1
|
Zweerings J, Sarasjärvi K, Mathiak KA, Iglesias-Fuster J, Cong F, Zvyagintsev M, Mathiak K. Data-Driven Approach to the Analysis of Real-Time FMRI Neurofeedback Data: Disorder-Specific Brain Synchrony in PTSD. Int J Neural Syst 2021; 31:2150043. [PMID: 34551675 DOI: 10.1142/s012906572150043x] [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] [Indexed: 12/13/2022]
Abstract
Brain-computer interfaces (BCIs) can be used in real-time fMRI neurofeedback (rtfMRI NF) investigations to provide feedback on brain activity to enable voluntary regulation of the blood-oxygen-level dependent (BOLD) signal from localized brain regions. However, the temporal pattern of successful self-regulation is dynamic and complex. In particular, the general linear model (GLM) assumes fixed temporal model functions and misses other dynamics. We propose a novel data-driven analyses approach for rtfMRI NF using intersubject covariance (ISC) analysis. The potential of ISC was examined in a reanalysis of data from 21 healthy individuals and nine patients with post-traumatic stress-disorder (PTSD) performing up-regulation of the anterior cingulate cortex (ACC). ISC in the PTSD group differed from healthy controls in a network including the right inferior frontal gyrus (IFG). In both cohorts, ISC decreased throughout the experiment indicating the development of individual regulation strategies. ISC analyses are a promising approach to reveal novel information on the mechanisms involved in voluntary self-regulation of brain signals and thus extend the results from GLM-based methods. ISC enables a novel set of research questions that can guide future neurofeedback and neuroimaging investigations.
Collapse
Affiliation(s)
- Jana Zweerings
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen, Aachen Germany.,JARA-Brain, Research Center Jülich, Jülich, Germany
| | - Kiira Sarasjärvi
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen, Aachen Germany.,Department of Digital Humanities, University of Helsinki, Helsinki, Finland
| | - Krystyna Anna Mathiak
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen, Aachen Germany.,JARA-Brain, Research Center Jülich, Jülich, Germany
| | | | - Fengyu Cong
- School of Biomedical Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, 116024 Dalian, P. R. China.,Faculty of Information Technology, University of Jyväskylä, 40014 Jyväskylä, Finland.,School of Artificial Intelligence, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, 116024 Dalian, P. R. China.,Key Laboratory of Integrated Circuit and Biomedical Electronic System, Liaoning Province, Dalian University of Technology, 116024 Dalian, P. R. China
| | - Mikhail Zvyagintsev
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen, Aachen Germany.,JARA-Brain, Research Center Jülich, Jülich, Germany
| | - Klaus Mathiak
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen, Aachen Germany.,JARA-Brain, Research Center Jülich, Jülich, Germany
| |
Collapse
|
2
|
Lynch CJ, Power JD, Scult MA, Dubin M, Gunning FM, Liston C. Rapid Precision Functional Mapping of Individuals Using Multi-Echo fMRI. Cell Rep 2020; 33:108540. [PMID: 33357444 PMCID: PMC7792478 DOI: 10.1016/j.celrep.2020.108540] [Citation(s) in RCA: 76] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Revised: 10/15/2020] [Accepted: 11/25/2020] [Indexed: 12/20/2022] Open
Abstract
Resting-state functional magnetic resonance imaging (fMRI) is widely used in cognitive and clinical neuroscience, but long-duration scans are currently needed to reliably characterize individual differences in functional connectivity (FC) and brain network topology. In this report, we demonstrate that multi-echo fMRI can improve the reliability of FC-based measurements. In four densely sampled individual humans, just 10 min of multi-echo data yielded better test-retest reliability than 30 min of single-echo data in independent datasets. This effect is pronounced in clinically important brain regions, including the subgenual cingulate, basal ganglia, and cerebellum, and is linked to three biophysical signal mechanisms (thermal noise, regional variability in the rate of T2* decay, and S0-dependent artifacts) with spatially distinct influences. Together, these findings establish the potential utility of multi-echo fMRI for rapid precision mapping using experimentally and clinically tractable scan times and will facilitate longitudinal neuroimaging of clinical populations. Lynch et al. demonstrate that the test-retest reliability of resting-state connectivity measurements can be improved using multi-echo fMRI. This effect is pronounced in clinically important brain regions and could help facilitate precision mapping of functional brain networks in healthy people and patient populations.
Collapse
Affiliation(s)
- Charles J Lynch
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10021, USA.
| | - Jonathan D Power
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10021, USA
| | - Matthew A Scult
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10021, USA
| | - Marc Dubin
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10021, USA
| | - Faith M Gunning
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10021, USA
| | - Conor Liston
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10021, USA.
| |
Collapse
|
3
|
Barreiros AR, Almeida I, Baía BC, Castelo-Branco M. Amygdala Modulation During Emotion Regulation Training With fMRI-Based Neurofeedback. Front Hum Neurosci 2019; 13:89. [PMID: 30971906 PMCID: PMC6444080 DOI: 10.3389/fnhum.2019.00089] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2018] [Accepted: 02/25/2019] [Indexed: 11/25/2022] Open
Abstract
Available evidence suggests that individuals can enhance their ability to modulate brain activity in target regions, within the Emotion Regulation network, using fMRI-based neurofeedback. However, there is no systematic review that investigates the effectiveness of this method on amygdala modulation, a core region within this network. The major goal of this study was to systematically review and analyze the effects of real-time fMRI-Neurofeedback concerning the neuromodulation of the amygdala during Emotion Regulation training. A search was performed in PubMed, Science Direct, and Web of Science with the following key terms: ≪(“neurofeedback” or “neuro feedback” or “neuro-feedback”) and (“emotion regulation”) and (fMRI OR “functional magnetic resonance”),≫ and afterwards two additional searches were performed, replacing the term “emotion regulation” for “amygdala” and “neurofeedback” for “feedback.” Of the 531 identified articles, only 19 articles reported results of amygdala modulation during Emotional Regulation training through rtfMRI-NF, using healthy participants or patients, in original research articles. The results, systematically reviewed here, provide evidence for amygdala's modulation during rtfMRI-NF training, although studies' heterogeneity precluded a quantitative meta-analysis—the included studies relied on different outcome measures to infer the success of neurofeedback intervention. Thus, a qualitative analysis was done instead. We identified critical features influencing inference on the quality of the intervention as: the inclusion of a Practice Run, a Transfer Run and a Control Group in the protocol, and to choose adequate Emotion Regulation strategies—in particular, the effective recall of autobiographic memories. Surprisingly, the Regulated vs. Control Condition was lacking in most of the studies, precluding valid inference of amygdala neuromodulation within Session. The best controlled studies nevertheless showed positive effects. The type of stimulus/interface did not seem critical for amygdala modulation. We also identified potential effects of lateralization of amygdala responses following Up- or Down-Regulation, and the impact of fMRI parameters for data acquisition and analysis. Despite qualitative evidence for amygdala modulation during rtfMRI-NF, there are still important limitations in the design of a clear conceptual framework of NF-training research. Future studies should focus on more homogeneous guidelines concerning design, protocol structure and, particularly, harmonized outcome measures to provide quantitative estimates of neuromodulatory effects in the amygdala.
Collapse
Affiliation(s)
- Ana Rita Barreiros
- CIBIT, ICNAS-Institute of Nuclear Sciences Applied to Health-and CNC.IBILI-Faculty of Medicine, Coimbra Institute for Biomedical Imaging and Translational Research, University of Coimbra, Azinhaga de Santa Comba, Coimbra, Portugal
| | - Inês Almeida
- CIBIT, ICNAS-Institute of Nuclear Sciences Applied to Health-and CNC.IBILI-Faculty of Medicine, Coimbra Institute for Biomedical Imaging and Translational Research, University of Coimbra, Azinhaga de Santa Comba, Coimbra, Portugal
| | - Bárbara Correia Baía
- CIBIT, ICNAS-Institute of Nuclear Sciences Applied to Health-and CNC.IBILI-Faculty of Medicine, Coimbra Institute for Biomedical Imaging and Translational Research, University of Coimbra, Azinhaga de Santa Comba, Coimbra, Portugal
| | - Miguel Castelo-Branco
- CIBIT, ICNAS-Institute of Nuclear Sciences Applied to Health-and CNC.IBILI-Faculty of Medicine, Coimbra Institute for Biomedical Imaging and Translational Research, University of Coimbra, Azinhaga de Santa Comba, Coimbra, Portugal
| |
Collapse
|
4
|
Wolf D, Mittelberg I, Rekittke LM, Bhavsar S, Zvyagintsev M, Haeck A, Cong F, Klasen M, Mathiak K. Interpretation of Social Interactions: Functional Imaging of Cognitive-Semiotic Categories During Naturalistic Viewing. Front Hum Neurosci 2018; 12:296. [PMID: 30154703 PMCID: PMC6102316 DOI: 10.3389/fnhum.2018.00296] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2018] [Accepted: 07/06/2018] [Indexed: 01/01/2023] Open
Abstract
Social interactions arise from patterns of communicative signs, whose perception and interpretation require a multitude of cognitive functions. The semiotic framework of Peirce's Universal Categories (UCs) laid ground for a novel cognitive-semiotic typology of social interactions. During functional magnetic resonance imaging (fMRI), 16 volunteers watched a movie narrative encompassing verbal and non-verbal social interactions. Three types of non-verbal interactions were coded ("unresolved," "non-habitual," and "habitual") based on a typology reflecting Peirce's UCs. As expected, the auditory cortex responded to verbal interactions, but non-verbal interactions modulated temporal areas as well. Conceivably, when speech was lacking, ambiguous visual information (unresolved interactions) primed auditory processing in contrast to learned behavioral patterns (habitual interactions). The latter recruited a parahippocampal-occipital network supporting conceptual processing and associative memory retrieval. Requesting semiotic contextualization, non-habitual interactions activated visuo-spatial and contextual rule-learning areas such as the temporo-parietal junction and right lateral prefrontal cortex. In summary, the cognitive-semiotic typology reflected distinct sensory and association networks underlying the interpretation of observed non-verbal social interactions.
Collapse
Affiliation(s)
- Dhana Wolf
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen University, Aachen, Germany.,Natural Media Lab, Human Technology Centre (HumTec), RWTH Aachen University, Aachen, Germany
| | - Irene Mittelberg
- Natural Media Lab, Human Technology Centre (HumTec), RWTH Aachen University, Aachen, Germany.,Center for Sign Language and Gesture (SignGes), RWTH Aachen University, Aachen, Germany
| | - Linn-Marlen Rekittke
- Natural Media Lab, Human Technology Centre (HumTec), RWTH Aachen University, Aachen, Germany.,Center for Sign Language and Gesture (SignGes), RWTH Aachen University, Aachen, Germany
| | - Saurabh Bhavsar
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen University, Aachen, Germany
| | - Mikhail Zvyagintsev
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen University, Aachen, Germany.,Brain Imaging Facility, Interdisciplinary Centre for Clinical Studies (IZKF), Medical Faculty, RWTH Aachen University, Aachen, Germany
| | - Annina Haeck
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen University, Aachen, Germany
| | - Fengyu Cong
- Department of Biomedical Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China
| | - Martin Klasen
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen University, Aachen, Germany
| | - Klaus Mathiak
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen University, Aachen, Germany.,Center for Sign Language and Gesture (SignGes), RWTH Aachen University, Aachen, Germany.,JARA-Translational Brain Medicine, Aachen, Germany
| |
Collapse
|
5
|
Wolf D, Rekittke LM, Mittelberg I, Klasen M, Mathiak K. Perceived Conventionality in Co-speech Gestures Involves the Fronto-Temporal Language Network. Front Hum Neurosci 2017; 11:573. [PMID: 29249945 PMCID: PMC5714878 DOI: 10.3389/fnhum.2017.00573] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2017] [Accepted: 11/13/2017] [Indexed: 11/16/2022] Open
Abstract
Face-to-face communication is multimodal; it encompasses spoken words, facial expressions, gaze, and co-speech gestures. In contrast to linguistic symbols (e.g., spoken words or signs in sign language) relying on mostly explicit conventions, gestures vary in their degree of conventionality. Bodily signs may have a general accepted or conventionalized meaning (e.g., a head shake) or less so (e.g., self-grooming). We hypothesized that subjective perception of conventionality in co-speech gestures relies on the classical language network, i.e., the left hemispheric inferior frontal gyrus (IFG, Broca's area) and the posterior superior temporal gyrus (pSTG, Wernicke's area) and studied 36 subjects watching video-recorded story retellings during a behavioral and an functional magnetic resonance imaging (fMRI) experiment. It is well documented that neural correlates of such naturalistic videos emerge as intersubject covariance (ISC) in fMRI even without involving a stimulus (model-free analysis). The subjects attended either to perceived conventionality or to a control condition (any hand movements or gesture-speech relations). Such tasks modulate ISC in contributing neural structures and thus we studied ISC changes to task demands in language networks. Indeed, the conventionality task significantly increased covariance of the button press time series and neuronal synchronization in the left IFG over the comparison with other tasks. In the left IFG, synchronous activity was observed during the conventionality task only. In contrast, the left pSTG exhibited correlated activation patterns during all conditions with an increase in the conventionality task at the trend level only. Conceivably, the left IFG can be considered a core region for the processing of perceived conventionality in co-speech gestures similar to spoken language. In general, the interpretation of conventionalized signs may rely on neural mechanisms that engage during language comprehension.
Collapse
Affiliation(s)
- Dhana Wolf
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen, Aachen, Germany.,Natural Media Lab, Human Technology Centre, RWTH Aachen, Aachen, Germany.,Center for Sign Language and Gesture (SignGes), RWTH Aachen, Aachen, Germany
| | - Linn-Marlen Rekittke
- Natural Media Lab, Human Technology Centre, RWTH Aachen, Aachen, Germany.,Center for Sign Language and Gesture (SignGes), RWTH Aachen, Aachen, Germany
| | - Irene Mittelberg
- Natural Media Lab, Human Technology Centre, RWTH Aachen, Aachen, Germany.,Center for Sign Language and Gesture (SignGes), RWTH Aachen, Aachen, Germany
| | - Martin Klasen
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen, Aachen, Germany.,JARA-Translational Brain Medicine, RWTH Aachen, Aachen, Germany
| | - Klaus Mathiak
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen, Aachen, Germany.,Center for Sign Language and Gesture (SignGes), RWTH Aachen, Aachen, Germany.,JARA-Translational Brain Medicine, RWTH Aachen, Aachen, Germany
| |
Collapse
|
6
|
Hamilton J, Franson D, Seiberlich N. Recent advances in parallel imaging for MRI. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2017; 101:71-95. [PMID: 28844222 PMCID: PMC5927614 DOI: 10.1016/j.pnmrs.2017.04.002] [Citation(s) in RCA: 106] [Impact Index Per Article: 15.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2017] [Revised: 04/09/2017] [Accepted: 04/17/2017] [Indexed: 05/22/2023]
Abstract
Magnetic Resonance Imaging (MRI) is an essential technology in modern medicine. However, one of its main drawbacks is the long scan time needed to localize the MR signal in space to generate an image. This review article summarizes some basic principles and recent developments in parallel imaging, a class of image reconstruction techniques for shortening scan time. First, the fundamentals of MRI data acquisition are covered, including the concepts of k-space, undersampling, and aliasing. It is demonstrated that scan time can be reduced by sampling a smaller number of phase encoding lines in k-space; however, without further processing, the resulting images will be degraded by aliasing artifacts. Nearly all modern clinical scanners acquire data from multiple independent receiver coil arrays. Parallel imaging methods exploit properties of these coil arrays to separate aliased pixels in the image domain or to estimate missing k-space data using knowledge of nearby acquired k-space points. Three parallel imaging methods-SENSE, GRAPPA, and SPIRiT-are described in detail, since they are employed clinically and form the foundation for more advanced methods. These techniques can be extended to non-Cartesian sampling patterns, where the collected k-space points do not fall on a rectangular grid. Non-Cartesian acquisitions have several beneficial properties, the most important being the appearance of incoherent aliasing artifacts. Recent advances in simultaneous multi-slice imaging are presented next, which use parallel imaging to disentangle images of several slices that have been acquired at once. Parallel imaging can also be employed to accelerate 3D MRI, in which a contiguous volume is scanned rather than sequential slices. Another class of phase-constrained parallel imaging methods takes advantage of both image magnitude and phase to achieve better reconstruction performance. Finally, some applications are presented of parallel imaging being used to accelerate MR Spectroscopic Imaging.
Collapse
Affiliation(s)
- Jesse Hamilton
- Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
| | - Dominique Franson
- Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
| | - Nicole Seiberlich
- Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA; Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA.
| |
Collapse
|
7
|
Caballero-Gaudes C, Reynolds RC. Methods for cleaning the BOLD fMRI signal. Neuroimage 2017; 154:128-149. [PMID: 27956209 PMCID: PMC5466511 DOI: 10.1016/j.neuroimage.2016.12.018] [Citation(s) in RCA: 320] [Impact Index Per Article: 45.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2016] [Revised: 12/05/2016] [Accepted: 12/08/2016] [Indexed: 01/13/2023] Open
Abstract
Blood oxygen-level-dependent functional magnetic resonance imaging (BOLD fMRI) has rapidly become a popular technique for the investigation of brain function in healthy individuals, patients as well as in animal studies. However, the BOLD signal arises from a complex mixture of neuronal, metabolic and vascular processes, being therefore an indirect measure of neuronal activity, which is further severely corrupted by multiple non-neuronal fluctuations of instrumental, physiological or subject-specific origin. This review aims to provide a comprehensive summary of existing methods for cleaning the BOLD fMRI signal. The description is given from a methodological point of view, focusing on the operation of the different techniques in addition to pointing out the advantages and limitations in their application. Since motion-related and physiological noise fluctuations are two of the main noise components of the signal, techniques targeting their removal are primarily addressed, including both data-driven approaches and using external recordings. Data-driven approaches, which are less specific in the assumed model and can simultaneously reduce multiple noise fluctuations, are mainly based on data decomposition techniques such as principal and independent component analysis. Importantly, the usefulness of strategies that benefit from the information available in the phase component of the signal, or in multiple signal echoes is also highlighted. The use of global signal regression for denoising is also addressed. Finally, practical recommendations regarding the optimization of the preprocessing pipeline for the purpose of denoising and future venues of research are indicated. Through the review, we summarize the importance of signal denoising as an essential step in the analysis pipeline of task-based and resting state fMRI studies.
Collapse
Affiliation(s)
| | - Richard C Reynolds
- Scientific and Statistical Computing Core, National Institute of Mental Health, National Institutes of Health, Department of Health and Human Services, USA
| |
Collapse
|
8
|
Witt ST, Warntjes M, Engström M. Increased fMRI Sensitivity at Equal Data Burden Using Averaged Shifted Echo Acquisition. Front Neurosci 2016; 10:544. [PMID: 27932947 PMCID: PMC5120083 DOI: 10.3389/fnins.2016.00544] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2016] [Accepted: 11/10/2016] [Indexed: 11/29/2022] Open
Abstract
There is growing evidence as to the benefits of collecting BOLD fMRI data with increased sampling rates. However, many of the newly developed acquisition techniques developed to collect BOLD data with ultra-short TRs require hardware, software, and non-standard analytic pipelines that may not be accessible to all researchers. We propose to incorporate the method of shifted echo into a standard multi-slice, gradient echo EPI sequence to achieve a higher sampling rate with a TR of <1 s with acceptable spatial resolution. We further propose to incorporate temporal averaging of consecutively acquired EPI volumes to both ameliorate the reduced temporal signal-to-noise inherent in ultra-fast EPI sequences and reduce the data burden. BOLD data were collected from 11 healthy subjects performing a simple, event-related visual-motor task with four different EPI sequences: (1) reference EPI sequence with TR = 1440 ms, (2) shifted echo EPI sequence with TR = 700 ms, (3) shifted echo EPI sequence with every two consecutively acquired EPI volumes averaged and effective TR = 1400 ms, and (4) shifted echo EPI sequence with every four consecutively acquired EPI volumes averaged and effective TR = 2800 ms. Both the temporally averaged sequences exhibited increased temporal signal-to-noise over the shifted echo EPI sequence. The shifted echo sequence with every two EPI volumes averaged also had significantly increased BOLD signal change compared with the other three sequences, while the shifted echo sequence with every four EPI volumes averaged had significantly decreased BOLD signal change compared with the other three sequences. The results indicated that incorporating the method of shifted echo into a standard multi-slice EPI sequence is a viable method for achieving increased sampling rate for collecting event-related BOLD data. Further, consecutively averaging every two consecutively acquired EPI volumes significantly increased the measured BOLD signal change and the subsequently calculated activation map statistics.
Collapse
Affiliation(s)
- Suzanne T Witt
- Center for Medical Image Science and Visualization, Linköping University Linköping, Sweden
| | - Marcel Warntjes
- Center for Medical Image Science and Visualization, Linköping UniversityLinköping, Sweden; Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linköping UniversityLinköping, Sweden
| | - Maria Engström
- Center for Medical Image Science and Visualization, Linköping UniversityLinköping, Sweden; Department of Medical and Health Sciences, Linköping UniversityLinköping, Sweden
| |
Collapse
|
9
|
Saotome K, Matsushita A, Nakai K, Kadone H, Tsurushima H, Sankai Y, Matsumura A. Quantitative Assessment of Head Motion toward Functional Magnetic Resonance Imaging during Stepping. Magn Reson Med Sci 2016; 15:273-80. [PMID: 26549164 PMCID: PMC5608123 DOI: 10.2463/mrms.mp.2015-0015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Purpose: Stepping motions have been often used as gait-like patterns in functional magnetic resonance imaging (fMRI) to understand gait control. However, it is still very difficult to stabilize the task-related head motion. Our main purpose is to provide characteristics of the task-related head motion during stepping to develop robust restraints toward fMRI. Methods: Multidirectional head and knee position during stepping were acquired using a motion capture system outside MRI room in 13 healthy participants. Six phases in a stepping motion were defined by reference to the left knee angles and the mean of superior-inferior head velocity (Vmean) in each phase was investigated. Furthermore, the correlation between the standard deviation of the knee angle (θsd) and the maximum of the head velocity (Vmax) was evaluated. Results: The standard deviation of each superior-inferior head position and pitch were significantly larger than the other measurements. Vmean showed a characteristic repeating pattern associated with the knee angle. Additionally, there were significant correlations between θsd and Vmax. Conclusions: This is the first report to reveal the characteristics of the task-related head motion during stepping. Our findings are an essential step in the development of robust restraint toward fMRI during stepping task.
Collapse
|
10
|
Robust resting state fMRI processing for studies on typical brain development based on multi-echo EPI acquisition. Brain Imaging Behav 2016; 9:56-73. [PMID: 25592183 DOI: 10.1007/s11682-014-9346-4] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
Several methodological challenges affect the study of typical brain development based on resting state blood oxygenation level dependent (BOLD) functional MRI (fMRI). One such challenge is mitigating artifacts such as those from head motion, known to be more substantial in younger subjects than older subjects. Other challenges include controlling for potential age-dependence in cerebrospinal fluid (CSF) volume affecting anatomical-functional coregistration; in vascular density affecting BOLD contrast-to-noise; and in CSF pulsation creating time series artifacts. Historically, these confounds have been approached through incorporating artifact-specific temporal and/or spatial filtering into preprocessing pipelines. However, such paths often come with new confounds or limitations. In this study we take the approach of a bottom-up revision of fMRI methodology based on acquisition of multi-echo fMRI and comprehensive utilization of the information in the TE-domain to enhance several aspects of fMRI analysis in the context of a developmental study. We show in a cohort of 25 healthy subjects, aged 9 to 43 years, that the analysis of multi-echo fMRI data eliminates a number of arbitrary processing steps such as bandpass filtering and spatial smoothing, while enabling procedures such as [Formula: see text] mapping, BOLD contrast normalization and signal dropout recovery, precise anatomical-functional coregistration based on [Formula: see text] measurements, automatic denoising through removing subject motion, scanner-related signal drifts and physiology, as well as statistical inference for seed-based connectivity. These enhancements are of both theoretical significance and practical benefit in the study of typical brain development.
Collapse
|
11
|
Sahib AK, Mathiak K, Erb M, Elshahabi A, Klamer S, Scheffler K, Focke NK, Ethofer T. Effect of temporal resolution and serial autocorrelations in event-related functional MRI. Magn Reson Med 2016; 76:1805-1813. [DOI: 10.1002/mrm.26073] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2015] [Revised: 10/16/2015] [Accepted: 11/15/2015] [Indexed: 11/07/2022]
Affiliation(s)
- Ashish Kaul Sahib
- Werner Reichardt Centre for Integrative Neuroscience; Tübingen Germany
- Department of Biomedical Magnetic Resonance; University Hospital Tübingen; Tübingen Germany
- Department of Neurology/Epileptology; University Hospital Tübingen and Hertie Institute of Clinical Brain Research; Tübingen Germany
- Graduate School of Neural and Behavioural Sciences/International Max Planck Research School; University of Tübingen; Tübingen Germany
| | - Klaus Mathiak
- Department of Psychiatry, Psychotherapy and Psychosomatics; University Hospital Aachen; Aachen Germany
| | - Michael Erb
- Department of Biomedical Magnetic Resonance; University Hospital Tübingen; Tübingen Germany
| | - Adham Elshahabi
- Department of Neurology/Epileptology; University Hospital Tübingen and Hertie Institute of Clinical Brain Research; Tübingen Germany
- Graduate School of Neural and Behavioural Sciences/International Max Planck Research School; University of Tübingen; Tübingen Germany
- MEG-Center; University of Tübingen; Tübingen Germany
| | - Silke Klamer
- Department of Neurology/Epileptology; University Hospital Tübingen and Hertie Institute of Clinical Brain Research; Tübingen Germany
| | - Klaus Scheffler
- Werner Reichardt Centre for Integrative Neuroscience; Tübingen Germany
- Department of Biomedical Magnetic Resonance; University Hospital Tübingen; Tübingen Germany
- Max-Planck-Institute for Biological Cybernetics; Tübingen Germany
| | - Niels K Focke
- Werner Reichardt Centre for Integrative Neuroscience; Tübingen Germany
- Department of Neurology/Epileptology; University Hospital Tübingen and Hertie Institute of Clinical Brain Research; Tübingen Germany
| | - Thomas Ethofer
- Werner Reichardt Centre for Integrative Neuroscience; Tübingen Germany
- Department of Biomedical Magnetic Resonance; University Hospital Tübingen; Tübingen Germany
- Department of General Psychiatry; University Hospital Tübingen; Tübingen Germany
| |
Collapse
|
12
|
Yu MC, Lin QH, Kuang LD, Gong XF, Cong F, Calhoun VD. ICA of full complex-valued fMRI data using phase information of spatial maps. J Neurosci Methods 2015; 249:75-91. [DOI: 10.1016/j.jneumeth.2015.03.036] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2015] [Revised: 03/30/2015] [Accepted: 03/31/2015] [Indexed: 12/17/2022]
|