Emotion Recognition with Eigen Features of Frequency Band Activities Embedded in Induced Brain Oscillations Mediated by Affective Pictures.

In this study, singular spectrum analysis (SSA) has been used for the first time in order to extract emotional features from well-defined electroencephalography (EEG) frequency band activities (BAs) so-called delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-16 Hz), beta (16-32 Hz), gamma (32-64 Hz). These five BAs were estimated by applying sixth-level multi-resolution wavelet decomposition (MRWD) with Daubechies wavelets (db-8) to single channel nonaveraged emotional EEG oscillations of 6 s for each scalp location over 16 recording sites (Fp1, Fp2, F3, F4, F7, F8, C3, C4, P3, P4, T3, T4, T5, T6, O1, O2). Every trial was mediated by different emotional stimuli which were selected from international affective picture system (IAPS) to induce emotional states such as pleasant (P), neutral (N), and unpleasant (UP). Largest principal components (PCs) of BAs were considered as emotional features and data mining approaches were used for the first time in order to classify both three different (P, N, UP) and two contrasting (P and UP) emotional states for 30 healthy controls. Emotional features extracted from gamma BAs (GBAs) for 16 recording sites provided the high classification accuracies of 87.1% and 100% for classification of three emotional states and two contrasting emotional states, respectively. In conclusion, we found the followings: (1) Eigenspectra of high frequency BAs in EEG are highly sensitive to emotional hemispheric activations, (2) emotional states are mostly mediated by GBA, (3) pleasant pictures induce the higher cortical activation in contrast to unpleasant pictures, (4) contrasting emotions induce opposite cortical activations, (5) cognitive activities are necessary for an emotion to occur.

Mutual information analysis of sleep EEG in detecting psycho-physiological insomnia.

The primary goal of this study is to state the clear changes in functional brain connectivity during all night sleep in psycho-physiological insomnia (PPI). The secondary goal is to investigate the usefulness of Mutual Information (MI) analysis in estimating cortical sleep EEG arousals for detection of PPI. For these purposes, healthy controls and patients were compared to each other with respect to both linear (Pearson correlation coefficient and coherence) and nonlinear quantifiers (MI) in addition to phase locking quantification for six sleep stages (stage.1-4, rem, wake) by means of interhemispheric dependency between two central sleep EEG derivations. In test, each connectivity estimation calculated for each couple of epoches (C3-A2 and C4-A1) was identified by the vector norm of estimation. Then, patients and controls were classified by using 10 different types of data mining classifiers for five error criteria such as accuracy, root mean squared error, sensitivity, specificity and precision. High performance in a classification through a measure will validate high contribution of that measure to detecting PPI. The MI was found to be the best method in detecting PPI. In particular, the patients had lower MI, higher PCC for all sleep stages. In other words, the lower sleep EEG synchronization suffering from PPI was observed. These results probably stand for the loss of neurons that then contribute to less complex dynamical processing within the neural networks in sleep disorders an the functional central brain connectivity is nonlinear during night sleep. In conclusion, the level of cortical hemispheric connectivity is strongly associated with sleep disorder. Thus, cortical communication quantified in all existence sleep stages might be a potential marker for sleep disorder induced by PPI.

Thrombopoietin levels of thrombocytopenic term and preterm newborns with infection.

We measured Thrombopoietin (Tpo) levels in thrombocytopenic term and preterm babies with infection to investigate the relationship between thrombopietin levels and platelet counts. Sixteen preterm (27-34 weeks' gestational age) and 5 term neonates (38-41 weeks' gestational age) with the diagnosis of neonatal infection and thrombocytopenia (platelets <150 x 10(9)/L) but, without the evidence of disseminated intravascular coagulation, were prospectively enrolled in the study. Fifteen preterm (27-34 weeks' gestational age) and 9 term (38-40 weeks' gestational age) age-matched healthy neonates were enrolled in the study as control. Blood samples were obtained from each subject at the time when infection and thrombocytopenia were detected and stored until assay. Bacterial infection was confirmed by blood cultures in five patients and by tracheal cultures in five. Median Tpo levels of term controls were lower than those of preterm controls (62 pg/mL vs. 87 pg/mL) (p <0.05). Median Tpo levels of thrombocyopenic preterm patients were higher than the levels of healthy preterms (258 pg/mL vs. 87 pg/mL) (p <0.05). Similarly, median Tpo levels of sick terms were significantly higher than those of healthy term controls (209 pg/mL vs. 62 pg/mL) (p <0.001). There was not significant difference between the median Tpo levels of term and preterm babies with infection (258 pg/mL vs. 209 pg/mL) (p >0.05). There was no correlation between platelet counts and Tpo levels in both term and preterm groups. The results of our study show that healthy term and preterm babies have detectable levels of Tpo and preterm babies have higher Tpo levels than term infants. Although thrombocytopenic babies with infection have increased levels of Tpo, these levels are still lower than the levels of thrombocytopenic children/adult patients and there seems to be no correlation between platelet counts and thrombopoietin levels. So our observation of increased Tpo levels may still be inadequate for normal platelet production in this period. and this group of babies may also be candidates for the administration of recombinant human Tpo.