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Objective: Electroencephalography changes that occur during the transition from eyes-closed to the eyes-open state in resting condition are related to the early phase of sensory processing and are defined as activation. The present study aimed to reveal the potential deteriorations that may occur in the initial period of sensory processing in resting electroencephalography between children with subclinical hypothyroidism and a control group., Materials and Methods: Electroencephalographies of 15 children with subclinical hypothyroidism and 15 healthy children aged 10 to 17 years were recorded for 2 minutes for EC and 2 minutes for eyes-open conditions in resting state. Absolute electroencephalography band powers (μV2 ) within the delta, theta, alpha, and beta frequency bands were calculated in Fz, Cz, Pz, and Oz electrodes, respectively, for eyes-closed and eyes-open conditions., Results: The results show that, although there was no noteworthy difference between the powers of the electroencephalography frequency bands of children with subclinical hypothyroidism and healthy children during the eyes-open condition, the alpha powers of the control group were significantly higher in all electrodes during the eyes-closed condition. Furthermore, the powers of all frequency bands were observed to decrease in the eyes-open condition in the control group. However, the same net decrease was not observed in the frequency powers of children with subclinical hypothyroidism., Conclusion: According to the results of this study, children with subclinical hypothyroidism may experience information processing impairments starting in the early stages of sensory processing.

Background: Epilepsy is one of the most common neurological disorders associated with disruption of brain activity. In the classification and detection of epileptic seizures, electroencephalography (EEG) measurements, which record the electrical activities of the brain, are frequently used. Empirical mode decomposition (EMD) and its derivative, ensemble EMD (EEMD) are recently developed methods used to decompose non-stationary and nonlinear signals such as EEG into a finite number of oscillations called intrinsic mode functions (IMFs). Our main objective in this study is to present a hybrid IMF selection method combining four different approaches (energy, correlation, power spectral distance, and statistical significance measures), and investigate the effect of selected IMFs extracted by EMD and EEMD on the classification. We have applied the proposed IMF selection approach on the classification of EEG signals recorded from epilepsy patients who are under treatment at our collaborator hospital. Multichannel EEG signals collected from epilepsy patients are decomposed into IMFs, and then IMF selection was performed. Finally, time- and spectral-domain, and nonlinear features are extracted and feature sets are created for the classification., Results: The maximum classification accuracies obtained using various combinations of IMFs were 94.56%, 95.63%, 96.8%, and 96.25% for SVM, KNN, naive Bayes, and logistic regression classifiers, respectively, by using EMD analysis; whereas, the EEMD approach has provided maximum classification accuracies of 96.06%, 97%, 97%, and 96.25% for SVM, KNN, naive Bayes, and logistic regression, respectively. Classification performance with the same features obtained using direct EEG signals instead of the decomposed IMFs was worse than the aforementioned 2 approaches for every combination., Conclusion: Simulation results demonstrate that the proposed IMF selection approach affects the classification results. Also, EEMD provides a robust method for feature extraction from EEG signals in order to classify pre-seizure and seizure segments.

Background The aim of this study was to examine the cognitive functions of children with subclinical hypothyroidism (SH) and healthy children with the use of auditory event-related potentials (AERPs) and neuropsychological tests. Methods Twenty children aged between 8 and 17 years, diagnosed with SH, and 20 age-matched healthy controls were included in this study. A classical auditory oddball paradigm was applied during the electroencephalography (EEG) recordings, and event-related potentials (ERPs) were evaluated between the 0.5- and 20-Hz frequency intervals. P1, N1, P2, N2 and P3 amplitudes and latencies were measured in Fz, FCz, Cz, CPz, Pz and Oz electrodes. Additionally, a number of neuropsychological tests evaluating the reaction time and various cognitive functions were carried out. Results In children with SH, P3 amplitudes in FCz, Cz and CPz electrodes were significantly lower than those in controls (p < 0.05). In addition to this, the P1N1 and N1P2 peak-to-peak amplitude values were also found to be smaller for children with SH than controls (p < 0.05). With regard to the neuropsychological tests, no significant difference was observed between the SH and control groups on any of the cognitive test parameters, reaction time or correct response rates. Conclusions In the present study, while children with SH did not differ from controls with respect to their cognitive functions evaluated via neuropsychological tests, cognitive differences were detected via electrophysiological investigations. This result implies that implicit changes in cognition which are not yet overtly reflected on neuropsychological tests may be detected at an early stage in children with SH.

Background: The study of brain functioning is a major challenge in neuroscience fields as human brain has a dynamic and ever changing information processing. Case is worsened with conditions where brain undergoes major changes in so-called different conscious states. Even though the exact definition of consciousness is a hard one, there are certain conditions where the descriptions have reached a consensus. The sleep and the anesthesia are different conditions which are separable from each other and also from wakefulness. The aim of our group has been to tackle the issue of brain functioning with setting up similar research conditions for these three conscious states., Methods: In order to achieve this goal we have designed an auditory stimulation battery with changing conditions to be recorded during a 40 channel EEG polygraph (Nuamps) session. The stimuli (modified mismatch, auditory evoked etc.) have been administered both in the operation room and the sleep lab via Embedded Interactive Stimulus Unit which was developed in our lab. The overall study has provided some results for three domains of consciousness. In order to be able to monitor the changes we have incorporated Bispectral Index Monitoring to both sleep and anesthesia conditions., Results: The first stage results have provided a basic understanding in these altered states such that auditory stimuli have been successfully processed in both light and deep sleep stages. The anesthesia provides a sudden change in brain responsiveness; therefore a dosage dependent anesthetic administration has proved to be useful. The auditory processing was exemplified targeting N1 wave, with a thorough analysis from spectrogram to sLORETA. The frequency components were observed to be shifting throughout the stages. The propofol administration and the deeper sleep stages both resulted in the decreasing of N1 component. The sLORETA revealed similar activity at BA7 in sleep (BIS 70) and target propofol concentration of 1.2 microg/mL., Conclusions: The current study utilized similar stimulation and recording system and incorporated BIS dependent values to validate a common approach to sleep and anesthesia. Accordingly the brain has a complex behavior pattern, dynamically changing its responsiveness in accordance with stimulations and states.

Among various types of clustering methods, partition-based methods such as k-means and FCM are widely used in the analysis of such data. However, when duration between stimuli is different, such methods are not able to provide satisfactory results because they find equal size clusters according to the fundamental running principle of these methods. In such cases, neighborhood-based clustering methods can give more satisfactory results because measurement series are separated from one another according to dramatic breaking points. In recent years, bispectral index (BIS) monitoring, which is used for monitoring the level of anesthesia, has been used in sleep studies. Sleep stages are classically scored according to the Rechtschaffen and Kales (R&K) scoring system. BIS has been shown to have a strong correlation with the R&K scoring system. In this study, fuzzy neighborhood/density-based spatial clustering of applications with noise (FN-DBSCAN) that combines speed of the DBSCAN algorithm and robustness of the NRFJP algorithm is applied to BIS measurement series. As a result of experiments, we can conclude that, by using BIS data, the FN-DBSCAN method estimates sleep stages better than the fuzzy c-means method.

Bipolar disorder involves dysfunction in gamma amino butyric acid (GABA)/glutamatergic systems and neural circuits that regulate cognitive processing. Valproate, a mood stabilizing anticonvulsant, modulates GABA/glutamate and shows neuroprotective effect. Electroencephalographic oscillatory activity assessment is an alternative brain imaging technique with high time resolution. It presents integrative brain functioning. We aimed to assess the oscillatory responses of patients with bipolar disorder in euthymic state of bipolar disorder and the changes after treatment with valproate. Event related potentials to visual odd-ball paradigm in 10 euthymic medication free, bipolar patients were measured before and after 6 weeks of valproate monotherapy and compared with sex- and age-matched healthy controls. Delta frequency bands, as representative of signal detection and decision-making, were obtained by digital filtering. At baseline, patients showed higher delta responses to target stimuli in all but significantly left frontal channels in comparison to controls. After 6 weeks of treatment, delta responses decreased significantly in central frontal (Fz) (p: 0.028), left frontal (F3) (p: 0.028), left (T3) (p: 0.015), right anterior (T4) (p: 0.011), and left posterior temporal (T5) (p: 0.011) channels compared to baseline and became no different to the controls, which did not differ between two assessments. The findings point to a diffuse increase in low frequency electrical activity which was prominent in the left frontal location in euthymic patients with bipolar disorder. Reduction of the electrical activity of the left frontal and bilateral anterior temporal areas with treatment may be through modulation of glutamatergic and GABAergic mechanisms and indicative of valproate's neuroprotective effect.