scholarly journals Differential Effects of Isoflurane on High-frequency and Low-frequency γ Oscillations in the Cerebral Cortex and Hippocampus in Freely Moving Rats

2011 ◽  
Vol 114 (3) ◽  
pp. 588-595 ◽  
Author(s):  
Anthony G. Hudetz ◽  
Jeannette A. Vizuete ◽  
Siveshigan Pillay
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Brain Regions ◽  
Loss Of Consciousness ◽  
Dependent Manner ◽  
General Anesthetics ◽  
Frequency Bands ◽  
Depth Electrodes ◽  
Righting Reflex ◽  
40 Hz

Background Cortical γ oscillations are thought to play a role in conscious cognitive functions. Suppression of 40-Hz γ activity was implicated in the loss of consciousness during general anesthesia. However, several experimental studies found that γ oscillations were preserved in anesthesia. The authors investigated the concentration-dependent effect of isoflurane on spontaneous γ oscillations in two frequency bands and three distinct brain regions in the rat. Methods Adult Sprague-Dawley rats were chronically implanted with epidural and coaxial depth electrodes to record cortical field potentials in frontal cortex, visual cortex, and hippocampus in waking and at steady-state isoflurane concentrations of 0.4, 0.8, and 1.2%. The γ power was calculated for the frequency bands 30-50 and 70-140 Hz. Temporal variation and interregional synchrony of γ activity were analyzed using wavelet transform. Loss of consciousness was indexed by the loss of righting reflex. Results Rats lost their righting reflex at 0.8 ± 0.1% isoflurane. High-frequency γ power was decreased by isoflurane in a concentration-dependent manner (P < 0.001, 50% decrease at 0.8% isoflurane) in all brain regions. Low-frequency γ power was unaffected by isoflurane. The duration and interregional synchrony of high-frequency γ bursts was also reduced (P l < 0.001, 40% decrease at 0.8% isoflurane). Conclusions Distinction between high- and low-frequency γ bands is important when evaluating the effect of general anesthetics on brain electrical activity. Spontaneous 40-Hz γ power does not indicate the state of consciousness. The attenuation and interregional desynchronization of high-frequency γ oscillations appear to correlate with the loss of consciousness.

scholarly journals Bispectrum-based Cross-frequency Functional Connectivity: A Study of Alzheimer's Disease

2021 ◽  
Author(s):  
Dominik Klepl ◽  
Fei He ◽  
Min Wu ◽  
Daniel J Blackburn ◽  
Ptolemaios G Sarrigiannis
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Functional Connectivity ◽  
High Frequency ◽  
Neurodegenerative Disorder ◽  
Low Frequency ◽  
Brain Regions ◽  
Frequency Bands ◽  
Frequency Coupling ◽  
Eeg Recordings

Alzheimer's disease (AD) is a neurodegenerative disorder known to affect functional connectivity (FC) across many brain regions. Linear FC measures have been applied to study the differences in AD by splitting neurophysiological signals such as electroencephalography (EEG) recordings into discrete frequency bands and analysing them in isolation from each other. We address this limitation by quantifying cross-frequency FC in addition to the traditional within-band approach. Cross-bispectrum, a higher-order spectral analysis approach, is used to measure the nonlinear FC and is compared with the cross-spectrum, which only measures the linear FC within bands. This work reports the first use of cross-bispectrum to reconstruct a cross-frequency FC network where each frequency band is treated as a layer in a multilayer network with both inter- and intra-layer edges. An increase of within-band FC in AD is observed in low-frequency bands using both methods. Bispectrum also detects multiple cross-frequency differences, mainly increased FC in AD in delta-theta coupling. An increased importance of low-frequency coupling and decreased importance of high-frequency coupling is observed in AD. Integration properties of AD networks are more vulnerable than HC, while the segregation property is maintained in AD. Moreover, the segregation property of γ is less vulnerable in AD, suggesting the shift of importance from high-frequency activity towards low-frequency components. The results highlight the importance of studying nonlinearity and including cross-frequency FC in characterising AD. Moreover, the results demonstrate the advantages and limitations of using bispectrum to reconstruct FC networks.

scholarly journals Spectral fingerprints or spectral tilt? Evidence for distinct oscillatory signatures of memory formation

2018 ◽  
Author(s):  
Marie-Christin Fellner ◽  
Stephanie Gollwitzer ◽  
Stefan Rampp ◽  
Gernot Kreiselmeyr ◽  
Daniel Bush ◽  
...  
Keyword(s):  
Power Spectrum ◽  
High Frequency ◽  
Low Frequency ◽  
Brain Regions ◽  
Memory Formation ◽  
Memory Encoding ◽  
Frequency Bands ◽  
Theta Power ◽  
Gamma Power ◽  
Frequency Power

AbstractDecreases in low frequency power (2-30 Hz) alongside high frequency power increases (>40 Hz) have been demonstrated to predict successful memory formation. Parsimoniously this change in the frequency spectrum can be explained by one factor, a change in the tilt of the power spectrum (from steep to flat) indicating engaged brain regions. A competing view is that the change in the power spectrum contains several distinct brain oscillatory fingerprints, each serving different computations. Here, we contrast these two theories in a parallel MEG-intracranial EEG study where healthy participants and epilepsy patients, respectively, studied either familiar verbal material, or unfamiliar faces. We investigated whether modulations in specific frequency bands can be dissociated in time, space and by experimental manipulation. Both, MEG and iEEG data, show that decreases in alpha/beta power specifically predicted the encoding of words, but not faces, whereas increases in gamma power and decreases in theta power predicted memory formation irrespective of material. Critically, these different oscillatory signatures of memory encoding were evident in different brain regions. Moreover, high frequency gamma power increases occurred significantly earlier compared to low frequency theta power decreases. These results speak against a “spectral tilt” and demonstrate that brain oscillations in different frequency bands serve different functions for memory encoding.

scholarly journals Kurtosis and skewness of high-frequency brain signals are altered in paediatric epilepsy

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Jing Xiang ◽  
Ellen Maue ◽  
Yuyin Fan ◽  
Lei Qi ◽  
Francesco T Mangano ◽  
...  
Keyword(s):  
High Frequency ◽  
Intractable Epilepsy ◽  
Low Frequency ◽  
Brain Regions ◽  
Control Group ◽  
Frequency Bands ◽  
Non Invasive ◽  
Brain Signals ◽  
Paediatric Epilepsy ◽  
Virtual Electrode

Abstract Intracranial studies provide solid evidence that high-frequency brain signals are a new biomarker for epilepsy. Unfortunately, epileptic (pathological) high-frequency signals can be intermingled with physiological high-frequency signals making these signals difficult to differentiate. Recent success in non-invasive detection of high-frequency brain signals opens a new avenue for distinguishing pathological from physiological high-frequency signals. The objective of the present study is to characterize pathological and physiological high-frequency signals at source levels by using kurtosis and skewness analyses. Twenty-three children with medically intractable epilepsy and age-/gender-matched healthy controls were studied using magnetoencephalography. Magnetoencephalographic data in three frequency bands, which included 2–80 Hz (the conventional low-frequency signals), 80–250 Hz (ripples) and 250–600 Hz (fast ripples), were analysed. The kurtosis and skewness of virtual electrode signals in eight brain regions, which included left/right frontal, temporal, parietal and occipital cortices, were calculated and analysed. Differences between epilepsy and controls were quantitatively compared for each cerebral lobe in each frequency band in terms of kurtosis and skewness measurements. Virtual electrode signals from clinical epileptogenic zones and brain areas outside of the epileptogenic zones were also compared with kurtosis and skewness analyses. Compared to controls, patients with epilepsy showed significant elevation in kurtosis and skewness of virtual electrode signals. The spatial and frequency patterns of the kurtosis and skewness of virtual electrode signals among the eight cerebral lobes in three frequency bands were also significantly different from that of the controls (2–80 Hz, P < 0.001; 80–250 Hz, P < 0.00001; 250–600 Hz, P < 0.0001). Compared to signals from non-epileptogenic zones, virtual electrode signals from epileptogenic zones showed significantly altered kurtosis and skewness (P < 0.001). Compared to normative data from the control group, aberrant virtual electrode signals were, for each patient, more pronounced in the epileptogenic lobes than in other lobes(kurtosis analysis of virtual electrode signals in 250–600 Hz; odds ratio = 27.9; P < 0.0001). The kurtosis values of virtual electrode signals in 80–250 and 250–600 Hz showed the highest sensitivity (88.23%) and specificity (89.09%) for revealing epileptogenic lobe, respectively. The combination of virtual electrode and kurtosis/skewness measurements provides a new quantitative approach to distinguishing pathological from physiological high-frequency signals for paediatric epilepsy. Non-invasive identification of pathological high-frequency signals may provide novel important information to guide clinical invasive recordings and direct surgical treatment of epilepsy.

Wavelet Transform with a Novel Integration Technique for Image Fusion

2011 ◽  
Vol 204-210 ◽  
pp. 1419-1422 ◽  
Author(s):  
Yong Yang
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
High Frequency ◽  
Low Frequency ◽  
Experimental Results ◽  
Integration Technique ◽  
Frequency Bands ◽  
Fusion Methods ◽  
Fusion Scheme ◽  
Measures Of Performance

Image fusion is to combine several different source images to form a new image by using a certain method. Recent studies show that among a variety of image fusion algorithms, the wavelet-based method is more effective. In the wavelet-based method, the key technique is the fusion scheme, which can decide the final fused result. This paper presents a novel fusion scheme that integrates the wavelet decomposed coefficients in a quite separate way when fusing images. The method is formed by considering the different physical meanings of the coefficients in both the low frequency and high frequency bands. The fused results were compared with several existing fusion methods and evaluated by three measures of performance. The experimental results can demonstrate that the proposed method can achieve better performance than conventional image fusion methods.

Development of Sound Absorbers for Large Spaces

2005 ◽  
Vol 12 (4) ◽  
pp. 237-254
Author(s):  
Yoshihito Kobayashi ◽  
Toshiya Kitamura ◽  
Shinji Yamada
Keyword(s):  
Absorption Coefficient ◽  
Resonance Frequency ◽  
High Frequency ◽  
Sound Absorption ◽  
Low Frequency ◽  
Frequency Bands ◽  
Sound Fields ◽  
Absorption Area ◽  
Translucent Material ◽  
The Chairs

Moulded chairs have been developed, in which sound absorption at low frequency bands is increased by using the seat section and/or the back section as a resonator. In addition, a translucent sound absorption panel has been developed for application in large spaces. In the case of the chairs the resonance frequency, determined by the position, number, and depth of the holes, was examined. Prototypes were constructed, and the equivalent absorption area was measured in a reverberation room. The resonators of the chairs achieved an equivalent absorption area of 0.15 m2/seat, in the 125 Hz band. For the case of the translucent material, sound absorption was measured and compared with conventional sound absorption materials. The panels were designed in order to control sound fields in large spaces. The panels achieved a sound absorption coefficient of 0.6 to 1.0 at middle and high frequency bands.

Influence of RE/Mn (RE= La, Nd and Gd) Ratios on the Infrared Absorption and Emission Properties of Co-Zn Ferrites

2011 ◽  
Vol 217-218 ◽  
pp. 311-316 ◽  
Author(s):  
Ying Zhang ◽  
Di Jiang Wen
Keyword(s):  
Infrared Absorption ◽  
High Frequency ◽  
Low Frequency ◽  
Ionic Radii ◽  
Ceramic Method ◽  
Absorption And Emission ◽  
Frequency Bands ◽  
Emission Properties ◽  
Octahedral Sites ◽  
Co Doped

The RE/Mn co-doped Co-Zn ferrites were prepared by the ceramic method. Infrared absorption and emission properties were obtained by investigating those ferrites. The IR spectra in the range from 400 to 1200 cm-1 were observed. Mainly, three bands were investigated. The high-frequency bands and low-frequency bands were assigned to the tetrahedral and octahedral complexes, respectively. The intensity of all the bands is found to increase while a decrease in broadness, which is explained on the cation distribution in the tetrahedral and octahedral sites were modified by RE/Mn addition. The Mn substitutes the Fe3+ and enters into the octahedral sites; while the partial RE3+ ions are apt to diffuse to the grain boundaries and others enter into the spinel lattice .This can be explained on the basis of ionic radii and ratios of the substituted cation. The results indicate that IR emissivity seems to be increasing with RE/Mn ratio within 8-14 μm wavebands. The maximum infrared emissivity is 0.968 when La/Mn ratio of 0.20 within 8-14 μm wavebands.

AN IMAGE FUSION FRAMEWORK BASED ON HUMAN VISUAL SYSTEM IN FRAMELET DOMAIN

2012 ◽  
Vol 10 (01) ◽  
pp. 1250002 ◽  
Author(s):  
GAURAV BHATNAGAR ◽  
Q. M. JONATHAN WU
Keyword(s):  
Visual System ◽  
Image Fusion ◽  
Human Visual System ◽  
High Frequency ◽  
Evaluation Criteria ◽  
Low Frequency ◽  
Weighted Average ◽  
Objective Evaluation ◽  
Fusion Algorithm ◽  
Frequency Bands

In this paper, a novel image fusion algorithm based on framelet transform is presented. The core idea is to decompose all the images to be fused into low and high-frequency bands using framelet transform. For fusion, two different selection strategies are developed and used for low and high-frequency bands. The first strategy is adaptive weighted average based on local energy and is applied to fuse the low-frequency bands. In order to fuse high-frequency bands, a new strategy is developed based on texture while exploiting the human visual system characteristics, which can preserve more details in source images and further improve the quality of fused image. Experimental results demonstrate the efficiency and better performance than existing image fusion methods both in visual inspection and objective evaluation criteria.

scholarly journals Investigating Data Cleaning Methods to Improve Performance of Brain–Computer Interfaces Based on Stereo-Electroencephalography

2021 ◽  
Vol 15 ◽  
Author(s):  
Shengjie Liu ◽  
Guangye Li ◽  
Shize Jiang ◽  
Xiaolong Wu ◽  
Jie Hu ◽  
...  
Keyword(s):  
Data Cleaning ◽  
Brain Activity ◽  
Low Frequency ◽  
Reference Electrode ◽  
Brain Regions ◽  
Subcortical Structures ◽  
Implanted Electrodes ◽  
Average Reference ◽  
Depth Electrodes ◽  
Cleaning Methods

Stereo-electroencephalography (SEEG) utilizes localized and penetrating depth electrodes to directly measure electrophysiological brain activity. The implanted electrodes generally provide a sparse sampling of multiple brain regions, including both cortical and subcortical structures, making the SEEG neural recordings a potential source for the brain–computer interface (BCI) purpose in recent years. For SEEG signals, data cleaning is an essential preprocessing step in removing excessive noises for further analysis. However, little is known about what kinds of effect that different data cleaning methods may exert on BCI decoding performance and, moreover, what are the reasons causing the differentiated effects. To address these questions, we adopted five different data cleaning methods, including common average reference, gray–white matter reference, electrode shaft reference, bipolar reference, and Laplacian reference, to process the SEEG data and evaluated the effect of these methods on improving BCI decoding performance. Additionally, we also comparatively investigated the changes of SEEG signals induced by these different methods from multiple-domain (e.g., spatial, spectral, and temporal domain). The results showed that data cleaning methods could improve the accuracy of gesture decoding, where the Laplacian reference produced the best performance. Further analysis revealed that the superiority of the data cleaning method with excellent performance might be attributed to the increased distinguishability in the low-frequency band. The findings of this work highlighted the importance of applying proper data clean methods for SEEG signals and proposed the application of Laplacian reference for SEEG-based BCI.

scholarly journals Network-targeted, multi-site direct cortical stimulation enhances working memory by modulating phase lag of low frequency oscillations

2019 ◽  
Author(s):  
Sankaraleengam Alagapan ◽  
Justin Riddle ◽  
Wei Angel Huang ◽  
Eldad Hadar ◽  
Hae Won Shin ◽  
...  
Keyword(s):  
Working Memory ◽  
Brain Stimulation ◽  
Effective Means ◽  
Low Frequency ◽  
Brain Regions ◽  
Phase Lag ◽  
Frequency Bands ◽  
Alpha Frequency ◽  
Cortical Regions ◽  
Parietal Cortices

AbstractWorking memory, an important component of cognitive control, is supported by the coordinated activation of a network of cortical regions in the frontal and parietal cortices. Oscillations in theta and alpha frequency bands are thought to coordinate these network interactions. Thus, targeting multiple nodes of the network with brain stimulation at the frequency of interaction may be an effective means of modulating working memory. We tested this hypothesis by identifying regions that are functionally connected in theta and alpha frequency bands and intracranially stimulating both regions simultaneously in participants undergoing invasive monitoring. We found that in-phase stimulation resulted in improvement in performance compared to sham stimulation. In contrast, anti-phase stimulation did not affect performance. In-phase stimulation resulted in decreased phase lag between regions within working memory network while anti-phase stimulation resulted in increased phase lag suggesting that shorter phase lag in oscillatory connectivity may lead to better performance. The results support the idea that phase lag may play a key role in information transmission across brain regions. More broadly, brain stimulation strategies that aim to improve cognition may be better served targeting multiple nodes of brain networks.

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