In brain-computer interface (BCI) applications the detection of neural processing as revealed by event-related potentials (ERPs) is a frequently used approach to regain communication for people unable to interact through any peripheral muscle control. However, the commonly used electroencephalography (EEG) provides signals of low signal-to-noise ratio, making the systems slow and inaccurate. As...

Visual search can be facilitated by the learning of spatial configurations that predict the location of a target among distractors. Neuropsychological and functional magnetic resonance imaging (fMRI) evidence implicates the medial temporal lobe (MTL) memory system in this contextual cueing effect, and electroencephalography (EEG) studies have identified the involvement of visual cortical region...

Learning is known to facilitate our ability to detect targets in clutter and optimize brain processes for successful visual recognition. Previous brain-imaging studies have focused on identifying spatial patterns (i.e., brain areas) that change with learning, implicating occipitotemporal and frontoparietal areas. However, little is known about the interactions within this network that mediate l...

Nearly all research in neurofeedback since the 1960s has focused on training voluntary control over EEG constructs. By contrast, EEG state discrimination training focuses on awareness of subjective correlates of EEG states. This study presents the first successful replication of EEG alpha state discrimination first reported by Kamiya (1962). A 150-s baseline was recorded in 106 participants. Du...

Objectives: 1to evaluate the ability of the power spectrum of brain electrical activity to discriminate between age matched normal children and children diagnosed as learning disabled (LD) and, 2to correlate brain electrical activity with intelligence, school achievement and neuropsychological performance test scores. Methods: Electrical potentials (EEG) were recorded from 19 channels in a rest...

P300 CLASSIFICATION USING DEEP BELIEF NETS Electroencephalogram (EEG) is measure of the electrical activity of the brain. One of the most important EEG paradigm that has been explored in BCI systems is the P300 signal. The P300 wave is an endogenous event-related-potential which can be captured during the process of decision making as a subject reacts to a stimulus. One way to detect the P300 s...