scholarly journals A Pilot Study Investigating a Novel Non-Linear Measure of Eyes Open versus Eyes Closed EEG Synchronization in People with Alzheimer’s Disease and Healthy Controls

2018 ◽  
Vol 8 (7) ◽  
pp. 134 ◽  
Author(s):  
Daniel Blackburn ◽  
Yifan Zhao ◽  
Matteo De Marco ◽  
Simon Bell ◽  
Fei He ◽  
...  
Keyword(s):  
Pilot Study ◽  
Resting State ◽  
Low Cost ◽  
Linear Measure ◽  
Ageing Population ◽  
Healthy Controls ◽  
Causality Test ◽  
Non Invasive ◽  
Eyes Closed ◽  
Eyes Open

Background: The incidence of Alzheimer disease (AD) is increasing with the ageing population. The development of low cost non-invasive diagnostic aids for AD is a research priority. This pilot study investigated whether an approach based on a novel dynamic quantitative parametric EEG method could detect abnormalities in people with AD. Methods: 20 patients with probable AD, 20 matched healthy controls (HC) and 4 patients with probable fronto temporal dementia (FTD) were included. All had detailed neuropsychology along with structural, resting state fMRI and EEG. EEG data were analyzed using the Error Reduction Ratio-causality (ERR-causality) test that can capture both linear and nonlinear interactions between different EEG recording areas. The 95% confidence intervals of EEG levels of bi-centroparietal synchronization were estimated for eyes open (EO) and eyes closed (EC) states. Results: In the EC state, AD patients and HC had very similar levels of bi-centro parietal synchronization; but in the EO resting state, patients with AD had significantly higher levels of synchronization (AD = 0.44; interquartile range (IQR) 0.41 vs. HC = 0.15; IQR 0.17, p < 0.0001). The EO/EC synchronization ratio, a measure of the dynamic changes between the two states, also showed significant differences between these two groups (AD ratio 0.78 versus HC ratio 0.37 p < 0.0001). EO synchronization was also significantly different between AD and FTD (FTD = 0.075; IQR 0.03, p < 0.0001). However, the EO/EC ratio was not informative in the FTD group due to very low levels of synchronization in both states (EO and EC). Conclusion: In this pilot work, resting state quantitative EEG shows significant differences between healthy controls and patients with AD. This approach has the potential to develop into a useful non-invasive and economical diagnostic aid in AD.

scholarly journals The effect of congenital blindness on resting-state functional connectivity revisited

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Maria J. S. Guerreiro ◽  
Madita Linke ◽  
Sunitha Lingareddy ◽  
Ramesh Kekunnaya ◽  
Brigitte Röder
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Visual Experience ◽  
Brain Regions ◽  
State Condition ◽  
Resting State Functional Connectivity ◽  
Congenital Blindness ◽  
Eyes Closed ◽  
Congenitally Blind ◽  
Eyes Open

AbstractLower resting-state functional connectivity (RSFC) between ‘visual’ and non-‘visual’ neural circuits has been reported as a hallmark of congenital blindness. In sighted individuals, RSFC between visual and non-visual brain regions has been shown to increase during rest with eyes closed relative to rest with eyes open. To determine the role of visual experience on the modulation of RSFC by resting state condition—as well as to evaluate the effect of resting state condition on group differences in RSFC—, we compared RSFC between visual and somatosensory/auditory regions in congenitally blind individuals (n = 9) and sighted participants (n = 9) during eyes open and eyes closed conditions. In the sighted group, we replicated the increase of RSFC between visual and non-visual areas during rest with eyes closed relative to rest with eyes open. This was not the case in the congenitally blind group, resulting in a lower RSFC between ‘visual’ and non-‘visual’ circuits relative to sighted controls only in the eyes closed condition. These results indicate that visual experience is necessary for the modulation of RSFC by resting state condition and highlight the importance of considering whether sighted controls should be tested with eyes open or closed in studies of functional brain reorganization as a consequence of blindness.

scholarly journals Resting state connectivity differences in eyes open versus eyes closed conditions

2019 ◽  
Vol 40 (8) ◽  
pp. 2488-2498 ◽  
Author(s):  
Oktay Agcaoglu ◽  
Tony W. Wilson ◽  
Yu‐Ping Wang ◽  
Julia Stephen ◽  
Vince D. Calhoun
Keyword(s):  
Resting State ◽  
Eyes Closed ◽  
Eyes Open ◽  
Open Versus ◽  
Resting State Connectivity

Assessing the Retest Reliability of Prefrontal EEG Markers of Brain Rhythm Slowing in the Eyes-Closed Resting State

2020 ◽  
Vol 51 (5) ◽  
pp. 348-356 ◽  
Author(s):  
Jungmi Choi ◽  
Eunjo Lim ◽  
Min-Goo Park ◽  
Wonseok Cha
Keyword(s):  
Resting State ◽  
Brain Aging ◽  
Low Cost ◽  
Peak Frequency ◽  
Brain Regions ◽  
Median Frequency ◽  
Brain Functions ◽  
Eyes Closed ◽  
Alpha Beta ◽  
Prefrontal Lobe

Objective. We examined whether prefrontal lobe EEG markers of slower brain rhythms, which are correlated with functional brain aging, can reliably reflect those of other brain lobes, as measured by a multichannel device. Methods. EEG measurements were taken of 112 healthy individuals aged 20 to 69 years in the eyes-closed resting state. A 5-minute measurement was taken at 8 regions (Fp1, Fp2, F3, F4, T3, T4, O1, O2). Indices (median frequency [MDF], peak frequency [PF]) that quantitatively reflect the characteristics of EEG slowing, and traditional commonly used spectral indices (absolute powers as delta, theta, alpha, beta, and relative power as alpha-to-theta ratio [ATR]), were extracted from the EEG signals. For these indices, the differences between the prefrontal lobe and other areas were analyzed and the test-retest reproducibility was investigated. Results. The EEG slowing indicators showed high conformity over all brain lobes and stable reproducibility. On the other hand, the typical EEG spectral indicators delta, theta, alpha, beta, and ATR differed between brain regions. Conclusion. It was found that EEG slowing markers, which were used for assessing the aging or degeneration of brain functions, could be reliably extracted from a prefrontal EEG alone. Significance. These findings suggest that EEG prefrontal markers may reflect markers of other brain regions when a multi-channel device is used. Thus, this method may constitute a low-cost, wearable, wireless, easily accessible, and noninvasive tool for neurological assessment that could be used in the early detection of cognitive decline and in the prevention of dementia.

scholarly journals Dynamic Resting-State Connectivity Differences in Eyes Open Versus Eyes Closed Conditions

2020 ◽  
Vol 10 (9) ◽  
pp. 504-519
Author(s):  
Oktay Agcaoglu ◽  
Tony W. Wilson ◽  
Yu-Ping Wang ◽  
Julia M. Stephen ◽  
Vince D. Calhoun
Keyword(s):  
Resting State ◽  
Eyes Closed ◽  
Eyes Open ◽  
Open Versus ◽  
Resting State Connectivity

scholarly journals Recognition of Biomarkers of Brain Connectivity and Pain Using Multi-Modal Imaging in Patients with Sickle Cell Disease

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 971-971
Author(s):  
Michelle Case ◽  
Clara Zhang ◽  
John Mundahl ◽  
Yvonne Datta ◽  
Stephen C Nelson ◽  
...  
Keyword(s):  
Chronic Pain ◽  
Sickle Cell Disease ◽  
Resting State ◽  
Brain Function ◽  
Brain Connectivity ◽  
Fmri Data ◽  
Healthy Controls ◽  
Cell Disease ◽  
Non Invasive ◽  
Microstate Analysis

Abstract Sickle cell disease (SCD) is associated with impaired cognitive function, pain, cerebral stroke and other neural dysfunctions suggestive of altered brain function. The most common reason for hospitalization of SCD patients is pain. Sickle pain is unique compared to other clinical pain conditions because it includes chronic pain as well as acute pain due to vasoocclusive crisis. The neuropathic and nociceptive aspects of pain in SCD make pain treatment challenging. Opioids, the most common analgesics, are associated with liabilities, such as addiction and tolerance. As a result, patients are often under-treated because of a lack of an objective pain measurement system. We therefore sought to develop an unbiased pain quantification method using non-invasive imaging techniques to recognize the biomarkers of pain and altered brain function. We examined the brain network connectivity in SCD patients (N=14) and healthy controls (N=13) to identify altered activity between the two groups that can be used as biomarkers for chronic pain. All experimental procedures were approved by the IRB of the University of Minnesota, and all subjects gave written informed consent before participating in the study. Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) were simultaneously recorded while the subjects were in a wakeful resting state. A 3T Siemens Trio whole-body scanner and a 16 channel head coil with an echo-planar imaging (EPI) sequence were used to acquire fMRI data. EEG data was recorded using a 64-channel EEG cap and MR-compatible amplifiers. Seed-based region of interest (ROI) analysis was performed on the fMRI data using Brain Voyager QX software. EEG informed fMRI (EEG-fMRI) was performed for power and microstate analysis using Matlab and SPM8 software. Statistical activation maps (p<0.001, uncorrected) were generated from general linear models (GLM) based on the time courses found from power and microstate analysis. Seeds were placed in the insula regions, and the functional connectivity between the left and right insula appeared to be stronger in SCD patients than in healthy controls. This result was verified in EEG-fMRI analysis. Activation of the insula and striatum regions positively correlated with the beta band in SCD patients, where healthy controls showed less activation in the insula in the same frequency band. Microstates corresponding to insula activation were observed in both healthy controls and SCD patients; however, activation seems stronger in SCD patients. Activation in the striatum regions was also observed in microstates for SCD patients, but not for healthy controls. These results show that the insula and striatum regions have greater activation in SCD patients compared to controls, and that patients have altered brain connectivity during resting state. Insula activation could be related to the salience network, a resting state network that is responsible for processing external input, or to pain processing. The insula and striatum are some of the common brain regions that have been shown to be active during painful stimuli. This altered activation could be caused by sickle pain and could be a potential biomarker of pain intensity. Due to the non-invasive nature of these quantitative data, this method can have applications in the unbiased objective quantification of pain and treatment outcomes. Altered connectivity observed in SCD patients can also be used to help better understand the neural pathophysiology of sickle pain and can lead to better management strategies for these patients. This work was supported in part by NIH grant U01-HL117664 and NSF IGERT grant DGE-1069104. Disclosures No relevant conflicts of interest to declare.

scholarly journals Validation of melomind™ signal quality: a proof of concept resting-state and ERPs study

2020 ◽  
Author(s):  
Giuseppe Spinelli ◽  
Alexandre Odouard ◽  
Marie-Cécile Nierat ◽  
Sébastien Campion ◽  
Mickael Bensoussan ◽  
...  
Keyword(s):  
Resting State ◽  
Signal To Noise Ratio ◽  
Cognitive Tasks ◽  
Signal Quality ◽  
Visual Responses ◽  
Cortical Dynamics ◽  
Oddball Task ◽  
Eyes Closed ◽  
Two Systems ◽  
Eyes Open

AbstractWearable EEG systems have become accessible to researchers and clinicians over the last decade, thus requiring neurotechnology companies to seek for outstanding EEG signal quality. Here, we show that the melomind™ headset equipped with dry electrodes (myBrain Technologies, Paris, France) allows the recording of reliable electro-cortical dynamics as compared to a wet-based standard-EEG system (actiCAP, Brain Products GmbH, Gilching, Germany). EEGs were acquired simultaneously from the two systems while thirteen subjects underwent a visual oddball, a steady-state visually-evoked potentials (SSVEPs) and two resting-state (RS) tasks. RS were acquired with eyes-closed and eyes-open (2 minutes each) and repeated twice (before and after the cognitive tasks). During the oddball task, participants responded on a gamepad when a target-stimulus was displayed. In the SSVEPs, visual responses were elicited at 15 and 20 Hz through a series of 15-second stimuli presented 5 times each. The power of theta- [4-8 Hz], alpha- [8-13 Hz], and beta- [13-30 Hz] band was extracted from the two RS. The signal-to-noise-ratio in the 15 (± 1) and 20 (± 1) Hz range was computed from the SSVEPs. The shape of the N2/P300 complex was analysed from the oddball task. Strong correlations resulted between the parameters obtained from the two EEG systems (0.53 < Pearson’s r < 0.97). Bland and Altman analysis revealed small dissimilarities between the two systems, with values laying in the 95% confidence interval in all the tasks. Our results demonstrate that the melomind™ is an affordable solution to reliably assess humans’ electro-cortical dynamics at-rest and during cognitive tasks, thus paving the way to its use in neuroscience studies and brain-computer interfaces.

scholarly journals Template-based prediction of vigilance fluctuations in resting-state fMRI

2017 ◽  
Author(s):  
Maryam Falahpour ◽  
Catie Chang ◽  
Chi Wah Wong ◽  
Thomas T. Liu
Keyword(s):  
Resting State ◽  
Brain Connectivity ◽  
Resting State Fmri ◽  
Fmri Data ◽  
Eyes Closed ◽  
Vigilance State ◽  
Global Signal ◽  
Significant Difference ◽  
Eyes Open ◽  
Positive Correlations

AbstractChanges in vigilance or alertness during a typical resting state fMRI scan are inevitable and have been found to affect measures of functional brain connectivity. Since it is not often feasible to monitor vigilance with EEG during fMRI scans, it would be of great value to have methods for estimating vigilance levels from fMRI data alone. A recent study, conducted in macaque monkeys, proposed a template-based approach for fMRI-based estimation of vigilance fluctuations. Here, we use simultaneously acquired EEG/fMRI data to investigate whether the same template-based approach can be employed to estimate vigilance fluctuations of awake humans across different resting-state conditions. We first demonstrate that the spatial pattern of correlations between EEG-defined vigilance and fMRI in our data is consistent with the previous literature. Notably, however, we observed a significant difference between the eyes-closed (EC) and eyes-open (EO) conditions finding stronger negative correlations with vigilance in regions forming the default mode network and higher positive correlations in thalamus and insula in the EC condition when compared to the EO condition. Taking these correlation maps as “templates” for vigilance estimation, we found that the template-based approach produced fMRI-based vigilance estimates that were significantly correlated with EEG-based vigilance measures, indicating its generalizability from macaques to humans. We also demonstrate that the performance of this method was related to the overall amount of variability in a subject’s vigilance state, and that the template-based approach outperformed the use of the global signal as a vigilance estimator. In addition, we show that the template-based approach can be used to estimate the variability across scans in the amplitude of the vigilance fluctuations. We discuss the benefits and tradeoffs of using the template-based approach in future fMRI studies.

scholarly journals Use of Stabilometric Platform and Evaluation of Methods for Further Measurments – A Pilot Study

2007 ◽  
Vol 50 (2) ◽  
pp. 139-143 ◽  
Author(s):  
Jitka Jančová ◽  
Vlasta Tošnerová
Keyword(s):  
Pilot Study ◽  
Center Of Pressure ◽  
Quiet Standing ◽  
Parallel Testing ◽  
Eyes Closed ◽  
Eyes Open ◽  
Single Force ◽  
Test Retest Reliability ◽  
Evaluation Of Methods ◽  
Anterior Posterior

Posture in a still stance has been quantified by changes in the center of pressure (COP), in both anterior-posterior (A/P) and medial-lateral (M/L) directions and measured on a single force platform (Bertec PRO VEC 5.0). The purpose of this study was to estimate the variance in error and the intrasession test-retest reliability, and to determine which measures shall be taken for further measurements, especially with adults age 65 and older. We used two types of approximation for the reliability coefficient. Firstly, we used the equation according to Blahuš (2) and secondly we used the Pearson’s correlation coefficient for test-retest measurements. The findings allow us to say, among other things, that the tests of quiet standing Double Narrow Stance Eyes Open (DNSEO) and Double Narrow Stance Eyes Closed (DNSEC) are parallel, in the sense of parallel testing.

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