A novel method of quantifying hemodynamic delays to improve hemodynamic response, and CVR estimates in CO2 challenge fMRI.
Ontology highlight
ABSTRACT:
SUBMITTER: Yao JF
PROVIDER: S-EPMC8327112 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:High-throughput sequencing of cDNA (RNA-seq) is used extensively to characterize the transcriptome of cells. Many transcriptomics studies aim at comparing either abundance levels or the transcriptome composition between given conditions, and as a first step, the sequencing reads must be used as the basis for abundance quantification of transcriptomic features of interest, such as genes or transcripts. Several different quantification approaches have been proposed, ranging from simple counting of reads overlapping given genomic regions to more complex estimation of underlying transcript abundances. In this paper, we show that gene-level abundance estimates and statistical inference offer advantages over transcript-level analyses, in terms of both performance and interpretability. We also illustrate that while the presence of differential isoform usage can lead to inflated false discovery rates in differential expression analyses on simple count matrices, and incorporation of transcript-level abundance estimates improves the performance in simulated data, the difference is relatively minor in several real data sets. Finally, we provide an R package (tximport) to help users integrate transcript-level abundance estimates from common quantification pipelines into count-based statistical inference engines.
2015-12-10 | E-MTAB-4119 | biostudies-arrayexpress
Project description:The interpretation of functional magnetic resonance imaging (fMRI) studies based on blood oxygen-level dependent (BOLD) contrast generally relies on the assumption of a linear relationship between evoked neuronal activity and fMRI response. While nonlinearities in this relationship have been suggested by a number of studies, it remains unclear to what extent they relate to the neurovascular response and are therefore inherent to BOLD fMRI. Full characterization of potential vascular nonlinearities is required for accurate inferences about the neuronal system under study. To investigate the extent of vascular nonlinearities, evoked activity was studied in humans with BOLD fMRI (n=28) and magnetoencephalography (MEG) (n=5). Brief (600-800 ms) rapidly repeated (1 Hz) visual stimuli were delivered using a stimulation paradigm that minimized neuronal nonlinearities. Nevertheless, BOLD fMRI experiments showed substantial remaining nonlinearities. The smallest stimulus separation (200-400 ms) resulted in significant response broadening (15-20% amplitude decrease; 10-12% latency increase; 6-14% duration increase) with respect to a linear prediction. The substantial slowing and widening of the response in the presence of preceding stimuli suggest a vascular rather than neuronal origin to the observed nonlinearity. This was confirmed by the MEG data, which showed no significant neuro-electric nonlinear interactions between stimuli as little as 200 ms apart. The presence of substantial vascular nonlinearities has important implications for rapid event-related studies by fMRI and other imaging modalities that infer neuronal activity from hemodynamic parameters.
| S-EPMC2731556 | biostudies-literature
Project description:The hemodynamic response function (HRF) describes the local response of brain vasculature to functional activation. Accurate HRF modeling enables the investigation of cerebral blood flow regulation and improves our ability to interpret fMRI results. Block designs have been used extensively as fMRI paradigms because detection power is maximized; however, block designs are not optimal for HRF parameter estimation. Here we assessed the utility of block design fMRI data for HRF modeling. The trueness (relative deviation), precision (relative uncertainty), and identifiability (goodness-of-fit) of different HRF models were examined and test-retest reproducibility of HRF parameter estimates was assessed using computer simulations and fMRI data from 82 healthy young adult twins acquired on two occasions 3 to 4 months apart. The effects of systematically varying attributes of the block design paradigm were also examined. In our comparison of five HRF models, the model comprising the sum of two gamma functions with six free parameters had greatest parameter accuracy and identifiability. Hemodynamic response function height and time to peak were highly reproducible between studies and width was moderately reproducible but the reproducibility of onset time was low. This study established the feasibility and test-retest reliability of estimating HRF parameters using data from block design fMRI studies.
| S-EPMC3915209 | biostudies-literature
Project description:Sickle erythrocytes exhibit abnormal morphology and membrane mechanics under deoxygenated conditions due to the polymerization of hemoglobin S. We employed dissipative particle dynamics to extend a validated multiscale model of red blood cells (RBCs) to represent different sickle cell morphologies based on a simulated annealing procedure and experimental observations. We quantified cell distortion using asphericity and elliptical shape factors, and the results were consistent with a medical image analysis. We then studied the rheology and dynamics of sickle RBC suspensions under constant shear and in a tube. In shear flow, the transition from shear-thinning to shear-independent flow revealed a profound effect of cell membrane stiffening during deoxygenation, with granular RBC shapes leading to the greatest viscosity. In tube flow, the increase of flow resistance by granular RBCs was also greater than the resistance of blood flow with sickle-shape RBCs. However, no occlusion was observed in a straight tube under any conditions unless an adhesive dynamics model was explicitly incorporated into simulations that partially trapped sickle RBCs, which led to full occlusion in some cases.
| S-EPMC3260690 | biostudies-literature
Project description:Background and purposeThe BOLD signal amplitude as a response to a hypercapnia stimulus is commonly used to assess cerebrovascular reserve. Despite recent advances, the implementation remains cumbersome and alternative ways to assess hemodynamic impairment are desirable. Resting-state BOLD signal fluctuations (rsBOLD) have been proposed however data on its sensitivity and dependence on baseline venous cerebral blood volume (vCBV) is limited. The primary aim of this study was to compare the effect sizes of resting-state and hypercapnia induced BOLD signal changes in the detection of hemodynamic impairment. The second aim of the study was to assess the dependence of BOLD signal variability on vCBV.Materials and methodsFifteen patients with internal carotid artery occlusive disease and 15 matched healthy controls were included in this study. The BOLD signal was derived from a dual-echo gradient-echo echo-planar sequence during hypercapnia (HC) and hyperoxia (HO) gas modulations. BOLD (fractional) amplitude of low frequency fluctuations ((f)ALFF) was compared to HC-BOLD, BOLD response delays derived from time delay analysis and ΔBOLD in response to progressively increasing HC. Effect sizes (i.e. the standard mean difference between patients and controls) were calculated. HO-BOLD was used to estimate vCBV, and its contribution to the variability in rsBOLD signal was evaluated.ResultsThe effect sizes of ALFF and fALFF (0.61 and 0.72) were lower than the effect sizes related to hypercapnia-based hemodynamic assessment analysis; 1.62, 1.56 and 0.90 for HC-BOLD, BOLD response delays and ΔBOLD in response to progressively increasing HC. A moderate relation was found between (f)ALFF and HC-BOLD in controls (R2 of 0.61 and 0.42), but this relation decreased in patients (R2 of 0.33 and 0.15). (f)ALFF did not differ between patients and controls whereas HC-BOLD did (p < 0.005). The ΔBOLD response to progressively increasing HC was significantly different in between patients and controls for ΔEtCO2 values ≥ 2 mmHg (at +2 mmHg F(1, 18) = 5.85, p = 0.026). Up to 31% and 53% of the variance in the ALFF and HC-BOLD spatial distribution could be explained by HO-BOLD.ConclusionALFF and fALFF demonstrated a moderate effect size to detect hemodynamic impairment whereas the effect size was large for methods employing a hypercapnia-based vascular stress stimulus. Based on our analysis of BOLD signal change as a response to a progressively increasing hypercapnia stimulus we can argue that a hypercapnia stimulus of at least 2 mmHg above baseline EtCO2 is necessary to evaluate hemodynamic impairment. We also demonstrated that a substantial amount of information imbedded in the rsBOLD and HC-BOLD was explained by HO-BOLD. HO-BOLD can serve as a proxy for vCBV and this thus indicates that one should be careful when adopting these techniques in disease cases with compromised CBV.
| S-EPMC6057274 | biostudies-literature
Project description:The effects of elevated CO2 on the early life stages of coral were investigated by culturing the pelagic larvae and new recruits of Acropora gemmifera at three concentrations of CO2 (corresponding to pH?=?8.1, 7.8 and 7.5, respectively). Acidified seawater resulted in fewer A. gemmifera larvae settling, and led to the production of smaller new recruits by slowing the development of the skeleton. The delayed development of new recruits due to elevated CO2 was consistent with the downregulation of calcification related genes. Several genes related to HCO3- and Ca2+ transporters were downregulated by elevated CO2, with solute carriers (SLC) (membrane transport proteins) possibly playing an important role. The downregulation of these membrane transport proteins might suppress the transport of calcium, bicarbonate and organic matter, resulting in the delayed development of A. gemmifera.
| S-EPMC5809585 | biostudies-literature
Project description:Conventional functional magnetic resonance imaging (FMRI) group analysis makes two key assumptions that are not always justified. First, the data from each subject is condensed into a single number per voxel, under the assumption that within-subject variance for the effect of interest is the same across all subjects or is negligible relative to the cross-subject variance. Second, it is assumed that all data values are drawn from the same Gaussian distribution with no outliers. We propose an approach that does not make such strong assumptions, and present a computationally efficient frequentist approach to FMRI group analysis, which we term mixed-effects multilevel analysis (MEMA), that incorporates both the variability across subjects and the precision estimate of each effect of interest from individual subject analyses. On average, the more accurate tests result in higher statistical power, especially when conventional variance assumptions do not hold, or in the presence of outliers. In addition, various heterogeneity measures are available with MEMA that may assist the investigator in further improving the modeling. Our method allows group effect t-tests and comparisons among conditions and among groups. In addition, it has the capability to incorporate subject-specific covariates such as age, IQ, or behavioral data. Simulations were performed to illustrate power comparisons and the capability of controlling type I errors among various significance testing methods, and the results indicated that the testing statistic we adopted struck a good balance between power gain and type I error control. Our approach is instantiated in an open-source, freely distributed program that may be used on any dataset stored in the universal neuroimaging file transfer (NIfTI) format. To date, the main impediment for more accurate testing that incorporates both within- and cross-subject variability has been the high computational cost. Our efficient implementation makes this approach practical. We recommend its use in lieu of the less accurate approach in the conventional group analysis.
| S-EPMC3404516 | biostudies-literature
Project description:One way to study connectivity in visual cortical areas is by examining spontaneous neural activity. In the absence of visual input, such activity remains shaped by the underlying neural architecture and, presumably, may still reflect visuotopic organization. Here, we applied population connective field (CF) modeling to estimate the spatial profile of functional connectivity in the early visual cortex during resting state functional magnetic resonance imaging (RS-fMRI). This model-based analysis estimates the spatial integration between blood-oxygen level dependent (BOLD) signals in distinct cortical visual field maps using fMRI. Just as population receptive field (pRF) mapping predicts the collective neural activity in a voxel as a function of response selectivity to stimulus position in visual space, CF modeling predicts the activity of voxels in one visual area as a function of the aggregate activity in voxels in another visual area. In combination with pRF mapping, CF locations on the cortical surface can be interpreted in visual space, thus enabling reconstruction of visuotopic maps from resting state data. We demonstrate that V1 ➤ V2 and V1 ➤ V3 CF maps estimated from resting state fMRI data show visuotopic organization. Therefore, we conclude that-despite some variability in CF estimates between RS scans-neural properties such as CF maps and CF size can be derived from resting state data.
| S-EPMC4215614 | biostudies-literature
Project description:In the event-related functional magnetic resonance imaging (fMRI) data analysis, there is an extensive interest in accurately and robustly estimating the hemodynamic response function (HRF) and its associated statistics (e.g., the magnitude and duration of the activation). Most methods to date are developed in the time domain and they have utilized almost exclusively the temporal information of fMRI data without accounting for the spatial information. The aim of this paper is to develop a multiscale adaptive smoothing model (MASM) in the frequency domain by integrating the spatial and temporal information to adaptively and accurately estimate HRFs pertaining to each stimulus sequence across all voxels in a three-dimensional (3D) volume. We use two sets of simulation studies and a real data set to examine the finite sample performance of MASM in estimating HRFs. Our real and simulated data analyses confirm that MASM outperforms several other state-of-art methods, such as the smooth finite impulse response (sFIR) model.
| S-EPMC3922314 | biostudies-literature
Project description:The selection of the appropriate hemodynamic response function (HRF) for signal modeling in functional magnetic resonance imaging (fMRI) is important. Although the use of the boxcar-shaped hemodynamic response function (BHRF) and canonical hemodynamic response (CHRF) has gained increasing popularity in rodent fMRI studies, whether the selected HRF affects the results of rodent fMRI has not been fully elucidated. Here we investigated the signal change and t-statistic sensitivities of BHRF, CHRF, and impulse response function (IRF). The effect of HRF selection on different tasks was analyzed by using data collected from two groups of rats receiving either 3 mA whisker pad or 3 mA forepaw electrical stimulations (n = 10 for each group). Under whisker pad stimulation with large blood-oxygen-level dependent (BOLD) signal change (4.31 ± 0.42%), BHRF significantly underestimated signal changes (P < 0.001) and t-statistics (P < 0.001) compared with CHRF or IRF. CHRF and IRF did not provide significantly different t-statistics (P > 0.05). Under forepaw stimulation with small BOLD signal change (1.71 ± 0.34%), different HRFs provided insignificantly different t-statistics (P > 0.05). Therefore, the selected HRF can influence data analysis in rodent fMRI experiments with large BOLD responses but not in those with small BOLD responses.
| S-EPMC6503084 | biostudies-literature