EEG "Signs" of Verbal Creative Task Fulfillment with and without Overcoming Self-Induced Stereotypes.

The study aimed to reveal task-related differences in story creation with and without the mental effort of overcoming self-induced stereotypes. Eighteen right-handed subjects (19.3 ± 1.1 years old) created stories. The subjects reported the formation of story plot stereotypes (as we call them: self-induced) during self-regulated creative production, which had to be overcome with the instruction to continue the story. Creative task fulfillment (without formed stereotypes-first stage of creation) was characterized by a decrease in the wave percentages of 9-10 Hz, 10-11 Hz and 11-12 Hz frequencies and EEG desynchronization (decreases in EEG spectral power) in the theta (4-8 Hz), alpha1 (8-10 Hz) and alpha2 (10-13 Hz) frequency bands in comparison with the REST (random episodic silent thought) state. The effortful creation task (with overcoming of self-induced stereotypes-second stage of creation) was characterized by increases in waves with frequencies of 9-10 Hz, 10-11 Hz, 11-12 Hz in temporal, occipital areas and pronounced EEG synchronization in alpha1,2 frequency bands in comparison with the free creation condition. It was also found, that the participants with the higher originality scores in psychological tests demonstrated increased percentage of high frequencies (11-12 Hz in comparison with those who had lower originality scores. Obtained results support the role of alpha and theta frequency bands dynamics in creative cognition.

Specificity of spontaneous EEG associated with different levels of cognitive and communicative dysfunctions in children.

This study aimed to reveal electrophysiological markers of communicative and cognitive dysfunctions of different severity in children with autism spectrum disorder (ASD). Eyes-opened electroencephalograms (EEGs) of 42 children with ASD, divided into two groups according to the severity of their communicative and cognitive dysfunctions (24 with severe and 18 children with less severe ASD), and 70 age-matched controls aged 4-9 years were examined by means of spectral and group independent component (gIC) analyses. A predominance of theta and beta EEG activity in both groups of children with ASD compared to the activity in the control group was found in the global gIC together with a predominance of beta EEG activity in the right occipital region. The quantity of local gICs with enhanced slow and high-frequency EEG activity (within the frontal, temporal, and parietal cortex areas) in children 4-9 years of age might be considered a marker of cognitive and communicative dysfunction severity.

Development of electroencephalographic pattern classifiers for real and imaginary thumb and index finger movements of one hand.

OBJECTIVE: This study aimed to find effective approaches to electroencephalographic (EEG) signal analysis and resolve problems of real and imaginary finger movement pattern recognition and categorization for one hand. METHODS AND MATERIALS: Eight right-handed subjects (mean age 32.8 [SD=3.3] years) participated in the study, and activity from sensorimotor zones (central and contralateral to the movements/imagery) was recorded for EEG data analysis. In our study, we explored the decoding accuracy of EEG signals using real and imagined finger (thumb/index of one hand) movements using artificial neural network (ANN) and support vector machine (SVM) algorithms for future brain-computer interface (BCI) applications. RESULTS: The decoding accuracy of the SVM based on a Gaussian radial basis function linearly increased with each trial accumulation (mean: 45%, max: 62% with 20 trial summarizations), and the decoding accuracy of the ANN was higher when single-trial discrimination was applied (mean: 38%, max: 42%). The chosen approaches of EEG signal discrimination demonstrated differential sensitivity to data accumulation. Additionally, the time responses varied across subjects and inside sessions but did not influence the discrimination accuracy of the algorithms. CONCLUSION: This work supports the feasibility of the approach, which is presumed suitable for one-hand finger movement (real and imaginary) decoding. These results could be applied in the elaboration of multiclass BCI systems.