scholarly journals Head motion during fMRI tasks is reduced in children and adults if participants take breaks

2019 ◽  
Author(s):  
Tobias W. Meissner ◽  
Jon Walbrin ◽  
Marisa Nordt ◽  
Kami Koldewyn ◽  
Sarah Weigelt
Keyword(s):  
Data Acquisition ◽  
Time Lag ◽  
Task Engagement ◽  
Fmri Data ◽  
Head Motion ◽  
List Type ◽  
Positive Effects ◽  
Scan Time ◽  
Pediatric Neuroimaging ◽  
Child Friendly

AbstractHead motion remains a challenging confound in functional magnetic resonance imaging (fMRI) studies of both children and adults. Most pediatric neuroimaging labs have developed experience-based, child-friendly standards concerning e.g. the maximum length of a session or the time between mock scanner training and actual scanning. However, it is unclear which factors of child-friendly neuroimaging approaches are effective in reducing head motion. Here, we investigate three main factors including (i) time lag of mock scanner training to the actual scan, (ii) prior scan time, and (iii) task engagement in a dataset of 77 children (aged 6-13) and 64 adults (aged 18-35) using a multilevel modeling approach. In children, distributing fMRI data acquisition across multiple same-day sessions reduces head motion. In adults, motion is reduced after inside-scanner breaks. Despite these positive effects of splitting up data acquisition, motion increases over the course of a study as well as over the course of a run in both children and adults. Our results suggest that splitting up fMRI data acquisition is an effective tool to reduce head motion in general. At the same time, different ways of splitting up data acquisition benefit children and adults.HighlightsIn children, fMRI data acquisition split into multiple sessions reduces head motionIn adults, fMRI data acquisition split by inside-scanner breaks reduces head motionIn both children and adults, motion increases over the duration of a studyIn both children and adults, motion increases over the duration of a run

scholarly journals Controlling motion artefact levels in MR images by suspending data acquisition during periods of head motion

2017 ◽  
Author(s):  
Rémi Castella ◽  
Lionel Arn ◽  
Estelle Dupuis ◽  
Martina F. Callaghan ◽  
Bogdan Draganski ◽  
...  
Keyword(s):  
Data Quality ◽  
Data Acquisition ◽  
Motion Correction ◽  
Head Movements ◽  
Head Motion ◽  
Motion Artefacts ◽  
Motion Artefact ◽  
Position Information ◽  
Trade Off ◽  
Scan Time

AbstractHead movements are a major source of MRI artefacts that hamper radiological assessment and computer-based morphological and functional measures of the human brain. Prospective motion correction techniques continuously update the MRI scanner based on head position information provided by an external tracking system. While prospective motion correction significantly improves data quality, strong motion artefacts may remain with large head motions or when motion takes place at sensitive times of the acquisition. Here we present a framework that allows the suspension of data acquisition when head motion is predicted to have a strong negative impact on data quality. The predictor, calculated in real-time during the acquisition, accounts for the amplitude of the signal acquired at the time of the motion, thereby offering a re-acquisition strategy more efficient than relying on head speed alone. The suspension of data acquisition is governed by the trade-off between image degradation due to motion and prolonging the scan time. This trade-off can be tuned by the user according to the desired level of image quality and the participant‘s tolerability. We test the framework using two motion experiments and two head coils. Significant improvements in data quality are obtained with stringent threshold values for the suspension of acquisition. Substantial reductions in motion artefact levels are also achieved with minimal prolongation of scan time. However, high levels of motion artefacts occasionally remain despite stringent thresholds with the 64-channel head coil, an effect that might be attributed to head movement in the sharp sensitivity profile of this coil.

scholarly journals Removal of high frequency contamination from motion estimates in single-band fMRI saves data without biasing functional connectivity

2019 ◽  
Author(s):  
Caterina Gratton ◽  
Ally Dworetsky ◽  
Rebecca S. Coalson ◽  
Babatunde Adeyemo ◽  
Timothy O. Laumann ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
High Frequency ◽  
Large Data ◽  
Motion Artifacts ◽  
Single Band ◽  
Fmri Data ◽  
Head Motion ◽  
List Type ◽  
Motion Parameters ◽  
Filtering Approach

AbstractDenoising fMRI data requires assessment of frame-to-frame head motion and removal of the biases motion introduces. This is usually done through analysis of the parameters calculated during retrospective head motion correction (i.e., ‘motion’ parameters). However, it is increasingly recognized that respiration introduces factitious head motion via perturbations of the main (B0) field. This effect appears as higher-frequency fluctuations in the motion parameters (> 0.1 Hz, here referred to as ‘HF-motion’), primarily in the phase-encoding direction. This periodicity can sometimes be obscured in standard single-band fMRI (TR 2.0 – 2.5 s.) due to aliasing. Here we examined (1) how prevalent HF-motion effects are in seven single-band datasets with TR from 2.0 - 2.5 s and (2) how HF-motion affects functional connectivity. We demonstrate that HF-motion is relatively trait-like and more common in older adults, those with higher body mass index, and those with lower cardiorespiratory fitness. We propose a low-pass filtering approach to remove the contamination of high frequency effects from motion summary measures, such as framewise displacement (FD). We demonstrate that in most datasets this filtering approach saves a substantial amount of data from FD-based frame censoring, while at the same time reducing motion biases in functional connectivity measures. These findings suggest that filtering motion parameters is an effective way to improve the fidelity of head motion estimates, even in single band datasets. Particularly large data savings may accrue in datasets acquired in older and less fit participants.Highlights-Single-band fMRI motion traces show factitious high-frequency content (HF-motion)-The magnitude of HF-motion relates to age and other demographic factors-HF-motion elevates framewise displacement (FD) and causes data loss-Substantial fMRI data can be recovered from censoring by filtering motion traces-Filtering motion traces reduces motion artifacts in functional connectivity

Aging effect on head motion: A Machine Learning study on resting state fMRI data

2021 ◽  
Vol 352 ◽  
pp. 109084
Author(s):  
Valeria Saccà ◽  
Alessia Sarica ◽  
Andrea Quattrone ◽  
Federico Rocca ◽  
Aldo Quattrone ◽  
...  
Keyword(s):  
Machine Learning ◽  
Resting State ◽  
Aging Effect ◽  
Resting State Fmri ◽  
Fmri Data ◽  
Head Motion ◽  
Learning Study

scholarly journals Automated video-based heart rate tracking for the anesthetized and behaving monkey

2020 ◽  
Author(s):  
Mathilda Froesel ◽  
Quentin Goudard ◽  
Marc Hauser ◽  
Maëva Gacoin ◽  
Suliann Ben Hamed
Keyword(s):  
Heart Rate ◽  
Wavelet Transform ◽  
Ground Truth ◽  
Macaque Monkey ◽  
Head Motion ◽  
List Type ◽  
Tracking Method ◽  
Skin Reflectance ◽  
Behaving Monkeys ◽  
Human Primate

AbstractBackgroundHeart rate is extremely valuable in the study of complex behaviours and their physiological correlates in non-human primates. However, collecting this information is often challenging, involving either invasive implants or tedious behavioural training.New MethodIn the present study, we implement a Eulerian Video Magnification (EVM) heart tracking method in the macaque monkey combined with wavelet transform. This is based on a measure of image to image fluctuations in skin reflectance due to changes in blood influx.ResultsWe show a strong temporal coherence and amplitude match between EVM-based heart tracking and ground truth ECG, from both color (RGB) and infrared (IR) videos, in anesthetized macaques, to a level comparable to what can be achieved in humans. We further show that this method allows to identify consistent heart rate changes following the presentation of conspecific emotional voices or faces.Comparison with Existing Method(s)Eulerian Video Magnification (EVM) is used to extract heart rate in humans but has never been applied to non-human primates. Video photoplethysmography allows to extract awake macaques heart rate from RGB videos. In contrast, our method allows to extract awake macaques heart rate from both RGB and IR videos and is particularly resilient to the head motion that can be observed in awake behaving monkeys.ConclusionsOverall, we believe that this method can be generalized as a tool to track heart rate of the awake behaving monkey, for ethological, behavioural, neuroscience or welfare purposes.HighlightsHeart rate varies during complex non-human primate (NHP) behaviour and cognition.We apply Eulerian Video Magnification to track NHP heart rate (EVM-HR).EVM-HR can be used with RGB & IR videos, and anesthetized or awake NHPs.NHP EVM-HR vary with emotional content of presented stimuli.EVM-HR is of interest to ethology, behavioural, neuroscience & welfare purposes.

scholarly journals Dissociating refreshing and elaboration and their impacts on memory

2018 ◽  
Author(s):  
Lea M. Bartsch ◽  
Vanessa M. Loaiza ◽  
Lutz Jäncke ◽  
Klaus Oberauer ◽  
Jarrod A. Lewis-Peacock
Keyword(s):  
Older Adults ◽  
Memory Performance ◽  
Ethics Committees ◽  
Fmri Data ◽  
Ethical Review ◽  
Long Term Memory ◽  
List Type ◽  
Term Memory ◽  
Age Related

AbstractMaintenance of information in working memory (WM) is assumed to rely on refreshing and elaboration, but clear mechanistic descriptions of these cognitive processes are lacking, and it is unclear whether they are simply two labels for the same process. This fMRI study investigated the extent to which refreshing, elaboration, and repeating of items in WM are distinct neural processes with dissociable behavioral outcomes in WM and long-term memory (LTM). Multivariate pattern analyses of fMRI data revealed differentiable neural signatures for these processes, which we also replicated in an independent sample of older adults. In some cases, the degree of neural separation within an individual predicted their memory performance. Elaboration improved LTM, but not WM, and this benefit increased as its neural signature became more distinct from repetition. Refreshing had no impact on LTM, but did improve WM, although the neural discrimination of this process was not predictive of the degree of improvement. These results demonstrate that refreshing and elaboration are separate processes that differently contribute to memory performance.HighlightsRepeated reading, refreshing, and elaboration are differentiable in brain activation patterns in both young and older adults.Elaboration selectively improved long-term memory for young adults, and the size of the benefit was related to the neural separability of elaboration from other processes.Older adults implemented a sub-optimal form of elaboration, and this may be a factor contributing to age-related deficits in long-term memory.Ethics statementThe study was approved by the ethical review board of the canton of Zurich (BASEC-No. 2017-00190) and all subjects gave informed written consent in accordance with the Declaration of Helsinki.Data and code availability statementAll behavioral data and analysis scripts can be assessed on the Open Science Framework (osf.io/p2h8b/). The fMRI data that support the findings of this study are available on request from the corresponding author, LMB. The fMRI data are not publicly available due to restrictions of the Swiss Ethics Committees on research involving humans regarding data containing information that could compromise the privacy of research participants.

scholarly journals Implications of drift and rapid evolution on negative niche construction

2021 ◽  
Author(s):  
Phuong Linh Nguyen ◽  
Manon Costa ◽  
Nicolas Loeuille
Keyword(s):  
Common Good ◽  
Niche Construction ◽  
Time Lag ◽  
Rapid Evolution ◽  
Tragedy Of The Commons ◽  
List Type ◽  
Time Lags ◽  
Process Waste ◽  
Waste Production ◽  
The Commons

AbstractOrganisms throughout their lives constantly modify their surrounding environment; such activities are often termed niche construction. An important property of niche construction is that its consequences can persist for a long period of time and several subsequent generations can be affected. This phenomenon is described as a time lag in niche construction, or ecological inheritance.Studies have suggested that time lag in niche construction can help avoiding the tragedy of the commons. In other words, it can lead to evolution of contribution to a common good, which is associated with positive niche construction, or to the limitation of a common bad, which is associated with negative niche construction.In this article, we will study the evolutionary consequences of incorporating time lags in a negative niche construction process: waste production. We consider a population that extrudes waste into its environment as it consumes resources to grow and reproduce. Higher consumption rates can lead to higher waste production. Individuals that adopt this selfish strategy are expected to be selected as toxic effects are equally shared among all individuals.We show that indeed this tragedy of the commons persists in many cases and selfish strategies evolve in general. When evolution is rapid and intragenerational time lag is incorporated, however, selfish strategies are no longer favoured and strategies resulting in less waste production can be selected. Importantly, heavy pollution results in smaller population sizes, so that drift becomes more important than natural selection and limits the evolution of higher waste production.

scholarly journals The efficacy of different preprocessing steps in reducing motion-related confounds in diffusion MRI connectomics

2020 ◽  
Author(s):  
Stuart Oldham ◽  
Aurina Arnatkevic̆iūtė ◽  
Robert E. Smith ◽  
Jeggan Tiego ◽  
Mark A. Bellgrove ◽  
...  
Keyword(s):  
Diffusion Mri ◽  
Motion Correction ◽  
Healthy Adult ◽  
Structural Connectivity ◽  
Head Motion ◽  
List Type ◽  
Edge Weighting ◽  
Quantitative Metrics ◽  
The Impact ◽  
Connectivity Strength

AbstractHead motion is a major confounding factor in neuroimaging studies. While numerous studies have investigated how motion impacts estimates of functional connectivity, the effects of motion on structural connectivity measured using diffusion MRI have not received the same level of attention, despite the fact that, like functional MRI, diffusion MRI relies on elaborate preprocessing pipelines that require multiple choices at each step. Here, we report a comprehensive analysis of how these choices influence motion-related contamination of structural connectivity estimates. Using a healthy adult sample (N = 252), we evaluated 240 different preprocessing pipelines, devised using plausible combinations of different choices related to explicit head motion correction, tractography propagation algorithms, track seeding methods, track termination constraints, quantitative metrics derived for each connectome edge, and parcellations. We found that an approach to motion correction that includes outlier replacement and within-slice volume correction led to a dramatic reduction in cross-subject correlations between head motion and structural connectivity strength, and that motion contamination is more severe when quantifying connectivity strength using mean tract fractional anisotropy rather than streamline count. We also show that the choice of preprocessing strategy can significantly influence subsequent inferences about network organization, with the location of network hubs varying considerably depending on the specific preprocessing steps applied. Our findings indicate that the impact of motion on structural connectivity can be successfully mitigated using recent motion-correction algorithms that include outlier replacement and within-slice motion correction.HighlightsWe assess how motion affects structural connectivity in 240 preprocessing pipelinesMotion contamination of structural connectivity depends on preprocessing choicesAdvanced motion correction tools reduce motion confoundsFA edge weighting is more susceptible to motion effects than streamline count

scholarly journals On the Optimal Strategy for Tackling Head Motion in fMRI Data

2021 ◽  
Author(s):  
Júlia Soares ◽  
Rodolfo Abreu ◽  
Ana Lima ◽  
Sónia Batista ◽  
Lívia Sousa ◽  
...  
Keyword(s):  
Optimal Strategy ◽  
Fmri Data ◽  
Head Motion

scholarly journals O09 Drug delivery kinetics of intravenous gentamicin in a population of neonates

2019 ◽  
Vol 104 (6) ◽  
pp. e4.2-e4
Author(s):  
G Salis ◽  
N Medlicott ◽  
D Reith
Keyword(s):  
Drug Delivery ◽  
Time Lag ◽  
Medical Science ◽  
Compartment Model ◽  
Pharmacokinetic Parameters ◽  
List Type ◽  
First Order ◽  
Model Drug ◽  
The Individual ◽  
Kinetics Of

BackgroundGentamicin is commonly used in the NICU setting and is often administered via long lines, which increases variability in the rate of administration. We aimed to model drug delivery pharmacokinetic parameters for intravenous gentamicin administered via umbilical venous catheters (UVCs).MethodsData was modelled from infusion simulations of gentamicin delivery using UVCs with a background flow rate of 0.5 ml/h.1 Different combinations of dose (2 mg, 5 mg) were given by bolus injection over 3–5 minutes, followed by a normal saline flush (1 ml, 2 ml). Gentamicin levels were measured at 5 minute intervals over an hour via high pressure liquid chromatography.Phoenix Certara (version 8.1) was used for modelling. An extravascular model with clearance removed was used to predict parameters: absorption constant (Ka), time lag (Tlag), and bioavailability (F). F was used to enable an estimate of the variability in dose administered. Different error models were tested to ascertain which best described the data.ResultsAn extravascular one compartment model with first order absorption and additive error best described the data. Estimates for the model with a 2 mg dose and 1 ml flush were Ka 0.34L/min, Tlag 1.28min, F 0.97, standard deviation (stdev) 0.14. For 2 mg, 2 ml flush, estimates were Ka 0.86L/min, Tlag 3.01min, F 0.87, stdev 0.01. For 5 mg, 1 ml flush, estimates were Ka 0.48L/min, Tlag 3.13min, F 1.03, stdev 0.12. For 5 mg, 2 ml flush, estimates were Ka 0.83L/min, Tlag 3.29min, F 1.09, stdev 0.02. For each model epsshrinkage and nshrinkage for Tlag and F were low, however nshrinkage for ka was 0.9999.ConclusionThis is the first known modelling of gentamicin delivery kinetics. The studies all had high nshrinkage for Ka, therefore the individual estimates of ka may be unreliable. Further studies with a higher number of replicates would provide more favourable data for estimating Ka.ReferenceLala AC ( 2016). Variability in neonatal gentamicin administration influencing drug delivery kinetics (Thesis, Master of Medical Science). University of Otago.Disclosure(s)No conflict of interest declared. Funding for research via the Freemasons Society of New Zealand.

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