-spatial information through neural maps, with locations associated with salient features being over-represented. Through selective stabilization of salient place cells, the hippocampal maps can be reorganized rapidly by coordination of new place field formation, lateral shifting of existing place fields, and selective stabilization of place fields encoding salient locations.
Article
Computer Science, Information Systems
Ashish Kumar, N. S. Raghava
Summary: In this paper, a lightweight cryptosystem is designed based on lookup table operations, reducing computational overhead and resource requirement. By combining one-dimensional elementary cellular automaton with Henon chaotic map, the designed cryptosystem demonstrates unprecedented results in cryptography.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Behavioral Sciences
Eloy Parra-Barrero, Sandhiya Vijayabaskaran, Eddie Seabrook, Laurenz Wiskott, Sen Cheng
Summary: Spatial navigation has been extensively studied by neuroscientists, who have identified key brain areas and discovered many spatially selective cells. However, there is still a lack of understanding regarding how these pieces fit together to drive behavior, which is partly due to insufficient communication between behavioral and neuroscientific researchers. To address this issue, a taxonomy of navigation processes in mammals is proposed as a common framework for interdisciplinary research in the field. This taxonomy has proven useful in identifying potential problems with experimental approaches, designing targeted experiments, interpreting neural activity, and suggesting new avenues of research.
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
(2023)
Article
Remote Sensing
Pei Dang, Jun Zhu, Saied Pirasteh, Weilian Li, Jigang You, Bingli Xu, Ce Liang
Summary: By applying traditional cellular automata crowd evacuation simulation algorithms to virtual reality scenes through a chain navigation grid, and proposing the vertex raster rendering method to efficiently visualize large-scale crowds, this study improved evacuation simulation efficiency by about 6% and increased the maximum number of people rendering from 2 times to 31 times.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2021)
Article
Computer Science, Information Systems
Reyhaneh Ameri, Mohammad Reza Meybodi
Summary: A blockchain is a distributed general ledger that records cryptographic transactions after authentication using consensus algorithms. AI and blockchain have gained significant attention and growth in recent years, and applying AI to solve blockchain challenges can yield fascinating results. Cognitive blockchain utilizes AI to improve performance and overcome challenges.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Krishna Kumar, Satyabrata Roy, Umashankar Rawat, Astitv Shandilya
Summary: This paper proposes a novel lightweight image encryption technique that combines Second-Order Cellular Automata (SOCA) and a chaotic map. The proposed scheme achieves a high encryption speed and low computational complexity, making it suitable for real-time applications and resource-constrained devices. Extensive experimental results demonstrate its effectiveness and robustness against various attacks.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Barbara Wolnik, Maciej Dziemianczuk, Bernard De Baets
Summary: In this paper, the authors investigate non-uniform elementary cellular automata and their relationship with number conservation. They provide a comprehensive characterization of number-conserving cellular automata on finite grids with both periodic and null boundary conditions. The obtained characterization allows for the enumeration of all number-conserving non-uniform elementary cellular automata, revealing a surprising connection to the Fibonacci sequence.
INFORMATION SCIENCES
(2023)
Article
Neurosciences
Nora A. Herweg, Lukas Kunz, Daniel Schonhaut, Armin Brandt, Paul A. Wanda, Ashwini D. Sharan, Michael R. Sperling, Andreas Schulze-Bonhage, Michael J. Kahana
Summary: Distinct lines of research in both humans and animals have found that the hippocampus plays a specific role in spatial and episodic memory function. Concept cells in the hippocampus and surrounding areas suggest that the medial temporal lobe maps physical and semantic spaces using a similar neural architecture. This study examines the emergence of such maps using recordings from the medial temporal lobe of patients navigating a virtual environment with meaningful landmarks, and finds that the field potentials in the medial temporal lobe contain information to decode the subjects' locations and temporal sequences.
JOURNAL OF NEUROSCIENCE
(2023)
Article
Computer Science, Artificial Intelligence
Jinyue Zhang, Xiaolu Xia, Ruiqi Liu, Nan Li
Summary: The study investigated the impact of immersive augmented reality (IAR) systems on cognitive map development and wayfinding performance. Results showed that IAR technology can effectively help people develop their cognitive maps and improve wayfinding performance with lower workload. Additionally, adding a 3D layout model enhanced the effect of IAR-based navigation systems on cognitive map development.
ADVANCED ENGINEERING INFORMATICS
(2021)
Article
Engineering, Multidisciplinary
Hejie Yu, Naigong Yu
Summary: This article proposes a robot navigation model based on the spatial cognitive mechanism of the hippocampus in the rat brain. The model constructs a cognitive map and achieves goal-oriented navigation by utilizing the dynamic predictive relationship between each location cognitive node. The research approach in this article provides inspiration for a robot navigation method with brain-like cognitive mechanisms.
JOURNAL OF ENGINEERING RESEARCH
(2023)
Review
Neurosciences
Flavio Donato, Anja Xu Schwartzlose, Renan Augusto Viana Mendes
Summary: In mammals, the entorhinal-hippocampal network consists of neurons whose activity is influenced by the animal's position and movements, enabling the creation of an internal cognitive map for navigation and memory encoding. Recent research has started to unravel the ontogeny of circuitry, firing patterns, and computations underlying the representation of space in the mammalian brain.
ANNUAL REVIEW OF NEUROSCIENCE
(2023)
Article
Engineering, Mechanical
C. Correia Ramos, Nada El Bouziani, Mouhaydine Tlemcani, Sara Fernandes
Summary: In this study, deterministic and probabilistic cellular automata are used to study and describe patterns in material blocks, with a focus on fracture-like patterns. The distribution of the internal structure is obtained using probabilistic cellular automata, and different methods of combining these patterns into a final one are discussed. Refinement techniques are introduced to improve the probability distributions and adjust the behavior of the cellular automata rules.
NONLINEAR DYNAMICS
(2023)
Article
Neurosciences
Alejandra Alonso, Levan Bokeria, Jacqueline van der Meij, Anumita Samanta, Ronny Eichler, Ali Lotfi, Patrick Spooner, Irene Navarro Lobato, Lisa Genzel
Summary: The study found that previous knowledge can facilitate the learning of new spatial information, and the buildup of a spatial map depends on the passage of time rather than the frequency of training the animal receives.
Article
Neurosciences
Christina-Anna Vallianatou, Alejandra Alonso, Adrian Zapata Aleman, Lisa Genzel, Federico Stellap
Summary: Shifts in spatial patterns during navigational tasks can track the effects of knowledge accumulation and structured information acquisition. Analysis of mice behavior in a large, modular arena revealed the emergence of a flexible representation of the task and performance improvement mediated by multiple time scales. A mathematical model was used to isolate specific contributions to the final navigational strategy, showing a goal-oriented component strengthening with learning progression and a random walk component influencing choices unrelated to the task.
Article
Mathematics, Applied
Tim Otto Roth
Summary: A new 'micro-historicizing' approach is proposed in this study for describing one-dimensional cellular automata dynamics, involving the concept of temporal sub-attractors to characterize cell activity as an underlying phase space similar to a heat map. The robustness of the sub-phase space can be assessed based on morphological trajectories, with a bifurcation indicating a non-robust automaton configuration. Temporal sub-attractors introduce a biological stress component into physically inspired cellular automata models, potentially useful in biology, material science, and engineering science.
PHYSICA D-NONLINEAR PHENOMENA
(2021)
Article
Mathematics, Applied
Carlos Calvo Tapia, Valeri A. Makarov, Cees van Leeuwen
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2020)
Review
Physics, Multidisciplinary
Alexander N. Gorban, Valery A. Makarov, Ivan Y. Tyukin
Article
Neurosciences
Sergey A. Lobov, Alexey N. Mikhaylov, Maxim Shamshin, Valeri A. Makarov, Victor B. Kazantsev
FRONTIERS IN NEUROSCIENCE
(2020)
Article
Computer Science, Artificial Intelligence
Carlos Calvo Tapia, Jose Antonio Villacorta-Atienza, Sergio Diez-Hermano, Maxim Khoruzhko, Sergey Lobov, Ivan Potapov, Abel Sanchez-Jimenez, Valeri A. Makarov
FRONTIERS IN NEUROROBOTICS
(2020)
Article
Multidisciplinary Sciences
Carlos Calvo Tapia, Ivan Tyukin, Valeri A. Makarov
SCIENTIFIC REPORTS
(2020)
Article
Multidisciplinary Sciences
Jose Antonio Villacorta-Atienza, Carlos Calvo Tapia, Sergio Diez-Hermano, Abel Sanchez-Jimenez, Sergey Lobov, Nadia Krilova, Antonio Murciano, Gabriela E. Lopez-Tolsa, Ricardo Pellon, Valeri A. Makarov
Summary: The human brain processes static and dynamic situations as purely static maps to efficiently deal with time-changing environments. Experimental evidence supports the theory of time compaction as a cognitive strategy adopted by the human brain, with mathematical modeling validating the findings. Men are shown to be more prone to exploiting time compaction as a cognitive basis for survival.
JOURNAL OF ADVANCED RESEARCH
(2021)
Article
Physics, Multidisciplinary
Victor Gallego, David Rios Insua
Summary: This work introduces a framework to enhance the efficiency of Bayesian inference by embedding a Markov chain sampler within a variational posterior approximation, termed as refined variational approximation. The framework's strengths lie in its ease of implementation, automatic tuning of sampler parameters, and faster mixing time through automatic differentiation. Experimental results demonstrate its efficient performance in state-space models, variational encoder, and conditional variational autoencoder.
Article
Chemistry, Analytical
Sergey A. Lobov, Alexey I. Zharinov, Valeri A. Makarov, Victor B. Kazantsev
Summary: The study introduces a spiking neural network capable of generating an internal representation of the external environment and implementing spatial memory, with the network's function explored through its embodiment in a robot moving in an arena with safe and dangerous zones.
Article
Neurosciences
Oscar Herreras, Daniel Torres, Gonzalo Martin-Vazquez, Sara Hernandez-Recio, Victor J. Lopez-Madrona, Nuria Benito, Valeri A. Makarov, Julia Makarova
Summary: Field potentials generated by neuron populations have a multisource origin and exhibit site-dependent blending. When assessing whether waveforms and temporal motifs arise from a single source, it is important to consider the spatial reach and the realistic structure of neuron aggregates.
Review
Mathematical & Computational Biology
Valeri A. Makarov, Sergey A. Lobov, Sergey Shchanikov, Alexey Mikhaylov, Viktor B. Kazantsev
Summary: The design of modern convolutional artificial neural networks (ANNs) imitates the architecture of the visual cortex, while spiking neural networks (SNNs) have the potential for a qualitative leap in cognitive computations. However, the training of SNNs remains challenging, and the concept of a high-dimensional brain provides new insights and possibilities for the development of neural networks.
FRONTIERS IN COMPUTATIONAL NEUROSCIENCE
(2022)
Article
Mathematics
Sergey A. Lobov, Alexey N. Mikhaylov, Ekaterina S. Berdnikova, Valeri A. Makarov, Victor B. Kazantsev
Summary: One challenge in modern neuroscience is creating a brain-on-a-chip, a device that can interact with the environment when integrated into a robot. This study proposes a mathematical model of a modular spiking neural network (SNN) to understand learning mechanisms in this context. The model shows that spike-timing-dependent plasticity, synaptic competition, and neuronal competition are all crucial for successful learning. The proposed solution has been tested in neuronal cultures and demonstrated the ability to establish associations between touch and ultrasonic sensors, allowing the robot to avoid obstacles.
Article
Statistics & Probability
David Banks, Victor Gallego, Roi Naveiro, David Rios Insua
Summary: Adversarial risk analysis is a relatively new area of research that informs decision-making when facing intelligent opponents and uncertain outcomes. It helps analysts maximize their expected utility by solving problems from the perspective of the opponent.
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL STATISTICS
(2022)
