The changes of electroencephalogram(EEG) in patients with dementia are most commonly studied by analyzing power or magnitude in certain traditionally defined frequency bands. However because of the absence of on identified metric which quantifies the complex amount of information, there are many limitations in using such a linear method. According to chaos theory, irregular signals of EEG cal also result from low dimensional deterministic chaos. Chaotic nonlinear dynamics in the EEG can be studied by calculating the correlation dimension. The authors have analyzed EEG epochs from three patients with dementia of Alzheimer type and three matched control subject. The result showed that patients with dementia of Alzheimer type had significantly lower correlation dimension than non-demented controls on 12 channels. Topographic analysis showed that the correlation dimensions were significantly lower in patients with Alzheimer's disease on frontal, temporal, central, and occipital head regions. These results show that brains of patients with dementia with dementia of Alzheimer type have a decreased complexity of electrophysiological behavior. We conclude that the nonlinear analysis such as calculating correlation dimension can be a promising tool for detecting changes in the complexity of brain dynamics.
Alzheimer Disease ; Brain ; Dementia* ; Electroencephalography* ; Head ; Humans ; Nonlinear Dynamics*

The primary purpose of this review is to present an overview of relationship between human spontaneous eyeblinking and internal cognitive processes. The second purpose is to address the neural substrates of human eyeblinking based on recent studies focusing on the central dopaminergic system and to explore the significance of spontaneous eyeblinks in neuropsychiatric disorders. We reviewed recent and previous studies on eyeblink patterns under various cognitive tasks. We also reviewed neural substrates of eyeblinking, particularly based on the central dopaminergic system. This paper suggests that spontaneous eyeblinks are highly correlated with various cognitive processes and the activity of central dopaminergic system. Various neuropsychiatric disorders are related to the alteration of the occurrence of eyeblinking. Spontaneous eyeblinking is the unique human behavior that occurs regularly without conscious effort. It is known that the rate of eyeblinking is modulated by internal cognitive processes and dopamine-related neuropsychiatric disorders. Further research is required to how the temporal dynamics of spontaneous eyeblinking is correlated with the disease activity and progression.
Dopamine ; Humans

OBJECTIVES: The neural substrate of fear is thought to be highly conserved among species including human. The purpose of this review was to address the neural substrates of fear based on recent findings obtained from animal and human studies. METHODS: Recent studies on brain regions related to fear, particularly fear conditioning in rodents and humans, were extensively reviewed. RESULTS: This paper suggests high consistency in anatomical structure and physiological mechanisms for fear perception, response, learning and modulation in animals and humans. CONCLUSIONS: Fear is manifested and modulated by well conserved neural circuits among species interconnected with the amygdala, such as the hippocampus and the ventromedial prefrontal cortex. Further research is required to incorporate findings from animal studies into a better understanding of neural circuitry of fear in human in a translational approach.
Amygdala ; Animals ; Brain ; Hippocampus ; Humans ; Learning ; Neuroanatomy ; Prefrontal Cortex ; Rodentia

OBJECTIVE: This study examined the mediating role of internet addiction in the association between psychological resilience and depressive symptoms. METHODS: 837 Korean university students completed a survey with items of demographic information, Connor-Davidson Resilience Scale (CD-RISC), Internet Addiction Test (IAT), and Patient Health Questionnaire (PHQ-9) in 2015. The complex associations among psychological resilience, internet addiction, and depressive symptoms were delineated using structural equation models. RESULTS: In the most parsimonious model, the total effect and indirect effect of resilience on depressive symptoms via internet addiction, were statistically significant. The goodness of fit of the measurement model was satisfactory with fit indices, normed fit index (NFI) of 0.990, non-normed fit index (NNFI) of 0.997, comparative fit index (CFI) of 0.998, root mean square error (RMSEA) of 0.018 (90%CI=0.001–0.034); and Akaike Information Criterion (AIC) of -21.049. CONCLUSION: The association between psychological resilience and depressive symptoms was mediated by internet addiction in Korean university students. Enhancement of resilience programs could help prevent internet addiction and reduce the related depression risks.
Depression* ; Humans ; Internet* ; Negotiating* ; Resilience, Psychological

OBJECT: It seemed worthwhile to estimate nonlinear measures of the electroencephalogram (EEG) in schizophrenic patients, because nonlinear measures might serve as indicators of the specific brain function in schizophrenia. METHOD: Previous studies which estimated the chaoticity in the brain of schizophrenia with nonlinear methods recorded the EEGs at limited electrodes, so we tried to record EEGs from 16 channels for nonlinear analysis in 19 patients with Schizophrenia and 8 healthy control subjects. We employed a new method to calculate the nonlinear invariant measures. For limited noisy data, this algorithm was strikingly faster and more accurate than previous ones. RESULTS: Our results showed that the schizophrenic patients had lower values of the largest positive Lyapunov exponent at the left inferior frontal and anterior temporal head regions compared with normal controls. CONCLUSIONS: These results suggest that the nonlinear analysis of the EEGs such as the estimation of the largest positive Lyapunov exponent seems to be a useful tool in analyzing EEG data to explore the neurodynamics of the brain of schizophrenic patients.
Brain ; Electrodes ; Electroencephalography* ; Head ; Humans ; Nonlinear Dynamics* ; Schizophrenia*

We would like to correct the degree for the 2nd author.