Quantitative Total-Body Imaging of Blood Flow with High Temporal Resolution Early Dynamic 18F-Fluorodeoxyglucose PET Kinetic Modeling.

Quantitative total-body PET imaging of blood flow can be performed with freely diffusible flow radiotracers such as 15O-water and 11C-butanol, but their short half-lives necessitate close access to a cyclotron. Past efforts to measure blood flow with the widely available radiotracer 18F-fluorodeoxyglucose (FDG) were limited to tissues with high 18F-FDG extraction fraction. In this study, we developed an early-dynamic 18F-FDG PET method with high temporal resolution kinetic modeling to assess total-body blood flow based on deriving the vascular transit time of 18F-FDG and conducted a pilot comparison study against a 11C-butanol reference. Methods: The first two minutes of dynamic PET scans were reconstructed at high temporal resolution (60×1 s, 30×2 s) to resolve the rapid passage of the radiotracer through blood vessels. In contrast to existing methods that use blood-to-tissue transport rate ( K 1 ) as a surrogate of blood flow, our method directly estimates blood flow using a distributed kinetic model (adiabatic approximation to the tissue homogeneity model; AATH). To validate our 18F-FDG measurements of blood flow against a flow radiotracer, we analyzed total-body dynamic PET images of six human participants scanned with both 18F-FDG and 11C-butanol. An additional thirty-four total-body dynamic 18F-FDG PET scans of healthy participants were analyzed for comparison against literature blood flow ranges. Regional blood flow was estimated across the body and total-body parametric imaging of blood flow was conducted for visual assessment. AATH and standard compartment model fitting was compared by the Akaike Information Criterion at different temporal resolutions. Results: 18F-FDG blood flow was in quantitative agreement with flow measured from 11C-butanol across same-subject regional measurements (Pearson R=0.955, p<0.001; linear regression y=0.973x-0.012), which was visually corroborated by total-body blood flow parametric imaging. Our method resolved a wide range of blood flow values across the body in broad agreement with literature ranges (e.g., healthy cohort average: 0.51±0.12 ml/min/cm3 in the cerebral cortex and 2.03±0.64 ml/min/cm3 in the lungs, respectively). High temporal resolution (1 to 2 s) was critical to enabling AATH modeling over standard compartment modeling. Conclusions: Total-body blood flow imaging was feasible using early-dynamic 18F-FDG PET with high-temporal resolution kinetic modeling. Combined with standard 18F-FDG PET methods, this method may enable efficient single-tracer flow-metabolism imaging, with numerous research and clinical applications in oncology, cardiovascular disease, pain medicine, and neuroscience.

Iterative Data-adaptive Autoregressive (IDAR) whitening procedure for long and short TR fMRI.

Introduction: Functional magnetic resonance imaging (fMRI) has become a fundamental tool for studying brain function. However, the presence of serial correlations in fMRI data complicates data analysis, violates the statistical assumptions of analyses methods, and can lead to incorrect conclusions in fMRI studies. Methods: In this paper, we show that conventional whitening procedures designed for data with longer repetition times (TRs) (>2 s) are inadequate for the increasing use of short-TR fMRI data. Furthermore, we comprehensively investigate the shortcomings of existing whitening methods and introduce an iterative whitening approach named "IDAR" (Iterative Data-adaptive Autoregressive model) to address these shortcomings. IDAR employs high-order autoregressive (AR) models with flexible and data-driven orders, offering the capability to model complex serial correlation structures in both short-TR and long-TR fMRI datasets. Results: Conventional whitening methods, such as AR(1), ARMA(1,1), and higher-order AR, were effective in reducing serial correlation in long-TR data but were largely ineffective in even reducing serial correlation in short-TR data. In contrast, IDAR significantly outperformed conventional methods in addressing serial correlation, power, and Type-I error for both long-TR and especially short-TR data. However, IDAR could not simultaneously address residual correlations and inflated Type-I error effectively. Discussion: This study highlights the urgent need to address the problem of serial correlation in short-TR (< 1 s) fMRI data, which are increasingly used in the field. Although IDAR can address this issue for a wide range of applications and datasets, the complexity of short-TR data necessitates continued exploration and innovative approaches. These efforts are essential to simultaneously reduce serial correlations and control Type-I error rates without compromising analytical power.

Individual peak alpha frequency correlates with visual temporal resolution, but only under specific task conditions.

The study of alpha band oscillations in the brain is a popular topic in cognitive neuroscience. A fair amount of research in recent years has focused on the potential role these oscillations may play in the discrete sampling of continuous sensory information. In particular, the question of whether or not peak frequency in the alpha band is linked with the temporal resolution of visual perception is a topic of ongoing debate. Some studies have reported a correlation between the two, whereas others were unable to observe a link. It is unclear whether these conflicting findings are due to differing methodologies and/or low statistical power, or due to the absence of a true relationship. Replication studies are needed to gain better insight into this matter. In the current study, we replicated an experiment published in a 2015 paper by Samaha and Postle. Additionally, we expanded on this study by adding an extra behavioural task, the critical flicker fusion task, to investigate if any links with peak alpha frequency are generalizable across multiple measures for visual temporal resolution. We succeeded in replicating some, but not all of Samaha and Postle's findings. Our partial replication suggests that there may be a link between visual temporal resolution and peak alpha frequency. However, this relationship may be very small and only apparent for specific stimulus parameters. The correlations found in our study did not generalize to other behavioural measures for visual temporal resolution.

Temporal resolution relates to sensory hyperreactivity independently of stimulus detection sensitivity in individuals with autism spectrum disorder.

Researchers have been focusing on perceptual characteristics of autism spectrum disorder (ASD) in terms of sensory hyperreactivity. Previously, we demonstrated that temporal resolution, which is the accuracy to differentiate the order of two successive vibrotactile stimuli, is associated with the severity of sensory hyperreactivity. We currently examined whether an increase in the perceptual intensity of a tactile stimulus, despite its short duration, is derived from high temporal resolution and high frequency of sensory temporal summation. Twenty ASD and 22 typically developing (TD) participants conducted two psychophysical experimental tasks to evaluate detectable duration of vibrotactile stimulus with same amplitude and to evaluate temporal resolution. The sensory hyperreactivity was estimated using self-reported questionnaire. There was no relationship between the temporal resolution and the duration of detectable stimuli in both groups. However, the ASD group showed severe sensory hyperreactivity in daily life than TD group, and the ASD participants with severe sensory hyperreactivity tended to have high temporal resolution, not high sensitivity of detectable duration. Contrary to the hypothesis, there might be different processing between temporal resolution and sensitivity for stimulus detection. We suggested that the atypical temporal processing would affect to sensory reactivity in ASD.

Effect of the Relationship between Respiratory Interval and Temporal Resolution on Image Quality in Free-breathing Abdominal MR Imaging.

PURPOSE: To evaluate how the relationship between respiratory interval (RI) and temporal resolution (TR) impacts image quality in free-breathing abdominal MRI (FB-aMRI) using golden-angle radial sparse parallel (GRASP). METHODS: Ten healthy volunteers (25.9 ± 2.5 years, four women) underwent 2 mins free-breathing fat-suppression T1-weighted imaging using GRASP at RIs of 3 and 5s (RI3 and RI5, respectively) and retrospectively reconstructed at TR of 1.8, 2.9, 4.8, and 7.7s (TR1.8, TR2.9, TR4.8, and TR7.7, respectively) in each patient. The standard deviation (SD) under the diaphragm was measured using SD maps showing the discrepancy for each horizontal section at all TRs. Two radiologists evaluated image quality (visualization of the right hepatic vein at the confluence of the inferior vena cava, posterior segment branch of portal vein, pancreas, left kidney, and artifacts) at all TRs using a 5-point scale. RESULTS: The SD was significantly higher at TR1.8 compared to TR4.8 (P < 0.01) and TR7.7 (P < 0.001), as well as at TR2.9 compared to TR7.7 (P < 0.01) for both RIs. The SD between TR4.8 and TR7.7 did not differ for both RIs. For all visual assessment metrics, the TR1.8 scores were significantly lower than the TR4.8 and TR7.7 scores for both RIs. The pancreas and left kidney scores at TR2.9 were significantly lower than those at TR7.7 (P < 0.05) for RI5. Additionally, the left kidney score at TR1.8 was lower than that at TR2.9 (P < 0.05) for RI3. All scores at TR2.9, TR4.8, and TR7.7 were similar for RI3, while those at TR4.8 and TR7.7 were similar for RI5. CONCLUSION: Prolonging the TRs compared to RIs enhances image quality in FB-aMRI using GRASP.

Temporal resolution and pitch discrimination in music education: novel data in children.

BACKGROUND: Rehabilitation of hearing and listening difficulties through neuroplasticity of the auditory nervous system is a promising technique. Evidence of enhanced auditory processing in adult musicians is often not based on clinical auditory processing tests and is lacking in children with musical education. PURPOSE: The aim of this study is to investigate the temporal resolution and frequency discrimination elements of auditory processing both in adults and children with musical education and to compare them with those without any musical education. METHODS: Participants consisted of ten children without musical training and ten children with musical training with mean age 11.3 years and range 8-15 years as well as ten adults without musical education and ten adults with musical education with mean age 38.1 years and range 30-45 years. All participants were tested with two temporal resolution tests (GIN:Gaps-In-Noise and RGDT:Random Gap Detection Test), a temporal ordering frequency test (FPT:Frequency Pattern Test), and a frequency discrimination test (DLF: Different Limen for Frequency). RESULTS: All test results revealed better performance in both children and adults with musical training for both ears. CONCLUSION: A positive effect of formal music education for specific auditory processing elements in both children and adults is documented. Larger samples, longitudinal studies, as well as groups with impaired hearing and/or auditory processing are needed to further substantiate the effect shown.

Imaging Spatial and Temporal Variation in Photosynthesis Using Chlorophyll Fluorescence.

Chlorophyll fluorescence imaging provides a noninvasive rapid screen to assess the physiological status of a number of leaves or plants simultaneously. Although there are no standard protocols for chlorophyll fluorescence imaging, here we provide an example of routines for some of the typical measurements.

Quantitative Characterization of Respiratory Patterns on Dynamic Higher Temporal Resolution MRI to Stratify Postacute Covid-19 Patients by Cardiopulmonary Symptom Burden.

BACKGROUND: Postacute Covid-19 patients commonly present with respiratory symptoms; however, a noninvasive imaging method for quantitative characterization of respiratory patterns is lacking. PURPOSE: To evaluate if quantitative characterization of respiratory pattern on free-breathing higher temporal resolution MRI stratifies patients by cardiopulmonary symptom burden. STUDY TYPE: Prospective analysis of retrospectively acquired data. SUBJECTS: A total of 37 postacute Covid-19 patients (25 male; median [interquartile range (IQR)] age: 58 [42-64] years; median [IQR] days from acute infection: 335 [186-449]). FIELD STRENGTH/SEQUENCE: 0.55 T/two-dimensional coronal true fast imaging with steady-state free precession (trueFISP) at higher temporal resolution. ASSESSMENT: Patients were stratified into three groups based on presence of no (N = 11), 1 (N = 14), or ≥2 (N = 14) cardiopulmonary symptoms, assessed using a standardized symptom inventory within 1 month of MRI. An automated lung postprocessing workflow segmented each lung in each trueFISP image (temporal resolution 0.2 seconds) and respiratory curves were generated. Quantitative parameters were derived including tidal lung area, rates of inspiration and expiration, lung area coefficient of variability (CV), and respiratory incoherence (departure from sinusoidal pattern) were. Pulmonary function tests were recorded if within 1 month of MRI. Qualitative assessment of respiratory pattern and lung opacity was performed by three independent readers with 6, 9, and 23 years of experience. STATISTICAL TESTS: Analysis of variance to assess differences in demographic, clinical, and quantitative MRI parameters among groups; univariable analysis and multinomial logistic regression modeling to determine features predictive of patient symptom status; Akaike information criterion to compare the quality of regression models; Cohen and Fleiss kappa (κ) to quantify inter-reader reliability. Two-sided 5% significance level was used. RESULTS: Tidal area and lung area CV were significantly higher in patients with two or more symptoms than in those with one or no symptoms (area: 15.4 cm2 vs. 12.9 cm2 vs. 12.8 cm2 ; CV: 0.072, 0.067, and 0.058). Respiratory incoherence was significantly higher in patients with two or more symptoms than in those with one or no symptoms (0.05 vs. 0.043 vs. 0.033). There were no significant differences in patient age (P = 0.19), sex (P = 0.88), lung opacity severity (P = 0.48), or pulmonary function tests (P = 0.35-0.97) among groups. Qualitative reader assessment did not distinguish between groups and showed slight inter-reader agreement (κ = 0.05-0.11). DATA CONCLUSION: Quantitative respiratory pattern measures derived from dynamic higher-temporal resolution MRI have potential to stratify patients by symptom burden in a postacute Covid-19 cohort. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 3.

High-Temporal-Resolution Kinetic Modeling of Lung Tumors with Dual-Blood Input Function Using Total-Body Dynamic PET.

The lungs are supplied by both the pulmonary arteries carrying deoxygenated blood originating from the right ventricle and the bronchial arteries carrying oxygenated blood downstream from the left ventricle. However, this effect of dual blood supply has never been investigated using PET, partially because the temporal resolution of conventional dynamic PET scans is limited. The advent of PET scanners with a long axial field of view, such as the uEXPLORER total-body PET/CT system, permits dynamic imaging with high temporal resolution (HTR). In this work, we modeled the dual-blood input function (DBIF) and studied its impact on the kinetic quantification of normal lung tissue and lung tumors using HTR dynamic PET imaging. Methods: Thirteen healthy subjects and 6 cancer subjects with lung tumors underwent a dynamic 18F-FDG scan with the uEXPLORER for 1 h. Data were reconstructed into dynamic frames of 1 s in the early phase. Regional time-activity curves of lung tissue and tumors were analyzed using a 2-tissue compartmental model with 3 different input functions: the right ventricle input function, left ventricle input function, and proposed DBIF, all with time delay and dispersion corrections. These models were compared for time-activity curve fitting quality using the corrected Akaike information criterion and for differentiating lung tumors from lung tissue using the Mann-Whitney U test. Voxelwise multiparametric images by the DBIF model were further generated to verify the regional kinetic analysis. Results: The effect of dual blood supply was pronounced in the high-temporal-resolution time-activity curves of lung tumors. The DBIF model achieved better time-activity curve fitting than the other 2 single-input models according to the corrected Akaike information criterion. The estimated fraction of left ventricle input was low in normal lung tissue of healthy subjects but much higher in lung tumors (∼0.04 vs. ∼0.3, P < 0.0003). The DBIF model also showed better robustness in the difference in 18F-FDG net influx rate [Formula: see text] and delivery rate [Formula: see text] between lung tumors and normal lung tissue. Multiparametric imaging with the DBIF model further confirmed the differences in tracer kinetics between normal lung tissue and lung tumors. Conclusion: The effect of dual blood supply in the lungs was demonstrated using HTR dynamic imaging and compartmental modeling with the proposed DBIF model. The effect was small in lung tissue but nonnegligible in lung tumors. HTR dynamic imaging with total-body PET can offer a sensitive tool for investigating lung diseases.

Blind deconvolution decreases requirements on temporal resolution of DCE-MRI: Application to 2nd generation pharmacokinetic modeling.

PURPOSE: Dynamic Contrast-Enhanced (DCE) MRI with 2nd generation pharmacokinetic models provides estimates of plasma flow and permeability surface-area product in contrast to the broadly used 1st generation models (e.g. the Tofts models). However, the use of 2nd generation models requires higher frequency with which the dynamic images are acquired (around 1.5 s per image). Blind deconvolution can decrease the demands on temporal resolution as shown previously for one of the 1st generation models. Here, the temporal-resolution requirements achievable for blind deconvolution with a 2nd generation model are studied. METHODS: The 2nd generation model is formulated as the distributed-capillary adiabatic-tissue-homogeneity (DCATH) model. Blind deconvolution is based on Parker's model of the arterial input function. The accuracy and precision of the estimated arterial input functions and the perfusion parameters is evaluated on synthetic and real clinical datasets with different levels of the temporal resolution. RESULTS: The estimated arterial input functions remained unchanged from their reference high-temporal-resolution estimates (obtained with the sampling interval around 1 s) when increasing the sampling interval up to about 5 s for synthetic data and up to 3.6-4.8 s for real data. Further increasing of the sampling intervals led to systematic distortions, such as lowering and broadening of the 1st pass peak. The resulting perfusion-parameter estimation error was below 10% for the sampling intervals up to 3 s (synthetic data), in line with the real data perfusion-parameter boxplots which remained unchanged up to the sampling interval 3.6 s. CONCLUSION: We show that use of blind deconvolution decreases the demands on temporal resolution in DCE-MRI from about 1.5 s (in case of measured arterial input functions) to 3-4 s. This can be exploited in increased spatial resolution or larger organ coverage.

Assessment of temporal resolution and detectability of moving objects in CT: A task-based image quality study.

The metrics used for assessing image quality in computed tomography (CT) do not integrate the influence of temporal resolution. A shortcoming in the assessment of image quality for imaging protocols where motion blur can therefore occur. We developed a method to calculate the temporal resolution of standard CT protocols and introduced a specific spatiotemporal formulation of the non-prewhitening with eye filter (NPWE) model observer to assess the detectability of moving objects as a function of their speed. We scanned a cubic water phantom with a plexiglass cylindrical insert (120 HU) using a large panel of acquisition parameters (rotation times, pitch factors and collimation widths) on two systems (GE Revolution Apex and Siemens SOMATOM Force) to determine the in-plane task-based transfer functions (TTF) and noise power spectra (NPS). The phantom set in a uniform rectilinear motion in the transverse plane allowed the temporal modulation transfer function (MTF) calculation. The temporal MTF appropriately compared the temporal resolution of the various acquisition protocols. The longitudinal TTF was measured using a thin tungsten wire. The detectability index showed the advantage of applying high rotation speed, wide collimations and high pitch for object detection in the presence of motion. No counterpart to the increase in these three parameters was found in the in-plane and longitudinal image quality.

Highly Localized Chemical Sampling at Subsecond Temporal Resolution Enabled with a Silicon Nanodialysis Platform at Nanoliter per Minute Flows.

Microdialysis (MD) is a versatile and powerful technique for chemical profiling of biological tissues and is widely used for quantification of neurotransmitters, neuropeptides, metabolites, biomarkers, and drugs in the central nervous system as well as in dermatology, ophthalmology, and pain research. However, MD performance is severely limited by fundamental tradeoffs between chemical sensitivity, spatial resolution, and temporal response. Here, by using wafer-scale silicon microfabrication, we develop and demonstrate a nanodialysis (ND) sampling probe that enables highly localized chemical sampling with 100 µm spatial resolution and subsecond temporal resolution at high recovery rates. These performance metrics, which are 100-1000× superior to existing MD approaches, are enabled by a 100× reduction of the microfluidic channel cross-section, a corresponding drastic 100× reduction of flow rates to exceedingly slow few nL/min flows, and integration of a nanometer-thin nanoporous membrane with high transport flux into the probe sampling area. Miniaturized ND probes may allow for the minimally invasive and highly localized sampling and chemical profiling in live biological tissues with high spatiotemporal resolution for clinical, biomedical, and pharmaceutical applications.

Quantification and Characterization of Fine Plastic Particles as Considerable Components in Atmospheric Fine Particles.

The negative effects of air pollution, especially fine particulate matter (PM2.5, particles with an aerodynamic diameter of ≤2.5 µm), on human health, climate, and ecosystems are causing significant concern. Nevertheless, little is known about the contributions of emerging pollutants such as plastic particles to PM2.5 due to the lack of continuous measurements and characterization methods for atmospheric plastic particles. Here, we investigated the levels of fine plastic particles (FPPs) in PM2.5 collected in urban Shanghai at a 2 h resolution by using a novel versatile aerosol concentration enrichment system that concentrates ambient aerosols up to 10-fold. The FPPs were analyzed offline using the combination of spectroscopic and microscopic techniques that distinguished FPPs from other carbon-containing particles. The average FPP concentrations of 5.6 µg/m3 were observed, and the ratio of FPPs to PM2.5 was 13.2% in this study. The FPP sources were closely related to anthropogenic activities, which pose a potential threat to ecosystems and human health. Given the dramatic increase in plastic production over the past 70 years, this study calls for better quantification and control of FPP pollution in the atmosphere.

Effect of temporal resolution on calcium scoring: insights from photon-counting detector CT.

To intra-individually investigate the variation of coronary artery calcium (CAC), aortic valve calcium (AVC), and mitral annular calcium (MAC) scores and the presence of blur artifacts as a function of temporal resolution in patients undergoing non-contrast cardiac CT on a dual-source photon counting detector (PCD) CT. This retrospective, IRB-approved study included 70 patients (30 women, 40 men, mean age 78 ± 9 years) who underwent ECG-gated cardiac non-contrast CT with PCD-CT (gantry rotation time 0.25 s) prior to transcatheter aortic valve replacement. Each scan was reconstructed at a temporal resolution of 66 ms using the dual-source information and at 125 ms using the single-source information. Average heart rate and heart rate variability were calculated from the recorded ECG. CAC, AVC, and MAC were quantified according to the Agatston method on images with both temporal resolutions. Two readers assessed blur artifacts using a 4-point visual grading scale. The influence of average heart rate and heart rate variability on calcium quantification and blur artifacts of the respective structures were analyzed by linear regression analysis. Mean heart rate and heart rate variability during data acquisition were 76 ± 17 beats per minute (bpm) and 4 ± 6 bpm, respectively. CAC scores were smaller on 66 ms (median, 511; interquartile range, 220-978) than on 125 ms reconstructions (538; 203-1050, p < 0.001). Median AVC scores [2809 (2009-3952) versus 3177 (2158-4273)] and median MAC scores [226 (0-1284) versus 251 (0-1574)] were also significantly smaller on 66ms than on 125ms reconstructions (p < 0.001). Reclassification of CAC and AVC risk categories occurred in 4% and 11% of cases, respectively, whereby the risk category was always overestimated on 125ms reconstructions. Image blur artifacts were significantly less on 66ms as opposed to 125 ms reconstructions (p < 0.001). Intra-individual analyses indicate that temporal resolution significantly impacts on calcium scoring with cardiac CT, with CAC, MAC, and AVC being overestimated at lower temporal resolution because of increased motion artifacts eventually leading to an overestimation of patient risk.

Optimal decoding of neural dynamics occurs at mesoscale spatial and temporal resolutions.

Introduction: Understanding the neural code has been one of the central aims of neuroscience research for decades. Spikes are commonly referred to as the units of information transfer, but multi-unit activity (MUA) recordings are routinely analyzed in aggregate forms such as binned spike counts, peri-stimulus time histograms, firing rates, or population codes. Various forms of averaging also occur in the brain, from the spatial averaging of spikes within dendritic trees to their temporal averaging through synaptic dynamics. However, how these forms of averaging are related to each other or to the spatial and temporal units of information representation within the neural code has remained poorly understood. Materials and methods: In this work we developed NeuroPixelHD, a symbolic hyperdimensional model of MUA, and used it to decode the spatial location and identity of static images shown to n = 9 mice in the Allen Institute Visual Coding-NeuroPixels dataset from large-scale MUA recordings. We parametrically varied the spatial and temporal resolutions of the MUA data provided to the model, and compared its resulting decoding accuracy. Results: For almost all subjects, we found 125ms temporal resolution to maximize decoding accuracy for both the spatial location of Gabor patches (81 classes for patches presented over a 9×9 grid) as well as the identity of natural images (118 classes corresponding to 118 images) across the whole brain. This optimal temporal resolution nevertheless varied greatly between different regions, followed a sensory-associate hierarchy, and was significantly modulated by the central frequency of theta-band oscillations across different regions. Spatially, the optimal resolution was at either of two mesoscale levels for almost all mice: the area level, where the spiking activity of all neurons within each brain area are combined, and the population level, where neuronal spikes within each area are combined across fast spiking (putatively inhibitory) and regular spiking (putatively excitatory) neurons, respectively. We also observed an expected interplay between optimal spatial and temporal resolutions, whereby increasing the amount of averaging across one dimension (space or time) decreases the amount of averaging that is optimal across the other dimension, and vice versa. Discussion: Our findings corroborate existing empirical practices of spatiotemporal binning and averaging in MUA data analysis, and provide a rigorous computational framework for optimizing the level of such aggregations. Our findings can also synthesize these empirical practices with existing knowledge of the various sources of biological averaging in the brain into a new theory of neural information processing in which the unit of information varies dynamically based on neuronal signal and noise correlations across space and time.

Clinical Gaps-in-Noise Measures in Blast-Exposed Veterans: Associations with Electrophysiological and Behavioral Responses.

It has been established that blast exposure and brain injury can result in self-reported and measured auditory processing deficits in individuals with normal or near-normal hearing sensitivity. However, the impaired sensory and/or cognitive mechanisms underlying these auditory difficulties are largely unknown. This work used a combination of behavioral and electrophysiological measures to explore how neural stimulus discrimination and processing speed contribute to impaired temporal processing in blast-exposed Veterans measured using the behavioral Gaps-in-Noise (GIN) Test. Results confirm previous findings that blast exposure can impact performance on the GIN and effect neural auditory discrimination, as measured using the P3 auditory event-related potential. Furthermore, analyses revealed correlations between GIN thresholds, P3 responses, and a measure of behavioral reaction time. Overall, this work illustrates that behavioral responses to the GIN are dependent on both auditory-specific bottom-up processing beginning with the neural activation of the cochlea and auditory brainstem as well as contributions from complex neural networks involved in processing speed and task-dependent target detection.

Considering Caenorhabditis elegans Aging on a Temporal and Tissue Scale: The Case of Insulin/IGF-1 Signaling.

The aging process is inherently complex, involving multiple mechanisms that interact at different biological scales. The nematode Caenorhabditis elegans is a simple model organism that has played a pivotal role in aging research following the discovery of mutations extending lifespan. Longevity pathways identified in C. elegans were subsequently found to be conserved and regulate lifespan in multiple species. These pathways intersect with fundamental hallmarks of aging that include nutrient sensing, epigenetic alterations, proteostasis loss, and mitochondrial dysfunction. Here we summarize recent data obtained in C. elegans highlighting the importance of studying aging at both the tissue and temporal scale. We then focus on the neuromuscular system to illustrate the kinetics of changes that take place with age. We describe recently developed tools that enabled the dissection of the contribution of the insulin/IGF-1 receptor ortholog DAF-2 to the regulation of worm mobility in specific tissues and at different ages. We also discuss guidelines and potential pitfalls in the use of these new tools. We further highlight the opportunities that they present, especially when combined with recent transcriptomic data, to address and resolve the inherent complexity of aging. Understanding how different aging processes interact within and between tissues at different life stages could ultimately suggest potential intervention points for age-related diseases.

Peripheral neural synchrony in post-lingually deafened adult cochlear implant users.

Objective: This paper reports a noninvasive method for quantifying neural synchrony in the cochlear nerve (i.e., peripheral neural synchrony) in cochlear implant (CI) users, which allows for evaluating this physiological phenomenon in human CI users for the first time in the literature. In addition, this study assessed how peripheral neural synchrony was correlated with temporal resolution acuity and speech perception outcomes measured in quiet and in noise in post-lingually deafened adult CI users. It tested the hypothesis that peripheral neural synchrony was an important factor for temporal resolution acuity and speech perception outcomes in noise in post-lingually deafened adult CI users. Design: Study participants included 24 post-lingually deafened adult CI users with a Cochlear™ Nucleus® device. Three study participants were implanted bilaterally, and each ear was tested separately. For each of the 27 implanted ears tested in this study, 400 sweeps of the electrically evoked compound action potential (eCAP) were measured at four electrode locations across the electrode array. Peripheral neural synchrony was quantified at each electrode location using the phase locking value (PLV), which is a measure of trial-by-trial phase coherence among eCAP sweeps/trials. Temporal resolution acuity was evaluated by measuring the within-channel gap detection threshold (GDT) using a three-alternative, forced-choice procedure in a subgroup of 20 participants (23 implanted ears). For each ear tested in these participants, GDTs were measured at two electrode locations with a large difference in PLVs. For 26 implanted ears tested in 23 participants, speech perception performance was evaluated using Consonant-Nucleus-Consonant (CNC) word lists presented in quiet and in noise at signal-to-noise ratios (SNRs) of +10 and +5 dB. Linear Mixed effect Models were used to evaluate the effect of electrode location on the PLV and the effect of the PLV on GDT after controlling for the stimulation level effects. Pearson product-moment correlation tests were used to assess the correlations between PLVs, CNC word scores measured in different conditions, and the degree of noise effect on CNC word scores. Results: There was a significant effect of electrode location on the PLV after controlling for the effect of stimulation level. There was a significant effect of the PLV on GDT after controlling for the effects of stimulation level, where higher PLVs (greater synchrony) led to lower GDTs (better temporal resolution acuity). PLVs were not significantly correlated with CNC word scores measured in any listening condition or the effect of competing background noise presented at a SNR of +10 dB on CNC word scores. In contrast, there was a significant negative correlation between the PLV and the degree of noise effect on CNC word scores for a competing background noise presented at a SNR of +5 dB, where higher PLVs (greater synchrony) correlated with smaller noise effects on CNC word scores. Conclusions: This newly developed method can be used to assess peripheral neural synchrony in CI users, a physiological phenomenon that has not been systematically evaluated in electrical hearing. Poorer peripheral neural synchrony leads to lower temporal resolution acuity and is correlated with a larger detrimental effect of competing background noise presented at a SNR of 5 dB on speech perception performance in post-lingually deafened adult CI users.

Impact of temporal and spatial resolution on atrial feature tracking cardiovascular magnetic resonance imaging.

BACKGROUND: Myocardial deformation assessment by cardiovascular magnetic resonance-feature tracking (CMR-FT) has incremental prognostic value over volumetric analyses. Recently, atrial functional analyses have come to the fore. However, to date recommendations for optimal resolution parameters for accurate atrial functional analyses are still lacking. METHODS: CMR-FT was performed in 12 healthy volunteers and 9 ischemic heart failure (HF) patients. Cine sequences were acquired using different temporal (20, 30, 40 and 50 frames/cardiac cycle) and spatial resolution parameters (high 1.5 × 1.5 mm in plane and 5 mm slice thickness, standard 1.8 × 1.8 × 8 mm and low 3.0 × 3.0 × 10 mm). Inter- and intra-observer reproducibility were calculated. RESULTS: Increasing temporal resolution is associated with higher absolute strain and strain rate (SR) values. Significant changes in strain assessment for left atrial (LA) total strain occurred between 20 and 30 frames/cycle amounting to 2,5-4,4% in absolute changes depending on spatial resolution settings. From 30 frames/cycle onward, absolute strain values remained unchanged. Significant changes of LA strain rate assessment were observed up to the highest temporal resolution of 50 frames/cycle. Effects of spatial resolution on strain assessment were smaller. For LA total strain a general trend emerged for a mild decrease in strain values obtained comparing the lowest to the highest spatial resolution at temporal resolutions of 20, 40 and 50 frames/cycle (p = 0.006-0.046) but not at 30 frames/cycle (p = 0.140). CONCLUSION: Temporal and to a smaller extent spatial resolution affect atrial functional assessment. Consistent strain assessment requires a standard spatial resolution and a temporal resolution of 30 frames/cycle, whilst SR assessment requires even higher settings of at least 50 frames/cycle.

Radial compressed sensing imaging improves the velocity detection limit of single cell tracking time-lapse MRI.

PURPOSE: Time-lapse MRI enables tracking of single iron-labeled cells. Yet, due to temporal blurring, only slowly moving cells can be resolved. To study faster cells for example during inflammatory processes, accelerated acquisition is needed. METHODS: A rotating phantom system was developed to quantitatively measure the current maximum detectable speed of cells in time-lapse MRI. For accelerated cell tracking, an interleaved radial acquisition scheme was applied to phantom and murine brain in vivo time-lapse MRI experiments at 9.4 T. Detection of iron-labeled cells was evaluated in fully sampled and undersampled reconstructions with and without compressed sensing. RESULTS: The rotating phantom system enabled ultra-slow rotation of phantoms and a velocity detection limit of full-brain Cartesian time-lapse MRI of up to 172 µm/min was determined. Both phantom and in vivo measurements showed that single cells can be followed dynamically using radial time-lapse MRI. Higher temporal resolution of undersampled reconstructions reduced geometric distortion, the velocity detection limit was increased to 1.1 mm/min in vitro, and previously hidden fast-moving cells were recovered. In the mouse brain after in vivo labeling, a total of 42 ± 4 cells were counted in fully sampled, but only 7 ± 1 in undersampled images due to streaking artifacts. Using compressed sensing 33 ± 4 cells were detected. CONCLUSION: Interleaved radial time-lapse MRI permits retrospective reconstruction of both fully sampled and accelerated images, enables single cell tracking at higher temporal resolution and recovers cells hidden before due to blurring. The velocity detection limit as determined with the rotating phantom system increased two- to three-fold compared to previous results.