1
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Smolders L, De Baene W, Rutten GJ, van der Hofstad R, Florack L. Can structure predict function at individual level in the human connectome? Brain Struct Funct 2024; 229:1209-1223. [PMID: 38656375 PMCID: PMC11147846 DOI: 10.1007/s00429-024-02796-2] [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: 01/10/2024] [Accepted: 03/25/2024] [Indexed: 04/26/2024]
Abstract
Several studies predicting Functional Connectivity (FC) from Structural Connectivity (SC) at individual level have been published in recent years, each promising increased performance and utility. We investigated three of these studies, analyzing whether the results truly represent a meaningful individual-level mapping from SC to FC. Using data from the Human Connectome Project shared accross the three studies, we constructed a predictor by averaging FC of training data and analyzed its performance in the same way. In each case, we found that group average FC is an equivalent or better predictor of individual FC than the predictive models in terms of raw prediction performance. Furthermore, we showed that additional analyses performed by the authors of the three studies, in which they attempt to show that their predicted FC has value beyond raw prediction performance, could also be reproduced using the group average FC predictor. This makes it unclear whether any of the three methods represent a meaningful individual-level predictive model. We conclude that either the methods are not appropriate for the data, that the sample size is too small, or that the data does not contain sufficient information to learn a mapping from SC to FC. We advise future individual-level studies to explicitly report results in comparison to the performance of the group average, and carefully demonstrate that their predictions contain meaningful individual-level information. Finally, we believe that investigating alternatives for the construction of SC and FC may improve the chances of developing a meaningful individual-level mapping from SC to FC.
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Affiliation(s)
- Lars Smolders
- Eindhoven University of Technology , Department of Mathematics and Computer Science, PO Box 513, Eindhoven, 5600 MB, Netherlands.
- Elisabeth-TweeSteden Hospital, Department of Neurosurgery, Hilvarenbeekseweg 60, Tilburg, 5022 GC, The Netherlands.
| | - Wouter De Baene
- Tilburg University, Department of Cognitive Neuropsychology, Warandelaan 2, Tilburg, 5000 LE, Netherlands
| | - Geert-Jan Rutten
- Elisabeth-TweeSteden Hospital, Department of Neurosurgery, Hilvarenbeekseweg 60, Tilburg, 5022 GC, The Netherlands
| | - Remco van der Hofstad
- Eindhoven University of Technology , Department of Mathematics and Computer Science, PO Box 513, Eindhoven, 5600 MB, Netherlands
| | - Luc Florack
- Eindhoven University of Technology , Department of Mathematics and Computer Science, PO Box 513, Eindhoven, 5600 MB, Netherlands
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2
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Schaefer M, Kühnel A, Rumpel F, Gärtner M. Altruistic acting caused by a touching hand: neural underpinnings of the Midas touch effect. Soc Cogn Affect Neurosci 2022; 17:437-446. [PMID: 34746947 PMCID: PMC9071415 DOI: 10.1093/scan/nsab119] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Revised: 08/30/2021] [Accepted: 11/04/2021] [Indexed: 01/09/2023] Open
Abstract
Giving and receiving touch are some of the most important social stimuli we exchange in daily life. By touching someone, we can communicate various types of information. Previous studies have also demonstrated that interpersonal touch may affect our altruistic behavior. A classic study showed that customers give bigger tips when they are lightly touched by a waitress, which has been called the Midas touch effect. Numerous studies reported similar effects of touch on different kinds of helping or prosocial behaviors. Here, we aim to examine the neural underpinnings of this effect by employing a functional magnetic resonance imaging approach. While lying in the scanner, participants played different rounds of the dictator game, a measure of prosocial behavior. Before each round, participants were touched (or not touched in the control condition) by an experimenter. We found that touching the hand increased the likeliness to behave prosocial (but not the general liking of control stimuli), thereby confirming the Midas touch effect. The effect was predicted by activity in the primary somatosensory cortex, indicating that the somatosensory cortex here plays a causal role in prosocial behavior. We conclude that the tactile modality in social life may be much more important than previously thought.
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Affiliation(s)
| | - Anja Kühnel
- Medical School Berlin, Berlin 14197, Germany
| | - Franziska Rumpel
- Otto-von-Guericke Business School Magdeburg, Magdeburg 39106, Germany
| | - Matti Gärtner
- Medical School Berlin, Berlin 14197, Germany
- Charité – Universitätsmedizin Berlin, Berlin 12200, Germany
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3
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Pais-Roldán P, Yun SD, Shah NJ. Pre-processing of Sub-millimeter GE-BOLD fMRI Data for Laminar Applications. FRONTIERS IN NEUROIMAGING 2022; 1:869454. [PMID: 37555171 PMCID: PMC10406219 DOI: 10.3389/fnimg.2022.869454] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Accepted: 03/31/2022] [Indexed: 08/10/2023]
Abstract
Over the past 30 years, brain function has primarily been evaluated non-invasively using functional magnetic resonance imaging (fMRI) with gradient-echo (GE) sequences to measure blood-oxygen-level-dependent (BOLD) signals. Despite the multiple advantages of GE sequences, e.g., higher signal-to-noise ratio, faster acquisitions, etc., their relatively inferior spatial localization compromises the routine use of GE-BOLD in laminar applications. Here, in an attempt to rescue the benefits of GE sequences, we evaluated the effect of existing pre-processing methods on the spatial localization of signals obtained with EPIK, a GE sequence that affords voxel volumes of 0.25 mm3 with near whole-brain coverage. The methods assessed here apply to both task and resting-state fMRI data assuming the availability of reconstructed magnitude and phase images.
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Affiliation(s)
- Patricia Pais-Roldán
- Institute of Neuroscience and Medicine 4, Medical Imaging Physics, Forschungszentrum Jülich, Jülich, Germany
| | - Seong Dae Yun
- Institute of Neuroscience and Medicine 4, Medical Imaging Physics, Forschungszentrum Jülich, Jülich, Germany
| | - N. Jon Shah
- Institute of Neuroscience and Medicine 4, Medical Imaging Physics, Forschungszentrum Jülich, Jülich, Germany
- Institute of Neuroscience and Medicine 11, Molecular Neuroscience and Neuroimaging, Jülich Aachen Research Alliance, Forschungszentrum Jülich, Jülich, Germany
- Jlich Aachen Research Alliance, Brain - Translational Medicine, Aachen, Germany
- Department of Neurology, Rheinisch-Westfälische Technische Hochschule Aachen University, Aachen, Germany
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4
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Zhang Q, Cramer SR, Ma Z, Turner KL, Gheres KW, Liu Y, Drew PJ, Zhang N. Brain-wide ongoing activity is responsible for significant cross-trial BOLD variability. Cereb Cortex 2022; 32:5311-5329. [PMID: 35179203 PMCID: PMC9712744 DOI: 10.1093/cercor/bhac016] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 01/09/2022] [Accepted: 01/11/2022] [Indexed: 12/27/2022] Open
Abstract
A notorious issue of task-based functional magnetic resonance imaging (fMRI) is its large cross-trial variability. To quantitatively characterize this variability, the blood oxygenation level-dependent (BOLD) signal can be modeled as a linear summation of a stimulation-relevant and an ongoing (i.e. stimulation-irrelevant) component. However, systematic investigation on the spatiotemporal features of the ongoing BOLD component and how these features affect the BOLD response is still lacking. Here we measured fMRI responses to light onsets and light offsets in awake rats. The neuronal response was simultaneously recorded with calcium-based fiber photometry. We established that between-region BOLD signals were highly correlated brain-wide at zero time lag, including regions that did not respond to visual stimulation, suggesting that the ongoing activity co-fluctuates across the brain. Removing this ongoing activity reduced cross-trial variability of the BOLD response by ~30% and increased its coherence with the Ca2+ signal. Additionally, the negative ongoing BOLD activity sometimes dominated over the stimulation-driven response and contributed to the post-stimulation BOLD undershoot. These results suggest that brain-wide ongoing activity is responsible for significant cross-trial BOLD variability, and this component can be reliably quantified and removed to improve the reliability of fMRI response. Importantly, this method can be generalized to virtually all fMRI experiments without changing stimulation paradigms.
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Affiliation(s)
- Qingqing Zhang
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, United States,Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, United States
| | - Samuel R Cramer
- Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, United States,The Neuroscience Graduate Program, The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA 16802, United States
| | - Zilu Ma
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, United States,Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, United States
| | - Kevin L Turner
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, United States,Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, United States
| | - Kyle W Gheres
- Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, United States,Graduate Program in Molecular, Cellular, and Integrative Biosciences, The Pennsylvania State University, University Park, PA 16802, United States
| | - Yikang Liu
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, United States,Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, United States
| | - Patrick J Drew
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, United States,Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, United States,The Neuroscience Graduate Program, The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA 16802, United States,Graduate Program in Molecular, Cellular, and Integrative Biosciences, The Pennsylvania State University, University Park, PA 16802, United States,Department of Engineering Science and Mechanics, The Pennsylvania State University, University Park, PA 16802, United States,Department of Neurosurgery, The Pennsylvania State University, Hershey, PA 17033, United States
| | - Nanyin Zhang
- Corresponding author: Biomedical Engineering and Electrical Engineering, Lloyd & Dorothy Foehr Huck Chair in Brain Imaging, The Huck Institutes of Life Sciences, The Pennsylvania State University, W-341 Millennium Science Complex, University Park, PA 16802, United States.
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5
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Tsvetanov KA, Henson RNA, Rowe JB. Separating vascular and neuronal effects of age on fMRI BOLD signals. Philos Trans R Soc Lond B Biol Sci 2021; 376:20190631. [PMID: 33190597 PMCID: PMC7741031 DOI: 10.1098/rstb.2019.0631] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/19/2020] [Indexed: 12/14/2022] Open
Abstract
Accurate identification of brain function is necessary to understand the neurobiology of cognitive ageing, and thereby promote well-being across the lifespan. A common tool used to investigate neurocognitive ageing is functional magnetic resonance imaging (fMRI). However, although fMRI data are often interpreted in terms of neuronal activity, the blood oxygenation level-dependent (BOLD) signal measured by fMRI includes contributions of both vascular and neuronal factors, which change differentially with age. While some studies investigate vascular ageing factors, the results of these studies are not well known within the field of neurocognitive ageing and therefore vascular confounds in neurocognitive fMRI studies are common. Despite over 10 000 BOLD-fMRI papers on ageing, fewer than 20 have applied techniques to correct for vascular effects. However, neurovascular ageing is not only a confound in fMRI, but an important feature in its own right, to be assessed alongside measures of neuronal ageing. We review current approaches to dissociate neuronal and vascular components of BOLD-fMRI of regional activity and functional connectivity. We highlight emerging evidence that vascular mechanisms in the brain do not simply control blood flow to support the metabolic needs of neurons, but form complex neurovascular interactions that influence neuronal function in health and disease. This article is part of the theme issue 'Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity'.
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Affiliation(s)
- Kamen A. Tsvetanov
- Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0SZ, UK
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK
| | - Richard N. A. Henson
- Department of Psychiatry, University of Cambridge, Cambridge CB2 0SP, UK
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK
| | - James B. Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0SZ, UK
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK
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6
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Dall'Orso S, Fifer WP, Balsam PD, Brandon J, O'Keefe C, Poppe T, Vecchiato K, Edwards AD, Burdet E, Arichi T. Cortical Processing of Multimodal Sensory Learning in Human Neonates. Cereb Cortex 2020; 31:1827-1836. [PMID: 33207366 PMCID: PMC7869081 DOI: 10.1093/cercor/bhaa340] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 10/15/2020] [Accepted: 10/15/2020] [Indexed: 12/13/2022] Open
Abstract
Following birth, infants must immediately process and rapidly adapt to the array of unknown sensory experiences associated with their new ex-utero environment. However, although it is known that unimodal stimuli induce activity in the corresponding primary sensory cortices of the newborn brain, it is unclear how multimodal stimuli are processed and integrated across modalities. The latter is essential for learning and understanding environmental contingencies through encoding relationships between sensory experiences; and ultimately likely subserves development of life-long skills such as speech and language. Here, for the first time, we map the intracerebral processing which underlies auditory-sensorimotor classical conditioning in a group of 13 neonates (median gestational age at birth: 38 weeks + 4 days, range: 32 weeks + 2 days to 41 weeks + 6 days; median postmenstrual age at scan: 40 weeks + 5 days, range: 38 weeks + 3 days to 42 weeks + 1 days) with blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (MRI) and magnetic resonance (MR) compatible robotics. We demonstrate that classical conditioning can induce crossmodal changes within putative unimodal sensory cortex even in the absence of its archetypal substrate. Our results also suggest that multimodal learning is associated with network wide activity within the conditioned neural system. These findings suggest that in early life, external multimodal sensory stimulation and integration shapes activity in the developing cortex and may influence its associated functional network architecture.
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Affiliation(s)
- S Dall'Orso
- Department of Bioengineering, Imperial College London, London SW7 2AZ, UK.,Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, Kings College London, London SE1 7EH, UK.,Department of Electrical Engineering, Chalmers University of Technology, Gothenburg 412 96, Sweden
| | - W P Fifer
- Department of Psychiatry, Columbia University, New York 10032, NY
| | - P D Balsam
- Department of Psychiatry, Columbia University, New York 10032, NY
| | - J Brandon
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, Kings College London, London SE1 7EH, UK
| | - C O'Keefe
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, Kings College London, London SE1 7EH, UK
| | - T Poppe
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, Kings College London, London SE1 7EH, UK
| | - K Vecchiato
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, Kings College London, London SE1 7EH, UK
| | - A D Edwards
- Department of Bioengineering, Imperial College London, London SW7 2AZ, UK.,Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, Kings College London, London SE1 7EH, UK
| | - E Burdet
- Department of Bioengineering, Imperial College London, London SW7 2AZ, UK
| | - T Arichi
- Department of Bioengineering, Imperial College London, London SW7 2AZ, UK.,Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, Kings College London, London SE1 7EH, UK.,Paediatric Neurosciences, Evelina London Children's Hospital, St Thomas' Hospital, London SE1 7EH, UK
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7
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Landelle C, Anton JL, Nazarian B, Sein J, Gharbi A, Felician O, Kavounoudias A. Functional brain changes in the elderly for the perception of hand movements: A greater impairment occurs in proprioception than touch. Neuroimage 2020; 220:117056. [PMID: 32562781 DOI: 10.1016/j.neuroimage.2020.117056] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 06/09/2020] [Accepted: 06/11/2020] [Indexed: 11/28/2022] Open
Abstract
Unlike age-related brain changes linked to motor activity, neural alterations related to self-motion perception remain unknown. Using fMRI data, we investigated age-related changes in the central processing of somatosensory information by inducing illusions of right-hand rotations with specific proprioceptive and tactile stimulation. Functional connectivity during resting-state (rs-FC) was also compared between younger and older participants. Results showed common sensorimotor activations in younger and older adults during proprioceptive and tactile illusions, but less deactivation in various right frontal regions and the precuneus were found in the elderly. Older participants exhibited a less-lateralized pattern of activity across the primary sensorimotor cortices (SM1) in the proprioceptive condition only. This alteration of the interhemispheric balance correlated with declining individual performance in illusion velocity perception from a proprioceptive, but not a tactile, origin. By combining task-related data, rs-FC and behavioral performance, this study provided consistent results showing that hand movement perception was altered in the elderly, with a more pronounced deterioration of the proprioceptive system, likely due to the breakdown of inhibitory processes with aging. Nevertheless, older people could benefit from an increase in internetwork connectivity to overcome this kinesthetic decline.
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Affiliation(s)
- Caroline Landelle
- Aix Marseille Univ, CNRS, LNSC (Laboratoire de Neurosciences Sensorielles et Cognitives - UMR 7260), Marseille, France; McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Jean-Luc Anton
- Aix Marseille Univ, CNRS, Centre IRM-INT@CERIMED (Institut des Neurosciences de la Timone - UMR 7289), Marseille, France
| | - Bruno Nazarian
- Aix Marseille Univ, CNRS, Centre IRM-INT@CERIMED (Institut des Neurosciences de la Timone - UMR 7289), Marseille, France
| | - Julien Sein
- Aix Marseille Univ, CNRS, Centre IRM-INT@CERIMED (Institut des Neurosciences de la Timone - UMR 7289), Marseille, France
| | - Ali Gharbi
- Aix Marseille Univ, CNRS, LNSC (Laboratoire de Neurosciences Sensorielles et Cognitives - UMR 7260), Marseille, France
| | - Olivier Felician
- Aix Marseille Univ, INSERM, INS (Institut des Neurosciences des Systèmes - UMR1106), Marseille, France
| | - Anne Kavounoudias
- Aix Marseille Univ, CNRS, LNSC (Laboratoire de Neurosciences Sensorielles et Cognitives - UMR 7260), Marseille, France.
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8
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Wilson R, Thomas A, Mayhew SD. Spatially congruent negative BOLD responses to different stimuli do not summate in visual cortex. Neuroimage 2020; 218:116891. [DOI: 10.1016/j.neuroimage.2020.116891] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Revised: 04/23/2020] [Accepted: 04/28/2020] [Indexed: 01/07/2023] Open
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9
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Marino M, Arcara G, Porcaro C, Mantini D. Hemodynamic Correlates of Electrophysiological Activity in the Default Mode Network. Front Neurosci 2019; 13:1060. [PMID: 31636535 PMCID: PMC6788217 DOI: 10.3389/fnins.2019.01060] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Accepted: 09/20/2019] [Indexed: 12/16/2022] Open
Abstract
Hemodynamic fluctuations in the default mode network (DMN), observed through functional magnetic resonance imaging (fMRI), have been linked to electrophysiological oscillations detected by electroencephalography (EEG). It has been reported that, among the electrophysiological oscillations, those in the alpha frequency range (8–13 Hz) are the most dominant during resting state. We hypothesized that DMN spatial configuration closely depends on the specific neuronal oscillations considered, and that alpha oscillations would mainly correlate with increased blood oxygen-level dependent (BOLD) signal in the DMN. To test this hypothesis, we used high-density EEG (hdEEG) data simultaneously collected with fMRI scanning in 20 healthy volunteers at rest. We first detected the DMN from source reconstructed hdEEG data for multiple frequency bands, and we then mapped the correlation between temporal profile of hdEEG-derived DMN activity and fMRI–BOLD signals on a voxel-by-voxel basis. In line with our hypothesis, we found that the correlation map associated with alpha oscillations, more than with any other frequency bands, displayed a larger overlap with DMN regions. Overall, our study provided further evidence for a primary role of alpha oscillations in supporting DMN functioning. We suggest that simultaneous EEG–fMRI may represent a powerful tool to investigate the neurophysiological basis of human brain networks.
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Affiliation(s)
- Marco Marino
- Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, Venice, Italy
| | - Giorgio Arcara
- Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, Venice, Italy
| | - Camillo Porcaro
- Institute of Cognitive Sciences and Technologies (ISTC) - National Research Council (CNR), Rome, Italy.,S. Anna Institute and Research in Advanced Neurorehabilitation (RAN), Crotone, Italy.,Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.,Research Center for Motor Control and Neuroplasticity, KU Leuven, Leuven, Belgium
| | - Dante Mantini
- Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, Venice, Italy.,Research Center for Motor Control and Neuroplasticity, KU Leuven, Leuven, Belgium
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10
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Chowdhury MEH, Khandakar A, Mullinger KJ, Al-Emadi N, Bowtell R. Simultaneous EEG-fMRI: Evaluating the Effect of the EEG Cap-Cabling Configuration on the Gradient Artifact. Front Neurosci 2019; 13:690. [PMID: 31354408 PMCID: PMC6635558 DOI: 10.3389/fnins.2019.00690] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2019] [Accepted: 06/18/2019] [Indexed: 01/11/2023] Open
Abstract
Electroencephalography (EEG) data recorded during simultaneous EEG-fMRI experiments are contaminated by large gradient artifacts (GA). The amplitude of the GA depends on the area of the wire loops formed by the EEG leads, as well as on the rate of switching of the magnetic field gradients, which are essential for MR imaging. Average artifact subtraction (AAS), the most commonly used method for GA correction, relies on the EEG amplifier having a large enough dynamic range to characterize the artifact voltages. Low-pass filtering (250 Hz cut-off) is generally used to attenuate the high-frequency voltage fluctuations of the GA, but even with this precaution channel saturation can occur, particularly during acquisition of high spatial resolution MRI data. Previous work has shown that the ribbon cable, used to connect the EEG cap and amplifier, makes a significant contribution to the GA, since the cable geometry produces large effective wire-loop areas. However, by appropriately connecting the wires of the ribbon cable to the EEG cap it should be possible to minimize the overall range and root mean square (RMS) amplitude of the GA by producing partial cancelation of the cap and cable contributions. Here by modifying the connections of the EEG cap to a 1 m ribbon cable we were able to reduce the range of the GA for a high-resolution coronal echo planar Imaging (EPI) acquisition by a factor of ∼ 1.6 and by a factor of ∼ 1.15 for a standard axial EPI acquisition. These changes could potentially be translated into a reduction in the required dynamic range, an increase in the EEG bandwidth or an increase in the achievable image resolution without saturation, all of which could be beneficially exploited in EEG-fMRI studies. The re-wiring could also prevent the system from saturating when small subject movements occur using the standard recording bandwidth.
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Affiliation(s)
- Muhammad E H Chowdhury
- Department of Electrical Engineering, College of Engineering, Qatar University, Doha, Qatar
| | - Amith Khandakar
- Department of Electrical Engineering, College of Engineering, Qatar University, Doha, Qatar
| | - Karen J Mullinger
- Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom.,Birmingham University Imaging Centre, School of Psychology, University of Birmingham, Birmingham, United Kingdom
| | - Nasser Al-Emadi
- Department of Electrical Engineering, College of Engineering, Qatar University, Doha, Qatar
| | - Richard Bowtell
- Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom
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11
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Wilson R, Mullinger KJ, Francis ST, Mayhew SD. The relationship between negative BOLD responses and ERS and ERD of alpha/beta oscillations in visual and motor cortex. Neuroimage 2019; 199:635-650. [PMID: 31189075 DOI: 10.1016/j.neuroimage.2019.06.009] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Revised: 04/10/2019] [Accepted: 06/03/2019] [Indexed: 01/06/2023] Open
Abstract
Previous work has investigated the electrophysiological origins of the intra-modal (within the stimulated sensory cortex) negative BOLD fMRI response (NBR, decrease from baseline) but little attention has been paid to the origin of cross-modal NBRs, those in a different sensory cortex. In the current study we use simultaneous EEG-fMRI recordings to assess the neural correlates of both intra- and cross-modal responses to left-hemifield visual stimuli and right-hand motor tasks, and evaluate the balance of activation and deactivation between the visual and motor systems. Within- and between-subject covariations of EEG and fMRI responses to both tasks are assessed to determine how patterns of event-related desynchronization/synchronisation (ERD/ERS) of alpha/beta frequency oscillations relate to the NBR in the two sensory cortices. We show that both visual and motor tasks induce intra-modal NBR and cross-modal NBR (e.g. visual stimuli evoked NBRs in both visual and motor cortices). In the EEG data, bilateral intra-modal alpha/beta ERD were consistently observed to both tasks, whilst the cross-modal EEG response varied across subjects between alpha/beta ERD and ERS. Both the mean cross-modal EEG and fMRI response amplitudes showed a small increase in magnitude with increasing task intensity. In response to the visual stimuli, subjects displaying cross-modal ERS of motor beta power displayed a significantly larger magnitude of cross-modal NBR in motor cortex. However, in contrast to the motor stimuli, larger cross-modal ERD of visual alpha power was associated with larger cross-modal visual NBR. Single-trial correlation analysis provided further evidence of relationship between EEG signals and the NBR, motor cortex beta responses to motor tasks were significantly negatively correlated with cross-modal visual cortex NBR amplitude, and positively correlated with intra-modal motor cortex PBR. This study provides a new body of evidence that the coupling between BOLD and low-frequency (alpha/beta) sensory cortex EEG responses extends to cross-modal NBR.
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Affiliation(s)
- Ross Wilson
- Centre for Human Brain Health (CHBH), University of Birmingham, Birmingham, UK
| | - Karen J Mullinger
- Centre for Human Brain Health (CHBH), University of Birmingham, Birmingham, UK; SPMIC, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Susan T Francis
- SPMIC, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Stephen D Mayhew
- Centre for Human Brain Health (CHBH), University of Birmingham, Birmingham, UK.
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12
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Shi F, Dey N, Ashour AS, Sifaki-Pistolla D, Sherratt RS. Meta-KANSEI Modeling with Valence-Arousal fMRI Dataset of Brain. Cognit Comput 2018. [DOI: 10.1007/s12559-018-9614-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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13
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Jin L, Sun J, Xu Z, Yang X, Liu P, Qin W. Intersubject Synchronisation Analysis of Brain Activity Associated with the Instant Effects of Acupuncture: An Fmri Study. Acupunct Med 2018; 36:14-20. [DOI: 10.1136/acupmed-2016-011327] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/22/2017] [Indexed: 11/03/2022]
Abstract
Objective To use a promising analytical method, namely intersubject synchronisation (ISS), to evaluate the brain activity associated with the instant effects of acupuncture and compare the findings with traditional general linear model (GLM) methods. Methods 30 healthy volunteers were recruited for this study. Block-designed manual acupuncture stimuli were delivered at SP6, and de qi sensations were measured after acupuncture stimulation. All subjects underwent functional MRI (fMRI) scanning during the acupuncture stimuli. The fMRI data were separately analysed by ISS and traditional GLM methods. Results All subjects experienced de qi sensations. ISS analysis showed that the regions activated during acupuncture stimulation at SP6 were mainly divided into five clusters based on the time courses. The time courses of clusters 1 and 2 were in line with the acupuncture stimulation pattern, and the active regions were mainly involved in the sensorimotor system and salience network. Clusters 3, 4 and 5 displayed an almost contrary time course relative to the stimulation pattern. The brain regions activated included the default mode network, descending pain modulation pathway and visual cortices. GLM analysis indicated that the brain responses associated with the instant effects of acupuncture were largely implicated in sensory and motor processing and sensory integration. Conclusion The ISS analysis considered the sustained effect of acupuncture and uncovered additional information not shown by GLM analysis. We suggest that ISS may be a suitable approach to investigate the brain responses associated with the instant effects of acupuncture.
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Affiliation(s)
- Lingmin Jin
- School of Life Sciences and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Jinbo Sun
- School of Life Sciences and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Ziliang Xu
- School of Life Sciences and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Xuejuan Yang
- School of Life Sciences and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Peng Liu
- School of Life Sciences and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Wei Qin
- School of Life Sciences and Technology, Xidian University, Xi'an, Shaanxi, China
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14
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Marino M, Liu Q, Samogin J, Tecchio F, Cottone C, Mantini D, Porcaro C. Neuronal dynamics enable the functional differentiation of resting state networks in the human brain. Hum Brain Mapp 2018; 40:1445-1457. [PMID: 30430697 DOI: 10.1002/hbm.24458] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2018] [Accepted: 10/22/2018] [Indexed: 12/11/2022] Open
Abstract
Intrinsic brain activity is organized in spatial-temporal patterns, called resting-state networks (RSNs), exhibiting specific structural-functional architecture. These networks presumably reflect complex neurophysiological processes and have a central role in distinct perceptual and cognitive functions. In this work, we propose an innovative approach for characterizing RSNs according to their underlying neural oscillations. We investigated specific electrophysiological properties, including spectral features, fractal dimension, and entropy, associated with eight core RSNs derived from high-density electroencephalography (EEG) source-reconstructed signals. Specifically, we found higher synchronization of the gamma-band activity and higher fractal dimension values in perceptual (PNs) compared with higher cognitive (HCNs) networks. The inspection of this underlying rapid activity becomes of utmost importance for assessing possible alterations related to specific brain disorders. The disruption of the coordinated activity of RSNs may result in altered behavioral and perceptual states. Thus, this approach could potentially be used for the early detection and treatment of neurological disorders.
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Affiliation(s)
- Marco Marino
- Research Center for Motor Control and Neuroplasticity, KU Leuven, Leuven, Belgium.,Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
| | - Quanying Liu
- Research Center for Motor Control and Neuroplasticity, KU Leuven, Leuven, Belgium.,Division of Engineering and Applied Science, California Institute of Technology, Pasadena, California.,Neurosciences, Huntington Medical Research Institutes, Pasadena, California
| | - Jessica Samogin
- Research Center for Motor Control and Neuroplasticity, KU Leuven, Leuven, Belgium
| | - Franca Tecchio
- ISTC-CNR, Rome, Italy.,Fondazione Policlinico Gemelli IRCCS, Rome, Italy
| | | | - Dante Mantini
- Research Center for Motor Control and Neuroplasticity, KU Leuven, Leuven, Belgium.,Functional Neuroimaging Laboratory, Fondazione Ospedale San Camillo, IRCCS, Venezia, Italy
| | - Camillo Porcaro
- Research Center for Motor Control and Neuroplasticity, KU Leuven, Leuven, Belgium.,ISTC-CNR, Rome, Italy.,Centre for Human Brain Health and School of Psychology, University of Birmingham, Birmingham, United Kingdom.,Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.,S. Anna Institute and Research in Advanced Neurorehabilitation (RAN) Crotone, Italy
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15
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Abstract
The ability to discriminate signal from noise plays a key role in the analysis and interpretation of functional magnetic resonance imaging (fMRI) measures of brain activity. Over the past two decades, a number of major sources of noise have been identified, including system-related instabilities, subject motion, and physiological fluctuations. This article reviews the characteristics of the various noise sources as well as the mechanisms through which they affect the fMRI signal. Approaches for distinguishing signal from noise and the associated challenges are also reviewed. These challenges reflect the fact that some noise sources, such as respiratory activity, are generated by the same underlying brain networks that give rise to functional signals that are of interest.
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Affiliation(s)
- Thomas T Liu
- Center for Functional MRI, University of California San Diego, 9500 Gilman Drive MC 0677, La Jolla, CA 92093, United States; Departments of Radiology, Psychiatry and Bioengineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, United States.
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16
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Jorge J, Figueiredo P, Gruetter R, van der Zwaag W. Mapping and characterization of positive and negative BOLD responses to visual stimulation in multiple brain regions at 7T. Hum Brain Mapp 2018; 39:2426-2441. [PMID: 29464809 DOI: 10.1002/hbm.24012] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2017] [Revised: 02/05/2018] [Accepted: 02/10/2018] [Indexed: 11/06/2022] Open
Abstract
External stimuli and tasks often elicit negative BOLD responses in various brain regions, and growing experimental evidence supports that these phenomena are functionally meaningful. In this work, the high sensitivity available at 7T was explored to map and characterize both positive (PBRs) and negative BOLD responses (NBRs) to visual checkerboard stimulation, occurring in various brain regions within and beyond the visual cortex. Recently-proposed accelerated fMRI techniques were employed for data acquisition, and procedures for exclusion of large draining vein contributions, together with ICA-assisted denoising, were included in the analysis to improve response estimation. Besides the visual cortex, significant PBRs were found in the lateral geniculate nucleus and superior colliculus, as well as the pre-central sulcus; in these regions, response durations increased monotonically with stimulus duration, in tight covariation with the visual PBR duration. Significant NBRs were found in the visual cortex, auditory cortex, default-mode network (DMN) and superior parietal lobule; NBR durations also tended to increase with stimulus duration, but were significantly less sustained than the visual PBR, especially for the DMN and superior parietal lobule. Responses in visual and auditory cortex were further studied for checkerboard contrast dependence, and their amplitudes were found to increase monotonically with contrast, linearly correlated with the visual PBR amplitude. Overall, these findings suggest the presence of dynamic neuronal interactions across multiple brain regions, sensitive to stimulus intensity and duration, and demonstrate the richness of information obtainable when jointly mapping positive and negative BOLD responses at a whole-brain scale, with ultra-high field fMRI.
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Affiliation(s)
- João Jorge
- Institute for Systems and Robotics and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal.,Laboratory for Functional and Metabolic Imaging, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Patrícia Figueiredo
- Institute for Systems and Robotics and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Rolf Gruetter
- Laboratory for Functional and Metabolic Imaging, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.,Department of Radiology, University of Lausanne, Lausanne, Switzerland.,Department of Radiology, University of Geneva, Geneva, Switzerland
| | - Wietske van der Zwaag
- Biomedical Imaging Research Center, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.,Spinoza Institute for Neuroimaging, Royal Netherlands Academy for Arts and Sciences, Amsterdam, The Netherlands
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17
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Zuo N, Yang Z, Liu Y, Li J, Jiang T. Both activated and less-activated regions identified by functional MRI reconfigure to support task executions. Brain Behav 2018; 8:e00893. [PMID: 29568689 PMCID: PMC5853621 DOI: 10.1002/brb3.893] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2017] [Accepted: 10/26/2017] [Indexed: 12/22/2022] Open
Abstract
INTRODUCTION Functional magnetic resonance imaging (fMRI) has become very important for noninvasively characterizing BOLD signal fluctuations, which reflect the changes in neuronal firings in the brain. Unlike the activation detection strategy utilized with fMRI, which only emphasizes the synchronicity between the functional nodes (activated regions) and the task design, brain connectivity and network theory are able to decipher the interactive structure across the entire brain. However, little is known about whether and how the activated/less-activated interactions are associated with the functional changes that occur when the brain changes from the resting state to a task state. What are the key networks that play important roles in the brain state changes? METHODS We used the fMRI data from the Human Connectome Project S500 release to examine the changes of network efficiency, interaction strength, and fractional modularity contributions of both the local and global networks, when the subjects change from the resting state to seven different task states. RESULTS We found that, from the resting state to each of seven task states, both the activated and less-activated regions had significantly changed to be in line with, and comparably contributed to, a global network reconfiguration. We also found that three networks, the default mode network, frontoparietal network, and salience network, dominated the flexible reconfiguration of the brain. CONCLUSIONS This study shows quantitatively that contributions from both activated and less-activated regions enable the global functional network to respond when the brain switches from the resting state to a task state and suggests the necessity of considering large-scale networks (rather than only activated regions) when investigating brain functions in imaging cognitive neuroscience.
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Affiliation(s)
- Nianming Zuo
- Brainnetome CenterInstitute of Automation Chinese Academy of Sciences Beijing China.,National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China.,University of Chinese Academy of Sciences Beijing China
| | - Zhengyi Yang
- Brainnetome CenterInstitute of Automation Chinese Academy of Sciences Beijing China.,National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China
| | - Yong Liu
- Brainnetome CenterInstitute of Automation Chinese Academy of Sciences Beijing China.,National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China.,CAS Center for Excellence in Brain Science and Intelligence Technology Institute of Automation Chinese Academy of Sciences Beijing China.,University of Chinese Academy of Sciences Beijing China
| | - Jin Li
- Brainnetome CenterInstitute of Automation Chinese Academy of Sciences Beijing China.,National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China
| | - Tianzi Jiang
- Brainnetome CenterInstitute of Automation Chinese Academy of Sciences Beijing China.,National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China.,CAS Center for Excellence in Brain Science and Intelligence Technology Institute of Automation Chinese Academy of Sciences Beijing China.,Key Laboratory for NeuroInformation of the Ministry of Education School of Life Science and Technology University of Electronic Science and Technology of China Chengdu China.,The Queensland Brain Institute University of Queensland Brisbane QLD Australia.,University of Chinese Academy of Sciences Beijing China
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18
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Medaglia JD, Huang W, Karuza EA, Kelkar A, Thompson-Schill SL, Ribeiro A, Bassett DS. Functional Alignment with Anatomical Networks is Associated with Cognitive Flexibility. Nat Hum Behav 2017; 2:156-164. [PMID: 30498789 PMCID: PMC6258039 DOI: 10.1038/s41562-017-0260-9] [Citation(s) in RCA: 68] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Cognitive flexibility describes the human ability to switch between modes of mental function to achieve goals. Mental switching is accompanied by transient changes in brain activity, which must occur atop an anatomical architecture that bridges disparate cortical and subcortical regions by underlying white matter tracts. However, an integrated perspective regarding how white matter networks might constrain brain dynamics during cognitive processes requiring flexibility has remained elusive. To address this challenge, we applied emerging tools from graph signal processing to examine whether BOLD signals measured at each point in time correspond to complex underlying anatomical networks in 28 individuals performing a perceptual task that probed cognitive flexibility. We found that the alignment between functional signals and the architecture of the underlying white matter network was associated with greater cognitive flexibility across subjects. By computing a concise measure using multi-modal neuroimaging data, we uncovered an integrated structure-function correlate of human behavior.
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Affiliation(s)
- John D Medaglia
- Department of Psychology, Drexel University, Philadelphia, PA, 19104 USA.,Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104 USA
| | - Weiyu Huang
- Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA, 19104 USA
| | - Elisabeth A Karuza
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, 19104 USA
| | - Apoorva Kelkar
- Department of Psychology, Drexel University, Philadelphia, PA, 19104 USA
| | | | - Alejandro Ribeiro
- Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA, 19104 USA
| | - Danielle S Bassett
- Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA, 19104 USA.,Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104 USA
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19
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Liu TT, Nalci A, Falahpour M. The global signal in fMRI: Nuisance or Information? Neuroimage 2017; 150:213-229. [PMID: 28213118 DOI: 10.1016/j.neuroimage.2017.02.036] [Citation(s) in RCA: 234] [Impact Index Per Article: 33.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2016] [Revised: 02/05/2017] [Accepted: 02/13/2017] [Indexed: 01/17/2023] Open
Abstract
The global signal is widely used as a regressor or normalization factor for removing the effects of global variations in the analysis of functional magnetic resonance imaging (fMRI) studies. However, there is considerable controversy over its use because of the potential bias that can be introduced when it is applied to the analysis of both task-related and resting-state fMRI studies. In this paper we take a closer look at the global signal, examining in detail the various sources that can contribute to the signal. For the most part, the global signal has been treated as a nuisance term, but there is growing evidence that it may also contain valuable information. We also examine the various ways that the global signal has been used in the analysis of fMRI data, including global signal regression, global signal subtraction, and global signal normalization. Furthermore, we describe new ways for understanding the effects of global signal regression and its relation to the other approaches.
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Affiliation(s)
- Thomas T Liu
- Center for Functional MRI, University of California San Diego, 9500 Gilman Drive MC 0677, La Jolla, CA 92093, United States; Departments of Radiology, Psychiatry, and Bioengineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, United States.
| | - Alican Nalci
- Center for Functional MRI, University of California San Diego, 9500 Gilman Drive MC 0677, La Jolla, CA 92093, United States; Department of Electrical and Computer Engineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, United States.
| | - Maryam Falahpour
- Center for Functional MRI, University of California San Diego, 9500 Gilman Drive MC 0677, La Jolla, CA 92093, United States.
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20
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Liu TT. Noise contributions to the fMRI signal: An overview. Neuroimage 2016; 143:141-151. [PMID: 27612646 DOI: 10.1016/j.neuroimage.2016.09.008] [Citation(s) in RCA: 139] [Impact Index Per Article: 17.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2016] [Revised: 09/01/2016] [Accepted: 09/03/2016] [Indexed: 01/21/2023] Open
Abstract
The ability to discriminate signal from noise plays a key role in the analysis and interpretation of functional magnetic resonance imaging (fMRI) measures of brain activity. Over the past two decades, a number of major sources of noise have been identified, including system-related instabilities, subject motion, and physiological fluctuations. This article reviews the characteristics of the various noise sources as well as the mechanisms through which they affect the fMRI signal. Approaches for distinguishing signal from noise and the associated challenges are also reviewed. These challenges reflect the fact that some noise sources, such as respiratory activity, are generated by the same underlying brain networks that give rise to functional signals that are of interest.
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Affiliation(s)
- Thomas T Liu
- Center for Functional MRI, University of California San Diego, 9500 Gilman Drive MC 0677, La Jolla, CA 92093, United States; Departments of Radiology, Psychiatry and Bioengineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, United States.
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