OBJECTIVE: Cartoons have been known to motivate learners and make learning process easier by combining verbal and visual effects. But they are mostly applied to motivate the less able learners, and have limits in delivering comprehensive information. Thus, more careful and scientific validation for the pros and cons of using cartoons for everyday use in various subjects is in need. METHODS: In this research, we used Electroencephalography(EEG) to compare cartoon learning and text learning by measuring four characteristic brainwaves including theta, alpha, sensory motor rhythms(SMR), and beta, from the left and right brain. The EEG signals acquired from 24 subjects are analyzed using the mean difference of the left and right brain and canonical correlation analysis. RESULTS: The theta brainwave of the left brain and right brain shows significant differences (p<0.05) from cartoon learning versus text learning in the theta brainwave while the other brain waves show similar patterns. CONCLUSION: Cartoon learning produced significantly stronger theta brainwaves than text learning implicating that cartoon learning reduces more focused attention, SMR brainwaves and beta brainwaves from the left brain explained cartoon learning and text learning process while alpha brainwaves explained those processes in the right brain.
Brain ; Brain Waves ; Electroencephalography ; Learning

The present study used the experimental patterns of Go/No Go and no motion contingent negative variation (CNV) task into the research in order to study whether the CNV can express the implication of expectation. Through comparing the CNV under different conditions, the data collected from experiment showed that the key to evoked CNV was close to the warning signal and command signal. Whether the command signal was related to the task would impact on the amplitude of the CNV. This characteristics responses to the subjects' expectation. On this basis, CNV can be used as the electrophysiological index for the reflection of expected value in the conditions of this experiment.
Anticipation, Psychological ; Brain Waves ; Contingent Negative Variation ; Humans

Stereo-electroencephalography (SEEG) is widely used to record the electrical activity of patients' brain in clinical. The SEEG-based epileptogenic network can better describe the origin and the spreading of seizures, which makes it an important measure to localize epileptogenic zone (EZ). SEEG data from six patients with refractory epilepsy are used in this study. Five of them are with temporal lobe epilepsy, and the other is with extratemporal lobe epilepsy. The node outflow (out-degree) and inflow (in-degree) of information are calculated in each node of epileptic network, and the overlay between selected nodes and resected nodes is analyzed. In this study, SEEG data is transformed to bipolar montage, and then the epileptic network is established by using independent effective coherence (iCoh) method. The SEEG segments at onset, middle and termination of seizures in Delta, Theta, Alpha, Beta, and Gamma rhythms are used respectively. Finally, the K-means clustering algorithm is applied on the node values of out-degree and in-degree respectively. The nodes in the cluster with high value are compared with the resected regions. The final results show that the accuracy of selected nodes in resected region in the Delta, Alpha and Beta rhythm are 0.90, 0.88 and 0.89 based on out-degree values in temporal lobe epilepsy patients respectively, while the in-degree values cannot differentiate them. In contrast, the out-degree values are higher outside the temporal lobe in the patient with extratemporal lobe epilepsy. Based on the out-degree feature in low-frequency epileptic network, this study provides a potential quantitative measure for identifying patients with temporal lobe epilepsy in clinical.
Brain Waves ; Electroencephalography ; Epilepsy, Temporal Lobe ; diagnosis ; Humans

In 1924, Hans Berger, a German psychiatrist, recorded the brain waves from a human brain for the first time. Many advances have been made in this field since then. Currently, brain waves are generated by a variety of computer technologies, including brain computer interface technology, and robot or artificial intelligence technology has also made amazing progress. A mental health practitioner who deals with brain-related medicine has an obligation and responsibility to research and find clinical applications of brain waves because they contain a great deal of information hidden in the brain. Therefore, understanding the basics of electroencephalography will contribute to a determination and resolution of various clinical situations. This review discusses basic knowledge before dealing with brain waves. In addition to a visual inspection of general brain waves, quantitative analysis of brain waves is expected to become an important area of interest for mental health practitioners.
Artificial Intelligence ; Brain ; Brain Mapping ; Brain Waves ; Brain-Computer Interfaces ; Electroencephalography ; Humans ; Mental Health ; Psychiatry

OBJECTIVE: To explore and determine the reorganizational changes in the cortical neural circuits associated with pruritis, this study was undertaken to compare the electroencephalography (EEG) changes in burn patients having primary symptoms of chronic itching (pruritis) and their paired healthy subjects. METHODS: Eight subjects were recruited for this exploratory pilot study: 4 patients with pruritus after burn injury matched by gender and age with 4 healthy subjects. EEG recordings were analyzed for absolute alpha, low beta, high beta, and theta power for both groups. RESULTS: The mean age of the burn patients was 41.75 years; while the mean age for the matched healthy subjects was 41.5 years. All subjects were male. A decreased alpha activity was observed in the occipital channels (0.82 vs. 1.4; p=0.01) and a decreased low beta activity in the frontal area (0.22 vs. 0.4; p=0.049) in eyes closed conditions. An overall decreased theta trend was observed in both the eyes open and eyes closed conditions in burn patients, compared to healthy individuals. CONCLUSION: This preliminary study presents initial evidence that chronic pruritus in burn subjects may be associated with brain reorganizational changes at the cortical level characterized by an EEG pattern.
Brain ; Brain Waves ; Burns* ; Electroencephalography ; Healthy Volunteers ; Humans ; Male ; Pilot Projects ; Pruritus* ; Quality of Life

Since the pharmacological treatment of insomnia has the potential risk for dependence and various side effects, nonpharmacological intervention for insomnia is very important in clinical practice. The neurophysiological characteristics and recent researches using quantitative EEG of insomnia suggest the insomnia as a state of CNS(central nervous system) hyperarousal. Insomnia should not be restricted to subjective sleep complaints alone because it appears to be a 24-hour disorder including daytime fatigue and decreased quality of life. The neurofeedback treatment is a self-regulation method based on the paradigm of operant conditioning. The goal of this treatment modality is to normalize the functioning of the brain by inhibiting and/or reinforcing specific frequency bands of brain waves. Therefore, the neurofeedback treatment on the basis of thalamocortical mechanisms which play an important role in sleep and arousal might be a useful treatment modality for the insomnia in the future. In this paper the authors suggest the clinical applications of neurofeedback for the treatment of insomnia and further clinical researches about its therapeutic effects in insomnia.
Arousal ; Brain ; Brain Waves ; Conditioning, Operant ; Electroencephalography ; Fatigue ; Neurofeedback* ; Quality of Life ; Sleep Initiation and Maintenance Disorders*

Since the pharmacological treatment of insomnia has the potential risk for dependence and various side effects, nonpharmacological intervention for insomnia is very important in clinical practice. The neurophysiological characteristics and recent researches using quantitative EEG of insomnia suggest the insomnia as a state of CNS(central nervous system) hyperarousal. Insomnia should not be restricted to subjective sleep complaints alone because it appears to be a 24-hour disorder including daytime fatigue and decreased quality of life. The neurofeedback treatment is a self-regulation method based on the paradigm of operant conditioning. The goal of this treatment modality is to normalize the functioning of the brain by inhibiting and/or reinforcing specific frequency bands of brain waves. Therefore, the neurofeedback treatment on the basis of thalamocortical mechanisms which play an important role in sleep and arousal might be a useful treatment modality for the insomnia in the future. In this paper the authors suggest the clinical applications of neurofeedback for the treatment of insomnia and further clinical researches about its therapeutic effects in insomnia.
Arousal ; Brain ; Brain Waves ; Conditioning, Operant ; Electroencephalography ; Fatigue ; Neurofeedback* ; Quality of Life ; Sleep Initiation and Maintenance Disorders*

Repetitive transcranial magnetic stimulation (rTMS) has been applied in a variety of diseases due to the clinical effects through the plasticity of the brain. The effects of TMS appear differently depending on the methods of stimulation. Single pulse TMS depolarizes and discharges nerves temporally under the cortex areas stimulated, whereas rTMS induces long-lasting effects of nerves stimulated. According to the intensity of stimulation, the direction of coil and stimulation frequency, rTMS can increase or decrease the excitability of the corticospinal tract and has been verified as techniques to treat a variety of neuropsychiatric disorders. In rTMS studies using electroencephalogram (EEG), changes in brain waves have been measured before and after TMS or simultaneously during TMS. In these studies, low frequency (< or =1 Hz) rTMS, high-frequency (5-25 Hz) rTMS, theta burst stimulation, paired association stimulation have been studied and somatosensory, visual, cognitive, and motor potentials and oscillatory activities were measured and compared before and after TMS. Combined with neurophysiological and, neuroimaging methods, TMS techniques could be used to study cortical excitability, cortical inhibition and excitement, and the cortical plasticity of local areas and neural network. In particular, because simultaneous measurement during TMS as well as measurement before and after TMS is possible, EEG could be very useful to determine the effects of TMS compared to other brain imaging tools.
Brain ; Brain Waves ; Electroencephalography* ; Methods ; Neuroimaging ; Plastics ; Pyramidal Tracts ; Transcranial Magnetic Stimulation*

Cyclic vomiting syndrome (CVS) is a disorder of unknown etiology that is characterized by its clinical pattern of intermittent episodes of severe vomiting, similar in time of onset and duration, with no symptoms during the intervening period. By definition, CVS is an idiopathic disorder that requires exclusionary laboratory testing. Not only can it be mimicked by many specific disorders, eg, surgical, neurologic, endocrine, metabolic, renal, but within idiopathic CVS there may be specific subgroups that have different mechanisms. It has been reported that CVS usually begins in toddlers and resolves during adolescence. Migraine is also self-limiting episodic condition of children and the clinical features of migraine and CVS show considerable similarity. It is proposed that CVS is a condition related to migraine. This paper reports clinical courses of long term follow-up and reversible EEG changes in three patients whose history included CVS. Clinical situations of attack interval, duration and associated symptoms had changed variablely in each patients through long term follow-up period. Cyclic vomiting subsided in two cases. Abnormal delta activity was seen during episodes and resolved at follow-up, when the patient asymptomatic. The brain wave changes support the interpretation of CVS as a migraine variant.
Adolescent ; Brain Waves ; Child ; Electroencephalography ; Follow-Up Studies* ; Humans ; Migraine Disorders ; Vomiting*

With extracting separately delta, theta, alpha and beta rhythms of electroencephalogram (EEG), we studied the characters of EEG for fatigued drivers by analyzing relative power spectrum, power spectral entropy and brain electrical activity mapping. The experimental results showed that with the average relative power spectrum in delta and theta rhythms of EEG increasing, the average relative power spectrum in alpha and beta rhythms decreased, while the average relative power spectrum in delta, theta and alpha rhythms increased in deep fatigue. The average power spectral entropy of EEG decreases with the increasing fatigue level. The average relative power spectrum and the average power spectral entropy of EEG could be expected to serve as the index for detecting fatigue level of drivers.
Automobile Driving ; Brain Waves ; physiology ; Electroencephalography ; Fatigue ; physiopathology ; Humans ; Monitoring, Physiologic ; Signal Processing, Computer-Assisted