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Zhang Y, Ye Z, Xia C, Tan Y, Zhang M, Lv X, Tang J, Li Z. Clinical Applications and Recent Updates of Simultaneous Multi-slice Technique in Accelerated MRI. Acad Radiol 2024; 31:1976-1988. [PMID: 38220568 DOI: 10.1016/j.acra.2023.12.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Revised: 12/15/2023] [Accepted: 12/19/2023] [Indexed: 01/16/2024]
Abstract
Simultaneous multi-slice (SMS) is a magnetic resonance imaging (MRI) acceleration technique that utilizes multi-band radio-frequency pulses to simultaneously excite and encode multiple slices. Currently, SMS has been widely studied and applied in the MRI examination to reduce acquisition time, which can significantly improve the examination efficiency and patient throughput. Moreover, SMS technique can improve spatial resolution, which is of great value in disease diagnosis, treatment response monitoring, and prognosis prediction. This review will briefly introduce the technical principles of SMS, and summarize its current clinical applications. More importantly, we will discuss the recent technical progress and future research direction of SMS, hoping to highlight the clinical value and scientific potential of this technique.
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Affiliation(s)
- Yiteng Zhang
- Department of Radiology, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, Sichuan, China
| | - Zheng Ye
- Department of Radiology, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, Sichuan, China
| | - Chunchao Xia
- Department of Radiology, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, Sichuan, China
| | - Yuqi Tan
- Department of Radiology, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, Sichuan, China
| | - Meng Zhang
- Department of Radiology, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, Sichuan, China
| | - Xinyang Lv
- Department of Radiology, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, Sichuan, China
| | - Jing Tang
- Department of Radiology, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, Sichuan, China
| | - Zhenlin Li
- Department of Radiology, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Chengdu, 610041, Sichuan, China.
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2
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Kenett YN, Chrysikou EG, Bassett DS, Thompson-Schill SL. Neural Dynamics During the Generation and Evaluation of Creative and Non-Creative Ideas. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.15.589621. [PMID: 38659810 PMCID: PMC11042297 DOI: 10.1101/2024.04.15.589621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
What are the neural dynamics that drive creative thinking? Recent studies have provided much insight into the neural mechanisms of creative thought. Specifically, the interaction between the executive control, default mode, and salience brain networks has been shown to be an important marker of individual differences in creative ability. However, how these different brain systems might be recruited dynamically during the two key components of the creative process-generation and evaluation of ideas-remains far from understood. In the current study we applied state-of-the-art network neuroscience methodologies to examine the neural dynamics related to the generation and evaluation of creative and non-creative ideas using a novel within-subjects design. Participants completed two functional magnetic resonance imaging sessions, taking place a week apart. In the first imaging session, participants generated either creative (alternative uses) or non-creative (common characteristics) responses to common objects. In the second imaging session, participants evaluated their own creative and non-creative responses to the same objects. Network neuroscience methods were applied to examine and directly compare reconfiguration, integration, and recruitment of brain networks during these four conditions. We found that generating creative ideas led to significantly higher network reconfiguration than generating non-creative ideas, whereas evaluating creative and non-creative ideas led to similar levels of network integration. Furthermore, we found that these differences were attributable to different dynamic patterns of neural activity across the executive control, default mode, and salience networks. This study is the first to show within-subject differences in neural dynamics related to generating and evaluating creative and non-creative ideas.
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Affiliation(s)
- Yoed N Kenett
- Faculty of Data and Decision Sciences, Technion, Israel Institute of Technology, Haifa, Israel, 3200003
| | - Evangelia G Chrysikou
- Department of Psychological and Brain Sciences, Drexel University, Philadelphia, PA 19104, USA
| | - Dani S Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, PA 19104, USA
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3
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Whitehead JC, Spiousas I, Armony JL. Individual differences in the evaluation of ambiguous visual and auditory threat-related expressions. Eur J Neurosci 2024; 59:370-393. [PMID: 38185821 DOI: 10.1111/ejn.16220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 10/29/2023] [Accepted: 11/22/2023] [Indexed: 01/09/2024]
Abstract
This study investigated the neural correlates of the judgement of auditory and visual ambiguous threat-related information, and the influence of state anxiety on this process. Healthy subjects were scanned using a fast, high-resolution functional magnetic resonance imaging (fMRI) multiband sequence while they performed a two-alternative forced-choice emotion judgement task on faces and vocal utterances conveying explicit anger or fear, as well as ambiguous ones. Critically, the latter was specific to each subject, obtained through a morphing procedure and selected prior to scanning following a perceptual decision-making task. Behavioural results confirmed a greater task-difficulty for subject-specific ambiguous stimuli and also revealed a judgement bias for visual fear, and, to a lesser extent, for auditory anger. Imaging results showed increased activity in regions of the salience and frontoparietal control networks (FPCNs) and deactivation in areas of the default mode network for ambiguous, relative to explicit, expressions. In contrast, the right amygdala (AMG) responded more strongly to explicit stimuli. Interestingly, its response to the same ambiguous stimulus depended on the subjective judgement of the expression. Finally, we found that behavioural and neural differences between ambiguous and explicit expressions decreased as a function of state anxiety scores. Taken together, our results show that behavioural and brain responses to emotional expressions are determined not only by emotional clarity but also modality and the subjects' subjective perception of the emotion expressed, and that some of these responses are modulated by state anxiety levels.
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Affiliation(s)
- Jocelyne C Whitehead
- Human Neuroscience, Douglas Mental Health University Institute, Verdun, Quebec, Canada
- BRAMS Laboratory, Centre for Research on Brain, Language and Music, Montreal, Quebec, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada
| | - Ignacio Spiousas
- BRAMS Laboratory, Centre for Research on Brain, Language and Music, Montreal, Quebec, Canada
- Laboratorio Interdisciplinario del Tiempo y la Experiencia (LITERA), CONICET, Universidad de San Andrés, Victoria, Argentina
| | - Jorge L Armony
- Human Neuroscience, Douglas Mental Health University Institute, Verdun, Quebec, Canada
- BRAMS Laboratory, Centre for Research on Brain, Language and Music, Montreal, Quebec, Canada
- Laboratorio Interdisciplinario del Tiempo y la Experiencia (LITERA), CONICET, Universidad de San Andrés, Victoria, Argentina
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada
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Okuno T, Hata J, Haga Y, Muta K, Tsukada H, Nakae K, Okano H, Woodward A. Group Surrogate Data Generating Models and similarity quantification of multivariate time-series: A resting-state fMRI study. Neuroimage 2023; 279:120329. [PMID: 37591477 DOI: 10.1016/j.neuroimage.2023.120329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 07/31/2023] [Accepted: 08/14/2023] [Indexed: 08/19/2023] Open
Abstract
Advancements in non-invasive brain analysis through novel approaches such as big data analytics and in silico simulation are essential for explaining brain function and associated pathologies. In this study, we extend the vector auto-regressive surrogate technique from a single multivariate time-series to group data using a novel Group Surrogate Data Generating Model (GSDGM). This methodology allowed us to generate biologically plausible human brain dynamics representative of a large human resting-state (rs-fMRI) dataset obtained from the Human Connectome Project. Simultaneously, we defined a novel similarity measure, termed the Multivariate Time-series Ensemble Similarity Score (MTESS). MTESS showed high accuracy and f-measure in subject identification, and it can directly compare the similarity between two multivariate time-series. We used MTESS to analyze both human and marmoset rs-fMRI data. Our results showed similarity differences between cortical and subcortical regions. We also conducted MTESS and state transition analysis between single and group surrogate techniques, and confirmed that a group surrogate approach can generate plausible group centroid multivariate time-series. Finally, we used GSDGM and MTESS for the fingerprint analysis of human rs-fMRI data, successfully distinguishing normal and outlier sessions. These new techniques will be useful for clinical applications and in silico simulation.
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Affiliation(s)
- Takuto Okuno
- Connectome Analysis Unit, RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan.
| | - Junichi Hata
- Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan; Graduate School of Human Health Sciences, Tokyo Metropolitan University, 7-2-10 Higashiogu, Arakawa-ku, Tokyo 116-8551, Japan
| | - Yawara Haga
- Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
| | - Kanako Muta
- Graduate School of Human Health Sciences, Tokyo Metropolitan University, 7-2-10 Higashiogu, Arakawa-ku, Tokyo 116-8551, Japan
| | - Hiromichi Tsukada
- Center for Mathematical Science and Artificial Intelligence, Chubu University, 1200 Matsumoto-cho, Kasugai, Aichi 487-8501, Japan
| | - Ken Nakae
- Exploratory Research Center on Life and Living Systems, National Institutes of Natural Sciences, Aichi, Japan
| | - Hideyuki Okano
- Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
| | - Alexander Woodward
- Connectome Analysis Unit, RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
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Eisenmenger LB, Peret A, Roberts GS, Spahic A, Tang C, Kuner AD, Grayev AM, Field AS, Rowley HA, Kennedy TA. Focused Abbreviated Survey MRI Protocols for Brain and Spine Imaging. Radiographics 2023; 43:e220147. [PMID: 37167089 PMCID: PMC10262597 DOI: 10.1148/rg.220147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 10/12/2022] [Accepted: 10/18/2022] [Indexed: 05/13/2023]
Abstract
There has been extensive growth in both the technical development and the clinical applications of MRI, establishing this modality as one of the most powerful diagnostic imaging tools. However, long examination and image interpretation times still limit the application of MRI, especially in emergent clinical settings. Rapid and abbreviated MRI protocols have been developed as alternatives to standard MRI, with reduced imaging times, and in some cases limited numbers of sequences, to more efficiently answer specific clinical questions. A group of rapid MRI protocols used at the authors' institution, referred to as FAST (focused abbreviated survey techniques), are designed to include or exclude emergent or urgent conditions or screen for specific entities. These FAST protocols provide adequate diagnostic image quality with use of accelerated approaches to produce imaging studies faster than traditional methods. FAST protocols have become critical diagnostic screening tools at the authors' institution, allowing confident and efficient confirmation or exclusion of actionable findings. The techniques commonly used to reduce imaging times, the imaging protocols used at the authors' institution, and future directions in FAST imaging are reviewed to provide a practical and comprehensive overview of FAST MRI for practicing neuroradiologists. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.
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Affiliation(s)
| | | | - Grant S. Roberts
- From the Departments of Radiology (L.B.E., A.P., A.D.K., A.M.G.,
A.S.F., H.A.R., T.A.K.) and Medical Physics (G.S.R., A.S., C.T.), University of
Wisconsin School of Medicine and Public Health, 600 Highland Ave, Madison, WI
53792-3252
| | - Alma Spahic
- From the Departments of Radiology (L.B.E., A.P., A.D.K., A.M.G.,
A.S.F., H.A.R., T.A.K.) and Medical Physics (G.S.R., A.S., C.T.), University of
Wisconsin School of Medicine and Public Health, 600 Highland Ave, Madison, WI
53792-3252
| | - Chenwei Tang
- From the Departments of Radiology (L.B.E., A.P., A.D.K., A.M.G.,
A.S.F., H.A.R., T.A.K.) and Medical Physics (G.S.R., A.S., C.T.), University of
Wisconsin School of Medicine and Public Health, 600 Highland Ave, Madison, WI
53792-3252
| | - Anthony D. Kuner
- From the Departments of Radiology (L.B.E., A.P., A.D.K., A.M.G.,
A.S.F., H.A.R., T.A.K.) and Medical Physics (G.S.R., A.S., C.T.), University of
Wisconsin School of Medicine and Public Health, 600 Highland Ave, Madison, WI
53792-3252
| | - Allison M. Grayev
- From the Departments of Radiology (L.B.E., A.P., A.D.K., A.M.G.,
A.S.F., H.A.R., T.A.K.) and Medical Physics (G.S.R., A.S., C.T.), University of
Wisconsin School of Medicine and Public Health, 600 Highland Ave, Madison, WI
53792-3252
| | - Aaron S. Field
- From the Departments of Radiology (L.B.E., A.P., A.D.K., A.M.G.,
A.S.F., H.A.R., T.A.K.) and Medical Physics (G.S.R., A.S., C.T.), University of
Wisconsin School of Medicine and Public Health, 600 Highland Ave, Madison, WI
53792-3252
| | - Howard A. Rowley
- From the Departments of Radiology (L.B.E., A.P., A.D.K., A.M.G.,
A.S.F., H.A.R., T.A.K.) and Medical Physics (G.S.R., A.S., C.T.), University of
Wisconsin School of Medicine and Public Health, 600 Highland Ave, Madison, WI
53792-3252
| | - Tabassum A. Kennedy
- From the Departments of Radiology (L.B.E., A.P., A.D.K., A.M.G.,
A.S.F., H.A.R., T.A.K.) and Medical Physics (G.S.R., A.S., C.T.), University of
Wisconsin School of Medicine and Public Health, 600 Highland Ave, Madison, WI
53792-3252
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6
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Phạm DĐ, McDonald DJ, Ding L, Nebel MB, Mejia AF. Less is more: balancing noise reduction and data retention in fMRI with data-driven scrubbing. Neuroimage 2023; 270:119972. [PMID: 36842522 PMCID: PMC10773988 DOI: 10.1016/j.neuroimage.2023.119972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 02/15/2023] [Accepted: 02/21/2023] [Indexed: 02/28/2023] Open
Abstract
Functional MRI (fMRI) data may be contaminated by artifacts arising from a myriad of sources, including subject head motion, respiration, heartbeat, scanner drift, and thermal noise. These artifacts cause deviations from common distributional assumptions, introduce spatial and temporal outliers, and reduce the signal-to-noise ratio of the data-all of which can have negative consequences for the accuracy and power of downstream statistical analysis. Scrubbing is a technique for excluding fMRI volumes thought to be contaminated by artifacts and generally comes in two flavors. Motion scrubbing based on subject head motion-derived measures is popular but suffers from a number of drawbacks, among them the need to choose a threshold, a lack of generalizability to multiband acquisitions, and high rates of censoring of individual volumes and entire subjects. Alternatively, data-driven scrubbing methods like DVARS are based on observed noise in the processed fMRI timeseries and may avoid some of these issues. Here we propose "projection scrubbing", a novel data-driven scrubbing method based on a statistical outlier detection framework and strategic dimension reduction, including independent component analysis (ICA), to isolate artifactual variation. We undertake a comprehensive comparison of motion scrubbing with data-driven projection scrubbing and DVARS. We argue that an appropriate metric for the success of scrubbing is maximal data retention subject to reasonable performance on typical benchmarks such as the validity, reliability, and identifiability of functional connectivity. We find that stringent motion scrubbing yields worsened validity, worsened reliability, and produced small improvements to fingerprinting. Meanwhile, data-driven scrubbing methods tend to yield greater improvements to fingerprinting while not generally worsening validity or reliability. Importantly, however, data-driven scrubbing excludes a fraction of the number of volumes or entire sessions compared to motion scrubbing. The ability of data-driven fMRI scrubbing to improve data retention without negatively impacting the quality of downstream analysis has major implications for sample sizes in population neuroscience research.
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Affiliation(s)
- Damon Đ Phạm
- Department of Statistics, Indiana University, Bloomington, IN, USA.
| | - Daniel J McDonald
- Department of Statistics, University of British Columbia, Vancouver, BC, Canada
| | - Lei Ding
- Department of Statistics, Indiana University, Bloomington, IN, USA
| | - Mary Beth Nebel
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, USA; Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
| | - Amanda F Mejia
- Department of Statistics, Indiana University, Bloomington, IN, USA
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Tabassi Mofrad F, Schiller NO. Connectivity Profile of Middle Inferior Parietal Cortex Confirms the Hypothesis About Modulating Cortical Areas. Neuroscience 2023; 519:1-9. [PMID: 36931424 DOI: 10.1016/j.neuroscience.2023.03.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 03/03/2023] [Accepted: 03/08/2023] [Indexed: 03/17/2023]
Abstract
According to the correlated transmitter-receptor based structure of the inferior parietal cortex (IPC), this brain area is divided into three clusters, namely, the caudal, the middle and the rostral. Nevertheless, in associating different cognitive functions to the IPC, previous studies considered this part of the cortex as a whole and thus inconsistent results have been reported. Using multiband EPI, we investigated the connectivity profile of the middle IPC while forty-five participants performed a task requiring cognitive control. The middle IPC demonstrated functional associations which do not have similarities to a contributing part in the frontoparietal network, in processing cognitive control. At the same time, this cortical area showed negative functional connectivity with both the precuneus cortex, which is resting- state related, and brain areas related to general cognitive functions. That is, the functions of the middle IPC are not accommodated by the traditional categorization of different brain areas i.e. resting state-related or task-related networks and this advanced our hypothesis about modulating cortical areas. Such brain areas are characterized by their negative functional connectivity with parts of the cortex involved in task performance, proportional to the difficulty of the task; yet, their functional associations are inconsistent with the resting state-related cortical areas.
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Affiliation(s)
- Fatemeh Tabassi Mofrad
- Leiden University Centre for Linguistics, Leiden, the Netherlands; Leiden Institute for Brain and Cognition, Leiden, the Netherlands; Institute of Cognitive Neuroscience, University College London, London, UK.
| | - Niels O Schiller
- Leiden University Centre for Linguistics, Leiden, the Netherlands; Leiden Institute for Brain and Cognition, Leiden, the Netherlands
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Liu P, Fall S, Ahiatsi M, Balédent O. Real-time phase contrast MRI versus conventional phase contrast MRI at different spatial resolutions and velocity encodings. Clin Imaging 2023; 94:93-102. [PMID: 36502617 DOI: 10.1016/j.clinimag.2022.11.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 11/09/2022] [Accepted: 11/28/2022] [Indexed: 12/04/2022]
Abstract
PURPOSES To compare the accuracy of real-time phase-contrast echo-planar MRI (EPI-PC) and conventional cine phase-contrast MRI (Conv-PC) and to assess the influence of spatial resolutions (pixel size) and velocity encoding on flow measurements obtained with the two sequences. METHODS Flow quantification was assessed using a pulsatile flow phantom (diameter: 9.5 mm; mean flow rate: 1150 mm3/s; mean flow velocity: 1.6 cm/s). Firstly, the accuracy of the EPI-PC was checked by comparing it with the flow rate in the calibrated phantom and the pulsation index from Conv-PC. Secondly, flow data from the two sequences were compared quantitatively as a function of the pixel size and the velocity encoding. RESULTS The mean percentage difference between the EPI-PC flow rate and calibrated phantom flow rate was -2.9 ± 2.1% (Mean ± SD). The pulsatility indices for EPI-PC and Conv-PC were respectively 0.64 and 0.59. In order to keep the flow rate measurement error within 10%, the ROI in Conv-PC had to contain at least 13 pixels, while the ROI in EPI-PC had to contain at least 9 pixels. Furthermore, Conv-PC had a higher velocity-to-noise ratio and could use a higher velocity encoding than EPI-PC (20 cm/s and 15 cm/s, respectively). CONCLUSIONS The result of this in vitro study confirmed the accuracy of EPI-PC, and found that EPI-PC can adapt to lower spatial resolutions, but is more sensitive to velocity encoding than Conv-PC.
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Affiliation(s)
- Pan Liu
- CHIMERE UR 7516, Jules Verne University of Picardy, Amiens, France; Medical Image Processing Department, Amiens Picardy University Hospital, Amiens, France.
| | - Sidy Fall
- MRI Department, Jules Verne University of Picardy, Amiens, France
| | - Maureen Ahiatsi
- CHIMERE UR 7516, Jules Verne University of Picardy, Amiens, France
| | - Olivier Balédent
- CHIMERE UR 7516, Jules Verne University of Picardy, Amiens, France; Medical Image Processing Department, Amiens Picardy University Hospital, Amiens, France; MRI Department, Jules Verne University of Picardy, Amiens, France.
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Cahart M, O'Daly O, Giampietro V, Timmers M, Streffer J, Einstein S, Zelaya F, Dell'Acqua F, Williams SCR. Comparing the test-retest reliability of resting-state functional magnetic resonance imaging metrics across single band and multiband acquisitions in the context of healthy aging. Hum Brain Mapp 2022; 44:1901-1912. [PMID: 36546653 PMCID: PMC9980889 DOI: 10.1002/hbm.26180] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 11/17/2022] [Accepted: 11/29/2022] [Indexed: 12/24/2022] Open
Abstract
The identification of meaningful functional magnetic resonance imaging (fMRI) biomarkers requires measures that reliably capture brain performance across different subjects and over multiple scanning sessions. Recent developments in fMRI acquisition, such as the introduction of multiband (MB) protocols and in-plane acceleration, allow for increased scanning speed and improved temporal resolution. However, they may also lead to reduced temporal signal to noise ratio and increased signal leakage between simultaneously excited slices. These methods have been adopted in several scanning modalities including diffusion weighted imaging and fMRI. To our knowledge, no study has formally compared the reliability of the same resting-state fMRI (rs-fMRI) metrics (amplitude of low-frequency fluctuations; seed-to-voxel and region of interest [ROI]-to-ROI connectivity) across conventional single-band fMRI and different MB acquisitions, with and without in-plane acceleration, across three sessions. In this study, 24 healthy older adults were scanned over three visits, on weeks 0, 1, and 4, and, on each occasion, underwent a conventional single band rs-fMRI scan and three different rs-fMRI scans with MB factors 4 and 6, with and without in-plane acceleration. Across all three rs-fMRI metrics, the reliability scores were highest with MB factor 4 with no in-plane acceleration for cortical areas and with conventional single band for subcortical areas. Recommendations for future research studies are discussed.
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Affiliation(s)
- Marie‐Stephanie Cahart
- Neuroimaging DepartmentInstitute of Psychiatry, Psychology and Neuroscience, Kings College LondonLondonUK
| | - Owen O'Daly
- Neuroimaging DepartmentInstitute of Psychiatry, Psychology and Neuroscience, Kings College LondonLondonUK
| | - Vincent Giampietro
- Neuroimaging DepartmentInstitute of Psychiatry, Psychology and Neuroscience, Kings College LondonLondonUK
| | - Maarten Timmers
- Division of Janssen Pharmaceutica NVJanssen Research and DevelopmentBeerseBelgium
| | - Johannes Streffer
- AC Immune SALausanneSwitzerland
- Reference Center for Biological Markers of Dementia (BIODEM)University of AntwerpAntwerpBelgium
| | | | - Fernando Zelaya
- Neuroimaging DepartmentInstitute of Psychiatry, Psychology and Neuroscience, Kings College LondonLondonUK
| | - Flavio Dell'Acqua
- Natbrainlab; Forensic and Neurodevelopmental Sciences DepartmentInstitute of Psychiatry, Psychology and Neuroscience, Kings College LondonLondonUK
| | - Steven C. R. Williams
- Neuroimaging DepartmentInstitute of Psychiatry, Psychology and Neuroscience, Kings College LondonLondonUK
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Cahart MS, Dell’Acqua F, Giampietro V, Cabral J, Timmers M, Streffer J, Einstein S, Zelaya F, Williams SCR, O’Daly O. Test-retest reliability of time-varying patterns of brain activity across single band and multiband resting-state functional magnetic resonance imaging in healthy older adults. Front Hum Neurosci 2022; 16:980280. [PMID: 36438643 PMCID: PMC9685802 DOI: 10.3389/fnhum.2022.980280] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Accepted: 10/25/2022] [Indexed: 12/23/2023] Open
Abstract
Leading Eigenvector Dynamics Analysis (LEiDA) is an analytic approach that characterizes brain activity recorded with functional Magnetic Resonance Imaging (fMRI) as a succession of discrete phase-locking patterns, or states, that consistently recur over time across all participants. LEiDA allows for the extraction of three state-related measures which have previously been key to gaining a better understanding of brain dynamics in both healthy and clinical populations: the probability of occurrence of a given state, its lifetime and the probability of switching from one state to another. The degree to which test-retest reliability of the LEiDA measures may be affected by increasing MRI multiband (MB) factors in comparison with single band sequences is yet to be established. In this study, 24 healthy older adults were scanned over three sessions, on weeks 0, 1, and 4. On each visit, they underwent a conventional single band resting-state fMRI (rs-fMRI) scan and three different MB rs-fMRI scans, with MB factors of 4, with and without in-plane acceleration, and 6 without in-plane acceleration. We found test-retest reliability scores to be significantly higher with MB factor 4 with and without in-plane acceleration for most cortical networks. These findings will inform the choice of acquisition parameters for future studies and clinical trials.
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Affiliation(s)
- Marie-Stephanie Cahart
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Flavio Dell’Acqua
- NatBrainLab, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Vincent Giampietro
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Joana Cabral
- Life and Health Sciences Research Institute, University of Minho, Braga, Portugal
| | - Maarten Timmers
- Janssen Research and Development, A Division of Janssen Pharmaceutica NV, Beerse, Belgium
| | - Johannes Streffer
- AC Immune SA, Lausanne, Switzerland
- Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | | | - Fernando Zelaya
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Steven C. R. Williams
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Owen O’Daly
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
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Fazal Z, Gomez DEP, Llera A, Marques JPRF, Beck T, Poser BA, Norris DG. A comparison of multiband and multiband multiecho gradient-echo EPI for task fMRI at 3 T. Hum Brain Mapp 2022; 44:82-93. [PMID: 36196782 PMCID: PMC9783458 DOI: 10.1002/hbm.26081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 08/05/2022] [Accepted: 08/16/2022] [Indexed: 02/05/2023] Open
Abstract
A multiband (MB) echo-planar imaging (EPI) sequence is compared to a multiband multiecho (MBME) EPI protocol to investigate differences in sensitivity for task functional magnetic resonance imaging (fMRI) at 3 T. Multiecho sampling improves sensitivity in areas where single-echo-EPI suffers from dropouts. However, It requires in-plane acceleration to reduce the echo train length, limiting the slice acceleration factor and the temporal and spatial resolution Data were acquired for both protocols in two sessions 24 h apart using an adapted color-word interference Stroop task. Besides protocol comparison statistically, we performed test-retest reliability across sessions for different protocols and denoising methods. We evaluated the sensitivity of two different echo-combination strategies for MBME-EPI. We examined the performance of three different data denoising approaches: "Standard," "AROMA," and "FIX" for MB and MBME, and assessed whether a specific method is preferable. We consider using an appropriate autoregressive model order within the general linear model framework to correct TR differences between the protocols. The comparison between protocols and denoising methods showed at group level significantly higher mean z-scores and the number of active voxels for MBME in the motor, subcortical and medial frontal cortices. When comparing different echo combinations, our results suggest that a contrast-to-noise ratio weighted echo combination improves sensitivity in MBME compared to simple echo-summation. This study indicates that MBME can be a preferred protocol in task fMRI at spatial resolution (≥2 mm), primarily in medial prefrontal and subcortical areas.
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Affiliation(s)
- Zahra Fazal
- Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Cognitive NeuroimagingRadboud University NijmegenNijmegenThe Netherlands
| | - Daniel E. P. Gomez
- Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Cognitive NeuroimagingRadboud University NijmegenNijmegenThe Netherlands
- Athinoula A. Martinos Center for Biomedical ImagingMassachusetts General HospitalBostonMassachusettsUSA
- Present address:
Department of Biomedical EngineeringBoston UniversityBostonMassachusettsUSA
| | - Alberto Llera
- Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Cognitive NeuroimagingRadboud University NijmegenNijmegenThe Netherlands
| | - José P. R. F. Marques
- Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Cognitive NeuroimagingRadboud University NijmegenNijmegenThe Netherlands
| | | | - Benedikt A. Poser
- Faculty of Psychology and NeuroscienceMaastricht UniversityMaastrichtNetherlands
| | - David G. Norris
- Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Cognitive NeuroimagingRadboud University NijmegenNijmegenThe Netherlands
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, UNESCO‐Weltkulturerbe Zollverein, Leitstand Kokerei ZollvereinEssenGermany
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12
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Mapping caudal inferior parietal cortex supports the hypothesis about a modulating cortical area. Neuroimage 2022; 259:119441. [DOI: 10.1016/j.neuroimage.2022.119441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 06/12/2022] [Accepted: 06/30/2022] [Indexed: 11/24/2022] Open
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13
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Chen L, Huang T, Ma D, Chen YC. Altered Default Mode Network Functional Connectivity in Parkinson’s Disease: A Resting-State Functional Magnetic Resonance Imaging Study. Front Neurosci 2022; 16:905121. [PMID: 35720728 PMCID: PMC9204219 DOI: 10.3389/fnins.2022.905121] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Accepted: 05/10/2022] [Indexed: 11/13/2022] Open
Abstract
PurposeWhether the intrinsic functional connectivity pattern of the default mode network (DMN) is involved in the progression of cognitive decline in Parkinson’s disease (PD) remains unclear. This study aimed to investigate the intrinsic functional connectivity (FC) pattern of the DMN anchored on the posterior cingulate cortex (PCC) in patients with PD by resting-state functional magnetic resonance imaging (fMRI).MethodsFifty patients with PD and 50 healthy controls (HCs) were included for resting-state fMRI scanning. A seed-based FC method was used to reveal FC patterns in the DMN with region of interest (ROI) in the PCC. Relationships between FC patterns and disease severity (UPDRS-III) were detected.ResultsCompared with the HCs, the patients with PD showed increased FC between the PCC and the right precuneus, left cuneus, and right angular gyrus. In the PD group, the increased FC values in the right precuneus were significantly and positively correlated with motor severity as assessed with UPDRS-III scores (rho = 0.337, p = 0.02).ConclusionOur result highlights that the patients with PD showed increased FC between the PCC and the right precuneus, left cuneus, and right angular gyrus in the DMN. The altered connectivity pattern in the DMN may play a crucial role in the neurophysiological mechanism of cognitive decline in patients with PD. These findings might provide new insights into neural mechanisms of cognitive decline in PD.
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Affiliation(s)
- Lu Chen
- Department of Radiology, Nanjing Integrated Traditional Chinese and Western Medicine Hospital Affiliated With Nanjing University of Chinese Medicine, Nanjing, China
| | - Ting Huang
- Department of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Di Ma
- College of Information Science and Technology, Nanjing Forestry University, Nanjing, China
| | - Yu-Chen Chen
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
- *Correspondence: Yu-Chen Chen,
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14
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Zhao MY, Woodward A, Fan AP, Chen KT, Yu Y, Chen DY, Moseley ME, Zaharchuk G. Reproducibility of cerebrovascular reactivity measurements: A systematic review of neuroimaging techniques . J Cereb Blood Flow Metab 2022; 42:700-717. [PMID: 34806918 PMCID: PMC9254040 DOI: 10.1177/0271678x211056702] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Cerebrovascular reactivity (CVR), the capacity of the brain to increase cerebral blood flow (CBF) to meet changes in physiological demand, is an important biomarker to evaluate brain health. Typically, this brain "stress test" is performed by using a medical imaging modality to measure the CBF change between two states: at baseline and after vasodilation. However, since there are many imaging modalities and many ways to augment CBF, a wide range of CVR values have been reported. An understanding of CVR reproducibility is critical to determine the most reliable methods to measure CVR as a clinical biomarker. This review focuses on CVR reproducibility studies using neuroimaging techniques in 32 articles comprising 427 total subjects. The literature search was performed in PubMed, Embase, and Scopus. The review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). We identified 5 factors of the experimental subjects (such as sex, blood characteristics, and smoking) and 9 factors of the measuring technique (such as the imaging modality, the type of the vasodilator, and the quantification method) that have strong effects on CVR reproducibility. Based on this review, we recommend several best practices to improve the reproducibility of CVR quantification in neuroimaging studies.
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Affiliation(s)
- Moss Y Zhao
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Amanda Woodward
- Lane Medical Library, Stanford University, Stanford, CA, USA
| | - Audrey P Fan
- Department of Biomedical Engineering, University of California Davis, Davis, CA, USA.,Department of Neurology, University of California Davis, Davis, CA, USA
| | - Kevin T Chen
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Yannan Yu
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - David Y Chen
- Department of Medical Imaging, Taipei Medical University - Shuan-Ho Hospital, New Taipei City.,Department of Radiology, School of Medicine, Taipei Medical University, Taipei *Research materials supporting this publication can be accessed at https://doi.org/10.25740/hd852bg4538
| | | | - Greg Zaharchuk
- Department of Radiology, Stanford University, Stanford, CA, USA
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15
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Kulkarni PH, Merchant S, Awate SP. Mixed-Dictionary Models and Variational Inference in Task fMRI for Shorter Scans and Better Image Quality. Med Image Anal 2022; 78:102392. [DOI: 10.1016/j.media.2022.102392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 10/31/2021] [Accepted: 02/10/2022] [Indexed: 11/28/2022]
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16
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Improved Activation and Hemodynamic Response Function of Olfactory fMRI Using Simultaneous Multislice with Reduced TR Acquisition. BIOMED RESEARCH INTERNATIONAL 2022; 2021:9965756. [PMID: 35005024 PMCID: PMC8731284 DOI: 10.1155/2021/9965756] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Revised: 09/08/2021] [Accepted: 11/30/2021] [Indexed: 11/17/2022]
Abstract
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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17
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Kovářová A, Gajdoš M, Rektor I, Mikl M. Contribution of the multi-echo approach in accelerated functional magnetic resonance imaging multiband acquisition. Hum Brain Mapp 2021; 43:955-973. [PMID: 34716738 PMCID: PMC8764472 DOI: 10.1002/hbm.25698] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 07/16/2021] [Accepted: 10/18/2021] [Indexed: 11/11/2022] Open
Abstract
We wanted to verify the effect of combining multi‐echo (ME) functional magnetic resonance imaging (fMRI) with slice acceleration in simultaneous multi‐slice acquisition. The aim was to shed light on the benefits of multiple echoes for various acquisition settings, especially for levels of slice acceleration and flip angle. Whole‐brain ME fMRI data were obtained from 26 healthy volunteers (using three echoes; seven runs with slice acceleration 1, 4, 6, and 8; and two different flip angles for each of the first three acceleration factors) and processed as single‐echo (SE) data and ME data based on optimal combinations weighted by the contrast‐to‐noise ratio. Global metrics (temporal signal‐to‐noise ratio, signal‐to‐noise separation, number of active voxels, etc.) and local characteristics in regions of interest were used to evaluate SE and ME data. ME results outperformed SE results in all runs; the differences became more apparent for higher acceleration, where a significant decrease in data quality is observed. ME fMRI can improve the observed data quality metrics over SE fMRI for a wide range of accelerated fMRI acquisitions.
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Affiliation(s)
- Anežka Kovářová
- CEITEC - Central European Institute of Technology, Masaryk University, Brno, Czech Republic.,First Department of Neurology, Faculty of Medicine of the Masaryk University, Brno, Czech Republic
| | - Martin Gajdoš
- CEITEC - Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Ivan Rektor
- CEITEC - Central European Institute of Technology, Masaryk University, Brno, Czech Republic.,First Department of Neurology, Faculty of Medicine of the Masaryk University, Brno, Czech Republic
| | - Michal Mikl
- CEITEC - Central European Institute of Technology, Masaryk University, Brno, Czech Republic
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18
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Dowdle LT, Ghose G, Chen CCC, Ugurbil K, Yacoub E, Vizioli L. Statistical power or more precise insights into neuro-temporal dynamics? Assessing the benefits of rapid temporal sampling in fMRI. Prog Neurobiol 2021; 207:102171. [PMID: 34492308 DOI: 10.1016/j.pneurobio.2021.102171] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 08/09/2021] [Accepted: 09/02/2021] [Indexed: 01/25/2023]
Abstract
Functional magnetic resonance imaging (fMRI), a non-invasive and widely used human neuroimaging method, is most known for its spatial precision. However, there is a growing interest in its temporal sensitivity. This is despite the temporal blurring of neuronal events by the blood oxygen level dependent (BOLD) signal, the peak of which lags neuronal firing by 4-6 seconds. Given this, the goal of this review is to answer a seemingly simple question - "What are the benefits of increased temporal sampling for fMRI?". To answer this, we have combined fMRI data collected at multiple temporal scales, from 323 to 1000 milliseconds, with a review of both historical and contemporary temporal literature. After a brief discussion of technological developments that have rekindled interest in temporal research, we next consider the potential statistical and methodological benefits. Most importantly, we explore how fast fMRI can uncover previously unobserved neuro-temporal dynamics - effects that are entirely missed when sampling at conventional 1 to 2 second rates. With the intrinsic link between space and time in fMRI, this temporal renaissance also delivers improvements in spatial precision. Far from producing only statistical gains, the array of benefits suggest that the continued temporal work is worth the effort.
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Affiliation(s)
- Logan T Dowdle
- Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN, 55455, United States; Department of Neurosurgery, University of Minnesota, 500 SE Harvard St, Minneapolis, MN, 55455, United States; Department of Neuroscience, University of Minnesota, 321 Church St SE, Minneapolis, MN, 55455, United States.
| | - Geoffrey Ghose
- Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN, 55455, United States; Department of Neuroscience, University of Minnesota, 321 Church St SE, Minneapolis, MN, 55455, United States
| | - Clark C C Chen
- Department of Neurosurgery, University of Minnesota, 500 SE Harvard St, Minneapolis, MN, 55455, United States
| | - Kamil Ugurbil
- Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN, 55455, United States
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN, 55455, United States
| | - Luca Vizioli
- Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN, 55455, United States; Department of Neurosurgery, University of Minnesota, 500 SE Harvard St, Minneapolis, MN, 55455, United States.
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19
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Risk BB, Murden RJ, Wu J, Nebel MB, Venkataraman A, Zhang Z, Qiu D. Which multiband factor should you choose for your resting-state fMRI study? Neuroimage 2021; 234:117965. [PMID: 33744454 PMCID: PMC8159874 DOI: 10.1016/j.neuroimage.2021.117965] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 03/05/2021] [Accepted: 03/06/2021] [Indexed: 12/30/2022] Open
Abstract
Multiband acquisition, also called simultaneous multislice, has become a popular technique in resting-state functional connectivity studies. Multiband (MB) acceleration leads to a higher temporal resolution but also leads to spatially heterogeneous noise amplification, suggesting the costs may be greater in areas such as the subcortex. We evaluate MB factors of 2, 3, 4, 6, 8, 9, and 12 with 2 mm isotropic voxels, and additionally 2 mm and 3.3 mm single-band acquisitions, on a 32-channel head coil. Noise amplification was greater in deeper brain regions, including subcortical regions. Correlations were attenuated by noise amplification, which resulted in spatially varying biases that were more severe at higher MB factors. Temporal filtering decreased spatial biases in correlations due to noise amplification, but also tended to decrease effect sizes. In seed-based correlation maps, left-right putamen connectivity and thalamo-motor connectivity were highest in the single-band 3.3 mm protocol. In correlation matrices, MB 4, 6, and 8 had a greater number of significant correlations than the other acquisitions (both with and without temporal filtering). We recommend single-band 3.3 mm for seed-based subcortical analyses, and MB 4 provides a reasonable balance for studies analyzing both seed-based correlation maps and connectivity matrices. In multiband studies including secondary analyses of large-scale datasets, we recommend reporting effect sizes or test statistics instead of correlations. If correlations are reported, temporal filtering (or another method for thermal noise removal) should be used. The Emory Multiband Dataset is available on OpenNeuro.
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Affiliation(s)
- Benjamin B Risk
- Department of Biostatistics and Bioinformatics, Atlanta, GA, United States.
| | - Raphiel J Murden
- Department of Biostatistics and Bioinformatics, Atlanta, GA, United States
| | - Junjie Wu
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA, United States
| | - Mary Beth Nebel
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, United States; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Arun Venkataraman
- Department of Physics and Astronomy, University of Rochester, Rochester, NY, United States
| | - Zhengwu Zhang
- Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Deqiang Qiu
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA, United States
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20
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Cohen AD, Jagra AS, Yang B, Fernandez B, Banerjee S, Wang Y. Detecting Task Functional MRI Activation Using the Multiband Multiecho (MBME) Echo-Planar Imaging (EPI) Sequence. J Magn Reson Imaging 2021; 53:1366-1374. [PMID: 33210793 PMCID: PMC10937038 DOI: 10.1002/jmri.27448] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 11/05/2020] [Accepted: 11/06/2020] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Blood oxygen level-dependent (BOLD) functional MRI (fMRI) has been widely applied to detect brain activations. Recent advances in multiband (MB) and multiecho (ME) techniques have greatly improved fMRI methods. MB imaging improves temporal and/or spatial resolution, while ME imaging has been shown to improve BOLD sensitivity. This study aimed to evaluate the novel MBME echo planar imaging (EPI) sequence utilizing MB and ME simultaneously to determine if the MBME outperform the MB single echo (MBSE) sequence for task fMRI. PURPOSE To compare the performance of MBME with MBSE in a task fMRI study. STUDY TYPE Prospective. POPULATION A total of 29 healthy volunteers aged 20-46 years (9 male, 20 female). FIELD STRENGTH/SEQUENCE MBSE and MBME gradient-echo EPI sequences were applied at 3T. Additional T1 -weighted magnetization-prepared rapid acquisition with gradient echo (MPRAGE) was collected. ASSESSMENT A checkerboard visual task was presented during the functional MBSE and MBME scans. The MBME or MBSE signal was evaluated using the temporal signal-to-noise ratio (tSNR). Task activation was evaluated using the z-score, volume, sensitivity, and specificity. Test-retest metrics of task activation were examined with the Dice coefficient (DC) and intraclass correlation coefficient (ICC) on subjects with repeated scans. STATISTICAL TESTS A linear mixed-effects model was used to compared MBME and MBSE activation at the voxel base. The paired t-test was used to compare tSNR, activation z-score, and volume, along with sensitivity, specificity, and DC between MBSE and MBME. RESULTS While similar task activation was detected in the visual cortex, MBME showed higher activation volume and higher sensitivity compared with MBSE (P < 0.05). ICC was higher for MBME than MBSE, while there was a trend of differences in DC (P = 0.08). DATA CONCLUSION MBME resulted in higher task fMRI activation volume and sensitivity without losing specificity. Reliability was also higher for MBME scans compared with MBSE. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY STAGE: 1.
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Affiliation(s)
- Alexander D. Cohen
- Department of Radiology, Medical College of Wisconsin, Milwaukee, WI, United States
| | | | | | | | | | - Yang Wang
- Department of Radiology, Medical College of Wisconsin, Milwaukee, WI, United States
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21
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Darányi V, Hermann P, Homolya I, Vidnyánszky Z, Nagy Z. An empirical investigation of the benefit of increasing the temporal resolution of task-evoked fMRI data with multi-band imaging. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2021; 34:667-676. [PMID: 33763764 PMCID: PMC8421273 DOI: 10.1007/s10334-021-00918-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 02/26/2021] [Accepted: 03/03/2021] [Indexed: 11/24/2022]
Abstract
Objective There is a tendency for reducing TR in MRI experiments with multi-band imaging. We empirically investigate its benefit for the group-level statistical outcome in task-evoked fMRI. Methods Three visual fMRI data sets were collected from 17 healthy adult participants. Multi-band acquisition helped vary the TR (2000/1000/410 ms, respectively). Because these data sets capture different temporal aspects of the haemodynamic response (HRF), we tested several HRF models. We computed a composite descriptive statistic, H, from β’s of each first-level model fit and carried it to the group-level analysis. The number of activated voxels and the t value of the group-level analysis as well as a goodness-of-fit measure were used as surrogate markers of data quality for comparison. Results Increasing the temporal sampling rate did not provide a universal improvement in the group-level statistical outcome. Rather, both the voxel-wise and ROI-averaged group-level results varied widely with anatomical location, choice of HRF and the setting of the TR. Correspondingly, the goodness-of-fit of HRFs became worse with increasing the sampling frequency. Conclusion Rather than universally increasing the temporal sampling rate in cognitive fMRI experiments, these results advocate the performance of a pilot study for the specific ROIs of interest to identify the appropriate temporal sampling rate for the acquisition and the correspondingly suitable HRF for the analysis of the data. Supplementary Information The online version contains supplementary material available at 10.1007/s10334-021-00918-z.
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Affiliation(s)
- Virág Darányi
- Brain Imaging Centre, Research Centre for Natural Sciences, Budapest, Hungary
| | - Petra Hermann
- Brain Imaging Centre, Research Centre for Natural Sciences, Budapest, Hungary
| | - István Homolya
- Brain Imaging Centre, Research Centre for Natural Sciences, Budapest, Hungary
| | - Zoltán Vidnyánszky
- Brain Imaging Centre, Research Centre for Natural Sciences, Budapest, Hungary
| | - Zoltan Nagy
- Laboratory for Social and Neural Systems Research, University of Zürich, Rämistrasse 100, P.O. Box 149, Zürich, Switzerland.
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22
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Sheikh UA, Carreiras M, Soto D. Neurocognitive mechanisms supporting the generalization of concepts across languages. Neuropsychologia 2020; 153:107740. [PMID: 33388337 DOI: 10.1016/j.neuropsychologia.2020.107740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Revised: 12/26/2020] [Accepted: 12/27/2020] [Indexed: 10/22/2022]
Abstract
The neurocognitive mechanisms that support the generalization of semantic representations across different languages remain to be determined. Current psycholinguistic models propose that semantic representations are likely to overlap across languages, although there is evidence also to the contrary. Neuroimaging studies observed that brain activity patterns associated with the meaning of words may be similar across languages. However, the factors that mediate cross-language generalization of semantic representations are not known. We here identify a key factor: the depth of processing. Human participants were asked to process visual words as they underwent functional MRI. We found that, during shallow processing, multivariate pattern classifiers could decode the word semantic category within each language in putative substrates of the semantic network, but there was no evidence of cross-language generalization in the shallow processing context. By contrast, when the depth of processing was higher, significant cross-language generalization was observed in several regions, including inferior parietal, ventromedial, lateral temporal, and inferior frontal cortex. These results are in keeping with distributed-only views of semantic processing and favour models based on multiple semantic hubs. The results also have ramifications for existing psycholinguistic models of word processing such as the BIA+, which by default assumes non-selective access to both native and second languages.
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Affiliation(s)
- Usman Ayub Sheikh
- Basque Center on Cognition, Brain and Language, San Sebastian, Spain.
| | - Manuel Carreiras
- Basque Center on Cognition, Brain and Language, San Sebastian, Spain; Ikerbasque, Basque Foundation for Science, Bilbao, Spain; University of the Basque Country, Bilbao, Spain
| | - David Soto
- Basque Center on Cognition, Brain and Language, San Sebastian, Spain; Ikerbasque, Basque Foundation for Science, Bilbao, Spain.
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23
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Kang D, Jo HJ, In MH, Yarach U, Meyer NK, Bardwell Speltz LJ, Gray EM, Trzasko JD, Huston Iii J, Bernstein MA, Shu Y. The benefit of high-performance gradients on echo planar imaging for BOLD-based resting-state functional MRI. Phys Med Biol 2020; 65:235024. [PMID: 33245051 DOI: 10.1088/1361-6560/abb2ec] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
Improved gradient performance in an MRI system reduces distortion in echo planar imaging (EPI), which has been a key imaging method for functional studies. A lightweight, low-cryogen compact 3T MRI scanner (C3T) is capable of achieving 80 mT m-1 gradient amplitude with 700 T m-1 s-1 slew rate, in comparison with a conventional whole-body 3T MRI scanner (WB3T, 50 mT m-1 with 200 T m-1 s-1). We investigated benefits of the high-performance gradients in a high-spatial-resolution (1.5 mm isotropic) functional MRI study. Reduced echo spacing in the EPI pulse sequence inherently leads to less severe geometric distortion, which provided higher accuracy than with WB3T for registration between EPI and anatomical images. The cortical coverage of C3T datasets was improved by more accurate signal depiction (i.e. less dropout or pile-up). Resting-state functional analysis results showed that greater magnitude and extent in functional connectivity (FC) for the C3T than the WB3T when the selected seed region is susceptible to distortions, while the FC matrix for well-known brain networks showed little difference between the two scanners. This shows that the improved quality in EPI is particularly valuable for studying certain brain regions typically obscured by severe distortion.
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Affiliation(s)
- Daehun Kang
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, United States of America. Co-first/equal authorship - these authors contributed equally to this work
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Bollmann S, Barth M. New acquisition techniques and their prospects for the achievable resolution of fMRI. Prog Neurobiol 2020; 207:101936. [PMID: 33130229 DOI: 10.1016/j.pneurobio.2020.101936] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 09/10/2020] [Accepted: 10/18/2020] [Indexed: 01/17/2023]
Abstract
This work reviews recent advances in technologies for functional magnetic resonance imaging (fMRI) of the human brain and highlights the push for higher functional specificity based on increased spatial resolution and specific MR contrasts to reveal previously undetectable functional properties of small-scale cortical structures. We discuss how the combination of MR hardware, advanced acquisition techniques and various MR contrast mechanisms have enabled recent progress in functional neuroimaging. However, these advanced fMRI practices have only been applied to a handful of neuroscience questions to date, with the majority of the neuroscience community still using conventional imaging techniques. We thus discuss upcoming challenges and possibilities for fMRI technology development in human neuroscience. We hope that readers interested in functional brain imaging acquire an understanding of current and novel developments and potential future applications, even if they don't have a background in MR physics or engineering. We summarize the capabilities of standard fMRI acquisition schemes with pointers to relevant literature and comprehensive reviews and introduce more recent developments.
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Affiliation(s)
- Saskia Bollmann
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia
| | - Markus Barth
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia; School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia; ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, QLD, Australia.
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25
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Hennig J, Kiviniemi V, Riemenschneider B, Barghoorn A, Akin B, Wang F, LeVan P. 15 Years MR-encephalography. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2020; 34:85-108. [PMID: 33079327 PMCID: PMC7910380 DOI: 10.1007/s10334-020-00891-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Revised: 09/02/2020] [Accepted: 09/29/2020] [Indexed: 02/07/2023]
Abstract
Objective This review article gives an account of the development of the MR-encephalography (MREG) method, which started as a mere ‘Gedankenexperiment’ in 2005 and gradually developed into a method for ultrafast measurement of physiological activities in the brain. After going through different approaches covering k-space with radial, rosette, and concentric shell trajectories we have settled on a stack-of-spiral trajectory, which allows full brain coverage with (nominal) 3 mm isotropic resolution in 100 ms. The very high acceleration factor is facilitated by the near-isotropic k-space coverage, which allows high acceleration in all three spatial dimensions. Methods The methodological section covers the basic sequence design as well as recent advances in image reconstruction including the targeted reconstruction, which allows real-time feedback applications, and—most recently—the time-domain principal component reconstruction (tPCR), which applies a principal component analysis of the acquired time domain data as a sparsifying transformation to improve reconstruction speed as well as quality. Applications Although the BOLD-response is rather slow, the high speed acquisition of MREG allows separation of BOLD-effects from cardiac and breathing related pulsatility. The increased sensitivity enables direct detection of the dynamic variability of resting state networks as well as localization of single interictal events in epilepsy patients. A separate and highly intriguing application is aimed at the investigation of the glymphatic system by assessment of the spatiotemporal patterns of cardiac and breathing related pulsatility. Discussion MREG has been developed to push the speed limits of fMRI. Compared to multiband-EPI this allows considerably faster acquisition at the cost of reduced image quality and spatial resolution.
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Affiliation(s)
- Juergen Hennig
- Department of Radiology, Medical Physics, Faculty of Medicine, Medical Center University of Freiburg, University of Freiburg, Freiburg, Germany. .,Center for Basics in NeuroModulation (NeuroModulBasics), Faculty of Medicine, University of Freiburg, Freiburg, Germany.
| | - Vesa Kiviniemi
- Oulu Functional NeuroImaging Group, Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland
| | - Bruno Riemenschneider
- Department of Radiology, Center for Biomedical Imaging, New York University Grossman School of Medicine, New York, NY, USA
| | - Antonia Barghoorn
- Department of Radiology, Medical Physics, Faculty of Medicine, Medical Center University of Freiburg, University of Freiburg, Freiburg, Germany.,Center for Basics in NeuroModulation (NeuroModulBasics), Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Burak Akin
- Department of Radiology, Medical Physics, Faculty of Medicine, Medical Center University of Freiburg, University of Freiburg, Freiburg, Germany.,Center for Basics in NeuroModulation (NeuroModulBasics), Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Fei Wang
- Department of Radiology, Medical Physics, Faculty of Medicine, Medical Center University of Freiburg, University of Freiburg, Freiburg, Germany.,Center for Basics in NeuroModulation (NeuroModulBasics), Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Pierre LeVan
- Departments of Radiology and Paediatrics, Hotchkiss Brain Institute and Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
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26
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Dual Function of Primary Somatosensory Cortex in Cognitive Control of Language: Evidence from Resting State fMRI. Neuroscience 2020; 446:59-68. [PMID: 32866600 DOI: 10.1016/j.neuroscience.2020.08.032] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Revised: 08/20/2020] [Accepted: 08/21/2020] [Indexed: 11/22/2022]
Abstract
Resting state functional connectivity can be leveraged to investigate bilingual individual differences in cognitive control of language; however, thus far no report is provided on how the connectivity profiles of brain functional networks at rest point to different language control behavior in bilinguals. In order to address this gap in state-of-the-art research we did a functional connectivity analysis on the resting state data acquired via multiband EPI to investigate three resting state networks of interest namely, the frontoparietal network (FPN), the salience network (SN), and the default mode network (DMN), which are related to cognitive control, between two groups of Dutch-English bilinguals based on how they performed in a language switching task. Results demonstrated that there is the increased coupling of the left primary somatosensory cortex with the dorsolateral prefrontal cortex in the group with better performance in cognitive control of language and the increased coupling of the right primary somatosensory cortex with the inferior parietal cortex in the group with poorer performance in this executive function. As regards these results, we claim that the primary somatosensory cortex has a dual function in coupling with the dorsolateral prefrontal cortex and the inferior parietal cortex in the FPN, and in fact, in what characterizes bilingual individual differences in cognitive control of language in healthy participants. The results of this study provide a model for future research in cognitive control of language and may serve as a reference in clinical neuroscience when bilinguals are diagnosed with dysfunction in cognitive control.
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27
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Lee HJ, Huang SY, Kuo WJ, Graham SJ, Chu YH, Stenroos M, Lin FH. Concurrent electrophysiological and hemodynamic measurements of evoked neural oscillations in human visual cortex using sparsely interleaved fast fMRI and EEG. Neuroimage 2020; 217:116910. [PMID: 32389729 DOI: 10.1016/j.neuroimage.2020.116910] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Revised: 04/21/2020] [Accepted: 04/30/2020] [Indexed: 11/17/2022] Open
Abstract
Electroencephalography (EEG) concurrently collected with functional magnetic resonance imaging (fMRI) is heavily distorted by the repetitive gradient coil switching during the fMRI acquisition. The performance of the typical template-based gradient artifact suppression method can be suboptimal because the artifact changes over time. Gradient artifact residuals also impede the subsequent suppression of ballistocardiography artifacts. Here we propose recording continuous EEG with temporally sparse fast fMRI (fast fMRI-EEG) to minimize the EEG artifacts caused by MRI gradient coil switching without significantly compromising the field-of-view and spatiotemporal resolution of fMRI. Using simultaneous multi-slice inverse imaging to achieve whole-brain fMRI with isotropic 5-mm resolution in 0.1 s, and performing these acquisitions once every 2 s, we have 95% of the duty cycle available to record EEG with substantially less gradient artifact. We found that the standard deviation of EEG signals over the entire acquisition period in fast fMRI-EEG was reduced to 54% of that in conventional concurrent echo-planar imaging (EPI) and EEG recordings (EPI-EEG) across participants. When measuring 15-Hz steady-state visual evoked potentials (SSVEPs), the baseline-normalized oscillatory neural response in fast fMRI-EEG was 2.5-fold of that in EPI-EEG. The functional MRI responses associated with the SSVEP delineated by EPI and fast fMRI were similar in the spatial distribution, the elicited waveform, and detection power. Sparsely interleaved fast fMRI-EEG provides high-quality EEG without substantially compromising the quality of fMRI in evoked response measurements, and has the potential utility for applications where the onset of the target stimulus cannot be precisely determined, such as epilepsy.
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Affiliation(s)
- Hsin-Ju Lee
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Shu-Yu Huang
- Institute of Neuroscience, National Yang-Ming University, Taipei, Taiwan
| | - Wen-Jui Kuo
- Institute of Neuroscience, National Yang-Ming University, Taipei, Taiwan
| | - Simon J Graham
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Ying-Hua Chu
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Matti Stenroos
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
| | - Fa-Hsuan Lin
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada; Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland.
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28
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Kulkarni PH, Merchant SN, Awate SP. R-fMRI reconstruction from k-t undersampled data using a subject-invariant dictionary model and VB-EM with nested minorization. Med Image Anal 2020; 65:101752. [PMID: 32623273 DOI: 10.1016/j.media.2020.101752] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Revised: 06/01/2020] [Accepted: 06/04/2020] [Indexed: 11/30/2022]
Abstract
Higher spatial resolution in resting-state functional magnetic resonance imaging (R-fMRI) can give reliable information about the functional networks in the cerebral cortex. Typical methods can achieve higher spatial or temporal resolution by speeding up scans using either (i) complex pulse-sequence designs or (ii) k-space undersampling coupled with priors on the signal. We propose to undersample the R-fMRI acquisition in k-space and time to speedup scans in order to improve spatial resolution. We propose a novel model-based R-fMRI reconstruction framework using a robust, subject-invariant, spatially regularized dictionary prior on the signal. Furthermore, we propose a novel inference framework based on variational Bayesian expectation maximization with nested minorization (VB-EM-NM). Our inference framework allows us to provide an estimate of uncertainty of the reconstruction, unlike typical reconstruction methods. Empirical evaluation of (i) simulated R-fMRI reconstruction and (ii) functional-network estimates from brain R-fMRI reconstructions demonstrate that our framework improves over the state of the art, and, additionally, enables significantly higher spatial resolution.
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Affiliation(s)
- Prachi H Kulkarni
- Electrical Engineering (EE) Department, Indian Institute of Technology (IIT) Bombay, Mumbai, India.
| | - S N Merchant
- Electrical Engineering (EE) Department, Indian Institute of Technology (IIT) Bombay, Mumbai, India
| | - Suyash P Awate
- Computer Science and Engineering (CSE) Department, Indian Institute of Technology (IIT) Bombay, Mumbai, India
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29
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Nezafati M, Temmar H, Keilholz SD. Functional MRI Signal Complexity Analysis Using Sample Entropy. Front Neurosci 2020; 14:700. [PMID: 32714141 PMCID: PMC7344022 DOI: 10.3389/fnins.2020.00700] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 06/09/2020] [Indexed: 11/13/2022] Open
Abstract
Resting-state functional magnetic resonance imaging (rs-fMRI) is an immensely powerful method in neuroscience that uses the blood oxygenation level-dependent (BOLD) signal to record and analyze neural activity in the brain. We examined the complexity of brain activity acquired by rs-fMRI to determine whether it exhibits variation across brain regions. In this study the complexity of regional brain activity was analyzed by calculating the sample entropy of 200 whole-brain BOLD volumes as well as of distinct brain networks, cortical regions, and subcortical regions of these brain volumes. It can be seen that different brain regions and networks exhibit distinctly different levels of entropy/complexity, and that entropy in the brain significantly differs between brains at rest and during task performance.
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Affiliation(s)
- Maysam Nezafati
- Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Hisham Temmar
- Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Shella D. Keilholz
- Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
- Neuroscience Program, Graduate Division of Biological and Biomedical Sciences, Laney Graduate School, Emory University, Atlanta, GA, United States
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30
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Seidel P, Levine SM, Tahedl M, Schwarzbach JV. Temporal Signal-to-Noise Changes in Combined Multislice- and In-Plane-Accelerated Echo-Planar Imaging with a 20- and 64-Channel Coil. Sci Rep 2020; 10:5536. [PMID: 32218476 PMCID: PMC7099092 DOI: 10.1038/s41598-020-62590-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Accepted: 03/17/2020] [Indexed: 11/08/2022] Open
Abstract
Echo-planar imaging (EPI) is the most common method of functional MRI for acquiring the blood oxygenation level-dependent (BOLD) contrast, allowing the acquisition of an entire brain volume within seconds. However, because imaging protocols are limited by hardware (e.g., fast gradient switching), researchers must compromise between spatial resolution, temporal resolution, or whole-brain coverage. Earlier attempts to circumvent this problem included developing protocols in which slices of a volume were acquired faster (i.e., in-plane acceleration (S)) or simultaneously (i.e., multislice acceleration (M)). However, applying acceleration methods can lead to a reduction in the temporal signal-to-noise ratio (tSNR): a critical measure of signal stability over time. Using a 20- and 64-channel receiver coil, we show that enabling S-acceleration consistently yielded a substantial decrease in tSNR, regardless of the receiver coil, whereas M-acceleration yielded less pronounced tSNR decrease. Moreover, tSNR losses tended to occur in temporal, insular, and medial brain regions and were more noticeable with the 20-channel coil, while with the 64-channel coil, the tSNR in lateral frontoparietal regions remained relatively stable up to six-fold M-acceleration producing comparable tSNR to that of no acceleration. Such methodological explorations can guide researchers and clinicians in optimizing imaging protocols depending on the brain regions under investigation.
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Affiliation(s)
- Philipp Seidel
- Department of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany
- Faculty of Psychology and Education Sciences, University of Coimbra, Coimbra, Portugal
| | - Seth M Levine
- Department of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany
| | - Marlene Tahedl
- Department of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany
| | - Jens V Schwarzbach
- Department of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany.
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31
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Bhandari R, Kirilina E, Caan M, Suttrup J, De Sanctis T, De Angelis L, Keysers C, Gazzola V. Does higher sampling rate (multiband + SENSE) improve group statistics - An example from social neuroscience block design at 3T. Neuroimage 2020; 213:116731. [PMID: 32173409 PMCID: PMC7181191 DOI: 10.1016/j.neuroimage.2020.116731] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Revised: 02/27/2020] [Accepted: 03/09/2020] [Indexed: 02/06/2023] Open
Abstract
Multiband (MB) or Simultaneous multi-slice (SMS) acquisition schemes allow the acquisition of MRI signals from more than one spatial coordinate at a time. Commercial availability has brought this technique within the reach of many neuroscientists and psychologists. Most early evaluation of the performance of MB acquisition employed resting state fMRI or the most basic tasks. In this study, we tested whether the advantages of using MB acquisition schemes generalize to group analyses using a cognitive task more representative of typical cognitive neuroscience applications. Twenty-three subjects were scanned on a Philips 3 T scanner using five sequences, up to eight-fold acceleration with MB-factors 1 to 4, SENSE factors up to 2 and corresponding TRs of 2.45s down to 0.63s, while they viewed (i) movie blocks showing complex actions with hand object interactions and (ii) control movie blocks without hand object interaction. Data were processed using a widely used analysis pipeline implemented in SPM12 including the unified segmentation and canonical HRF modelling. Using random effects group-level, voxel-wise analysis we found that all sequences were able to detect the basic action observation network known to be recruited by our task. The highest t-values were found for sequences with MB4 acceleration. For the MB1 sequence, a 50% bigger voxel volume was needed to reach comparable t-statistics. The group-level t-values for resting state networks (RSNs) were also highest for MB4 sequences. Here the MB1 sequence with larger voxel size did not perform comparable to the MB4 sequence. Altogether, we can thus recommend the use of MB4 (and SENSE 1.5 or 2) on a Philips scanner when aiming to perform group-level analyses using cognitive block design fMRI tasks and voxel sizes in the range of cortical thickness (e.g. 2.7 mm isotropic). While results will not be dramatically changed by the use of multiband, our results suggest that MB will bring a moderate but significant benefit.
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Affiliation(s)
- Ritu Bhandari
- Netherlands Institute for Neuroscience, KNAW, Amsterdam, the Netherlands.
| | - Evgeniya Kirilina
- Center for Cognitive Neuroscience, Free University, Berlin, Germany; Max Plank Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Matthan Caan
- Spinoza Centre for Neuroimaging, Amsterdam, the Netherlands; Amsterdam UMC, University of Amsterdam, Biomedical Engineering & Physics, Amsterdam, the Netherlands
| | - Judith Suttrup
- Netherlands Institute for Neuroscience, KNAW, Amsterdam, the Netherlands
| | - Teresa De Sanctis
- Netherlands Institute for Neuroscience, KNAW, Amsterdam, the Netherlands
| | - Lorenzo De Angelis
- Netherlands Institute for Neuroscience, KNAW, Amsterdam, the Netherlands
| | - Christian Keysers
- Netherlands Institute for Neuroscience, KNAW, Amsterdam, the Netherlands; Department of Psychology, University of Amsterdam, the Netherlands
| | - Valeria Gazzola
- Netherlands Institute for Neuroscience, KNAW, Amsterdam, the Netherlands; Department of Psychology, University of Amsterdam, the Netherlands.
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32
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Chen JCC, Forsyth A, Dubowitz DJ, Muthukumaraswamy SD. On the Quality, Statistical Efficiency, and Safety of Simultaneously Recorded Multiband fMRI/EEG. Brain Topogr 2020; 33:303-316. [PMID: 32144628 DOI: 10.1007/s10548-020-00761-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Accepted: 02/24/2020] [Indexed: 01/19/2023]
Abstract
The recent development of multiband functional magnetic resonance imaging (MB-fMRI) allows for the reduction of sampling period by simultaneously exciting multiple slices-the number of which is referred to as the multiband factor. Simultaneously recorded electroencephalography (EEG)/MB-fMRI has yet to be validated for data quality against conventional single band (SB)-fMRI. Pilot scans were conducted on phantoms twice and on a healthy volunteer to ensure no heating effects. In the main study, two thermometer probes were attached to 16 healthy individuals (ages 20-39, 9 females) whilst they completed two sets of 16-min resting-state and two sets of 9-min n-back task scans-each set consisting of one MB4 and one SB pulse sequence. No heating effects were reported and thermometer data showed mean increases of < 1.0 °C. Minimal differences between the two scan types were found in EEG channel variance and spectra. Expected decreases in MB4-fMRI tSNR were observed. In n-back task scans, little to no differences were detected in both EEG source analyses and fMRI local analyses for mixed effects. Resting-state posterior cingulate cortex seed-based analyses of the default mode network along with EEG-informed fMRI analysis of the occipital alpha anticorrelation effect showed improved statistical and spatial sensitivity at lower scan durations. Using EEG/MB4-fMRI for n-back tasks provided no statistical advantages nor disadvantages. However, for studying the resting-state, MB4-fMRI potentially allows for reduced scanning durations for equivalent statistical significance to be obtained or alternatively, larger effect sizes for the same scanning duration. As such, simultaneous EEG/MB4-fMRI is a viable alternative to EEG/SB-fMRI.
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Affiliation(s)
- Joseph C C Chen
- School of Pharmacy, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Anna Forsyth
- School of Pharmacy, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - David J Dubowitz
- Department of Anatomy and Medical Imaging, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.,Centre for Advanced MRI, Auckland UniServices Limited, Auckland, New Zealand
| | - Suresh D Muthukumaraswamy
- School of Pharmacy, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.
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33
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Fair DA, Miranda-Dominguez O, Snyder AZ, Perrone A, Earl EA, Van AN, Koller JM, Feczko E, Tisdall MD, van der Kouwe A, Klein RL, Mirro AE, Hampton JM, Adeyemo B, Laumann TO, Gratton C, Greene DJ, Schlaggar BL, Hagler DJ, Watts R, Garavan H, Barch DM, Nigg JT, Petersen SE, Dale AM, Feldstein-Ewing SW, Nagel BJ, Dosenbach NU. Correction of respiratory artifacts in MRI head motion estimates. Neuroimage 2020; 208:116400. [PMID: 31778819 PMCID: PMC7307712 DOI: 10.1016/j.neuroimage.2019.116400] [Citation(s) in RCA: 122] [Impact Index Per Article: 30.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Revised: 11/19/2019] [Accepted: 11/23/2019] [Indexed: 02/08/2023] Open
Abstract
Head motion represents one of the greatest technical obstacles in magnetic resonance imaging (MRI) of the human brain. Accurate detection of artifacts induced by head motion requires precise estimation of movement. However, head motion estimates may be corrupted by artifacts due to magnetic main field fluctuations generated by body motion. In the current report, we examine head motion estimation in multiband resting state functional connectivity MRI (rs-fcMRI) data from the Adolescent Brain and Cognitive Development (ABCD) Study and comparison 'single-shot' datasets. We show that respirations contaminate movement estimates in functional MRI and that respiration generates apparent head motion not associated with functional MRI quality reductions. We have developed a novel approach using a band-stop filter that accurately removes these respiratory effects from motion estimates. Subsequently, we demonstrate that utilizing a band-stop filter improves post-processing fMRI data quality. Lastly, we demonstrate the real-time implementation of motion estimate filtering in our FIRMM (Framewise Integrated Real-Time MRI Monitoring) software package.
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Affiliation(s)
- Damien A. Fair
- Department of Behavioral Neuroscience, Oregon Health & Sciences University, Portland, OR, USA.,Department of Psychiatry, Oregon Health & Sciences University, Portland, OR, USA.,Advanced Imaging Research Center, Oregon Health & Sciences University, Portland, OR, USA.,To whom correspondence should be addressed. ,
| | - Oscar Miranda-Dominguez
- Department of Behavioral Neuroscience, Oregon Health & Sciences University, Portland, OR, USA
| | - Abraham Z. Snyder
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.,Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Anders Perrone
- Department of Behavioral Neuroscience, Oregon Health & Sciences University, Portland, OR, USA
| | - Eric A. Earl
- Department of Behavioral Neuroscience, Oregon Health & Sciences University, Portland, OR, USA
| | - Andrew N. Van
- Department of Biomedical Engineering, Washington University, St. Louis, MO, USA
| | - Jonathan M. Koller
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Eric Feczko
- Department of Behavioral Neuroscience, Oregon Health & Sciences University, Portland, OR, USA.,Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Sciences University, Portland OR, USA
| | - M. Dylan Tisdall
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Andre van der Kouwe
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA USA
| | - Rachel L. Klein
- Department of Psychiatry, Oregon Health & Sciences University, Portland, OR, USA
| | - Amy E. Mirro
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.,Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, USA
| | - Jacqueline M. Hampton
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Babatunde Adeyemo
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Timothy O. Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Caterina Gratton
- Department of Psychology & Neurology, Northwestern University, Chicago, IL, USA
| | - Deanna J. Greene
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA.,Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Bradley L. Schlaggar
- Kennedy Krieger Institute, Baltimore, MD, USA; Department of Neurology; Johns Hopkins University; Baltimore; MD; USA Department of Pediatrics; Johns Hopkins University
| | - Donald J. Hagler
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Richard Watts
- FAS Brain Imaging Center, Yale University, New Haven, CT, USA
| | - Hugh Garavan
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - Deanna M. Barch
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA.,Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA.,Department of Psychological & Brain Sciences, Washington University, St. Louis, MO, USA
| | - Joel T. Nigg
- Department of Behavioral Neuroscience, Oregon Health & Sciences University, Portland, OR, USA.,Department of Psychiatry, Oregon Health & Sciences University, Portland, OR, USA
| | - Steven E. Petersen
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.,Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA.,Department of Biomedical Engineering, Washington University, St. Louis, MO, USA,Department of Psychological & Brain Sciences, Washington University, St. Louis, MO, USA,Department of Neuroscience, Washington University, St. Louis, MO, USA
| | - Anders M. Dale
- Department of Radiology, University of California San Diego, La Jolla, CA, USA,Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
| | | | - Bonnie J. Nagel
- Department of Behavioral Neuroscience, Oregon Health & Sciences University, Portland, OR, USA.,Department of Psychiatry, Oregon Health & Sciences University, Portland, OR, USA
| | - Nico U.F. Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.,Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA.,Department of Biomedical Engineering, Washington University, St. Louis, MO, USA,Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, USA,Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO, USA,To whom correspondence should be addressed. ,
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34
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Luo Q, Misaki M, Mulyana B, Wong CK, Bodurka J. Improved autoregressive model for correction of noise serial correlation in fast fMRI. Magn Reson Med 2020; 84:1293-1305. [PMID: 32060948 PMCID: PMC7263980 DOI: 10.1002/mrm.28203] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Revised: 12/31/2019] [Accepted: 01/17/2020] [Indexed: 11/07/2022]
Abstract
PURPOSE In rapidly acquired functional MRI (fast fMRI) data, the noise serial correlations (SC) can produce problematically overestimated T-statistics which lead to invalid statistical inferences. This study aims to evaluate and improve the accuracy of high-order autoregressive model (AR(p), where p is the model order) based prewhitening method in the SC correction. METHODS Fast fMRI images were acquired at rest (null data) using a multiband simultaneous multi-slice echo planar imaging pulse sequence with repetition time (TR) = 300 and 500 ms. The SC effect in the fast fMRI data was corrected using the prewhitening method based on two AR(p) models: (1) the conventional model (fixed AR(p)) which preselects a constant p for all the image voxels; (2) an improved model (ARAICc ) that employs the corrected Akaike information criterion voxel-wise to automatically select the model orders for each voxel. To evaluate accuracy of SC correction, false positive characteristics were measured by assuming the presence of block and event-related tasks in the null data without image smoothing. The performance of prewhitening was also examined in smoothed images by adding pseudo task fMRI signals into the null data and comparing the detected to simulated activations (ground truth). RESULTS The measured false positive characteristics agreed well with the theoretical curve when using the ARAICc , and the activation maps in the smoothed data matched the ground truth. The ARAICc showed improved performance than the fixed AR(p) method. CONCLUSION The ARAICc can effectively remove noise SC, and accurate statistical analysis results can be obtained with the ARAICc correction in fast fMRI.
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Affiliation(s)
- Qingfei Luo
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA
| | - Masaya Misaki
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA
| | - Ben Mulyana
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA
| | - Chung-Ki Wong
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA
| | - Jerzy Bodurka
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA.,Stephenson School for Biomedical Engineering, University of Oklahoma, Norman, Oklahoma, USA
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Tabassi Mofrad F, Schiller NO. Cognitive demand modulates connectivity patterns of rostral inferior parietal cortex in cognitive control of language. Cogn Neurosci 2019; 11:181-193. [DOI: 10.1080/17588928.2019.1696764] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Affiliation(s)
- Fatemeh Tabassi Mofrad
- Leiden University Centre for Linguistics, Leiden 2300, The Netherlands
- Leiden Institute for Brain and Cognition, RC Leiden 2300, The Netherlands
- Cognitive Psychology Unit, Leiden University, AK Leiden 2333, The Netherlands
- Department of Applied Linguistics, Tarbiat Modares University, Tehran, Iran
| | - Niels O. Schiller
- Leiden University Centre for Linguistics, Leiden 2300, The Netherlands
- Leiden Institute for Brain and Cognition, RC Leiden 2300, The Netherlands
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Comparison of SMS-EPI and 3D-EPI at 7T in an fMRI localizer study with matched spatiotemporal resolution and homogenized excitation profiles. PLoS One 2019; 14:e0225286. [PMID: 31751410 PMCID: PMC6872176 DOI: 10.1371/journal.pone.0225286] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2019] [Accepted: 10/31/2019] [Indexed: 02/06/2023] Open
Abstract
The simultaneous multi-slice EPI (SMS-EPI, a.k.a. MB-EPI) sequence has met immense popularity recently in functional neuroimaging. A still less common alternative is the use of 3D-EPI, which offers similar acceleration capabilities. The aim of this work was to compare the SMS-EPI and the 3D-EPI sequences in terms of sampling strategies for the detection of task-evoked activations at 7T using detection theory. To this end, the spatial and temporal resolutions of the sequences were matched (1.6 mm isotropic resolution, TR = 1200 ms) and their excitation profiles were homogenized by means of calibration-free parallel-transmission (Universal Pulses). We used a fast-event “localizer” paradigm of 5:20 min in order to probe sensorimotor functions (visual, auditory and motor tasks) as well as higher level functions (language comprehension, mental calculation), where results from a previous large-scale study at 3T (N = 81) served as ground-truth reference for the brain areas implicated in each cognitive function. In the current study, ten subjects were scanned while their activation maps were generated for each cognitive function with the GLM analysis. The SMS-EPI and 3D-EPI sequences were compared in terms of raw tSNR, t-score testing for the mean signal, activation strength and accuracy of the robust sensorimotor functions. To this end, the sensitivity and specificity of these contrasts were computed by comparing their activation maps to the reference brain areas obtained in the 3T study. Estimated flip angle distributions in the brain reported a normalized root mean square deviation from the target value below 10% for both sequences. The analysis of the t-score testing for the mean signal revealed temporal noise correlations, suggesting the use of this metric instead of the traditional tSNR for testing fMRI sequences. The SMS-EPI and 3D-EPI thereby yielded similar performance from a detection theory perspective.
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37
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Kayser AS. Functional imaging. HANDBOOK OF CLINICAL NEUROLOGY 2019; 163:61-72. [PMID: 31590748 DOI: 10.1016/b978-0-12-804281-6.00004-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/03/2023]
Abstract
Functional imaging methodology has revolutionized our ability to understand brain-behavior relationships. In contrast with the static images obtained with standard imaging methods, functional images permit us to track brain activity as humans view stimuli, hear sounds, consider choices, and make decisions. The insights now possible because of this technology have not only provided new potential markers for disease but have also permitted questions of neural mechanism to be addressed in living humans. Because of the breadth and depth of research that directly or tangentially touches upon functional imaging, it is impossible to do justice to the various subfields, analysis streams, and methodological complexities in one chapter. Instead, this chapter will provide a brief overview of the underlying conceptual framework, basic analytic techniques, and details of the imaging methodologies available for the acquisition of functional imaging data.
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Affiliation(s)
- Andrew S Kayser
- Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States.
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38
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Aigner CS, Rund A, Abo Seada S, Price AN, Hajnal JV, Malik SJ, Kunisch K, Stollberger R. Time optimal control-based RF pulse design under gradient imperfections. Magn Reson Med 2019; 83:561-574. [PMID: 31441536 PMCID: PMC6899978 DOI: 10.1002/mrm.27955] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Revised: 07/25/2019] [Accepted: 07/29/2019] [Indexed: 12/15/2022]
Abstract
Purpose This study incorporates a gradient system imperfection model into an optimal control framework for radio frequency (RF) pulse design. Theory and Methods The joint design of minimum‐time RF and slice selective gradient shapes is posed as an optimal control problem. Hardware limitations such as maximal amplitudes for RF and slice selective gradient or its slew rate are included as hard constraints to assure practical applicability of the optimized waveforms. In order to guarantee the performance of the optimized waveform with possible gradient system disturbances such as limited system bandwidth and eddy currents, a measured gradient impulse response function (GIRF) for a specific system is integrated into the optimization. Results The method generates optimized RF and pre‐distorted slice selective gradient shapes for refocusing that are able to fully compensate the modeled imperfections of the gradient system under investigation. The results nearly regenerate the optimal results of an idealized gradient system. The numerical Bloch simulations are validated by phantom and in‐vivo experiments on 2 3T scanners. Conclusions The presented design approach demonstrates the successful correction of gradient system imperfections within an optimal control framework for RF pulse design.
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Affiliation(s)
- Christoph S Aigner
- Institute of Medical Engineering, Graz University of Technology, Graz, Austria
| | - Armin Rund
- Institute for Mathematics and Scientific Computing, University of Graz, Graz, Austria
| | - Samy Abo Seada
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Anthony N Price
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Joseph V Hajnal
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Shaihan J Malik
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Karl Kunisch
- Institute for Mathematics and Scientific Computing, University of Graz, Graz, Austria.,Johann Radon Institute for Computational and Applied Mathematics (RICAM), Austrian Academy of Sciences, Linz, Austria.,BioTechMed-Graz, Graz, Austria
| | - Rudolf Stollberger
- Institute of Medical Engineering, Graz University of Technology, Graz, Austria.,BioTechMed-Graz, Graz, Austria
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The potential of MR-Encephalography for BCI/Neurofeedback applications with high temporal resolution. Neuroimage 2019; 194:228-243. [PMID: 30910728 DOI: 10.1016/j.neuroimage.2019.03.046] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2018] [Revised: 03/14/2019] [Accepted: 03/19/2019] [Indexed: 11/20/2022] Open
Abstract
Real-time functional magnetic resonance imaging (rt-fMRI) enables the update of various brain-activity measures during an ongoing experiment as soon as a new brain volume is acquired. However, the recorded Blood-oxygen-level dependent (BOLD) signal also contains physiological artifacts such as breathing and heartbeat, which potentially cause misleading false positive effects especially problematic in brain-computer interface (BCI) and neurofeedback (NF) setups. The low temporal resolution of echo planar imaging (EPI) sequences (which is in the range of seconds) prevents a proper separation of these artifacts from the BOLD signal. MR-Encephalography (MREG) has been shown to provide the high temporal resolution required to unalias and correct for physiological fluctuations and leads to increased specificity and sensitivity for mapping task-based activation and functional connectivity as well as for detecting dynamic changes in connectivity over time. By comparing a simultaneous multislice echo planar imaging (SMS-EPI) sequence and an MREG sequence using the same nominal spatial resolution in an offline analysis for three different experimental fMRI paradigms (perception of house and face stimuli, motor imagery, Stroop task), the potential of this novel technique for future BCI and NF applications was investigated. First, adapted general linear model pre-whitening which accounts for the high temporal resolution in MREG was implemented to calculate proper statistical results and be able to compare these with the SMS-EPI sequence. Furthermore, the respiration- and cardiac pulsation-related signals were successfully separated from the MREG signal using independent component analysis which were then included as regressors for a GLM analysis. Only the MREG sequence allowed to clearly separate cardiac pulsation and respiration components from the signal time course. It could be shown that these components highly correlate with the recorded respiration and cardiac pulsation signals using a respiratory belt and fingertip pulse plethysmograph. Temporal signal-to-noise ratios of SMS-EPI and MREG were comparable. Functional connectivity analysis using partial correlation showed a reduced standard error in MREG compared to SMS-EPI. Also, direct time course comparisons by down-sampling the MREG signal to the SMS-EPI temporal resolution showed lower variance in MREG. In general, we show that the higher temporal resolution is beneficial for fMRI time course modeling and this aspect can be exploited in offline application but also, is especially attractive, for real-time BCI and NF applications.
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40
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Krishnamurthy R, Wang DJJ, Cervantes B, McAllister A, Nelson E, Karampinos DC, Hu HH. Recent Advances in Pediatric Brain, Spine, and Neuromuscular Magnetic Resonance Imaging Techniques. Pediatr Neurol 2019; 96:7-23. [PMID: 31023603 DOI: 10.1016/j.pediatrneurol.2019.03.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2018] [Revised: 02/25/2019] [Accepted: 03/03/2019] [Indexed: 12/21/2022]
Abstract
Magnetic resonance imaging (MRI) is a powerful radiologic tool with the ability to generate a variety of proton-based signal contrast from tissues. Owing to this immense flexibility in signal generation, new MRI techniques are constantly being developed, tested, and optimized for clinical utility. In addition, the safe and nonionizing nature of MRI makes it a suitable modality for imaging in children. In this review article, we summarize a few of the most popular advances in MRI techniques in recent years. In particular, we highlight how these new developments have affected brain, spine, and neuromuscular imaging and focus on their applications in pediatric patients. In the first part of the review, we discuss new approaches such as multiphase and multidelay arterial spin labeling for quantitative perfusion and angiography of the brain, amide proton transfer MRI of the brain, MRI of brachial plexus and lumbar plexus nerves (i.e., neurography), and T2 mapping and fat characterization in neuromuscular diseases. In the second part of the review, we focus on describing new data acquisition strategies in accelerated MRI aimed collectively at reducing the scan time, including simultaneous multislice imaging, compressed sensing, synthetic MRI, and magnetic resonance fingerprinting. In discussing the aforementioned, the review also summarizes the advantages and disadvantages of each method and their current state of commercial availability from MRI vendors.
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Affiliation(s)
| | - Danny J J Wang
- Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Barbara Cervantes
- Department of Diagnostic and Interventional Radiology, Technische Universität München, Munich, Germany
| | | | - Eric Nelson
- Center for Biobehavioral Health, Nationwide Children's Hospital, Columbus, Ohio
| | - Dimitrios C Karampinos
- Department of Diagnostic and Interventional Radiology, Technische Universität München, Munich, Germany
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41
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Georgiopoulos C, Witt ST, Haller S, Dizdar N, Zachrisson H, Engström M, Larsson EM. Olfactory fMRI: Implications of Stimulation Length and Repetition Time. Chem Senses 2019; 43:389-398. [PMID: 29726890 DOI: 10.1093/chemse/bjy025] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Studying olfaction with functional magnetic resonance imaging (fMRI) poses various methodological challenges. This study aimed to investigate the effects of stimulation length and repetition time (TR) on the activation pattern of 4 olfactory brain regions: the anterior and the posterior piriform cortex, the orbitofrontal cortex, and the insula. Twenty-two healthy participants with normal olfaction were examined with fMRI, with 2 stimulation lengths (6 s and 15 s) and 2 TRs (0.901 s and 1.34 s). Data were analyzed using General Linear Model (GLM), Tensorial Independent Component Analysis (TICA), and by plotting the event-related time course of brain activation in the 4 olfactory regions of interest. The statistical analysis of the time courses revealed that short TR was associated with more pronounced signal increase and short stimulation was associated with shorter time to peak signal. Additionally, both long stimulation and short TR were associated with oscillatory time courses, whereas both short stimulation and short TR resulted in more typical time courses. GLM analysis showed that the combination of short stimulation and short TR could result in visually larger activation within these olfactory areas. TICA validated that the tested paradigm was spatially and temporally associated with a functionally connected network that included all 4 olfactory regions. In conclusion, the combination of short stimulation and short TR is associated with higher signal increase and shorter time to peak, making it more amenable to standard GLM-type analyses than long stimulation and long TR, and it should, thus, be preferable for olfactory fMRI.
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Affiliation(s)
- Charalampos Georgiopoulos
- Department of Radiology and Department of Medical and Health Sciences, Linköping University, Röntgenkliniken, Universitetssjukhuset, Linköping, Sweden.,Center for Medical Image Science and Visualization (CMIV), Linköping University, University Hospital, Linköping, Sweden
| | - Suzanne T Witt
- Center for Medical Image Science and Visualization (CMIV), Linköping University, University Hospital, Linköping, Sweden
| | - Sven Haller
- Affidea CDRC Centre de Diagnostic Radiologique de Carouge SA, clos de la Fonderie, Geneva, Switzerland.,Department of Surgical Sciences/Radiology, Uppsala University, Akademiska sjukhuset Uppsala, Sweden
| | - Nil Dizdar
- Department of Neurology and Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden
| | - Helene Zachrisson
- Department of Clinical Physiology and Department of Medical and Health Sciences, Linköping University, Linköping, Sweden
| | - Maria Engström
- Center for Medical Image Science and Visualization (CMIV), Linköping University, University Hospital, Linköping, Sweden.,Department of Medical and Health Sciences, Linköping University, Sandbäcksgatan, Linköping, Sweden
| | - Elna-Marie Larsson
- Department of Surgical Sciences/Radiology, Uppsala University, Akademiska sjukhuset Uppsala, Sweden
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42
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Hoinkiss DC, Erhard P, Breutigam NJ, von Samson-Himmelstjerna F, Günther M, Porter DA. Prospective motion correction in functional MRI using simultaneous multislice imaging and multislice-to-volume image registration. Neuroimage 2019; 200:159-173. [PMID: 31226496 DOI: 10.1016/j.neuroimage.2019.06.042] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Revised: 06/14/2019] [Accepted: 06/18/2019] [Indexed: 10/26/2022] Open
Abstract
The sensitivity to subject motion is one of the major challenges in functional MRI (fMRI) studies in which a precise alignment of images from different time points is required to allow reliable quantification of brain activation throughout the scan. Especially the long measurement times and laborious fMRI tasks add to the amount of subject motion found in typical fMRI measurements, even when head restraints are used. In case of moving subjects, prospective motion correction can maintain the relationship between spatial image information and subject anatomy by constantly adapting the image slice positioning to follow the subject in real time. Image-based prospective motion correction is well-established in fMRI studies and typically computes the motion estimates based on a volume-to-volume image registration, resulting in low temporal resolution. This study combines fMRI using simultaneous multislice imaging with multislice-to-volume-based image registration to allow sub-TR motion detection with subsequent real-time adaption of the imaging system. Simultaneous multislice imaging is widely used in fMRI studies and, together with multislice-to-volume-based image registration algorithms, enables computing suitable motion states after only a single readout by registering the simultaneously excited slices to a reference volume acquired at the start of the measurement. The technique is evaluated in three human BOLD fMRI studies (n = 1, 5, and 1) to explore different aspects of the method. It is compared to conventional, volume-to-volume-based prospective motion correction as well as retrospective motion correction methods. Results show a strong reduction in retrospectively computed residual motion parameters of up to 50% when comparing the two prospective motion correction techniques. An analysis of temporal signal-to-noise ratio as well as brain activation results shows high consistency between the results before and after additional retrospective motion correction when using the proposed technique, indicating successful prospective motion correction. The comparison of absolute tSNR values does not show an improvement compared to using retrospective motion correction alone. However, the improved temporal resolution may provide improved tSNR in the presence of more exaggerated intra-volume motion.
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Affiliation(s)
| | - Peter Erhard
- Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany; University of Bremen, Bremen, Germany
| | | | | | - Matthias Günther
- Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany; University of Bremen, Bremen, Germany
| | - David Andrew Porter
- Imaging Centre of Excellence, College of Medical, Veterinary & Life Sciences, University of Glasgow, Glasgow, Scotland, UK
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43
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Cohen AD, Wang Y. Improving the Assessment of Breath-Holding Induced Cerebral Vascular Reactivity Using a Multiband Multi-echo ASL/BOLD Sequence. Sci Rep 2019; 9:5079. [PMID: 30911056 PMCID: PMC6434035 DOI: 10.1038/s41598-019-41199-w] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2018] [Accepted: 02/28/2019] [Indexed: 01/18/2023] Open
Abstract
Breath holding (BH) is a viable vasodilatory stimulus for calculating functional MRI-derived cerebral vascular reactivity (CVR). The BH technique suffers from reduced repeatability compared with gas inhalation techniques; however, extra equipment is needed to perform gas inhalation techniques, and this equipment is not available at all institutions. This study aimed to determine the sensitivity and repeatability of BH activation and CVR using a multiband multi-echo simultaneous arterial spin labelling/blood oxygenation level dependent (ASL/BOLD) sequence. Whole-brain images were acquired in 14 volunteers. Ten subjects returned for repeat imaging. Each subject performed four cycles of 16 s BH on expiration interleaved with paced breathing. Following standard preprocessing, the echoes were combined using a T2*-weighted approach. BOLD and ASL BH activation was computed, and CVR was then determined as the percent signal change related to the activation. The "M" parameter from the Davis Model was also computed by incorporating the ASL signal. Our results showed higher BH activation strength, volume, and repeatability for the combined multi-echo (MEC) data compared with the single-echo data. MEC CVR also had higher repeatability, sensitivity, specificity, and reliability compared with the single-echo BOLD data. These data support the usefulness of an MBME ASL/BOLD acquisition for BH CVR and M measurements.
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Affiliation(s)
- Alexander D Cohen
- Medical College of Wisconsin, Department of Radiology, Milwaukee, WI, USA.
| | - Yang Wang
- Medical College of Wisconsin, Department of Radiology, Milwaukee, WI, USA.
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44
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Lee HL, Li Z, Coulson EJ, Chuang KH. Ultrafast fMRI of the rodent brain using simultaneous multi-slice EPI. Neuroimage 2019; 195:48-58. [PMID: 30910726 DOI: 10.1016/j.neuroimage.2019.03.045] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2018] [Revised: 03/05/2019] [Accepted: 03/19/2019] [Indexed: 12/25/2022] Open
Abstract
Increasing spatial and temporal resolutions of functional MRI (fMRI) measurement has been shown to benefit the study of neural dynamics and functional interaction. However, acceleration of rodent brain fMRI using parallel and simultaneous multi-slice imaging techniques is hampered by the lack of high-density phased-array coils for the small brain. To overcome this limitation, we adapted phase-offset multiplanar and blipped-controlled aliasing echo planar imaging (EPI) to enable simultaneous multi-slice fMRI of the mouse brain using a single loop coil on a 9.4T scanner. Four slice bands of 0.3 × 0.3 × 0.5 mm3 resolution can be simultaneously acquired to cover the whole brain at a temporal resolution of 300 ms or the whole cerebrum in 150 ms. Instead of losing signal-to-noise ratio (SNR), both spatial and temporal SNR can be increased due to the increased k-space sampling compared to a standard single-band EPI. Task fMRI using a visual stimulation shows close to 80% increase of z-score and 4 times increase of activated area in the visual cortex using the multiband EPI due to the highly increased temporal samples. Resting-state fMRI shows reliable detection of bilateral connectivity by both single-band and multiband EPI, but no significant difference was found. Without the need of a dedicated hardware, we have demonstrated a practical method that can enable unparallelly fast whole-brain fMRI for preclinical studies. This technique can be used to increase sensitivity, distinguish transient response or acquire high spatiotemporal resolution fMRI.
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Affiliation(s)
- Hsu-Lei Lee
- Queensland Brain Institute, The University of Queensland, Brisbane, Australia; Centre of Advanced Imaging, The University of Queensland, Brisbane, Australia
| | - Zengmin Li
- Queensland Brain Institute, The University of Queensland, Brisbane, Australia
| | - Elizabeth J Coulson
- Queensland Brain Institute, The University of Queensland, Brisbane, Australia; School of Biomedical Sciences, The University of Queensland, Brisbane, Australia
| | - Kai-Hsiang Chuang
- Queensland Brain Institute, The University of Queensland, Brisbane, Australia; Centre of Advanced Imaging, The University of Queensland, Brisbane, Australia.
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45
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Chen JE, Polimeni JR, Bollmann S, Glover GH. On the analysis of rapidly sampled fMRI data. Neuroimage 2019; 188:807-820. [PMID: 30735828 PMCID: PMC6984348 DOI: 10.1016/j.neuroimage.2019.02.008] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2018] [Revised: 01/11/2019] [Accepted: 02/04/2019] [Indexed: 02/08/2023] Open
Abstract
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 motivated by the altered spectral distribution and noise characteristics at short sampling intervals, while the second question seeks to reconcile the complicated trade-offs between the functional contrast-to-noise ratio and the effective degrees of freedom. Although there have been recent efforts to empirically approach different aspects of these two questions, in this work we discuss, from a theoretical perspective accompanied by some illustrative, proof-of-concept experimental in vivo human fMRI data, a few considerations that are rarely mentioned, yet are important for both preprocessing and optimizing statistical inferences for studies that employ acquisitions with sub-second sampling intervals. Several summary recommendations include concerns regarding advisability of relying on low-pass filtering to de-noise physiological contributions, employment of statistical models with sufficient complexity to account for the substantially increased serial correlation, and cautions regarding using rapid sampling to enhance functional sensitivity given that different analysis models may associate with distinct trade-offs between contrast-to-noise ratios and the effective degrees of freedom. As an example, we demonstrate that as TR shortens, the intrinsic differences in how noise is accommodated in general linear models and Pearson correlation analyses (assuming Gaussian distributed stochastic signals and noise) can result in quite different outcomes, either gaining or losing statistical power.
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Affiliation(s)
- Jingyuan E Chen
- Department of Radiology, Stanford University, Stanford, CA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA.
| | - Jonathan R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA; Harvard-Massachusetts Institute of Technology Division of Health Sciences and Technology, Cambridge, MA, USA
| | - Saskia Bollmann
- Centre for Advanced Imaging, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Gary H Glover
- Department of Radiology, Stanford University, Stanford, CA, USA
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46
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Abbas A, Belloy M, Kashyap A, Billings J, Nezafati M, Schumacher EH, Keilholz S. Quasi-periodic patterns contribute to functional connectivity in the brain. Neuroimage 2019; 191:193-204. [PMID: 30753928 DOI: 10.1016/j.neuroimage.2019.01.076] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2018] [Revised: 01/07/2019] [Accepted: 01/30/2019] [Indexed: 02/03/2023] Open
Abstract
Functional connectivity is widely used to study the coordination of activity between brain regions over time. Functional connectivity in the default mode and task positive networks is particularly important for normal brain function. However, the processes that give rise to functional connectivity in the brain are not fully understood. It has been postulated that low-frequency neural activity plays a key role in establishing the functional architecture of the brain. Quasi-periodic patterns (QPPs) are a reliably observable form of low-frequency neural activity that involve the default mode and task positive networks. Here, QPPs from resting-state and working memory task-performing individuals were acquired. The spatiotemporal pattern, strength, and frequency of the QPPs between the two groups were compared and the contribution of QPPs to functional connectivity in the brain was measured. In task-performing individuals, the spatiotemporal pattern of the QPP changes, particularly in task-relevant regions, and the QPP tends to occur with greater strength and frequency. Differences in the QPPs between the two groups could partially account for the variance in functional connectivity between resting-state and task-performing individuals. The QPPs contribute strongly to connectivity in the default mode and task positive networks and to the strength of anti-correlation seen between the two networks. Many of the connections affected by QPPs are also disrupted during several neurological disorders. These findings contribute to understanding the dynamic neural processes that give rise to functional connectivity in the brain and how they may be disrupted during disease.
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Affiliation(s)
- Anzar Abbas
- Neuroscience, Emory University, 1760 Haygood Dr NE Suite W-200, Atlanta, GA, 30322, USA
| | - Michaël Belloy
- Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1, 2610, Wilrijk, Antwerp, Belgium
| | - Amrit Kashyap
- Biomedical Engineering, Emory University and Georgia Institute of Technology, 1760, Haygood Dr NE Suite, W-200, Atlanta, GA, 30322, USA
| | - Jacob Billings
- Neuroscience, Emory University, 1760 Haygood Dr NE Suite W-200, Atlanta, GA, 30322, USA
| | - Maysam Nezafati
- Biomedical Engineering, Emory University and Georgia Institute of Technology, 1760, Haygood Dr NE Suite, W-200, Atlanta, GA, 30322, USA
| | - Eric H Schumacher
- School of Psychology, Georgia Institute of Technology, 654 Cherry Street, Atlanta, GA 30332, USA
| | - Shella Keilholz
- Neuroscience, Emory University, 1760 Haygood Dr NE Suite W-200, Atlanta, GA, 30322, USA; Biomedical Engineering, Emory University and Georgia Institute of Technology, 1760, Haygood Dr NE Suite, W-200, Atlanta, GA, 30322, USA.
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47
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Jahanian H, Holdsworth S, Christen T, Wu H, Zhu K, Kerr AB, Middione MJ, Dougherty RF, Moseley M, Zaharchuk G. Advantages of short repetition time resting-state functional MRI enabled by simultaneous multi-slice imaging. J Neurosci Methods 2019; 311:122-132. [DOI: 10.1016/j.jneumeth.2018.09.033] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2018] [Revised: 09/17/2018] [Accepted: 09/28/2018] [Indexed: 01/15/2023]
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48
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Cole MW, Ito T, Schultz D, Mill R, Chen R, Cocuzza C. Task activations produce spurious but systematic inflation of task functional connectivity estimates. Neuroimage 2018; 189:1-18. [PMID: 30597260 DOI: 10.1016/j.neuroimage.2018.12.054] [Citation(s) in RCA: 114] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2018] [Revised: 12/12/2018] [Accepted: 12/26/2018] [Indexed: 01/21/2023] Open
Abstract
Most neuroscientific studies have focused on task-evoked activations (activity amplitudes at specific brain locations), providing limited insight into the functional relationships between separate brain locations. Task-state functional connectivity (FC) - statistical association between brain activity time series during task performance - moves beyond task-evoked activations by quantifying functional interactions during tasks. However, many task-state FC studies do not remove the first-order effect of task-evoked activations prior to estimating task-state FC. It has been argued that this results in the ambiguous inference "likely active or interacting during the task", rather than the intended inference "likely interacting during the task". Utilizing a neural mass computational model, we verified that task-evoked activations substantially and inappropriately inflate task-state FC estimates, especially in functional MRI (fMRI) data. Various methods attempting to address this problem have been developed, yet the efficacies of these approaches have not been systematically assessed. We found that most standard approaches for fitting and removing mean task-evoked activations were unable to correct these inflated correlations. In contrast, methods that flexibly fit mean task-evoked response shapes effectively corrected the inflated correlations without reducing effects of interest. Results with empirical fMRI data confirmed the model's predictions, revealing activation-induced task-state FC inflation for both Pearson correlation and psychophysiological interaction (PPI) approaches. These results demonstrate that removal of mean task-evoked activations using an approach that flexibly models task-evoked response shape is an important preprocessing step for valid estimation of task-state FC.
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Affiliation(s)
- Michael W Cole
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, 07102, USA.
| | - Takuya Ito
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, 07102, USA; Behavioral and Neural Sciences PhD Program, Rutgers University, Newark, NJ, 07102, USA
| | - Douglas Schultz
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, 07102, USA
| | - Ravi Mill
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, 07102, USA
| | - Richard Chen
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, 07102, USA; Behavioral and Neural Sciences PhD Program, Rutgers University, Newark, NJ, 07102, USA
| | - Carrisa Cocuzza
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, 07102, USA; Behavioral and Neural Sciences PhD Program, Rutgers University, Newark, NJ, 07102, USA
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49
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Pais-Roldán P, Biswal B, Scheffler K, Yu X. Identifying Respiration-Related Aliasing Artifacts in the Rodent Resting-State fMRI. Front Neurosci 2018; 12:788. [PMID: 30455623 PMCID: PMC6230988 DOI: 10.3389/fnins.2018.00788] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2018] [Accepted: 10/12/2018] [Indexed: 12/31/2022] Open
Abstract
Resting-state functional magnetic resonance imaging (rs-fMRI) combined with optogenetics and electrophysiological/calcium recordings in animal models is becoming a popular platform to investigate brain dynamics under specific neurological states. Physiological noise originating from the cardiac and respiration signal is the dominant interference in human rs-fMRI and extensive efforts have been made to reduce these artifacts from the human data. In animal fMRI studies, physiological noise sources including the respiratory and cardiorespiratory artifacts to the rs-fMRI signal fluctuation have typically been less investigated. In this article, we demonstrate evidence of aliasing effects into the low-frequency rs-fMRI signal fluctuation mainly due to respiration-induced B0 offsets in anesthetized rats. This aliased signal was examined by systematically altering the fMRI sampling rate, i.e., the time of repetition (TR), in free-breathing conditions and by adjusting the rate of ventilation. Anesthetized rats under ventilation showed a significantly narrower frequency bandwidth of the aliasing effect than free-breathing animals. It was found that the aliasing effect could be further reduced in ventilated animals with a muscle relaxant. This work elucidates the respiration-related aliasing effects on the rs-fMRI signal fluctuation from anesthetized rats, indicating non-negligible physiological noise needed to be taken care of in both awake and anesthetized animal rs-fMRI studies.
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Affiliation(s)
- Patricia Pais-Roldán
- High-Field Magnetic Resonance Department, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany.,Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Bharat Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, United States
| | - Klaus Scheffler
- High-Field Magnetic Resonance Department, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany.,Department for Biomedical Magnetic Resonance, University of Tuebingen, Tuebingen, Germany
| | - Xin Yu
- High-Field Magnetic Resonance Department, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States
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50
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Luo Y, Zhang J, Chen L, Cai S, Cai C. Accelerating multi-slice spatiotemporally encoded MRI with simultaneous echo refocusing. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2018; 296:12-22. [PMID: 30195714 DOI: 10.1016/j.jmr.2018.08.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/13/2018] [Revised: 07/25/2018] [Accepted: 08/30/2018] [Indexed: 06/08/2023]
Abstract
Single-shot spatiotemporally encoded (SPEN) ultrafast magnetic resonance imaging (MRI) is of great value to both scientific research and clinical application owing to its capability for delivering MR images with greater robustness to magnetic field inhomogeneity and chemical-shift displacement effects than conventional methods like EPI due to high effective phase-encoded bandwidth. Many SPEN MRI methods have been developed, among which multi-slice SPEN MRI arises as a promising supplement to ultrafast multi-slice sampling. In this work, we propose a new multi-slice SPEN MRI method, termed multi-echo segmented SPEN (ME-SeSPEN) method, which produces multiple images within a single train of echoes and successively samples widely separated slices. The resulting images were reconstructed using de-convolution super-resolved algorithm. The robustness and efficiency of the proposed method were demonstrated by phantom, lemon and in vivo experiments in comparison with spin-echo EPI, spin-echo simultaneous echo refocusing (SER), and segmented SPEN (SeSPEN) MRI. The results indicate that the new method effectively shortens the sampling time (20% reduction practically in comparison with SeSPEN when two slices are simultaneously sampled). ME-SeSPEN also reduces eddy current effects while maintaining the benefits of SPEN MRI, such as similar robustness to field inhomogeneity, spatial resolution and signal-to-noise ratio to SeSPEN MRI. The new method will promote the versatility of multi-slice MRI in practical applications.
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Affiliation(s)
- Yao Luo
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
| | - Jun Zhang
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
| | - Lin Chen
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
| | - Shuhui Cai
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China.
| | - Congbo Cai
- Department of Communication Engineering, Xiamen University, Xiamen 361005, China.
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