Consistency of Regions of Interest as nodes of fMRI functional brain networks

The functional network approach, where fMRI BOLD time series are mapped to networks depicting functional relationships between brain areas, has opened new insights into the function of the human brain. In this approach, the choice of network nodes is of crucial importance. One option is to consider fMRI voxels as nodes. This results in a large number of nodes, making network analysis and interpretation of results challenging. A common alternative is to use predefined clusters of anatomically close voxels, Regions of Interest (ROIs). This approach assumes that voxels within ROIs are functionally similar. Because these two approaches result in different network structures, it is crucial to understand what happens to network connectivity when moving from the voxel level to the ROI level. We show that the consistency of ROIs, defined as the mean Pearson correlation coefficient between the time series of their voxels, varies widely in resting-state experimental data. Therefore the assumption of similar voxel dynamics within each ROI does not generally hold. Further, the time series of low-consistency ROIs may be highly correlated, resulting in spurious links in ROI-level networks. Based on these results, we recommend that averaging BOLD signals over anatomically defined ROIs should be carefully considered.

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A comparison of methods to estimate vertical land motion trends from GNSS and altimetry at tide gauge stations

Ocean Science ◽

10.5194/os-14-187-2018 ◽

2018 ◽

Vol 14 (2) ◽

pp. 187-204 ◽

Cited By ~ 12

Author(s):

Marcel Kleinherenbrink ◽

Riccardo Riva ◽

Thomas Frederikse

Keyword(s):

Time Series ◽

Sea Level ◽

Tide Gauge ◽

Satellite System ◽

Vertical Land Motion ◽

Correlation Threshold ◽

The Mean ◽

Highly Correlated ◽

Global Navigation Satellite ◽

Along Track

Abstract. Tide gauge (TG) records are affected by vertical land motion (VLM), causing them to observe relative instead of geocentric sea level. VLM can be estimated from global navigation satellite system (GNSS) time series, but only a few TGs are equipped with a GNSS receiver. Hence, (multiple) neighboring GNSS stations can be used to estimate VLM at the TG. This study compares eight approaches to estimate VLM trends at 570 TG stations using GNSS by taking into account all GNSS trends with an uncertainty smaller than 1 mm yr−1 within 50 km. The range between the methods is comparable with the formal uncertainties of the GNSS trends. Taking the median of the surrounding GNSS trends shows the best agreement with differenced altimetry–tide gauge (ALT–TG) trends. An attempt is also made to improve VLM trends from ALT–TG time series. Only using highly correlated along-track altimetry and TG time series reduces the SD of ALT–TG time series by up to 10 %. As a result, there are spatially coherent changes in the trends, but the reduction in the root mean square (RMS) of differences between ALT–TG and GNSS trends is insignificant. However, setting correlation thresholds also acts like a filter to remove problematic TG time series. This results in sets of ALT–TG VLM trends at 344–663 TG locations, depending on the correlation threshold. Compared to other studies, we decrease the RMS of differences between GNSS and ALT–TG trends (from 1.47 to 1.22 mm yr−1), while we increase the number of locations (from 109 to 155), Depending on the methods the mean of differences between ALT–TG and GNSS trends vary between 0.1 and 0.2 mm yr−1. We reduce the mean of the differences by taking into account the effect of elastic deformation due to present-day mass redistribution. At varying ALT–TG correlation thresholds, we provide new sets of trends for 759 to 939 different TG stations. If both GNSS and ALT–TG trend estimates are available, we recommend using the GNSS trend estimates because residual ocean signals might correlate over long distances. However, if large discrepancies ( > 3 mm yr−1) between the two methods are present, local VLM differences between the TG and the GNSS station are likely the culprit and therefore it is better to take the ALT–TG trend estimate. GNSS estimates for which only a single GNSS station and no ALT–TG estimate are available might still require some inspection before they are used in sea level studies.

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A comparison of data weighting methods to derive vertical land motion trends from GNSS and altimetry at tide gauge stations

10.5194/os-2017-92 ◽

2017 ◽

Author(s):

Marcel Kleinherenbrink ◽

Riccardo Riva ◽

Thomas Frederikse

Keyword(s):

Time Series ◽

Tide Gauge ◽

Satellite System ◽

Vertical Land Motion ◽

Correlation Threshold ◽

The Mean ◽

Highly Correlated ◽

Global Navigation Satellite ◽

Along Track ◽

Weighting Methods

Abstract. This study compares eight weighting techniques for Global Navigation Satellite System (GNSS)-derived Vertical Land Motion (VLM) trends at 570 tide gauge (TG) stations. The spread between the methods has a comparable size as the formal uncertainties of the GNSS trends. Taking the median of the surrounding GNSS trends shows the best agreement with differenced altimetry – tide gauge (ALT-TG) trends. An attempt is also made to improve VLM trends from ALT-TG time series. Only using highly correlated along-track altimetry and TG time series, reduces the standard deviation of ALT-TG time series up to 10 %. As a result, there are spatially coherent changes in the trends, but the reduction in the RMS of differences between ALT-TG and GNSS trends is insignificant. However, setting correlation thresholds also acts like a filter to remove problematic TG stations. This results in sets of ALT-TG VLM trends at 344–663 TG locations, depending on the correlation threshold. Compared to other studies, we decrease the RMS of differences between GNSS and ALT-TG trends (from 1.47 to 1.22 mm/yr), while we increase the number of locations (from 109 to 155), Depending on the weighting methods the mean of differences between ALT-TG and GNSS trends varies between 0.1–0.2 mm/yr. We reduce the mean of differences by taking into account the effect of elastic deformation due to present-day mass redistribution into account.

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Physiological fractals: Visual and statistical evidence across timescales and experimental states

10.31234/osf.io/agxzt ◽

2020 ◽

Author(s):

Jeffrey J Kim

Keyword(s):

Time Series ◽

Published Data ◽

Compassion Meditation ◽

Open Questions ◽

Mean And Variance ◽

Time Series Analyses ◽

The Mean ◽

Highly Correlated ◽

Mind Training ◽

Stable Signal

A marker of engaging in compassion meditation and related processes is an increase in heart-rate variability (HRV), typically interpreted as a marker of parasympathetic nervous response. Whilst insightful, open questions remain. For example, which timescale is best to examine the effects of meditation and related practices on HRV? Furthermore, how might advanced time series analyses – such as stationarity – be able to examine dynamic changes in the mean and variance of the HRV signal across time? Here we apply such methods to previously published data, which measured HRV pre- and post- a two-week compassionate mind training (CMT) intervention. Inspection of these data reveal that a visualization of HRV correlations across resting and compassion meditation states, pre- and post- two-week training, is retained across numerous recording timescales. Here, the fractal-like nature of our data indicate that the accuracy of representing HRV data can exist across timescales, albeit with greater or lesser granularity. Interestingly, inspection of the HRV signal at Time 2 compassion meditation versus Time 1 revealed a more highly correlated (i.e., potentially more stable) signal. We followed up these results with tests of stationarity, which revealed Time 2 had a less stochastic (variable) signal than Time 1, and a measure of distance in the time series, which showed that Time 2 had less of an average difference between rest and meditation than at Time 1. Our results provide novel assessment of visual and statistical markers of HRV change across distinct experimental states.

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Performance assessment of the database downscaled ocean waves (DOW) on Santa Catarina coast, South Brazil

Anais da Academia Brasileira de Ciências ◽

10.1590/0001-3765201520140329 ◽

2015 ◽

Vol 87 (2) ◽

pp. 623-634 ◽

Cited By ~ 3

Author(s):

Paula G. Silva ◽

Antonio H.F. Klein ◽

Mauricio González ◽

Omar Gutierrez ◽

Antonio Espejo

Keyword(s):

Time Series ◽

Pearson Correlation ◽

Simulated Data ◽

Gumbel Distribution ◽

Wave Model ◽

Ocean Waves ◽

Statistical Parameters ◽

Santa Catarina ◽

Peak Period ◽

The Mean

This work presents a validation of wave parameters from the new sixty years Downscaled Ocean Waves (DOW) reanalysis database. This study compares quantiles of the Gumbel distribution of Hs (significant wave height) and Tp (peak period) from simulated data with an 11 months' time series obtained from a buoy moored seaward on the Santa Catarina coast. Analysis by means of Gumbel distribution quantiles allows more weight to be given to the highest values of the time series, which are especially important in design projects. The statistical parameters used to verify the fit between the measured and the modeled data included: RMSE, BIAS, Scatter Index and Pearson Correlation Coefficient. Mean direction (θm) validation was conducted qualitatively. The database showed good fit of the mean conditions, especially Hs which was well reproduced by the wave model. Underestimation of Tp, related mainly to the low spatial and temporal resolution of wind data used to generate waves, highlights this general modeling problem. Based on calculated statistical parameters, DOW data were considered comparable to the values obtained by measurements; however, such data must be cautiously used for extreme events analysis and in areas of bimodal sea conditions, where major deficiencies in the database were observed.

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Sacral Anatomical Orientation in the Lebanese Population

Advances in Orthopedics ◽

10.1155/2020/4292384 ◽

2020 ◽

Vol 2020 ◽

pp. 1-5

Author(s):

Joseph Maalouly ◽

Fouad Jabbour ◽

Elias Saidy ◽

Georgio Lati ◽

Gerard El-Hajj ◽

...

Keyword(s):

Volume Rendering ◽

Pearson Correlation ◽

Intraclass Correlation ◽

Spinal Diseases ◽

3D Images ◽

Correlation Test ◽

Postural Changes ◽

Pearson Correlation Test ◽

The Mean ◽

Highly Correlated

Introduction. PI is currently used as the gold standard measurement in spinopelvic anatomy. There is a need for a reliable method to calculate sacral anatomic orientation (SAO) independent of posture and to establish its association with PI, which was previously established in a single study (Peleg et al., 2007). Therefore, the aim of our study is the application and verification of this association on a Lebanese sample. Methods. Methods for measuring SAO and PI on living individuals are described. The study was carried out on 200 adult individuals using CT 3D images (volume-rendering method). Reliability (intratester and intertester) was evaluated using the intraclass correlation test. A regression analysis was carried out to evaluate the association between the two measurements. Results. There were 103 females (51%) and 97 males (49%) with a mean age of 58.68 ± 19.6 years (min = 20; max = 93). The mean SAO and PI in our population were found to be 52.65° (SD = 8.16°) and 59.08° (SD = 12.53°), respectively. SAO and PI measurements were highly correlated (Pearson correlation test; r = −0.296, P<0.0001 for our general population). PI can be predicted via SAO, i.e., SAO = (−0.193 × PI) + 64.057. Conclusions. SAO may be an important tool, alongside PI, in defining the sagittal shape of the spine and useful for understanding its association with spinal diseases as they are not affected by postural changes.

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Asteroid and Comet Impact Speeds upon Mars: Significance for Panspermia and the Supply of Organics

International Astronomical Union Colloquium ◽

10.1017/s0252921100014718 ◽

1997 ◽

Vol 161 ◽

pp. 197-201 ◽

Cited By ~ 1

Author(s):

Duncan Steel

Keyword(s):

Probability Distributions ◽

Regions Of Interest ◽

Significant Fraction ◽

Organic Chemicals ◽

Impact Speed ◽

The Mean ◽

The Impact

AbstractWhilst lithopanspermia depends upon massive impacts occurring at a speed above some limit, the intact delivery of organic chemicals or other volatiles to a planet requires the impact speed to be below some other limit such that a significant fraction of that material escapes destruction. Thus the two opposite ends of the impact speed distributions are the regions of interest in the bioastronomical context, whereas much modelling work on impacts delivers, or makes use of, only the mean speed. Here the probability distributions of impact speeds upon Mars are calculated for (i) the orbital distribution of known asteroids; and (ii) the expected distribution of near-parabolic cometary orbits. It is found that cometary impacts are far more likely to eject rocks from Mars (over 99 percent of the cometary impacts are at speeds above 20 km/sec, but at most 5 percent of the asteroidal impacts); paradoxically, the objects impacting at speeds low enough to make organic/volatile survival possible (the asteroids) are those which are depleted in such species.

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Detection of Circulating Tissue Factor and Factor VII in a Normal Population

Thrombosis and Haemostasis ◽

10.1055/s-0038-1650365 ◽

1996 ◽

Vol 75 (05) ◽

pp. 772-777 ◽

Cited By ~ 30

Author(s):

Sybille Albrecht ◽

Matthias Kotzsch ◽

Gabriele Siegert ◽

Thomas Luther ◽

Heinz Großmann ◽

...

Keyword(s):

Tissue Factor ◽

Normal Population ◽

Mean Value ◽

Factor Vii ◽

Significant Difference ◽

Age Dependent ◽

The Mean ◽

Highly Correlated ◽

And Gender

SummaryThe plasma tissue factor (TF) concentration was correlated to factor VII concentration (FVIIag) and factor VII activity (FVIIc) in 498 healthy volunteers ranging in age from 17 to 64 years. Immunoassays using monoclonal antibodies (mAbs) were developed for the determination of TF and FVIIag in plasma. The mAbs and the test systems were characterized. The mean value of the TF concentration was 172 ± 135 pg/ml. TF showed no age- and gender-related differences. For the total population, FVIIc, determined by a clotting test, was 110 ± 15% and the factor VIlag was 0.77 ± 0.19 μg/ml. FVII activity was significantly increased with age, whereas the concentration demonstrated no correlation to age in this population. FVII concentration is highly correlated with the activity as measured by clotting assay using rabbit thromboplastin. The ratio between FVIIc and FVIIag was not age-dependent, but demonstrated a significant difference between men and women. Between TF and FVII we could not detect a correlation.

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Der Sommer und Herbst 2003 aus phänologischer Sicht | Summer and autumn 2003 from a phenological point of view

Schweizerische Zeitschrift fur Forstwesen ◽

10.3188/szf.2004.0142 ◽

2004 ◽

Vol 155 (5) ◽

pp. 142-145 ◽

Cited By ~ 2

Author(s):

Claudio Defila

Keyword(s):

Time Series ◽

New Record ◽

Point Of View ◽

Late Spring ◽

Mean Deviation ◽

Leaf Shedding ◽

The Mean ◽

Very High ◽

Selection Of

The record-breaking heatwave of 2003 also had an impact on the vegetation in Switzerland. To examine its influences seven phenological late spring and summer phases were evaluated together with six phases in the autumn from a selection of stations. 30% of the 122 chosen phenological time series in late spring and summer phases set a new record (earliest arrival). The proportion of very early arrivals is very high and the mean deviation from the norm is between 10 and 20 days. The situation was less extreme in autumn, where 20% of the 103 time series chosen set a new record. The majority of the phenological arrivals were found in the class «normal» but the class«very early» is still well represented. The mean precocity lies between five and twenty days. As far as the leaf shedding of the beech is concerned, there was even a slight delay of around six days. The evaluation serves to show that the heatwave of 2003 strongly influenced the phenological events of summer and spring.

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The influence of solar wind on extratropical cyclones – Part 1: Wilcox effect revisited

Annales Geophysicae ◽

10.5194/angeo-27-1-2009 ◽

2009 ◽

Vol 27 (1) ◽

pp. 1-30 ◽

Cited By ~ 24

Author(s):

P. Prikryl ◽

V. Rušin ◽

M. Rybanský

Keyword(s):

Time Series ◽

Solar Wind ◽

Northern Hemisphere ◽

High Speed ◽

Coronal Holes ◽

Extratropical Cyclones ◽

Sector Boundary ◽

Speed Solar Wind ◽

The Mean ◽

High Speed Solar Wind

Abstract. A sun-weather correlation, namely the link between solar magnetic sector boundary passage (SBP) by the Earth and upper-level tropospheric vorticity area index (VAI), that was found by Wilcox et al. (1974) and shown to be statistically significant by Hines and Halevy (1977) is revisited. A minimum in the VAI one day after SBP followed by an increase a few days later was observed. Using the ECMWF ERA-40 re-analysis dataset for the original period from 1963 to 1973 and extending it to 2002, we have verified what has become known as the "Wilcox effect" for the Northern as well as the Southern Hemisphere winters. The effect persists through years of high and low volcanic aerosol loading except for the Northern Hemisphere at 500 mb, when the VAI minimum is weak during the low aerosol years after 1973, particularly for sector boundaries associated with south-to-north reversals of the interplanetary magnetic field (IMF) BZ component. The "disappearance" of the Wilcox effect was found previously by Tinsley et al. (1994) who suggested that enhanced stratospheric volcanic aerosols and changes in air-earth current density are necessary conditions for the effect. The present results indicate that the Wilcox effect does not require high aerosol loading to be detected. The results are corroborated by a correlation with coronal holes where the fast solar wind originates. Ground-based measurements of the green coronal emission line (Fe XIV, 530.3 nm) are used in the superposed epoch analysis keyed by the times of sector boundary passage to show a one-to-one correspondence between the mean VAI variations and coronal holes. The VAI is modulated by high-speed solar wind streams with a delay of 1–2 days. The Fourier spectra of VAI time series show peaks at periods similar to those found in the solar corona and solar wind time series. In the modulation of VAI by solar wind the IMF BZ seems to control the phase of the Wilcox effect and the depth of the VAI minimum. The mean VAI response to SBP associated with the north-to-south reversal of BZ is leading by up to 2 days the mean VAI response to SBP associated with the south-to-north reversal of BZ. For the latter, less geoeffective events, the VAI minimum deepens (with the above exception of the Northern Hemisphere low-aerosol 500-mb VAI) and the VAI maximum is delayed. The phase shift between the mean VAI responses obtained for these two subsets of SBP events may explain the reduced amplitude of the overall Wilcox effect. In a companion paper, Prikryl et al. (2009) propose a new mechanism to explain the Wilcox effect, namely that solar-wind-generated auroral atmospheric gravity waves (AGWs) influence the growth of extratropical cyclones. It is also observed that severe extratropical storms, explosive cyclogenesis and significant sea level pressure deepenings of extratropical storms tend to occur within a few days of the arrival of high-speed solar wind. These observations are discussed in the context of the proposed AGW mechanism as well as the previously suggested atmospheric electrical current (AEC) model (Tinsley et al., 1994), which requires the presence of stratospheric aerosols for a significant (Wilcox) effect.

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Technical note: Inherent benchmark or not? Comparing Nash–Sutcliffe and Kling–Gupta efficiency scores

Hydrology and Earth System Sciences ◽

10.5194/hess-23-4323-2019 ◽

2019 ◽

Vol 23 (10) ◽

pp. 4323-4331 ◽

Cited By ~ 60

Author(s):

Wouter J. M. Knoben ◽

Jim E. Freer ◽

Ross A. Woods

Keyword(s):

Time Series ◽

Coefficient Of Variation ◽

Ad Hoc ◽

Model Performance ◽

Technical Note ◽

Mean Flow ◽

Model Adequacy ◽

Robust Model ◽

The Mean ◽

Adequacy Assessment

Abstract. A traditional metric used in hydrology to summarize model performance is the Nash–Sutcliffe efficiency (NSE). Increasingly an alternative metric, the Kling–Gupta efficiency (KGE), is used instead. When NSE is used, NSE = 0 corresponds to using the mean flow as a benchmark predictor. The same reasoning is applied in various studies that use KGE as a metric: negative KGE values are viewed as bad model performance, and only positive values are seen as good model performance. Here we show that using the mean flow as a predictor does not result in KGE = 0, but instead KGE =1-√2≈-0.41. Thus, KGE values greater than −0.41 indicate that a model improves upon the mean flow benchmark – even if the model's KGE value is negative. NSE and KGE values cannot be directly compared, because their relationship is non-unique and depends in part on the coefficient of variation of the observed time series. Therefore, modellers who use the KGE metric should not let their understanding of NSE values guide them in interpreting KGE values and instead develop new understanding based on the constitutive parts of the KGE metric and the explicit use of benchmark values to compare KGE scores against. More generally, a strong case can be made for moving away from ad hoc use of aggregated efficiency metrics and towards a framework based on purpose-dependent evaluation metrics and benchmarks that allows for more robust model adequacy assessment.

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