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Demidenko MI, Mumford JA, Ram N, Poldrack RA. A multi-sample evaluation of the measurement structure and function of the modified monetary incentive delay task in adolescents. Dev Cogn Neurosci 2024; 65:101337. [PMID: 38160517 PMCID: PMC10801229 DOI: 10.1016/j.dcn.2023.101337] [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: 11/27/2022] [Revised: 12/11/2023] [Accepted: 12/26/2023] [Indexed: 01/03/2024] Open
Abstract
Interpreting the neural response elicited during task functional magnetic resonance imaging (fMRI) remains a challenge in neurodevelopmental research. The monetary incentive delay (MID) task is an fMRI reward processing task that is extensively used in the literature. However, modern psychometric tools have not been used to evaluate measurement properties of the MID task fMRI data. The current study uses data for a similar task design across three adolescent samples (N = 346 [Agemean 12.0; 44 % Female]; N = 97 [19.3; 58 %]; N = 112 [20.2; 38 %]) to evaluate multiple measurement properties of fMRI responses on the MID task. Confirmatory factor analysis (CFA) is used to evaluate an a priori theoretical model for the task and its measurement invariance across three samples. Exploratory factor analysis (EFA) is used to identify the data-driven measurement structure across the samples. CFA results suggest that the a priori model is a poor representation of these MID task fMRI data. Across the samples, the data-driven EFA models consistently identify a six-to-seven factor structure with run and bilateral brain region factors. This factor structure is moderately-to-highly congruent across the samples. Altogether, these findings demonstrate a need to evaluate theoretical frameworks for popular fMRI task designs to improve our understanding and interpretation of brain-behavior associations.
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Affiliation(s)
| | | | - Nilam Ram
- Department of Psychology, Stanford University, Stanford, United States
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Báez-Yáñez MG, Siero JCW, Petridou N. A mechanistic computational framework to investigate the hemodynamic fingerprint of the blood oxygenation level-dependent signal. NMR IN BIOMEDICINE 2023; 36:e5026. [PMID: 37643645 DOI: 10.1002/nbm.5026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 07/18/2023] [Accepted: 07/28/2023] [Indexed: 08/31/2023]
Abstract
Blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is one of the most used imaging techniques to map brain activity or to obtain clinical information about human cortical vasculature, in both healthy and disease conditions. Nevertheless, BOLD fMRI is an indirect measurement of brain functioning triggered by neurovascular coupling. The origin of the BOLD signal is quite complex, and the signal formation thus depends, among other factors, on the topology of the cortical vasculature and the associated hemodynamic changes. To understand the hemodynamic evolution of the BOLD signal response in humans, it is beneficial to have a computational framework available that virtually resembles the human cortical vasculature, and simulates hemodynamic changes and corresponding MRI signal changes via interactions of intrinsic biophysical and magnetic properties of the tissues. To this end, we have developed a mechanistic computational framework that simulates the hemodynamic fingerprint of the BOLD signal based on a statistically defined, three-dimensional, vascular model that approaches the human cortical vascular architecture. The microvasculature is approximated through a Voronoi tessellation method and the macrovasculature is adapted from two-photon microscopy mice data. Using this computational framework, we simulated hemodynamic changes-cerebral blood flow, cerebral blood volume, and blood oxygen saturation-induced by virtual arterial dilation. Then we computed local magnetic field disturbances generated by the vascular topology and the corresponding blood oxygen saturation changes. This mechanistic computational framework also considers the intrinsic biophysical and magnetic properties of nearby tissue, such as water diffusion and relaxation properties, resulting in a dynamic BOLD signal response. The proposed mechanistic computational framework provides an integrated biophysical model that can offer better insights regarding the spatial and temporal properties of the BOLD signal changes.
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Affiliation(s)
- Mario Gilberto Báez-Yáñez
- Department of Radiology, Centre for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jeroen C W Siero
- Department of Radiology, Centre for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
- Spinoza Centre for Neuroimaging Amsterdam, Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
| | - Natalia Petridou
- Department of Radiology, Centre for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
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Fesharaki NJ, Taylor A, Mosby K, Kim JH, Ress D. Global effects of aging on the hemodynamic response function in the human brain. RESEARCH SQUARE 2023:rs.3.rs-3299293. [PMID: 37720046 PMCID: PMC10503846 DOI: 10.21203/rs.3.rs-3299293/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/19/2023]
Abstract
In functional magnetic resonance imaging, the hemodynamic response function (HRF) is a transient, stereotypical response to local changes in cerebral hemodynamics and oxygen metabolism due to briefly (< 4 s) evoked neural activity. Accordingly, the HRF is often used as an impulse response with the assumption of linearity in data analysis. In cognitive aging studies, it has been very common to interpret differences in brain activation as age-related changes in neural activity. Contrary to this assumption, however, evidence has accrued that normal aging may also significantly affect the vasculature, thereby affecting cerebral hemodynamics and metabolism, confounding interpretation of fMRI aging studies. In this study, use was made of a multisensory stimulus to evoke the HRF in ~ 87% of cerebral cortex in cognitively intact adults with ages ranging from 22-75 years. The stimulus evokes both positive and negative HRFs, which were characterized using model-free parameters in native-space coordinates. Results showed significant age trends in HRF parameter distributions in terms of both amplitudes (e.g., peak amplitude and CNR) and temporal dynamics (e.g., full-width-at-half-maximum). This work sets the stage for using HRF methods as a biomarker for age-related pathology.
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Zaidi AD, Birbaumer N, Fetz E, Logothetis N, Sitaram R. The hemodynamic initial-dip consists of both volumetric and oxymetric changes reflecting localized spiking activity. Front Neurosci 2023; 17:1170401. [PMID: 37304038 PMCID: PMC10248142 DOI: 10.3389/fnins.2023.1170401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 04/28/2023] [Indexed: 06/13/2023] Open
Abstract
The initial-dip is a transient decrease frequently observed in functional neuroimaging signals, immediately after stimulus onset, believed to originate from a rise in deoxy-hemoglobin (HbR) caused by local neural activity. It has been shown to be more spatially specific than the hemodynamic response, and is believed to represent focal neuronal activity. However, despite being observed in various neuroimaging modalities (such as fMRI, fNIRS, etc), its origins are disputed, and its precise neuronal correlates are unknown. Here we show that the initial-dip is dominated by a decrease in total-hemoglobin (HbT). We also find a biphasic response in deoxy-Hb (HbR), with an early decrease and later rebound. Both the HbT-dip and HbR-rebound were strongly correlated to highly localized spiking activity. However, HbT decreases were always large enough to counter the spiking-induced increase in HbR. We find that the HbT-dip counters spiking induced HbR increases, imposing an upper-limit to HbR concentration in the capillaries. Building on our results, we explore the possibility of active venule dilation (purging) as a possible mechanism for the HbT dip.
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Affiliation(s)
- Ali Danish Zaidi
- Department of Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
- Institute for Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, United States
| | - Niels Birbaumer
- Center for Imaging Sciences, Biomedical Imaging Institute, University of Manchester, Manchester, United Kingdom
| | - Eberhard Fetz
- Institute of Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Nikos Logothetis
- Department of Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
- Department of Psychiatry and Section of Neuroscience, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Ranganatha Sitaram
- Institute of Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
- Department of Psychiatry and Section of Neuroscience, Pontificia Universidad Católica de Chile, Santiago, Chile
- Multimodal Functional Brain Imaging and Neurorehabilitation Hub, Diagnostic Imaging Department, St. Jude Children's Research Hospital, Memphis, TN, United States
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Ionescu TM, Grohs-Metz G, Hengerer B. Functional ultrasound detects frequency-specific acute and delayed S-ketamine effects in the healthy mouse brain. Front Neurosci 2023; 17:1177428. [PMID: 37266546 PMCID: PMC10229773 DOI: 10.3389/fnins.2023.1177428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 04/21/2023] [Indexed: 06/03/2023] Open
Abstract
Introduction S-ketamine has received great interest due to both its antidepressant effects and its potential to induce psychosis when administered subchronically. However, no studies have investigated both its acute and delayed effects using in vivo small-animal imaging. Recently, functional ultrasound (fUS) has emerged as a powerful alternative to functional magnetic resonance imaging (fMRI), outperforming it in sensitivity and in spatiotemporal resolution. In this study, we employed fUS to thoroughly characterize acute and delayed S-ketamine effects on functional connectivity (FC) within the same cohort at slow frequency bands ranging from 0.01 to 1.25 Hz, previously reported to exhibit FC. Methods We acquired fUS in a total of 16 healthy C57/Bl6 mice split in two cohorts (n = 8 received saline, n = 8 S-ketamine). One day after the first scans, performed at rest, the mice received the first dose of S-ketamine during the second measurement, followed by four further doses administered every 2 days. First, we assessed FC reproducibility and reliability at baseline in six frequency bands. Then, we investigated the acute and delayed effects at day 1 after the first dose and at day 9, 1 day after the last dose, for all bands, resulting in a total of four fUS measurements for every mouse. Results We found reproducible (r > 0.9) and reliable (r > 0.9) group-average readouts in all frequency bands, only the 0.01-0.27 Hz band performing slightly worse. Acutely, S-ketamine induced strong FC increases in five of the six bands, peaking in the 0.073-0.2 Hz band. These increases comprised both cortical and subcortical brain areas, yet were of a transient nature, FC almost returning to baseline levels towards the end of the scan. Intriguingly, we observed robust corticostriatal FC decreases in the fastest band acquired (0.75 Hz-1.25 Hz). These changes persisted to a weaker extent after 1 day and at this timepoint they were accompanied by decreases in the other five bands as well. After 9 days, the decreases in the 0.75-1.25 Hz band were maintained, however no changes between cohorts could be detected in any other bands. Discussion In summary, the study reports that acute and delayed ketamine effects in mice are not only dissimilar but have different directionalities in most frequency bands. The complementary readouts of the employed frequency bands recommend the use of fUS for frequency-specific investigation of pharmacological effects on FC.
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Doyen M, Hossu G, Heyer S, Zaragori T, Imbert L, Verger A. Identification of resting-state networks using dynamic brain perfusion SPECT imaging: A fSPECT case report. Front Hum Neurosci 2023; 17:1125765. [PMID: 37151905 PMCID: PMC10157397 DOI: 10.3389/fnhum.2023.1125765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 03/21/2023] [Indexed: 05/09/2023] Open
Abstract
Connectivity studies with nuclear medicine systems are scarce in literature. They mainly employ PET imaging and group level analyses due to the low temporal resolution of PET and especially SPECT imaging. Our current study analyses connectivity at an individual level using dynamic SPECT imaging, which has been enabled by the improved temporal resolution performances provided by the 360°CZT cameras. We present the case of an 80-year-old man referred for brain perfusion SPECT imaging for cognitive disorders for whom a dynamic SPECT acquisition was performed utilizing a 360°CZT camera (temporal sampling of 15 frames × 3 s, 10 frames × 15 s, 14 frames × 30 s), followed by a conventional static acquisition of 15 m. Functional SPECT connectivity (fSPECT) was assessed through a seed correlation analysis and 5 well-known resting-state networks were identified: the executive, the default mode, the sensory motor, the salience, and the visual networks. This case report supports the feasibility of fSPECT imaging to identify well known resting-state networks, thanks to the novel properties of a 360°CZT camera, and opens the way to the development of more dedicated functional connectivity studies using brain perfusion SPECT imaging.
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Affiliation(s)
- Matthieu Doyen
- Department of Nuclear Medicine and Nancyclotep Imaging Platform, CHRU Nancy, Université de Lorraine, Nancy, France
- IADI, INSERM U1254, Université de Lorraine, Nancy, France
- *Correspondence: Matthieu Doyen,
| | - Gabriela Hossu
- IADI, INSERM U1254, Université de Lorraine, Nancy, France
- CHRU-Nancy, INSERM, CIC, Innovation Technologique, Université de Lorraine, Nancy, France
| | - Sébastien Heyer
- Department of Nuclear Medicine and Nancyclotep Imaging Platform, CHRU Nancy, Université de Lorraine, Nancy, France
| | | | - Laetitia Imbert
- Department of Nuclear Medicine and Nancyclotep Imaging Platform, CHRU Nancy, Université de Lorraine, Nancy, France
- IADI, INSERM U1254, Université de Lorraine, Nancy, France
| | - Antoine Verger
- Department of Nuclear Medicine and Nancyclotep Imaging Platform, CHRU Nancy, Université de Lorraine, Nancy, France
- IADI, INSERM U1254, Université de Lorraine, Nancy, France
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Nag S, Uludag K. Dynamic Effective Connectivity using Physiologically informed Dynamic Causal Model with Recurrent Units: A functional Magnetic Resonance Imaging simulation study. Front Hum Neurosci 2023; 17:1001848. [PMID: 36936613 PMCID: PMC10014816 DOI: 10.3389/fnhum.2023.1001848] [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: 07/24/2022] [Accepted: 01/25/2023] [Indexed: 03/05/2023] Open
Abstract
Functional MRI (fMRI) is an indirect reflection of neuronal activity. Using generative biophysical model of fMRI data such as Dynamic Causal Model (DCM), the underlying neuronal activities of different brain areas and their causal interactions (i.e., effective connectivity) can be calculated. Most DCM studies typically consider the effective connectivity to be static for a cognitive task within an experimental run. However, changes in experimental conditions during complex tasks such as movie-watching might result in temporal variations in the connectivity strengths. In this fMRI simulation study, we leverage state-of-the-art Physiologically informed DCM (P-DCM) along with a recurrent window approach and discretization of the equations to infer the underlying neuronal dynamics and concurrently the dynamic (time-varying) effective connectivities between various brain regions for task-based fMRI. Results from simulation studies on 3- and 10-region models showed that functional magnetic resonance imaging (fMRI) blood oxygenation level-dependent (BOLD) responses and effective connectivity time-courses can be accurately predicted and distinguished from faulty graphical connectivity models representing cognitive hypotheses. In summary, we propose and validate a novel approach to determine dynamic effective connectivity between brain areas during complex cognitive tasks by combining P-DCM with recurrent units.
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Affiliation(s)
- Sayan Nag
- Techna Institute & Koerner Scientist in MR Imaging, University Health Network, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- *Correspondence: Sayan Nag,
| | - Kamil Uludag
- Techna Institute & Koerner Scientist in MR Imaging, University Health Network, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea
- Kamil Uludag,
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Sjuls GS, Specht K. Variability in Resting-State Functional Magnetic Resonance Imaging: The Effect of Body Mass, Blood Pressure, Hematocrit, and Glycated Hemoglobin on Hemodynamic and Neuronal Parameters. Brain Connect 2022; 12:870-882. [PMID: 35473334 PMCID: PMC9807254 DOI: 10.1089/brain.2021.0125] [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] [Indexed: 01/13/2023] Open
Abstract
Introduction: Replicability has become an increasing focus within the scientific communities with the ongoing "replication crisis." One area that appears to struggle with unreliable results is resting-state functional magnetic resonance imaging (rs-fMRI). Therefore, the current study aimed at improving the knowledge of endogenous factors that contribute to inter-individual variability. Methods: Arterial blood pressure (BP), body mass, hematocrit, and glycated hemoglobin were investigated as potential sources of between-subject variability in rs-fMRI, in healthy individuals. Whether changes in resting-state networks (rs-networks) could be attributed to variability in the blood-oxygen-level-dependent (BOLD)-signal, changes in neuronal activity, or both was of special interest. Within-subject parameters were estimated by utilizing dynamic-causal modeling, as it allows to make inferences on the estimated hemodynamic (BOLD-signal dynamics) and neuronal parameters (effective connectivity) separately. Results: The results of the analyses imply that BP and body mass can cause between-subject and between-group variability in the BOLD-signal and that all the included factors can affect the underlying connectivity. Discussion: Given the results of the current and previous studies, rs-fMRI results appear to be susceptible to a range of factors, which is likely to contribute to the low degree of replicability of these studies. Interestingly, the highest degree of variability seems to appear within the much-studied default mode network and its connections to other networks. Impact statement We believe that thanks to the evidence that we have collected by analyzing the well-controlled data of the Human Connectome Project with dynamic-causal modeling (DCM) and by focusing not only on the effective connectivity, which is the typical way of using DCM, but also by analyzing the underlying hemodynamic parameters, we were able to explore the underlying vascular dependencies in a much broader perspective. Our results challenge the premise for studying changes in the default mode network as a clinical marker of disease, and we add to the growing list of factors that contribute to resting-state network variability.
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Affiliation(s)
- Guro Stensby Sjuls
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway.,Mohn Medical and Imaging Visualization Centre, Haukeland University Hospital, Bergen, Norway.,Language Acquisition and Language Processing Lab, Department of Language and Literature, Norwegian University of Science and Technology, Trondheim, Norway.,Address correspondence to: Guro Stensby Sjuls, Language Acquisition and Language Processing Lab, Department of Language and Literature, Norwegian University of Science and Technology, Trondheim 7491, Norway
| | - Karsten Specht
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway.,Mohn Medical and Imaging Visualization Centre, Haukeland University Hospital, Bergen, Norway.,Department of Education, UiT/The Arctic University of Norway, Tromsø, Norway
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Multi-Echo Investigations of Positive and Negative CBF and Concomitant BOLD Changes: Positive and negative CBF and BOLD changes. Neuroimage 2022; 263:119661. [PMID: 36198353 DOI: 10.1016/j.neuroimage.2022.119661] [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: 08/26/2022] [Revised: 09/27/2022] [Accepted: 09/30/2022] [Indexed: 11/21/2022] Open
Abstract
Unlike the positive blood oxygenation level-dependent (BOLD) response (PBR), commonly taken as an indication of an 'activated' brain region, the physiological origin of negative BOLD signal changes (i.e. a negative BOLD response, NBR), also referred to as 'deactivation' is still being debated. In this work, an attempt was made to gain a better understanding of the underlying mechanism by obtaining a comprehensive measure of the contributing cerebral blood flow (CBF) and its relationship to the NBR in the human visual cortex, in comparison to a simultaneously induced PBR in surrounding visual regions. To overcome the low signal-to-noise ratio (SNR) of CBF measurements, a newly developed multi-echo version of a center-out echo planar-imaging (EPI) readout was employed with pseudo-continuous arterial spin labeling (pCASL). It achieved very short echo and inter-echo times and facilitated a simultaneous detection of functional CBF and BOLD changes at 3 T with improved sensitivity. Evaluations of the absolute and relative changes of CBF and the effective transverse relaxation rate,R2* the coupling ratios, and their dependence on CBF at rest, CBFrest indicated differences between activated and deactivated regions. Analysis of the shape of the respective functional responses also revealed faster negative responses with more pronounced post-stimulus transients. Resulting differences in the flow-metabolism coupling ratios were further examined for potential distinctions in the underlying neuronal contributions.
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Chen JJ, Uthayakumar B, Hyder F. Mapping oxidative metabolism in the human brain with calibrated fMRI in health and disease. J Cereb Blood Flow Metab 2022; 42:1139-1162. [PMID: 35296177 PMCID: PMC9207484 DOI: 10.1177/0271678x221077338] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Conventional functional MRI (fMRI) with blood-oxygenation level dependent (BOLD) contrast is an important tool for mapping human brain activity non-invasively. Recent interest in quantitative fMRI has renewed the importance of oxidative neuroenergetics as reflected by cerebral metabolic rate of oxygen consumption (CMRO2) to support brain function. Dynamic CMRO2 mapping by calibrated fMRI require multi-modal measurements of BOLD signal along with cerebral blood flow (CBF) and/or volume (CBV). In human subjects this "calibration" is typically performed using a gas mixture containing small amounts of carbon dioxide and/or oxygen-enriched medical air, which are thought to produce changes in CBF (and CBV) and BOLD signal with minimal or no CMRO2 changes. However non-human studies have demonstrated that the "calibration" can also be achieved without gases, revealing good agreement between CMRO2 changes and underlying neuronal activity (e.g., multi-unit activity and local field potential). Given the simpler set-up of gas-free calibrated fMRI, there is evidence of recent clinical applications for this less intrusive direction. This up-to-date review emphasizes technological advances for such translational gas-free calibrated fMRI experiments, also covering historical progression of the calibrated fMRI field that is impacting neurological and neurodegenerative investigations of the human brain.
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Affiliation(s)
- J Jean Chen
- Medical Biophysics, University of Toronto, Toronto, Canada.,Rotman Research Institute, Baycrest, Toronto, Canada
| | - Biranavan Uthayakumar
- Medical Biophysics, University of Toronto, Toronto, Canada.,Sunnybrook Research Institute, Toronto, Canada
| | - Fahmeed Hyder
- Magnetic Resonance Research Center (MRRC), Yale University, New Haven, Connecticut, USA.,Department of Radiology, Yale University, New Haven, Connecticut, USA.,Quantitative Neuroscience with Magnetic Resonance (QNMR) Research Program, Yale University, New Haven, Connecticut, USA.,Department of Biomedical Engineering, Yale University, New Haven, Connecticut, USA
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Hakim U, Pinti P, Noah AJ, Zhang X, Burgess P, Hamilton A, Hirsch J, Tachtsidis I. Investigation of functional near-infrared spectroscopy signal quality and development of the hemodynamic phase correlation signal. NEUROPHOTONICS 2022; 9:025001. [PMID: 35599691 PMCID: PMC9116886 DOI: 10.1117/1.nph.9.2.025001] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 04/13/2022] [Indexed: 06/15/2023]
Abstract
Significance: There is a longstanding recommendation within the field of fNIRS to use oxygenated (HbO 2 ) and deoxygenated (HHb) hemoglobin when analyzing and interpreting results. Despite this, many fNIRS studies do focus onHbO 2 only. Previous work has shown thatHbO 2 on its own is susceptible to systemic interference and results may mostly reflect that rather than functional activation. Studies using bothHbO 2 and HHb to draw their conclusions do so with varying methods and can lead to discrepancies between studies. The combination ofHbO 2 and HHb has been recommended as a method to utilize both signals in analysis. Aim: We present the development of the hemodynamic phase correlation (HPC) signal to combineHbO 2 and HHb as recommended to utilize both signals in the analysis. We use synthetic and experimental data to evaluate how the HPC and current signals used for fNIRS analysis compare. Approach: About 18 synthetic datasets were formed using resting-state fNIRS data acquired from 16 channels over the frontal lobe. To simulate fNIRS data for a block-design task, we superimposed a synthetic task-related hemodynamic response to the resting state data. This data was used to develop an HPC-general linear model (GLM) framework. Experiments were conducted to investigate the performance of each signal at different SNR and to investigate the effect of false positives on the data. Performance was based on each signal's mean T -value across channels. Experimental data recorded from 128 participants across 134 channels during a finger-tapping task were used to investigate the performance of multiple signals [HbO 2 , HHb, HbT, HbD, correlation-based signal improvement (CBSI), and HPC] on real data. Signal performance was evaluated on its ability to localize activation to a specific region of interest. Results: Results from varying the SNR show that the HPC signal has the highest performance for high SNRs. The CBSI performed the best for medium-low SNR. The next analysis evaluated how false positives affect the signals. The analyses evaluating the effect of false positives showed that the HPC and CBSI signals reflect the effect of false positives onHbO 2 and HHb. The analysis of real experimental data revealed that the HPC and HHb signals provide localization to the primary motor cortex with the highest accuracy. Conclusions: We developed a new hemodynamic signal (HPC) with the potential to overcome the current limitations of usingHbO 2 and HHb separately. Our results suggest that the HPC signal provides comparable accuracy to HHb to localize functional activation while at the same time being more robust against false positives.
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Affiliation(s)
- Uzair Hakim
- University College London, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Paola Pinti
- University College London, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
- University of London, Birkbeck College, Centre for Brain and Cognitive Development, London, United Kingdom
| | - Adam J. Noah
- Yale University, Department of Neuroscience and Comparative Medicine, Yale School of Medicine, United States
| | - Xian Zhang
- Yale University, Department of Neuroscience and Comparative Medicine, Yale School of Medicine, United States
| | - Paul Burgess
- University College London, Institute of Cognitive Neuroscience, London, United Kingdom
| | - Antonia Hamilton
- University College London, Institute of Cognitive Neuroscience, London, United Kingdom
| | - Joy Hirsch
- University College London, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
- Yale University, Department of Neuroscience and Comparative Medicine, Yale School of Medicine, United States
| | - Ilias Tachtsidis
- University College London, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
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Maith O, Dinkelbach HÜ, Baladron J, Vitay J, Hamker FH. BOLD Monitoring in the Neural Simulator ANNarchy. Front Neuroinform 2022; 16:790966. [PMID: 35392282 PMCID: PMC8981038 DOI: 10.3389/fninf.2022.790966] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 02/08/2022] [Indexed: 01/13/2023] Open
Abstract
Multi-scale network models that simultaneously simulate different measurable signals at different spatial and temporal scales, such as membrane potentials of single neurons, population firing rates, local field potentials, and blood-oxygen-level-dependent (BOLD) signals, are becoming increasingly popular in computational neuroscience. The transformation of the underlying simulated neuronal activity of these models to simulated non-invasive measurements, such as BOLD signals, is particularly relevant. The present work describes the implementation of a BOLD monitor within the neural simulator ANNarchy to allow an on-line computation of simulated BOLD signals from neural network models. An active research topic regarding the simulation of BOLD signals is the coupling of neural processes to cerebral blood flow (CBF) and cerebral metabolic rate of oxygen (CMRO2). The flexibility of ANNarchy allows users to define this coupling with a high degree of freedom and thus, not only allows to relate mesoscopic network models of populations of spiking neurons to experimental BOLD data, but also to investigate different hypotheses regarding the coupling between neural processes, CBF and CMRO2 with these models. In this study, we demonstrate how simulated BOLD signals can be obtained from a network model consisting of multiple spiking neuron populations. We first demonstrate the use of the Balloon model, the predominant model for simulating BOLD signals, as well as the possibility of using novel user-defined models, such as a variant of the Balloon model with separately driven CBF and CMRO2 signals. We emphasize how different hypotheses about the coupling between neural processes, CBF and CMRO2 can be implemented and how these different couplings affect the simulated BOLD signals. With the BOLD monitor presented here, ANNarchy provides a tool for modelers who want to relate their network models to experimental MRI data and for scientists who want to extend their studies of the coupling between neural processes and the BOLD signal by using modeling approaches. This facilitates the investigation and model-based analysis of experimental BOLD data and thus improves multi-scale understanding of neural processes in humans.
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13
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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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14
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Wu GR, Colenbier N, Van Den Bossche S, Clauw K, Johri A, Tandon M, Marinazzo D. rsHRF: A toolbox for resting-state HRF estimation and deconvolution. Neuroimage 2021; 244:118591. [PMID: 34560269 DOI: 10.1016/j.neuroimage.2021.118591] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 06/25/2021] [Accepted: 09/16/2021] [Indexed: 10/20/2022] Open
Abstract
The hemodynamic response function (HRF) greatly influences the intra- and inter-subject variability of brain activation and connectivity, and might confound the estimation of temporal precedence in connectivity analyses, making its estimation necessary for a correct interpretation of neuroimaging studies. Additionally, the HRF shape itself is a useful local measure. However, most algorithms for HRF estimation are specific for task-related fMRI data, and only a few can be directly applied to resting-state protocols. Here we introduce rsHRF, a Matlab and Python toolbox that implements HRF estimation and deconvolution from the resting-state BOLD signal. We first provide an overview of the main algorithm, practical implementations, and then demonstrate the feasibility and usefulness of rsHRF by validation experiments with a publicly available resting-state fMRI dataset. We also provide tools for statistical analyses and visualization. We believe that this toolbox may significantly contribute to a better analysis and understanding of the components and variability of BOLD signals.
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Affiliation(s)
- Guo-Rong Wu
- Key Laboratory of Cognition and Personality, Faculty of Psychology, Southwest University, Chongqing 400715, China; Department of Data Analysis, Faculty of Psychology and Educational Sciences, Ghent University, Ghent 9000, Belgium.
| | - Nigel Colenbier
- Department of Data Analysis, Faculty of Psychology and Educational Sciences, Ghent University, Ghent 9000, Belgium; Research Center for Motor Control and Neuroplasticity, KU Leuven, Leuven 3001, Belgium; Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, Venice 30126, Italy
| | - Sofie Van Den Bossche
- Department of Data Analysis, Faculty of Psychology and Educational Sciences, Ghent University, Ghent 9000, Belgium
| | - Kenzo Clauw
- Department of Data Analysis, Faculty of Psychology and Educational Sciences, Ghent University, Ghent 9000, Belgium
| | - Amogh Johri
- International Institute of Information Technology, Bangalore 560100, India
| | - Madhur Tandon
- Indraprastha Institute of Information Technology, Delhi 110020, India
| | - Daniele Marinazzo
- Department of Data Analysis, Faculty of Psychology and Educational Sciences, Ghent University, Ghent 9000, Belgium; Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, Venice 30126, Italy
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15
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Cai Z, Uji M, Aydin Ü, Pellegrino G, Spilkin A, Delaire É, Abdallah C, Lina J, Grova C. Evaluation of a personalized functional near infra-red optical tomography workflow using maximum entropy on the mean. Hum Brain Mapp 2021; 42:4823-4843. [PMID: 34342073 PMCID: PMC8449120 DOI: 10.1002/hbm.25566] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 05/25/2021] [Accepted: 06/11/2021] [Indexed: 11/20/2022] Open
Abstract
In the present study, we proposed and evaluated a workflow of personalized near infra-red optical tomography (NIROT) using functional near-infrared spectroscopy (fNIRS) for spatiotemporal imaging of cortical hemodynamic fluctuations. The proposed workflow from fNIRS data acquisition to local 3D reconstruction consists of: (a) the personalized optimal montage maximizing fNIRS channel sensitivity to a predefined targeted brain region; (b) the optimized fNIRS data acquisition involving installation of optodes and digitalization of their positions using a neuronavigation system; and (c) the 3D local reconstruction using maximum entropy on the mean (MEM) to accurately estimate the location and spatial extent of fNIRS hemodynamic fluctuations along the cortical surface. The workflow was evaluated on finger-tapping fNIRS data acquired from 10 healthy subjects for whom we estimated the reconstructed NIROT spatiotemporal images and compared with functional magnetic resonance imaging (fMRI) results from the same individuals. Using the fMRI activation maps as our reference, we quantitatively compared the performance of two NIROT approaches, the MEM framework and the conventional minimum norm estimation (MNE) method. Quantitative comparisons were performed at both single subject and group-level. Overall, our results suggested that MEM provided better spatial accuracy than MNE, while both methods offered similar temporal accuracy when reconstructing oxygenated (HbO) and deoxygenated hemoglobin (HbR) concentration changes evoked by finger-tapping. Our proposed complete workflow was made available in the brainstorm fNIRS processing plugin-NIRSTORM, thus providing the opportunity for other researchers to further apply it to other tasks and on larger populations.
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Affiliation(s)
- Zhengchen Cai
- Multimodal Functional Imaging Lab, Department of Physics and PERFORM CentreConcordia UniversityMontréalQuébecCanada
| | - Makoto Uji
- Multimodal Functional Imaging Lab, Department of Physics and PERFORM CentreConcordia UniversityMontréalQuébecCanada
| | - Ümit Aydin
- Multimodal Functional Imaging Lab, Department of Physics and PERFORM CentreConcordia UniversityMontréalQuébecCanada
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
| | - Giovanni Pellegrino
- Neurology and Neurosurgery Department, Montreal Neurological InstituteMcGill UniversityMontréalQuébecCanada
- Multimodal Functional Imaging Lab, Biomedical Engineering DepartmentMcGill UniversityMontréalQuébecCanada
| | - Amanda Spilkin
- Multimodal Functional Imaging Lab, Department of Physics and PERFORM CentreConcordia UniversityMontréalQuébecCanada
| | - Édouard Delaire
- Multimodal Functional Imaging Lab, Department of Physics and PERFORM CentreConcordia UniversityMontréalQuébecCanada
| | - Chifaou Abdallah
- Neurology and Neurosurgery Department, Montreal Neurological InstituteMcGill UniversityMontréalQuébecCanada
- Multimodal Functional Imaging Lab, Biomedical Engineering DepartmentMcGill UniversityMontréalQuébecCanada
| | - Jean‐Marc Lina
- Département de Génie ElectriqueÉcole de Technologie SupérieureMontréalQuébecCanada
- Centre De Recherches En MathématiquesMontréalQuébecCanada
| | - Christophe Grova
- Multimodal Functional Imaging Lab, Department of Physics and PERFORM CentreConcordia UniversityMontréalQuébecCanada
- Neurology and Neurosurgery Department, Montreal Neurological InstituteMcGill UniversityMontréalQuébecCanada
- Multimodal Functional Imaging Lab, Biomedical Engineering DepartmentMcGill UniversityMontréalQuébecCanada
- Centre De Recherches En MathématiquesMontréalQuébecCanada
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16
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Si X, Li S, Xiang S, Yu J, Ming D. Imagined speech increases the hemodynamic response and functional connectivity of the dorsal motor cortex. J Neural Eng 2021; 18. [PMID: 34507311 DOI: 10.1088/1741-2552/ac25d9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 09/10/2021] [Indexed: 11/12/2022]
Abstract
Objective. Decoding imagined speech from brain signals could provide a more natural, user-friendly way for developing the next generation of the brain-computer interface (BCI). With the advantages of non-invasive, portable, relatively high spatial resolution and insensitivity to motion artifacts, the functional near-infrared spectroscopy (fNIRS) shows great potential for developing the non-invasive speech BCI. However, there is a lack of fNIRS evidence in uncovering the neural mechanism of imagined speech. Our goal is to investigate the specific brain regions and the corresponding cortico-cortical functional connectivity features during imagined speech with fNIRS.Approach. fNIRS signals were recorded from 13 subjects' bilateral motor and prefrontal cortex during overtly and covertly repeating words. Cortical activation was determined through the mean oxygen-hemoglobin concentration changes, and functional connectivity was calculated by Pearson's correlation coefficient.Main results. (a) The bilateral dorsal motor cortex was significantly activated during the covert speech, whereas the bilateral ventral motor cortex was significantly activated during the overt speech. (b) As a subregion of the motor cortex, sensorimotor cortex (SMC) showed a dominant dorsal response to covert speech condition, whereas a dominant ventral response to overt speech condition. (c) Broca's area was deactivated during the covert speech but activated during the overt speech. (d) Compared to overt speech, dorsal SMC(dSMC)-related functional connections were enhanced during the covert speech.Significance. We provide fNIRS evidence for the involvement of dSMC in speech imagery. dSMC is the speech imagery network's key hub and is probably involved in the sensorimotor information processing during the covert speech. This study could inspire the BCI community to focus on the potential contribution of dSMC during speech imagery.
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Affiliation(s)
- Xiaopeng Si
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, People's Republic of China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, People's Republic of China.,Tianjin International Engineering Institute, Tianjin University, Tianjin 300072, People's Republic of China.,Institute of Applied Psychology, Tianjin University, Tianjin 300350, People's Republic of China
| | - Sicheng Li
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, People's Republic of China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, People's Republic of China
| | - Shaoxin Xiang
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, People's Republic of China.,Tianjin International Engineering Institute, Tianjin University, Tianjin 300072, People's Republic of China
| | - Jiayue Yu
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, People's Republic of China.,Tianjin International Engineering Institute, Tianjin University, Tianjin 300072, People's Republic of China
| | - Dong Ming
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, People's Republic of China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, People's Republic of China
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17
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Stout JN, Liao C, Gagoski B, Turk EA, Feldman HA, Bibbo C, Barth WH, Shainker SA, Wald LL, Grant PE, Adalsteinsson E. Quantitative T 1 and T 2 mapping by magnetic resonance fingerprinting (MRF) of the placenta before and after maternal hyperoxia. Placenta 2021; 114:124-132. [PMID: 34537569 DOI: 10.1016/j.placenta.2021.08.058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 06/16/2021] [Accepted: 08/05/2021] [Indexed: 11/13/2022]
Abstract
INTRODUCTION MR relaxometry has been used to assess placental exchange function, but methods to date are not sufficiently fast to be robust to placental motion. Magnetic resonance fingerprinting (MRF) permits rapid, voxel-wise, intrinsically co-registered T1 and T2 mapping. After characterizing measurement error, we scanned pregnant women during air and oxygen breathing to demonstrate MRF's ability to detect placental oxygenation changes. METHODS The accuracy of FISP-based, sliding-window reconstructed MRF was tested on phantoms. MRF scans in 9-s breath holds were acquired at 3T in 31 pregnant women during air and oxygen breathing. A mixed effects model was used to test for changes in placenta relaxation times between physiological states, to assess the dependency on gestational age (GA), and the impact of placental motion. RESULTS MRF estimates of known phantom relaxation times resulted in mean absolute errors for T1 of 92 ms (4.8%), but T2 was less accurate at 16 ms (13.6%). During normoxia, placental T1 = 1825 ± 141 ms (avg ± standard deviation) and T2 = 60 ± 16 ms (gestational age range 24.3-36.7, median 32.6 weeks). In the statistical model, placental T2 rose and T1 remained contant after hyperoxia, and no GA dependency was observed for T1 or T2. DISCUSSION Well-characterized, motion-robust MRF was used to acquire T1 and T2 maps of the placenta. Changes with hyperoxia are consistent with a net increase in oxygen saturation. Toward the goal of whole-placenta quantitative oxygenation imaging over time, we aim to implement 3D MRF with integrated motion correction to improve T2 accuracy.
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Affiliation(s)
- Jeffrey N Stout
- Fetal and Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, 02115, USA.
| | - Congyu Liao
- Department of Radiology, Stanford University, Stanford, CA, 94305, USA
| | - Borjan Gagoski
- Fetal and Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, 02115, USA
| | - Esra Abaci Turk
- Fetal and Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, 02115, USA
| | - Henry A Feldman
- Centers for Clinical and Translational Research, Boston Children's Hospital, Boston, MA, 02115, USA
| | - Carolina Bibbo
- Brigham and Women's Hospital, Division of Maternal-Fetal Medicine, Boston, MA, 02115, USA
| | - William H Barth
- Maternal-Fetal Medicine, Obstetrics and Gynecology, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Scott A Shainker
- Maternal-Fetal Medicine, Obstetrics and Gynecology, Beth Israel Deaconess Medical Center, Boston, MA, 02115, USA
| | - Lawrence L Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, 02129, USA
| | - P Ellen Grant
- Fetal and Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, 02115, USA
| | - Elfar Adalsteinsson
- Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA; Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
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18
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Imaging faster neural dynamics with fast fMRI: A need for updated models of the hemodynamic response. Prog Neurobiol 2021; 207:102174. [PMID: 34525404 DOI: 10.1016/j.pneurobio.2021.102174] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2020] [Revised: 07/30/2021] [Accepted: 09/08/2021] [Indexed: 12/20/2022]
Abstract
Fast fMRI enables the detection of neural dynamics over timescales of hundreds of milliseconds, suggesting it may provide a new avenue for studying subsecond neural processes in the human brain. The magnitudes of these fast fMRI dynamics are far greater than predicted by canonical models of the hemodynamic response. Several studies have established nonlinear properties of the hemodynamic response that have significant implications for fast fMRI. We first review nonlinear properties of the hemodynamic response function that may underlie fast fMRI signals. We then illustrate the breakdown of canonical hemodynamic response models in the context of fast neural dynamics. We will then argue that the canonical hemodynamic response function is not likely to reflect the BOLD response to neuronal activity driven by sparse or naturalistic stimuli or perhaps to spontaneous neuronal fluctuations in the resting state. These properties suggest that fast fMRI is capable of tracking surprisingly fast neuronal dynamics, and we discuss the neuroscientific questions that could be addressed using this approach.
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19
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Geerts H, Roberts P, Spiros A. Exploring the relation between BOLD fMRI and cognitive performance using a computer-based quantitative systems pharmacology model: Applications to the COMTVAL158MET genotype and ketamine. Eur Neuropsychopharmacol 2021; 50:12-22. [PMID: 33951587 DOI: 10.1016/j.euroneuro.2021.04.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Revised: 03/14/2021] [Accepted: 04/06/2021] [Indexed: 10/21/2022]
Abstract
BOLD fMRI is increasingly used mostly in an observational way to probe the effect of genotypes or therapeutic intervention in normal and diseased subjects. We use a mechanism-based quantitative systems pharmacology computer model of a human cortical microcircuit, previously calibrated for the 2-back working memory paradigm, adding established biophysical principles, of glucose metabolism, oxygen consumption, neurovascular effects and the paramagnetic impact on blood oxygen levels to calculate a readout for the voxel-based BOLD fMRI signal. The objective was to study the effect of the Catechol-O-methyl Transferase Val158Met (COMT) genotype on performance and BOLD fMRI. While the simulation suggests that on average virtual COMTVV genotype subjects perform worse, subjects with lower GABA, lower 5-HT3 and higher 5-HT1A activation can improve cognitive performance to the level of COMTMM subjects but at the expense of higher BOLD fMRI signal. In a schizophrenia condition, increased NMDA, GABA tone and noise levels, and lower D1R activity can improve cognitive outcome with greater BOLD fMRI signal in COMT Val-carriers. We further generate hypotheses about why ketamine in healthy controls increases the BOLD fMRI signal but reduces cognitive performance. These simulations suggest a strong non-linear relationship between BOLD fMRI signal and cognitive performance. When validated, this mechanistic approach can be useful for moving beyond the descriptive nature of BOLD fMRI imaging and supporting the proper interpretation of imaging biomarkers in CNS disorders.
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Affiliation(s)
- Hugo Geerts
- In Silico Biosciences, Hugo Geerts, 686 Westwind Dr, Berwyn, PA 19312, United States.
| | - Patrick Roberts
- In Silico Biosciences, Hugo Geerts, 686 Westwind Dr, Berwyn, PA 19312, United States
| | - Athan Spiros
- In Silico Biosciences, Hugo Geerts, 686 Westwind Dr, Berwyn, PA 19312, United States
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20
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Salch A, Regalski A, Abdallah H, Suryadevara R, Catanzaro MJ, Diwadkar VA. From mathematics to medicine: A practical primer on topological data analysis (TDA) and the development of related analytic tools for the functional discovery of latent structure in fMRI data. PLoS One 2021; 16:e0255859. [PMID: 34383838 PMCID: PMC8360597 DOI: 10.1371/journal.pone.0255859] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2021] [Accepted: 07/23/2021] [Indexed: 11/19/2022] Open
Abstract
fMRI is the preeminent method for collecting signals from the human brain in vivo, for using these signals in the service of functional discovery, and relating these discoveries to anatomical structure. Numerous computational and mathematical techniques have been deployed to extract information from the fMRI signal. Yet, the application of Topological Data Analyses (TDA) remain limited to certain sub-areas such as connectomics (that is, with summarized versions of fMRI data). While connectomics is a natural and important area of application of TDA, applications of TDA in the service of extracting structure from the (non-summarized) fMRI data itself are heretofore nonexistent. “Structure” within fMRI data is determined by dynamic fluctuations in spatially distributed signals over time, and TDA is well positioned to help researchers better characterize mass dynamics of the signal by rigorously capturing shape within it. To accurately motivate this idea, we a) survey an established method in TDA (“persistent homology”) to reveal and describe how complex structures can be extracted from data sets generally, and b) describe how persistent homology can be applied specifically to fMRI data. We provide explanations for some of the mathematical underpinnings of TDA (with expository figures), building ideas in the following sequence: a) fMRI researchers can and should use TDA to extract structure from their data; b) this extraction serves an important role in the endeavor of functional discovery, and c) TDA approaches can complement other established approaches toward fMRI analyses (for which we provide examples). We also provide detailed applications of TDA to fMRI data collected using established paradigms, and offer our software pipeline for readers interested in emulating our methods. This working overview is both an inter-disciplinary synthesis of ideas (to draw researchers in TDA and fMRI toward each other) and a detailed description of methods that can motivate collaborative research.
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Affiliation(s)
- Andrew Salch
- Department of Mathematics, Wayne State University, Detroit, Michigan, United States of America
- * E-mail: (AS); (AR); (HA)
| | - Adam Regalski
- Department of Mathematics, Wayne State University, Detroit, Michigan, United States of America
- * E-mail: (AS); (AR); (HA)
| | - Hassan Abdallah
- Department of Mathematics, Wayne State University, Detroit, Michigan, United States of America
- * E-mail: (AS); (AR); (HA)
| | - Raviteja Suryadevara
- Department of Mathematics, Wayne State University, Detroit, Michigan, United States of America
- Department of Psychiatry & Behavioral Neuroscience, Wayne State University, Detroit, Michigan, United States of America
| | - Michael J. Catanzaro
- Department of Mathematics, Iowa State University, Ames, Iowa, United States of America
| | - Vaibhav A. Diwadkar
- Department of Psychiatry & Behavioral Neuroscience, Wayne State University, Detroit, Michigan, United States of America
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21
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Varfolomeev SD, Bykov VI, Semenova NA, Tsybenova SB. Dynamics of the Multipathway Regulation of the Vasodilator Bold Effect Induced by a Nerve Impulse: A Kinetic Model of the Neurovascular Coupling Process. ACS Chem Neurosci 2021; 12:2202-2208. [PMID: 34096262 DOI: 10.1021/acschemneuro.1c00214] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
A kinetic model of the dynamics of a multipathway mechanism of neurovascular coupling induced by nerve impulses was constructed. The model calculations were compared with experimental data on the changes in the blood oxygen level dependent signal during sensory-motor and visual excitation before and after the use of the nonsteroidal anti-inflammatory drug indomethacin. The influence of the catalytic activity of key enzymes on the dynamics of the neurovascular response in the proposed model is shown. The multipathway mechanism of the biochemical reactions provides stability of the neurovascular coupling during various possible catalytic activities of the key enzymes in the process.
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Affiliation(s)
- Sergey D. Varfolomeev
- Institute of Physical and Chemical Grounds of Neuronet Functions and Artificial Intelligence, Lomonosov Moscow State University, Moscow 119991, Russia
- Department of Chemistry, Lomonosov Moscow State University, Moscow 119991, Russia
- Emanuel Institute of Biochemical Physics, Moscow 119334, Russia
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22
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Demidenko MI, Weigard AS, Ganesan K, Jang H, Jahn A, Huntley ED, Keating DP. Interactions between methodological and interindividual variability: How Monetary Incentive Delay (MID) task contrast maps vary and impact associations with behavior. Brain Behav 2021; 11:e02093. [PMID: 33750042 PMCID: PMC8119872 DOI: 10.1002/brb3.2093] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Revised: 02/01/2021] [Accepted: 02/05/2021] [Indexed: 12/28/2022] Open
Abstract
INTRODUCTION Phenomena related to reward responsiveness have been extensively studied in their associations with substance use and socioemotional functioning. One important task in this literature is the Monetary Incentive Delay (MID) task. By cueing and delivering performance-contingent reward, the MID task has been demonstrated to elicit robust activation of neural circuits involved in different phases of reward responsiveness. However, systematic evaluations of common MID task contrasts have been limited to between-study comparisons of group-level activation maps, limiting their ability to directly evaluate how researchers' choice of contrasts impacts conclusions about individual differences in reward responsiveness or brain-behavior associations. METHODS In a sample of 104 participants (Age Mean = 19.3, SD = 1.3), we evaluate similarities and differences between contrasts in: group- and individual-level activation maps using Jaccard's similarity index, region of interest (ROI) mean signal intensities using Pearson's r, and associations between ROI mean signal intensity and psychological measures using Bayesian correlation. RESULTS Our findings demonstrate more similarities than differences between win and loss cues during the anticipation contrast, dissimilarity between some win anticipation contrasts, an apparent deactivation effect in the outcome phase, likely stemming from the blood oxygen level-dependent undershoot, and behavioral associations that are less robust than previously reported. CONCLUSION Consistent with recent empirical findings, this work has practical implications for helping researchers interpret prior MID studies and make more informed a priori decisions about how their contrast choices may modify results.
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Affiliation(s)
| | - Alexander S Weigard
- Department of Psychology, University of Michigan, Ann Arbor, MI, USA.,Addiction Center, Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | | | - Hyesue Jang
- Department of Psychology, University of Michigan, Ann Arbor, MI, USA
| | - Andrew Jahn
- The Functional MRI Laboratory, University of Michigan, Ann Arbor, MI, USA
| | - Edward D Huntley
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Daniel P Keating
- Department of Psychology, University of Michigan, Ann Arbor, MI, USA.,Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
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23
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Ionescu TM, Amend M, Hafiz R, Biswal BB, Wehrl HF, Herfert K, Pichler BJ. Elucidating the complementarity of resting-state networks derived from dynamic [ 18F]FDG and hemodynamic fluctuations using simultaneous small-animal PET/MRI. Neuroimage 2021; 236:118045. [PMID: 33848625 PMCID: PMC8339191 DOI: 10.1016/j.neuroimage.2021.118045] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 03/15/2021] [Accepted: 04/04/2021] [Indexed: 12/02/2022] Open
Abstract
Functional connectivity (FC) and resting-state network (RSN) analyses using functional magnetic resonance imaging (fMRI) have evolved into a growing field of research and have provided useful biomarkers for the assessment of brain function in neurological disorders. However, the underlying mechanisms of the blood oxygen level-dependant (BOLD) signal are not fully resolved due to its inherent complexity. In contrast, [18F]fluorodeoxyglucose positron emission tomography ([18F]FDG-PET) has been shown to provide a more direct measure of local synaptic activity and may have additional value for the readout and interpretation of brain connectivity. We performed an RSN analysis from simultaneously acquired PET/fMRI data on a single-subject level to directly compare fMRI and [18F]FDG-PET-derived networks during the resting state. Simultaneous [18F]FDG-PET/fMRI scans were performed in 30 rats. Pairwise correlation analysis, as well as independent component analysis (ICA), were used to compare the readouts of both methods. We identified three RSNs with a high degree of similarity between PET and fMRI-derived readouts: the default-mode-like network (DMN), the basal ganglia network and the cerebellar-midbrain network. Overall, [18F]FDG connectivity indicated increased integration between different, often distant, brain areas compared to the results indicated by the more segregated fMRI-derived FC. Additionally, several networks exclusive to either modality were observed using ICA. These networks included mainly bilateral cortical networks of a limited spatial extent for fMRI and more spatially widespread networks for [18F]FDG-PET, often involving several subcortical areas. This is the first study using simultaneous PET/fMRI to report RSNs subject-wise from dynamic [18F]FDG tracer delivery and BOLD fluctuations with both independent component analysis (ICA) and pairwise correlation analysis in small animals. Our findings support previous studies, which show a close link between local synaptic glucose consumption and BOLD-fMRI-derived FC. However, several brain regions were exclusively attributed to either [18F]FDG or BOLD-derived networks underlining the complementarity of this hybrid imaging approach, which may contribute to the understanding of brain functional organization and could be of interest for future clinical applications.
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Affiliation(s)
- Tudor M Ionescu
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tuebingen, Tuebingen, Germany
| | - Mario Amend
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tuebingen, Tuebingen, Germany
| | - Rakibul Hafiz
- Department of Biomedical Engineering, New Jersey Institute of Technology, University Heights, Newark, NJ, United States
| | - Bharat B Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology, University Heights, Newark, NJ, United States
| | - Hans F Wehrl
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tuebingen, Tuebingen, Germany
| | - Kristina Herfert
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tuebingen, Tuebingen, Germany
| | - Bernd J Pichler
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tuebingen, Tuebingen, Germany.
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24
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Valdés BA, Lajoie K, Marigold DS, Menon C. Cortical Effects of Noisy Galvanic Vestibular Stimulation Using Functional Near-Infrared Spectroscopy. SENSORS 2021; 21:s21041476. [PMID: 33672519 PMCID: PMC7923808 DOI: 10.3390/s21041476] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/09/2021] [Revised: 02/03/2021] [Accepted: 02/16/2021] [Indexed: 11/25/2022]
Abstract
Noisy galvanic vestibular stimulation (nGVS) can improve different motor, sensory, and cognitive behaviors. However, it is unclear how this stimulation affects brain activity to facilitate these improvements. Functional near-infrared spectroscopy (fNIRS) is inexpensive, portable, and less prone to motion artifacts than other neuroimaging technology. Thus, fNIRS has the potential to provide insight into how nGVS affects cortical activity during a variety of natural behaviors. Here we sought to: (1) determine if fNIRS can detect cortical changes in oxygenated (HbO) and deoxygenated (HbR) hemoglobin with application of subthreshold nGVS, and (2) determine how subthreshold nGVS affects this fNIRS-derived hemodynamic response. A total of twelve healthy participants received nGVS and sham stimulation during a seated, resting-state paradigm. To determine whether nGVS altered activity in select cortical regions of interest (BA40, BA39), we compared differences between nGVS and sham HbO and HbR concentrations. We found a greater HbR response during nGVS compared to sham stimulation in left BA40, a region previously associated with vestibular processing, and with all left hemisphere channels combined (p < 0.05). We did not detect differences in HbO responses for any region during nGVS (p > 0.05). Our results suggest that fNIRS may be suitable for understanding the cortical effects of nGVS.
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Affiliation(s)
- Bulmaro A. Valdés
- Menrva Research Group, Schools of Mechatronic Systems and Engineering Science, Simon Fraser University, 250-13450 102nd Avenue, Surrey, BC V5A 1S6, Canada; (B.A.V.); (K.L.)
| | - Kim Lajoie
- Menrva Research Group, Schools of Mechatronic Systems and Engineering Science, Simon Fraser University, 250-13450 102nd Avenue, Surrey, BC V5A 1S6, Canada; (B.A.V.); (K.L.)
| | - Daniel S. Marigold
- Sensorimotor Neuroscience Lab, Department of Biomedical Physiology and Kinesiology, Simon Fraser University, 8888 University Drive, Burnaby, BC V5A 1S6, Canada;
| | - Carlo Menon
- Menrva Research Group, Schools of Mechatronic Systems and Engineering Science, Simon Fraser University, 250-13450 102nd Avenue, Surrey, BC V5A 1S6, Canada; (B.A.V.); (K.L.)
- Biomedical and Mobile Health Technology Laboratory, Department of Health Sciences and Technology, ETH Zurich, 8008 Zurich, Switzerland
- Correspondence:
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25
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Wang L, Li C, Chen D, Lv X, Go R, Wu J, Yan T. Hemodynamic response varies across tactile stimuli with different temporal structures. Hum Brain Mapp 2020; 42:587-597. [PMID: 33169898 PMCID: PMC7814760 DOI: 10.1002/hbm.25243] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 10/01/2020] [Accepted: 10/03/2020] [Indexed: 11/23/2022] Open
Abstract
Tactile stimuli can be distinguished based on their temporal features (e.g., duration, local frequency, and number of pulses), which are fundamental for vibrotactile frequency perception. Characterizing how the hemodynamic response changes in shape across experimental conditions is important for designing and interpreting fMRI studies on tactile information processing. In this study, we focused on periodic tactile stimuli with different temporal structures and explored the hemodynamic response function (HRF) induced by these stimuli. We found that HRFs were stimulus‐dependent in tactile‐related brain areas. Continuous stimuli induced a greater area of activation and a stronger and narrower hemodynamic response than intermittent stimuli with the same duration. The magnitude of the HRF increased with increasing stimulus duration. By normalizing the characteristics into topographic matrix, nonlinearity was obvious. These results suggested that stimulation patterns and duration within a cycle may be key characters for distinguishing different stimuli. We conclude that different temporal structures of tactile stimuli induced different HRFs, which are essential for vibrotactile perception and should be considered in fMRI experimental designs and analyses.
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Affiliation(s)
- Luyao Wang
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China.,Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing, China
| | - Chunlin Li
- School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Duanduan Chen
- School of Life Science, Beijing Institute of Technology, Beijing, China
| | - Xiaoyu Lv
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China.,Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing, China
| | - Ritsu Go
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China.,Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing, China
| | - Jinglong Wu
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China.,Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing, China.,Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama, Japan
| | - Tianyi Yan
- School of Life Science, Beijing Institute of Technology, Beijing, China.,Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing, China
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26
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Chen X, Song X, Chen L, An X, Ming D. Performance Improvement for Detecting Brain Function Using fNIRS: A Multi-Distance Probe Configuration With PPL Method. Front Hum Neurosci 2020; 14:569508. [PMID: 33240063 PMCID: PMC7677412 DOI: 10.3389/fnhum.2020.569508] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 09/25/2020] [Indexed: 11/25/2022] Open
Abstract
To improve the spatial resolution of imaging and get more effective brain function information, a multi-distance probe configuration with three distances (28.2, 40, and 44.7 mm) and 52 channels is designed. At the same time, a data conversion method of modified Beer–Lambert law (MBLL) with partial pathlength (PPL) is proposed. In the experiment, three kinds of tasks, grip of left hand, grip of right hand, and rest, are performed with eight healthy subjects. First, with a typical single-distance probe configuration (30 mm, 24 channels), the feasibility of the proposed MBLL with PPL is preliminarily validated. Further, the characteristic of the proposed method is evaluated with the multi-distance probe configuration. Compared with MBLL with differential pathlength factor (DPF), the proposed MBLL with PPL is able to acquire more obvious concentration change and can achieve higher classification accuracy of the three tasks. Then, with the proposed method, the performance of the multi-distance probe configuration is discussed. Results show that, compared with a single distance, the combination of the three distances has better spatial resolution and could explore more accurate brain activation information. Besides, the classification accuracy of the three tasks obtained with the combination of three distances is higher than that of any combination of two distances. Also, with the combination of the three distances, the two-class classification between different tasks is carried out. Both theory and experimental results demonstrate that, using multi-distance probe configuration and the MBLL with PPL method, the performance of brain function detected by NIRS can be improved.
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Affiliation(s)
- Xinrui Chen
- Academy of Medical Engineering and Translation Medicine, Tianjin University, Tianjin, China
| | - Xizi Song
- Academy of Medical Engineering and Translation Medicine, Tianjin University, Tianjin, China
| | - Long Chen
- Academy of Medical Engineering and Translation Medicine, Tianjin University, Tianjin, China
| | - Xingwei An
- Academy of Medical Engineering and Translation Medicine, Tianjin University, Tianjin, China
| | - Dong Ming
- Academy of Medical Engineering and Translation Medicine, Tianjin University, Tianjin, China
- College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
- *Correspondence: Dong Ming,
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27
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Kronovsek T, Hermand E, Berthoz A, Castilla A, Gallou-Guyot M, Daviet JC, Perrochon A. Age-related decline in visuo-spatial working memory is reflected by dorsolateral prefrontal activation and cognitive capabilities. Behav Brain Res 2020; 398:112981. [PMID: 33144176 DOI: 10.1016/j.bbr.2020.112981] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Revised: 10/21/2020] [Accepted: 10/22/2020] [Indexed: 12/14/2022]
Abstract
INTRODUCTION Visuo-spatial working memory (VSWM) performances undergo a decline throughout aging and are affected by the space in which the task is performed (reaching or navigational). Cerebral oxygenation and cognitive capabilities could explain this decline. We assessed the effects of age on cerebral oxygenation of the dorsolateral prefrontal cortex (dlPFC) in VSWM tasks in reaching and navigational space. We also assessed cognitive correlates of VSWM performance in each space. METHOD Thirty-one (31) young adults (YA) and 24 healthy older adults (OA) performed a battery of neuropsychological tests and the electronic Corsi Block-tapping Test in reaching space (e-CBT) and in navigational space on the "Virtual Carpet" (VWCT). Participants were asked to memorize and recall a sequential pathway, progressively increasing from 2 to 9 blocks. Their span score reflected VSWM performance. The dlPFC oxygenation (oxyhaemoglobin: ΔO2Hb and deoxyhaemoglobin: ΔHHb) was measured by using functional Near-Infrared Spectroscopy (fNIRS) during the encoding of the sequential pathway in both tasks. RESULTS YA had higher span scores than OA in both spaces. We identified a significantly stronger decrease of ΔHHb in YA compared to OA during encoding in VWCT. OA also exhibited significantly lower cerebral oxygenation in VWCT compared to e-CBT. A decrease of ΔHHb was also associated with a better performance in VWCT. Finally, we identified the association of mental rotation and executive functions with VSWM performance in both tasks. CONCLUSION VSWM performance and cerebral oxygenation during encoding are impacted by aging. Space in which the task was performed was found to be associated with different cognitive functions and revealed differences in cerebral oxygenation.
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Affiliation(s)
- Téo Kronovsek
- Université De Limoges, HAVAE, EA 6310, F-87000 Limoges, France
| | - Eric Hermand
- Université De Limoges, HAVAE, EA 6310, F-87000 Limoges, France; EA 7369 URePSSS (Unité de Recherche Pluridisciplinaire Sport, Santé, Société), Université du Littoral Côte d'Opale, Dunkerque, France
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28
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Bu L, Xu N, Wang Y, Liu H. Decreased low-frequency brain effective connectivity in seafarers during voyages: a functional near-infrared spectroscopy study. Physiol Meas 2020; 41:095003. [PMID: 32759489 DOI: 10.1088/1361-6579/abad13] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE During voyages, seafarers experience psychological problems that act to decrease operational safety. Psychological problems in seafarers can lead to changes in functional brain networks. This study investigated the low-frequency brain effective connectivity (EC) in seafarers during voyages by using the coupling strength (CS) of functional near-infrared spectroscopy (fNIRS) imaging. APPROACH This study recruited 15 seafarers (seafarer group) working on a container ship and 15 healthy age-matched controls (control group). The EC was assessed using dynamic Bayesian inference (DBI) of the oxygenated hemoglobin concentration (delta HbO2) as measured through a 14-channel fNIRS system. These channels covered the left and right prefrontal cortices (LPFC/RPFC), left and right motor cortices (LMC/RMC), and left and right occipital lobes (LOL/ROL). MAIN RESULTS The EC levels of LPFC to RMC (F = 4.239, p = 0.049), LPFC to ROL (F = 5.385, p = 0.028), LOL to RPFC (F = 11.128, p = 0.002), ROL to RPFC (F = 10.714, p = 0.003) and LMC to ROL (F= 6.136, p = 0.02) were significantly lower in the seafarer group than in the control group. Correlation analysis revealed that the patient health questionnaire-9 (PHQ-9) scores were positively correlated with the systolic blood pressure (SBP) values, delta HbO2 values and EC levels, respectively. Meanwhile, the correlation analysis revealed that the SBP values significantly positively correlated with the CS values. SIGNIFICANCE Decreased EC levels may be a marker of psychological subhealth in seafarers. The approach combines fNIRS and PHQ-9 scores, providing a quantitative method for the assessment of mental health problems and further help with better rehabilitation designs in seafarers during voyages.
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Affiliation(s)
- Lingguo Bu
- Department of Physical Medicine and Rehabilitation, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, People's Republic of China. School of Mechanical and Aerospace Engineering, Nanyang Technological University, 639798, Singapore
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29
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He Y, Wang M, Yu X. High spatiotemporal vessel-specific hemodynamic mapping with multi-echo single-vessel fMRI. J Cereb Blood Flow Metab 2020; 40:2098-2114. [PMID: 31696765 PMCID: PMC7786852 DOI: 10.1177/0271678x19886240] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
High-resolution fMRI enables noninvasive mapping of the hemodynamic responses from individual penetrating vessels in animal brains. Here, a 2D multi-echo single-vessel fMRI (MESV-fMRI) method has been developed to map the fMRI signal from arterioles and venules with a 100 ms sampling rate at multiple echo times (TE, 3-30 ms) and short acquisition windows (<1 ms). The T2*-weighted signal shows the increased extravascular effect on venule voxels as a function of TE. In contrast, the arteriole voxels show an increased fMRI signal with earlier onset than venules voxels at the short TE (3 ms) with increased blood inflow and volume effects. MESV-fMRI enables vessel-specific T2* mapping and presents T2*-based fMRI time courses with higher contrast-to-noise ratios (CNRs) than the T2*-weighted fMRI signal at a given TE. The vessel-specific T2* mapping also allows semi-quantitative estimation of the oxygen saturation levels (Y) and their changes (ΔY) at a given blood volume fraction upon neuronal activation. The MESV-fMRI method enables vessel-specific T2* measurements with high spatiotemporal resolution for better modeling of the fMRI signal based on the hemodynamic parameters.
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Affiliation(s)
- Yi He
- Translational Neuroimaging and Neural Control Group, 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.,Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
| | - Maosen Wang
- Translational Neuroimaging and Neural Control Group, 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
| | - Xin Yu
- Translational Neuroimaging and Neural Control Group, 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, USA
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30
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Kananen J, Helakari H, Korhonen V, Huotari N, Järvelä M, Raitamaa L, Raatikainen V, Rajna Z, Tuovinen T, Nedergaard M, Jacobs J, LeVan P, Ansakorpi H, Kiviniemi V. Respiratory-related brain pulsations are increased in epilepsy-a two-centre functional MRI study. Brain Commun 2020; 2:fcaa076. [PMID: 32954328 PMCID: PMC7472909 DOI: 10.1093/braincomms/fcaa076] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Revised: 04/29/2020] [Accepted: 05/05/2020] [Indexed: 01/03/2023] Open
Abstract
Resting-state functional MRI has shown potential for detecting changes in cerebral blood oxygen level-dependent signal in patients with epilepsy, even in the absence of epileptiform activity. Furthermore, it has been suggested that coefficient of variation mapping of fast functional MRI signal may provide a powerful tool for the identification of intrinsic brain pulsations in neurological diseases such as dementia, stroke and epilepsy. In this study, we used fast functional MRI sequence (magnetic resonance encephalography) to acquire ten whole-brain images per second. We used the functional MRI data to compare physiological brain pulsations between healthy controls (n = 102) and patients with epilepsy (n = 33) and furthermore to drug-naive seizure patients (n = 9). Analyses were performed by calculating coefficient of variation and spectral power in full band and filtered sub-bands. Brain pulsations in the respiratory-related frequency sub-band (0.11-0.51 Hz) were significantly (P < 0.05) increased in patients with epilepsy, with an increase in both signal variance and power. At the individual level, over 80% of medicated and drug-naive seizure patients exhibited areas of abnormal brain signal power that correlated well with the known clinical diagnosis, while none of the controls showed signs of abnormality with the same threshold. The differences were most apparent in the basal brain structures, respiratory centres of brain stem, midbrain and temporal lobes. Notably, full-band, very low frequency (0.01-0.1 Hz) and cardiovascular (0.8-1.76 Hz) brain pulses showed no differences between groups. This study extends and confirms our previous results of abnormal fast functional MRI signal variance in epilepsy patients. Only respiratory-related brain pulsations were clearly increased with no changes in either physiological cardiorespiratory rates or head motion between the subjects. The regional alterations in brain pulsations suggest that mechanisms driving the cerebrospinal fluid homeostasis may be altered in epilepsy. Magnetic resonance encephalography has both increased sensitivity and high specificity for detecting the increased brain pulsations, particularly in times when other tools for locating epileptogenic areas remain inconclusive.
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Affiliation(s)
- Janne Kananen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Heta Helakari
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Vesa Korhonen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Niko Huotari
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Matti Järvelä
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Lauri Raitamaa
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Ville Raatikainen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Zalan Rajna
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Center for Machine Vision and Signal Analysis (CMVS), University of Oulu, Oulu 90014, Finland
| | - Timo Tuovinen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Maiken Nedergaard
- Center for Translational Neuromedicine, Department of Neurosurgery, University of Rochester Medical Center, Rochester, NY 14642, USA
- Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Julia Jacobs
- Department of Pediatric Neurology and Muscular Disease, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg 79110, Germany
- Department of Paediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
- Department of Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
- Hotchkiss Brain Institute and Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB T2N 4N1, Canada
| | - Pierre LeVan
- Department of Paediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
- Department of Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
- Hotchkiss Brain Institute and Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB T2N 4N1, Canada
- Department of Radiology, Medical Physics, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg 79110, Germany
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
| | - Hanna Ansakorpi
- Medical Research Center (MRC), Oulu 90220, Finland
- Research Unit of Neuroscience, Neurology, University of Oulu, Oulu 90220, Finland
- Department of Neurology, Oulu University Hospital, Oulu 90029, Finland
| | - Vesa Kiviniemi
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
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31
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Krishnamurthy V, Krishnamurthy LC, Drucker JH, Kundu S, Ji B, Hortman K, Roberts SR, Mammino K, Tran SM, Gopinath K, McGregor KM, Rodriguez AD, Qiu D, Crosson B, Nocera JR. Correcting Task fMRI Signals for Variability in Baseline CBF Improves BOLD-Behavior Relationships: A Feasibility Study in an Aging Model. Front Neurosci 2020; 14:336. [PMID: 32425745 PMCID: PMC7205008 DOI: 10.3389/fnins.2020.00336] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Accepted: 03/20/2020] [Indexed: 12/24/2022] Open
Abstract
Blood Oxygen Level Dependent (BOLD) functional MRI is a complex neurovascular signal whose magnitude depends on baseline physiological factors such as cerebral blood flow (CBF). Because baseline CBF varies across the brain and is altered with aging, the interpretation of stand-alone aging-related BOLD changes can be misleading. The primary objective of this study was to develop a methodology that combines task fMRI and arterial spin labeling (ASL) techniques to sensitize task-induced BOLD activity by covarying out the baseline physiology (i.e., CBF) in an aging model. We recruited 11 younger and 13 older healthy participants who underwent ASL and an overt language fMRI task (semantic category member generation). We measured in-scanner language performance to investigate the effect of BOLD sensitization on BOLD-behavior relationships. The results demonstrate that our correction approach is effective at enhancing the specificity and sensitivity of the BOLD signal in both groups. In addition, the correction strengthens the statistical association between task BOLD activity and behavioral performance. Although CBF has inherent age dependence, our results show that retaining the age factor within CBF aides in greater sensitization of task fMRI signals. From a cognitive standpoint, compared to young adults, the older participants showed a delayed domain-general language-related task activity possibly due to compromised vessel compliance. Further, assessment of functional evolution of corrected BOLD activity revealed biphasic BOLD dynamics in both groups where BOLD deactivation may reflect greater semantic demand or increased premium on domain general executive functioning in response to task difficulty. Although it was promising to note that the predictability of behavior using the proposed methodology outperforms other methodologies (i.e., no correction and normalization by division), and provides moderate stability and adequate power, further work with a larger cohort and other task designs is necessary to improve the stability of predicting associated behavior. In summary, we recommend correction of task fMRI signals by covarying out baseline CBF especially when comparing groups with different neurovascular properties. Given that ASL and BOLD fMRI are well established and widely employed techniques, our proposed multi-modal methodology can be readily implemented into data processing pipelines to obtain more accurate BOLD activation maps.
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Affiliation(s)
- Venkatagiri Krishnamurthy
- Department of Neurology, Emory University, Atlanta, GA, United States.,Center for Visual and Neurocognitive Rehabilitation, Atlanta Veterans Affairs Medical Center (VAMC), Decatur, GA, United States
| | - Lisa C Krishnamurthy
- Center for Visual and Neurocognitive Rehabilitation, Atlanta Veterans Affairs Medical Center (VAMC), Decatur, GA, United States.,Department of Physics and Astronomy, Georgia State University, Atlanta, GA, United States
| | - Jonathan H Drucker
- Department of Neurology, Emory University, Atlanta, GA, United States.,Center for Visual and Neurocognitive Rehabilitation, Atlanta Veterans Affairs Medical Center (VAMC), Decatur, GA, United States
| | - Suprateek Kundu
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, United States
| | - Bing Ji
- Department of Neurology, Emory University, Atlanta, GA, United States.,Center for Visual and Neurocognitive Rehabilitation, Atlanta Veterans Affairs Medical Center (VAMC), Decatur, GA, United States.,Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA, United States
| | - Kyle Hortman
- Center for Visual and Neurocognitive Rehabilitation, Atlanta Veterans Affairs Medical Center (VAMC), Decatur, GA, United States
| | - Simone R Roberts
- Department of Neurology, Emory University, Atlanta, GA, United States.,Center for Visual and Neurocognitive Rehabilitation, Atlanta Veterans Affairs Medical Center (VAMC), Decatur, GA, United States.,Department of Psychology, Georgia State University, Atlanta, GA, United States
| | - Kevin Mammino
- Center for Visual and Neurocognitive Rehabilitation, Atlanta Veterans Affairs Medical Center (VAMC), Decatur, GA, United States
| | - Stella M Tran
- Department of Psychology, Georgia State University, Atlanta, GA, United States
| | - Kaundinya Gopinath
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA, United States
| | - Keith M McGregor
- Department of Neurology, Emory University, Atlanta, GA, United States.,Center for Visual and Neurocognitive Rehabilitation, Atlanta Veterans Affairs Medical Center (VAMC), Decatur, GA, United States
| | - Amy D Rodriguez
- Department of Neurology, Emory University, Atlanta, GA, United States.,Center for Visual and Neurocognitive Rehabilitation, Atlanta Veterans Affairs Medical Center (VAMC), Decatur, GA, United States
| | - Deqiang Qiu
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA, United States
| | - Bruce Crosson
- Department of Neurology, Emory University, Atlanta, GA, United States.,Center for Visual and Neurocognitive Rehabilitation, Atlanta Veterans Affairs Medical Center (VAMC), Decatur, GA, United States.,Department of Psychology, Georgia State University, Atlanta, GA, United States
| | - Joe R Nocera
- Department of Neurology, Emory University, Atlanta, GA, United States.,Center for Visual and Neurocognitive Rehabilitation, Atlanta Veterans Affairs Medical Center (VAMC), Decatur, GA, United States.,Division of Physical Therapy, School of Medicine, Emory University, Atlanta, GA, United States
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Mangini F, DiNuzzo M, Maugeri L, Moraschi M, Mascali D, Cedola A, Frezza F, Giove F, Fratini M. Numerical simulation of the blood oxygenation level-dependent functional magnetic resonance signal using finite element method. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2020; 36:e3290. [PMID: 31808299 DOI: 10.1002/cnm.3290] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2019] [Revised: 08/10/2019] [Accepted: 11/10/2019] [Indexed: 06/10/2023]
Abstract
Since the introduction of functional magnetic resonance imaging (fMRI), several computational approaches have been developed to examine the effect of the morphology and arrangement of blood vessels on the blood oxygenation-level dependent (BOLD) signal in the brain. In the present work, we implemented the original Ogawa's model using a numerical simulation based on the finite element method (FEM) instead of the analytical models. In literature, there are different works using analytical methods to analyse the transverse relaxation rate ( R2∗ ), which BOLD signal is related to, modelling the vascular system with simple and canonical geometries such as an infinite cylinder model (ICM) or a set of cylinders. We applied the numerical simulation to the extravascular BOLD signal as a function of angular vessel distribution (perpendicular vs parallel to the static magnetic field) relevant for anatomical districts characterized by geometrical symmetries, such as spinal cord. Numerical simulations confirmed analytical results for the canonical ICM. Moreover, the perturbation to the magnetic field induced by blood deoxyhaemoglobin, as quantified assuming Brownian diffusion of water molecules around the vessel, revealed that vessels contribute the most to the variation of the R2∗ when they are preferentially perpendicular to the external magnetic field, regardless of their size. Our results indicate that the numerical simulation method is sensitive to the effects of different vascular geometry. This work highlights the opportunity to extend R2∗ simulations to realistic models of vasculature based on high-resolution anatomical images.
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Affiliation(s)
- Fabio Mangini
- Fondazione Santa Lucia, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Rome, Italy
| | - Mauro DiNuzzo
- Fondazione Santa Lucia, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Rome, Italy
| | - Laura Maugeri
- Fondazione Santa Lucia, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Rome, Italy
| | - Marta Moraschi
- Centro Fermi-Museo Storico della Fisica e Centro Studi e Ricerche Enrico Fermi, Rome, Italy
| | - Daniele Mascali
- Centro Fermi-Museo Storico della Fisica e Centro Studi e Ricerche Enrico Fermi, Rome, Italy
| | | | - Fabrizio Frezza
- Department of Information Engineering, Electronics and Telecommunications, La Sapienza University of Rome, Rome, Italy
| | - Federico Giove
- Fondazione Santa Lucia, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Rome, Italy
- Centro Fermi-Museo Storico della Fisica e Centro Studi e Ricerche Enrico Fermi, Rome, Italy
| | - Michela Fratini
- Fondazione Santa Lucia, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Rome, Italy
- CNR Consiglio Nazionale delle Ricerche, Rome, Italy
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33
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Specht K. Current Challenges in Translational and Clinical fMRI and Future Directions. Front Psychiatry 2020; 10:924. [PMID: 31969840 PMCID: PMC6960120 DOI: 10.3389/fpsyt.2019.00924] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Accepted: 11/20/2019] [Indexed: 12/15/2022] Open
Abstract
Translational neuroscience is an important field that brings together clinical praxis with neuroscience methods. In this review article, the focus will be on functional neuroimaging (fMRI) and its applicability in clinical fMRI studies. In the light of the "replication crisis," three aspects will be critically discussed: First, the fMRI signal itself, second, current fMRI praxis, and, third, the next generation of analysis strategies. Current attempts such as resting-state fMRI, meta-analyses, and machine learning will be discussed with their advantages and potential pitfalls and disadvantages. One major concern is that the fMRI signal shows substantial within- and between-subject variability, which affects the reliability of both task-related, but in particularly resting-state fMRI studies. Furthermore, the lack of standardized acquisition and analysis methods hinders the further development of clinical relevant approaches. However, meta-analyses and machine-learning approaches may help to overcome current shortcomings in the methods by identifying new, and yet hidden relationships, and may help to build new models on disorder mechanisms. Furthermore, better control of parameters that may have an influence on the fMRI signal and that can easily be controlled for, like blood pressure, heart rate, diet, time of day, might improve reliability substantially.
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Affiliation(s)
- Karsten Specht
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
- Mohn Medical Imaging and Visualization Centre, Haukeland University Hospital, Bergen, Norway
- Department of Education, UiT/The Arctic University of Norway, Tromsø, Norway
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34
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Affiliation(s)
- Stephen J Payne
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, UK
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35
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Bu L, Wu Y, Yan Q, Tang L, Liu X, Diao C, Li K, Dong G. Effects of physical training on brain functional connectivity of methamphetamine dependencies as assessed using functional near-infrared spectroscopy. Neurosci Lett 2019; 715:134605. [PMID: 31698028 DOI: 10.1016/j.neulet.2019.134605] [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: 09/04/2019] [Revised: 10/28/2019] [Accepted: 10/29/2019] [Indexed: 12/19/2022]
Abstract
OBJECTIVE This study aims to assess the effects of physical training based on the functional near-infrared spectroscopy (fNIRS) and heart rate signals. METHODS The oxygenated hemoglobin concentration (Delta [HbO2]) signals were recorded from the left prefrontal cortex (LPFC), right prefrontal cortex (RPFC), left motor cortex (LMC) and right motor cortex (RMC) of 23 subjects with methamphetamine (METH) dependencies at resting, spinning training and strength training states. The wavelet phase coherence (WPCO) values were calculated in four frequency intervals: I, 0.6-2; II, 0.145-0.6; III, 0.052-0.145; and IV, 0.021-0.052 Hz. During the spinning training and strength training states, heart rate signals were recorded at 1, 2, 3, 4, 5, 6, 7, 8, 9 and 10 min, respectively. RESULTS After physical training, the brain regions of LPFC, RPFC and LMC showed different degrees of activation in the subjects with METH dependencies (p < 0.05). The WPCO values between the brain regions significantly altered after spinning training and strength training (p < 0.05) in frequency intervals I, II, III and IV. CONCLUSIONS The altered WPCO values indicated physical training could affect brain functional connectivity (FC) to a certain extent in the subjects with METH dependencies. These findings provide a method for the assessment of the effects of physical training in FC and will contribute to the development of drug rehabilitation methods in subjects with METH dependencies.
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Affiliation(s)
- Lingguo Bu
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, 639798, Singapore; Key Laboratory of High Efficiency and Clean Mechanical Manufacture, School of Mechanical Engineering, Shandong University, Jinan, 250061, PR China
| | - Yan Wu
- Shandong Sport University, Jinan, 250102, PR China
| | - Qian Yan
- Shandong Sport University, Jinan, 250102, PR China
| | - Lei Tang
- Luzhong Compulsory Isolation Drug Rehabilitation Center of Shandong Province, Zibo, 255311, PR China
| | - Xin Liu
- Drug Rehabilitation Administration of Shandong Province, Jinan, 250014, PR China
| | - Chunfeng Diao
- Drug Rehabilitation Administration of Shandong Province, Jinan, 250014, PR China
| | - Kefeng Li
- Shandong Sport University, Jinan, 250102, PR China.
| | - Guijun Dong
- Shandong Sport University, Jinan, 250102, PR China.
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36
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Taylor AJ, Kim JH, Singh V, Halfen EJ, Pfeuffer J, Ress D. More than BOLD: Dual-spin populations create functional contrast. Magn Reson Med 2019; 83:681-694. [PMID: 31423634 DOI: 10.1002/mrm.27941] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Revised: 07/16/2019] [Accepted: 07/21/2019] [Indexed: 11/06/2022]
Abstract
PURPOSE Functional MRI contrast has generally been associated with changes in transverse relaxivity caused by blood oxygen concentration, the so-called blood oxygen level dependent contrast. However, this interpretation of fMRI contrast has been called into question by several recent experiments at high spatial resolution. Experiments were conducted to examine contrast dependencies that cannot be explained only by differences in relaxivity in a single-spin population. METHODS Measurements of functional signal and contrast were obtained in human early visual cortex during a high-contrast visual stimulation over a large range of TEs and for several flip angles. Small voxels (1.5 mm) were used to restrict the measurements to cortical gray matter in early visual areas identified using retinotopic mapping procedures. RESULTS Measurements were consistent with models that include 2 spin populations. The dominant population has a relatively short transverse lifetime that is strongly modulated by activation. However, functional contrast is also affected by volume changes between this short-lived population and the longer-lived population. CONCLUSION Some of the previously observed "nonclassical" behaviors of functional contrast can be explained by these interacting dual-spin populations.
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Affiliation(s)
- Amanda J Taylor
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas
| | - Jung H Kim
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas
| | | | | | - Josef Pfeuffer
- Siemens Healthcare, Application Development, Erlangen, Germany
| | - David Ress
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas
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37
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Aksenov DP, Li L, Miller MJ, Wyrwicz AM. Role of the inhibitory system in shaping the BOLD fMRI response. Neuroimage 2019; 201:116034. [PMID: 31326573 DOI: 10.1016/j.neuroimage.2019.116034] [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: 02/11/2019] [Revised: 07/11/2019] [Accepted: 07/17/2019] [Indexed: 12/17/2022] Open
Abstract
The shape of the blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) signal can vary considerably even across structures of the same sensory pathway. Here, we characterized the temporal behavior of the stimulus-evoked BOLD response in the primary cortical and subcortical regions of the visual and somatosensory whisker systems in awake rabbits. Despite similar BOLD responses in the thalamic nuclei, considerable differences in shape and duration emerged between the sensory cortices. Whereas the BOLD response in the whisker barrel cortex (WBC) was non-adaptive, BOLD in the visual cortex (V1) showed adaptation similar to simultaneously-recorded LFP and single unit activity. Analysis of baseline neuronal activity revealed significantly lower firing rates in V1 vs. WBC. We hypothesized that these changes point to region-dependent differences in the inhibitory systems which shape the hemodynamic response in each structure. To test the effect of neuronal baseline level inhibition on the BOLD signal shape, we locally injected the GABAA agonist muscimol in WBC. Adaptation emerged in the BOLD response after injection, along with an overall decrease in baseline firing rate. These findings point to the importance of region-specific inhibitory shaping in determining the temporal behavior of the BOLD response in different brain areas.
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Affiliation(s)
| | - Limin Li
- NorthShore University HealthSystem, Evanston, IL, 60201, USA
| | | | - Alice M Wyrwicz
- NorthShore University HealthSystem, Evanston, IL, 60201, USA.
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38
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Zou D, Wen F, Zeng H, Mai H, Yuan X, Wang L, Li Y, Liu L, Liu S, Liu G. Improving brain function of pediatric acute lymphoblastic leukemia patients after induction chemotherapy, a pilot self-contrast study by fractional amplitude of low-frequency fluctuation. J Clin Neurosci 2019; 66:149-155. [PMID: 31104963 DOI: 10.1016/j.jocn.2019.04.033] [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: 10/26/2018] [Revised: 04/12/2019] [Accepted: 04/28/2019] [Indexed: 10/26/2022]
Abstract
Our previous study revealed altered resting-stated brain function in children with acute lymphoblastic leukemia (ALL) on new-onset stage. To investigate the effects after induction chemotherapy, a pilot self-contrast study was conducted to compare the difference in resting-stated brain function between pre- and post-induction chemotherapy of ALL. Fractional amplitude of low-frequency fluctuation (fALFF) was employed for fMRI data analysis. Clinical and resting state functional magnetic resonance imaging (RS-fMRI) data of 14 new-onset pediatric ALL patients were collected before and after 3 months of induction chemotherapy. Fourteen age- and gender-matched healthy controls (HCs) were recruited for comparison. Before induction chemotherapy, fALFF values of ALL patients decreased globally, especially in the default mode network (DMN), left frontal lobe, left occipital lobe, and bilateral postcentral gyri as compared to HCs. After induction chemotherapy, fALFF values of ALL patients decreased significantly in the bilateral cuneus, left lingual and calcarine gyri, and left mid frontal gyrus. Paired-sample t-tests and self-contrast analysis showed fALFF increased in the left precuneus, bilateral cuneus, left occipital lobe, bilateral frontal gyri, and bilateral temporal lobes, whereas fALFF in the bilateral precuneus decreased in the ALL patients after induction, which suggests potential side-effects of the treatment. The alteration of fALFF values suggested that resting brain function was impaired before induction chemotherapy and mostly recovered after treatment. This study suggested that fALFF is a reliable and feasible tool in detecting spontaneous brain activity to monitor early neurocognitive impairments in pediatric ALL to better understand the underlying neurobiological mechanisms of chemotherapy on the brain.
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Affiliation(s)
- Dongfang Zou
- Department of Pediatrics, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China; Department of Neurology, Shenzhen Children's Hospital, Shenzhen, Guangdong, China
| | - Feiqiu Wen
- Department of Hematology and Oncology, Shenzhen Children's Hospital, Shenzhen, Guangdong, China.
| | - Hongwu Zeng
- Department of Radiology, Shenzhen Children's Hospital, Shenzhen, Guangdong, China.
| | - Huirong Mai
- Department of Hematology and Oncology, Shenzhen Children's Hospital, Shenzhen, Guangdong, China
| | - Xiuli Yuan
- Department of Hematology and Oncology, Shenzhen Children's Hospital, Shenzhen, Guangdong, China
| | - Lihong Wang
- Department of Hematology and Oncology, Shenzhen Children's Hospital, Shenzhen, Guangdong, China
| | - Yue Li
- Department of Hematology and Oncology, Shenzhen Children's Hospital, Shenzhen, Guangdong, China
| | - Liwei Liu
- Department of Hematology and Oncology, Shenzhen Children's Hospital, Shenzhen, Guangdong, China
| | - Sixi Liu
- Department of Hematology and Oncology, Shenzhen Children's Hospital, Shenzhen, Guangdong, China
| | - Guosheng Liu
- Department of Pediatrics, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China
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39
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Guo J, Biswal BB, Han S, Li J, Yang S, Yang M, Chen H. Altered dynamics of brain segregation and integration in poststroke aphasia. Hum Brain Mapp 2019; 40:3398-3409. [PMID: 31016854 DOI: 10.1002/hbm.24605] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2018] [Revised: 03/30/2019] [Accepted: 04/08/2019] [Indexed: 01/06/2023] Open
Abstract
Poststroke aphasia (PSA) results from direct effect of focal lesions and dysfunction of distributed language networks. However, how flexible the activity at specific nodes control global dynamics is currently unknown. In this study, we demonstrate that alterations in the regional activity may cause imbalances between segregation and integration in temporo-spatial pattern, and the transient dynamics are disrupted in PSA patients. Specifically, we applied dynamic framework to eyes-closed resting-state functional MRI data from PSA patients (n = 17), and age-, gender-, and education-matched healthy controls (HCs, n = 20). Subsequently, we calculated two basis brain organizational principles: "dynamic segregation," obtained from dynamic amplitude of low-frequency fluctuations (dALFF), which represent the specialized processing within interconnected brain regions; and "dynamic integration," obtained from dynamic functional connectivity, which measures the efficient communication between interconnected brain regions. We found that both measures were decreased in the PSA patients within the left frontal and temporal subregions compared to the HCs. PSA patients displayed increased flexibility of interaction between left temporo-frontal subregions and right temporo-parieto-frontal subnetworks. Furthermore, we found that dALFF in the pars triangularis of left inferior frontal gyrus was associated with aphasia quotient. These findings suggest that the reduced temporal flexibility of regional activity in language-relevant cortical regions in PSA is related to the disrupted organization of intrahemispheric networks, leading to a loss of the corresponding functions. By using dynamic framework, our results offer valuable information about the alterations in segregation and integration of spatiotemporal information across networks and illuminate how dysfunction in flexible activity may underlie language deficits in PSA.
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Affiliation(s)
- Jing Guo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Bharat B Biswal
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, New Jersey
| | - Shaoqiang Han
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Jiao Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Siqi Yang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Mi Yang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
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40
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BOLD signal physiology: Models and applications. Neuroimage 2019; 187:116-127. [DOI: 10.1016/j.neuroimage.2018.03.018] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2017] [Revised: 02/14/2018] [Accepted: 03/08/2018] [Indexed: 12/14/2022] Open
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41
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Mäki-Marttunen T, Kaufmann T, Elvsåshagen T, Devor A, Djurovic S, Westlye LT, Linne ML, Rietschel M, Schubert D, Borgwardt S, Efrim-Budisteanu M, Bettella F, Halnes G, Hagen E, Næss S, Ness TV, Moberget T, Metzner C, Edwards AG, Fyhn M, Dale AM, Einevoll GT, Andreassen OA. Biophysical Psychiatry-How Computational Neuroscience Can Help to Understand the Complex Mechanisms of Mental Disorders. Front Psychiatry 2019; 10:534. [PMID: 31440172 PMCID: PMC6691488 DOI: 10.3389/fpsyt.2019.00534] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2018] [Accepted: 07/10/2019] [Indexed: 12/11/2022] Open
Abstract
The brain is the most complex of human organs, and the pathophysiology underlying abnormal brain function in psychiatric disorders is largely unknown. Despite the rapid development of diagnostic tools and treatments in most areas of medicine, our understanding of mental disorders and their treatment has made limited progress during the last decades. While recent advances in genetics and neuroscience have a large potential, the complexity and multidimensionality of the brain processes hinder the discovery of disease mechanisms that would link genetic findings to clinical symptoms and behavior. This applies also to schizophrenia, for which genome-wide association studies have identified a large number of genetic risk loci, spanning hundreds of genes with diverse functionalities. Importantly, the multitude of the associated variants and their prevalence in the healthy population limit the potential of a reductionist functional genetics approach as a stand-alone solution to discover the disease pathology. In this review, we outline the key concepts of a "biophysical psychiatry," an approach that employs large-scale mechanistic, biophysics-founded computational modelling to increase transdisciplinary understanding of the pathophysiology and strive toward robust predictions. We discuss recent scientific advances that allow a synthesis of previously disparate fields of psychiatry, neurophysiology, functional genomics, and computational modelling to tackle open questions regarding the pathophysiology of heritable mental disorders. We argue that the complexity of the increasing amount of genetic data exceeds the capabilities of classical experimental assays and requires computational approaches. Biophysical psychiatry, based on modelling diseased brain networks using existing and future knowledge of basic genetic, biochemical, and functional properties on a single neuron to a microcircuit level, may allow a leap forward in deriving interpretable biomarkers and move the field toward novel treatment options.
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Affiliation(s)
- Tuomo Mäki-Marttunen
- Department of Computational Physiology, Simula Research Laboratory, Oslo, Norway.,NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Tobias Kaufmann
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Torbjørn Elvsåshagen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Anna Devor
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States.,Department of Radiology, University of California, San Diego, La Jolla, CA, United States.,Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway.,NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Lars T Westlye
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Psychology, University of Oslo, Oslo, Norway
| | - Marja-Leena Linne
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Dirk Schubert
- Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, Netherlands
| | - Stefan Borgwardt
- Department of Psychiatry (UPK), University of Basel, Basel, Switzerland
| | - Magdalena Efrim-Budisteanu
- Prof. Dr. Alex. Obregia Clinical Hospital of Psychiatry, Bucharest, Romania.,Victor Babes National Institute of Pathology, Bucharest, Romania.,Faculty of Medicine, Titu Maiorescu University, Bucharest, Romania
| | - Francesco Bettella
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Geir Halnes
- Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway
| | - Espen Hagen
- Department of Physics, University of Oslo, Oslo, Norway
| | - Solveig Næss
- Department of Informatics, University of Oslo, Oslo, Norway
| | - Torbjørn V Ness
- Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway
| | - Torgeir Moberget
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Christoph Metzner
- Centre for Computer Science and Informatics Research, University of Hertfordshire, Hatfield, United Kingdom.,Institute of Software Engineering and Theoretical Computer Science, Technische Universität zu Berlin, Berlin, Germany
| | - Andrew G Edwards
- Department of Computational Physiology, Simula Research Laboratory, Oslo, Norway
| | - Marianne Fyhn
- Department of Biosciences, University of Oslo, Oslo, Norway
| | - Anders M Dale
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States.,Department of Radiology, University of California, San Diego, La Jolla, CA, United States
| | - Gaute T Einevoll
- Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway.,Department of Physics, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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Gandini Wheeler-Kingshott CAM, Riemer F, Palesi F, Ricciardi A, Castellazzi G, Golay X, Prados F, Solanky B, D'Angelo EU. Challenges and Perspectives of Quantitative Functional Sodium Imaging (fNaI). Front Neurosci 2018; 12:810. [PMID: 30473659 PMCID: PMC6237845 DOI: 10.3389/fnins.2018.00810] [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: 07/19/2018] [Accepted: 10/17/2018] [Indexed: 12/31/2022] Open
Abstract
Brain function has been investigated via the blood oxygenation level dependent (BOLD) effect using magnetic resonance imaging (MRI) for the past decades. Advances in sodium imaging offer the unique chance to access signal changes directly linked to sodium ions (23Na) flux across the cell membrane, which generates action potentials, hence signal transmission in the brain. During this process 23Na transiently accumulates in the intracellular space. Here we show that quantitative functional sodium imaging (fNaI) at 3T is potentially sensitive to 23Na concentration changes during finger tapping, which can be quantified in gray and white matter regions key to motor function. For the first time, we measured a 23Na concentration change of 0.54 mmol/l in the ipsilateral cerebellum, 0.46 mmol/l in the contralateral primary motor cortex (M1), 0.27 mmol/l in the corpus callosum and -11 mmol/l in the ipsilateral M1, suggesting that fNaI is sensitive to distributed functional alterations. Open issues persist on the role of the glymphatic system in maintaining 23Na homeostasis, the role of excitation and inhibition as well as volume distributions during neuronal activity. Haemodynamic and physiological signal recordings coupled to realistic models of tissue function will be critical to understand the mechanisms of such changes and contribute to meeting the overarching challenge of measuring neuronal activity in vivo.
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Affiliation(s)
- Claudia A M Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.,Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy.,Brain MRI 3T Mondino Research Center, IRCCS Mondino Foundation, Pavia, Italy
| | - Frank Riemer
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.,Department of Radiology, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Fulvia Palesi
- Neuroradiology Unit, IRCCS Mondino Foundation, Pavia, Italy
| | - Antonio Ricciardi
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.,Center for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Gloria Castellazzi
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.,Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Xavier Golay
- NMR Research Unit, Queen Square MS Centre, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
| | - Ferran Prados
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.,Center for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom.,Universitat Oberta de Catalunya, Barcelona, Spain
| | - Bhavana Solanky
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
| | - Egidio U D'Angelo
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy.,Brain Connectivity Center, IRCCS Mondino Foundation, Pavia, Italy
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Ryman SG, El Shaikh AA, Shaff NA, Hanlon FM, Dodd AB, Wertz CJ, Ling JM, Barch DM, Stromberg SF, Lin DS, Abrams S, Mayer AR. Proactive and reactive cognitive control rely on flexible use of the ventrolateral prefrontal cortex. Hum Brain Mapp 2018; 40:955-966. [PMID: 30407681 DOI: 10.1002/hbm.24424] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Revised: 08/07/2018] [Accepted: 10/03/2018] [Indexed: 11/05/2022] Open
Abstract
The role of ventral versus dorsolateral prefrontal regions in instantiating proactive and reactive cognitive control remains actively debated, with few studies parsing cue versus probe-related activity. Rapid sampling (460 ms), long cue-probe delays, and advanced analytic techniques (deconvolution) were therefore used to quantify the magnitude and variability of neural responses during the AX Continuous Performance Test (AX-CPT; N = 46) in humans. Behavioral results indicated slower reaction times during reactive cognitive control (AY trials) in conjunction with decreased accuracy and increased variability for proactive cognitive control (BX trials). The anterior insula/ventrolateral prefrontal cortex (aI/VLPFC) was commonly activated across comparisons of both proactive and reactive cognitive control. In contrast, activity within the dorsomedial and dorsolateral prefrontal cortex was limited to reactive cognitive control. The instantiation of proactive cognitive control during the probe period was also associated with sparse neural activation relative to baseline, potentially as a result of the high degree of neural and behavioral variability observed across individuals. Specifically, the variability of the hemodynamic response function (HRF) within motor circuitry increased after the presentation of B relative to A cues (i.e., late in HRF) and persisted throughout the B probe period. Finally, increased activation of right aI/VLPFC during the cue period was associated with decreased motor circuit activity during BX probes, suggesting a possible role for the aI/VLPFC in proactive suppression of neural responses. Considered collectively, current results highlight the flexible role of the VLPFC in implementing cognitive control during the AX-CPT task but suggest large individual differences in proactive cognitive control strategies.
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Affiliation(s)
- Sephira G Ryman
- Department of Psychology, University of New Mexico, Albuquerque, New Mexico.,The Mind Research Network/Lovelace Biomedical and Environmental Research Institute, Albuquerque, New Mexico
| | - Ansam A El Shaikh
- The Mind Research Network/Lovelace Biomedical and Environmental Research Institute, Albuquerque, New Mexico
| | - Nicholas A Shaff
- The Mind Research Network/Lovelace Biomedical and Environmental Research Institute, Albuquerque, New Mexico
| | - Faith M Hanlon
- The Mind Research Network/Lovelace Biomedical and Environmental Research Institute, Albuquerque, New Mexico
| | - Andrew B Dodd
- The Mind Research Network/Lovelace Biomedical and Environmental Research Institute, Albuquerque, New Mexico
| | - Christopher J Wertz
- The Mind Research Network/Lovelace Biomedical and Environmental Research Institute, Albuquerque, New Mexico
| | - Josef M Ling
- The Mind Research Network/Lovelace Biomedical and Environmental Research Institute, Albuquerque, New Mexico
| | - Deanna M Barch
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, Missouri
| | - Shannon F Stromberg
- Department of Psychiatry, University of New Mexico School of Medicine, Albuquerque, New Mexico
| | - Denise S Lin
- Department of Psychiatry, University of New Mexico School of Medicine, Albuquerque, New Mexico
| | - Swala Abrams
- Department of Psychiatry, University of New Mexico School of Medicine, Albuquerque, New Mexico
| | - Andrew R Mayer
- Department of Psychology, University of New Mexico, Albuquerque, New Mexico.,The Mind Research Network/Lovelace Biomedical and Environmental Research Institute, Albuquerque, New Mexico.,Department of Psychiatry, University of New Mexico School of Medicine, Albuquerque, New Mexico.,Department of Neurology, University of New Mexico School of Medicine, Albuquerque, New Mexico
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44
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The renaissance of functional 18F-FDG PET brain activation imaging. Eur J Nucl Med Mol Imaging 2018; 45:2338-2341. [DOI: 10.1007/s00259-018-4165-2] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Accepted: 09/10/2018] [Indexed: 10/28/2022]
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45
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Functional magnetic resonance imaging: Basic principles and application in the neurosciences. RADIOLOGIA 2018. [DOI: 10.1016/j.rxeng.2018.04.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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46
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Lee SH, Jin SH, An J. Distinction of directional coupling in sensorimotor networks between active and passive finger movements using fNIRS. BIOMEDICAL OPTICS EXPRESS 2018; 9:2859-2870. [PMID: 30258695 PMCID: PMC6154205 DOI: 10.1364/boe.9.002859] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2018] [Revised: 05/23/2018] [Accepted: 05/24/2018] [Indexed: 06/08/2023]
Abstract
The purpose of this study is to investigate cerebral cortex activation during active movement and passive movement by using a functional near-infrared spectroscopy (fNIRS). Tasks were the flexion/extension of the right hand finger by active movement and passive movement. Oxy-hemoglobin concentration changes calculated from fNIRS and analyzed the activation and connectivity so as to understand dynamical brain relationship. The results demonstrated that the brain activation in passive movements is similar to motor execution. During active movement, the estimated causality patterns showed significant causality value from the supplementary motor area (SMA) to the primary motor cortex (M1). During the passive movement, the causality from the primary somatosensory cortex (S1) to the primary motor cortex (M1) was stronger than active movement. These results demonstrated that active and passive movements had a direct effect on the cerebral cortex but the stimulus pathway of active and passive movement is different. This study may contribute to better understanding how active and passive movements can be expressed into cortical activation by means of fNIRS.
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47
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Huneau C, Houot M, Joutel A, Béranger B, Giroux C, Benali H, Chabriat H. Altered dynamics of neurovascular coupling in CADASIL. Ann Clin Transl Neurol 2018; 5:788-802. [PMID: 30009197 PMCID: PMC6043774 DOI: 10.1002/acn3.574] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2018] [Accepted: 04/13/2018] [Indexed: 12/12/2022] Open
Abstract
Background and Objective Neurovascular coupling is the complex biological process that underlies use‐dependent increases in blood flow in response to neural activation. Neurovascular coupling was investigated at the early stage of CADASIL, a genetic paradigm of ischemic small vessel disease. Methods Functional hyperemia and evoked potentials during 20‐ and 40‐sec visual and motor stimulations were monitored simultaneously using arterial spin labeling‐functional magnetic resonance imaging (ASL‐fMRI) and electroencephalography. Results Cortical functional hyperemia differed significantly between 19 patients and 19 healthy individuals, whereas evoked potentials were unaltered. Functional hyperemia dynamics, assessed using the difference in the slope of the response curve between 15 and 30 sec, showed a time‐shifted decrease in the response to 40‐sec neural stimulations in CADASIL patients. These results were replicated in a second cohort of 10 patients and 10 controls and confirmed in the whole population. Interpretation Alterations of neurovascular coupling occur early in CADASIL and can be assessed by ASL‐fMRI using a simple marker of vascular dysfunction.
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Affiliation(s)
- Clément Huneau
- Laboratoire des Sciences du Numérique de Nantes - LS2N Centre National de la Recherche Scientifique UMR6004 Université de Nantes Nantes France.,Laboratoire d'Imagerie Biomédicale Centre de la Recherche Scientifique UMR7371 Inserm UMR1146 Université Pierre et Marie Curie Paris VI Paris France
| | - Marion Houot
- Centre of Excellence of Neurodegenerative Disease - CoEN ICM, APHP Department of Neurology Hôpital Pitié-Salpêtrière Institute of Memory and Alzheimer's Disease - IM2A University Paris 6 Paris France
| | - Anne Joutel
- Sorbonne Paris Cité Inserm UMR1161 Université Denis Diderot Paris VII Paris France
| | - Benoit Béranger
- Centre de Neuro-Imagerie de Recherche - CENIR Institut du Cerveau et de la Moelle épinière - ICM Paris France
| | - Christian Giroux
- Département de Neurologie and DHU NeuroVasc AP-HP Hôpital Lariboisière Paris France
| | - Habib Benali
- Laboratoire d'Imagerie Biomédicale Centre de la Recherche Scientifique UMR7371 Inserm UMR1146 Université Pierre et Marie Curie Paris VI Paris France.,Faculty of Engineering and Computer Science University Concordia Quebec Canada
| | - Hugues Chabriat
- Sorbonne Paris Cité Inserm UMR1161 Université Denis Diderot Paris VII Paris France.,Département de Neurologie and DHU NeuroVasc AP-HP Hôpital Lariboisière Paris France
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48
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Chiacchiaretta P, Cerritelli F, Bubbico G, Perrucci MG, Ferretti A. Reduced Dynamic Coupling Between Spontaneous BOLD-CBF Fluctuations in Older Adults: A Dual-Echo pCASL Study. Front Aging Neurosci 2018; 10:115. [PMID: 29740310 PMCID: PMC5925323 DOI: 10.3389/fnagi.2018.00115] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2018] [Accepted: 04/03/2018] [Indexed: 11/13/2022] Open
Abstract
Measurement of the dynamic coupling between spontaneous Blood Oxygenation Level Dependent (BOLD) and cerebral blood flow (CBF) fluctuations has been recently proposed as a method to probe resting-state brain physiology. Here we investigated how the dynamic BOLD-CBF coupling during resting-state is affected by aging. Fifteen young subjects and 17 healthy elderlies were studied using a dual-echo pCASL sequence. We found that the dynamic BOLD-CBF coupling was markedly reduced in elderlies, in particular in the left supramarginal gyrus, an area known to be involved in verbal working memory and episodic memory. Moreover, correcting for temporal shift between BOLD and CBF timecourses resulted in an increased correlation of the two signals for both groups, but with a larger increase for elderlies. However, even after temporal shift correction, a significantly decreased correlation was still observed for elderlies in the left supramarginal gyrus, indicating that the age-related dynamic BOLD-CBF uncoupling in this region is more pronounced and can be only partially explained with a simple time-shift between the two signals. Interestingly, these results were observed in a group of elderlies with normal cognitive functions, suggesting that the study of dynamic BOLD-CBF coupling during resting-state is a promising technique, potentially able to provide early biomarkers of functional changes in the aging brain.
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Affiliation(s)
- Piero Chiacchiaretta
- Department of Neuroscience, Imaging and Clinical Sciences, Università degli Studi G. d'Annunzio Chieti e Pescara, Chieti, Italy.,Institute for Advanced Biomedical Technologies (ITAB), Università degli Studi G. d'Annunzio Chieti e Pescara, Chieti, Italy
| | - Francesco Cerritelli
- Department of Neuroscience, Imaging and Clinical Sciences, Università degli Studi G. d'Annunzio Chieti e Pescara, Chieti, Italy.,Institute for Advanced Biomedical Technologies (ITAB), Università degli Studi G. d'Annunzio Chieti e Pescara, Chieti, Italy.,Clinical-Based Human Research Department-C.O.M.E. Collaboration ONLUS, Pescara, Italy
| | - Giovanna Bubbico
- Department of Neuroscience, Imaging and Clinical Sciences, Università degli Studi G. d'Annunzio Chieti e Pescara, Chieti, Italy.,Institute for Advanced Biomedical Technologies (ITAB), Università degli Studi G. d'Annunzio Chieti e Pescara, Chieti, Italy
| | - Mauro Gianni Perrucci
- Department of Neuroscience, Imaging and Clinical Sciences, Università degli Studi G. d'Annunzio Chieti e Pescara, Chieti, Italy.,Institute for Advanced Biomedical Technologies (ITAB), Università degli Studi G. d'Annunzio Chieti e Pescara, Chieti, Italy
| | - Antonio Ferretti
- Department of Neuroscience, Imaging and Clinical Sciences, Università degli Studi G. d'Annunzio Chieti e Pescara, Chieti, Italy.,Institute for Advanced Biomedical Technologies (ITAB), Università degli Studi G. d'Annunzio Chieti e Pescara, Chieti, Italy
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49
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Labbé Atenas T, Ciampi Díaz E, Cruz Quiroga JP, Uribe Arancibia S, Cárcamo Rodríguez C. Functional magnetic resonance imaging: basic principles and application in the neurosciences. RADIOLOGIA 2018; 60:368-377. [PMID: 29544987 DOI: 10.1016/j.rx.2017.12.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2017] [Revised: 12/25/2017] [Accepted: 12/26/2017] [Indexed: 11/25/2022]
Abstract
Functional magnetic resonance imaging (fMRI) is an advanced tool for the study of brain functions in healthy subjects and in neuropsychiatric patients. This tool makes it possible to identify and locate specific phenomena related to neuronal metabolism and activity. Starting with the detection of changes in the blood supply to a region that participates in a function, more complex approaches have been developed to study the dynamics of neuronal networks. Studies examining the brain at rest or involved in different tasks have provided evidence related to the onset, development, and/or response to treatment in various diseases. The diversity of the possible artifacts associated with image registration as well as the complexity of the analytical experimental designs has generated abundant debate about the technique behind fMRI. This article aims to introduce readers to the fundamentals underlying fMRI, to explain how fMRI studies are interpreted, and to discuss fMRI's contributions to the study of the mechanisms underlying diverse diseases of the nervous system.
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Affiliation(s)
- T Labbé Atenas
- Centro Interdisciplinario de Neurociencias, Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - E Ciampi Díaz
- Departamento de Neurología, Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - J P Cruz Quiroga
- Departamento de Radiología, Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - S Uribe Arancibia
- Departamento de Radiología, Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile; Centro de Imágenes Biomédicas, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - C Cárcamo Rodríguez
- Centro Interdisciplinario de Neurociencias, Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile; Departamento de Neurología, Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile.
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50
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Angleys H, Jespersen SN, Østergaard L. The effects of capillary transit time heterogeneity on the BOLD signal. Hum Brain Mapp 2018; 39:2329-2352. [PMID: 29498762 DOI: 10.1002/hbm.23991] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2017] [Revised: 12/06/2017] [Accepted: 01/23/2018] [Indexed: 12/18/2022] Open
Abstract
Neurovascular coupling mechanisms give rise to vasodilation and functional hyperemia upon neural activation, thereby altering blood oxygenation. This blood oxygenation level dependent (BOLD) contrast allows studies of activation patterns in the working human brain by functional MRI (fMRI). The BOLD-weighted fMRI signal shows characteristic transients in relation to functional activation, such as the so-called initial dip, overshoot, and post-stimulus undershoot. These transients are modulated by other physiological stimuli and in disease, but the underlying physiological mechanisms remain incompletely understood. Capillary transit time heterogeneity (CTH) has been shown to affect oxygen extraction, and hence blood oxygenation. Here, we examine how recently reported redistributions of capillary blood flow during functional activation would be expected to affect BOLD signal transients. We developed a three-compartment (hemoglobin, plasma, and tissue) model to predict the BOLD signal, incorporating the effects of dynamic changes in CTH. Our model predicts that the BOLD signal represents the superposition of a positive component resulting from increases in cerebral blood flow (CBF), and a negative component, resulting from elevated tissue metabolism and homogenization of capillary flows (reduced CTH). The model reproduces salient features of BOLD signal dynamics under conditions such as hypercapnia, hyperoxia, and caffeine intake, where both brain physiology and BOLD characteristics are altered. Neuroglial signaling and metabolism could affect CBF and capillary flow patterns differently. Further studies of neurovascular and neuro-capillary coupling mechanisms may help us relate BOLD signals to the firing of certain neuronal populations based on their respective BOLD "fingerprints."
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Affiliation(s)
- Hugo Angleys
- Center of Functionally Integrative Neuroscience and MindLab, Aarhus University, Aarhus, Denmark
| | - Sune N Jespersen
- Center of Functionally Integrative Neuroscience and MindLab, Aarhus University, Aarhus, Denmark.,Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark
| | - Leif Østergaard
- Center of Functionally Integrative Neuroscience and MindLab, Aarhus University, Aarhus, Denmark.,Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark
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