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The ability to effectively control brain dynamics holds great promise for the enhancement of cognitive function in humans, and the betterment of their quality of life. Yet, successfully controlling dynamics in neural systems is challenging,…

Quantitative Methods · Quantitative Biology 2018-08-29 Evelyn Tang , Danielle S. Bassett

The question of controllability of natural and man-made network systems has recently received considerable attention. In the context of the human brain, the study of controllability may not only shed light into the organization and function…

Optimization and Control · Mathematics 2021-02-10 Tommaso Menara , Shi Gu , Danielle S. Bassett , Fabio Pasqualetti

Inspired by the hierarchical cognitive architecture and the perception-action model (PAM), we propose that the internal status acts as a kind of common-coding representation which affects, mediates and even regulates the sensorimotor…

Robotics · Computer Science 2016-05-12 Junpei Zhong , Rony Novianto , Mingjun Dai , Xinzheng Zhang , Angelo Cangelosi

In this paper we introduce a knowledge engine, which learns and shares knowledge representations, for robots to carry out a variety of tasks. Building such an engine brings with it the challenge of dealing with multiple data modalities…

Artificial Intelligence · Computer Science 2015-04-14 Ashutosh Saxena , Ashesh Jain , Ozan Sener , Aditya Jami , Dipendra K. Misra , Hema S. Koppula

This study investigates how adequate coordination among the different cognitive processes of a humanoid robot can be developed through end-to-end learning of direct perception of visuomotor stream. We propose a deep dynamic neural network…

Artificial Intelligence · Computer Science 2017-06-09 Jungsik Hwang , Jun Tani

Living systems process sensory data to facilitate adaptive behaviour. A given sensor can be stimulated as the result of internally driven activity, or by purely external (environmental) sources. It is clear that these inputs are processed…

Neural and Evolutionary Computing · Computer Science 2022-05-16 James Garner , Matthew Egbert

Digital life, a form of life generated by computer programs or artificial intelligence systems, it possesses self-awareness, thinking abilities, emotions, and subjective consciousness. Achieving it involves complex neural networks,…

Human-Computer Interaction · Computer Science 2023-10-24 Qikang Zhang

Understanding of the phenomena of vision and thought require clarification of the general mechanism of perception. So far, philosophical inquiries and scientific investigations have not been able to address clearly the mysteries surrounding…

Neurons and Cognition · Quantitative Biology 2019-09-16 Jahan N. Schad

Artificial intelligence research to a great degree focuses on the brain and behaviors that the brain generates. But the brain, an extremely complex structure resulting from millions of years of evolution, can be viewed as a solution to…

Neurons and Cognition · Quantitative Biology 2017-03-07 Thomas E. Portegys

To meet ongoing cognitive demands, the human brain must seamlessly transition from one brain state to another, in the process drawing on different cognitive systems. How does the brain's network of anatomical connections help facilitate…

Neurons and Cognition · Quantitative Biology 2016-09-08 Richard F. Betzel , Shi Gu , John D. Medaglia , Fabio Pasqualetti , Danielle S. Bassett

Learning and interpreting the structure of the environment is an innate feature of biological systems, and is integral to guiding flexible behaviours for evolutionary viability. The concept of a cognitive map has emerged as one of the…

Neurons and Cognition · Quantitative Biology 2022-02-04 James C. R. Whittington , David McCaffary , Jacob J. W. Bakermans , Timothy E. J. Behrens

Brain decoding involves the determination of a subject's cognitive state or an associated stimulus from functional neuroimaging data measuring brain activity. In this setting the cognitive state is typically characterized by an element of a…

Machine Learning · Statistics 2015-04-14 Nicole Croteau , Farouk S. Nathoo , Jiguo Cao , Ryan Budney

Animals achieve sophisticated behavioral control through dynamic coupling of the brain, body, and environment. Accordingly, the co-design approach, in which both the controllers and the physical properties are optimized simultaneously, has…

Neural and Evolutionary Computing · Computer Science 2025-03-10 Hiroki Tomioka , Katsuma Inoue , Yasuo Kuniyoshi , Kohei Nakajima

The standard model of memory consolidation foresees that memories are initially recorded in the hippocampus, while features that capture higher-level generalisations of data are created in the cortex, where they are stored for a possibly…

Neurons and Cognition · Quantitative Biology 2017-06-20 Alessandro Fontana

Information integration from different modalities is an active area of research. Human beings and, in general, biological neural systems are quite adept at using a multitude of signals from different sensory perceptive fields to interact…

Neural and Evolutionary Computing · Computer Science 2021-10-05 Shiv Shankar

Robotic navigation has historically struggled to reconcile reactive, sensor-based control with the decisive capabilities of model-based planners. This duality becomes critical when the absence of a predominant option among goals leads to…

Robotics · Computer Science 2026-02-06 Chuwei Wang , Eduardo Sebastián , Amanda Prorok , Anastasia Bizyaeva

Self-recognition -- the ability to maintain an internal representation of one's own body within the environment -- underpins intelligent, autonomous behavior. As a foundational component of the minimal self, self-recognition provides the…

Animal brains exhibit remarkable efficiency in perception and action, while being robust to both external and internal perturbations. The means by which brains accomplish this remains, for now, poorly understood, hindering our understanding…

Neurons and Cognition · Quantitative Biology 2026-03-11 André Urbano , Pablo Lanillos , Sander Keemink

How does the brain predict physical outcomes while acting in the world? Machine learning world models compress visual input into latent spaces, discarding the spatial structure that characterizes sensory cortex. We propose isomorphic world…

Neurons and Cognition · Quantitative Biology 2026-02-24 Joshua Nunley

The fundamental, powerful process of computation in the brain has been widely misunderstood. The paper [1] associates the general failure to build intelligent thinking machines with current reductionist principles of temporal coding and…

Neural and Evolutionary Computing · Computer Science 2012-10-09 Dorian Aur
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