1
|
Banerjee R, Kaptan M, Tinnermann A, Khatibi A, Dabbagh A, Büchel C, Kündig CW, Law CSW, Pfyffer D, Lythgoe DJ, Tsivaka D, Van De Ville D, Eippert F, Muhammad F, Glover GH, David G, Haynes G, Haaker J, Brooks JCW, Finsterbusch J, Martucci KT, Hemmerling KJ, Mobarak-Abadi M, Hoggarth MA, Howard MA, Bright MG, Kinany N, Kowalczyk OS, Freund P, Barry RL, Mackey S, Vahdat S, Schading S, McMahon SB, Parish T, Marchand-Pauvert V, Chen Y, Smith ZA, Weber KA, De Leener B, Cohen-Adad J. EPISeg: Automated segmentation of the spinal cord on echo planar images using open-access multi-center data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.01.07.631402. [PMID: 39829895 PMCID: PMC11741348 DOI: 10.1101/2025.01.07.631402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 01/22/2025]
Abstract
Functional magnetic resonance imaging (fMRI) of the spinal cord is relevant for studying sensation, movement, and autonomic function. Preprocessing of spinal cord fMRI data involves segmentation of the spinal cord on gradient-echo echo planar imaging (EPI) images. Current automated segmentation methods do not work well on these data, due to the low spatial resolution, susceptibility artifacts causing distortions and signal drop-out, ghosting, and motion-related artifacts. Consequently, this segmentation task demands a considerable amount of manual effort which takes time and is prone to user bias. In this work, we (i) gathered a multi-center dataset of spinal cord gradient-echo EPI with ground-truth segmentations and shared it on OpenNeuro https://openneuro.org/datasets/ds005143/versions/1.3.0, and (ii) developed a deep learning-based model, EPISeg, for the automatic segmentation of the spinal cord on gradient-echo EPI data. We observe a significant improvement in terms of segmentation quality compared to other available spinal cord segmentation models. Our model is resilient to different acquisition protocols as well as commonly observed artifacts in fMRI data. The training code is available at https://github.com/sct-pipeline/fmri-segmentation/, and the model has been integrated into the Spinal Cord Toolbox as a command-line tool.
Collapse
Affiliation(s)
- Rohan Banerjee
- Department of Computer Science, Polytechnique Montreal, Montreal, Quebec, Canada
- Mila - Quebec AI Institute, Montreal, Quebec, Canada
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada
| | - Merve Kaptan
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Alexandra Tinnermann
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Ali Khatibi
- McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
- Centre de recherche de l'Institut Universitaire de Gériatrie de Montréal, Montréal, Quebec, Canada
- Centre of Precision Rehabilitation for Spinal Pain (CPR Spine), University of Birmingham, UK
- Centre for Human Brain Health, University of Birmingham, UK
| | - Alice Dabbagh
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Christian Büchel
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Christian W Kündig
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Christine S W Law
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Dario Pfyffer
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, United States
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - David J Lythgoe
- Department of Neuroimaging, Institute of Psychology, Psychiatry & Neuroscience, King's College London, London, UK
| | - Dimitra Tsivaka
- Department of Neuroimaging, Institute of Psychology, Psychiatry & Neuroscience, King's College London, London, UK
- Medical Physics Department, Medical School, University of Thessaly, Larisa, Greece
| | - Dimitri Van De Ville
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
- Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
| | - Falk Eippert
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Fauziyya Muhammad
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, OK, USA
| | - Gary H Glover
- Radiological Sciences Laboratory, Department of Radiology, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Gergely David
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Grace Haynes
- Stephenson School of Biomedical Engineering at the University of Oklahoma in Norman, OK, USA
| | - Jan Haaker
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jonathan C W Brooks
- Department of Psychology, University of Liverpool, Liverpool, United Kingdom
| | - Jürgen Finsterbusch
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Katherine T Martucci
- Center for Translational Pain Medicine, Department of Anesthesiology, Duke University Medical Center, Durham, NC, USA
| | - Kimberly J Hemmerling
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
- Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, Illinois, USA
| | - Mahdi Mobarak-Abadi
- Centre de recherche de l'Institut Universitaire de Gériatrie de Montréal, Montréal, Quebec, Canada
| | - Mark A Hoggarth
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
- Department of Physical Therapy, North Central College, Naperville, Illinois, USA
| | - Matthew A Howard
- Department of Neuroimaging, Institute of Psychology, Psychiatry & Neuroscience, King's College London, London, UK
| | - Molly G Bright
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
- Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, Illinois, USA
| | - Nawal Kinany
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
- Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
| | - Olivia S Kowalczyk
- Functional Imaging Laboratory, Department of Imaging Neuroscience, Queen Square Institute of Neurology, University College London, London, UK
- Department of Neuroimaging, Institute of Psychology, Psychiatry & Neuroscience, King's College London, London, UK
| | - Patrick Freund
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Functional Imaging Laboratory, Department of Imaging Neuroscience, Queen Square Institute of Neurology, University College London, London, UK
| | - Robert L Barry
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
- Harvard-Massachusetts Institute of Technology Health Sciences & Technology, Cambridge, MA, USA
| | - Sean Mackey
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Shahabeddin Vahdat
- McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
- Centre de recherche de l'Institut Universitaire de Gériatrie de Montréal, Montréal, Quebec, Canada
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA
| | - Simon Schading
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Stephen B McMahon
- Wolfson Centre for Age Related Diseases, King's College London, London UK
| | - Todd Parish
- Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, Illinois, USA
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | | | - Yufen Chen
- Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, Illinois, USA
| | - Zachary A Smith
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, OK, USA
| | - Kenneth A Weber
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Benjamin De Leener
- Department of Computer Science, Polytechnique Montreal, Montreal, Quebec, Canada
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada
- Research Center, Ste-Justine Hospital University Centre, Montreal, Quebec, Canada
| | - Julien Cohen-Adad
- Mila - Quebec AI Institute, Montreal, Quebec, Canada
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada
- Functional Neuroimaging Unit, CRIUGM, University of Montreal, Montreal, Quebec, Canada
- Research Center, Ste-Justine Hospital University Centre, Montreal, Quebec, Canada
| |
Collapse
|
2
|
Dabbagh A, Horn U, Kaptan M, Mildner T, Müller R, Lepsien J, Weiskopf N, Brooks JCW, Finsterbusch J, Eippert F. Reliability of task-based fMRI in the dorsal horn of the human spinal cord. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.22.572825. [PMID: 38187724 PMCID: PMC10769329 DOI: 10.1101/2023.12.22.572825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
The application of functional magnetic resonance imaging (fMRI) to the human spinal cord is still a relatively small field of research and faces many challenges. Here we aimed to probe the limitations of task-based spinal fMRI at 3T by investigating the reliability of spinal cord blood oxygen level dependent (BOLD) responses to repeated nociceptive stimulation across two consecutive days in 40 healthy volunteers. We assessed the test-retest reliability of subjective ratings, autonomic responses, and spinal cord BOLD responses to short heat pain stimuli (1s duration) using the intraclass correlation coefficient (ICC). At the group level, we observed robust autonomic responses as well as spatially specific spinal cord BOLD responses at the expected location, but no spatial overlap in BOLD response patterns across days. While autonomic indicators of pain processing showed good-to-excellent reliability, both β-estimates and z-scores of task-related BOLD responses showed poor reliability across days in the target region (gray matter of the ipsilateral dorsal horn). When taking into account the sensitivity of gradient-echo echo planar imaging (GE-EPI) to draining vein signals by including the venous plexus in the analysis, we observed BOLD responses with fair reliability across days. Taken together, these results demonstrate that heat pain stimuli as short as one second are able to evoke a robust and spatially specific BOLD response, which is however strongly variable within participants across time, resulting in low reliability in the dorsal horn gray matter. Further improvements in data acquisition and analysis techniques are thus necessary before event-related spinal cord fMRI as used here can be reliably employed in longitudinal designs or clinical settings.
Collapse
Affiliation(s)
- Alice Dabbagh
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Ulrike Horn
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Merve Kaptan
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, CA, USA
| | - Toralf Mildner
- Methods & Development Group Nuclear Magnetic Resonance, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Roland Müller
- Methods & Development Group Nuclear Magnetic Resonance, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Jöran Lepsien
- Methods & Development Group Nuclear Magnetic Resonance, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, University of Leipzig, Leipzig, Germany
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London, UK
| | - Jonathan C W Brooks
- School of Psychology, University of East Anglia Wellcome Wolfson Brain Imaging Centre (UWWBIC), Norwich, United Kingdom
| | - Jürgen Finsterbusch
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Falk Eippert
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| |
Collapse
|
3
|
Sengupta A, Mishra A, Wang F, Chen LM, Gore JC. Characteristic BOLD signals are detectable in white matter of the spinal cord at rest and after a stimulus. Proc Natl Acad Sci U S A 2024; 121:e2316117121. [PMID: 38776372 PMCID: PMC11145258 DOI: 10.1073/pnas.2316117121] [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: 09/26/2023] [Accepted: 02/16/2024] [Indexed: 05/25/2024] Open
Abstract
We report the reliable detection of reproducible patterns of blood-oxygenation-level-dependent (BOLD) MRI signals within the white matter (WM) of the spinal cord during a task and in a resting state. Previous functional MRI studies have shown that BOLD signals are robustly detectable not only in gray matter (GM) in the brain but also in cerebral WM as well as the GM within the spinal cord, but similar signals in WM of the spinal cord have been overlooked. In this study, we detected BOLD signals in the WM of the spinal cord in squirrel monkeys and studied their relationships with the locations and functions of ascending and descending WM tracts. Tactile sensory stimulus -evoked BOLD signal changes were detected in the ascending tracts of the spinal cord using a general-linear model. Power spectral analysis confirmed that the amplitude at the fundamental frequency of the response to a periodic stimulus was significantly higher in the ascending tracts than the descending ones. Independent component analysis of resting-state signals identified coherent fluctuations from eight WM hubs which correspond closely to the known anatomical locations of the major WM tracts. Resting-state analyses showed that the WM hubs exhibited correlated signal fluctuations across spinal cord segments in reproducible patterns that correspond well with the known neurobiological functions of WM tracts in the spinal cord. Overall, these findings provide evidence of a functional organization of intraspinal WM tracts and confirm that they produce hemodynamic responses similar to GM both at baseline and under stimulus conditions.
Collapse
Affiliation(s)
- Anirban Sengupta
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN37235
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN37235
| | - Arabinda Mishra
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN37235
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN37235
| | - Feng Wang
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN37235
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN37235
| | - Li Min Chen
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN37235
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN37235
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN37235
| | - John C. Gore
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN37235
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN37235
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN37235
- Department of Physics and Astronomy, Vanderbilt University, Nashville, TN37235
| |
Collapse
|
4
|
Agyeman KA, Lee DJ, Russin J, Kreydin EI, Choi W, Abedi A, Lo YT, Cavaleri J, Wu K, Edgerton VR, Liu C, Christopoulos VN. Functional ultrasound imaging of the human spinal cord. Neuron 2024; 112:1710-1722.e3. [PMID: 38458198 DOI: 10.1016/j.neuron.2024.02.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 11/03/2023] [Accepted: 02/15/2024] [Indexed: 03/10/2024]
Abstract
Utilizing the first in-human functional ultrasound imaging (fUSI) of the spinal cord, we demonstrate the integration of spinal functional responses to electrical stimulation. We record and characterize the hemodynamic responses of the spinal cord to a neuromodulatory intervention commonly used for treating pain and increasingly used for the restoration of sensorimotor and autonomic function. We found that the hemodynamic response to stimulation reflects a spatiotemporal modulation of the spinal cord circuitry not previously recognized. Our analytical capability offers a mechanism to assess blood flow changes with a new level of spatial and temporal precision in vivo and demonstrates that fUSI can decode the functional state of spinal networks in a single trial, which is of fundamental importance for developing real-time closed-loop neuromodulation systems. This work is a critical step toward developing a vital technique to study spinal cord function and effects of clinical neuromodulation.
Collapse
Affiliation(s)
- K A Agyeman
- Department of Bioengineering, University of California Riverside, Riverside, CA, USA
| | - D J Lee
- Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Neurorestoration Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Rancho Los Amigos National Rehabilitation Center, Downey, CA, USA; Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - J Russin
- Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Neurorestoration Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Rancho Los Amigos National Rehabilitation Center, Downey, CA, USA; Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - E I Kreydin
- Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Neurorestoration Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Rancho Los Amigos National Rehabilitation Center, Downey, CA, USA; Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - W Choi
- Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Neurorestoration Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - A Abedi
- Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Neurorestoration Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Y T Lo
- Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Neurorestoration Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Department of Neurosurgery, National Neuroscience Institute, Singapore, Singapore
| | - J Cavaleri
- Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - K Wu
- Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Neurorestoration Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - V R Edgerton
- Neurorestoration Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Rancho Los Amigos National Rehabilitation Center, Downey, CA, USA.
| | - C Liu
- Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Neurorestoration Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Rancho Los Amigos National Rehabilitation Center, Downey, CA, USA; Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA.
| | - V N Christopoulos
- Department of Bioengineering, University of California Riverside, Riverside, CA, USA; Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Neurorestoration Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Neuroscience Graduate Program, University of California Riverside, Riverside, CA, USA.
| |
Collapse
|
5
|
Kowalczyk OS, Medina S, Tsivaka D, McMahon SB, Williams SCR, Brooks JCW, Lythgoe DJ, Howard MA. Spinal fMRI demonstrates segmental organisation of functionally connected networks in the cervical spinal cord: A test-retest reliability study. Hum Brain Mapp 2024; 45:e26600. [PMID: 38339896 PMCID: PMC10831202 DOI: 10.1002/hbm.26600] [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: 07/07/2023] [Revised: 12/21/2023] [Accepted: 01/04/2024] [Indexed: 02/12/2024] Open
Abstract
Resting functional magnetic resonance imaging (fMRI) studies have identified intrinsic spinal cord activity, which forms organised motor (ventral) and sensory (dorsal) resting-state networks. However, to facilitate the use of spinal fMRI in, for example, clinical studies, it is crucial to first assess the reliability of the method, particularly given the unique anatomical, physiological, and methodological challenges associated with acquiring the data. Here, we characterise functional connectivity relationships in the cervical cord and assess their between-session test-retest reliability in 23 young healthy volunteers. Resting-state networks were estimated in two ways (1) by estimating seed-to-voxel connectivity maps and (2) by calculating seed-to-seed correlations. Seed regions corresponded to the four grey matter horns (ventral/dorsal and left/right) of C5-C8 segmental levels. Test-retest reliability was assessed using the intraclass correlation coefficient. Spatial overlap of clusters derived from seed-to-voxel analysis between sessions was examined using Dice coefficients. Following seed-to-voxel analysis, we observed distinct unilateral dorsal and ventral organisation of cervical spinal resting-state networks that was largely confined in the rostro-caudal extent to each spinal segmental level, with more sparse connections observed between segments. Additionally, strongest correlations were observed between within-segment ipsilateral dorsal-ventral connections, followed by within-segment dorso-dorsal and ventro-ventral connections. Test-retest reliability of these networks was mixed. Reliability was poor when assessed on a voxelwise level, with more promising indications of reliability when examining the average signal within clusters. Reliability of correlation strength between seeds was highly variable, with the highest reliability achieved in ipsilateral dorsal-ventral and dorso-dorsal/ventro-ventral connectivity. However, the spatial overlap of networks between sessions was excellent. We demonstrate that while test-retest reliability of cervical spinal resting-state networks is mixed, their spatial extent is similar across sessions, suggesting that these networks are characterised by a consistent spatial representation over time.
Collapse
Affiliation(s)
- Olivia S. Kowalczyk
- Department of Neuroimaging, Institute of Psychology, Psychiatry & NeuroscienceKing's College LondonLondonUK
- The Wellcome Centre for Human Neuroimaging, Queen Square Institute of NeurologyUniversity College LondonLondonUK
| | - Sonia Medina
- Department of Neuroimaging, Institute of Psychology, Psychiatry & NeuroscienceKing's College LondonLondonUK
| | - Dimitra Tsivaka
- Department of Neuroimaging, Institute of Psychology, Psychiatry & NeuroscienceKing's College LondonLondonUK
- Medical Physics Department, Medical SchoolUniversity of ThessalyLarisaGreece
| | | | - Steven C. R. Williams
- Department of Neuroimaging, Institute of Psychology, Psychiatry & NeuroscienceKing's College LondonLondonUK
| | | | - David J. Lythgoe
- Department of Neuroimaging, Institute of Psychology, Psychiatry & NeuroscienceKing's College LondonLondonUK
| | - Matthew A. Howard
- Department of Neuroimaging, Institute of Psychology, Psychiatry & NeuroscienceKing's College LondonLondonUK
| |
Collapse
|
6
|
Kaptan M, Pfyffer D, Konstantopoulos CG, Law CS, Weber II KA, Glover GH, Mackey S. Recent developments and future avenues for human corticospinal neuroimaging. Front Hum Neurosci 2024; 18:1339881. [PMID: 38332933 PMCID: PMC10850311 DOI: 10.3389/fnhum.2024.1339881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 01/09/2024] [Indexed: 02/10/2024] Open
Abstract
Non-invasive neuroimaging serves as a valuable tool for investigating the mechanisms within the central nervous system (CNS) related to somatosensory and motor processing, emotions, memory, cognition, and other functions. Despite the extensive use of brain imaging, spinal cord imaging has received relatively less attention, regardless of its potential to study peripheral communications with the brain and the descending corticospinal systems. To comprehensively understand the neural mechanisms underlying human sensory and motor functions, particularly in pathological conditions, simultaneous examination of neuronal activity in both the brain and spinal cord becomes imperative. Although technically demanding in terms of data acquisition and analysis, a growing but limited number of studies have successfully utilized specialized acquisition protocols for corticospinal imaging. These studies have effectively assessed sensorimotor, autonomic, and interneuronal signaling within the spinal cord, revealing interactions with cortical processes in the brain. In this mini-review, we aim to examine the expanding body of literature that employs cutting-edge corticospinal imaging to investigate the flow of sensorimotor information between the brain and spinal cord. Additionally, we will provide a concise overview of recent advancements in functional magnetic resonance imaging (fMRI) techniques. Furthermore, we will discuss potential future perspectives aimed at enhancing our comprehension of large-scale neuronal networks in the CNS and their disruptions in clinical disorders. This collective knowledge will aid in refining combined corticospinal fMRI methodologies, leading to the development of clinically relevant biomarkers for conditions affecting sensorimotor processing in the CNS.
Collapse
Affiliation(s)
- Merve Kaptan
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Dario Pfyffer
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Christiane G. Konstantopoulos
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Christine S.W. Law
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Kenneth A. Weber II
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Gary H. Glover
- Radiological Sciences Laboratory, Department of Radiology, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Sean Mackey
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, United States
| |
Collapse
|
7
|
Ge X, Wang L, Yan J, Pan L, Ye H, Zhu X, Feng Q, Chen B, Du Q, Yu W, Ding Z. Altered brain function in classical trigeminal neuralgia patients: ALFF, ReHo, and DC static- and dynamic-frequency study. Cereb Cortex 2024; 34:bhad455. [PMID: 38012118 DOI: 10.1093/cercor/bhad455] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 11/02/2023] [Accepted: 11/10/2023] [Indexed: 11/29/2023] Open
Abstract
The present study aimed to clarify the brain function of classical trigeminal neuralgia (CTN) by analyzing 77 CTN patients and age- and gender-matched 73 healthy controls (HCs) based on three frequency bands of the static and dynamic amplitude of low-frequency fluctuation, regional homogeneity, and degree centrality (sALFF, sReHo, sDC, dALFF, dReHo, and dDC). Compared to HCs, the number of altered brain regions was different in three frequency bands, and the classical frequency band was most followed by slow-4 in CTN patients. Cerrelellum_8_L (sReHo), Cerrelellum_8_R (sDC), Calcarine_R (sDC), and Caudate_R (sDC) were found only in classical frequency band, while Precuneus_L (sALFF) and Frontal_Inf_Tri_L (sReHo) were found only in slow-4 frequency band. Except for the above six brain regions, the others overlapped in the classical and slow-4 frequency bands. CTN seriously affects the mental health of patients, and some different brain regions are correlated with clinical parameters. The static and dynamic indicators of brain function were complementary in CTN patients, and the changing brain regions showed frequency specificity. Compared to slow-5 frequency band, slow-4 is more consistent with the classical frequency band, which could be valuable in exploring the pathophysiology of CTN.
Collapse
Affiliation(s)
- Xiuhong Ge
- Department of Radiology, Hangzhou First People's Hospital, No. 261, Huansha Road, Shangcheng District, Hangzhou City, Zhejiang Province 310000, China
- Department of Radiology, Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Affiliated Hangzhou First People's Hospital, Cancer Center, Zhejiang University School of Medicine, No. 261, Huansha Road, Shangcheng District, Hangzhou City, Zhejiang Province 310000, China
| | - Luoyu Wang
- Department of Radiology, Hangzhou First People's Hospital, No. 261, Huansha Road, Shangcheng District, Hangzhou City, Zhejiang Province 310000, China
- Department of Radiology, Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Affiliated Hangzhou First People's Hospital, Cancer Center, Zhejiang University School of Medicine, No. 261, Huansha Road, Shangcheng District, Hangzhou City, Zhejiang Province 310000, China
| | - Juncheng Yan
- Department of Rehabilitation, Hangzhou First People's Hospital, No. 261, Huansha Road, Shangcheng District, Hangzhou City, Zhejiang Province 310000, China
| | - Lei Pan
- Department of Radiology, Hangzhou First People's Hospital, No. 261, Huansha Road, Shangcheng District, Hangzhou City, Zhejiang Province 310000, China
| | - Haiqi Ye
- Department of Radiology, Hangzhou First People's Hospital, No. 261, Huansha Road, Shangcheng District, Hangzhou City, Zhejiang Province 310000, China
| | - Xiaofen Zhu
- Department of Radiology, Hangzhou First People's Hospital, No. 261, Huansha Road, Shangcheng District, Hangzhou City, Zhejiang Province 310000, China
| | - Qi Feng
- Department of Radiology, Hangzhou First People's Hospital, No. 261, Huansha Road, Shangcheng District, Hangzhou City, Zhejiang Province 310000, China
| | - Bing Chen
- Jing Hengyi School of Education, Hangzhou Normal University, No. 2318, Yuhang Tang Road, Yuhang District, Hangzhou City, Zhejiang Province 311121, China
| | - Quan Du
- Department of Neurosurgery, Hangzhou First People's Hospital, No. 261, Huansha Road, Shangcheng District, Hangzhou City, Zhejiang Province 310000, China
| | - Wenhua Yu
- Department of Neurosurgery, Hangzhou First People's Hospital, No. 261, Huansha Road, Shangcheng District, Hangzhou City, Zhejiang Province 310000, China
| | - Zhongxiang Ding
- Department of Radiology, Hangzhou First People's Hospital, No. 261, Huansha Road, Shangcheng District, Hangzhou City, Zhejiang Province 310000, China
- Department of Radiology, Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Affiliated Hangzhou First People's Hospital, Cancer Center, Zhejiang University School of Medicine, No. 261, Huansha Road, Shangcheng District, Hangzhou City, Zhejiang Province 310000, China
| |
Collapse
|
8
|
Kinany N, Pirondini E, Micera S, Van De Ville D. Spinal Cord fMRI: A New Window into the Central Nervous System. Neuroscientist 2023; 29:715-731. [PMID: 35822665 PMCID: PMC10623605 DOI: 10.1177/10738584221101827] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
With the brain, the spinal cord forms the central nervous system. Initially considered a passive relay between the brain and the periphery, the spinal cord is now recognized as being active and plastic. Yet, it remains largely overlooked by the human neuroscience community, in stark contrast with the wealth of research investigating the brain. In this review, we argue that fMRI, traditionally used to image cerebral function, can be extended beyond the brain to help unravel spinal mechanisms involved in human behaviors. To this end, we first outline strategies that have been proposed to tackle the challenges inherent to spinal cord fMRI. Then, we discuss how they have been utilized to provide insights into the functional organization of spinal sensorimotor circuits, highlighting their potential to address fundamental and clinical questions. By summarizing guidelines and applications of spinal cord fMRI, we hope to stimulate and support further research into this promising yet underexplored field.
Collapse
Affiliation(s)
- Nawal Kinany
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
- Medical Image Processing Laboratory, Center for Neuroprosthetics, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland
- Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland
| | - Elvira Pirondini
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
- Department of BioEngineering, University of Pittsburgh, PA, USA
- Rehabilitation Neural Engineering Laboratories, University of Pittsburgh, Pittsburgh, PA, USA
| | - Silvestro Micera
- Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland
- Translational Neural Engineering Area, The Biorobotics Institute, Scuola Superiore Sant’Anna, Pisa, Italy
| | - Dimitri Van De Ville
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
- Medical Image Processing Laboratory, Center for Neuroprosthetics, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland
| |
Collapse
|
9
|
Haynes G, Muhammad F, Khan AF, Mohammadi E, Smith ZA, Ding L. The current state of spinal cord functional magnetic resonance imaging and its application in clinical research. J Neuroimaging 2023; 33:877-888. [PMID: 37740582 DOI: 10.1111/jon.13158] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 09/05/2023] [Accepted: 09/11/2023] [Indexed: 09/24/2023] Open
Abstract
Since its development, spinal cord functional magnetic resonance imaging (fMRI) has utilized various methodologies and stimulation protocols to develop a deeper understanding of a healthy human spinal cord that lays a foundation for its use in clinical research and practice. In this review, we conducted a comprehensive literature search on spinal cord fMRI studies and summarized the recent advancements and resulting scientific achievements of spinal cord fMRI in the following three aspects: the current state of spinal cord fMRI methodologies and stimulation protocols, knowledge about the healthy spinal cord's functions obtained via spinal cord fMRI, and fMRI's exemplary usage in spinal cord diseases and injuries. We conclude with a discussion that, while technical challenges exist, novel fMRI technologies for and new knowledge about the healthy human spinal cord have been established. Empowered by these developments, investigations of pathological and injury states within the spinal cord have become the next important direction of spinal cord fMRI. Recent clinical investigations into spinal cord pathologies, for example, fibromyalgia, multiple sclerosis, spinal cord injury, and cervical spondylotic myelopathy, have already provided deep insights into spinal cord impairments and the time course of impairment-caused changes. We expect that future spinal cord fMRI advancement and research development will further enhance our understanding of various spinal cord diseases and provide the foundation for evaluating existing and developing new treatment plans.
Collapse
Affiliation(s)
- Grace Haynes
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, Oklahoma, USA
| | - Fauziyya Muhammad
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Ali F Khan
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Esmaeil Mohammadi
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Zachary A Smith
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Lei Ding
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, Oklahoma, USA
- Institute for Biomedical Engineering, Science, and Technology, University of Oklahoma, Norman, Oklahoma, USA
| |
Collapse
|
10
|
Combes A, Narisetti L, Sengupta A, Rogers BP, Sweeney G, Prock L, Houston D, McKnight CD, Gore JC, Smith SA, O'Grady KP. Detection of resting-state functional connectivity in the lumbar spinal cord with 3T MRI. Sci Rep 2023; 13:18189. [PMID: 37875563 PMCID: PMC10597994 DOI: 10.1038/s41598-023-45302-0] [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: 03/14/2023] [Accepted: 10/18/2023] [Indexed: 10/26/2023] Open
Abstract
Functional MRI (fMRI) of the spinal cord is an expanding area of research with potential to investigate neuronal activity in the central nervous system. We aimed to characterize the functional connectivity features of the human lumbar spinal cord using resting-state fMRI (rs-fMRI) at 3T, using region-based and data-driven analysis approaches. A 3D multi-shot gradient echo resting-state blood oxygenation level dependent-sensitive rs-fMRI protocol was implemented in 26 healthy participants. Average temporal signal-to-noise ratio in the gray matter was 16.35 ± 4.79 after denoising. Evidence of synchronous signal fluctuations in the ventral and dorsal horns with their contralateral counterparts was observed in representative participants using interactive, exploratory seed-based correlations. Group-wise average in-slice Pearson's correlations were 0.43 ± 0.17 between ventral horns, and 0.48 ± 0.16 between dorsal horns. Group spatial independent component analysis (ICA) was used to identify areas of coherent activity¸ and revealed components within the gray matter corresponding to anatomical regions. Lower-dimensionality ICA revealed bilateral components corresponding to ventral and dorsal networks. Additional separate ICAs were run on two subsets of the participant group, yielding two sets of components that showed visual consistency and moderate spatial overlap. This work shows feasibility of rs-fMRI to probe the functional features and organization of the lumbar spinal cord.
Collapse
Affiliation(s)
- Anna Combes
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave S, MCN AA1105, Nashville, TN, 37232, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Lipika Narisetti
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave S, MCN AA1105, Nashville, TN, 37232, USA
| | - Anirban Sengupta
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave S, MCN AA1105, Nashville, TN, 37232, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Baxter P Rogers
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave S, MCN AA1105, Nashville, TN, 37232, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Grace Sweeney
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave S, MCN AA1105, Nashville, TN, 37232, USA
| | - Logan Prock
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave S, MCN AA1105, Nashville, TN, 37232, USA
| | - Delaney Houston
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave S, MCN AA1105, Nashville, TN, 37232, USA
| | - Colin D McKnight
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - John C Gore
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave S, MCN AA1105, Nashville, TN, 37232, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, 37235, USA
| | - Seth A Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave S, MCN AA1105, Nashville, TN, 37232, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, 37235, USA
| | - Kristin P O'Grady
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave S, MCN AA1105, Nashville, TN, 37232, USA.
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37232, USA.
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, 37235, USA.
| |
Collapse
|
11
|
Chen LM, Wang F, Mishra A, Yang PF, Sengupta A, Reed JL, Gore JC. Longitudinal multiparametric MRI of traumatic spinal cord injury in animal models. Magn Reson Imaging 2023; 102:184-200. [PMID: 37343904 PMCID: PMC10528214 DOI: 10.1016/j.mri.2023.06.007] [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: 03/17/2022] [Revised: 06/14/2023] [Accepted: 06/17/2023] [Indexed: 06/23/2023]
Abstract
Multi-parametric MRI (mpMRI) technology enables non-invasive and quantitative assessments of the structural, molecular, and functional characteristics of various neurological diseases. Despite the recognized importance of studying spinal cord pathology, mpMRI applications in spinal cord research have been somewhat limited, partly due to technical challenges associated with spine imaging. However, advances in imaging techniques and improved image quality now allow longitudinal investigations of a comprehensive range of spinal cord pathological features by exploiting different endogenous MRI contrasts. This review summarizes the use of mpMRI techniques including blood oxygenation level-dependent (BOLD) functional MRI (fMRI), diffusion tensor imaging (DTI), quantitative magnetization transfer (qMT), and chemical exchange saturation transfer (CEST) MRI in monitoring different aspects of spinal cord pathology. These aspects include cyst formation and axonal disruption, demyelination and remyelination, changes in the excitability of spinal grey matter and the integrity of intrinsic functional circuits, and non-specific molecular changes associated with secondary injury and neuroinflammation. These approaches are illustrated with reference to a nonhuman primate (NHP) model of traumatic cervical spinal cord injuries (SCI). We highlight the benefits of using NHP SCI models to guide future studies of human spinal cord pathology, and demonstrate how mpMRI can capture distinctive features of spinal cord pathology that were previously inaccessible. Furthermore, the development of mechanism-based MRI biomarkers from mpMRI studies can provide clinically useful imaging indices for understanding the mechanisms by which injured spinal cords progress and repair. These biomarkers can assist in the diagnosis, prognosis, and evaluation of therapies for SCI patients, potentially leading to improved outcomes.
Collapse
Affiliation(s)
- Li Min Chen
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Feng Wang
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Arabinda Mishra
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Pai-Feng Yang
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Anirban Sengupta
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jamie L Reed
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - John C Gore
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| |
Collapse
|
12
|
Kaptan M, Horn U, Vannesjo SJ, Mildner T, Weiskopf N, Finsterbusch J, Brooks JCW, Eippert F. Reliability of resting-state functional connectivity in the human spinal cord: Assessing the impact of distinct noise sources. Neuroimage 2023; 275:120152. [PMID: 37142169 PMCID: PMC10262064 DOI: 10.1016/j.neuroimage.2023.120152] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2023] [Revised: 04/20/2023] [Accepted: 05/01/2023] [Indexed: 05/06/2023] Open
Abstract
The investigation of spontaneous fluctuations of the blood-oxygen-level-dependent (BOLD) signal has recently been extended from the brain to the spinal cord, where it has stimulated interest from a clinical perspective. A number of resting-state functional magnetic resonance imaging (fMRI) studies have demonstrated robust functional connectivity between the time series of BOLD fluctuations in bilateral dorsal horns and between those in bilateral ventral horns, in line with the functional neuroanatomy of the spinal cord. A necessary step prior to extension to clinical studies is assessing the reliability of such resting-state signals, which we aimed to do here in a group of 45 healthy young adults at the clinically prevalent field strength of 3T. When investigating connectivity in the entire cervical spinal cord, we observed fair to good reliability for dorsal-dorsal and ventral-ventral connectivity, whereas reliability was poor for within- and between-hemicord dorsal-ventral connectivity. Considering how prone spinal cord fMRI is to noise, we extensively investigated the impact of distinct noise sources and made two crucial observations: removal of physiological noise led to a reduction in functional connectivity strength and reliability - due to the removal of stable and participant-specific noise patterns - whereas removal of thermal noise considerably increased the detectability of functional connectivity without a clear influence on reliability. Finally, we also assessed connectivity within spinal cord segments and observed that while the pattern of connectivity was similar to that of whole cervical cord, reliability at the level of single segments was consistently poor. Taken together, our results demonstrate the presence of reliable resting-state functional connectivity in the human spinal cord even after thoroughly accounting for physiological and thermal noise, but at the same time urge caution if focal changes in connectivity (e.g. due to segmental lesions) are to be studied, especially in a longitudinal manner.
Collapse
Affiliation(s)
- Merve Kaptan
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Ulrike Horn
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - S Johanna Vannesjo
- Department of Physics, Norwegian University of Science and Technology, Trondheim, Norway
| | - Toralf Mildner
- Methods & Development Group Nuclear Magnetic Resonance, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, University of Leipzig, Leipzig, Germany
| | - Jürgen Finsterbusch
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jonathan C W Brooks
- School of Psychology, University of East Anglia Wellcome Wolfson Brain Imaging Centre (UWWBIC), Norwich, UK
| | - Falk Eippert
- Max Planck Research Group Pain Perception, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| |
Collapse
|
13
|
Rangaprakash D, Barry RL, Deshpande G. The confound of hemodynamic response function variability in human resting-state functional MRI studies. Front Neurosci 2023; 17:934138. [PMID: 37521709 PMCID: PMC10375034 DOI: 10.3389/fnins.2023.934138] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 04/07/2023] [Indexed: 08/01/2023] Open
Abstract
Functional magnetic resonance imaging (fMRI) is an indirect measure of neural activity with the hemodynamic response function (HRF) coupling it with unmeasured neural activity. The HRF, modulated by several non-neural factors, is variable across brain regions, individuals and populations. Yet, a majority of human resting-state fMRI connectivity studies continue to assume a non-variable HRF. In this article, with supportive prior evidence, we argue that HRF variability cannot be ignored as it substantially confounds within-subject connectivity estimates and between-subjects connectivity group differences. We also discuss its clinical relevance with connectivity impairments confounded by HRF aberrations in several disorders. We present limited data on HRF differences between women and men, which resulted in a 15.4% median error in functional connectivity estimates in a group-level comparison. We also discuss the implications of HRF variability for fMRI studies in the spinal cord. There is a need for more dialogue within the community on the HRF confound, and we hope that our article is a catalyst in the process.
Collapse
Affiliation(s)
- D. Rangaprakash
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
| | - Robert L. Barry
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Harvard-Massachusetts Institute of Technology Division of Health Sciences and Technology, Cambridge, MA, United States
| | - Gopikrishna Deshpande
- Department of Electrical and Computer Engineering, AU MRI Research Center, Auburn University, Auburn, AL, United States
- Department of Psychological Sciences, Auburn University, Auburn, AL, United States
- Center for Neuroscience, Auburn University, Auburn, AL, United States
- Alabama Advanced Imaging Consortium, Birmingham, AL, United States
- Key Laboratory for Learning and Cognition, School of Psychology, Capital Normal University, Beijing, China
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
- Centre for Brain Research, Indian Institute of Science, Bangalore, India
| |
Collapse
|
14
|
Kinany N, Khatibi A, Lungu O, Finsterbusch J, Büchel C, Marchand-Pauvert V, Ville DVD, Vahdat S, Doyon J. Decoding cerebro-spinal signatures of human behavior: application to motor sequence learning. Neuroimage 2023; 275:120174. [PMID: 37201642 DOI: 10.1016/j.neuroimage.2023.120174] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 05/12/2023] [Accepted: 05/15/2023] [Indexed: 05/20/2023] Open
Abstract
Mapping the neural patterns that drive human behavior is a key challenge in neuroscience. Even the simplest of our everyday actions stem from the dynamic and complex interplay of multiple neural structures across the central nervous system (CNS). Yet, most neuroimaging research has focused on investigating cerebral mechanisms, while the way the spinal cord accompanies the brain in shaping human behavior has been largely overlooked. Although the recent advent of functional magnetic resonance imaging (fMRI) sequences that can simultaneously target the brain and spinal cord has opened up new avenues for studying these mechanisms at multiple levels of the CNS, research to date has been limited to inferential univariate techniques that cannot fully unveil the intricacies of the underlying neural states. To address this, we propose to go beyond traditional analyses and instead use a data-driven multivariate approach leveraging the dynamic content of cerebro-spinal signals using innovation-driven coactivation patterns (iCAPs). We demonstrate the relevance of this approach in a simultaneous brain-spinal cord fMRI dataset acquired during motor sequence learning (MSL), to highlight how large-scale CNS plasticity underpins rapid improvements in early skill acquisition and slower consolidation after extended practice. Specifically, we uncovered cortical, subcortical and spinal functional networks, which were used to decode the different stages of learning with a high accuracy and, thus, delineate meaningful cerebro-spinal signatures of learning progression. Our results provide compelling evidence that the dynamics of neural signals, paired with a data-driven approach, can be used to disentangle the modular organization of the CNS. While we outline the potential of this framework to probe the neural correlates of motor learning, its versatility makes it broadly applicable to explore the functioning of cerebro-spinal networks in other experimental or pathological conditions.
Collapse
Affiliation(s)
- N Kinany
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, 1211, Switzerland; Neuro-X Institute, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, 1202, Switzerland.
| | - A Khatibi
- Center of Precision Rehabilitation for Spinal Pain, School of Sport, Exercise and Rehabilitation Sciences, College of Life and Environmental Sciences, University of Birmingham, Edgbaston, B15 2TT, United Kingdom
| | - O Lungu
- McConnell Brain Imaging Center, Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - J Finsterbusch
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Germany
| | - C Büchel
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Germany
| | - V Marchand-Pauvert
- Sorbonne Université, Inserm, CNRS, Laboratoire d'Imagerie biomédicale, Paris F-75006, France
| | - D Van De Ville
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, 1211, Switzerland; Neuro-X Institute, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, 1202, Switzerland
| | - S Vahdat
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, Florida, FL 32611, United States
| | - J Doyon
- McConnell Brain Imaging Center, Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| |
Collapse
|
15
|
Sengupta A, Mishra A, Wang F, Chen L, Gore J. Identification of synchronous BOLD signal patterns in white matter of primate spinal cord. RESEARCH SQUARE 2023:rs.3.rs-2389151. [PMID: 36993492 PMCID: PMC10055542 DOI: 10.21203/rs.3.rs-2389151/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2023]
Abstract
Functional MRI studies of the brain have shown that blood-oxygenation-level-dependent (BOLD) signals are robustly detectable not only in gray matter (GM) but also in white matter (WM). Here, we report the detection and characteristics of BOLD signals in WM of spinal cord (SC) of squirrel monkeys. Tactile stimulus-evoked BOLD signal changes were detected in the ascending sensory tracts of SC using a General-Linear Model (GLM) as well as Independent Component Analysis (ICA). ICA of resting state signals identified coherent fluctuations from eight WM hubs which correspond closely with known anatomical locations of SC WM tracts. Resting state analyses showed that the WM hubs exhibited correlated signal fluctuations within and between SC segments in specific patterns that correspond well with the known neurobiological functions of WM tracts in SC. Overall, these findings suggest WM BOLD signals in SC show similar features as GM both at baseline and under stimulus conditions.
Collapse
Affiliation(s)
| | | | - Feng Wang
- Vanderbilt University Medical Center
| | - Li Chen
- Vanderbilt University Medical Center
| | - John Gore
- Vanderbilt University Medical Center
| |
Collapse
|
16
|
Landelle C, Dahlberg LS, Lungu O, Misic B, De Leener B, Doyon J. Altered Spinal Cord Functional Connectivity Associated with Parkinson's Disease Progression. Mov Disord 2023; 38:636-645. [PMID: 36802374 DOI: 10.1002/mds.29354] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 01/13/2023] [Accepted: 01/30/2023] [Indexed: 02/23/2023] Open
Abstract
BACKGROUND Parkinson's disease (PD) has traditionally been viewed as an α-synucleinopathy brain pathology. Yet evidence based on postmortem human and animal experimental models indicates that the spinal cord may also be affected. OBJECTIVE Functional magnetic resonance imaging (fMRI) seems to be a promising candidate to better characterize spinal cord functional organization in PD patients. METHODS Resting-state spinal fMRI was performed in 70 PD patients and 24 age-matched healthy controls, the patients being divided into three groups based on their motor symptom severity: PDlow (n = 24), PDmed (n = 22), and PDadv (n = 24) groups. A combination of independent component analysis (ICA) and a seed-based approach was applied. RESULTS When pooling all participants, the ICA revealed distinct ventral and dorsal components distributed along the rostro-caudal axis. This organization was highly reproducible within subgroups of patients and controls. PD severity, assessed by Unified Parkinson's Disease Rating Scale (UPDRS) scores, was associated with a decrease in spinal functional connectivity (FC). Notably, we observed a reduced intersegmental correlation in PD as compared to controls, the latter being negatively associated with patients' upper-limb UPDRS scores (P = 0.0085). This negative association between FC and upper-limb UPDRS scores was significant between adjacent C4-C5 (P = 0.015) and C5-C6 (P = 0.20) cervical segments, levels associated with upper-limb functions. CONCLUSIONS The present study provides the first evidence of spinal cord FC changes in PD and opens new avenues for the effective diagnosis and therapeutic strategies in PD. This underscores how spinal cord fMRI can serve as a powerful tool to characterize, in vivo, spinal circuits for a variety of neurological diseases. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
Collapse
Affiliation(s)
- Caroline Landelle
- Department of Neurology and Neurosurgery, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Linda Solstrand Dahlberg
- Department of Neurology and Neurosurgery, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Ovidiu Lungu
- Department of Neurology and Neurosurgery, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Bratislav Misic
- Department of Neurology and Neurosurgery, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Benjamin De Leener
- Department of Computer Engineering and Software Engineering, Polytechnique Montreal, Montreal, Quebec, Canada.,CHU Sainte-Justine Research Centre, Montreal, Quebec, Canada
| | - Julien Doyon
- Department of Neurology and Neurosurgery, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| |
Collapse
|
17
|
Combes AJE, Clarke MA, O'Grady KP, Schilling KG, Smith SA. Advanced spinal cord MRI in multiple sclerosis: Current techniques and future directions. Neuroimage Clin 2022; 36:103244. [PMID: 36306717 PMCID: PMC9668663 DOI: 10.1016/j.nicl.2022.103244] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 09/02/2022] [Accepted: 10/19/2022] [Indexed: 11/11/2022]
Abstract
Spinal cord magnetic resonance imaging (MRI) has a central role in multiple sclerosis (MS) clinical practice for diagnosis and disease monitoring. Advanced MRI sequences capable of visualizing and quantifying tissue macro- and microstructure and reflecting different pathological disease processes have been used in MS research; however, the spinal cord remains under-explored, partly due to technical obstacles inherent to imaging this structure. We propose that the study of the spinal cord merits equal ambition in overcoming technical challenges, and that there is much information to be exploited to make valuable contributions to our understanding of MS. We present a narrative review on the latest progress in advanced spinal cord MRI in MS, covering in the first part structural, functional, metabolic and vascular imaging methods. We focus on recent studies of MS and those making significant technical steps, noting the challenges that remain to be addressed and what stands to be gained from such advances. Throughout we also refer to other works that presend more in-depth review on specific themes. In the second part, we present several topics that, in our view, hold particular potential. The need for better imaging of gray matter is discussed. We stress the importance of developing imaging beyond the cervical spinal cord, and explore the use of ultra-high field MRI. Finally, some recommendations are given for future research, from study design to newer developments in analysis, and the need for harmonization of sequences and methods within the field. This review is aimed at researchers and clinicians with an interest in gaining an overview of the current state of advanced MRI research in this field and what is primed to be the future of spinal cord imaging in MS research.
Collapse
Affiliation(s)
- Anna J E Combes
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States.
| | - Margareta A Clarke
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States
| | - Kristin P O'Grady
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States; Department of Biomedical Engineering, Vanderbilt University, 2301 Vanderbilt Place, PMB 351826, Nashville, TN 37235-1826, United States
| | - Kurt G Schilling
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States
| | - Seth A Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States; Department of Biomedical Engineering, Vanderbilt University, 2301 Vanderbilt Place, PMB 351826, Nashville, TN 37235-1826, United States
| |
Collapse
|
18
|
Kaptan M, Vannesjo SJ, Mildner T, Horn U, Hartley‐Davies R, Oliva V, Brooks JCW, Weiskopf N, Finsterbusch J, Eippert F. Automated slice-specific z-shimming for functional magnetic resonance imaging of the human spinal cord. Hum Brain Mapp 2022; 43:5389-5407. [PMID: 35938527 PMCID: PMC9704784 DOI: 10.1002/hbm.26018] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 06/21/2022] [Accepted: 06/24/2022] [Indexed: 01/15/2023] Open
Abstract
Functional magnetic resonance imaging (fMRI) of the human spinal cord faces many challenges, such as signal loss due to local magnetic field inhomogeneities. This issue can be addressed with slice-specific z-shimming, which compensates for the dephasing effect of the inhomogeneities using a slice-specific gradient pulse. Here, we aim to address outstanding issues regarding this technique by evaluating its effects on several aspects that are directly relevant for spinal fMRI and by developing two automated procedures in order to improve upon the time-consuming and subjective nature of manual selection of z-shims: one procedure finds the z-shim that maximizes signal intensity in each slice of an EPI reference-scan and the other finds the through-slice field inhomogeneity for each EPI-slice in field map data and calculates the required compensation gradient moment. We demonstrate that the beneficial effects of z-shimming are apparent across different echo times, hold true for both the dorsal and ventral horn, and are also apparent in the temporal signal-to-noise ratio (tSNR) of EPI time-series data. Both of our automated approaches were faster than the manual approach, lead to significant improvements in gray matter tSNR compared to no z-shimming and resulted in beneficial effects that were stable across time. While the field-map-based approach performed slightly worse than the manual approach, the EPI-based approach performed as well as the manual one and was furthermore validated on an external corticospinal data-set (N > 100). Together, automated z-shimming may improve the data quality of future spinal fMRI studies and lead to increased reproducibility in longitudinal studies.
Collapse
Affiliation(s)
- Merve Kaptan
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - S. Johanna Vannesjo
- Department of PhysicsNorwegian University of Science and TechnologyTrondheimNorway
| | - Toralf Mildner
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Ulrike Horn
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | | | - Valeria Oliva
- School of Physiology, Pharmacology and NeuroscienceUniversity of BristolBristolUK
| | - Jonathan C. W. Brooks
- School of PsychologyUniversity of East Anglia Wellcome Wolfson Brain Imaging Centre (UWWBIC)NorwichUK
| | - Nikolaus Weiskopf
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany,Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth SciencesLeipzig UniversityLeipzigGermany
| | - Jürgen Finsterbusch
- Department of Systems NeuroscienceUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Falk Eippert
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| |
Collapse
|
19
|
Zhang H, Zhu L, Gao DS, Liu Y, Zhang J, Yan M, Qian J, Xi W. Imaging the Deep Spinal Cord Microvascular Structure and Function with High-Speed NIR-II Fluorescence Microscopy. SMALL METHODS 2022; 6:e2200155. [PMID: 35599368 DOI: 10.1002/smtd.202200155] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 04/23/2022] [Indexed: 06/15/2023]
Abstract
The spinal cord (SC) is crucial for a myriad of somatosensory, autonomic signal processing, and transductions. Understanding the SC vascular structure and function thus plays an integral part in neuroscience and clinical research. However, the dense layers of myelinated ascending axons on the dorsal side inconveniently grant the SC tissue with high optical scattering property, which significantly hinders the imaging depth of the SC vasculature in vivo. Commonly used antiscattering techniques such as multiphoton fluorescence microscopy have low imaging speed and cannot capture the rapid vascular particle flow without significant motion blur. Here, advantage of the high penetration of near-infrared (NIR)-II fluorescence is taken to demonstrate a deep SC vascular structural image stack up to 350 µm, comparable to two-photon microscopy. Furthermore, the red blood cells are labelled with the clinically approved NIR dye indocyanine. The combination of a fast NIR camera and indocyanine green-red blood cells (RBCs) makes it possible to attain high-speed 100 frame-per-second NIR-II imaging to identify the corresponding changes in RBC velocity during the external hind leg stimulus. For the first time, it is established that the NIR-II region would be a promising spectral window for SC imaging. NIR-II fluorescence microscopy has excellent potential for clinical and basic science research on SC.
Collapse
Affiliation(s)
- Hequn Zhang
- Interdisciplinary Institute of Neuroscience and Technology (ZIINT), Department of Anesthesiology, the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310020, China
- MOE Frontier Science Center for Brain Research and Brain Machine Integration, Zhejiang University, Hangzhou, 310058, China
| | - Liang Zhu
- Interdisciplinary Institute of Neuroscience and Technology (ZIINT), Department of Anesthesiology, the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310020, China
- MOE Frontier Science Center for Brain Research and Brain Machine Integration, Zhejiang University, Hangzhou, 310058, China
- Interdisciplinary Institute of Neuroscience and Technology (ZIINT), College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, 310027, China
| | - Dave Schwinn Gao
- Key Laboratory of The Diagnosis and Treatment of Severe Trauma and Burn of Zhejiang Province, Department of Anesthesiology, the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310009, China
| | - Yin Liu
- Interdisciplinary Institute of Neuroscience and Technology (ZIINT), Department of Anesthesiology, the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310020, China
- MOE Frontier Science Center for Brain Research and Brain Machine Integration, Zhejiang University, Hangzhou, 310058, China
| | - Jun Zhang
- Department of Spine Surgery, Zhejiang Provincial People's Hospital, Hangzhou Medical School People's Hospital, Shangtang Road 158th, Hangzhou, Zhejiang Province, 310014, China
| | - Min Yan
- Key Laboratory of The Diagnosis and Treatment of Severe Trauma and Burn of Zhejiang Province, Department of Anesthesiology, the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310009, China
| | - Jun Qian
- State Key Laboratory of Modern Optical Instrumentations, Centre for Optical and Electromagnetic Research, College of Optical Science and Engineering, Zhejiang University, Hangzhou, 310058, China
| | - Wang Xi
- Interdisciplinary Institute of Neuroscience and Technology (ZIINT), Department of Anesthesiology, the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310020, China
- MOE Frontier Science Center for Brain Research and Brain Machine Integration, Zhejiang University, Hangzhou, 310058, China
- Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and instrument Science, Zhejiang University, Hangzhou, 310027, China
| |
Collapse
|
20
|
Pirondini E, Kinany N, Sueur CL, Griffis JC, Shulman GL, Corbetta M, Ville DVD. Post-stroke reorganization of transient brain activity characterizes deficits and recovery of cognitive functions. Neuroimage 2022; 255:119201. [PMID: 35405342 DOI: 10.1016/j.neuroimage.2022.119201] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Revised: 03/24/2022] [Accepted: 04/07/2022] [Indexed: 02/06/2023] Open
Abstract
Functional magnetic resonance imaging (fMRI) has been widely employed to study stroke pathophysiology. In particular, analyses of fMRI signals at rest were directed at quantifying the impact of stroke on spatial features of brain networks. However, brain networks have intrinsic time features that were, so far, disregarded in these analyses. In consequence, standard fMRI analysis failed to capture temporal imbalance resulting from stroke lesions, hence restricting their ability to reveal the interdependent pathological changes in structural and temporal network features following stroke. Here, we longitudinally analyzed hemodynamic-informed transient activity in a large cohort of stroke patients (n = 103) to assess spatial and temporal changes of brain networks after stroke. Metrics extracted from the hemodynamic-informed transient activity were replicable within- and between-individuals in healthy participants, hence supporting their robustness and their clinical applicability. While large-scale spatial patterns of brain networks were preserved after stroke, their durations were altered, with stroke subjects exhibiting a varied pattern of longer and shorter network activations compared to healthy individuals. Specifically, patients showed a longer duration in the lateral precentral gyrus and anterior cingulum, and a shorter duration in the occipital lobe and in the cerebellum. These temporal alterations were associated with white matter damage in projection and association pathways. Furthermore, they were tied to deficits in specific behavioral domains as restoration of healthy brain dynamics paralleled recovery of cognitive functions (attention, language and spatial memory), but was not significantly correlated to motor recovery. These findings underscore the critical importance of network temporal properties in dissecting the pathophysiology of brain changes after stroke, thus shedding new light on the clinical potential of time-resolved methods for fMRI analysis.
Collapse
Affiliation(s)
- Elvira Pirondini
- Department of Radiology and Medical Informatics, University of Geneva; 1211 Geneva, Switzerland; Medical Image Processing Laboratory, Center for Neuroprosthetics, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL); 1202 Geneva, Switzerland; Department of Physical Medicine and Rehabilitation, University of Pittsburgh; Pittsburgh, PA, USA; Rehabilitation Neural Engineering Laboratories, University of Pittsburgh; Pittsburgh, PA, USA; Department of BioEngineering, University of Pittsburgh; Pittsburgh, PA, USA.
| | - Nawal Kinany
- Department of Radiology and Medical Informatics, University of Geneva; 1211 Geneva, Switzerland; Medical Image Processing Laboratory, Center for Neuroprosthetics, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL); 1202 Geneva, Switzerland; Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics, Institute of Bioengineerin, Ecole Polytechnique Fédérale de Lausanne (EPFL); 1202 Geneva, Switzerland
| | - Cécile Le Sueur
- Medical Image Processing Laboratory, Center for Neuroprosthetics, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL); 1202 Geneva, Switzerland
| | - Joseph C Griffis
- Department of Neurology, Washington University School of Medicine, St. Louis; MO, 63110, USA
| | - Gordon L Shulman
- Department of Neurology, Washington University School of Medicine, St. Louis; MO, 63110, USA
| | - Maurizio Corbetta
- Department of Neurology, Washington University School of Medicine, St. Louis; MO, 63110, USA; Department of Radiology, Washington University School of Medicine, St. Louis; MO, 63110, USA; Department of Anatomy and Neurobiology, Washington University School of Medicine, St. Louis; MO, 63110, USA; Department of Bioengineering, Washington University School of Medicine, St. Louis; MO, 63110, USA; Department of Neuroscience and Padua Neuroscience Center, University of Padua; Padua, Italy; Venetian Institute of Molecular Medicine (VIMM); Padua, Italy
| | - Dimitri Van De Ville
- Department of Radiology and Medical Informatics, University of Geneva; 1211 Geneva, Switzerland; Medical Image Processing Laboratory, Center for Neuroprosthetics, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL); 1202 Geneva, Switzerland.
| |
Collapse
|
21
|
Stienen MN, Ha Y. Scientific Achievements of Our Era: “Making the Lame Walk”. Neurospine 2022; 19:246-248. [PMID: 35378593 PMCID: PMC8987551 DOI: 10.14245/ns.2244180.090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Affiliation(s)
- Martin N. Stienen
- Department of Neurosurgery & Spine Center of Eastern Switzerland, Kantonsspital St.Gallen, St.Gallen, Switzerland
- Corresponding Author Martin N. Stienen https://orcid.org/0000-0002-6417-1787 Department of Neurosurgery, Spine Center of Eastern Switzerland, Kantonsspital St.Gallen Rorschacher Str. 95, CH-9000 St.Gallen, Switzerland
| | - Yoon Ha
- Department of Neurosurgery, Spine and Spinal Cord Institute, Severance Hospital, College of Medicine, Yonsei University, Seoul, Korea
| |
Collapse
|
22
|
Activity-dependent spinal cord neuromodulation rapidly restores trunk and leg motor functions after complete paralysis. Nat Med 2022; 28:260-271. [PMID: 35132264 DOI: 10.1038/s41591-021-01663-5] [Citation(s) in RCA: 205] [Impact Index Per Article: 68.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 12/16/2021] [Indexed: 12/15/2022]
Abstract
Epidural electrical stimulation (EES) targeting the dorsal roots of lumbosacral segments restores walking in people with spinal cord injury (SCI). However, EES is delivered with multielectrode paddle leads that were originally designed to target the dorsal column of the spinal cord. Here, we hypothesized that an arrangement of electrodes targeting the ensemble of dorsal roots involved in leg and trunk movements would result in superior efficacy, restoring more diverse motor activities after the most severe SCI. To test this hypothesis, we established a computational framework that informed the optimal arrangement of electrodes on a new paddle lead and guided its neurosurgical positioning. We also developed software supporting the rapid configuration of activity-specific stimulation programs that reproduced the natural activation of motor neurons underlying each activity. We tested these neurotechnologies in three individuals with complete sensorimotor paralysis as part of an ongoing clinical trial ( www.clinicaltrials.gov identifier NCT02936453). Within a single day, activity-specific stimulation programs enabled these three individuals to stand, walk, cycle, swim and control trunk movements. Neurorehabilitation mediated sufficient improvement to restore these activities in community settings, opening a realistic path to support everyday mobility with EES in people with SCI.
Collapse
|
23
|
Towards reliable spinal cord fMRI: assessment of common imaging protocols. Neuroimage 2022; 250:118964. [DOI: 10.1016/j.neuroimage.2022.118964] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 01/07/2022] [Accepted: 02/01/2022] [Indexed: 01/29/2023] Open
|
24
|
Landelle C, Lungu O, Vahdat S, Kavounoudias A, Marchand-Pauvert V, De Leener B, Doyon J. Investigating the human spinal sensorimotor pathways through functional magnetic resonance imaging. Neuroimage 2021; 245:118684. [PMID: 34732324 DOI: 10.1016/j.neuroimage.2021.118684] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 10/25/2021] [Accepted: 10/25/2021] [Indexed: 01/29/2023] Open
Abstract
Most of our knowledge about the human spinal ascending (sensory) and descending (motor) pathways comes from non-invasive electrophysiological investigations. However, recent methodological advances in acquisition and analyses of functional magnetic resonance imaging (fMRI) data from the spinal cord, either alone or in combination with the brain, have allowed us to gain further insights into the organization of this structure. In the current review, we conducted a systematic search to produced somatotopic maps of the spinal fMRI activity observed through different somatosensory, motor and resting-state paradigms. By cross-referencing these human neuroimaging findings with knowledge acquired through neurophysiological recordings, our review demonstrates that spinal fMRI is a powerful tool for exploring, in vivo, the human spinal cord pathways. We report strong cross-validation between task-related and resting-state fMRI in accordance with well-known hemicord, postero-anterior and rostro-caudal organization of these pathways. We also highlight the specific advantages of using spinal fMRI in clinical settings to characterize better spinal-related impairments, predict disease progression, and guide the implementation of therapeutic interventions.
Collapse
Affiliation(s)
- Caroline Landelle
- McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada.
| | - Ovidiu Lungu
- McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | | | - Anne Kavounoudias
- CNRS, UMR7291, Laboratory of Cognitive Neurosciences, Aix-Marseille University, Marseille, France
| | | | - Benjamin De Leener
- Department of Computer Engineering and Software Engineering, Polytechnique Montreal, Montreal, QC, Canada; CHU Sainte-Justine Research Centre, Montreal, QC, Canada
| | - Julien Doyon
- McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| |
Collapse
|
25
|
Valenzuela F, Rana M, Sitaram R, Uribe S, Eblen-Zajjur A. Non-Invasive Functional Evaluation of the Human Spinal Cord by Assessing the Peri-Spinal Neurovascular Network With Near Infrared Spectroscopy. IEEE Trans Neural Syst Rehabil Eng 2021; 29:2312-2321. [PMID: 34705650 DOI: 10.1109/tnsre.2021.3123587] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Current medical care lacks an effective functional evaluation for the spinal cord. Magnetic resonance imaging and computed tomography mainly provide structural information of the spinal cord, while spinal somatosensory evoked potentials are limited by a low signal to noise ratio. We developed a non-invasive approach based on near-infrared spectroscopy in dual-wavelength (760 and 850 nm for deoxy- or oxyhemoglobin respectively) to record the neurovascular response (NVR) of the peri-spinal vascular network at the 7th cervical and 10th thoracic vertebral levels of the spinal cord, triggered by unilateral median nerve electrical stimulation (square pulse, 5-10 mA, 5 ms, 1 pulse every 4 minutes) at the wrist. Amplitude, rise-time, and duration of NVR were characterized in 20 healthy participants. A single, painless stimulus was able to elicit a high signal-to-noise ratio and multi-segmental NVR (mainly from Oxyhemoglobin) with a fast rise time of 6.18 [4.4-10.4] seconds (median [Percentile 25-75]) followed by a slow decay phase for about 30 seconds toward the baseline. Cervical NVR was earlier and larger than thoracic and no left/right asymmetry was detected. Stimulus intensity/NVR amplitude fitted to a 2nd order function. The characterization and feasibility of the peri-spinal NVR strongly support the potential clinical applications for a functional assessment of spinal cord lesions.
Collapse
|
26
|
Sengupta A, Mishra A, Wang F, Li M, Yang PF, Chen LM, Gore JC. Functional networks in non-human primate spinal cord and the effects of injury. Neuroimage 2021; 240:118391. [PMID: 34271158 PMCID: PMC8527400 DOI: 10.1016/j.neuroimage.2021.118391] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 06/15/2021] [Accepted: 07/12/2021] [Indexed: 12/12/2022] Open
Abstract
Spontaneous fluctuations of Blood Oxygenation-Level Dependent (BOLD) MRI signal in a resting state have previously been detected and analyzed to describe intrinsic functional networks in the spinal cord of rodents, non-human primates and human subjects. In this study we combined high resolution imaging at high field with data-driven Independent Component Analysis (ICA) to i) delineate fine-scale functional networks within and between segments of the cervical spinal cord of monkeys, and also to ii) characterize the longitudinal effects of a unilateral dorsal column injury on these networks. Seven distinct functional hubs were revealed within each spinal segment, with new hubs detected at bilateral intermediate and gray commissure regions in addition to the bilateral dorsal and ventral horns previously reported. Pair-wise correlations revealed significantly stronger connections between hubs on the dominant hand side. Unilateral dorsal-column injuries disrupted predominantly inter-segmental rather than intra-segmental functional connectivities as revealed by correlation strengths and graph-theory based community structures. The effects of injury on inter-segmental connectivity were evident along the length of the cord both below and above the lesion region. Connectivity strengths recovered over time and there was revival of inter-segmental communities as animals recovered function. BOLD signals of frequency 0.01-0.033 Hz were found to be most affected by injury. The results in this study provide new insights into the intrinsic functional architecture of spinal cord and underscore the potential of functional connectivity measures to characterize changes in networks after an injury and during recovery.
Collapse
Affiliation(s)
- Anirban Sengupta
- Vanderbilt University Institute of Imaging Science, Nashville, TN, 37232, USA; Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Arabinda Mishra
- Vanderbilt University Institute of Imaging Science, Nashville, TN, 37232, USA; Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Feng Wang
- Vanderbilt University Institute of Imaging Science, Nashville, TN, 37232, USA; Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Muwei Li
- Vanderbilt University Institute of Imaging Science, Nashville, TN, 37232, USA; Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Pai-Feng Yang
- Vanderbilt University Institute of Imaging Science, Nashville, TN, 37232, USA; Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Li Min Chen
- Vanderbilt University Institute of Imaging Science, Nashville, TN, 37232, USA; Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37232, USA.
| | - John C Gore
- Vanderbilt University Institute of Imaging Science, Nashville, TN, 37232, USA; Biomedical Engineering, Vanderbilt University, Nashville, TN, 37232, USA; Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37232, USA; Department of Physics and Astronomy, Vanderbilt University, Nashville, TN, 37232, USA
| |
Collapse
|
27
|
Structural and resting state functional connectivity beyond the cortex. Neuroimage 2021; 240:118379. [PMID: 34252527 DOI: 10.1016/j.neuroimage.2021.118379] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 05/21/2021] [Accepted: 07/07/2021] [Indexed: 12/14/2022] Open
Abstract
Mapping the structural and functional connectivity of the central nervous system has become a key area within neuroimaging research. While detailed network structures across the entire brain have been probed using animal models, non-invasive neuroimaging in humans has thus far been dominated by cortical investigations. Beyond the cortex, subcortical nuclei have traditionally been less accessible due to their smaller size and greater distance from radio frequency coils. However, major neuroimaging developments now provide improved signal and the resolution required to study these structures. Here, we present an overview of the connectivity between the amygdala, brainstem, cerebellum, spinal cord and the rest of the brain. While limitations to their imaging and analyses remain, we also provide some recommendations and considerations for mapping brain connectivity beyond the cortex.
Collapse
|
28
|
Wang F, Zhang L, Yue L, Zeng Y, Zhao Q, Gong Q, Zhang J, Liu D, Luo X, Xia X, Wan L, Hu L. A novel method to simultaneously record spinal cord electrophysiology and electroencephalography signals. Neuroimage 2021; 232:117892. [PMID: 33617992 DOI: 10.1016/j.neuroimage.2021.117892] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2020] [Revised: 01/13/2021] [Accepted: 02/16/2021] [Indexed: 11/16/2022] Open
Abstract
The brain and the spinal cord together make up the central nervous system (CNS). The functions of the human brain have been the focus of neuroscience research for a long time. However, the spinal cord is largely ignored, and the functional interaction of these two parts of the CNS is only partly understood. This study developed a novel method to simultaneously record spinal cord electrophysiology (SCE) and electroencephalography (EEG) signals and validated its performance using a classical resting-state study design with two experimental conditions: eyes-closed (EC) and eyes-open (EO). We recruited nine postherpetic neuralgia patients implanted with a spinal cord stimulator, which was modified to record SCE signals simultaneously with EEG signals. For both EEG and SCE, similar differences were found in delta- and alpha-band oscillations between the EC and EO conditions, and the spectral power of these frequency bands was able to predict EC/EO behaviors. Moreover, causal connectivity analysis suggested a top-down regulation in delta-band oscillations from the brain to the spinal cord. Altogether, this study demonstrates the validity of simultaneous SCE-EEG recording and shows that the novel method is a valuable tool to investigate the brain-spinal interaction. With this method, we can better unite knowledge about the brain and the spinal cord for a deeper understanding of the functions of the whole CNS.
Collapse
Affiliation(s)
- Feixue Wang
- Department of Pain Management, The State Key Clinical Specialty in Pain Medicine, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, China; CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China; Research Center of Brain Cognitive Neuroscience, Liaoning Normal University, Dalian, China
| | - Libo Zhang
- CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Lupeng Yue
- CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Yuxuan Zeng
- CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, China
| | - Qing Zhao
- Department of Pain Management, The State Key Clinical Specialty in Pain Medicine, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, China; CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, China
| | - Qingjuan Gong
- Department of Pain Management, The State Key Clinical Specialty in Pain Medicine, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, China
| | - Jianbo Zhang
- Department of Pain Management, The State Key Clinical Specialty in Pain Medicine, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, China
| | - Dongyang Liu
- Department of Pain Management, The State Key Clinical Specialty in Pain Medicine, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, China
| | - Xiuying Luo
- Department of Pain Management, The State Key Clinical Specialty in Pain Medicine, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, China
| | - Xiaolei Xia
- CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Li Wan
- Department of Pain Management, The State Key Clinical Specialty in Pain Medicine, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, China.
| | - Li Hu
- Department of Pain Management, The State Key Clinical Specialty in Pain Medicine, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, China; CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.
| |
Collapse
|
29
|
Eslami T, Almuqhim F, Raiker JS, Saeed F. Machine Learning Methods for Diagnosing Autism Spectrum Disorder and Attention- Deficit/Hyperactivity Disorder Using Functional and Structural MRI: A Survey. Front Neuroinform 2021; 14:575999. [PMID: 33551784 PMCID: PMC7855595 DOI: 10.3389/fninf.2020.575999] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Accepted: 12/07/2020] [Indexed: 12/15/2022] Open
Abstract
Here we summarize recent progress in machine learning model for diagnosis of Autism Spectrum Disorder (ASD) and Attention-deficit/Hyperactivity Disorder (ADHD). We outline and describe the machine-learning, especially deep-learning, techniques that are suitable for addressing research questions in this domain, pitfalls of the available methods, as well as future directions for the field. We envision a future where the diagnosis of ASD, ADHD, and other mental disorders is accomplished, and quantified using imaging techniques, such as MRI, and machine-learning models.
Collapse
Affiliation(s)
- Taban Eslami
- Department of Computer Science, Western Michigan University, Kalamazoo, MI, United States
| | - Fahad Almuqhim
- School of Computing and Information Sciences, Florida International University, Miami, FL, United States
| | - Joseph S. Raiker
- Department of Psychology, Florida International University, Miami, FL, United States
| | - Fahad Saeed
- School of Computing and Information Sciences, Florida International University, Miami, FL, United States
| |
Collapse
|
30
|
Tarun A, Wainstein-Andriano D, Sterpenich V, Bayer L, Perogamvros L, Solms M, Axmacher N, Schwartz S, Van De Ville D. NREM sleep stages specifically alter dynamical integration of large-scale brain networks. iScience 2020; 24:101923. [PMID: 33409474 PMCID: PMC7773861 DOI: 10.1016/j.isci.2020.101923] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 11/07/2020] [Accepted: 12/07/2020] [Indexed: 02/07/2023] Open
Abstract
Functional dissociations in the brain observed during non-rapid eye movement (NREM) sleep have been associated with reduced information integration and impaired consciousness that accompany increasing sleep depth. Here, we explored the dynamical properties of large-scale functional brain networks derived from transient brain activity using functional magnetic resonance imaging. Spatial brain maps generally display significant modifications in terms of their tendency to occur across wakefulness and NREM sleep. Unexpectedly, almost all networks predominated in activity during NREM stage 2 before an abrupt loss of activity is observed in NREM stage 3. Yet, functional connectivity and mutual dependencies between these networks progressively broke down with increasing sleep depth. Thus, the efficiency of information transfer during NREM stage 2 is low despite the high attempt to communicate. Critically, our approach provides relevant data for evaluating functional brain network integrity and our findings robustly support a significant advance in our neural models of human sleep and consciousness.
Collapse
Affiliation(s)
- Anjali Tarun
- École Polytechnique Fédérale de Lausanne (Institute of Bioengineering, Medical Image Processing Laboratory), Geneva 1202, Switzerland.,University of Geneva (Department of Radiology and Medical Informatics), Geneva 1202, Switzerland
| | - Danyal Wainstein-Andriano
- University of Cape Town (Psychology Department, Faculty of Humanities), Cape Town 7701, South Africa.,Ruhr-Universität Bochum (Institute of Cognitive Neuroscience, Faculty of Psychology), Ruhr 44801, Germany
| | - Virginie Sterpenich
- University of Geneva, (Department of Basic Neurosciences), Geneva 1202, Switzerland
| | - Laurence Bayer
- University Hospitals of Geneva (Center for Sleep Medicine, Department of Medicine), Geneva 1202, Switzerland
| | - Lampros Perogamvros
- University of Geneva, (Department of Basic Neurosciences), Geneva 1202, Switzerland.,University Hospitals of Geneva (Center for Sleep Medicine, Department of Medicine), Geneva 1202, Switzerland
| | - Mark Solms
- University of Cape Town (Psychology Department, Faculty of Humanities), Cape Town 7701, South Africa
| | - Nikolai Axmacher
- Ruhr-Universität Bochum (Institute of Cognitive Neuroscience, Faculty of Psychology), Ruhr 44801, Germany
| | - Sophie Schwartz
- University of Geneva, (Department of Basic Neurosciences), Geneva 1202, Switzerland
| | - Dimitri Van De Ville
- École Polytechnique Fédérale de Lausanne (Institute of Bioengineering, Medical Image Processing Laboratory), Geneva 1202, Switzerland.,University of Geneva (Department of Radiology and Medical Informatics), Geneva 1202, Switzerland
| |
Collapse
|