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Hokama Y, Nishimura M, Usugi R, Fujiwara K, Katagiri C, Takagi H, Ishiuchi S. Recovery from the damage of cranial radiation modulated by memantine, an NMDA receptor antagonist, combined with hyperbaric oxygen therapy. Neuro Oncol 2022; 25:108-122. [PMID: 35762568 PMCID: PMC9825311 DOI: 10.1093/neuonc/noac162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND Radiotherapy is an important treatment option for central nervous system malignancies. However, cranial radiation induces hippocampal dysfunction and white matter injury; this leads to cognitive dysfunction, and results in a reduced quality of life in patients. Excitatory glutamate signaling through N-methyl-d-aspartate receptors (NMDARs) plays a central role both in hippocampal neurogenesis and in the myelination of oligodendrocytes in the cerebrum. METHODS We provide a method for quantifying neurogenesis in human subjects in live brain during cancer therapy. Neuroimaging using originally created behavioral tasks was employed to examine human hippocampal memory pathway in patients with brain disorders. RESULTS Treatment with memantine, a non-competitive NMDAR antagonist, reversed impairment in hippocampal pattern separation networks as detected by functional magnetic resonance imaging. Hyperbaric preconditioning of the patients just before radiotherapy with memantine mostly reversed white matter injury as detected by whole brain analysis with Tract-Based Spatial Statics. Neuromodulation combined with the administration of hyperbaric oxygen therapy and memantine during radiotherapy facilitated the restoration of hippocampal function and white matter integrity, and improved higher cognitive function in patients receiving cranial radiation. CONCLUSIONS The method described herein, for diagnosis of hippocampal dysfunction, and therapeutic intervention can be utilized to restore some of the cognitive decline experienced by patients who have received cranial radiation. The underlying mechanism of restoration is the production of new neurons, which enhances functionality in pattern separation networks in the hippocampi, resulting in an increase in cognitive score, and restoration of microstructural integrity of white matter tracts revealed by Tract-Based Spatial Statics Analysis.
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Affiliation(s)
- Yohei Hokama
- Department of Neurosurgery, Graduate School of Medicine, University of The Ryukyus, 207 Uehara, Nishihara-machi, Okinawa 903-0215, Japan
| | - Masahiko Nishimura
- Department of Neurosurgery, Graduate School of Medicine, University of The Ryukyus, 207 Uehara, Nishihara-machi, Okinawa 903-0215, Japan
| | - Ryoichi Usugi
- Department of Neurosurgery, Graduate School of Medicine, University of The Ryukyus, 207 Uehara, Nishihara-machi, Okinawa 903-0215, Japan
| | - Kyoko Fujiwara
- Department of Neurosurgery, Graduate School of Medicine, University of The Ryukyus, 207 Uehara, Nishihara-machi, Okinawa 903-0215, Japan
| | - Chiaki Katagiri
- Department of Neurosurgery, Graduate School of Medicine, University of The Ryukyus, 207 Uehara, Nishihara-machi, Okinawa 903-0215, Japan
| | - Hiroshi Takagi
- Department of Neurosurgery, Graduate School of Medicine, University of The Ryukyus, 207 Uehara, Nishihara-machi, Okinawa 903-0215, Japan
| | - Shogo Ishiuchi
- Corresponding Author: Dr. Shogo Ishiuchi, Department of Neurosurgery, Graduate School of Medicine, University of The Ryukyus, 207 Uehara, Nishihara-machi, Okinawa 903-0215, Japan ()
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2
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Northoff G, Vatansever D, Scalabrini A, Stamatakis EA. Ongoing Brain Activity and Its Role in Cognition: Dual versus Baseline Models. Neuroscientist 2022:10738584221081752. [PMID: 35611670 DOI: 10.1177/10738584221081752] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
What is the role of the brain's ongoing activity for cognition? The predominant perspectives associate ongoing brain activity with resting state, the default-mode network (DMN), and internally oriented mentation. This triad is often contrasted with task states, non-DMN brain networks, and externally oriented mentation, together comprising a "dual model" of brain and cognition. In opposition to this duality, however, we propose that ongoing brain activity serves as a neuronal baseline; this builds upon Raichle's original search for the default mode of brain function that extended beyond the canonical default-mode brain regions. That entails what we refer to as the "baseline model." Akin to an internal biological clock for the rest of the organism, the ongoing brain activity may serve as an internal point of reference or standard by providing a shared neural code for the brain's rest as well as task states, including their associated cognition. Such shared neural code is manifest in the spatiotemporal organization of the brain's ongoing activity, including its global signal topography and dynamics like intrinsic neural timescales. We conclude that recent empirical evidence supports a baseline model over the dual model; the ongoing activity provides a global shared neural code that allows integrating the brain's rest and task states, its DMN and non-DMN, and internally and externally oriented cognition.
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3
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Li X, Fischer H, Manzouri A, Månsson KNT, Li TQ. A Quantitative Data-Driven Analysis Framework for Resting-State Functional Magnetic Resonance Imaging: A Study of the Impact of Adult Age. Front Neurosci 2021; 15:768418. [PMID: 34744623 PMCID: PMC8565286 DOI: 10.3389/fnins.2021.768418] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 09/28/2021] [Indexed: 01/08/2023] Open
Abstract
The objective of this study is to introduce a new quantitative data-driven analysis (QDA) framework for the analysis of resting-state fMRI (R-fMRI) and use it to investigate the effect of adult age on resting-state functional connectivity (RFC). Whole-brain R-fMRI measurements were conducted on a 3T clinical MRI scanner in 227 healthy adult volunteers (N = 227, aged 18-76 years old, male/female = 99/128). With the proposed QDA framework we derived two types of voxel-wise RFC metrics: the connectivity strength index and connectivity density index utilizing the convolutions of the cross-correlation histogram with different kernels. Furthermore, we assessed the negative and positive portions of these metrics separately. With the QDA framework we found age-related declines of RFC metrics in the superior and middle frontal gyri, posterior cingulate cortex (PCC), right insula and inferior parietal lobule of the default mode network (DMN), which resembles previously reported results using other types of RFC data processing methods. Importantly, our new findings complement previously undocumented results in the following aspects: (1) the PCC and right insula are anti-correlated and tend to manifest simultaneously declines of both the negative and positive connectivity strength with subjects' age; (2) separate assessment of the negative and positive RFC metrics provides enhanced sensitivity to the aging effect; and (3) the sensorimotor network depicts enhanced negative connectivity strength with the adult age. The proposed QDA framework can produce threshold-free and voxel-wise RFC metrics from R-fMRI data. The detected adult age effect is largely consistent with previously reported studies using different R-fMRI analysis approaches. Moreover, the separate assessment of the negative and positive contributions to the RFC metrics can enhance the RFC sensitivity and clarify some of the mixed results in the literature regarding to the DMN and sensorimotor network involvement in adult aging.
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Affiliation(s)
- Xia Li
- Institute of Informatics Engineering, China Jiliang University, Hangzhou, China
| | - Håkan Fischer
- Department of Psychology, Stockholm University, Stockholm, Sweden.,Stockholm University Brain Imaging Centre, Stockholm, Sweden
| | | | - Kristoffer N T Månsson
- Department of Psychology, Stockholm University, Stockholm, Sweden.,Centre of Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Tie-Qiang Li
- Institute of Informatics Engineering, China Jiliang University, Hangzhou, China.,Department of Clinical Science, Intervention, and Technology, Karolinska Institute, Solna, Sweden.,Department of Medical Radiation and Nuclear Medicine, Karolinska University Hospital, Solna, Sweden
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4
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Kupis L, Goodman ZT, Kornfeld S, Hoang S, Romero C, Dirks B, Dehoney J, Chang C, Spreng RN, Nomi JS, Uddin LQ. Brain Dynamics Underlying Cognitive Flexibility Across the Lifespan. Cereb Cortex 2021; 31:5263-5274. [PMID: 34145442 PMCID: PMC8491685 DOI: 10.1093/cercor/bhab156] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 05/13/2021] [Accepted: 05/16/2021] [Indexed: 11/14/2022] Open
Abstract
The neural mechanisms contributing to flexible cognition and behavior and how they change with development and aging are incompletely understood. The current study explored intrinsic brain dynamics across the lifespan using resting-state fMRI data (n = 601, 6-85 years) and examined the interactions between age and brain dynamics among three neurocognitive networks (midcingulo-insular network, M-CIN; medial frontoparietal network, M-FPN; and lateral frontoparietal network, L-FPN) in relation to behavioral measures of cognitive flexibility. Hierarchical multiple regression analysis revealed brain dynamics among a brain state characterized by co-activation of the L-FPN and M-FPN, and brain state transitions, moderated the relationship between quadratic effects of age and cognitive flexibility as measured by scores on the Delis-Kaplan Executive Function System (D-KEFS) test. Furthermore, simple slope analyses of significant interactions revealed children and older adults were more likely to exhibit brain dynamic patterns associated with poorer cognitive flexibility compared with younger adults. Our findings link changes in cognitive flexibility observed with age with the underlying brain dynamics supporting these changes. Preventative and intervention measures should prioritize targeting these networks with cognitive flexibility training to promote optimal outcomes across the lifespan.
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Affiliation(s)
- Lauren Kupis
- Department of Psychology, University of Miami, Coral Gables, FL 33124, USA
| | - Zachary T Goodman
- Department of Psychology, University of Miami, Coral Gables, FL 33124, USA
| | - Salome Kornfeld
- Department of Psychology, University of Miami, Coral Gables, FL 33124, USA
| | - Stephanie Hoang
- Department of Psychology, University of Miami, Coral Gables, FL 33124, USA
| | - Celia Romero
- Department of Psychology, University of Miami, Coral Gables, FL 33124, USA
| | - Bryce Dirks
- Department of Psychology, University of Miami, Coral Gables, FL 33124, USA
| | - Joseph Dehoney
- Department of Psychology, University of Miami, Coral Gables, FL 33124, USA
| | - Catie Chang
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37235, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA
| | - R Nathan Spreng
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC H3A 2B4, Canada
| | - Jason S Nomi
- Department of Psychology, University of Miami, Coral Gables, FL 33124, USA
| | - Lucina Q Uddin
- Department of Psychology, University of Miami, Coral Gables, FL 33124, USA
- Neuroscience Program, University of Miami Miller School of Medicine, Miami, FL 33136, USA
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5
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Marshall E, Nomi JS, Dirks B, Romero C, Kupis L, Chang C, Uddin LQ. Coactivation pattern analysis reveals altered salience network dynamics in children with autism spectrum disorder. Netw Neurosci 2020; 4:1219-1234. [PMID: 33409437 PMCID: PMC7781614 DOI: 10.1162/netn_a_00163] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Accepted: 07/29/2020] [Indexed: 12/17/2022] Open
Abstract
Brain connectivity studies of autism spectrum disorder (ASD) have historically relied on static measures of functional connectivity. Recent work has focused on identifying transient configurations of brain activity, yet several open questions remain regarding the nature of specific brain network dynamics in ASD. We used a dynamic coactivation pattern (CAP) approach to investigate the salience/midcingulo-insular (M-CIN) network, a locus of dysfunction in ASD, in a large multisite resting-state fMRI dataset collected from 172 children (ages 6–13 years; n = 75 ASD; n = 138 male). Following brain parcellation by using independent component analysis, dynamic CAP analyses were conducted and k-means clustering was used to determine transient activation patterns of the M-CIN. The frequency of occurrence of different dynamic CAP brain states was then compared between children with ASD and typically developing (TD) children. Dynamic brain configurations characterized by coactivation of the M-CIN with central executive/lateral fronto-parietal and default mode/medial fronto-parietal networks appeared less frequently in children with ASD compared with TD children. This study highlights the utility of time-varying approaches for studying altered M-CIN function in prevalent neurodevelopmental disorders. We speculate that altered M-CIN dynamics in ASD may underlie the inflexible behaviors commonly observed in children with the disorder. Autism spectrum disorder (ASD) is a neurodevelopmental disorder associated with altered patterns of functional brain connectivity. Little is currently known about how moment-to-moment brain dynamics differ in children with ASD and typically developing (TD) children. Altered functional integrity of the midcingulo-insular network (M-CIN) has been implicated in the neurobiology of ASD. Here we use a novel coactivation analysis approach applied to a large sample of resting-state fMRI data collected from children with ASD and TD children to demonstrate altered patterns of M-CIN dynamics in children with the disorder. We speculate that these atypical patterns of brain dynamics may underlie behavioral inflexibility in ASD.
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Affiliation(s)
- Emily Marshall
- Department of Psychology, University of Miami, Coral Gables, FL, USA
| | - Jason S Nomi
- Department of Psychology, University of Miami, Coral Gables, FL, USA
| | - Bryce Dirks
- Department of Psychology, University of Miami, Coral Gables, FL, USA
| | - Celia Romero
- Department of Psychology, University of Miami, Coral Gables, FL, USA
| | - Lauren Kupis
- Department of Psychology, University of Miami, Coral Gables, FL, USA
| | - Catie Chang
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Lucina Q Uddin
- Department of Psychology, University of Miami, Coral Gables, FL, USA
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6
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Uddin LQ. Bring the Noise: Reconceptualizing Spontaneous Neural Activity. Trends Cogn Sci 2020; 24:734-746. [PMID: 32600967 PMCID: PMC7429348 DOI: 10.1016/j.tics.2020.06.003] [Citation(s) in RCA: 69] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Revised: 06/04/2020] [Accepted: 06/05/2020] [Indexed: 12/17/2022]
Abstract
Definitions of what constitutes the 'signal of interest' in neuroscience can be controversial, due in part to continuously evolving notions regarding the significance of spontaneous neural activity. This review highlights how the challenge of separating brain signal from noise has led to new conceptualizations of brain functional organization at both the micro- and macroscopic level. Recent debates in the functional neuroimaging community surrounding artifact removal processes have revived earlier discussions surrounding how to appropriately isolate and measure neuronal signals against a background of noise from various sources. Insights from electrophysiological studies and computational modeling can inform current theory and data analytic practices in human functional neuroimaging, given that signal and noise may be inextricably linked in the brain.
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Affiliation(s)
- Lucina Q Uddin
- Department of Psychology, University of Miami, PO Box 248185-0751, Coral Gables, FL 33124, USA; Neuroscience Program, University of Miami Miller School of Medicine, Miami, FL 33136, USA.
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7
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Li J, Bolt T, Bzdok D, Nomi JS, Yeo BTT, Spreng RN, Uddin LQ. Topography and behavioral relevance of the global signal in the human brain. Sci Rep 2019; 9:14286. [PMID: 31582792 PMCID: PMC6776616 DOI: 10.1038/s41598-019-50750-8] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2019] [Accepted: 09/18/2019] [Indexed: 11/09/2022] Open
Abstract
The global signal in resting-state functional MRI data is considered to be dominated by physiological noise and artifacts, yet a growing literature suggests that it also carries information about widespread neural activity. The biological relevance of the global signal remains poorly understood. Applying principal component analysis to a large neuroimaging dataset, we found that individual variation in global signal topography recapitulates well-established patterns of large-scale functional brain networks. Using canonical correlation analysis, we delineated relationships between individual differences in global signal topography and a battery of phenotypes. The first canonical variate of the global signal, resembling the frontoparietal control network, was significantly related to an axis of positive and negative life outcomes and psychological function. These results suggest that the global signal contains a rich source of information related to trait-level cognition and behavior. This work has significant implications for the contentious debate over artifact removal practices in neuroimaging.
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Affiliation(s)
- Jingwei Li
- ECE, CIRC, N.1 & MNP, National University of Singapore, Singapore, Singapore
| | - Taylor Bolt
- Data Science Division, Gallup, Atlanta, GA, USA
| | - Danilo Bzdok
- Department of Psychiatry, Psychotherapy and Psychosomatics, Aachen University, Aachen, Germany.,JARA, Translational Brain Medicine, Aachen, Germany.,Parietal Team, INRIA, Neurospin, bat 145, CEA Saclay, 91191, Gif-sur-Yvette, France
| | - Jason S Nomi
- Department of Psychology, University of Miami, Coral Gables, FL, USA
| | - B T Thomas Yeo
- ECE, CIRC, N.1 & MNP, National University of Singapore, Singapore, Singapore
| | - R Nathan Spreng
- Laboratory of Brain and Cognition, Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada. .,Departments of Psychiatry and Psychology, McGill University, Montreal, QC, Canada.
| | - Lucina Q Uddin
- Department of Psychology, University of Miami, Coral Gables, FL, USA. .,Neuroscience Program, University of Miami Miller School of Medicine, Miami, FL, USA.
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8
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Shulman RG, Rothman DL. A Non-cognitive Behavioral Model for Interpreting Functional Neuroimaging Studies. Front Hum Neurosci 2019; 13:28. [PMID: 30914933 PMCID: PMC6421518 DOI: 10.3389/fnhum.2019.00028] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Accepted: 01/21/2019] [Indexed: 12/17/2022] Open
Abstract
The dominant model for interpreting brain imaging experiments, which we refer to as the Standard Cognitive Model (SCM), assumes that the brain is organized in support of mental processes that control behavior. However, functional neuroimaging experiments of cognitive tasks have not shown clear anatomic segregation between mental processes originally proposed by this model. This failing has been blamed on limitations in imaging technology and non-linearity in the brain's implementation of these processes. However, the validity of the underlying cognitive models used to describe the brain has rarely been questioned or directly tested against imaging results. We propose an alternative model of brain function, that we term the Non-cognitive Behavioral Model (NBM), which correlates observed human behavior directly with measured brain activity without making assumptions about intervening cognitive processes. Our model derives from behavioral psychology but is extended to include brain activity, in addition to behavior, as observables. A further extension is the role of neuroplasticity, as opposed to innate cognitive processes, in developing the brain's support of cognitive behavior. We present the theoretical basis with which the SCM maps cognitive processes onto functional magnetic resonance and positron emission tomography images and compare and contrast with the NBM. We also describe how the NBM can be used experimentally to study how the brain supports behavior. Two applications are presented that support the usefulness of the NBM. In one, the NBM use of the total functional imaging signal (not just the differences between states) provides a stronger correlation of neural activity with the behavioral state of consciousness than the SCM approach in both anesthesia and coma. The second example reviews studies of facial and object recognition that provide evidence for the NBM proposal that neuroplasticity and experience play key roles in the brain's support of recognition and other behaviors. The conclusions regarding neuroplasticity are then generalized to explain the incomplete functional segregation observed in the application of the SCM to neuroimaging.
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Affiliation(s)
- Robert G. Shulman
- Magnetic Resonance Research Center, Department of Radiology, Yale University School of Medicine, New Haven, CT, United States
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, United States
| | - Douglas L. Rothman
- Magnetic Resonance Research Center, Department of Radiology, Yale University School of Medicine, New Haven, CT, United States
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9
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Pais-Roldán P, Biswal B, Scheffler K, Yu X. Identifying Respiration-Related Aliasing Artifacts in the Rodent Resting-State fMRI. Front Neurosci 2018; 12:788. [PMID: 30455623 PMCID: PMC6230988 DOI: 10.3389/fnins.2018.00788] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2018] [Accepted: 10/12/2018] [Indexed: 12/31/2022] Open
Abstract
Resting-state functional magnetic resonance imaging (rs-fMRI) combined with optogenetics and electrophysiological/calcium recordings in animal models is becoming a popular platform to investigate brain dynamics under specific neurological states. Physiological noise originating from the cardiac and respiration signal is the dominant interference in human rs-fMRI and extensive efforts have been made to reduce these artifacts from the human data. In animal fMRI studies, physiological noise sources including the respiratory and cardiorespiratory artifacts to the rs-fMRI signal fluctuation have typically been less investigated. In this article, we demonstrate evidence of aliasing effects into the low-frequency rs-fMRI signal fluctuation mainly due to respiration-induced B0 offsets in anesthetized rats. This aliased signal was examined by systematically altering the fMRI sampling rate, i.e., the time of repetition (TR), in free-breathing conditions and by adjusting the rate of ventilation. Anesthetized rats under ventilation showed a significantly narrower frequency bandwidth of the aliasing effect than free-breathing animals. It was found that the aliasing effect could be further reduced in ventilated animals with a muscle relaxant. This work elucidates the respiration-related aliasing effects on the rs-fMRI signal fluctuation from anesthetized rats, indicating non-negligible physiological noise needed to be taken care of in both awake and anesthetized animal rs-fMRI studies.
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Affiliation(s)
- Patricia Pais-Roldán
- High-Field Magnetic Resonance Department, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany.,Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Bharat Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, United States
| | - Klaus Scheffler
- High-Field Magnetic Resonance Department, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany.,Department for Biomedical Magnetic Resonance, University of Tuebingen, Tuebingen, Germany
| | - Xin Yu
- High-Field Magnetic Resonance Department, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States
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10
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Bauer AQ, Kraft AW, Baxter GA, Wright PW, Reisman MD, Bice AR, Park JJ, Bruchas MR, Snyder AZ, Lee JM, Culver JP. Effective Connectivity Measured Using Optogenetically Evoked Hemodynamic Signals Exhibits Topography Distinct from Resting State Functional Connectivity in the Mouse. Cereb Cortex 2018; 28:370-386. [PMID: 29136125 PMCID: PMC6057523 DOI: 10.1093/cercor/bhx298] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2017] [Indexed: 02/07/2023] Open
Abstract
Brain connectomics has expanded from histological assessment of axonal projection connectivity (APC) to encompass resting state functional connectivity (RS-FC). RS-FC analyses are efficient for whole-brain mapping, but attempts to explain aspects of RS-FC (e.g., interhemispheric RS-FC) based on APC have been only partially successful. Neuroimaging with hemoglobin alone lacks specificity for determining how activity in a population of cells contributes to RS-FC. Wide-field mapping of optogenetically defined connectivity could provide insights into the brain's structure-function relationship. We combined optogenetics with optical intrinsic signal imaging to create an efficient, optogenetic effective connectivity (Opto-EC) mapping assay. We examined EC patterns of excitatory neurons in awake, Thy1-ChR2 transgenic mice. These Thy1-based EC (Thy1-EC) patterns were evaluated against RS-FC over the cortex. Compared to RS-FC, Thy1-EC exhibited increased spatial specificity, reduced interhemispheric connectivity in regions with strong RS-FC, and appreciable connection strength asymmetry. Comparing the topography of Thy1-EC and RS-FC patterns to maps of APC revealed that Thy1-EC more closely resembled APC than did RS-FC. The more general method of Opto-EC mapping with hemoglobin can be determined for 100 sites in single animals in under an hour, and is amenable to other neuroimaging modalities. Opto-EC mapping represents a powerful strategy for examining evolving connectivity-related circuit plasticity.
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Affiliation(s)
- Adam Q Bauer
- Department of Radiology, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Andrew W Kraft
- Department of Neurology, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Grant A Baxter
- Department of Radiology, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Patrick W Wright
- Department of Radiology, Washington University School of Medicine, Saint Louis, MO 63110, USA.,Department of Biomedical Engineering, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Matthew D Reisman
- Department of Physics, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Annie R Bice
- Department of Radiology, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Jasmine J Park
- Department of Radiology, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Michael R Bruchas
- Department of Biomedical Engineering, Washington University School of Medicine, Saint Louis, MO 63110, USA.,Department of Anesthesiology, Washington University School of Medicine, Saint Louis, MO 63110, USA.,Department of Neuroscience, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Abraham Z Snyder
- Department of Radiology, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Jin-Moo Lee
- Department of Radiology, Washington University School of Medicine, Saint Louis, MO 63110, USA.,Department of Neurology, Washington University School of Medicine, Saint Louis, MO 63110, USA.,Department of Biomedical Engineering, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Joseph P Culver
- Department of Radiology, Washington University School of Medicine, Saint Louis, MO 63110, USA.,Department of Biomedical Engineering, Washington University School of Medicine, Saint Louis, MO 63110, USA.,Department of Physics, Washington University School of Medicine, Saint Louis, MO 63110, USA
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11
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Lv H, Wang Z, Tong E, Williams LM, Zaharchuk G, Zeineh M, Goldstein-Piekarski AN, Ball TM, Liao C, Wintermark M. Resting-State Functional MRI: Everything That Nonexperts Have Always Wanted to Know. AJNR Am J Neuroradiol 2018; 39:1390-1399. [PMID: 29348136 DOI: 10.3174/ajnr.a5527] [Citation(s) in RCA: 168] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Resting-state fMRI was first described by Biswal et al in 1995 and has since then been widely used in both healthy subjects and patients with various neurologic, neurosurgical, and psychiatric disorders. As opposed to paradigm- or task-based functional MR imaging, resting-state fMRI does not require subjects to perform any specific task. The low-frequency oscillations of the resting-state fMRI signal have been shown to relate to the spontaneous neural activity. There are many ways to analyze resting-state fMRI data. In this review article, we will briefly describe a few of these and highlight the advantages and limitations of each. This description is to facilitate the adoption and use of resting-state fMRI in the clinical setting, helping neuroradiologists become familiar with these techniques and applying them for the care of patients with neurologic and psychiatric diseases.
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Affiliation(s)
- H Lv
- From the Department of Radiology (H.L., Z.W.), Beijing Friendship Hospital, Capital Medical University, Beijing, China
- Department of Radiology (H.L., G.Z., M.Z., M.W.), Neuroradiology Division
| | - Z Wang
- From the Department of Radiology (H.L., Z.W.), Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - E Tong
- Department of Radiology (E.T.), Neuroradiology Section, University of California, San Francisco, San Francisco, California
| | - L M Williams
- Department of Psychiatry and Behavioral Sciences (L.M.W., A.N.G.-P., T.M.B.), Stanford University, Stanford, California
| | - G Zaharchuk
- Department of Radiology (H.L., G.Z., M.Z., M.W.), Neuroradiology Division
| | - M Zeineh
- Department of Radiology (H.L., G.Z., M.Z., M.W.), Neuroradiology Division
| | - A N Goldstein-Piekarski
- Department of Psychiatry and Behavioral Sciences (L.M.W., A.N.G.-P., T.M.B.), Stanford University, Stanford, California
| | - T M Ball
- Department of Psychiatry and Behavioral Sciences (L.M.W., A.N.G.-P., T.M.B.), Stanford University, Stanford, California
| | - C Liao
- Department of Radiology (C.L.), Yunnan Tumor Hospital (The Third Affiliated Hospital of Kunming Medical University), Kunming, Yunnan Province, China
| | - M Wintermark
- Department of Radiology (H.L., G.Z., M.Z., M.W.), Neuroradiology Division
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12
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Impact of Global Mean Normalization on Regional Glucose Metabolism in the Human Brain. Neural Plast 2018; 2018:6120925. [PMID: 30008742 PMCID: PMC6020504 DOI: 10.1155/2018/6120925] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2017] [Revised: 02/20/2018] [Accepted: 04/03/2018] [Indexed: 02/02/2023] Open
Abstract
Because the human brain consumes a disproportionate fraction of the resting body's energy, positron emission tomography (PET) measurements of absolute glucose metabolism (CMRglc) can serve as disease biomarkers. Global mean normalization (GMN) of PET data reveals disease-based differences from healthy individuals as fractional changes across regions relative to a global mean. To assess the impact of GMN applied to metabolic data, we compared CMRglc with and without GMN in healthy awake volunteers with eyes closed (i.e., control) against specific physiological/clinical states, including healthy/awake with eyes open, healthy/awake but congenitally blind, healthy/sedated with anesthetics, and patients with disorders of consciousness. Without GMN, global CMRglc alterations compared to control were detected in all conditions except in congenitally blind where regional CMRglc variations were detected in the visual cortex. However, GMN introduced regional and bidirectional CMRglc changes at smaller fractions of the quantitative delocalized changes. While global information was lost with GMN, the quantitative approach (i.e., a validated method for quantitative baseline metabolic activity without GMN) not only preserved global CMRglc alterations induced by opening eyes, sedation, and varying consciousness but also detected regional CMRglc variations in the congenitally blind. These results caution the use of GMN upon PET-measured CMRglc data in health and disease.
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Vos de Wael R, Hyder F, Thompson GJ. Effects of Tissue-Specific Functional Magnetic Resonance Imaging Signal Regression on Resting-State Functional Connectivity. Brain Connect 2018; 7:482-490. [PMID: 28825320 DOI: 10.1089/brain.2016.0465] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
Neuroimaging studies typically consider white matter as unchanging in different neural and metabolic states. However, a recent study demonstrated that white matter signal regression (WMSR) produced a similar loss of neurometabolic information to global (whole-brain) signal regression (GSR) in resting-state functional magnetic resonance imaging (R-fMRI) data. This was unexpected as the loss of information would normally be attributed to neural activity within gray matter correlating with the global R-fMRI signal. Indeed, WMSR has been suggested as an alternative to avoid such pitfalls in GSR. To address these concerns about tissue-specific regression in R-fMRI data analysis, we performed GSR, WMSR, and gray matter signal regression (GMSR) on R-fMRI data from the 1000 Functional Connectomes Project. We describe several regional and motion-related differences between different types of regressions. However, the overall effects of concern, particularly network-specific alteration of correlation coefficients, are present for all regressions. This suggests that tissue-specific regression is not an adequate strategy to counter pitfalls of GSR. Conversely, if GSR is desired, but the studied disease state excludes either gray matter or white matter from analysis (e.g., due to tissue atrophy), our results indicate that WMSR or GMSR may reproduce the gross effects of GSR.
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Affiliation(s)
- Reinder Vos de Wael
- 1 McConnell Brain Imaging Centre, McGill University , Montreal, Canada .,2 Neuroimaging Center, University of Groningen , Groningen, The Netherlands .,3 Magnetic Resonance Research Center (MRRC), Yale University , New Haven, Connecticut
| | - Fahmeed Hyder
- 3 Magnetic Resonance Research Center (MRRC), Yale University , New Haven, Connecticut.,4 Department of Radiology and Biomedical Imaging, Yale University , New Haven, Connecticut.,5 Department of Biomedical Engineering, Yale University , New Haven, Connecticut.,6 Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University , New Haven, Connecticut
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14
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Kannurpatti SS. Mitochondrial calcium homeostasis: Implications for neurovascular and neurometabolic coupling. J Cereb Blood Flow Metab 2017; 37:381-395. [PMID: 27879386 PMCID: PMC5381466 DOI: 10.1177/0271678x16680637] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Mitochondrial function is critical to maintain high rates of oxidative metabolism supporting energy demands of both spontaneous and evoked neuronal activity in the brain. Mitochondria not only regulate energy metabolism, but also influence neuronal signaling. Regulation of "energy metabolism" and "neuronal signaling" (i.e. neurometabolic coupling), which are coupled rather than independent can be understood through mitochondria's integrative functions of calcium ion (Ca2+) uptake and cycling. While mitochondrial Ca2+ do not affect hemodynamics directly, neuronal activity changes are mechanistically linked to functional hyperemic responses (i.e. neurovascular coupling). Early in vitro studies lay the foundation of mitochondrial Ca2+ homeostasis and its functional roles within cells. However, recent in vivo approaches indicate mitochondrial Ca2+ homeostasis as maintained by the role of mitochondrial Ca2+ uniporter (mCU) influences system-level brain activity as measured by a variety of techniques. Based on earlier evidence of subcellular cytoplasmic Ca2+ microdomains and cellular bioenergetic states, a mechanistic model of Ca2+ mobilization is presented to understand systems-level neurovascular and neurometabolic coupling. This integrated view from molecular and cellular to the systems level, where mCU plays a major role in mitochondrial and cellular Ca2+ homeostasis, may explain the wide range of activation-induced coupling across neuronal activity, hemodynamic, and metabolic responses.
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15
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Hyder F, Herman P, Bailey CJ, Møller A, Globinsky R, Fulbright RK, Rothman DL, Gjedde A. Uniform distributions of glucose oxidation and oxygen extraction in gray matter of normal human brain: No evidence of regional differences of aerobic glycolysis. J Cereb Blood Flow Metab 2016; 36:903-16. [PMID: 26755443 PMCID: PMC4853838 DOI: 10.1177/0271678x15625349] [Citation(s) in RCA: 65] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2015] [Accepted: 12/03/2015] [Indexed: 11/17/2022]
Abstract
Regionally variable rates of aerobic glycolysis in brain networks identified by resting-state functional magnetic resonance imaging (R-fMRI) imply regionally variable adenosine triphosphate (ATP) regeneration. When regional glucose utilization is not matched to oxygen delivery, affected regions have correspondingly variable rates of ATP and lactate production. We tested the extent to which aerobic glycolysis and oxidative phosphorylation power R-fMRI networks by measuring quantitative differences between the oxygen to glucose index (OGI) and the oxygen extraction fraction (OEF) as measured by positron emission tomography (PET) in normal human brain (resting awake, eyes closed). Regionally uniform and correlated OEF and OGI estimates prevailed, with network values that matched the gray matter means, regardless of size, location, and origin. The spatial agreement between oxygen delivery (OEF≈0.4) and glucose oxidation (OGI ≈ 5.3) suggests that no specific regions have preferentially high aerobic glycolysis and low oxidative phosphorylation rates, with globally optimal maximum ATP turnover rates (VATP ≈ 9.4 µmol/g/min), in good agreement with (31)P and (13)C magnetic resonance spectroscopy measurements. These results imply that the intrinsic network activity in healthy human brain powers the entire gray matter with ubiquitously high rates of glucose oxidation. Reports of departures from normal brain-wide homogeny of oxygen extraction fraction and oxygen to glucose index may be due to normalization artefacts from relative PET measurements.
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Affiliation(s)
- Fahmeed Hyder
- Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, USA Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University, New Haven, CT, USA Department of Radiology & Biomedical Imaging, Yale University, New Haven, CT, USA Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Peter Herman
- Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, USA Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University, New Haven, CT, USA Department of Radiology & Biomedical Imaging, Yale University, New Haven, CT, USA
| | - Christopher J Bailey
- Center of Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark
| | - Arne Møller
- Center of Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark Department of Nuclear Medicine and PET, Aarhus University Hospital, Aarhus, Denmark
| | - Ronen Globinsky
- Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, USA Department of Radiology & Biomedical Imaging, Yale University, New Haven, CT, USA
| | - Robert K Fulbright
- Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, USA Department of Radiology & Biomedical Imaging, Yale University, New Haven, CT, USA
| | - Douglas L Rothman
- Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, USA Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University, New Haven, CT, USA Department of Radiology & Biomedical Imaging, Yale University, New Haven, CT, USA Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Albert Gjedde
- Center of Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark Department of Neuroscience and Pharmacology, University of Copenhagen, Copenhagen, Denmark
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16
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Dai W, Varma G, Scheidegger R, Alsop DC. Quantifying fluctuations of resting state networks using arterial spin labeling perfusion MRI. J Cereb Blood Flow Metab 2016; 36:463-73. [PMID: 26661226 PMCID: PMC4794099 DOI: 10.1177/0271678x15615339] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/12/2015] [Accepted: 06/15/2015] [Indexed: 11/17/2022]
Abstract
Blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) has been widely used to investigate spontaneous low-frequency signal fluctuations across brain resting state networks. However, BOLD only provides relative measures of signal fluctuations. Arterial Spin Labeling (ASL) MRI holds great potential for quantitative measurements of resting state network fluctuations. This study systematically quantified signal fluctuations of the large-scale resting state networks using ASL data from 20 healthy volunteers by separating them from global signal fluctuations and fluctuations caused by residual noise. Global ASL signal fluctuation was 7.59% ± 1.47% relative to the ASL baseline perfusion. Fluctuations of seven detected resting state networks vary from 2.96% ± 0.93% to 6.71% ± 2.35%. Fluctuations of networks and residual noise were 6.05% ± 1.18% and 6.78% ± 1.16% using 4-mm resolution ASL data applied with Gaussian smoothing kernel of 6mm. However, network fluctuations were reduced by 7.77% ± 1.56% while residual noise fluctuation was markedly reduced by 39.75% ± 2.90% when smoothing kernel of 12 mm was applied to the ASL data. Therefore, global and network fluctuations are the dominant structured noise sources in ASL data. Quantitative measurements of resting state networks may enable improved noise reduction and provide insights into the function of healthy and diseased brain.
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Affiliation(s)
- Weiying Dai
- Department of Radiology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Gopal Varma
- Department of Radiology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Rachel Scheidegger
- Department of Radiology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - David C Alsop
- Department of Radiology, Beth Israel Deaconess Medical Center, Boston, MA, USA
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17
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Kannurpatti SS, Sanganahalli BG, Herman P, Hyder F. Role of mitochondrial calcium uptake homeostasis in resting state fMRI brain networks. NMR IN BIOMEDICINE 2015; 28:1579-1588. [PMID: 26439799 PMCID: PMC4621005 DOI: 10.1002/nbm.3421] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2015] [Revised: 08/27/2015] [Accepted: 09/01/2015] [Indexed: 06/05/2023]
Abstract
Mitochondrial Ca(2+) uptake influences both brain energy metabolism and neural signaling. Given that brain mitochondrial organelles are distributed in relation to vascular density, which varies considerably across brain regions, we hypothesized different physiological impacts of mitochondrial Ca(2+) uptake across brain regions. We tested the hypothesis by monitoring brain "intrinsic activity" derived from the resting state functional MRI (fMRI) blood oxygen level dependent (BOLD) fluctuations in different functional networks spanning the somatosensory cortex, caudate putamen, hippocampus and thalamus, in normal and perturbed mitochondrial Ca(2+) uptake states. In anesthetized rats at 11.7 T, mitochondrial Ca(2+) uptake was inhibited or enhanced respectively by treatments with Ru360 or kaempferol. Surprisingly, mitochondrial Ca(2+) uptake inhibition by Ru360 and enhancement by kaempferol led to similar dose-dependent decreases in brain-wide intrinsic activities in both the frequency domain (spectral amplitude) and temporal domain (resting state functional connectivity; RSFC). The fact that there were similar dose-dependent decreases in the frequency and temporal domains of the resting state fMRI-BOLD fluctuations during mitochondrial Ca(2+) uptake inhibition or enhancement indicated that mitochondrial Ca(2+) uptake and its homeostasis may strongly influence the brain's functional organization at rest. Interestingly, the resting state fMRI-derived intrinsic activities in the caudate putamen and thalamic regions saturated much faster with increasing dosage of either drug treatment than the drug-induced trends observed in cortical and hippocampal regions. Regional differences in how the spectral amplitude and RSFC changed with treatment indicate distinct mitochondrion-mediated spontaneous neuronal activity coupling within the various RSFC networks determined by resting state fMRI.
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Affiliation(s)
| | - Basavaraju G. Sanganahalli
- Department of Diagnostic Radiology, Yale University School of Medicine, New Haven, CT 06520-808
- Magnetic Resonance Research Center (MRRC), Yale University School of Medicine, New Haven, CT 06520-808
- Core Center for Quantitative Neuroscience with Magnetic Resonance (QNMR), Yale University School of Medicine, New Haven, CT 06520-808
| | - Peter Herman
- Department of Diagnostic Radiology, Yale University School of Medicine, New Haven, CT 06520-808
- Magnetic Resonance Research Center (MRRC), Yale University School of Medicine, New Haven, CT 06520-808
- Core Center for Quantitative Neuroscience with Magnetic Resonance (QNMR), Yale University School of Medicine, New Haven, CT 06520-808
| | - Fahmeed Hyder
- Department of Diagnostic Radiology, Yale University School of Medicine, New Haven, CT 06520-808
- Department of Biomedical Engineering, Yale University School of Medicine, New Haven, CT 06520-808
- Magnetic Resonance Research Center (MRRC), Yale University School of Medicine, New Haven, CT 06520-808
- Core Center for Quantitative Neuroscience with Magnetic Resonance (QNMR), Yale University School of Medicine, New Haven, CT 06520-808
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18
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Peeters S, Simas T, Suckling J, Gronenschild E, Patel A, Habets P, van Os J, Marcelis M. Semi-metric analysis of the functional brain network: Relationship with familial risk for psychotic disorder. NEUROIMAGE-CLINICAL 2015; 9:607-16. [PMID: 26740914 PMCID: PMC4644247 DOI: 10.1016/j.nicl.2015.10.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/06/2015] [Revised: 09/21/2015] [Accepted: 10/02/2015] [Indexed: 12/26/2022]
Abstract
Background Dysconnectivity in schizophrenia can be understood in terms of dysfunctional integration of a distributed network of brain regions. Here we propose a new methodology to analyze complex networks based on semi-metric behavior, whereby higher levels of semi-metricity may represent a higher level of redundancy and dispersed communication. It was hypothesized that individuals with (increased risk for) psychotic disorder would have more semi-metric paths compared to controls and that this would be associated with symptoms. Methods Resting-state functional MRI scans were obtained from 73 patients with psychotic disorder, 83 unaffected siblings and 72 controls. Semi-metric percentages (SMP) at the whole brain, hemispheric and lobar level were the dependent variables in a multilevel random regression analysis to investigate group differences. SMP was further examined in relation to symptomatology (i.e., psychotic/cognitive symptoms). Results At the whole brain and hemispheric level, patients had a significantly higher SMP compared to siblings and controls, with no difference between the latter. In the combined sibling and control group, individuals with high schizotypy had intermediate SMP values in the left hemisphere with respect to patients and individuals with low schizotypy. Exploratory analyses in patients revealed higher SMP in 12 out of 42 lobar divisions compared to controls, of which some were associated with worse PANSS symptomatology (i.e., positive symptoms, excitement and emotional distress) and worse cognitive performance on attention and emotion processing tasks. In the combined group of patients and controls, working memory, attention and social cognition were associated with higher SMP. Discussion The results are suggestive of more dispersed network communication in patients with psychotic disorder, with some evidence for trait-based network alterations in high-schizotypy individuals. Dispersed communication may contribute to the clinical phenotype in psychotic disorder. In addition, higher SMP may contribute to neuro- and social cognition, independent of psychosis risk. Higher SMP was observed at whole brain and hemispheric level in psychotic disorder. In patients, lobar SMP was associated with psychotic and cognitive symptoms. Trait-based SMP alterations were observed in high schizotypy individuals.
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Affiliation(s)
- Sanne Peeters
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, EURON, Maastricht University Medical Centre, PO Box 616 (Vijv1), 6200 MD Maastricht, The Netherlands; Faculty of Psychology and Educational Sciences, Open University of the Netherlands, Heerlen, The Netherlands
| | - Tiago Simas
- Behavioral and Clinical Neuroscience Institute, Department of Psychiatry, University of Cambridge, United Kingdom
| | - John Suckling
- Behavioral and Clinical Neuroscience Institute, Department of Psychiatry, University of Cambridge, United Kingdom; Cambridge and Peterborough Foundation NHS Trust. Cambridge, United Kingdom
| | - Ed Gronenschild
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, EURON, Maastricht University Medical Centre, PO Box 616 (Vijv1), 6200 MD Maastricht, The Netherlands
| | - Ameera Patel
- Behavioral and Clinical Neuroscience Institute, Department of Psychiatry, University of Cambridge, United Kingdom
| | - Petra Habets
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, EURON, Maastricht University Medical Centre, PO Box 616 (Vijv1), 6200 MD Maastricht, The Netherlands
| | - Jim van Os
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, EURON, Maastricht University Medical Centre, PO Box 616 (Vijv1), 6200 MD Maastricht, The Netherlands; King's College London, King's Health Partners, Department of Psychosis Studies Institute of Psychiatry, London, United Kingdom
| | - Machteld Marcelis
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, EURON, Maastricht University Medical Centre, PO Box 616 (Vijv1), 6200 MD Maastricht, The Netherlands; Institute for Mental Health Care Eindhoven (GGzE), Eindhoven, The Netherlands
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Marshall O, Uh J, Lurie D, Lu H, Milham MP, Ge Y. The influence of mild carbon dioxide on brain functional homotopy using resting-state fMRI. Hum Brain Mapp 2015; 36:3912-21. [PMID: 26138728 PMCID: PMC6320689 DOI: 10.1002/hbm.22886] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2015] [Revised: 06/09/2015] [Accepted: 06/16/2015] [Indexed: 11/10/2022] Open
Abstract
Homotopy reflects the intrinsic functional architecture of the brain through synchronized spontaneous activity between corresponding bilateral regions, measured as voxel mirrored homotopic connectivity (VMHC). Hypercapnia is known to have clear impact on brain hemodynamics through vasodilation, but have unclear effect on neuronal activity. This study investigates the effect of hypercapnia on brain homotopy, achieved by breathing 5% carbon dioxide (CO2 ) gas mixture. A total of 14 healthy volunteers completed three resting state functional MRI (RS-fMRI) scans, the first and third under normocapnia and the second under hypercapnia. VMHC measures were calculated as the correlation between the BOLD signal of each voxel and its counterpart in the opposite hemisphere. Group analysis was performed between the hypercapnic and normocapnic VMHC maps. VMHC showed a diffused decrease in response to hypercapnia. Significant regional decreases in VMHC were observed in all anatomical lobes, except for the occipital lobe, in the following functional hierarchical subdivisions: the primary sensory-motor, unimodal, heteromodal, paralimbic, as well as in the following functional networks: ventral attention, somatomotor, default frontoparietal, and dorsal attention. Our observation that brain homotopy in RS-fMRI is affected by arterial CO2 levels suggests that caution should be used when comparing RS-fMRI data between healthy controls and patients with pulmonary diseases and unusual respiratory patterns such as sleep apnea or chronic obstructive pulmonary disease.
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Affiliation(s)
- Olga Marshall
- Radiology/Center for Biomedical ImagingNew York University School of MedicineNew YorkNew York
| | - Jinsoo Uh
- Advanced Imaging Research CenterUniversity of Texas Southwestern Medical CenterDallasTexas
| | - Daniel Lurie
- Center for the Developing Brain, Child Mind InstituteNew YorkNew York
| | - Hanzhang Lu
- Advanced Imaging Research CenterUniversity of Texas Southwestern Medical CenterDallasTexas
- Department of RadiologyJohns Hopkins University School of MedicineBaltimoreMaryland
| | - Michael P. Milham
- Center for the Developing Brain, Child Mind InstituteNew YorkNew York
- Nathan S Kline Institute for Psychiatric ResearchNew York
| | - Yulin Ge
- Radiology/Center for Biomedical ImagingNew York University School of MedicineNew YorkNew York
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20
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Simas T, Chattopadhyay S, Hagan C, Kundu P, Patel A, Holt R, Floris D, Graham J, Ooi C, Tait R, Spencer M, Baron-Cohen S, Sahakian B, Bullmore E, Goodyer I, Suckling J. Semi-Metric Topology of the Human Connectome: Sensitivity and Specificity to Autism and Major Depressive Disorder. PLoS One 2015; 10:e0136388. [PMID: 26308854 PMCID: PMC4550361 DOI: 10.1371/journal.pone.0136388] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2015] [Accepted: 08/04/2015] [Indexed: 01/28/2023] Open
Abstract
Introduction The human functional connectome is a graphical representation, consisting of nodes connected by edges, of the inter-relationships of blood oxygenation-level dependent (BOLD) time-series measured by MRI from regions encompassing the cerebral cortices and, often, the cerebellum. Semi-metric analysis of the weighted, undirected connectome distinguishes an edge as either direct (metric), such that there is no alternative path that is accumulatively stronger, or indirect (semi-metric), where one or more alternative paths exist that have greater strength than the direct edge. The sensitivity and specificity of this method of analysis is illustrated by two case-control analyses with independent, matched groups of adolescents with autism spectrum conditions (ASC) and major depressive disorder (MDD). Results Significance differences in the global percentage of semi-metric edges was observed in both groups, with increases in ASC and decreases in MDD relative to controls. Furthermore, MDD was associated with regional differences in left frontal and temporal lobes, the right limbic system and cerebellum. In contrast, ASC had a broadly increased percentage of semi-metric edges with a more generalised distribution of effects and some areas of reduction. In summary, MDD was characterised by localised, large reductions in the percentage of semi-metric edges, whilst ASC is characterised by more generalised, subtle increases. These differences were corroborated in greater detail by inspection of the semi-metric backbone for each group; that is, the sub-graph of semi-metric edges present in >90% of participants, and by nodal degree differences in the semi-metric connectome. Conclusion These encouraging results, in what we believe is the first application of semi-metric analysis to neuroimaging data, raise confidence in the methodology as potentially capable of detection and characterisation of a range of neurodevelopmental and psychiatric disorders.
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Affiliation(s)
- Tiago Simas
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | | | - Cindy Hagan
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
- Department of Psychology, Columbia University, New York, New York, United States of America
| | - Prantik Kundu
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Ameera Patel
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Rosemary Holt
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Dorothea Floris
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Julia Graham
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
- Department of Psychiatry, University of Oxford, Medical Sciences Division, Oxford, United Kingdom
| | - Cinly Ooi
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Roger Tait
- MRC/Wellcome Trust Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom
| | - Michael Spencer
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Simon Baron-Cohen
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
- MRC/Wellcome Trust Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom
| | - Barbara Sahakian
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
- MRC/Wellcome Trust Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom
| | - Ed Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
- Cambridge and Peterborough Foundation NHS Trust, Cambridge, United Kingdom
- MRC/Wellcome Trust Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom
| | - Ian Goodyer
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
- Cambridge and Peterborough Foundation NHS Trust, Cambridge, United Kingdom
- MRC/Wellcome Trust Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom
| | - John Suckling
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
- Cambridge and Peterborough Foundation NHS Trust, Cambridge, United Kingdom
- MRC/Wellcome Trust Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom
- * E-mail:
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21
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van Graan LA, Lemieux L, Chaudhary UJ. Methods and utility of EEG-fMRI in epilepsy. Quant Imaging Med Surg 2015; 5:300-12. [PMID: 25853087 DOI: 10.3978/j.issn.2223-4292.2015.02.04] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2014] [Accepted: 01/22/2015] [Indexed: 12/13/2022]
Abstract
Brain activity data in general and more specifically in epilepsy can be represented as a matrix that includes measures of electrophysiology, anatomy and behaviour. Each of these sub-matrices has a complex interaction depending upon the brain state i.e., rest, cognition, seizures and interictal periods. This interaction presents significant challenges for interpretation but also potential for developing further insights into individual event types. Successful treatments in epilepsy hinge on unravelling these complexities, and also on the sensitivity and specificity of methods that characterize the nature and localization of underlying physiological and pathological networks. Limitations of pharmacological and surgical treatments call for refinement and elaboration of methods to improve our capability to localise the generators of seizure activity and our understanding of the neurobiology of epilepsy. Simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI), by potentially circumventing some of the limitations of EEG in terms of sensitivity, can allow the mapping of haemodynamic networks over the entire brain related to specific spontaneous and triggered epileptic events in humans, and thereby provide new localising information. In this work we review the published literature, and discuss the methods and utility of EEG-fMRI in localising the generators of epileptic activity. We draw on our experience and that of other groups, to summarise the spectrum of information provided by an increasing number of EEG-fMRI case-series, case studies and group studies in patients with epilepsy, for its potential role to elucidate epileptic generators and networks. We conclude that EEG-fMRI provides a multidimensional view that contributes valuable clinical information to localize the epileptic focus with potential important implications for the surgical treatment of some patients with drug-resistant epilepsy, and insights into the resting state and cognitive network dynamics.
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Affiliation(s)
- Louis André van Graan
- 1 Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, UK ; 2 MRI Unit, Epilepsy Society, Chalfont St. Peter SL9 0RJ, UK
| | - Louis Lemieux
- 1 Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, UK ; 2 MRI Unit, Epilepsy Society, Chalfont St. Peter SL9 0RJ, UK
| | - Umair Javaid Chaudhary
- 1 Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, UK ; 2 MRI Unit, Epilepsy Society, Chalfont St. Peter SL9 0RJ, UK
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22
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Mark CI, Mazerolle EL, Chen JJ. Metabolic and vascular origins of the BOLD effect: Implications for imaging pathology and resting-state brain function. J Magn Reson Imaging 2015; 42:231-46. [DOI: 10.1002/jmri.24786] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2014] [Accepted: 09/02/2014] [Indexed: 01/08/2023] Open
Affiliation(s)
- Clarisse I. Mark
- Centre for Neuroscience Studies; Queen's University; Kingston ON Canada
| | | | - J. Jean Chen
- Rotman Research Institute, Baycrest, University of Toronto; Toronto ON Canada
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Shulman RG, Hyder F, Rothman DL. Insights from neuroenergetics into the interpretation of functional neuroimaging: an alternative empirical model for studying the brain's support of behavior. J Cereb Blood Flow Metab 2014; 34:1721-35. [PMID: 25160670 PMCID: PMC4269754 DOI: 10.1038/jcbfm.2014.145] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/12/2014] [Revised: 06/12/2014] [Accepted: 07/21/2014] [Indexed: 02/05/2023]
Abstract
Functional neuroimaging measures quantitative changes in neurophysiological parameters coupled to neuronal activity during observable behavior. These results have usually been interpreted by assuming that mental causation of behavior arises from the simultaneous actions of distinct psychological mechanisms or modules. However, reproducible localization of these modules in the brain using functional magnetic resonance imaging (MRI) and positron emission tomography (PET) imaging has been elusive other than for sensory systems. In this paper, we show that neuroenergetic studies using PET, calibrated functional magnetic resonance imaging (fMRI), (13)C magnetic resonance spectroscopy, and electrical recordings do not support the standard approach, which identifies the location of mental modules from changes in brain activity. Of importance in reaching this conclusion is that changes in neuronal activities underlying the fMRI signal are many times smaller than the high ubiquitous, baseline neuronal activity, or energy in resting, awake humans. Furthermore, the incremental signal depends on the baseline activity contradicting theoretical assumptions about linearity and insertion of mental modules. To avoid these problems, while making use of these valuable results, we propose that neuroimaging should be used to identify observable brain activities that are necessary for a person's observable behavior rather than being used to seek hypothesized mental processes.
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Affiliation(s)
- Robert G Shulman
- Magnetic Resonance Research Center, Yale University, New Haven, Connecticut, USA
| | - Fahmeed Hyder
- Magnetic Resonance Research Center, Yale University, New Haven, Connecticut, USA
- Departments of Diagnostic Radiology, Yale University, New Haven, Connecticut, USA
- Biomedical Engineering, Yale University, New Haven, Connecticut, USA
- Quantitative Neuroscience with Magnetic Resonance Core Center, Yale University, New Haven, Connecticut, USA
| | - Douglas L Rothman
- Magnetic Resonance Research Center, Yale University, New Haven, Connecticut, USA
- Departments of Diagnostic Radiology, Yale University, New Haven, Connecticut, USA
- Biomedical Engineering, Yale University, New Haven, Connecticut, USA
- Quantitative Neuroscience with Magnetic Resonance Core Center, Yale University, New Haven, Connecticut, USA
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24
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Wehrl HF, Wiehr S, Divine MR, Gatidis S, Gullberg GT, Maier FC, Rolle AM, Schwenck J, Thaiss WM, Pichler BJ. Preclinical and Translational PET/MR Imaging. J Nucl Med 2014; 55:11S-18S. [PMID: 24833493 DOI: 10.2967/jnumed.113.129221] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Combined PET and MR imaging (PET/MR imaging) has progressed tremendously in recent years. The focus of current research has shifted from technologic challenges to the application of this new multimodal imaging technology in the areas of oncology, cardiology, neurology, and infectious diseases. This article reviews studies in preclinical and clinical translation. The common theme of these initial results is the complementary nature of combined PET/MR imaging that often provides additional insights into biologic systems that were not clearly feasible with just one modality alone. However, in vivo findings require ex vivo validation. Combined PET/MR imaging also triggers a multitude of new developments in image analysis that are aimed at merging and using multimodal information that ranges from better tumor characterization to analysis of metabolic brain networks. The combination of connectomics information that maps brain networks derived from multiparametric MR data with metabolic information from PET can even lead to the formation of a new research field that we would call cometomics that would map functional and metabolic brain networks. These new methodologic developments also call for more multidisciplinarity in the field of molecular imaging, in which close interaction and training among clinicians and a variety of scientists is needed.
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Affiliation(s)
- Hans F Wehrl
- Werner Siemens Imaging Center, Department for Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tuebingen, Tuebingen, Germany
| | - Stefan Wiehr
- Werner Siemens Imaging Center, Department for Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tuebingen, Tuebingen, Germany
| | - Mathew R Divine
- Werner Siemens Imaging Center, Department for Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tuebingen, Tuebingen, Germany
| | - Sergios Gatidis
- Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, Tuebingen, Germany
| | - Grant T Gullberg
- Department of Radiotracer Development and Imaging Technology, Ernest Orlando Lawrence Berkeley National Laboratory, Berkeley, California Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California; and
| | - Florian C Maier
- Werner Siemens Imaging Center, Department for Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tuebingen, Tuebingen, Germany
| | - Anna-Maria Rolle
- Werner Siemens Imaging Center, Department for Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tuebingen, Tuebingen, Germany
| | - Johannes Schwenck
- Werner Siemens Imaging Center, Department for Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tuebingen, Tuebingen, Germany Department of Nuclear Medicine, Eberhard Karls University Tuebingen, Tuebingen, Germany
| | - Wolfgang M Thaiss
- Werner Siemens Imaging Center, Department for Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tuebingen, Tuebingen, Germany Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, Tuebingen, Germany
| | - Bernd J Pichler
- Werner Siemens Imaging Center, Department for Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tuebingen, Tuebingen, Germany
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25
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Sanganahalli BG, Herman P, Hyder F, Kannurpatti SS. Mitochondrial functional state impacts spontaneous neocortical activity and resting state FMRI. PLoS One 2013; 8:e63317. [PMID: 23650561 PMCID: PMC3641133 DOI: 10.1371/journal.pone.0063317] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2013] [Accepted: 04/01/2013] [Indexed: 11/19/2022] Open
Abstract
Mitochondrial Ca2+ uptake, central to neural metabolism and function, is diminished in aging whereas enhanced after acute/sub-acute traumatic brain injury. To develop relevant translational models for these neuropathologies, we determined the impact of perturbed mitochondrial Ca2+ uptake capacities on intrinsic brain activity using clinically relevant markers. From a multi-compartment estimate of probable baseline Ca2+ ranges in the brain, we hypothesized that reduced or enhanced mitochondrial Ca2+ uptake capacity would decrease or increase spontaneous neuronal activity respectively. As resting state fMRI-BOLD fluctuations and stimulus-evoked BOLD responses have similar physiological origins [1] and stimulus-evoked neuronal and hemodynamic responses are modulated by mitochondrial Ca2+ uptake capacity [2], [3] respectively, we tested our hypothesis by measuring hemodynamic fluctuations and spontaneous neuronal activities during normal and altered mitochondrial functional states. Mitochondrial Ca2+ uptake capacity was perturbed by pharmacologically inhibiting or enhancing the mitochondrial Ca2+ uniporter (mCU) activity. Neuronal electrical activity and cerebral blood flow (CBF) fluctuations were measured simultaneously and integrated with fMRI-BOLD fluctuations at 11.7T. mCU inhibition reduced spontaneous neuronal activity and the resting state functional connectivity (RSFC), whereas mCU enhancement increased spontaneous neuronal activity but reduced RSFC. We conclude that increased or decreased mitochondrial Ca2+ uptake capacities lead to diminished resting state modes of brain functional connectivity.
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Affiliation(s)
- Basavaraju G. Sanganahalli
- Department of Diagnostic Radiology, Yale University School of Medicine, New Haven, Connecticut, United States of America
- Department of Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, Connecticut, United States of America
- Core Center for Quantitative Neuroscience with Magnetic Resonance, Yale University School of Medicine, New Haven, Connecticut, United States of America
| | - Peter Herman
- Department of Diagnostic Radiology, Yale University School of Medicine, New Haven, Connecticut, United States of America
- Department of Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, Connecticut, United States of America
- Core Center for Quantitative Neuroscience with Magnetic Resonance, Yale University School of Medicine, New Haven, Connecticut, United States of America
| | - Fahmeed Hyder
- Department of Diagnostic Radiology, Yale University School of Medicine, New Haven, Connecticut, United States of America
- Department of Biomedical Engineering, Yale University School of Medicine, New Haven, Connecticut, United States of America
- Department of Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, Connecticut, United States of America
- Core Center for Quantitative Neuroscience with Magnetic Resonance, Yale University School of Medicine, New Haven, Connecticut, United States of America
| | - Sridhar S. Kannurpatti
- Department of Radiology, UMDNJ-New Jersey Medical School, Newark, New Jersey, United States of America
- * E-mail:
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26
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Hyder F, Fulbright RK, Shulman RG, Rothman DL. Glutamatergic function in the resting awake human brain is supported by uniformly high oxidative energy. J Cereb Blood Flow Metab 2013; 33:339-47. [PMID: 23299240 PMCID: PMC3587823 DOI: 10.1038/jcbfm.2012.207] [Citation(s) in RCA: 90] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Rodent (13)C magnetic resonance spectroscopy studies show that glutamatergic signaling requires high oxidative energy in the awake resting state and allowed calibration of functional magnetic resonance imaging (fMRI) signal in terms of energy relative to the resting energy. Here, we derived energy used for glutamatergic signaling in the awake resting human. We analyzed human data of electroencephalography (EEG), positron emission tomography (PET) maps of oxygen (CMR(O2)) and glucose (CMR(glc)) utilization, and calibrated fMRI from a variety of experimental conditions. CMR(glc) and EEG in the visual cortex were tightly coupled over several conditions, showing that the oxidative demand for signaling was four times greater than the demand for nonsignaling events in the awake state. Variations of CMR(O2) and CMR(glc) from gray-matter regions and networks were within ±10% of means, suggesting that most areas required similar energy for ubiquitously high resting activity. Human calibrated fMRI results suggest that changes of fMRI signal in cognitive studies contribute at most ±10% CMR(O2) changes from rest. The PET data of sleep, vegetative state, and anesthesia show metabolic reductions from rest, uniformly >20% across, indicating no region is selectively reduced when consciousness is lost. Future clinical investigations will benefit from using quantitative metabolic measures.
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Affiliation(s)
- Fahmeed Hyder
- Magnetic Resonance Research Center, Yale University, New Haven, Connecticut 06520, USA.
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27
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Hyder F, Herman P, Sanganahalli BG, Coman D, Blumenfeld H, Rothman DL. Role of ongoing, intrinsic activity of neuronal populations for quantitative neuroimaging of functional magnetic resonance imaging-based networks. Brain Connect 2013; 1:185-93. [PMID: 22433047 DOI: 10.1089/brain.2011.0032] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Abstract
A primary objective in neuroscience is to determine how neuronal populations process information within networks. In humans and animal models, functional magnetic resonance imaging (fMRI) is gaining increasing popularity for network mapping. Although neuroimaging with fMRI-conducted with or without tasks-is actively discovering new brain networks, current fMRI data analysis schemes disregard the importance of the total neuronal activity in a region. In task fMRI experiments, the baseline is differenced away to disclose areas of small evoked changes in the blood oxygenation level-dependent (BOLD) signal. In resting-state fMRI experiments, the spotlight is on regions revealed by correlations of tiny fluctuations in the baseline (or spontaneous) BOLD signal. Interpretation of fMRI-based networks is obscured further, because the BOLD signal indirectly reflects neuronal activity, and difference/correlation maps are thresholded. Since the small changes of BOLD signal typically observed in cognitive fMRI experiments represent a minimal fraction of the total energy/activity in a given area, the relevance of fMRI-based networks is uncertain, because the majority of neuronal energy/activity is ignored. Thus, another alternative for quantitative neuroimaging of fMRI-based networks is a perspective in which the activity of a neuronal population is accounted for by the demanded oxidative energy (CMR(O2)). In this article, we argue that network mapping can be improved by including neuronal energy/activity of both the information about baseline and small differences/fluctuations of BOLD signal. Thus, total energy/activity information can be obtained through use of calibrated fMRI to quantify differences of ΔCMR(O2) and through resting-state positron emission tomography/magnetic resonance spectroscopy measurements for average CMR(O2).
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Affiliation(s)
- Fahmeed Hyder
- Magnetic Resonance Research Center (MRRC), Yale University, New Haven, Connecticut, USA.
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28
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Kannurpatti SS, Rypma B, Biswal BB. Prediction of Task-Related BOLD fMRI with Amplitude Signatures of Resting-State fMRI. Front Syst Neurosci 2012; 6:7. [PMID: 22408609 PMCID: PMC3294272 DOI: 10.3389/fnsys.2012.00007] [Citation(s) in RCA: 56] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2011] [Accepted: 02/04/2012] [Indexed: 11/13/2022] Open
Abstract
Blood oxygen contrast-functional magnetic resonance imaging (fMRI) signals are a convolution of neural and vascular components. Several studies indicate that task-related (T-fMRI) or resting-state (R-fMRI) responses linearly relate to hypercapnic task responses. Based on the linearity of R-fMRI and T-fMRI with hypercapnia demonstrated by different groups using different study designs, we hypothesized that R-fMRI and T-fMRI signals are governed by a common physiological mechanism and that resting-state fluctuation of amplitude (RSFA) should be linearly related to T-fMRI responses. We tested this prediction in a group of healthy younger humans where R-fMRI, T-fMRI, and hypercapnic (breath hold, BH) task measures were obtained form the same scan session during resting state and during performance of motor and BH tasks. Within individual subjects, significant linear correlations were observed between motor and BH task responses across voxels. When averaged over the whole brain, the subject-wise correlation between the motor and BH tasks showed a similar linear relationship within the group. Likewise, a significant linear correlation was observed between motor-task activity and RSFA across voxels and subjects. The linear rest-task (R-T) relationship between motor activity and RSFA suggested that R-fMRI and T-fMRI responses are governed by similar physiological mechanisms. A practical use of the R-T relationship is its potential to estimate T-fMRI responses in special populations unable to perform tasks during fMRI scanning. Using the R-T relationship determined from the first group of 12 healthy subjects, we predicted the T-fMRI responses in a second group of 7 healthy subjects. RSFA in both the lower and higher frequency ranges robustly predicted the magnitude of T-fMRI responses at the subject and voxel levels. We propose that T-fMRI responses are reliably predictable to the voxel level in situations where only R-fMRI measures are possible, and may be useful for assessing neural activity in task non-compliant clinical populations.
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Affiliation(s)
- Sridhar S Kannurpatti
- Department of Radiology, New Jersey Medical School, University of Medicine and Dentistry of New Jersey Newark, NJ, USA
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29
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Leopold DA, Maier A. Ongoing physiological processes in the cerebral cortex. Neuroimage 2011; 62:2190-200. [PMID: 22040739 DOI: 10.1016/j.neuroimage.2011.10.059] [Citation(s) in RCA: 90] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2011] [Revised: 10/02/2011] [Accepted: 10/18/2011] [Indexed: 10/16/2022] Open
Abstract
Functional magnetic resonance imaging (fMRI) has revealed that the human brain undergoes prominent, regional hemodynamic fluctuations when a subject is at rest. These ongoing fluctuations exhibit distinct patterns of spatiotemporal synchronization that have been dubbed "resting state functional connectivity", and which currently serve as a principal tool to investigate neural networks in the normal and pathological human brain. Despite the wide application of this approach in human neuroscience, the neural mechanisms that give rise to spontaneous fMRI correlations are largely unknown. Here we review results of recent electrophysiological studies in the cerebral cortex of humans and nonhuman primates that link neural activity to ongoing fMRI fluctuations. We begin by describing results obtained with simultaneous fMRI and electrophysiological measurements that allow for the identification of direct neural correlates of resting state functional connectivity. We next highlight experiments that investigate the correlational structure of spontaneous neural signals, including the spatial variation of signal coherence over the cortical surface, across cortical laminae, and between the two hemispheres. In the final section we speculate on the origins and potential consequences of ongoing signals for normal brain function, and point out inherent limitations of the fMRI correlation approach.
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Affiliation(s)
- David A Leopold
- Section on Cognitive Neurophysiology and Imaging, Laboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Department of Health and Human Services, 49 Convent Dr. 1E-21, MSC 4400, Bethesda, MD 20892, USA.
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30
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Herman P, Sanganahalli BG, Hyder F, Eke A. Fractal analysis of spontaneous fluctuations of the BOLD signal in rat brain. Neuroimage 2011; 58:1060-9. [PMID: 21777682 DOI: 10.1016/j.neuroimage.2011.06.082] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2011] [Revised: 06/14/2011] [Accepted: 06/26/2011] [Indexed: 12/01/2022] Open
Abstract
Analysis of task-evoked fMRI data ignores low frequency fluctuations (LFF) of the resting-state the BOLD signal, yet LFF of the spontaneous BOLD signal is crucial for analysis of resting-state connectivity maps. We characterized the LFF of resting-state BOLD signal at 11.7T in α-chloralose and domitor anesthetized rat brain and modeled the spontaneous signal as a scale-free (i.e., fractal) distribution of amplitude power (|A|²) across a frequency range (f) compatible with an |A(f)|² ∝ 1/f(β) model where β is the scaling exponent (or spectral index). We compared β values from somatosensory forelimb area (S1FL), cingulate cortex (CG), and caudate putamen (CPu). With α-chloralose, S1FL and CG β values dropped from ~0.7 at in vivo to ~0.1 at post mortem (p<0.0002), whereas CPu β values dropped from ~0.3 at in vivo to ~0.1 at post mortem (p<0.002). With domitor, cortical (S1FL, CG) β values were slightly higher than with α-chloralose, while subcortical (CPu) β values were similar with α-chloralose. Although cortical and subcortical β values with both anesthetics were significantly different in vivo (p<0.002), at post mortem β values in these regions were not significantly different and approached zero (i.e., range of -0.1 to 0.2). Since a water phantom devoid of susceptibility gradients had a β value of zero (i.e., random), we conclude that deoxyhemoglobin present in voxels post-sacrifice still impacts tissue water diffusion. These results suggest that in the anesthetized rat brain the LFF of BOLD signal at 11.7T follow a general 1/f(β) model of fractality where β is a variable responding to physiology. We describe typical experimental pitfalls which may elude detection of fractality in the resting-state BOLD signal.
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Affiliation(s)
- Peter Herman
- Magnetic Resonance Research Center, Yale University, New Haven, Connecticut, USA
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31
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Iacovella V, Hasson U. The relationship between BOLD signal and autonomic nervous system functions: implications for processing of "physiological noise". Magn Reson Imaging 2011; 29:1338-45. [PMID: 21543181 DOI: 10.1016/j.mri.2011.03.006] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2010] [Revised: 03/07/2011] [Accepted: 03/07/2011] [Indexed: 12/30/2022]
Abstract
Functional magnetic resonance imaging (fMRI) research has revealed not only important aspects of the neural basis of cognitive and perceptual functions, but also important information on the relation between high-level brain functions and physiology. One of the central outstanding questions, given the features of the blood oxygenation level-dependent (BOLD) signal, is whether and how autonomic nervous system (ANS) functions are related to changes in brain states as measured in the human brain. A straightforward way to address this question has been to acquire external measurements of ANS activity such as cardiac and respiratory data, and examine their relation to the BOLD signal. In this article, we describe two conceptual approaches to the treatment of ANS measures in the context of BOLD fMRI analysis. On the one hand, several research lines have treated ANS activity measures as noise, considering them as nothing but a confounding factor that reduces the power of fMRI analysis or its validity. Work in this line has developed powerful methods to remove ANS effects from the BOLD signal. On the other hand, a different line of work has made important progress in showing that ANS functions such as cardiac pulsation, heart rate variability and breathing rate could be considered as a theoretically meaningful component of the signal that is useful for understanding brain function. Work within this latter framework suggests that caution should be exercised when employing procedures to remove correlations between BOLD data and physiological measures. We discuss these two positions and the reasoning underlying them. Thereafter, we draw on the reviewed literature in presenting practical guidelines for treatment of ANS data, which are based on the premise that ANS data should be considered as theoretically meaningful information. This holds particularly when studying cortical systems involved in regulation, monitoring and/or generation of ANS activity, such as those involved in decision making, conflict resolution and the experience of emotion.
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Affiliation(s)
- Vittorio Iacovella
- Center for Mind/Brain Sciences (CIMeC), The University of Trento, 38060 Mattarello, Trento, Italy.
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32
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Evidence for the importance of measuring total brain activity in neuroimaging. Proc Natl Acad Sci U S A 2011; 108:5475-6. [PMID: 21441108 DOI: 10.1073/pnas.1102026108] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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