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A feature of the brains of intelligent animals is the ability to learn to respond to an ensemble of active neuronal inputs with a behaviorally appropriate ensemble of active neuronal outputs. Previously, a hypothesis was proposed on how…

Neurons and Cognition · Quantitative Biology 2025-02-04 Marat M. Rvachev

The predictive processing (PP) hypothesizes that the predictive inference of our sensorimotor system is encoded implicitly in the regularities between perception and action. We propose a neural architecture in which such regularities of…

Robotics · Computer Science 2018-04-12 Junpei Zhong , Angelo Cangelosi , Xinzheng Zhang , Tetsuya Ogata

Existing theoretical universal algorithmic intelligence models are not practically realizable. More pragmatic approach to artificial general intelligence is based on cognitive architectures, which are, however, non-universal in sense that…

Artificial Intelligence · Computer Science 2012-09-20 Alexey Potapov , Sergey Rodionov , Andrew Myasnikov , Galymzhan Begimov

A large repertoire of spatiotemporal activity patterns in the brain is the basis for adaptive behaviour. Understanding the mechanism by which the brain's hundred billion neurons and hundred trillion synapses manage to produce such a range…

Neurons and Cognition · Quantitative Biology 2010-10-14 Dante R. Chialvo

Previous soft tissue manipulation studies assumed that the grasping point was known and the target deformation can be achieved. During the operation, the constraints are supposed to be constant, and there is no obstacles around the soft…

Robotics · Computer Science 2023-12-27 Xian He , Shuai Zhang , Shanlin Yang , Bo Ouyang

Uncovering the fundamental neural correlates of biological intelligence, developing mathematical models, and conducting computational simulations are critical for advancing new paradigms in artificial intelligence (AI). In this study, we…

Neural and Evolutionary Computing · Computer Science 2024-09-05 Jie Su , Fang Cai , Shu-Kuo Zhao , Xin-Yi Wang , Tian-Yi Qian , Da-Hui Wang , Bo Hong

This article questions the widespread assumption that there are brain representations that will always remain unconscious in the sense of being inaccessible to individual awareness under any circumstances. This implies that some part of the…

Neurons and Cognition · Quantitative Biology 2022-02-23 Birgitta Dresp-Langley

In this paper, we are introducing a novel model of artificial intelligence, the functional neural network for modeling of human decision-making processes. This neural network is composed of multiple artificial neurons racing in the network.…

Neural and Evolutionary Computing · Computer Science 2022-12-13 Frederic Jumelle , Kelvin So , Didan Deng

The brain can be considered as a system that dynamically optimizes the structure of anatomical connections based on the efficiency requirements of functional connectivity. To illustrate the power of this principle in organizing the…

Neurons and Cognition · Quantitative Biology 2024-02-07 Carlos Calvo Tapia , Valeriy A. Makarov Slizneva , Cees van Leeuwen

The existence of a universal learning architecture in human cognition is a widely spread conjecture supported by experimental findings from neuroscience. While no low-level implementation can be specified yet, an abstract outline of human…

Machine Learning · Computer Science 2021-12-07 Christos Mavridis , John Baras

Criticality is hypothesized as a physical mechanism underlying efficient transitions between cortical states and remarkable information processing capacities in the brain. While considerable evidence generally supports this hypothesis,…

Neurons and Cognition · Quantitative Biology 2023-06-12 Yang Tian , Zeren Tan , Hedong Hou , Guoqi Li , Aohua Cheng , Yike Qiu , Kangyu Weng , Chun Chen , Pei Sun

Progress has led to a detailed understanding of the neural mechanisms that underlie decision making in primates. However, less is known about why such mechanisms are present in the first place. Theory suggests that primate decision making…

Neurons and Cognition · Quantitative Biology 2026-01-21 Nathan J. Wispinski , Scott A. Stone , Anthony Singhal , Patrick M. Pilarski , Craig S. Chapman

Reinforcement learning defines the problem facing agents that learn to make good decisions through action and observation alone. To be effective problem solvers, such agents must efficiently explore vast worlds, assign credit from delayed…

Machine Learning · Computer Science 2022-03-02 David Abel

Optimal Feedback Control (OFC) provides a theoretical framework for goal-directed movements, where the nervous system adjusts actions based on sensory feedback. In OFC, the central nervous system (CNS) not only reacts to stimuli but…

Neurons and Cognition · Quantitative Biology 2025-11-26 O. White , F. Buisseret , F. Dierick , N. Boulanger

The ability to anticipate others' goals and intentions is at the basis of human-human social interaction. Such ability, largely based on non-verbal communication, is also a key to having natural and pleasant interactions with artificial…

Robotics · Computer Science 2024-08-13 Federico Figari Tomenotti , Nicoletta Noceti

The study of attentional processing in vision has a long and deep history. Recently, several papers have presented insightful perspectives into how the coordination of multiple attentional functions in the brain might occur. These begin…

Artificial Intelligence · Computer Science 2021-01-06 John K. Tsotsos , Omar Abid , Iuliia Kotseruba , Markus D. Solbach

Recently, much progress has been made for self-supervised action recognition. Most existing approaches emphasize the contrastive relations among videos, including appearance and motion consistency. However, two main issues remain for…

Computer Vision and Pattern Recognition · Computer Science 2022-04-28 Guanhong Wang , Keyu Lu , Yang Zhou , Zhanhao He , Gaoang Wang

There is a concerted effort to build domain-general artificial intelligence in the form of universal neural network models with sufficient computational flexibility to solve a wide variety of cognitive tasks but without requiring…

Neural and Evolutionary Computing · Computer Science 2023-03-27 Jascha Achterberg , Danyal Akarca , Moataz Assem , Moritz Heimbach , Duncan E. Astle , John Duncan

Previous studies suggested that lateral interactions of V1 cells are responsible, among other visual effects, of bottom-up visual attention (alternatively named visual salience or saliency). Our objective is to mimic these connections with…

Neurons and Cognition · Quantitative Biology 2019-11-19 David Berga , Xavier Otazu

The rapid aging of societies is intensifying demand for autonomous care robots; however, most existing systems are task-specific and rely on handcrafted preprocessing, limiting their ability to generalize across diverse scenarios. A…

Robotics · Computer Science 2025-10-30 Hayato Idei , Tamon Miyake , Tetsuya Ogata , Yuichi Yamashita