Introduction: Lead intoxication in children has been associated with neurodevelopment disabilities that may result in motor and cognitive impairment. The aim of the present study is to evaluate in long term effects of prenatal exposure to low-level Pb2+ on learning, memory and EEG. Materials & Methods: Rat pregnant were exposed to distilled water or 0.05, 0.1, 0.2 % of Pb-acetate in the dr...

Introduction: Regarding the neurofeedback training process, previous studies indicate that 10%-50% of subjects cannot gain control over their brain activity even after repeated training sessions. This study is conducted to overcome this problem by investigating inter-individual differences in neurofeedback learning to propose some predictors for the trainability of subjects. Methods: Eight hea...

The human brain is a complex system consist of connected nerve cells that adapts with and learn from the environment by changing its regional activities. Synchrony between these regional activities called functional network changes during the life, and with learning of new skills. Time perception and interval discrimination are among the most necessary skills for the human being to perceive mot...

AbstractAccuracy in identifying the subjects’ intentions for moving their different limbs from EEG signals is regarded as an important factor in the studies related to BCI. In fact, the complexity of motor-imagination and low amount of signal-to-noise ratio for EEG signal makes this identification as a difficult task. In order to overcome these complexities, many techniques such as variou...

Prior research has shown that the ratio between resting-state theta (4-7 Hz)-beta (13-30 Hz) oscillations in the electroencephalogram (EEG) is associated with reward- and punishment-related feedback learning and risky decision making. However, it remains unclear whether the theta/beta EEG ratio is also an electrophysiological index for poorer behavioral adaptation when reward and punishment con...

Objective: A clinical decision support tool that automatically interprets EEGs can reduce time to diagnosis and enhance real-time applications such as ICU monitoring. Clinicians have indicated that a sensitivity of 95% with a specificity below 5% was the minimum requirement for clinical acceptance. We propose a highperformance classification system based on principles of big data and machine le...

This publication aims at developing computer based learning environments adapting to learners’ individual cognitive condition. The adaptive mechanism, based on Brain-Computer-Interface (BCI) methodology, relays on electroencephalogram (EEG)-data to diagnose learners’ mental states. A first within-subjects study (10 students) was accomplished aiming at differentiating between states of learning ...

In this paper, we demonstrate a closed-loop EEG-based learning environment, that adapts instructional learning material online, to improve learning success in students during arithmetic learning. The amount of cognitive workload during learning is crucial for successful learning and should be held in the optimal range for each learner. Based on EEG data from 10 subjects, we created a prediction...

Methods for rapid and objective quantification of interictal spikes in raw, unprocessed electroencephalogram (EEG) samples are scarce. We evaluated the accuracy of a tailored automated spike quantification algorithm. The automated quantification was compared with the quantification by two board-certified clinical neurophysiologists (gold-standard) in five steps: 1) accuracy in a single EEG chan...

In regard to the role of Aluminium in the emergence of psychological disorded in patients with chronic kidney diseases,this research project studied the acute,and chronic effects of Alluminium on different stages of memory and learning abilitis,after grouping the rats Alluminium chloride with concentrations of 1mg,5mg,10mg and 20 mg was used per kg of body weight.the Alluminium was given by int...