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Notte C, Alionte C, Strubakos CD. The efficacy and methodology of using near-infrared spectroscopy to determine resting-state brain networks. J Neurophysiol 2024; 131:668-677. [PMID: 38416714 DOI: 10.1152/jn.00357.2023] [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: 09/27/2023] [Revised: 02/14/2024] [Accepted: 02/19/2024] [Indexed: 03/01/2024] Open
Abstract
Functional connectivity is a critical aspect of brain function and is essential for understanding, diagnosing, and treating neurological and psychiatric disorders. It refers to the synchronous activity between different regions of the brain, which gives rise to communication and information processing. Resting-state functional connectivity is a subarea of study that allows researchers to examine brain activity in the absence of a task or stimulus. This can provide insight into the brain's intrinsic functional architecture and help identify neural networks that are active during rest. Thus, determining functional connectivity topography is valuable both clinically and in research. Traditional methods using functional magnetic resonance imaging have proven to be effective, however, they have their limitations. In this review, we investigate the feasibility of using functional near-infrared spectroscopy (fNIRS) as a low-cost, portable alternative for measuring functional connectivity. We first establish fNIRS' ability to detect localized brain activity during task-based experiments. Next, we verify its use in resting-state studies with results showing a high degree of correspondence with resting-state functional magnetic resonance imaging (rs-fMRI). Also discussed are various data-processing methods and the validity of filtering the global signal, which is the current standard for analysis. We consider the possible origins of the global signal, if it contains pertinent neuronal information that could be of importance in better understanding neuronal networks, and what we believe is the best method of approaching signal analysis and regression.
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Affiliation(s)
- Christian Notte
- Department of Physics, University of Windsor, Windsor, Ontario, Canada
| | - Caroline Alionte
- Department of Physics, University of Windsor, Windsor, Ontario, Canada
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2
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Amemiya S, Takao H, Abe O. Resting-State fMRI: Emerging Concepts for Future Clinical Application. J Magn Reson Imaging 2024; 59:1135-1148. [PMID: 37424140 DOI: 10.1002/jmri.28894] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 06/22/2023] [Accepted: 06/22/2023] [Indexed: 07/11/2023] Open
Abstract
Resting-state functional magnetic resonance imaging (rsfMRI) has been developed as a method of investigating spontaneous neural activity. Based on its low-frequency signal synchronization, rsfMRI has made it possible to identify multiple macroscopic structures termed resting-state networks (RSNs) on a single scan of less than 10 minutes. It is easy to implement even in clinical practice, in which assigning tasks to patients can be challenging. These advantages have accelerated the adoption and growth of rsfMRI. Recently, studies on the global rsfMRI signal have attracted increasing attention. Because it primarily arises from physiological events, less attention has hitherto been paid to the global signal than to the local network (i.e., RSN) component. However, the global signal is not a mere nuisance or a subsidiary component. On the contrary, it is quantitatively the dominant component that accounts for most of the variance in the rsfMRI signal throughout the brain and provides rich information on local hemodynamics that can serve as an individual-level diagnostic biomarker. Moreover, spatiotemporal analyses of the global signal have revealed that it is closely and fundamentally associated with the organization of RSNs, thus challenging the basic assumptions made in conventional rsfMRI analyses and views on RSNs. This review introduces new concepts emerging from rsfMRI spatiotemporal analyses focusing on the global signal and discusses how they may contribute to future clinical medicine. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Shiori Amemiya
- Department of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Hidemasa Takao
- Department of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Osamu Abe
- Department of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
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3
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Gomez DEP, Polimeni JR, Lewis LD. The temporal specificity of BOLD fMRI is systematically related to anatomical and vascular features of the human brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.01.578428. [PMID: 38352610 PMCID: PMC10862860 DOI: 10.1101/2024.02.01.578428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
The ability to detect fast responses with functional MRI depends on the speed of hemodynamic responses to neural activity, because hemodynamic responses act as a temporal low-pass filter smoothing out rapid changes. However, hemodynamic responses (their shape and timing) are highly variable across the brain and across stimuli. This heterogeneity of responses implies that the temporal specificity of fMRI signals, or the ability of fMRI to preserve fast information, should also vary substantially across the cortex. In this work we investigated how local differences in hemodynamic response timing impact the temporal specificity of fMRI. We conducted our research using ultra-high field (7T) fMRI at high spatiotemporal resolution, using the primary visual cortex (V1) as a model area for investigation. We used visual stimuli oscillating at slow and fast frequencies to probe the temporal specificity of individual voxels. As expected, we identified substantial variability in temporal specificity, with some voxels preserving their responses to fast neural activity more effectively than others. We investigated which voxels had the highest temporal specificity and related those to anatomical and vascular features of V1. We found that low temporal specificity is only weakly explained by the presence of large veins or cerebral cortical depth. Notably, however, temporal specificity depended strongly on a voxel's position along the anterior-posterior anatomical axis of V1, with voxels within the calcarine sulcus being capable of preserving close to 25% of their amplitude as the frequency of stimulation increased from 0.05-Hz to 0.20-Hz, and voxels nearest to the occipital pole preserving less than 18%. These results indicate that detection biases in high-resolution fMRI will depend on the anatomical and vascular features of the area being imaged, and that these biases will differ depending on the timing of the underlying neuronal activity. Importantly, this spatial heterogeneity of temporal specificity suggests that it could be exploited to achieve higher specificity in some locations, and that tailored data analysis strategies may help improve the detection and interpretation of fast fMRI responses.
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Affiliation(s)
- Daniel E. P. Gomez
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Jonathan R. Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Laura D. Lewis
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, United States
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, United States
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Novitskaya Y, Dümpelmann M, Schulze-Bonhage A. Physiological and pathological neuronal connectivity in the living human brain based on intracranial EEG signals: the current state of research. FRONTIERS IN NETWORK PHYSIOLOGY 2023; 3:1297345. [PMID: 38107334 PMCID: PMC10723837 DOI: 10.3389/fnetp.2023.1297345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 11/17/2023] [Indexed: 12/19/2023]
Abstract
Over the past decades, studies of human brain networks have received growing attention as the assessment and modelling of connectivity in the brain is a topic of high impact with potential application in the understanding of human brain organization under both physiological as well as various pathological conditions. Under specific diagnostic settings, human neuronal signal can be obtained from intracranial EEG (iEEG) recording in epilepsy patients that allows gaining insight into the functional organisation of living human brain. There are two approaches to assess brain connectivity in the iEEG-based signal: evaluation of spontaneous neuronal oscillations during ongoing physiological and pathological brain activity, and analysis of the electrophysiological cortico-cortical neuronal responses, evoked by single pulse electrical stimulation (SPES). Both methods have their own advantages and limitations. The paper outlines available methodological approaches and provides an overview of current findings in studies of physiological and pathological human brain networks, based on intracranial EEG recordings.
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Affiliation(s)
- Yulia Novitskaya
- Epilepsy Center, Department of Neurosurgery, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Matthias Dümpelmann
- Epilepsy Center, Department of Neurosurgery, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Department of Microsystems Engineering (IMTEK), University of Freiburg, Freiburg, Germany
| | - Andreas Schulze-Bonhage
- Epilepsy Center, Department of Neurosurgery, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Center for Basics in NeuroModulation, Faculty of Medicine, University of Freiburg, Freiburg, Germany
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5
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Schneider SC, Kaczmarz S, Göttler J, Kufer J, Zott B, Priller J, Kallmayer M, Zimmer C, Sorg C, Preibisch C. Stronger influence of systemic than local hemodynamic-vascular factors on resting-state BOLD functional connectivity. Neuroimage 2023; 281:120380. [PMID: 37741595 DOI: 10.1016/j.neuroimage.2023.120380] [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: 04/06/2023] [Revised: 08/28/2023] [Accepted: 09/13/2023] [Indexed: 09/25/2023] Open
Abstract
Correlated fluctuations in the blood oxygenation level dependent (BOLD) signal of resting-state functional MRI (i.e., BOLD-functional connectivity, BOLD-FC) reflect a spectrum of neuronal and non-neuronal processes. In particular, there are multiple hemodynamic-vascular influences on BOLD-FC on both systemic (e.g., perfusion delay) and local levels (e.g., neurovascular coupling). While the influence of individual factors has been studied extensively, combined and comparative studies of systemic and local hemodynamic-vascular factors on BOLD-FC are scarce, notably in humans. We employed a multi-modal MRI approach to investigate and compare distinct hemodynamic-vascular processes and their impact on homotopic BOLD-FC in healthy controls and patients with unilateral asymptomatic internal carotid artery stenosis (ICAS). Asymptomatic ICAS is a cerebrovascular disorder, in which neuronal functioning is largely preserved but hemodynamic-vascular processes are impaired, mostly on the side of stenosis. Investigated indicators for local hemodynamic-vascular processes comprise capillary transit time heterogeneity (CTH) and cerebral blood volume (CBV) from dynamic susceptibility contrast (DSC) MRI, and cerebral blood flow (CBF) from pseudo-continuous arterial spin labeling (pCASL). Indicators for systemic processes are time-to-peak (TTP) from DSC MRI and BOLD lags from functional MRI. For each of these parameters, their influence on BOLD-FC was estimated by a comprehensive linear mixed model. Equally across groups, we found that individual mean BOLD-FC, local (CTH, CBV, and CBF) and systemic (TTP and BOLD lag) hemodynamic-vascular factors together explain 40.7% of BOLD-FC variance, with 20% of BOLD-FC variance explained by hemodynamic-vascular factors, with an about two-times larger contribution of systemic versus local factors. We conclude that regional differences in blood supply, i.e., systemic perfusion delays, exert a stronger influence on BOLD-FC than impairments in local neurovascular coupling.
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Affiliation(s)
- Sebastian C Schneider
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Clinic for Psychiatry, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675 Munich, Munich, Germany.
| | - Stephan Kaczmarz
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675 Munich, Munich, Germany; Philips GmbH Market DACH, Hamburg, Germany
| | - Jens Göttler
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675 Munich, Munich, Germany
| | - Jan Kufer
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675 Munich, Munich, Germany; Department of Radiology & Biomedical Imaging, Yale University, New Haven, CT, United States of America
| | - Benedikt Zott
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675 Munich, Munich, Germany
| | - Josef Priller
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Clinic for Psychiatry, Ismaningerstr. 22, 81675 Munich, Germany
| | - Michael Kallmayer
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Clinic for vascular surgery, Ismaningerstr. 22, 81675 Munich, Munich, Germany
| | - Claus Zimmer
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675 Munich, Munich, Germany
| | - Christian Sorg
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Clinic for Psychiatry, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675 Munich, Munich, Germany
| | - Christine Preibisch
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675 Munich, Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Clinic for Neurology, Ismaningerstr. 22, 81675 Munich, Munich, Germany
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6
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Wei B, Peng L, Guo Y, Manatunga A, Stevens J. Tensor response quantile regression with neuroimaging data. Biometrics 2023; 79:1947-1958. [PMID: 36482808 PMCID: PMC10250564 DOI: 10.1111/biom.13809] [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: 02/20/2022] [Accepted: 11/25/2022] [Indexed: 12/14/2022]
Abstract
Collecting neuroimaging data in the form of tensors (i.e. multidimensional arrays) has become more common in mental health studies, driven by an increasing interest in studying the associations between neuroimaging phenotypes and clinical disease manifestation. Motivated by a neuroimaging study of post-traumatic stress disorder (PTSD) from the Grady Trauma Project, we study a tensor response quantile regression framework, which enables novel analyses that confer a detailed view of the potentially heterogeneous association between a neuroimaging phenotype and relevant clinical predictors. We adopt a sensible low-rank structure to represent the association of interest, and propose a simple two-step estimation procedure which is easy to implement with existing software. We provide rigorous theoretical justifications for the intuitive two-step procedure. Simulation studies demonstrate good performance of the proposed method with realistic sample sizes in neuroimaging studies. We conduct the proposed tensor response quantile regression analysis of the motivating PTSD study to investigate the association between fMRI resting-state functional connectivity and PTSD symptom severity. Our results uncover non-homogeneous effects of PTSD symptoms on brain functional connectivity, which cannot be captured by existing tensor response methods.
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Affiliation(s)
- Bo Wei
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, 30322, U.S.A
| | - Limin Peng
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, 30322, U.S.A
| | - Ying Guo
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, 30322, U.S.A
| | - Amita Manatunga
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, 30322, U.S.A
| | - Jennifer Stevens
- Department of Psychiatry and Behavior Sciences, Emory University, Atlanta, GA, 30322, U.S.A
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7
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Amemiya S, Takao H, Hanaoka S, Abe O. Resting-state networks representation of the global phenomena. Front Neurosci 2023; 17:1220848. [PMID: 37662100 PMCID: PMC10469869 DOI: 10.3389/fnins.2023.1220848] [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: 05/11/2023] [Accepted: 08/07/2023] [Indexed: 09/05/2023] Open
Abstract
Resting-state functional magnetic resonance imaging (rsfMRI) has been widely applied to investigate spontaneous neural activity, often based on its macroscopic organization that is termed resting-state networks (RSNs). Although the neurophysiological mechanisms underlying the RSN organization remain largely unknown, accumulating evidence points to a substantial contribution from the global signals to their structured synchronization. This study further explored the phenomenon by taking advantage of the inter- and intra-subject variations of the time delay and correlation coefficient of the signal timeseries in each region using the global mean signal as the reference signal. Consistent with the hypothesis based on the empirical and theoretical findings, the time lag and correlation, which have consistently been proven to represent local hemodynamic status, were shown to organize networks equivalent to RSNs. The results not only provide further evidence that the local hemodynamic status could be the direct source of the RSNs' spatial patterns but also explain how the regional variations in the hemodynamics, combined with the changes in the global events' power spectrum, lead to the observations. While the findings pose challenges to interpretations of rsfMRI studies, they further support the view that rsfMRI can offer detailed information related to global neurophysiological phenomena as well as local hemodynamics that would have great potential as biomarkers.
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Affiliation(s)
- Shiori Amemiya
- Department of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
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8
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Wanger TJ, Janes AC, Frederick BB. Spatial variation of changes in test-retest reliability of functional connectivity after global signal regression: The effect of considering hemodynamic delay. Hum Brain Mapp 2022; 44:668-678. [PMID: 36214198 PMCID: PMC9842913 DOI: 10.1002/hbm.26091] [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: 06/08/2022] [Revised: 08/24/2022] [Accepted: 09/07/2022] [Indexed: 01/25/2023] Open
Abstract
Global signal regression (GSR) is a controversial analysis method, since its removal of signal has been observed to reduce the reliability of functional connectivity estimates. Here, we used test-retest reliability to characterize potential differences in spatial patterns between conventional, static GSR (sGSR) and a novel dynamic form of GSR (dGSR). In contrast with sGSR, dGSR models the global signal at a time delay to correct for blood arrival time. Thus, dGSR accounts for greater variation in global signal, removes blood-flow-related nuisance signal, and leaves higher quality neuronal signal remaining. We used intraclass correlation coefficients (ICCs) to estimate the reliability of functional connectivity in 462 healthy controls from the Human Connectome Project. We tested across two factors: denoising method used (control, sGSR, and dGSR), and interacquisition interval (between days, or within session while varying phase encoding direction). Reliability was estimated regionally to identify topographic patterns for each condition. sGSR and dGSR provided global reductions in reliability compared with the non-GSR control. Test-retest reliability was highest in the frontoparietal and default mode regions, and lowest in sensorimotor cortex for all conditions. dGSR provides more effective denoising in regions where both strategies greatly reduce reliability. Both GSR methods substantially reduced test-retest reliability, which was most evident in brain regions that had low reliability prior to denoising. These findings suggest that reliability of interregional correlation is likely inflated by the global signal, which is thought to primarily reflect dynamic blood flow.
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Affiliation(s)
- Timothy J. Wanger
- McLean Imaging CenterMcLean HospitalBelmontMassachusettsUSA,Department of PsychiatryHarvard Medical SchoolBostonMassachusettsUSA
| | - Amy C. Janes
- Neuroimaging Research Branch, National Institute on Drug Abuse (NIDA)Intramural Research Program, National Institutes of HealthBaltimoreMarylandUSA
| | - Blaise B. Frederick
- McLean Imaging CenterMcLean HospitalBelmontMassachusettsUSA,Department of PsychiatryHarvard Medical SchoolBostonMassachusettsUSA
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9
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Amemiya S, Takao H, Watanabe Y, Miyawaki S, Koizumi S, Saito N, Abe O. Reliability and Sensitivity to Alterered Hemodynamics Measured with Resting-state fMRI Metrics: Comparison with 123I-IMP SPECT. Neuroimage 2022; 263:119654. [PMID: 36180009 DOI: 10.1016/j.neuroimage.2022.119654] [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: 08/02/2022] [Revised: 09/16/2022] [Accepted: 09/26/2022] [Indexed: 11/24/2022] Open
Abstract
Blood oxygenation level-dependent (BOLD) contrast is sensitive to local hemodynamic changes and thus is applicable to imaging perfusion or vascular reactivity. However, knowledge about its measurement characteristics compared to reference standard perfusion imaging is limited. This study longitudinally evaluated perfusion in patients with steno-occlusive disease using resting-state functional MRI (rsfMRI) acquired before and within nine days of anterior circulation revascularization in patients with large cerebral artery steno-occlusive diseases. The reliability and sensitivity to longitudinal changes of rsfMRI temporal correlation (Rc) and time delay (TDc) relative to the cerebellar signal were examined voxel-wise in comparison with single-photon emission CT (SPECT) cerebral blood flow (CBF) using the within-subject standard deviation (Sw) and intraclass correlation coefficients (ICCs). For statistical comparisons, the standard deviation (SD) of longitudinal changes within the cerebellum, the number of voxels with significant changes in the left middle cerebral artery territory ipsilateral to surgery, and their average changes relative to the cerebellar SD were evaluated. The test-retest reliability of the fMRI metrics was also similarly evaluated using the human connectome project (HCP) healthy young adult dataset. The test-retest time interval was 31 ± 18 days. Test-retest reliability was significantly higher for SPECT (cerebellar SD: -2.59 ± 0.20) than for fMRI metrics (cerebellar SD: Rc, -2.34 ± 0.24, p = 0.04; TDc, -2.19 ± 0.21, p = 0.003). Sensitivity to postoperative changes, which was evaluated as the number of voxels, was significantly higher for fMRI TDc (8.78 ± 0.72) than for Rc (7.42 ± 1.48, p = 0.03) or SPECT CBF (6.88 ± 0.67, p < 0.001). The ratio between the average Rc, TDc, and SPECT CBF changes within the left MCA target region and cerebellar SD was also significantly higher for fMRI TDc (1.21 ± 0.79) than Rc (0.48 ± 0.94, p = 0.006) or SPECT CBF (0.23 ± 0.57, p = 0.001). The measurement variability of time delay was also larger than that of temporal correlation in HCP data within the cerebellum (t = -8.7, p < 0.001) or in the whole-brain (t = -27.4, p < 0.001) gray matter. These data suggest that fMRI time delay is more sensitive to the hemodynamic changes than SPECT CBF, although the reliability is lower. The implication for fMRI connectivity studies is that temporal correlation can be significantly decreased due to altered hemodynamics, even in cases with normal CBF.
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Affiliation(s)
- Shiori Amemiya
- Department of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, JAPAN.
| | - Hidemasa Takao
- Department of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, JAPAN
| | - Yusuke Watanabe
- Department of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, JAPAN
| | - Satoru Miyawaki
- Department of Neurosurgery, Graduate School of Medicine, University of Tokyo, Tokyo, JAPAN
| | - Satoshi Koizumi
- Department of Neurosurgery, Graduate School of Medicine, University of Tokyo, Tokyo, JAPAN
| | - Nobuhito Saito
- Department of Neurosurgery, Graduate School of Medicine, University of Tokyo, Tokyo, JAPAN
| | - Osamu Abe
- Department of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, JAPAN
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10
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Vijayakrishnan Nair V, Kish BR, Inglis B, Yang HC(S, Wright AM, Wu YC, Zhou X, Schwichtenberg AJ, Tong Y. Human CSF movement influenced by vascular low frequency oscillations and respiration. Front Physiol 2022; 13:940140. [PMID: 36060685 PMCID: PMC9437252 DOI: 10.3389/fphys.2022.940140] [Citation(s) in RCA: 5] [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: 05/10/2022] [Accepted: 07/11/2022] [Indexed: 12/03/2022] Open
Abstract
Cerebrospinal fluid (CSF) movement through the pathways within the central nervous system is of high significance for maintaining normal brain health and function. Low frequency hemodynamics and respiration have been shown to drive CSF in humans independently. Here, we hypothesize that CSF movement may be driven simultaneously (and in synchrony) by both mechanisms and study their independent and coupled effects on CSF movement using novel neck fMRI scans. Caudad CSF movement at the fourth ventricle and hemodynamics of the major neck blood vessels (internal carotid arteries and internal jugular veins) was measured from 11 young, healthy volunteers using novel neck fMRI scans with simultaneous measurement of respiration. Two distinct models of CSF movement (1. Low-frequency hemodynamics and 2. Respiration) and possible coupling between them were investigated. We show that the dynamics of brain fluids can be assessed from the neck by studying the interrelationships between major neck blood vessels and the CSF movement in the fourth ventricle. We also demonstrate that there exists a cross-frequency coupling between these two separable mechanisms. The human CSF system can respond to multiple coupled physiological forces at the same time. This information may help inform the pathological mechanisms behind CSF movement-related disorders.
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Affiliation(s)
| | - Brianna R. Kish
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States
| | - Ben Inglis
- Henry H. Wheeler, Jr. Brain Imaging Center, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, United States
| | - Ho-Ching (Shawn) Yang
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Adam M. Wright
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States
| | - Yu-Chien Wu
- Stark Neuroscience Research Institute, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Xiaopeng Zhou
- School of Health Sciences, Purdue University, West Lafayette, IN, United States
| | - Amy J. Schwichtenberg
- Department of Human Development and Family Studies, College of Health and Human Sciences, Purdue University, West Lafayette, IN, United States
| | - Yunjie Tong
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States
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11
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Whittaker JR, Steventon JJ, Venzi M, Murphy K. The Spatiotemporal Dynamics of Cerebral Autoregulation in Functional Magnetic Resonance Imaging. Front Neurosci 2022; 16:795683. [PMID: 35873811 PMCID: PMC9304653 DOI: 10.3389/fnins.2022.795683] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Accepted: 06/20/2022] [Indexed: 12/02/2022] Open
Abstract
The thigh-cuff release (TCR) maneuver is a physiological challenge that is widely used to assess dynamic cerebral autoregulation (dCA). It is often applied in conjunction with Transcranial Doppler ultrasound (TCD), which provides temporal information of the global flow response in the brain. This established method can only yield very limited insights into the regional variability of dCA, whereas functional MRI (fMRI) has the ability to reveal the spatial distribution of flow responses in the brain with high spatial resolution. The aim of this study was to use whole-brain blood-oxygenation-level-dependent (BOLD) fMRI to characterize the spatiotemporal dynamics of the flow response to the TCR challenge, and thus pave the way toward mapping dCA in the brain. We used a data driven approach to derive a novel basis set that was then used to provide a voxel-wise estimate of the TCR associated haemodynamic response function (HRF TCR ). We found that the HRF TCR evolves with a specific spatiotemporal pattern, with gray and white matter showing an asynchronous response, which likely reflects the anatomical structure of cerebral blood supply. Thus, we propose that TCR challenge fMRI is a promising method for mapping spatial variability in dCA, which will likely prove to be clinically advantageous.
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Affiliation(s)
- Joseph R. Whittaker
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Physics and Astronomy, Cardiff University, Cardiff, United Kingdom
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Jessica J. Steventon
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Marcello Venzi
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Physics and Astronomy, Cardiff University, Cardiff, United Kingdom
| | - Kevin Murphy
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Physics and Astronomy, Cardiff University, Cardiff, United Kingdom
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Fischer F, Malherbe C, Schlemm E, Schröder J, Heinze M, Cheng B, Schulz M, Fiehler J, Larena-Avellaneda A, Gerloff C, Thomalla G. Intrinsic functional brain connectivity is resilient to chronic hypoperfusion caused by unilateral carotid artery stenosis. Neuroimage Clin 2022; 34:103014. [PMID: 35483135 PMCID: PMC9125779 DOI: 10.1016/j.nicl.2022.103014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 04/18/2022] [Accepted: 04/19/2022] [Indexed: 12/01/2022]
Abstract
Unilateral internal carotid artery stenosis leads to chronic cerebral hypoperfusion. rsfMRI functional connectivity is well-compensated in asymptomatic ICA stenosis. Functional network properties remain stable before and after revascularization.
Introduction Chronic cerebral hypoperfusion caused by asymptomatic high-grade stenosis of the internal carotid artery (ICA) has been associated with impaired cognitive function. Only few studies exist on underlying changes of functional connectivity (FC). Methods 20 patients with unilateral high-grade ICA stenosis without MRI lesions and 25 aged-match controls underwent resting-state functional MRI (rsfMRI) and neuropsychological assessment. Patients were examined within ten days before and 6–10 weeks after surgical or interventional revascularization of carotid stenosis. We examined mean resting-state FC ipsi- and contralateral to stenosis and network topology using graph-theoretical measures. Results At baseline, intrahemispheric FC was similar for patients and healthy controls. After revascularization mean FC increased moderately without an effect on network topology. Patients performed worse in TMT B and Stroop test, while performance in global screening tests for dementia (Mini Mental Status Examination, DemTect) were comparable. Test results did not improve after revascularization. Conclusion In our study population, we find no effect of chronic hypoperfusion on FC and global cognitive function, although we observe minor impairments in processing speed and mental flexibility. The subtle increase of FC after revascularization could indicate excessive upregulation after restoration of perfusion. However, it might as well be a coincidental finding due to the limited sample size.
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Affiliation(s)
- Felix Fischer
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
| | - Caroline Malherbe
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; Institute of Computational Neuroscience, University Medical Center Hamburg Eppendorf, Hamburg, Germany
| | - Eckhard Schlemm
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Julian Schröder
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Marlene Heinze
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Bastian Cheng
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Maximilian Schulz
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jens Fiehler
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | | | - Christian Gerloff
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Götz Thomalla
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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Bollmann S, Mattern H, Bernier M, Robinson SD, Park DJ, Speck O, Polimeni JR. Imaging of the pial arterial vasculature of the human brain in vivo using high-resolution 7T time-of-flight angiography. eLife 2022; 11:71186. [PMID: 35486089 PMCID: PMC9150892 DOI: 10.7554/elife.71186] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 04/28/2022] [Indexed: 11/30/2022] Open
Abstract
The pial arterial vasculature of the human brain is the only blood supply to the neocortex, but quantitative data on the morphology and topology of these mesoscopic arteries (diameter 50–300 µm) remains scarce. Because it is commonly assumed that blood flow velocities in these vessels are prohibitively slow, non-invasive time-of-flight magnetic resonance angiography (TOF-MRA)—which is well suited to high 3D imaging resolutions—has not been applied to imaging the pial arteries. Here, we provide a theoretical framework that outlines how TOF-MRA can visualize small pial arteries in vivo, by employing extremely small voxels at the size of individual vessels. We then provide evidence for this theory by imaging the pial arteries at 140 µm isotropic resolution using a 7 Tesla (T) magnetic resonance imaging (MRI) scanner and prospective motion correction, and show that pial arteries one voxel width in diameter can be detected. We conclude that imaging pial arteries is not limited by slow blood flow, but instead by achievable image resolution. This study represents the first targeted, comprehensive account of imaging pial arteries in vivo in the human brain. This ultra-high-resolution angiography will enable the characterization of pial vascular anatomy across the brain to investigate patterns of blood supply and relationships between vascular and functional architecture.
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Affiliation(s)
- Saskia Bollmann
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia
| | - Hendrik Mattern
- Department of Biomedical Magnetic Resonance, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
| | - Michaël Bernier
- Athinoula A Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, United States
| | - Simon D Robinson
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia
| | - Daniel J Park
- Athinoula A Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, United States
| | - Oliver Speck
- German Center for Neurodegenerative Diseases, Magdeburg, Germany
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Huotari N, Tuunanen J, Raitamaa L, Raatikainen V, Kananen J, Helakari H, Tuovinen T, Järvelä M, Kiviniemi V, Korhonen V. Cardiovascular Pulsatility Increases in Visual Cortex Before Blood Oxygen Level Dependent Response During Stimulus. Front Neurosci 2022; 16:836378. [PMID: 35185462 PMCID: PMC8853630 DOI: 10.3389/fnins.2022.836378] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 01/13/2022] [Indexed: 11/13/2022] Open
Abstract
The physiological pulsations that drive tissue fluid homeostasis are not well characterized during brain activation. Therefore, we used fast magnetic resonance encephalography (MREG) fMRI to measure full band (0–5 Hz) blood oxygen level-dependent (BOLDFB) signals during a dynamic visual task in 23 subjects. This revealed brain activity in the very low frequency (BOLDVLF) as well as in cardiac and respiratory bands. The cardiovascular hemodynamic envelope (CHe) signal correlated significantly with the visual BOLDVLF response, considered as an independent signal source in the V1-V2 visual cortices. The CHe preceded the canonical BOLDVLF response by an average of 1.3 (± 2.2) s. Physiologically, the observed CHe signal could mark increased regional cardiovascular pulsatility following vasodilation.
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Affiliation(s)
- Niko Huotari
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
- *Correspondence: Niko Huotari,
| | - Johanna Tuunanen
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
| | - Lauri Raitamaa
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
| | - Ville Raatikainen
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
| | - Janne Kananen
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
| | - Heta Helakari
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
| | - Timo Tuovinen
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
| | - Matti Järvelä
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
| | - Vesa Kiviniemi
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
| | - Vesa Korhonen
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
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