Electroencephalographic (EEG) Evoked Potentials (EPs) have gained significant attention
as promising tools for non-invasive investigation of a wide array of neurological and …

Objective Overlapping neurophysiological signals are the main obstacle preventing from
using cortical auditory event-related potentials (AEPs) in clinical settings. Children AEPs are …

OBJECTIVE: This study examines developmental and aging trends in auditory evoked
potentials (AEPs) by applying two analysis methods to a large database of healthy subjects …

Due to its high temporal resolution and relatively low costs, electroencephalography (EEG)
is a widespread tool in neuroscientific research and clinical diagnosis. However, EEG …

Volume conduction from insignificant neuronal sources in the brain poses a challenge to the
detection and classification of single-trial low amplitude evoked potentials in …

Multi-subject or group-level component analysis provides a data-driven approach to study
properties of brain networks. Algorithms for group-level data decomposition of functional …

Objective: Scalp electroencephalogram (EEG) provides a substantial amount of data about
information processing in the human brain. In the context of conventional event-related …

Many cognitive and neurological disorders today, such as Autism Spectrum Disorders (ASD)
and various forms of epilepsy such as infantile spasms (IS), manifest as changes in voltage …

Overlapping neurophysiological signals are the main obstacle preventing from using cortical
event-related potentials (ERPs) in clinical settings. Children ERPs are particularly affected …

OBJECTIVE: To evaluate the effectiveness of a new method of using Independent
Component Analysis (ICA) and k-means clustering to increase the signal-to-noise ratio of …