An Effective Brain Imaging Biomarker for AD and aMCI: ALFF in Slow-5 Frequency Band

2021 ◽  
Vol 18 ◽  
Author(s):  
Luoyu Wang ◽  
Qi Feng ◽  
Mei Wang ◽  
Tingting Zhu ◽  
Enyan Yu ◽  
...  
Keyword(s):  
Brain Imaging ◽  
Frequency Band ◽  
Low Frequency ◽  
Posterior Cingulate Cortex ◽  
Angular Gyrus ◽  
Imaging Biomarker ◽  
Support Vector ◽  
Frequency Bands ◽  
Local Functional ◽  
Left Angular Gyrus

Background: As a potential brain imaging biomarker, amplitude of low frequency fluc-tuation (ALFF) has been used as a feature to distinguish patients with Alzheimer’s disease (AD) and amnestic mild cognitive impairment (aMCI) from normal controls (NC). However, it remains unclear whether the frequency-dependent pattern of ALFF alterations can effectively distinguish the different phases of the disease. Methods: In the present study, 52 AD and 50 aMCI patients were enrolled together with 43 NC in total. The ALFF values were calculated in the following three frequency bands: classical (0.01-0.08 Hz), slow-4 (0.027-0.073 Hz) and slow-5 (0.01-0.027 Hz) for the three different groups. Subsequently, the local functional abnormalities were employed as features to examine the effect of classification among AD, aMCI and NC using a support vector machine (SVM). Results: We found that the among-group differences of ALFF in the different frequency bands were mainly located in the left hippocampus (HP), right HP, bilateral posterior cingulate cortex (PCC) and bilateral precuneus (PCu), left angular gyrus (AG) and left medial prefrontal cortex (mPFC). When the local functional abnormalities were employed as features, we identified that the ALFF in the slow-5 frequency band showed the highest accuracy to distinguish among the three groups. Conclusion: These findings may deepen our understanding of the pathogenesis of AD and suggest that slow-5 frequency band may be helpful to explore the pathogenesis and distinguish the phases of this disease.

AMPLITUDE OF LOW FREQUENCY FLUCTUATION AT DIFFERENT FREQUENCY BANDS IN EARLY AMNESTIC MILD COGNITIVE IMPAIRMENT: RESULTS FROM ADNI

2012 ◽  
Vol 05 (01) ◽  
pp. 1150003 ◽  
Author(s):  
LONG-LONG JING ◽  
LI-YU HUANG ◽  
DENG-FENG HUANG ◽  
JIE NIU ◽  
ZHENG ZHONG
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Frequency Band ◽  
Inferior Frontal Gyrus ◽  
Low Frequency ◽  
Posterior Cingulate Cortex ◽  
Amnestic Mild Cognitive Impairment ◽  
Posterior Lobe ◽  
Frequency Bands ◽  
Normal Controls

We used resting-state functional magnetic resonance imaging (fMRI) to determine whether there are any abnormalities in different frequency bands between amplitude of low-frequency fluctuations (ALFF) and fractional ALFF (fALFF) and between 10 early amnestic mild cognitive impairment (EMCI) patients and eight normal controls participating in the Alzheimer's Disease Neuroimaging Initiative (ADNI). We showed widespread difference in ALFF/fALFF between two frequency bands (slow-4: 0.027–0.073 Hz, slow-5: 0.01–0.027 Hz) in many brain areas including posterior cingulate cortex (PCC), medial prefrontal cortex (MPFC), suprasellar cistern (SC) and ambient cistern (AC). Compared to the normal controls, the EMCI patients showed increased ALFF values in PCu , cerebellum, occipital lobe and cerebellum posterior lobe in frequency band slow-4. While in frequency band slow-5, the EMCI patients showed decreased ALFF values in temporal lobe, left cerebrum and middle temporal gyrus5. Moreover, the EMCI patients showed increased fALFF values in frontal lobe and inferior frontal gyrus in band slow-5. While in frequency band slow-4, the EMCI patients showed decreased fALFF values in limbic lobe, cingulate gyrus and corpus callosum. These results demonstrated that EMCI patients had widespread abnormalities of amplitude of LFF in different frequency bands.

scholarly journals Spillovers of Stock Markets among the BRICS: New Evidence in Time and Frequency Domains before the Outbreak of COVID-19 Pandemic

2021 ◽  
Vol 14 (3) ◽  
pp. 112
Author(s):  
Kai Shi
Keyword(s):  
Stock Market ◽  
Frequency Band ◽  
Stock Markets ◽  
Emerging Market ◽  
Low Frequency ◽  
Systematic Risk ◽  
Error Variance ◽  
Frequency Bands ◽  
Volatility Spillovers ◽  
Risk Sources

We attempted to comprehensively decode the connectedness among the abbreviation of five emerging market countries (BRICS) stock markets between 1 August 2002 and 31 December 2019 not only in time domain but also in frequency domain. A continuously varying spillover index based on forecasting error variance decomposition within a generalized abbreviation of vector-autoregression (VAR) framework was computed. With the help of spectral representation, heterogeneous frequency responses to shocks were separated into frequency-specific spillovers in five different frequency bands to reveal differentiated linkages among BRICS markets. Rolling sample analyses were introduced to allow for multiple changes during the sample period. It is found that return spillovers dominated by the high frequency band (within 1 week) part declined with the drop of frequencies, while volatility spillovers dominated by the low frequency band (above 1 quarter) part grew with the decline in frequencies; the dynamics of spillovers were influenced by crucial systematic risk events, and some similarities implied in the spillover dynamics in different frequency bands were found. From the perspective of identifying systematic risk sources, China’s stock market and Russia’s stock market, respectively, played an influential role for return spillover and volatility spillover across BRICS markets.

Determining patterns of motor recruitment during locomotion

2002 ◽  
Vol 205 (3) ◽  
pp. 359-369 ◽  
Author(s):  
James M. Wakeling ◽  
Motoshi Kaya ◽  
Genevieve K. Temple ◽  
Ian A. Johnston ◽  
Walter Herzog
Keyword(s):  
Motor Unit ◽  
Frequency Band ◽  
Fibre Type ◽  
Low Frequency ◽  
Motor Units ◽  
Motor Unit Recruitment ◽  
Medial Gastrocnemius ◽  
Fibre Types ◽  
Myoelectric Signals ◽  
Frequency Bands

SUMMARY Motor units are the functional units of muscle contraction in vertebrates. Each motor unit comprises muscle fibres of a particular fibre type and can be considered as fast or slow depending on its fibre-type composition. Motor units are typically recruited in a set order, from slow to fast, in response to the force requirements from the muscle. The anatomical separation of fast and slow muscle in fish permits direct recordings from these two fibre types. The frequency spectra from different slow and fast myotomal muscles were measured in the rainbow trout Oncorhynchus mykiss. These two muscle fibre types generated distinct low and high myoelectric frequency bands. The cat paw-shake is an activity that recruits mainly fast muscle. This study showed that the myoelectric signal from the medial gastrocnemius of the cat was concentrated in a high frequency band during paw-shake behaviour. During slow walking, the slow motor units of the medial gastrocnemius are also recruited, and this appeared as increased muscle activity within a low frequency band. Therefore, high and low frequency bands could be distinguished in the myoelectric signals from the cat medial gastrocnemius and probably corresponded, respectively, to fast and slow motor unit recruitment. Myoelectric signals are resolved into time/frequency space using wavelets to demonstrate how patterns of motor unit recruitment can be determined for a range of locomotor activities.

scholarly journals Comparison of Frequency Bands Using Spectral Entropy for Epileptic Seizure Prediction

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Susana Blanco ◽  
Arturo Garay ◽  
Diego Coulombie
Keyword(s):  
Frequency Band ◽  
Epileptic Seizure ◽  
Signal Analysis ◽  
Fourier Spectrum ◽  
Low Frequency ◽  
Eeg Signals ◽  
High Frequencies ◽  
Frequency Bands ◽  
Low Correlation ◽  
Rate Of Increase

Introduction. Under the hypothesis that the uncontrolled neuronal synchronization propagates recruiting more and more neurons, the aim is to detect its onset as early as possible by signal analysis. This synchronization is not noticeable just by looking at the EEG, so mathematical tools are needed for its identification. Objective. The aim of this study is to compare the results of spectral entropies calculated in different frequency bands of the EEG signals to decide which band may be a better tool to predict an epileptic seizure. Materials and Methods. Invasive ictal records were used. We measured the Fourier spectrum entropy of the electroencephalographic signals 4 to 32 minutes before the attack in low, medium and high frequencies. Results. The high-frequency band shows a markedly rate of increase of the entropy, with positive slopes and low correlation coefficient. The entropy rate of growth in the low-frequency band is practically zero, with a correlation around 0.2 and mostly positive slopes. The mid-frequency band showed both positive and negative slopes with low correlation. Conclusions. The entropy in the high frequencies could be predictor, because it shows changes in the previous moments of the attack. Its main problem is the variability, which makes it difficult to set the threshold that ensures an adequate prediction.

scholarly journals Modulation of Brain Electroencephalography Oscillations by Electroacupuncture in a Rat Model of Postincisional Pain

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Jing Wang ◽  
Jing Wang ◽  
Xuezhu Li ◽  
Duan Li ◽  
Xiao-Li Li ◽  
...  
Keyword(s):  
Frequency Band ◽  
Low Frequency ◽  
Spontaneous Pain ◽  
Brain Oscillations ◽  
Beta Band ◽  
Pain Model ◽  
Frequency Bands ◽  
Analgesic Effects ◽  
Before And After ◽  
Beta Frequency

The present study aimed to investigate how ongoing brain rhythmical oscillations changed during the postoperative pain and whether electroacupuncture (EA) regulated these brain oscillations when it relieved pain. We established a postincisional pain model of rats with plantar incision to mimic the clinical pathological pain state, tested the analgesic effects of EA, and recorded electroencephalography (EEG) activities before and after the EA application. By analysis of power spectrum and bicoherence of EEG, we found that in rats with postincisional pain, ongoing activities at the delta-frequency band decreased, while activities at theta-, alpha-, and beta-frequency bands increased. EA treatment on these postincisional pain rats decreased the power at high-frequency bands especially at the beta-frequency band and reversed the enhancement of the cross-frequency coupling strength between the beta band and low-frequency bands. After searching for the PubMed, our study is the first time to describe that brain oscillations are correlated with the processing of spontaneous pain information in postincisional pain model of rats, and EA could regulate these brain rhythmical frequency oscillations, including the power and cross-frequency couplings.

scholarly journals Surface-Based Falff: A Potential Novel Biomarker for Prediction of Radiation Encephalopathy in Patients With Nasopharyngeal Carcinoma

2021 ◽  
Vol 15 ◽  
Author(s):  
You-ming Zhang ◽  
Ya-fei Kang ◽  
Jun-jie Zeng ◽  
Li Li ◽  
Jian-ming Gao ◽  
...  
Keyword(s):  
Nasopharyngeal Carcinoma ◽  
Low Frequency ◽  
Superior Temporal Gyrus ◽  
Brain Regions ◽  
Imaging Biomarker ◽  
Support Vector ◽  
Radiation Encephalopathy ◽  
Radiation Induced

Radiation encephalopathy (RE) is an important potential complication in patients with nasopharyngeal carcinoma (NPC) who undergo radiotherapy (RT) that can affect the quality of life. However, a functional imaging biomarker of pre-symptomatic RE has not yet been established. This study aimed to assess radiation-induced gray matter functional alterations and explore fractional amplitude of low-frequency fluctuation (fALFF) as an imaging biomarker for predicting or diagnosing RE in patients with NPC. A total of 60 patients with NPC were examined, 21 in the pre-RT cohort and 39 in the post-RT cohort. Patients in the post-RT cohort were further divided into two subgroups according to the occurrence of RE in follow-up: post-RT non−RE (n = 21) and post-RT REprovedinfollow−up (n = 18). Surface-based and volume-based fALFF were used to detect radiation-induced functional alterations. Functional derived features were then adopted to construct a predictive model for the diagnosis of RE. We observed that surface-based fALFF could sensitively detect radiation-induced functional alterations in the intratemporal brain regions (such as the hippocampus and superior temporal gyrus), as well as the extratemporal regions (such as the insula and prefrontal lobe); however, no significant intergroup differences were observed using volume-based fALFF. No significant correlation between fALFF and radiation dose to the ipsilateral temporal lobe was observed. Support vector machine (SVM) analysis revealed that surface-based fALFF in the bilateral superior temporal gyri and left insula exhibited impressive performance (accuracy = 80.49%) in identifying patients likely to develop RE. We conclude that surface-based fALFF may serve as a sensitive imaging biomarker in the prediction of RE.

Effect of Spindle Speeds on 3D Topography of Ball-End Milled Surfaces Using Wavelet Analysis Method

2016 ◽  
Vol 836-837 ◽  
pp. 13-19 ◽  
Author(s):  
Shuai Liu ◽  
Jun Zhao ◽  
Wen Zhen Qin ◽  
Ji Ming Pang
Keyword(s):  
Wavelet Analysis ◽  
Frequency Band ◽  
Low Frequency ◽  
Spindle Speed ◽  
Median Frequency ◽  
Frequency Bands ◽  
Multi Scale ◽  
3D Topography ◽  
Changing Trend ◽  
Height Data

Optical profiler is employed to acquire topography height data of ball-end milled die steel surface under different spindle speeds ranging from 2000rpm to 12000rpm with lead angle of 20° and tilt angle of-10°. By multi-scale wavelet analysis, measured height data are decomposed and then been reconstructed, meanwhile 3D topography and 3D roughness in different frequency bands are obtained. The results show that the changing trend of roughness with frequency band under different spindle speeds is not the same. In the high frequency bands, roughness has a tendency to increase with the increasing spindle speed. In the median frequency band, the roughness of the surface machined under low spindle speed 2000 rpm is the largest and the roughness of the surface machined under high spindle speed 12000 rpm is the lowest. In the low frequency bands, the roughness of the surface machined under low spindle speed 2000rpm is much larger than those obtained under other spindle speeds, and with the increasing spindle speed, the changing trend of roughness increases firstly then decreases.

A Wavelet-Based Watermarking Algorithm Using the Human Visual System

2012 ◽  
Vol 424-425 ◽  
pp. 304-308
Author(s):  
Yu Feng Chen ◽  
Gang Yin
Keyword(s):  
Visual System ◽  
Frequency Band ◽  
Human Visual System ◽  
Low Frequency ◽  
Jpeg Compression ◽  
Experimental Results ◽  
Frequency Bands

A wavelet based multiresolution watermarking method using the human visual system (HVS) is proposed. The watermark is added to the large coefficients at the middle frequency bands and low frequency band of the DWT of an image. The experimental results show that the proposed method is robust for some common image distortions, such as cutting, filtering and the JPEG compression

ANALYSIS OF FLUCTUATIONS IN WIND DEPENDENT SHALLOW WATER AMBIENT NOISE SPECTRUM

2007 ◽  
Vol 07 (03) ◽  
pp. L313-L319 ◽  
Author(s):  
S. RAMJI ◽  
G. LATHA ◽  
S. RAMAKRISHANAN
Keyword(s):  
Shallow Water ◽  
Frequency Band ◽  
Noise Level ◽  
Ambient Noise ◽  
Low Frequency ◽  
Noise Spectrum ◽  
Sea State ◽  
Spectrum Level ◽  
Frequency Bands ◽  
Lower Frequency Band

In this work, the fluctuations in the spectrum level of shallow water ambient noise is analyzed for 3 different sea states. The shallow water ambient noise data were collected of Bay of Bengal using an omni directional hydrophone and a portable data acquisition system.100 sets of data were collected and organized according to the three different sea states using Beaufort scale. Fluctuations in noise spectrum level at different sea states were studied by dividing the spectral bandwidth of 12 kHz into low, mid and high frequency bands. Mean noise spectrum level for each sea state was calculated and the result shows the noise spectrum level increases with the sea state. Further it was found that the noise level was higher in lower frequency band and decreases in the higher frequency band. Also the correlation between the noise level and sea state was higher in the low frequency band and tend to decrease in the mid frequency band and there was no correlation in the higher frequency bands. The higher noise levels were associated with lower frequencies of the bandwidth whereas it is less in higher frequencies. The fluctuations were found to be higher in the lower frequency band than the mid and higher frequency band. In this paper the data collection, data processing and noise spectrum analysis are presented in detail. As the fluctuations in power spectrum level of the ambient noise is one of the primary factor which decides the signal to noise ratio of most of the acoustic instruments, these results seems to be significant.

scholarly journals Abnormal Regional Spontaneous Brain Activity and Its Indirect Effect on Spasm Ratings in Patients With Hemifacial Spasm

2020 ◽  
Vol 14 ◽  
Author(s):  
Fei-Fei Luo ◽  
Hui Xu ◽  
Ming Zhang ◽  
Yuan Wang
Keyword(s):  
Hemifacial Spasm ◽  
Indirect Effect ◽  
Brain Activity ◽  
Low Frequency ◽  
Posterior Cingulate Cortex ◽  
Angular Gyrus ◽  
Neurovascular Compression ◽  
Regional Brain ◽  
Middle Occipital Gyrus ◽  
The Right

PurposeThree classical methods of resting-state functional magnetic resonance imaging (rs-fMRI) were employed to explore the local functional abnormalities and their effect on spasm ratings in hemifacial spasm (HFS) patients.MethodsThirty HFS patients and 30 matched healthy controls (HCs) were recruited. Rs-fMRI data, neurovascular compression (NVC) degree and spasm severity were collected in each subject. Fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), and degree centrality (DC) were calculated in the whole brain voxels. Two sample t-tests were performed to investigate group differences of fALFF, ReHo, and DC. Correlation analysis was performed to assess the relationships between the regional brain abnormalities and clinical variables in HFS.ResultsCompared with HCs, HFS patients exhibited increased fALFF in the left precuneus and right posterior cingulate cortex (PCC), together with increased ReHo in the bilateral PCC and bilateral precuneus. Decreased ReHo was observed in the right middle occipital gyrus (MOG), right superior occipital gyrus (SOG), right cuneus, and right angular gyrus (AG) in HFS patients. Moreover, ReHo in the right PCC were positively correlated with NVC degree and spasm severity in HFS patients, respectively. Mediation analysis revealed that increased ReHo in the right PCC regulated the neurovascular compression degree, and further resulted in increased spasm ratings.ConclusionOur study revealed regional brain dysfunctions from different perspectives and an indirect effect of ReHo in right PCC on spasm ratings predominantly through the alteration of NVC.

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