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

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.

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

Scientific Reports ◽

10.1038/s41598-021-91976-9 ◽

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.

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Resting-state MEG measurement of functional activation as a biomarker for cognitive decline in MS

Multiple Sclerosis Journal ◽

10.1177/1352458518810260 ◽

2018 ◽

Vol 25 (14) ◽

pp. 1896-1906 ◽

Cited By ~ 4

Author(s):

Deborah N Schoonhoven ◽

Matteo Fraschini ◽

Prejaas Tewarie ◽

Bernard MJ Uitdehaag ◽

Anand JC Eijlers ◽

...

Keyword(s):

Cognitive Impairment ◽

Resting State ◽

Brain Function ◽

Peak Frequency ◽

Cognitively Impaired ◽

Clinical Neurology ◽

Linear Regression Models ◽

Eyes Closed ◽

Gender And Education ◽

Cognitive Disturbances

Background: Neurophysiological measures of brain function, such as magnetoencephalography (MEG), are widely used in clinical neurology and have strong relations with cognitive impairment and dementia but are still underdeveloped in multiple sclerosis (MS). Objectives: To demonstrate the value of clinically applicable MEG-measures in evaluating cognitive impairment in MS. Methods: In eyes-closed resting-state, MEG data of 83 MS patients and 34 healthy controls (HCs) peak frequencies and relative power of six canonical frequency bands for 78 cortical and 10 deep gray matter (DGM) areas were calculated. Linear regression models, correcting for age, gender, and education, assessed the relation between cognitive performance and MEG biomarkers. Results: Increased alpha1 and theta power was strongly associated with impaired cognition in patients, which differed between cognitively impaired (CI) patients and HCs in bilateral parietotemporal cortices. CI patients had a lower peak frequency than HCs. Oscillatory slowing was also widespread in the DGM, most pronounced in the thalamus. Conclusion: There is a clinically relevant slowing of neuronal activity in MS patients in parietotemporal cortical areas and the thalamus, strongly related to cognitive impairment. These measures hold promise for the application of resting-state MEG as a biomarker for cognitive disturbances in MS in a clinical setting.

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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

Brain Sciences ◽

10.3390/brainsci8070134 ◽

2018 ◽

Vol 8 (7) ◽

pp. 134 ◽

Cited By ~ 6

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.

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Effective brain connectivity estimation between active brain regions in autism using the dual Kalman-based method

Biomedical Engineering / Biomedizinische Technik ◽

10.1515/bmt-2019-0062 ◽

2020 ◽

Vol 65 (1) ◽

pp. 23-32

Author(s):

Mehdi Rajabioun ◽

Ali Motie Nasrabadi ◽

Mohammad Bagher Shamsollahi ◽

Robert Coben

Keyword(s):

Resting State ◽

Brain Connectivity ◽

Effective Connectivity ◽

Estimation Error ◽

Brain Regions ◽

Estimation Methods ◽

Estimation Errors ◽

Normal Children ◽

Brain Functions ◽

The Brain

AbstractBrain connectivity estimation is a useful method to study brain functions and diagnose neuroscience disorders. Effective connectivity is a subdivision of brain connectivity which discusses the causal relationship between different parts of the brain. In this study, a dual Kalman-based method is used for effective connectivity estimation. Because of connectivity changes in autism, the method is applied to autistic signals for effective connectivity estimation. For method validation, the dual Kalman based method is compared with other connectivity estimation methods by estimation error and the dual Kalman-based method gives acceptable results with less estimation errors. Then, connectivities between active brain regions of autistic and normal children in the resting state are estimated and compared. In this simulation, the brain is divided into eight regions and the connectivity between regions and within them is calculated. It can be concluded from the results that in the resting state condition the effective connectivity of active regions is decreased between regions and is increased within each region in autistic children. In another result, by averaging the connectivity between the extracted active sources of each region, the connectivity between the left and right of the central part is more than that in other regions and the connectivity in the occipital part is less than that in others.

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Evaluating the Contribution of EEG Power Profiles to Characterize and Discriminate Posttraumatic Stress Symptom Factors in a Combat-Exposed Population

Clinical EEG and Neuroscience ◽

10.1177/1550059418767583 ◽

2018 ◽

Vol 49 (6) ◽

pp. 379-387 ◽

Cited By ~ 3

Author(s):

Christina M. Sheerin ◽

Laura M. Franke ◽

Steven H. Aggen ◽

Ananda B. Amstadter ◽

William C. Walker

Keyword(s):

Posttraumatic Stress ◽

Resting State ◽

Ptsd Symptom ◽

Factor Model ◽

Common Factor ◽

Frequency Bands ◽

Eyes Closed ◽

Exposed Population ◽

Theta Frequency ◽

Alpha Beta

This study investigated the use of resting-state electroencephalography (EEG) data to help differentiate posttraumatic stress disorder (PTSD) symptom factors. The sample, 147 combat-exposed OIF/OEF (Operation Iraqi Freedom/Operation Enduring Freedom) Veterans and service members, was a polytrauma population with variable PTSD and mild traumatic brain injury (mTBI) diagnoses. Participants completed the PTSD Checklist (PCL) and resting-state EEG was assessed for 10 minutes, with eyes closed. Regional averages of absolute power in alpha, beta, delta, and theta frequency bands were computed to estimate a single EEG common factor per band. An oblique 4 common-factor model was then fit to the 17 PCL items that included a residual EEG factor as an exogenous predictor with the group mean effect of mTBI on the EEG factor removed. Separate comparative model testing sequences for the alpha, beta, delta, and theta EEG factor frequency bands were conducted. An inverse relationship of delta and theta frequency bands on avoidance and numbing symptom factors (but not re-experiencing and hyperarousal) was found. Results provide evidence for possible neurobiological basis for the 4 PTSD symptom factors.

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Modulatory Interactions between the Default Mode Network and Task Positive Networks in Resting-State

10.7287/peerj.preprints.124v1 ◽

2013 ◽

Author(s):

Xin Di ◽

Bharat B. Biswal

Keyword(s):

Basal Ganglia ◽

Functional Connectivity ◽

Default Mode Network ◽

Resting State ◽

Brain Networks ◽

Brain Regions ◽

Salience Network ◽

Imaging Data ◽

Default Mode ◽

Brain Functions

Communications between different brain systems are critical to support complex brain functions. Unlike generally high functional connectivity between brain regions from same system, functional connectivity between regions from different systems are more variable. In the present study, we examined whether the connectivity between different brain networks were modulated by other regions by using physiophysiological interaction (PPI) on resting-state functional magnetic resonance imaging data. Spatial independent component analysis was first conducted to identify the default mode network (DMN) and several task positive networks, including the salience, dorsal attention, left and right executive networks. PPI analysis was conducted between pairs of these networks to identify networks or regions that showed modulatory interactions with the two networks. Network-wise analysis revealed reciprocal modulatory interactions between the DMN, salience, and executive networks. Together with the anatomical properties of the salience network regions, the results suggest that the salience network may modulate the relationship between the DMN and executive networks. In addition, voxel-wise analysis demonstrated that the basal ganglia and thalamus positively interacted with the salience network and the dorsal attention network, and negatively interacted with the salience network and the DMN. The results demonstrated complex relationships among brain networks in resting-state, and suggested that between network communications of these networks may be modulated by some critical brain structures such as the salience network, basal ganglia, and thalamus.

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Interhemispheric Integration for Complex Behaviors, Absent the Corpus Callosum in Normal Ontogeny

10.1101/271072 ◽

2018 ◽

Author(s):

Elliot A. Layden ◽

Kathryn E. Schertz ◽

Sarah E. London ◽

Marc G. Berman

Keyword(s):

White Matter ◽

Functional Connectivity ◽

Corpus Callosum ◽

Zebra Finch ◽

Resting State ◽

Hemispheric Specialization ◽

Resting State Fmri ◽

Brain Regions ◽

Human Language ◽

Brain Functions

AbstractFunctional homotopy, or synchronous spontaneous activity between symmetric, contralateral brain regions, is a fundamental characteristic of the mammalian brain’s functional architecture(1–6). In mammals, functional homotopy may be predominantly mediated by the corpus callosum (CC), a white matter structure thought to balance the interhemispheric coordination and hemispheric specialization critical for many complex brain functions, including lateralized human language abilities(7, 8). The CC first emerged with the Eutherian (placental) mammals ~160 MYA and is not found in other vertebrates(9, 10). Despite this, other vertebrates also exhibit complex brain functions requiring bilateral integration and lateralization(11). For example, much as humans acquire speech, the zebra finch (Taeniopygia guttata) songbird learns to sing from tutors and must balance hemispheric specialization(12) with interhemispheric coordination to successfully learn and produce song(13). We therefore tested whether the zebra finch brain also exhibits functional homotopy despite lacking the CC. Implementing custom resting-state fMRI (rs-fMRI) functional connectivity (FC) analyses, we demonstrate widespread functional homotopy between pairs of contralateral brain regions required for learned song but which lack direct anatomical projections (i.e., structural connectivity; SC). We believe this is the first demonstration of functional homotopy in a non-Eutherian vertebrate; however, it is unlikely to be the only instance of it. The remarkable congruence between functional homotopy in the zebra finch and Eutherian brains indicates that alternative mechanisms must exist for balanced interhemispheric coordination in the absence of a CC. This insight may have broad implications for understanding complex, bilateral neural processing across phylogeny and how information is integrated between hemispheres.Significance StatementThe mammalian brain exhibits strongly synchronized hemodynamic activity (i.e., functional connectivity) between symmetric, contralateral (i.e., homotopic) brain regions. This pattern is thought to be largely mediated by the corpus callosum (CC), a large white matter tract unique to mammals, which balances interhemispheric coordination and lateralization. Many complex brain functions, including human language, are thought to critically rely upon this balance. Despite lacking the CC, the zebra finch exhibits a song learning process with striking parallels to human speech acquisition, including lateralization and interhemispheric coordination. Using resting-state fMRI, we show that the zebra finch brain exhibits widespread homotopic functional connectivity within a network critical for learned song, suggesting that this symmetrical activity pattern may phylogenetically precede the evolution of the CC.

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Individual alpha peak frequency is slower in schizophrenia and related to deficits in visual perception and cognition

Scientific Reports ◽

10.1038/s41598-021-97303-6 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Ian S. Ramsay ◽

Peter Lynn ◽

Brandon Schermitzler ◽

Scott Sponheim

Keyword(s):

Visual Perception ◽

Visual Attention ◽

Resting State ◽

Peak Frequency ◽

Attention Task ◽

Eyes Closed ◽

Global Cognition ◽

The Relationship ◽

The Brain ◽

Alpha Peak

AbstractThe brain at rest generates cycles of electrical activity that have been shown to be abnormal in people with schizophrenia. The alpha rhythm (~ 10 Hz) is the dominant resting state electrical cycle and each person has a propensity toward a particular frequency of oscillation for this rhythm. This individual alpha peak frequency (IAPF) is hypothesized to be central to visual perceptual processes and may have downstream influences on cognitive functions such as attention, working memory, or problem solving. In the current study we sought to determine whether IAPF was slower in schizophrenia, and whether lower IAPF predicted deficits in visual perception and cognition that are often observed in schizophrenia. Eyes-closed resting state EEG activity, visual attention, and global cognitive functioning were assessed in individuals with schizophrenia (N = 104) and a group of healthy controls (N = 101). Compared to controls, the schizophrenia group showed slower IAPF and was associated with poorer discrimination of visual targets and nontargets on a computerized attention task, as well as impaired global cognition measured using neuropsychological tests across groups. Notably, disruptions in visual attention fully mediated the relationship between IAPF and global cognition across groups. The current findings demonstrate that slower alpha oscillatory cycling accounts for global cognitive deficits in schizophrenia by way of impairments in perceptual discrimination measured during a visual attention task.

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Duration of the Symptoms and Brain Aging in Women with Fibromyalgia: A Cross-Sectional Study

Applied Sciences ◽

10.3390/app9102106 ◽

2019 ◽

Vol 9 (10) ◽

pp. 2106 ◽

Cited By ~ 2

Author(s):

Santos Villafaina ◽

Daniel Collado-Mateo ◽

Juan P. Fuentes-García ◽

Francisco J. Domínguez-Muñoz ◽

Narcís Gusi

Keyword(s):

Resting State ◽

Exploratory Study ◽

Brain Aging ◽

Cross Sectional Study ◽

Sectional Study ◽

Cross Sectional ◽

Duration Of Symptoms ◽

Theta Power ◽

Alpha Beta ◽

First Time

Fibromyalgia is a chronic syndrome that is characterized by widespread pain and an altered brain dynamic. The aim of this study was to analyze the effect of the duration of the symptoms on the cortical activity of women with fibromyalgia using electroencephalogram power spectrum analyses in an eye-closed resting state. Twenty-nine women participated in this cross-sectional study (N: 29; age: 55.59 [9.50]). Theta, alpha, beta-1, beta-2, and beta-3 frequency bands were analyzed using EEGLAB. Theta power significantly correlated with the duration of the symptoms, but not with age. In addition, participants were divided into two groups according to number the years for which they were suffering from fibromyalgia. Participants who had a longer duration of symptoms obtained higher theta power in the frontal (Fp1, F4, F7, F8, and Fz), central (C3, C4, and Cz), and parietal (P3 and Pz) areas than those who had a shorter duration of symptoms, which may be related to brain aging. This exploratory study demonstrates for the first time that the frontal, central, and parietal areas may be influenced by the years in which they were suffering from the symptoms of fibromyalgia. This might indicate that the duration of these symptoms may have a higher impact on brain aging than the actual age of the patient.

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Comparison of resting-state EEG between adults with Down syndrome and typically developing controls

Journal of Neurodevelopmental Disorders ◽

10.1186/s11689-021-09392-z ◽

2021 ◽

Vol 13 (1) ◽

Author(s):

Sarah Hamburg ◽

Daniel Bush ◽

Andre Strydom ◽

Carla M. Startin

Keyword(s):

Down Syndrome ◽

Cognitive Decline ◽

Resting State ◽

Peak Frequency ◽

Peak Amplitude ◽

Typically Developing ◽

Eyes Closed ◽

Eeg Spectrum ◽

Beta Power ◽

Diagnosis Of Dementia

Abstract Background Down syndrome (DS) is the most common genetic cause of intellectual disability (ID) worldwide. Understanding electrophysiological characteristics associated with DS provides potential mechanistic insights into ID, helping inform biomarkers and targets for intervention. Currently, electrophysiological characteristics associated with DS remain unclear due to methodological differences between studies and inadequate controls for cognitive decline as a potential cofounder. Methods Eyes-closed resting-state EEG measures (specifically delta, theta, alpha, and beta absolute and relative powers, and alpha peak amplitude, frequency and frequency variance) in occipital and frontal regions were compared between adults with DS (with no diagnosis of dementia or evidence of cognitive decline) and typically developing (TD) matched controls (n = 25 per group). Results We report an overall ‘slower’ EEG spectrum, characterised by higher delta and theta power, and lower alpha and beta power, for both regions in people with DS. Alpha activity in particular showed strong group differences, including lower power, lower peak amplitude and greater peak frequency variance in people with DS. Conclusions Such EEG ‘slowing’ has previously been associated with cognitive decline in both DS and TD populations. These findings indicate the potential existence of a universal EEG signature of cognitive impairment, regardless of origin (neurodevelopmental or neurodegenerative), warranting further exploration.

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