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Modeling the behavior of coupled networks is challenging due to their intricate dynamics. For example in neuroscience, it is of critical importance to understand the relationship between the functional neural processes and anatomical…

Machine Learning · Computer Science 2021-04-20 Hongyuan You , Sikun Lin , Ambuj K. Singh

Although social neuroscience is concerned with understanding how the brain interacts with its social environment, prevailing research in the field has primarily considered the human brain in isolation, deprived of its rich social context.…

Social and Information Networks · Computer Science 2020-02-13 Elisa C. Baek , Mason A. Porter , Carolyn Parkinson

Humans and many animals show remarkably adaptive behavior and can respond differently to the same input depending on their internal goals. The brain not only represents the intermediate abstractions needed to perform a computation but also…

Machine Learning · Computer Science 2024-07-25 Ali Hummos , Felipe del Río , Brabeeba Mien Wang , Julio Hurtado , Cristian B. Calderon , Guangyu Robert Yang

Higher brain function relies upon the ability to flexibly integrate information across specialized communities of brain regions, however it is unclear how this mechanism manifests over time. In this study, we use time-resolved network…

The network architecture of the human brain has become a feature of increasing interest to the neuroscientific community, largely because of its potential to illuminate human cognition, its variation over development and aging, and its…

Neurons and Cognition · Quantitative Biology 2016-11-07 Richard F. Betzel , Danielle S. Bassett

Computational intelligence is broadly defined as biologically-inspired computing. Usually, inspiration is drawn from neural systems. This article shows how to analyze neural systems using information theory to obtain constraints that help…

Neurons and Cognition · Quantitative Biology 2018-05-11 Michael Wibral , Joseph T. Lizier , Viola Priesemann

Accurate and robust recording and decoding from the central nervous system (CNS) is essential for advances in human-machine interfacing. However, technologies used to directly measure CNS activity are limited by their resolution,…

Neurons and Cognition · Quantitative Biology 2025-09-19 Jaime Ibáñez , Blanka Zicher , Etienne Burdet , Stuart N. Baker , Carsten Mehring , Dario Farina

This paper shows and evaluates a novel approach to integrate a non-invasive Brain-Computer Interface (BCI) with the Robot Operating System (ROS) to mentally drive a telepresence robot. Controlling a mobile device by using human brain…

Robotics · Computer Science 2019-04-08 Gloria Beraldo , Morris Antonello , Andrea Cimolato , Emanuele Menegatti , Luca Tonin

Brain computer interfaces (BCI) enable direct communication with a computer, using neural activity as the control signal. This neural signal is generally chosen from a variety of well-studied electroencephalogram (EEG) signals. For a given…

Machine Learning · Computer Science 2018-06-28 Vernon J. Lawhern , Amelia J. Solon , Nicholas R. Waytowich , Stephen M. Gordon , Chou P. Hung , Brent J. Lance

Over recent decades, neuroimaging tools, particularly electroencephalography (EEG), have revolutionized our understanding of the brain and its functions. EEG is extensively used in traditional brain-computer interface (BCI) systems due to…

Neurons and Cognition · Quantitative Biology 2026-05-12 Zaineb Ajra , Binbin Xu , Gérard Dray , Jacky Montmain , Stéphane Perrey

The Motor Imagery (MI) electroencephalography (EEG) based Brain Computer Interfaces (BCIs) allow the direct communication between humans and machines by exploiting the neural pathways connected to motor imagination. Therefore, these systems…

Signal Processing · Electrical Eng. & Systems 2023-10-26 Aurora Saibene , Silvia Corchs , Mirko Caglioni , Francesca Gasparini

Diverse cognitive processes set different demands on locally segregated and globally integrated brain activity. However, it remains unclear how resting brains configure their functional organization to balance the demands on network…

Neurons and Cognition · Quantitative Biology 2022-04-25 Rong Wang , Mianxin Liu , Xinhong Cheng , Ying Wu , Andrea Hildebrandt , Changsong Zhou

Spiking neural networks (SNNs) are gaining popularity in the computational simulation and artificial intelligence fields owing to their biological plausibility and computational efficiency. This paper explores the historical development of…

Neural and Evolutionary Computing · Computer Science 2024-08-29 Tianyu Zheng , Liyuan Han , Tielin Zhang

Brain-computer interfaces (BCIs) have been gaining momentum in making human-computer interaction more natural, especially for people with neuro-muscular disabilities. Among the existing solutions the systems relying on electroencephalograms…

This article proposes a novel framework that utilizes an over-the-air Brain-Computer Interface (BCI) to learn Metaverse users' expectations. By interpreting users' brain activities, our framework can optimize physical resources and enhance…

Human-Computer Interaction · Computer Science 2024-10-10 Nguyen Quang Hieu , Dinh Thai Hoang , Diep N. Nguyen , Van-Dinh Nguyen , Yong Xiao , Eryk Dutkiewicz

Informatics studies all aspects of the structure of natural and artificial information systems. Theoretical and abstract approaches to information have made great advances, but human information processing is still unmatched in many areas,…

Artificial Intelligence · Computer Science 2021-01-12 Włodzisław Duch

The brain is a highly complex organ consisting of a myriad of subsystems that flexibly interact and adapt over time and context to enable perception, cognition, and behavior. Understanding the multi-scale nature of the brain, i.e., how…

Neurons and Cognition · Quantitative Biology 2025-01-17 Adam S. Charles

It has become increasingly popular to study the brain as a network due to the realization that functionality cannot be explained exclusively by independent activation of specialized regions. Instead, across a large spectrum of behaviors,…

Neurons and Cognition · Quantitative Biology 2014-07-22 Petko Bogdanov , Nazli Dereli , Danielle S. Bassett , Scott T. Grafton , Ambuj K. Singh

The N400 is an Event Related Potential that is evoked in response to conceptually meaningful stimuli. It is for instance more negative in response to incongruent than congruent words in a sentence, and more negative for unrelated than…

Neurons and Cognition · Quantitative Biology 2019-08-29 Karen Dijkstra , Jason Farquhar , Peter Desain

The relationship between brain structure and function has been probed using a variety of approaches, but how the underlying structural connectivity of the human brain drives behavior is far from understood. To investigate the effect of…

Neurons and Cognition · Quantitative Biology 2018-11-15 Kanika Bansal , John D. Medaglia , Danielle S. Bassett , Jean M. Vettel , Sarah F. Muldoon