Cross-frequency coupling (CFC) reflects (nonlinear) interactions between signals of different
frequencies. Evidence from both patient and healthy participant studies suggests that CFC …

Electrocortical network dynamics are integral to brain function. Linear and nonlinear
connectivity applications enrich neurophysiological investigations into anxiety disorders …

The cross-frequency coupling relationship of EEG signals is of great significance to identify
abnormal EEG signals and diagnose diseases. This paper proposes a new algorithm …

Emotion, an essential aspect in inferring human psychological states, is featured by
entangled oscillators operating at multiple frequencies and montages. However, the …

Increasing reports indicated that multiscale entropy (MSE) is an efficient approach to
investigate various physical and physiological states, especially effective for cardiac …

Growing evidence links impairment of brain functions in Alzheimer's disease (AD) with
disruptions of brain functional connectivity. However, whether the AD brain shows similar …

Monitoring fetal heart rate during pregnancy is essential to assist clinicians in making more
timely decisions. Non-invasive monitoring of fetal heart activities using abdominal ECGs is …

Objective: Functional coupling between the motor cortex and muscle activity is commonly
detected and quantified by cortico-muscular coherence (CMC) or Granger causality (GC) …

EEG emotion recognition based on Granger causality (GC) brain networks mainly focus on
the EEG signal from the same-frequency bands, however, there are still some causality …

The construction of time series networks in complex systems facilitates the investigation of
information interaction mechanisms among subsystems. As widely used causal relationship …