Brain functional and effective connectivity based on electroencephalography recordings: A review
Functional connectivity and effective connectivity of the human brain, representing statistical
dependence and directed information flow between cortical regions, significantly contribute …
dependence and directed information flow between cortical regions, significantly contribute …
Neural network-based parametric system identification: A review
Parametric system identification, which is the process of uncovering the inherent dynamics
of a system based on the model built with the observed inputs and outputs data, has been …
of a system based on the model built with the observed inputs and outputs data, has been …
Nonlinear system identification of neural systems from neurophysiological signals
The human nervous system is one of the most complicated systems in nature. Complex
nonlinear behaviours have been shown from the single neuron level to the system level. For …
nonlinear behaviours have been shown from the single neuron level to the system level. For …
[图书][B] Causality, correlation and artificial intelligence for rational decision making
T Marwala - 2015 - books.google.com
Causality has been a subject of study for a long time. Often causality is confused with
correlation. Human intuition has evolved such that it has learned to identify causality through …
correlation. Human intuition has evolved such that it has learned to identify causality through …
Measuring the non-linear directed information flow in schizophrenia by multivariate transfer entropy
People living with schizophrenia (SCZ) experience severe brain network deterioration. The
brain is constantly fizzling with non-linear causal activities measured by …
brain is constantly fizzling with non-linear causal activities measured by …
[HTML][HTML] A novel defect depth measurement method based on Nonlinear System Identification for pulsed thermographic inspection
This paper introduces a new method to improve the reliability and confidence level of defect
depth measurement based on pulsed thermographic inspection by addressing the over …
depth measurement based on pulsed thermographic inspection by addressing the over …
Driver workload estimation using a novel hybrid method of error reduction ratio causality and support vector machine
Measuring driver workload is of great significance for improving the understanding of driver
behaviours and supporting the improvement of advanced driver assistance systems …
behaviours and supporting the improvement of advanced driver assistance systems …
NCREANN: Nonlinear causal relationship estimation by artificial neural network; applied for autism connectivity study
N Talebi, AM Nasrabadi… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
Quantifying causal (effective) interactions between different brain regions are very important
in neuroscience research. Many conventional methods estimate effective connectivity based …
in neuroscience research. Many conventional methods estimate effective connectivity based …
[HTML][HTML] Kernel-based nonlinear manifold learning for EEG-based functional connectivity analysis and channel selection with application to Alzheimer's disease
Dynamical, causal, and cross-frequency coupling analysis using the electroencephalogram
(EEG) has gained significant attention for diagnosing and characterizing neurological …
(EEG) has gained significant attention for diagnosing and characterizing neurological …
A self-organized recurrent neural network for estimating the effective connectivity and its application to EEG data
Z Abbasvandi, AM Nasrabadi - Computers in biology and medicine, 2019 - Elsevier
Objective Effective connectivity is an important notion in neuroscience research, useful for
detecting the interactions between regions of the brain. New method Since we are dealing …
detecting the interactions between regions of the brain. New method Since we are dealing …