Comparison of resting electroencephalogram coherence in patients with mild cognitive impairment and normal elderly subjects

Mild cognitive impairment (MCI) was a condition beginning before more serious deterioration, leading to Alzheimer’s dementia (AD). MCI detection was needed to determine the patient's therapeutic management. Analysis of electroencephalogram (EEG) coherence is one of the modalities for MCI detection. Therefore, this study investigated the inter and intra-hemispheric coherence over 16 EEG channels in the frequency range of 1-30 Hz. The simulation results showed that most of the electrode pair coherence in MCI patients have decreased compared to normal elderly subjects. In inter hemisphere coherence, significant differences (p<0.05) were found in the FP1-FP2 electrode pairs. Meanwhile, significant differences (p<0.05) were found in almost all pre-frontal area connectivity of the intra-hemisphere coherence pairs. The electrode pairs were FP2-F4, FP2-T4, FP1-F3, FP1-F7, FP1-C3, FP1-T3, FP1-P3, FP1-T5, FP1-O1, F3-O1, and T3-T5. The decreased coherence in MCI patients showed the disconnection of cortical connections as a result of the death of the neurons. Furthermore, the coherence value can be used as a multimodal feature in normal elderly subjects and MCI. It is hoped that current studies may be considered for early detection of Alzheimer’s in a larger population.

A-31 Distinguishing Neuro-Markers of Math Learning Disability Using EEG Coherence

Objective The current study evaluated brain connectivity in math learning disability (MLD) by examining intra- and interhemispheric electroencephalography (EEG) coherence in three groups of children with differing math profiles. Differential patterns of connectivity were evaluated during “at-rest” conditions and statistically evaluated across three groups. Method Testing occurred in a university laboratory setting. Participants were recruited through media and local agencies serving children with disabilities. The Woodcock Johnson cognitive and achievement tests were used to determine general intelligence and skills across all math achievement subtests. Additionally, 3-minute eye-closed EEG resting data was collected. Groups used in the current study were: neurotypical controls (NC) (n = 30), math learning disability (MLD) (n = 15), and lower achievement (LA) (n = 15). Participants’ mean age was 9.58 (SD = 1.38) with 53.3% being male. Results Intrahemispheric comparisons suggest MLD children demonstrated reduced left hemispheric coherence to NC’s (p = 0.006), not seen in LA children. Additionally, NC’s had greater beta coherence (p = 0.002). Interhemispheric analyses revealed the MLD group had reduced alpha occipital coherence compared to the LA group (p = 0.031). Conclusion The current study provides supporting evidence for implicating brain connectivity as an underlying cause of MLD. Specifically, left hemispheric differences in delta coherence were found in children with MLD not observed in children with LA profiles. Weaknesses in areas of visuo-spatial integration in the MLD group were also observed. Results suggest atypical patterns of brain connectivity in the default-mode network (DMN) in delta wavelengths may serve as a useful biomarker of MLD.

EEG Coherence During Resting State Over Frontal Regions in Paranormal Beliefs

Introduction: Paranormal beliefs are defined as believing in extrasensory perception, precognition, witchcraft, and telekinesis, magical thinking, psychokinesis, superstitions. Previous studies corroborate that executive brain functions underpin paranormal beliefs. To test causal hypotheses, neurophysiological studies of brain activity are required. Method: A sample of 20 students (10 females, age: 22.50 ± 4.07 years) were included for the current study. The absolute power of resting-state EEG in intrahemispheric and interhemispheric coherence was analyzed with eyes opened. The paranormal beliefs were determined based on the total score of the Revised Paranormal Belief Scale (RPBS). Result: The results of this study demonstrated that there was a significant negative relationship between paranormal beliefs and EEG resting state in alpha band activity in the frontal lobe (left hemisphere), EEG coherence of alpha and beta1, beta2, and gamma band activities in the frontal lobe (right hemisphere) and coherence of alpha and beta1, beta2 and gamma band activities between frontal regions (two hemispheres). In addition, the results showed that coherence of alpha, alpha1, beta, and beta2 band activities between frontal lobe (right hemispheres) and EEG coherence of delta, alpha1, and band activities in the frontal lobe (two hemispheres) predicted paranormal beliefs. Conclusion: This study confirms connecting executive brain functions to paranormal beliefs, and determines that frontal brain functioning may contribute to paranormal beliefs.

EEG Coherence Analysis for Suppression of MEP Amplitude Variability in TMS

Transcranial magnetic stimulation (TMS) is a non-invasive stimulation method for cortical neurons. When TMS is delivered to the primary motor cortex (M1), motor evoked potentials can be measured in electromyograms for the peripheral muscle. However, the motor-evoked potential (MEP) amplitudes measured by stimulations for M1 fluctuated from trial to trial. MEP fluctuations are caused by changes in cortical excitability. We hypothesized that MEP variability could be suppressed with application of TMS when cortical excitability was stable. Thus, we developed a TMS system to suppress MEP amplitude variabilities. We used electroencephalographic (EEG) online measurements with coherence analysis to obtain the similarity of cortical excitabilities. The system enables us to trigger TMS if the EEGs measured from the two channels have a high similarity in the frequency domain. In this study, we found that the suppression of MEP fluctuation was dependent on the state of cortical excitability obtained by EEG coherence analysis.

EEG Patterns and Performance When Facing the Cardinal Directions

1) Background and Objectives: Position in space and passage of time are encoded in the firing of thalamic, hippocampal and entorhinal cortices in rodents. Head direction cells have been reported in freely moving monkeys, and differential brain patterns have been observed in humans while playing a navigation video game and in response to changes in electromagnetic fields. The sensitivity of organisms to environmental and electromagnetic cues could explain recommendations from a traditional system of architecture, Vastu architecture, which recommends aligning homes to the cardinal directions. 2) Hypothesis: Vastu architecture predicts that facing east and north are more advantageous than facing west and south. If facing east and north are more advantageous, then subjects should show distinct EEG patterns and improved performance when facing east and north compared to west or south. 3) Materials and Methods: EEG coherence patterns from 32-channel EEG and time-to-complete jigsaw puzzles were compared while subjects faced the four cardinal directions. 4) Results: When facing east and north, subjects’ frontal beta2 and gamma EEG coherence were significantly higher, and they assembled jigsaw puzzles significantly faster than when facing west or south. 5) Discussion: The brain findings fit the performance data. Better focus, which would reasonably be related with faster performance, is associated with higher levels of beta2 and gamma coherence. 6) Conclusion: These data support the possibility that the human brain may be sensitive to cardinal directions. This highlights how intimately we are connected to the environment and suggests a factor that may be important in orienting work spaces and designing class rooms.

Research on Differential Brain Networks before and after WM Training under Different Frequency Band Oscillations

Previous studies have shown that different frequency band oscillations are associated with cognitive processing such as working memory (WM). Electroencephalogram (EEG) coherence and graph theory can be used to measure functional connections between different brain regions and information interaction between different clusters of neurons. At the same time, it was found that better cognitive performance of individuals indicated stronger small-world characteristics of resting-state WM networks. However, little is known about the neural synchronization of the retention stage during ongoing WM tasks (i.e., online WM) by training on the whole-brain network level. Therefore, combining EEG coherence and graph theory analysis, the present study examined the topological changes of WM networks before and after training based on the whole brain and constructed differential networks with different frequency band oscillations (i.e., theta, alpha, and beta). The results showed that after WM training, the subjects’ WM networks had higher clustering coefficients and shorter optimal path lengths than before training during the retention period. Moreover, the increased synchronization of the frontal theta oscillations seemed to reflect the improved executive ability of WM and the more mature resource deployment; the enhanced alpha oscillatory synchronization in the frontoparietal and fronto-occipital regions may reflect the enhanced ability to suppress irrelevant information during the delay and pay attention to memory guidance; the enhanced beta oscillatory synchronization in the temporoparietal and frontoparietal regions may indicate active memory maintenance and preparation for memory-guided attention. The findings may add new evidence to understand the neural mechanisms of WM on the changes of network topological attributes in the task-related mode.