7 research outputs found

    A travelling heads study investigating qMRI metrics on cortical regions

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    Technological advances in magnetic resonance imaging (MRI) have facilitated numerous studies on neural architecture, such as studies addressing pathology, behaviour or individual differences in brain activity. It is important, however, to first ascertain what variation can arise due to site-specific scanner properties (hard- and software). A certain amount of noise in MR images can indeed be attributable to such properties, even when the same scanner is used across different sites. Reproducibility across sites is possible with the use of quantitative MRI metrics (qMRI), where physical properties assigned to voxels allow for non-invasive analysis of brain tissue including sensitivity to iron and myelin content. Leutritz et al. (2020) investigated intra-site (scan-rescan) and intersite (between sites) variability on Siemens and Philips scanners through multi-parameter mapping techniques (MPM). The authors found intra-site scan-rescan coefficients of variance (CoV) ranging between 4% and 16% across parameters, with similar results for inter-site CoV. The current study implements a similar strategy to Leutritz et al. (2020) in that it investigates inter-site and interscanner variability in a "travelling heads" type of study. Using scanners by the same manufacturer (but two different models), the study investigates qMRI metrics for inter-site and inter-scanner differences and their corresponding effects on cortical regions.peer-reviewe

    Frequency drift in MR spectroscopy at 3T

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    Purpose: Heating of gradient coils and passive shim components is a common cause of instability in the B-0 field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites.Method: A standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC).Results: Of the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the first 5:20 min (64 transients), median (interquartile range) drift was 0.44 (1.29) Hz before fMRI and 0.83 (1.29) Hz after. This increased to 3.15 (4.02) Hz for the full 30 min (360 transients) run. Average drift rates were 0.29 Hz/min before fMRI and 0.43 Hz/min after. Paired t-tests indicated that drift increased after fMRI, as expected (p &lt; 0.05). Simulated spectra convolved with the frequency drift showed that the intensity of the NAA singlet was reduced by up to 26%, 44 % and 18% for GE, Philips and Siemens scanners after fMRI, respectively. ICCs indicated good agreement between datasets acquired on separate days. The single site long acquisition showed drift rate was reduced to 0.03 Hz/min approximately three hours after fMRI.Discussion: This study analyzed frequency drift data from 95 3T MRI scanners. Median levels of drift were relatively low (5-min average under 1 Hz), but the most extreme cases suffered from higher levels of drift. The extent of drift varied across scanners which both linear and nonlinear drifts were observed.</p

    Cognitive control and emotional control - theoretical analysis

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    W celu efektywnego funkcjonowania w spo艂ecze艅stwie oraz osi膮gania wyznaczonych cel贸w organizm potrzebuje sprawnych system贸w regulacji reakcji emocjonalnych oraz kontroli poznawczej. Pierwszy z nich definiuje si臋 jako odg贸rny mechanizm moduluj膮cy przetwarzanie bod藕c贸w emocjonalnego lub reakcji behawioralnej organizmu. Drugi odnosi si臋 do zdolno艣ci kierowania procesami poznawczymi i dzia艂aniami organizmu zgodnie z wyznaczonym celem. Wsp贸lnie mechanizmy te umo偶liwiaj膮 dostosowanie zachowa艅 jednostki do aktualnej sytuacji, wykrycie potencjalnych konflikt贸w oraz sterowanie zachowaniem. Pomimo ich wsp贸lnego celu, cz臋sto zostaj膮 rozdzielone na gruncie teoretycznym, w du偶ej mierze z powodu ograniczonych mo偶liwo艣ci metodologicznych bada艅 eksperymentalnych. Niniejsza praca przedstawia kr贸tkie zestawienie najwa偶niejszych informacji na temat teorii, neuronalnych korelat贸w oraz wynik贸w bada艅 empirycznych z zakresu kontroli poznawczej oraz kontroli emocjonalnej. Wbrew zakorzenionej historycznie tendencji do rozdzielania przetwarzania emocjonalnego i kognitywnego na potrzeby bada艅, w pracy podkre艣lony zostaje ich 艣cis艂y zwi膮zek. Sugeruje si臋, 偶e poj臋cia te w znacznej mierze si臋 pokrywaj膮 i dziel膮 wsp贸lne mechanizmy. Nie oznacza to, 偶e procesy emocjonalne s膮 to偶same z procesami poznawczymi, ale pr贸ba ich przeciwstawiania uniemo偶liwia kompleksowe podej艣cie i stworzenie sp贸jnego modelu ludzkiego umys艂u.In order to function effectively in society and achieve set goals, the organism needs efficient systems for regulating emotional reactions and cognitive control. The first one is defined as a top-down mechanism that modulates the processing of emotional stimuli and the behavioral response of the body. The second refers to the ability to manage the cognitive processes and to adjust the individual鈥檚 activities according to the objective set. Together, these mechanisms allow the organism to tailor its behaviors to the current situation, control them and detect potential conflicts. Despite their common purpose, they are often separated on a theoretical basis, largely due to the limited capacity of methodological experimental research. This work presents a brief overview of the most important information concerning theories, neuronal correlates, and empirical findings regarding cognitive control and emotional control. Contrary to the historically rooted tendency to separate emotional and cognitive processing for the purposes of research, their close connection is emphasized in this thesis. It is argued that these concepts largely overlap and share common mechanisms. This does not mean that emotional processes are identical to cognitive processes, but an attempt to set one against the other prevents a comprehensive approach and the creation of a coherent model of the human mind

    Frequency drift in MR spectroscopy at 3T

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    Purpose: Heating of gradient coils and passive shim components is a common cause of instability in the B-0 field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites. Method: A standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC). Results: Of the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the first 5:20 min (64 transients), median (interquartile range) drift was 0.44 (1.29) Hz before fMRI and 0.83 (1.29) Hz after. This increased to 3.15 (4.02) Hz for the full 30 min (360 transients) run. Average drift rates were 0.29 Hz/min before fMRI and 0.43 Hz/min after. Paired t-tests indicated that drift increased after fMRI, as expected (p < 0.05). Simulated spectra convolved with the frequency drift showed that the intensity of the NAA singlet was reduced by up to 26%, 44 % and 18% for GE, Philips and Siemens scanners after fMRI, respectively. ICCs indicated good agreement between datasets acquired on separate days. The single site long acquisition showed drift rate was reduced to 0.03 Hz/min approximately three hours after fMRI. Discussion: This study analyzed frequency drift data from 95 3T MRI scanners. Median levels of drift were relatively low (5-min average under 1 Hz), but the most extreme cases suffered from higher levels of drift. The extent of drift varied across scanners which both linear and nonlinear drifts were observed

    Frequency drift in MR spectroscopy at 3T

    No full text
    Purpose: Heating of gradient coils and passive shim components is a common cause of instability in the B 0 field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites. Method: A standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC). Results: Of the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the first 5:20 min (64 transients), median (interquartile range) drift was 0.44 (1.29) Hz before fMRI and 0.83 (1.29) Hz after. This increased to 3.15 (4.02) Hz for the full 30 min (360 transients) run. Average drift rates were 0.29 Hz/min before fMRI and 0.43 Hz/min after. Paired t-tests indicated that drift increased after fMRI, as expected (p < 0.05). Simulated spectra convolved with the frequency drift showed that the intensity of the NAA singlet was reduced by up to 26%, 44 % and 18% for GE, Philips and Siemens scanners after fMRI, respectively. ICCs indicated good agreement between datasets acquired on separate days. The single site long acquisition showed drift rate was reduced to 0.03 Hz/min approximately three hours after fMRI. Discussion: This study analyzed frequency drift data from 95 3T MRI scanners. Median levels of drift were relatively low (5-min average under 1 Hz), but the most extreme cases suffered from higher levels of drift. The extent of drift varied across scanners which both linear and nonlinear drifts were observed
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