Optimal repetition time reduction for single subject event‐related functional magnetic resonance imaging

McDowell, Amy R; Carmichael, David W.

doi:10.1002/mrm.27498

Cited by 19 publications

(14 citation statements)

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“…Implications of such discrepancies between the serial structure of short-TR data and parametric models implemented in common toolkits have been cautioned by several studies (Bollmann et al, 2018;Eklund et al, 2012;McDowell and Carmichael, 2018;Olszowy et al, 2018;Sahib et al, 2016), and the proposed solutions include invoking nonparametric alternatives (e.g., (Woolrich et al, 2001)) or a slightly more complicated parametric model (essentially with more free parameters for model fittings), such as higher-order AR models (Bollmann et al, 2018;Jacobs et al, 2014;Sahib et al, 2016;Worsley et al, 2002), and the new FAST option of SPM (https://www.fil.ion.ucl.ac.uk/spm/), which fits the serial correlation structure with more versatile dictionary components based on exponential covariance functions (Corbin et al, 2018;Todd et al, 2016). These more complicated models flexibly adapt to data collected at different TRs and have been demonstrated to be effective.…”

Section: Modeling Signal and Noise Autocorrelations At Sub-second Trsmentioning

confidence: 99%

On the analysis of rapidly sampled fMRI data

et al. 2019

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Recent advances in parallel imaging and simultaneous multi-slice techniques have permitted whole-brain fMRI acquisitions at sub-second sampling intervals, without significantly sacrificing the spatial coverage and resolution. Apart from probing brain function at finer temporal scales, faster sampling rates may potentially lead to enhanced functional sensitivity, owing possibly to both cleaner neural representations (due to less aliased physiological noise) and additional statistical benefits (due to more degrees of freedom for a fixed scan duration). Accompanying these intriguing aspects of fast acquisitions, however, confusion has also arisen regarding (1) how to preprocess/analyze these fast fMRI data, and (2) what exactly is the extent of benefits with fast acquisitions, i.e., how fast is fast enough for a specific research aim? The first question is

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Section: Modeling Signal and Noise Autocorrelations At Sub-second Trsmentioning

confidence: 99%

On the analysis of rapidly sampled fMRI data

et al. 2019

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“…We could only hypothesise that acquiring 800 timepoints and using multislice short TR acquisition improved our sensitivity and specificity similarly to the event-related fMRI studies available in the literature (60).…”

Section: Strengths Of the Studymentioning

confidence: 83%

Resting-State Functional Connectivity of the Ageing Female Brain—Differences Between Young and Elderly Female Adults on Multislice Short TR rs-fMRI

et al. 2021

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Introduction: Age-related brain changes are one of the most important world health problems due to the rising lifespan and size of the elderly populations. The aim of the study was to assess the effect of ageing in women on coordinated brain activity between eight resting-state networks.Material and Methods: The study group comprised 60 healthy female volunteers who were divided into two age groups: younger women (aged 20–30 n = 30) and older women (aged 55–80 n = 30). Resting-state data were collected during a 15 min scan in the eyes-closed condition using a 3T MR scanner. Data were preprocessed and analysed using the CONN toolbox version 19.c. The large-scale network analysis included a priori selected regions of interest of the default mode, the sensorimotor, the visual, the salience, the dorsal attention, the fronto-parietal, the language, and the cerebellar network.Results: Within the visual, the default mode, the salience, and the sensorimotor network, the intra-network resting-state functional connectivity (RSFC) was significantly higher with increasing age. There was also a significant increase in the inter-network RSFC in older females compared to young females found in the following networks: sensorimotor lateral and salience, salience and language, salience and fronto-parietal, cerebellar anterior and default mode, cerebellar posterior and default mode, visual and sensorimotor lateral, visual and sensorimotor, visual lateral and default mode, language and cerebellar anterior, language and cerebellar posterior, fronto-parietal and cerebellar anterior, dorsal attention and sensorimotor, dorsal attention and default mode, sensorimotor superior, and salience. Compared to young females, elderly women presented bilaterally significantly lower inter-network RSFC of the salience supramarginal gyrus and cerebellar posterior, sensorimotor lateral, and cerebellar anterior network, and sensorimotor lateral and cerebellar posterior as well as sensorimotor superior and cerebellar posterior network.Conclusion: Increased RSFC between some brain networks including the visual, the default mode, the salience, the sensorimotor, the language, the fronto-parietal, the dorsal attention, and the cerebellar networks in elderly females may function as a compensation mechanism during the ageing process of the brain. To the best of our knowledge, this study is the first to report the importance of increase of cerebellar networks RSFC during healthy female ageing.

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“…The steady-state MR signal was reduced at shorter TRs. At the short TR acquisition, image signal was exponentially reduced due to decreased T1 recovery within the TR [ 10 , 22 ]. Therefore, a shorter TR might have a punitive effect on image signal levels.…”

Section: Discussionmentioning

confidence: 99%

“…The short TR within the range of 300 ms to 600 ms was recommended for more captured information per unit time and more accurate representation of the BOLD response [ 24 ]. On the other hand, moderate reduction of TR (1000 ± 200 ms) was also chosen for greater sensitivity and specificity in signal subject event-related fMRI [ 22 ]. The difference of optimal TR was thought to be caused by the differences in the experimental design, SMS acquisition parameters, and fMRI data analysis measures.…”

Section: Discussionmentioning

confidence: 99%

Improved Activation and Hemodynamic Response Function of Olfactory fMRI Using Simultaneous Multislice with Reduced TR Acquisition

Chen

Yin

et al. 2021

BioMed Research International

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Objectives. The respiration could decrease the time synchronization between odor stimulation and data acquisition, consequently deteriorating the functional activation and hemodynamic response function (HRF) in olfactory functional magnetic resonance imaging (fMRI) with a conventional repetition time (TR). In this study, we aimed to investigate whether simultaneous multislice (SMS) technology with reduced TR could improve the blood oxygen level-dependent (BOLD) activation and optimize HRF modeling in olfactory fMRI. Methods. Sixteen young healthy subjects with normal olfaction underwent olfactory fMRI on a 3T MRI scanner using a 64 channel head coil. FMRI data were acquired using SMS acceleration at three different TRs: 3000 ms, 1000 ms, and 500 ms. Both metrics of BOLD activation (activated voxels, mean, and maximum t -scores) and the HRF modeling (response height and time to peak) were calculated in the bilateral amygdalae, hippocampi, and insulae. Results. The 500 ms and 1000 ms TRs both significantly improved the number of activated voxels, mean, and maximum t -score in the amygdalae and insulae, compared with a 3000 ms TR (all P < 0.05 ). But the increase of these metrics in the hippocampi did not reach a statistical significance (all P > 0.05 ). No significant difference in any BOLD activation metrics between TR 500 ms and 1000 ms was observed in all regions of interest (ROIs) (all P > 0.05 ). The HRF curves showed that higher response height and shorter time to peak in all ROIs were obtained at 500 ms and 1000 ms TRs compared to 3000 ms TR. TR 500 ms had a more significant effect on response height than TR 1000 ms in the amygdalae ( P = 0.017 ), and there was no significant difference in time to peak between TR 500 ms and 1000 ms in all ROIs (all P > 0.05 ). Conclusions. The fast image acquisition technique of SMS with reduced TR could significantly improve the functional activation and HRF curve in olfactory fMRI.

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Optimal repetition time reduction for single subject event‐related functional magnetic resonance imaging

Abstract: Modest TR reductions (to 1000 ± 200 ms) optimally improved event-related fMRI performance independent of design frequency. Autoregressive models with a local as opposed to global fit performed better, while low order autoregressive models were sufficient at the optimal TR.

Cited by 19 publications

References 14 publications

On the analysis of rapidly sampled fMRI data

On the analysis of rapidly sampled fMRI data

Resting-State Functional Connectivity of the Ageing Female Brain—Differences Between Young and Elderly Female Adults on Multislice Short TR rs-fMRI

Improved Activation and Hemodynamic Response Function of Olfactory fMRI Using Simultaneous Multislice with Reduced TR Acquisition

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