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Found 12 papers, 3 papers with code
Low-dimensional controllability of brain networks
Network controllability is a powerful tool to study causal relationships in complex systems and identify the driver nodes for steering the network dynamics into desired states.
HappyFeat -- An interactive and efficient BCI framework for clinical applications
We also show that it can be used as an efficient tool for comparing different metrics extracted from the signals, to train the classification algorithm.
Intentional binding enhances hybrid BCI control
Mental imagery-based brain-computer interfaces (BCIs) allow to interact with the external environment by naturally bypassing the musculoskeletal system.
Statistical models of complex brain networks: a maximum entropy approach
The brain is a highly complex system.
The impact of aging on human brain network target controllability
Understanding how few distributed areas can steer large-scale brain activity is a fundamental question that has practical implications, which range from inducing specific patterns of behavior to counteracting disease.
Multiscale modeling of brain network organization
A complete understanding of the brain requires an integrated description of the numerous scales of neural organization.
Functional connectivity ensemble method to enhance BCI performance (FUCONE)
Functional connectivity is a key approach to investigate oscillatory activities of the brain that provides important insights on the underlying dynamic of neuronal interactions and that is mostly applied for brain activity analysis.
Improving J-divergence of brain connectivity states by graph Laplacian denoising
Using our novel formulation of the J-divergence, we are able to quantify the distance between the FC networks in the motor imagery and resting states, as well as to understand the contribution of each Laplacian variable to the total J-divergence between two states.
BCI learning induces core-periphery reorganization in M/EEG multiplex brain networks
Brain-computer interfaces (BCIs) constitute a promising tool for communication and control.
Step-wise target controllability identifies dysregulated pathways of macrophage networks in multiple sclerosis
In many applications it is often essential to test the ability of an individual node to control a specific target subset of the network.
Phase/amplitude synchronization of brain signals during motor imagery BCI tasks
In the last decade, functional connectivity (FC) estimators have been increasingly explored based on their ability to capture synchronization between multivariate brain signals.
Human brain distinctiveness based on EEG spectral coherence connectivity
The use of EEG biometrics, for the purpose of automatic people recognition, has received increasing attention in the recent years.
