Deficit Versus Nondeficit Schizophrenia: An MEG-EEG Investigation of Resting State and Source Coherence—Preliminary Data

2019 ◽  
Vol 51 (1) ◽  
pp. 34-44 ◽  
Author(s):  
Klevest Gjini ◽  
Susan M. Bowyer ◽  
Frank Wang ◽  
Nash N. Boutros
Keyword(s):  
Spectral Analysis ◽  
Resting State ◽  
Low Frequency ◽  
Source Analysis ◽  
Beta Band ◽  
Source Imaging ◽  
Low Frequencies ◽  
Deficit Syndrome ◽  
Beta Frequency Band ◽  
Eeg Recordings

This study investigated the magneto- and electroencephalography (MEG and EEG, respectively) resting state to identify the deviations closely associated with the deficit syndrome (DS) in schizophrenia patients. Ten subjects in each group (control, DS, and nondeficit schizophrenia [NDS]) were included. Subjects underwent MEG-EEG recordings during a resting state condition. MEG coherence source imaging (CSI) in source space and spectral analysis in sensor space were performed. Significant differences were found between the 2 patient groups: (1) MEG and EEG spectral analysis showed significantly higher power at low frequencies (delta band) at sensor space in DS compared with NDS patients; (2) source analysis revealed larger power in the DS compared with NDS group at low frequencies in the frontal region; (3) NDS patients showed significantly higher MEG signal relative power in beta bands in sensor space compared with DS patients; (4) both DS and NDS patients showed higher EEG absolute power at higher beta band compared to controls; and (5) patients with DS were found to have a significantly higher MEG CSI than controls in the beta frequency band. These data support the observation of increased power in the low-frequency EEG/MEG rhythms associated with the DS. Increased power in the beta rhythms was more associated with the NDS.

scholarly journals Heritability of Resting State EEG Functional Connectivity Patterns

2013 ◽  
Vol 16 (5) ◽  
pp. 962-969 ◽  
Author(s):  
Nienke M. Schutte ◽  
Narelle K. Hansell ◽  
Eco J. C. de Geus ◽  
Nicholas G. Martin ◽  
Margaret J. Wright ◽  
...  
Keyword(s):  
Resting State ◽  
Cluster Coefficient ◽  
Path Length ◽  
Brain Connectivity ◽  
Network Clustering ◽  
Beta Band ◽  
Band Frequency ◽  
Functional Brain ◽  
Synchronization Likelihood ◽  
Eeg Recordings

We examined the genetic architecture of functional brain connectivity measures in resting state electroencephalographic (EEG) recordings. Previous studies in Dutch twins have suggested that genetic factors are a main source of variance in functional brain connectivity derived from EEG recordings. In addition, qualitative descriptors of the brain network derived from graph analysis — network clustering and average path length — are also heritable traits. Here we replicated previous findings for connectivity, quantified by the synchronization likelihood, and the graph theoretical parameters cluster coefficient and path length in an Australian sample of 16-year-old twins (879) and their siblings (93). Modeling of monozygotic and dizygotic twins and sibling resemblance indicated heritability estimates of the synchronization likelihood (27–74%) and cluster coefficient and path length in the alpha and theta band (40–44% and 23–40% respectively) and path length in the beta band frequency (41%). This corroborates synchronization likelihood and its graph theoretical derivatives cluster coefficient and path length as potential endophenotypes for behavioral traits and neurological disorders.

scholarly journals Prestimulus frontal-parietal coherence predicts auditory detection performance in rats

2014 ◽  
Vol 111 (10) ◽  
pp. 1986-2000 ◽  
Author(s):  
Linnea Herzog ◽  
Kia Salehi ◽  
Kaitlin S. Bohon ◽  
Michael C. Wiest
Keyword(s):  
Long Range ◽  
Parietal Cortex ◽  
Low Frequency ◽  
Detection Performance ◽  
Beta Band ◽  
Low Frequencies ◽  
Auditory Detection ◽  
Local Synchronization ◽  
Motivational Changes ◽  
External Stimuli

Electrophysiology in primates has implicated long-range neural coherence as a potential mechanism for enhancing sensory detection. To test whether local synchronization and long-range neural coherence support detection performance in rats, we recorded local field potentials (LFPs) in frontal and parietal cortex while rats performed an auditory detection task. We observed significantly elevated power at multiple low frequencies (<15 Hz) preceding the target beep when the animal failed to respond to the signal (misses), in both frontal and parietal cortex. In terms of long-range coherence, we observed significantly more frontal-parietal coherence in the beta band (15–30 Hz) before the signal on misses compared with hits. This effect persisted after regressing away linear trends in the coherence values during a session, showing that the excess frontal-parietal beta coherence prior to misses cannot be explained by slow motivational changes during a session. In addition, a trend toward higher low-frequency (<15 Hz) coherence prior to miss trials compared with hits became highly significant when we rereferenced the LFPs to the mean voltage on each recording array, suggesting that the results are specific to our frontal and parietal areas. These results do not support a role for long-range frontal-parietal coherence or local synchronization in facilitating the detection of external stimuli. Rather, they extend to long-range frontal-parietal coherence previous findings that correlate local synchronization of low-frequency (<15 Hz) oscillations with inattention to external stimuli and synchronization of beta rhythms (15–30 Hz) with voluntary or involuntary prolongation of the current cognitive or motor state.

scholarly journals Multiscale Decomposition and Spectral Analysis of Sector ETF Price Dynamics

2021 ◽  
Vol 14 (10) ◽  
pp. 464
Author(s):  
Tim Leung ◽  
Theodore Zhao
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Financial Time Series ◽  
Low Frequency ◽  
Ensemble Empirical Mode Decomposition ◽  
Price Dynamics ◽  
Exchange Traded Funds ◽  
Intrinsic Mode Functions ◽  
Low Frequencies ◽  
Financial Time

We present a multiscale analysis of the price dynamics of U.S. sector exchange-traded funds (ETFs). Our methodology features a multiscale noise-assisted approach, called the complementary ensemble empirical mode decomposition (CEEMD), that decomposes any financial time series into a number of intrinsic mode functions from high to low frequencies. By combining high-frequency modes or low-frequency modes, we show how to filter the financial time series and estimate conditional volatilities. The results show the different dynamics of the sector ETFs on multiple timescales. We then apply Hilbert spectral analysis to derive the instantaneous energy-frequency spectrum of each sector ETF. Using historical ETF prices, we illustrate and compare the properties of various timescales embedded in the original time series. Through the new metrics of the Hilbert power spectrum and frequency deviation, we are able to identify differences among sector ETF and with respect to SPY that were not obvious before.

Profiling Parkinson's disease cognitive phenotypes via resting-state magnetoencephalography

2021 ◽  
Author(s):  
Olivier B Simon ◽  
Donald Rojas ◽  
Debashis Ghosh ◽  
Xinyi Yang ◽  
Sarah E Rogers ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Cognitive Decline ◽  
Resting State ◽  
Source Analysis ◽  
Beta Band ◽  
Cognitive Changes ◽  
Cross Sectional ◽  
Normal Cognition

Aberrant brain oscillations are a hallmark of Parkinson's disease (PD) pathophysiology and may be related to motor and non-motor symptoms. Mild cognitive impairment (MCI) affects many people with PD even at the time of diagnosis and conversion risks to PD dementia (PDD) are very high. Unfortunately, pharmacotherapies are not addressing cognitive symptoms in PD. Profiling PD cognitive phenotypes (eg. MCI, PDD...) may therefore help inform future treatments. Neurophysiological methods, such as magnetoencephalography (MEG), offer the advantage of observing oscillatory patterns, whose regional and temporal profiles may elucidate how cognitive changes relate to neural mechanisms. We conducted a resting state MEG cross-sectional study of 89 persons with PD stratified into three phenotypic groups: normal cognition, MCI and PDD, in order to identify brain regions and frequencies most associated with each cognitive profile. In addition, a neuropsychological battery was administered to assess each domain of cognition. Our data showed higher power in lower frequency bands (delta and theta) observed along with more severe cognitive impairment, and associated with memory, language, attention and global cognition. Of the total 119 brain parcels assessed during source analysis, widespread group differences were found in the beta band, with significant changes mostly occurring between the normal cognition and MCI groups. Moreover, bilateral frontal and left-hemispheric regions were particularly affected in the other frequencies as cognitive decline becomes more pronounced. Our results suggest MCI and PDD may be qualitatively distinct cognitive phenotypes, and most dramatic changes seem to have happened when the PD brain shows mild cognitive decline.

Changes in the Total Power of Beta and Theta Bands When Using EEG Biofeedback in Primary School-Age Children Having Difficulties with Voluntary Regulation

2020 ◽  
pp. 331-340
Author(s):  
Yuliya S. Dzhos ◽  
◽  
Irina A. Men’shikova ◽  
Keyword(s):  
Left Hemisphere ◽  
Spectral Characteristics ◽  
Low Frequency ◽  
School Age Children ◽  
Total Power ◽  
Eeg Biofeedback ◽  
Beta Band ◽  
Bioelectric Activity ◽  
Voluntary Regulation ◽  
The Brain

This article presents the results of the study on spectral electroencephalogram (EEG) characteristics in 7–10-year-old children (8 girls and 22 boys) having difficulties with voluntary regulation of activity after 10 and 20 neurofeedback sessions using beta-activating training. Brain bioelectric activity was recorded in 16 standard leads using the Neuron-Spectrum-4/VPM complex. The dynamics was assessed by EEG beta and theta bands during neurofeedback. An increase in the total power of beta band oscillations was established both after 10 and after 20 sessions of EEG biofeedback in the frontal (p ≤ 0.001), left parietal (p ≤ 0.036), and temporal (p ≤ 0.003) areas of the brain. A decrease in the spectral characteristics of theta band oscillations was detected: after 10 neurofeedback sessions in the frontal (p ≤ 0.008) and temporal (p ≤ 0.006) areas of both hemispheres, as well as in the parietal area of the left hemisphere (p ≤ 0.005); after 20 sessions, in the central (p ≤ 0.004), frontal (p ≤ 0.001) and temporal (p ≤ 0.001) areas of both hemispheres, as well as in the occipital (p ≤ 0.047) and parietal (p ≤ 0.001) areas of the left hemisphere. The study into the dynamics of bioelectric activity during biofeedback using EEG parameters in 7–10-year-old children with impaired voluntary regulation of higher mental functions allowed us to prove the advisability of 20 sessions, as the increase in high-frequency activity and decrease in low-frequency activity do not stop with the 10th session. Changes in these parameters after 10 EEG biofeedback sessions are expressed mainly in the frontotemporal areas of both hemispheres, while after a course of 20 sessions, in both the frontotemporal and central parietal areas of the brain.

scholarly journals Conditional Entropy: A Potential Digital Marker for Stress

Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 286
Author(s):  
Soheil Keshmiri
Keyword(s):  
Resting State ◽  
Nearest Neighbor ◽  
Brain Activity ◽  
Solution Concept ◽  
Conditional Entropy ◽  
K Nearest Neighbor ◽  
Brain Response ◽  
Substantial Progress ◽  
Eeg Recordings ◽  
The Brain

Recent decades have witnessed a substantial progress in the utilization of brain activity for the identification of stress digital markers. In particular, the success of entropic measures for this purpose is very appealing, considering (1) their suitability for capturing both linear and non-linear characteristics of brain activity recordings and (2) their direct association with the brain signal variability. These findings rely on external stimuli to induce the brain stress response. On the other hand, research suggests that the use of different types of experimentally induced psychological and physical stressors could potentially yield differential impacts on the brain response to stress and therefore should be dissociated from more general patterns. The present study takes a step toward addressing this issue by introducing conditional entropy (CE) as a potential electroencephalography (EEG)-based resting-state digital marker of stress. For this purpose, we use the resting-state multi-channel EEG recordings of 20 individuals whose responses to stress-related questionnaires show significantly higher and lower level of stress. Through the application of representational similarity analysis (RSA) and K-nearest-neighbor (KNN) classification, we verify the potential that the use of CE can offer to the solution concept of finding an effective digital marker for stress.

scholarly journals Earless toads sense low frequencies but miss the high notes

2017 ◽  
Vol 284 (1864) ◽  
pp. 20171670 ◽  
Author(s):  
Molly C. Womack ◽  
Jakob Christensen-Dalsgaard ◽  
Luis A. Coloma ◽  
Juan C. Chaparro ◽  
Kim L. Hoke
Keyword(s):  
High Frequency ◽  
Species Differences ◽  
Low Frequency ◽  
Auditory Brainstem ◽  
Low Frequencies ◽  
Hearing Sensitivity ◽  
Sensory Pathways ◽  
Airborne Sound ◽  
Vibrational Sensitivity ◽  
Species Specific

Sensory losses or reductions are frequently attributed to relaxed selection. However, anuran species have lost tympanic middle ears many times, despite anurans' use of acoustic communication and the benefit of middle ears for hearing airborne sound. Here we determine whether pre-existing alternative sensory pathways enable anurans lacking tympanic middle ears (termed earless anurans) to hear airborne sound as well as eared species or to better sense vibrations in the environment. We used auditory brainstem recordings to compare hearing and vibrational sensitivity among 10 species (six eared, four earless) within the Neotropical true toad family (Bufonidae). We found that species lacking middle ears are less sensitive to high-frequency sounds, however, low-frequency hearing and vibrational sensitivity are equivalent between eared and earless species. Furthermore, extratympanic hearing sensitivity varies among earless species, highlighting potential species differences in extratympanic hearing mechanisms. We argue that ancestral bufonids may have sufficient extratympanic hearing and vibrational sensitivity such that earless lineages tolerated the loss of high frequency hearing sensitivity by adopting species-specific behavioural strategies to detect conspecifics, predators and prey.

scholarly journals Synaptic Molecular and Neurophysiological Markers Are Independent Predictors of Progression in Alzheimer’s Disease

2021 ◽  
pp. 1-12
Author(s):  
Una Smailovic ◽  
Ingemar Kåreholt ◽  
Thomas Koenig ◽  
Nicholas J. Ashton ◽  
Bengt Winblad ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Global Field ◽  
Prognostic Indicators ◽  
Early Event ◽  
Functional Markers ◽  
Beta Band ◽  
Global Field Power ◽  
Synaptic Markers ◽  
Eeg Recordings

Background: Cerebrospinal fluid (CSF) neurogranin and quantitative electroencephalography (qEEG) are potential molecular and functional markers of synaptic pathology in Alzheimer’s disease (AD). Synaptic markers have emerged as candidate prognostic indicators of AD since synaptic degeneration was shown to be an early event and the best correlate of cognitive deficits in patients along the disease continuum. Objective: The present study investigated the association between CSF neurogranin and qEEG measures as well as their potential to predict clinical deterioration in mild cognitive impairment (MCI) patients. Methods: Patients diagnosed with MCI (n = 99) underwent CSF conventional AD biomarkers and neurogranin analysis and resting-state EEG recordings. The study population was further stratified into stable (n = 41) and progressive MCI (n = 31), based on the progression to AD dementia during two years follow-up. qEEG analysis included computation of global field power and global field synchronization in four conventional frequency bands. Results: CSF neurogranin levels were associated with theta power and synchronization in the progressive MCI group. CSF neurogranin and qEEG measures were significant predictors of progression to AD dementia, independent of baseline amyloid status in MCI patients. A combination of CSF neurogranin with global EEG power in theta and global EEG synchronization in beta band exhibited the highest classification accuracy as compared to either of these markers alone. Conclusion: qEEG and CSF neurogranin are independent predictors of progression to AD dementia in MCI patients. Molecular and neurophysiological synaptic markers may have additive value in a multimodal diagnostic and prognostic approach to dementia.

A waveform inversion technique for measuring elastic wave attenuation in cylindrical bars

Geophysics ◽  
1992 ◽  
Vol 57 (6) ◽  
pp. 854-859 ◽  
Author(s):  
Xiao Ming Tang
Keyword(s):  
Elastic Wave ◽  
Wave Attenuation ◽  
Waveform Inversion ◽  
Finite Size ◽  
Low Frequency ◽  
Frequency Range ◽  
Multiple Reflections ◽  
Low Frequencies ◽  
The Time Domain ◽  
Attenuation Values

A new technique for measuring elastic wave attenuation in the frequency range of 10–150 kHz consists of measuring low‐frequency waveforms using two cylindrical bars of the same material but of different lengths. The attenuation is obtained through two steps. In the first, the waveform measured within the shorter bar is propagated to the length of the longer bar, and the distortion of the waveform due to the dispersion effect of the cylindrical waveguide is compensated. The second step is the inversion for the attenuation or Q of the bar material by minimizing the difference between the waveform propagated from the shorter bar and the waveform measured within the longer bar. The waveform inversion is performed in the time domain, and the waveforms can be appropriately truncated to avoid multiple reflections due to the finite size of the (shorter) sample, allowing attenuation to be measured at long wavelengths or low frequencies. The frequency range in which this technique operates fills the gap between the resonant bar measurement (∼10 kHz) and ultrasonic measurement (∼100–1000 kHz). By using the technique, attenuation values in a PVC (a highly attenuative) material and in Sierra White granite were measured in the frequency range of 40–140 kHz. The obtained attenuation values for the two materials are found to be reliable and consistent.

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