All that glitters is not BOLD: inconsistencies in functional MRI

The blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) signal is a widely-accepted marker of brain activity. The acquisition parameters (APs) of fMRI aim at maximizing the signals related to neuronal activity while minimizing unrelated signal fluctuations. Currently, a diverse set of APs is used to acquire BOLD fMRI data. Here we demonstrate that some fMRI responses are alarmingly inconsistent across APs, ranging from positive to negative, or disappearing entirely, under identical stimulus conditions. These discrepancies, resulting from non-BOLD effects masquerading as BOLD signals, have remained largely unnoticed because studies rarely employ more than one set of APs. We identified and characterized non-BOLD responses in several brain areas, including posterior cingulate cortex and precuneus, as well as AP-dependence of both the signal time courses and of seed-based functional networks, noticing that AP manipulation can inform about the origin of the measured signals.Peer reviewe

Stimulus-Rate Sensitivity Discerns Area 3b of the Human Primary Somatosensory Cortex

Previous studies have shown that the hemodynamic response of the primary somatosensory cortex (SI) to electrical median nerve stimulation doubles in strength when the stimulus rate (SR) increases from 1 to 5 Hz. Here we investigated whether such sensitivity to SR is homogenous within the functionally different subareas of the SI cortex, and whether SR sensitivity would help discern area 3b among the other SI subareas. We acquired 3-tesla functional magnetic resonance imaging (fMRI) data from nine healthy adults who received pneumotactile stimuli in 25-s blocks to three right-hand fingers, either at 1, 4, or 10 Hz. The main contrast (all stimulations pooled vs. baseline), applied to the whole brain, first limited the search to the whole SI cortex. The conjunction of SR-sensitive contrasts [4 Hz − 1 Hz] > 0 and [10 Hz − 1 Hz] > 0 ([4Hz − 1Hz] + [10Hz − 1Hz] > 0), applied to the SI cluster, then revealed an anterior-ventral subcluster that reacted more strongly to both 10-Hz and 4-Hz stimuli than to the 1-Hz stimuli. No other SR-sensitive clusters were found at the group-level in the whole-brain analysis. The site of the SR-sensitive SI subcluster corresponds to the canonical position of area 3b; such differentiation was also possible at the individual level in 5 out of 9 subjects. Thus the SR sensitivity of the BOLD response appears to discern area 3b among other subareas of the human SI cortex.Peer reviewe

Rape with Extreme Violence: The New Pathology in South Kivu, Democratic Republic of Congo

Cathy Nangini and Denis Mukwege describe their work at the Panzi Hospital in the Democratic Republic of Congo, which treats women victims of rape with extreme violence that are often perpetrated at the hands of armed groups

Was the cold European winter 2009-2010 modified by anthropogenic climate change? An attribution study

An attribution study has been performed to investigate the degree to which the unusually cold European winter 2009-2010 was modified by anthropogenic climate change. Two different methods have been included for the attribution: one based on a large HadGEM3-A ensemble and one based on a statistical surrogate method. Both methods are evaluated by comparing simulated winter temperature means, trends, standard deviations, skewness, return periods, and 5 % quantiles with observations. While the surrogate method performs well, HadGEM3-A in general underestimates the trend in winter by a factor of 2/3. It has a mean cold bias dominated by the mountainous regions and also underestimates the cold 5 % quantile in many regions of Europe. Both methods show that the probability of experiencing a winter as cold as 2009-2010 has been reduced by approximately a factor of two due to anthropogenic changes. The method based on HadGEM3-A ensembles gives somewhat larger changes than the surrogate method because of differences in the definition of the unperturbed climate. The results are based on two diagnostics: the coldest day in winter and the largest continuous area with temperatures colder than twice the local standard deviation. The results are not sensitive to the choice of bias correction except in the mountainous regions. Previous results regarding the behavior of the measures of the changed probability have been extended. The counter-intuitive behavior for heavy-tailed distributions is found to hold for a range of measures and for events that become more rare in a changed climate

Evaluation of the HadGEM3-A simulations in view of detection and attribution of human influence on extreme events in Europe

A detailed analysis is carried out to assess the HadGEM3-A global atmospheric model skill in simulating extreme temperatures, precipitation and storm surges in Europe in the view of their attribution to human influence. The analysis is performed based on an ensemble of 15 atmospheric simulations forced with observed Sea Surface Temperature of the 54 year period 1960-2013. These simulations, together with dual simulations without human influence in the forcing, are intended to be used in weather and climate event attribution. The analysis investigates the main processes leading to extreme events, including atmospheric circulation patterns, their links with temperature extremes, land-atmosphere and troposphere-stratosphere interactions. It also compares observed and simulated variability, trends and generalized extreme value theory parameters for temperature and precipitation. One of the most striking findings is the ability of the model to capture North Atlantic atmospheric weather regimes as obtained from a cluster analysis of sea level pressure fields. The model also reproduces the main observed weather patterns responsible for temperature and precipitation extreme events. However, biases are found in many physical processes. Slightly excessive drying may be the cause of an overestimated summer interannual variability and too intense heat waves, especially in central/northern Europe. However, this does not seem to hinder proper simulation of summer temperature trends. Cold extremes appear well simulated, as well as the underlying blocking frequency and stratosphere-troposphere interactions. Extreme precipitation amounts are overestimated and too variable. The atmospheric conditions leading to storm surges were also examined in the Baltics region. There, simulated weather conditions appear not to be leading to strong enough storm surges, but winds were found in very good agreement with reanalyses. The performance in reproducing atmospheric weather patterns indicates that biases mainly originate from local and regional physical processes. This makes local bias adjustment meaningful for climate change attribution

Stimulus-rate sensitive subcluster within SI.

<p>A. Group results (n = 9): The statistical map overlaid onto one subject’s Talairach-normalized anatomical images. Contrast ([1Hz] + [4Hz] + [10Hz] – [baseline]) at false-discovery rate q(FDR) < 0.1 was used to define SI activation cluster (orange + green colors). The green color demarcates the stimulus-rate sensitive subcluster in SI obtained in the conjunction of the contrasts: [4 Hz − 1 Hz] > 0 and [10 Hz − 1 Hz] > 0 (presumably area 3b; see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0128462#sec006" target="_blank">Results</a>). B. Individual subjects’ results: Stimulus-rate sensitive subclusters within SI corresponded to the conventional location of area 3b in 5 out of 9 subjects. The stimulus-rate sensitive cluster “AREA 3b” is marked with green color, while the “REST of SI” cluster with orange. The SI cluster was defined at q(FDR) < 0. 1, and in the subsequent search for stimulus-rate sensitive voxels within that cluster, the statistical threshold was q(FDR) < 0.1 (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0128462#sec002" target="_blank">Methods</a> for details). The bar graphs show for each subject and each SR the BOLD-response amplitudes in “AREA 3b” (top row) and in the “REST of SI” (bottom row) clusters (estimated as the average % BOLD response across the stimulus block, starting 5 s after stimulus onset and ending 5 s after stimulus offset). C. Response time courses: The insets show the BOLD responses (mean ± SEM) for the stimulus-rate sensitive cluster “AREA 3b” (on the left) and for the rest of the SI cluster (on the right). The data correspond to the average of the individual clusters shown in panel B (n = 5).</p

Presentation of the stimuli.

<p>The pneumatic tactile stimuli were delivered to the fingertips of the right index (D2), middle (D3) and ring (D4) digits in a randomized order within a stimulation block. 25-s stimulation blocks alternated with the rest blocks of the same duration. While each single stimulus caused deviation of the pneumatic membrane for 282ms, time between onsets of the stimuli corresponded to the stimulus rate (SR) which was fixed (1, 4 or 10 Hz) for each 25-s stimulation block.</p

Web processing service for climate impact and extreme weather event analyses. Flyingpigeon (Version 1.0)

Analyses of extreme weather events and their impacts often requires big data processing of ensembles of climate model simulations. Researchers generally proceed by downloading the data from the providers and processing the data files " at home " with their own analysis processes. However, the growing amount of available climate model and observation data makes this procedure quite awkward. In addition, data processing knowledge is kept local, instead of being consolidated into a common resource of reusable code. These drawbacks can be mitigated by using a web processing service (WPS). A WPS hosts services such as data analysis processes that are accessible over the web, and can be installed close to the data archives. We developed a WPS named 'flyingpigeon' that communicates over an HTTP network protocol based on standards defined by the Open Geospatial Consortium (OGC) [23], to be used by climatologists and impact modelers as a tool for analyzing large datasets remotely. Here, we present the current processes we developed in flyingpigeon relating to commonly-used processes (preprocessing steps, spatial subsets at continent, country or region level, and climate indices) as well as methods for specific climate data analysis (weather regimes, analogues of circulation, segetal flora distribution, and species distribution models). We also developed a novel, browser-based interactive data visualization for circulation analogues , illustrating the flexibility of WPS in designing custom outputs. Bringing the software to the data instead of transferring the data to the code is becoming increasingly necessary, especially with the upcoming massive climate datasets

Web processing service for climate impact and extreme weather event analyses. Flyingpigeon (Version 1.0)

International audienceAnalyses of extreme weather events and their impacts often requires big data processing of ensembles of climate model simulations. Researchers generally proceed by downloading the data from the providers and processing the data files " at home " with their own analysis processes. However, the growing amount of available climate model and observation data makes this procedure quite awkward. In addition, data processing knowledge is kept local, instead of being consolidated into a common resource of reusable code. These drawbacks can be mitigated by using a web processing service (WPS). A WPS hosts services such as data analysis processes that are accessible over the web, and can be installed close to the data archives. We developed a WPS named 'flyingpigeon' that communicates over an HTTP network protocol based on standards defined by the Open Geospatial Consortium (OGC) [23], to be used by climatologists and impact modelers as a tool for analyzing large datasets remotely. Here, we present the current processes we developed in flyingpigeon relating to commonly-used processes (preprocessing steps, spatial subsets at continent, country or region level, and climate indices) as well as methods for specific climate data analysis (weather regimes, analogues of circulation, segetal flora distribution, and species distribution models). We also developed a novel, browser-based interactive data visualization for circulation analogues , illustrating the flexibility of WPS in designing custom outputs. Bringing the software to the data instead of transferring the data to the code is becoming increasingly necessary, especially with the upcoming massive climate datasets