Detrended fluctuation analysis (DFA) is fit for studies on the long-range exponential correlations of non-stationary time serial. In this paper, for elucidating the characteristics of different sleep stages, DFA is adopted to analyze the physiological data collected during sleep. The parameters such as electroencephalogram (EEG), R-R interval sequence and stroke volume (SV) are analyzed, and the scaling exponent a is calculated. The experimental results reveal that the values of a differ much in different sleep stages,that the rules of EEG and SV are alike, that alpha increases with the deepening of sleep, but in inverse for R-R interval sequence that alpha decreases with the deepening of sleep. These indicate that the method of DFA is practical in the analysis of physiological parameters.
Data Interpretation, Statistical ; Electrocardiography ; statistics & numerical data ; Electroencephalography ; statistics & numerical data ; Humans ; Polysomnography ; Signal Processing, Computer-Assisted ; Sleep Stages ; physiology

In regard to the controls and schizophrenia EEGs, we have got alpha rhythm from three points of view and verified the nonlinearity of the three kinds of rhythms. The results show that neither normal EEG alpha nor patients EEG alpha have the typical nonlinear characteristics. Therefore, we could not blindly use the theories of nonlinear dynamics to analyze the rhythm of brain wave.
Alpha Rhythm ; statistics & numerical data ; Brain ; physiology ; physiopathology ; Electroencephalography ; statistics & numerical data ; Humans ; Nonlinear Dynamics ; Schizophrenia ; physiopathology

To correctly classify EEG with different mental tasks, a new learning algorithm for Evolving Cascade Neural Networks (ECNNs) is described to avoid over-fitting of a neural network due to noise and redundant features. The learning algorithm calculates the value of a fitness function on validate set and accordingly updates the connection weights on training set. The learning algorithm uses the regularity criterion for selecting the neurons with relevant connection. If the value Cr calculated for the rth neuron is less than the value Cr-1 calculated for the previous (r-1) neuron, the features that feed the rth neuron are relevant, else they are irrelevant. An ECNN starts to learn with one input node and then, adding new inputs as well as new hidden neurons, evolves it. The trained ECNN has a nearly minimal number of input and hidden neurons as well as connections. The algorithm is applied to classify EEG with two mental tasks. The trained ECNN has correctly classified 83.1% of the testing segments. It shows a better result, compared with a standard BP network.
Algorithms ; Electroencephalography ; methods ; statistics & numerical data ; Humans ; Neural Networks (Computer) ; Signal Processing, Computer-Assisted

BACKGROUND AND OBJECTIVES: Nocturnal epilepsy is rare but an interesting phenomenon suggesting a close relationship between epilepsy and sleep. However, previous efforts to characterize the nocturnal epilepsy as a specific epileptic syndrome have been incomplete. This study was conducted to evaluate the prognosis and the recurrence rate of diurnal seizure in patients presented with nocturnal seizures only to further determine the clinical characteristics of nocturnal epilepsy. METHODS: Sixty-six patients with nocturnal seizures only were identified through the epilepsy registry form of the Yonsei Epilepsy Clinic(YEC) Data Bank. All patients had thorough history, physical and neurological examinations, blood tests, sleep deprived EEG with nasopharyngeal electrodes, and MRI or CT of brain according to the protocol of YEC. Patients followed at the YEC shorter than one year were excluded from the data analysis. All patients included to the study were initially treated by maximally tolerable monotherapy and then polytherapy if seizures were not controlled. RESULTS: Among sixty-six, patients, seizure descriptions were compatible with generalized tonic-clonic seizures in forty-seven patients and partial seizures with or without GTC in ninteen patients. EEG demonstrated either generalized or partial interictal epileptiform discharges in twenty-nine patients. CT or MRI showed focal lesions in eleven patients. For the follow up period of average thirty-nine months, twenty-five patients developed seizures while awake. Comparison of clinical characteristics between the patients with nocturnal seizures only and the patients with recurrent diurnal seizures did reveal followings ; duration of seizures at the time of initial evaluation was longer in the diurnal seizure (6. 7 vs. 9. 3 years), but it was not statistically significant (p<0.05). The presence of partial features in the history, neurological examinations, EEG, and MRI were more frequently associated with recurrent diurnal seizures. Responses to the AEDs.
Brain ; Electrodes ; Electroencephalography ; Epilepsy* ; Follow-Up Studies ; Hematologic Tests ; Humans ; Magnetic Resonance Imaging ; Neurologic Examination ; Prognosis ; Recurrence ; Seizures ; Statistics as Topic

The present paper focused on the extraction of event-related potentials on a single sweep under extremely low S/N ratio. Two methods that can efficiently remove spontaneous EEG, ocular artifacts and power line interference were presented based on ARX modeling and independent component analysis (ICA). The former method applied ARX model to the measured compound signal that extensively contained the three kinds of ordinary noises mentioned above, and used ARX algorithm for parametric identification. The latter decomposed the signal by means of independent component analysis. Besides, some of ICA's important decomposing characters and its intrinsic causality were pointed out definitely. According to the practical situation, some modification on FastICA algorithm was also given, so as to implement auto-adaptive mapping of decomposed results to ERP component. Through simulation, both the two ways are proved to be highly capable of signal extraction and S/N ratio improving.
Electroencephalography ; methods ; statistics & numerical data ; Event-Related Potentials, P300 ; physiology ; Evoked Potentials ; physiology ; Humans ; Signal Processing, Computer-Assisted

We have investigated spatio-temporal source modeling (STSM) of the electroencephalogram (EEG) by using a Quasi-Newton method based on Independent Component Analysis (ICA) for localization of multiple dipole sources from the scalp EEG. The problem of multiple dipole localization was transformed into several single dipole localization problems. Another benefit of the present method is that the number of independent sources can be estimated. Computer simulation studies were conducted to evaluate the performance of this approach. The present simulation results indicate that the ICA-based method is superior to the conventional nonlinear methods in localization accuracy, computation time and anti-noise performance, for multiple dipole localization when the sources are stationary over the period of interest.
Brain ; physiology ; Brain Mapping ; methods ; Computer Simulation ; Data Interpretation, Statistical ; Electroencephalography ; statistics & numerical data ; Humans ; Models, Statistical

To optimize the monitoring time of interictal epileptiform discharges (IED) in patients with epilepsy by long-term video electroencephalogram (VEEG).The cumulative percentages of IED detected by VEEG in 346 epilepsy patients (349 times) with different purposes, different waking sleep states and different MRI findings were retrospectively analyzed. According to the purposes, there were 164 patients (165 times) for clarifying diagnosis, 124 patients (124 times) for preoperative evaluation and 58 patients (60 times) for adjustment of medications. According to MRI results, there were responsible lesions in 98 patients (98 times) and no responsible lesions in 173 patients (174 times).Among 346 patients (349 times), IED was detected within 24 h in 231 patients (times). The percentage of detection in patients with purpose of preoperative evaluation was higher than those with purpose of diagnosis and medication adjustment. The detection of LED was gradually increased in first 8 h with 59.0%, then stably in 24 h. 46.8% IED was recorded during sleep time, particularly in the second stage of sleep. The cumulative percentage of IED in patients with abnormal MRI findings was higher in all periods. It reached 83.7% within 8 h, and then tended to be stable.The study shows that LED should be monitored by VEEG at least 8 hours and should include the second stage of sleep in patients with epilepsy. Patients with refractory epilepsy and with abnormal lesions on MRI should record IED more frequently.
Brain ; diagnostic imaging ; pathology ; Brain Waves ; Electroencephalography ; methods ; statistics & numerical data ; Epilepsy ; pathology ; physiopathology ; Female ; Humans ; Magnetic Resonance Imaging ; statistics & numerical data ; Male ; Retrospective Studies ; Sleep ; physiology ; Time Factors

Patients with human immunodeficiency virus (HIV) infection have a higher burden of seizures, but few studies have examined seizures in HIV-infected individuals in Korea. A retrospective study was conducted to determine the epidemiology and clinical characteristics of seizures in patients with HIV infection. Among a total of 1,141 patients, 34 (3%) had seizures or epilepsy; 4 of these individuals had epilepsy before HIV infection, and the others showed new-onset seizures. Most patients exhibited moderate (200 to 500, n = 13) or low (below 200, n = 16) CD4 counts. The most common seizure etiology was progressive multifocal leukoencephalopathy (n = 14), followed by other HIV-associated central nervous system (CNS) complications (n = 6). Imaging studies revealed brain lesions in 21 patients. A total of 9 patients experienced only one seizure during the follow-up period, and 25 patients experienced multiple seizures or status epilepticus (n = 2). Multiple seizures were more common in patients with brain etiologies (P = 0.019) or epileptiform discharges on EEG (P = 0.032). Most seizures were controlled without anticonvulsants (n = 12) or with a single anticonvulsant (n = 12). Among patients with HIV infection, seizures are significantly more prevalent than in the general population. Most seizures, with the exception of status epilepticus, have a benign clinical course and few complications.
Adult ; Aged ; Anticonvulsants/therapeutic use ; Causality ; Comorbidity ; Electroencephalography/*statistics & numerical data ; Female ; HIV Infections/diagnosis/*epidemiology ; Humans ; Incidence ; Longitudinal Studies ; Male ; Middle Aged ; Republic of Korea/epidemiology ; Risk Factors ; Seizures/*diagnosis/*epidemiology/prevention & control ; Treatment Outcome

To investigate the features of electroencephalography (EEG) power and coherence at rest and during a working memory task of patients with mild cognitive impairment (MCI). Thirty-five patients (17 males, 18 females; 52-71 years old) and 34 sex- and age-matched controls (17 males, 17 females; 51-63 years old) were recruited in the present study. Mini-Mental State Examination (MMSE) of 35 patients with MCI and 34 normal controls revealed that the scores of MCI patients did not differ significantly from those of normal controls (P>0.05). Then, EEGs at rest and during working memory task with three levels of working memory load were recorded. The EEG power was computed over 10 channels: right and left frontal (F3, F4), central (C3, C4), parietal (P3, P4), temporal (T5, T6) and occipital (O1, O2); inter-hemispheric coherences were computed from five electrode pairs of F3-F4, C3-C4, P3-P4, T5-T6 and O1-O2 for delta (1.0-3.5 Hz), theta (4.0-7.5 Hz), alpha-1 (8.0-10.0 Hz), alpha-2 (10.5 -13.0 Hz), beta-1 (13.5-18.0 Hz) and beta-2 (18.5-30.0 Hz) frequency bands. All values of the EEG power of MCI patients were found to be higher than those of normal controls at rest and during working memory tasks. Furthermore, the values of EEG power in the theta, alpha-1, alpha-2 and beta-1 bands of patients with MCI were significantly high (P<0.05) in comparison with those of normal controls. Correlation analysis indicated a significant negative correlation between the EEG powers and MMSE scores. In addition, during working memory tasks, the EEG coherences in all bands were significantly higher in the MCI group in comparison with those in the control group (P<0.05). However, there was no significant difference in EEG coherences between two groups at rest. These findings comprise evidence that MCI patients have higher EEG power at rest, and higher EEG power and coherence during working conditions. It suggests that MCI may be associated with compensatory processes at rest and during working memory tasks. Moreover, failure of normal cortical connections may be exist in MCI patients.
Aged ; Brain ; physiopathology ; Cognition Disorders ; diagnosis ; physiopathology ; Diagnosis, Computer-Assisted ; methods ; Electroencephalography ; methods ; Female ; Humans ; Male ; Memory, Short-Term ; Middle Aged ; Severity of Illness Index ; Statistics as Topic ; Task Performance and Analysis

OBJECTIVETo study correlation of brain hypoxia of different degrees with brain function and damage.

METHODSThe brain regional oxygen saturation (rSO2) was determined by using a non-invasive near infrared spectroscopy (NIRS) technique in 15 piglets; the piglets were subjected to inhale 3% - 11% oxygen-nitrogen mixed gas through mechanical ventilation for 30 min. The piglets were divided into groups according to the level of brain rSO2 (i.e. < 30%, 30% - 35%, 35% - 40%, and 40% - 50%), and the data were compared with those of the control group (rSO2 > 60%). Changes of brain function were detected through amplitude and frequency of EEG waves and signal complexity. The piglets were sacrificed via decapitation 72 h after brain damage, and then histopathological and ultrastructural examinations were performed on cerebral cortex and hippocampal CA1 area.

RESULTSIn the group with rSO2 > 40%, the mean arterial pressure (MAP) after hypoxia was (56 +/- 0.00) mm Hg (1 mm Hg = 0.133 kPa), the blood lactic acid (LA) was (2.3 +/- 1.2) mmol/L, the EEG findings were within normal range, and there was no change in brain tissue ultrastructure. In the group with brain rSO2 = 30% approximately 40%, the MAP was (73 +/- 8) mm Hg, the LA was (8.2 +/- 3.9) mmol/L, the EEG waves showed decreased amplitude, frequency and complexity, but restored to some extent after hypoxia. The brain tissue ultrastructure showed damages to the cerebral cortex and neuron mitochondria at hippocampal CA1 area. In the group with brain rSO2 < 30%, the MAP was (35 +/- 0) mm Hg, the LA was (12 +/- 2) mmol/L, the EEG showed decreased amplitude, frequency, and complexity of signals compared with those of the normal control group, and was difficult to restore after hypoxia in some of the piglets; the brain tissue ultrastructure appeared to be similar to the changes seen with high-degree swollen cerebral cortex and neuron mitochondria at hippocampal CA1 area.

CONCLUSIONDifferent degrees of hypoxia had different influence on brain function and brain damage. The lower the brain rSO2, the more severe the damages to the brain and its function. The rSO2 of brain tissues detected with noninvasive NIRS can reflect brain injury and its severity during cerebral anoxia.

Animals ; Blood Gas Analysis ; Brain Injuries ; complications ; Cerebral Cortex ; physiopathology ; Cerebrovascular Circulation ; physiology ; Electroencephalography ; Female ; Hypoxia ; metabolism ; pathology ; Hypoxia, Brain ; complications ; Hypoxia-Ischemia, Brain ; physiopathology ; Male ; Neurons ; pathology ; Oximetry ; instrumentation ; Oxygen ; metabolism ; Oxygen Consumption ; Spectroscopy, Near-Infrared ; methods ; Statistics as Topic ; Swine