Resting Electroencephalography Differences Between Eyes-Closed and Eyes-Open Conditions in Children with Subclinical Hypothyroidism.

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.

Epileptic seizure classifications using empirical mode decomposition and its derivative.

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.

Auditory event-related potentials demonstrate early cognitive impairment in children with subclinical hypothyroidism.

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.