Activation of the Brain During Motor Imagination Task with Auditory Stimulation

Background: Auditory feedback is one of the most important feedback in cognitive process. It plays an important guiding role in cognitive motor process. However, previous studies on auditory stimuli mainly focused on the cognitive effects of auditory stimuli on cortex, while the role of auditory feedback stimuli in motor imagery tasks is still unclear.Methods: 18 healthy subjects were recruited to complete the motor imagination task stimulated by meaningful words and meaningless words. In order to explore the role of auditory stimuli in motor imagination tasks, we studied EEG power spectrum, frontal parietal mismatch negativity (MMN) and inter test phase-locked consistency (ITPC). one-way Analysis of Variance (ANOVA) and Least Significant Difference (LSD) correction were used to test the differences between the two experimental groups and the differences of different bands in each experimental group.Results: EEG power spectrum analysis showed that the activity of contralateral motor cortex was significantly increased under the stimulation of meaningful words, and the amplitude of mismatch negative wave was also significantly increased. ITPC is mainly concentrated in μ, α and γ bands in the process of motor imagery task guided by the auditory stimulus of meaningful words, while it is mainly concentrated in the β band under the meaningless words stimulation.Conclusions: This results may be due to the influence of auditory cognitive process on motor imagery. We speculate that there may be a more complex mechanism for the effect of auditory stimulation on the inter test phase lock consistency. When the stimulus sound has the corresponding meaning to the motor action, the parietal motor cortex may be more affected by the prefrontal cognitive cortex, thus changing its normal response mode. This mode change is caused by the joint action of motor imagination, cognitive and auditory stimuli. This study provides a new insight into the neural mechanism of motor imagery task guided by auditory stimuli, and provides more information on the activity characteristics of the brain network in motor imagery task by cognitive auditory feedback.

Effects of Neurofeedback on the Working Memory of Children with Learning Disorders—An EEG Power-Spectrum Analysis

Learning disorders (LDs) are diagnosed in children impaired in the academic skills of reading, writing and/or mathematics. Children with LDs usually exhibit a slower resting-state electroencephalogram (EEG), corresponding to a neurodevelopmental lag. Frequently, children with LDs show working memory (WM) impairment, associated with an abnormal task-related EEG with overall slower EEG activity (more delta and theta power, and less gamma activity in posterior sites). These EEG patterns indicate inefficient neural resource management. Neurofeedback (NFB) treatments aimed at normalizing the resting-state EEG of LD children have shown improvements in cognitive-behavioral indices and diminished EEG abnormalities. Given the typical findings of WM impairment in children with LDs, we aimed to explore the effects of an NFB treatment on the WM of children with LDs by analyzing the WM-related EEG power spectrum. EEGs of 18 children (8–11 y.o.) with LDs were recorded, pre- and post-treatment, during performance of a Sternberg-type WM task. Thirty sessions of an NFB treatment (NFB-group, n = 10) or 30 sessions of a placebo-sham treatment (sham-group, n = 8) were administered. We analyzed the before and after treatment group differences for the behavioral performance and the WM-related EEG power spectrum. The NFB group showed faster response times in the WM task post-treatment. They also exhibited a decreased theta power and increased beta and gamma power at the frontal and posterior sites post-treatment. We explain these findings in terms of NFB improving the efficiency of neural resource management, maintenance of memory representations, and improved subvocal memory rehearsal.

Effects of Neurofeedback in the Working Memory of Children with Learning Disorders: An EEG Power-Spectrum Analysis

Learning disorders (LD) are diagnosed in children impaired in the academic skills of reading, writing and/or mathematics. Children with LD usually show a slower resting-state electroencephalogram (EEG), with EEG patterns corresponding to a neurodevelopmental lag. LD-children also show a consistent cognitive impairment in working memory (WM), including an abnormal task-related EEG with an overall slower EEG activity of more delta and theta power, and less gamma activity in posterior sites; task-related EEG patterns considered indices of an inefficient neural resource management. Neurofeedback (NFB) treatments aimed at normalizing the resting-state EEG of LD-children have shown improvements in cognitive-behavioral indices and diminished EEG abnormalities. Given the typical findings of a WM impairment in LD-children; we aimed to explore the effects of a NFB treatment in the WM of children with LD, by analyzing the WM-related EEG power-spectrum. We recruited 18 children with LD (8-10 years old). They performed a Sternberg-type WM-task synchronized with an EEG of 19 leads (10-20 system) twice in pre-post treatment conditions. They went through either 30 sessions of a NFB treatment (NFB-group, n= 10); or through 30 sessions of a placebo-sham treatment (Sham-group, n= 8). We analyzed the before-after treatment group differences for the behavioral performance and the WM-related power-spectrum. The NFB group showed faster response times in the WM-task post-treatment. They also showed an increased gamma power at posterior sites and a decreased beta power. We explain these findings in terms of NFB improving the maintenance of memory representations coupled with a reduction of anxiety.

Analysis of EEG Characteristics of Drivers at the Entrance and Exit of an Undersea Tunnel and Research on Driving Safety

To study the influence of illumination and longitudinal slope at the entrance and exit of an undersea tunnel on driver EEG characteristics, a real vehicle experiment was performed with the Jiaozhou Bay Undersea Tunnel. The experimental data of a driver’s real vehicle experiment were collected using an illuminance meter, EEG instrument, video recorder and other experimental equipment. The EEG power spectrum was classified according to frequency, the difference between the EEG power spectrum at the entrance and exit sections and other regions was analyzed, and the influence of the illumination and longitudinal slope of the undersea tunnel on the brain activity of drivers was studied. The region near the entrance and exit of the undersea tunnel was divided equidistantly, the changes in the EEG power of the driver during the process of entering and exiting the undersea tunnel were analyzed, and the changes in brain activity and different brain regions during the process were studied. Based on the EEG power, the model of illumination, longitudinal slope and their coupling effect was established. The traffic safety of the entrance and exit of the undersea tunnel was analyzed, and a high-risk driving region was found. The results show that the power spectrum of the entrance and exit sections of the undersea tunnel is obviously different from those of other sections. At 50 m behind the entrance point and 50 m in front of the exit point of the undersea tunnel, the power of the β wave changes rapidly and is at a high level. The consistency between the variation law of the β wave and the variation law of illumination is high. At the entrance and exit of the undersea tunnel, the active regions of the driver’s brain are concentrated in the frontal lobe and occipital lobe.

EEG data might help identify children at risk for social anxiety

Electroencephalography (EEG) is a non-invasive method to monitor the electrical activity of the brain. There are five main broad frequency bands in the EEG power spectrum: alpha, beta, gamma, delta and theta. Data suggest that EEG-derived delta–beta coupling — indicating related activity in the delta and beta frequency bands — might serve as a marker of emotion regulation.

Relating resting EEG power spectra to age-related differences in cognitive performance: An observational pilot study

BackgroundPrevious research has shown that the slope of the electroencephalography (EEG) power spectrum mediates the difference between older and younger adults on a visuo-spatial working memory task. The present study sought to replicate and extend that work using a larger sample and a validated set of neuropsychological tests: The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS).MethodsForty-four participants (21 younger adults, 23 older adults) completed a battery of cognitive and motor tasks that included the RBANS. EEG data were collected both during rest and on-task. Excluding the alpha-band, RBANS scores were regressed onto the slope of the resting EEG power spectrum, controlling for age and using robust mediation analysis.ResultsOlder adults performed reliably lower on the RBANS composite and the Coding, List Recall, List Recognition, and Figure Recall subtests. However, boot-strapped mediation models only showed a mediating effect of the spectral slope on RBANS composite and the Coding subtest.ConclusionsThe resting slope of the EEG power spectrum mediated age-related differences in cognition in the current study, which replicates prior work and is consistent with the neural noise hypothesis of aging. In extending this work, it was shown that these effects are strongest in tasks requiring speeded processing and/or executive functions, whereas this effect was weaker (to absent) for delayed memory, even though age-related differences were present. This pilot study warrants further exploration of the EEG power spectrum in age-related cognitive decline.

Entropy of Chaotic Transitions of EEG Phase Growth in Bipolar Disorder With Lithium Carbonate

The application of chaos theory measures in the association of EEG signals which allows for differentiating pre and postmedicated epochs for bipolar patients. We propose a new approach on positive Schwarzian chaos necessary for a proof of EEG power spectrum of metastability. Shannon entropies of those concealed patterns of positive Schwarzian derivatives from canonical angle transformations of EEG phases from Hilbert transform are compared and found significantly statistical different between pre and post medication periods. Entropy change of chaotic transition measures were compared at first baseline and then at the end of first hour of 300 mg lithium carbonate intake for the same subject in depressive patients. With an application of Schwarzian derivative on the prediction of the von Bertalanffy’s models, integration and segregation of phase growth orbits of neural oscillations can be understood as an influence of chaos on mixing of frequencies. A first order curve-fitting function was performed to determine bifurcation parameter of von Bertalanffy’s model at each given overlapped EEG segment. Schwarzian derivative was positive near the origin which revealed robust chaos. We founded that treatment with Lithium carbonate significantly altered Schwarzian spectrum of chaotic structure and entropy change in Schwarzian amplitudes even though it was not observed in classical EEG power spectrum. Lithium carbonate reduced the strong chaos spectrum of EEG Schwarzian dynamics and removed sharp boundaries in bipolar spectrum.