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Treves IN, Yang WFZ, Sparby T, Sacchet MD. Dynamic brain states underlying advanced concentrative absorption meditation: A 7-T fMRI-intensive case study. Netw Neurosci 2025; 9:125-145. [PMID: 40161981 PMCID: PMC11949543 DOI: 10.1162/netn_a_00432] [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: 07/09/2024] [Accepted: 11/19/2024] [Indexed: 04/02/2025] Open
Abstract
Advanced meditation consists of states and stages of practice that unfold with mastery and time. Dynamic functional connectivity (DFC) analysis of fMRI could identify brain states underlying advanced meditation. We conducted an intensive DFC case study of a meditator who completed 27 runs of jhāna advanced absorptive concentration meditation (ACAM-J), concurrently with 7-T fMRI and phenomenological reporting. We identified three brain states that marked differences between ACAM-J and nonmeditative control conditions. These states were characterized as a DMN-anticorrelated brain state, a hyperconnected brain state, and a sparsely connected brain state. Our analyses indicate higher prevalence of the DMN-anticorrelated brain state during ACAM-J than control states, and the prevalence increased significantly with deeper ACAM-J states. The hyperconnected brain state was also more common during ACAM-J and was characterized by elevated thalamocortical connectivity and somatomotor network connectivity. The hyperconnected brain state significantly decreased over the course of ACAM-J, associating with self-reports of wider attention and diminished physical sensations. This brain state may be related to sensory awareness. Advanced meditators have developed well-honed abilities to move in and out of different altered states of consciousness, and this study provides initial evidence that functional neuroimaging can objectively track their dynamics.
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Affiliation(s)
- Isaac N. Treves
- Meditation Research Program, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Winson F. Z. Yang
- Meditation Research Program, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Terje Sparby
- Rudolf Steiner University College, Oslo, Norway
- Department of Psychology and Psychotherapy, Witten/Herdecke University, Witten, Germany
- Integrated Curriculum for Anthroposophic Psychology, Witten/Herdecke University, Witten, Germany
| | - Matthew D. Sacchet
- Meditation Research Program, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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2
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Zhang J, Chen D, Deming P, Srirangarajan T, Theriault J, Kragel PA, Hartley L, Lee KM, McVeigh K, Wager TD, Wald LL, Satpute AB, Quigley KS, Whitfield-Gabrieli S, Barrett LF, Bianciardi M. Cortical and subcortical mapping of the allostatic-interoceptive system in the human brain using 7 Tesla fMRI. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2023.07.20.548178. [PMID: 37546889 PMCID: PMC10401932 DOI: 10.1101/2023.07.20.548178] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
The brain continuously anticipates the energetic needs of the body and prepares to meet those needs before they arise, called allostasis. In support of allostasis, the brain continually models the sensory state of the body, called interoception. We replicated and extended a large-scale system supporting allostasis and interoception in the human brain using ultra-high precision 7 Tesla functional magnetic resonance imaging (fMRI) (N = 90), improving the precision of subgenual and pregenual anterior cingulate topography combined with extensive brainstem nuclei mapping. We observed over 90% of the anatomical connections published in tract-tracing studies in non-human animals. The system also included regions of dense intrinsic connectivity broadly throughout the system, some of which were identified previously as part of the backbone of neural communication across the brain. These results strengthen previous evidence for a whole-brain system supporting the modeling and regulation of the internal milieu of the body.
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Affiliation(s)
- Jiahe Zhang
- Department of Psychology, Northeastern University, Boston, MA 02115
| | - Danlei Chen
- Department of Psychology, Northeastern University, Boston, MA 02115
| | - Philip Deming
- Department of Psychology, Northeastern University, Boston, MA 02115
| | | | - Jordan Theriault
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA 02139
| | | | - Ludger Hartley
- Department of Psychology, Northeastern University, Boston, MA 02115
| | - Kent M. Lee
- Department of Psychology, Northeastern University, Boston, MA 02115
| | - Kieran McVeigh
- Department of Psychology, Northeastern University, Boston, MA 02115
| | - Tor D. Wager
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH 03755
| | - Lawrence L. Wald
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA 02139
| | - Ajay B. Satpute
- Department of Psychology, Northeastern University, Boston, MA 02115
| | - Karen S. Quigley
- Department of Psychology, Northeastern University, Boston, MA 02115
| | | | - Lisa Feldman Barrett
- Department of Psychology, Northeastern University, Boston, MA 02115
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA 02139
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02139
| | - Marta Bianciardi
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA 02139
- Division of Sleep Medicine, Harvard University, Boston, MA
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3
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Yang WFZ, Chowdhury A, Sparby T, Sacchet MD. Deconstructing the self and reshaping perceptions: An intensive whole-brain 7T MRI case study of the stages of insight during advanced investigative insight meditation. Neuroimage 2025; 305:120968. [PMID: 39653180 DOI: 10.1016/j.neuroimage.2024.120968] [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: 03/18/2024] [Revised: 12/05/2024] [Accepted: 12/06/2024] [Indexed: 12/19/2024] Open
Abstract
The stages of insight (SoI) are a series of psychological realizations experienced through advanced investigative insight meditation (AIIM). SoI provide a powerful structured framework of AIIM for understanding and evaluating insight-based meditative development through changes in perception, experiences of self, cognition, and emotional processing. Yet, the neurophenomenology of SoI remains unstudied due to methodological difficulties, rarity of suitable advanced meditation practitioners, and dominant research emphasis on attention-based meditative practices. We investigated the neurophenomenology of SoI in an intensively sampled adept meditator case study (4 hr 7T fMRI collected in 26 runs with concurrent phenomenology) who performed SoI and rated specific aspects of experience immediately thereafter. Linear mixed models and correlations were used to examine relations among the cortex, subcortex, brainstem, and cerebellum, and SoI phenomenology. We identified distinctive whole-brain activity patterns associated with specific SoI, and that were different from two non-meditative control states. SoI consistently deactivated regions implicated in self-related processing, including the medial prefrontal cortex and temporal poles, while activating regions associated with awareness and perception, including the parietal and visual cortices, caudate, several brainstem nuclei, and cerebellum. Patterns of brain activity related to affective processing and SoI phenomenology were also identified. Our study presents the first neurophenomenological evidence that SoI shifts and deconstructs self-related perception and conceptualization, and increases general awareness and perceptual sensitivity and acuity. Our study provides SoI as a foundation for investigative, and advanced meditation in particular.
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Affiliation(s)
- Winson F Z Yang
- Meditation Research Program, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA
| | - Avijit Chowdhury
- Meditation Research Program, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA; Depression and Anxiety Center for Discovery and Treatment, Icahn School of Medicine at Mount Sinai, NY 10029, USA
| | - Terje Sparby
- Steiner University College, 0260 Oslo, Norway; Department of Psychology and Psychotherapy, Witten/Herdecke University, 58455 Witten, Germany; Integrated Curriculum for Anthroposophic Psychology, Witten/Herdecke University, 58455 Witten, Germany
| | - Matthew D Sacchet
- Meditation Research Program, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA.
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4
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Chen JE, Blazejewska AI, Fan J, Fultz NE, Rosen BR, Lewis LD, Polimeni JR. Differentiating BOLD and non-BOLD signals in fMRI time series using cross-cortical depth delay patterns. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.12.26.628516. [PMID: 39764035 PMCID: PMC11703183 DOI: 10.1101/2024.12.26.628516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/11/2025]
Abstract
Over the past two decades, rapid advancements in magnetic resonance technology have significantly enhanced the imaging resolution of functional Magnetic Resonance Imaging (fMRI), far surpassing its initial capabilities. Beyond mapping brain functional architecture at unprecedented scales, high-spatial-resolution acquisitions have also inspired and enabled several novel analytical strategies that can potentially improve the sensitivity and neuronal specificity of fMRI. With small voxels, one can sample from different levels of the vascular hierarchy within the cerebral cortex and resolve the temporal progression of hemodynamic changes from parenchymal to pial vessels. We propose that this characteristic pattern of temporal progression across cortical depths can aid in distinguishing neurogenic blood-oxygenation-level-dependent (BOLD) signals from typical nuisance factors arising from non-BOLD origins, such as head motion and pulsatility. In this study, we examine the feasibility of applying cross-cortical depth temporal delay patterns to automatically categorize BOLD and non-BOLD signal components in modern-resolution BOLD-fMRI data. We construct an independent component analysis (ICA)-based framework for fMRI de-noising, analogous to previously proposed multi-echo (ME) ICA, except that here we explore the across-depth instead of across-echo dependence to distinguish BOLD and non-BOLD components. The efficacy of this framework is demonstrated using visual task data at three graded spatiotemporal resolutions (voxel sizes = 1.1, 1.5, and 2.0 mm isotropic at temporal intervals = 1700, 1120, and 928 ms). The proposed framework leverages prior knowledge of the spatiotemporal properties of BOLD-fMRI and serves as an alternative to ME-ICA for cleaning moderate- and high-spatial-resolution fMRI data when multi-echo acquisitions are not available.
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Affiliation(s)
- Jingyuan E. Chen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Anna I. Blazejewska
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Jiawen Fan
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Nina E. Fultz
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Bruce R. Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Harvard-MIT Program in Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Laura D. Lewis
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge MA, USA
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge MA, USA
| | - Jonathan R. Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Harvard-MIT Program in Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
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5
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Hansen JY, Cauzzo S, Singh K, García-Gomar MG, Shine JM, Bianciardi M, Misic B. Integrating brainstem and cortical functional architectures. Nat Neurosci 2024; 27:2500-2511. [PMID: 39414973 PMCID: PMC11614745 DOI: 10.1038/s41593-024-01787-0] [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: 11/06/2023] [Accepted: 09/13/2024] [Indexed: 10/18/2024]
Abstract
The brainstem is a fundamental component of the central nervous system, yet it is typically excluded from in vivo human brain mapping efforts, precluding a complete understanding of how the brainstem influences cortical function. In this study, we used high-resolution 7-Tesla functional magnetic resonance imaging to derive a functional connectome encompassing cortex and 58 brainstem nuclei spanning the midbrain, pons and medulla. We identified a compact set of integrative hubs in the brainstem with widespread connectivity with cerebral cortex. Patterns of connectivity between brainstem and cerebral cortex manifest as neurophysiological oscillatory rhythms, patterns of cognitive functional specialization and the unimodal-transmodal functional hierarchy. This persistent alignment between cortical functional topographies and brainstem nuclei is shaped by the spatial arrangement of multiple neurotransmitter receptors and transporters. We replicated all findings using 3-Tesla data from the same participants. Collectively, this work demonstrates that multiple organizational features of cortical activity can be traced back to the brainstem.
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Affiliation(s)
- Justine Y Hansen
- Montréal Neurological Institute, McGill University, Montréal, Quebec, Canada
| | - Simone Cauzzo
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Parkinson's Disease and Movement Disorders Unit, Center for Rare Neurological Diseases (ERN-RND), University of Padova, Padova, Italy
| | - Kavita Singh
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - María Guadalupe García-Gomar
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Escuela Nacional de Estudios Superiores, Unidad Juriquilla, Universidad Nacional Autónoma de México, Querétaro, Mexico
| | - James M Shine
- Brain and Mind Centre, The University of Sydney, Sydney, Australia
| | - Marta Bianciardi
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Division of Sleep Medicine, Harvard University, Boston, MA, USA
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, Quebec, Canada.
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6
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Olchanyi MD, Augustinack J, Haynes RL, Lewis LD, Cicero N, Li J, Destrieux C, Folkerth RD, Kinney HC, Fischl B, Brown EN, Iglesias JE, Edlow BL. Histology-guided MRI segmentation of brainstem nuclei critical to consciousness. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.09.26.24314117. [PMID: 39399006 PMCID: PMC11469455 DOI: 10.1101/2024.09.26.24314117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 10/15/2024]
Abstract
While substantial progress has been made in mapping the connectivity of cortical networks responsible for conscious awareness, neuroimaging analysis of subcortical arousal networks that modulate arousal (i.e., wakefulness) has been limited by a lack of a robust segmentation procedures for brainstem arousal nuclei. Automated segmentation of brainstem arousal nuclei is an essential step toward elucidating the physiology of arousal in human consciousness and the pathophysiology of disorders of consciousness. We created a probabilistic atlas of brainstem arousal nuclei built on diffusion MRI scans of five ex vivo human brain specimens scanned at 750 μm isotropic resolution. Labels of arousal nuclei used to generate the probabilistic atlas were manually annotated with reference to nucleus-specific immunostaining in two of the five brain specimens. We then developed a Bayesian segmentation algorithm that utilizes the probabilistic atlas as a generative model and automatically identifies brainstem arousal nuclei in a resolution- and contrast-agnostic manner. The segmentation method displayed high accuracy in both healthy and lesioned in vivo T1 MRI scans and high test-retest reliability across both T1 and T2 MRI contrasts. Finally, we show that the segmentation algorithm can detect volumetric changes and differences in magnetic susceptibility within brainstem arousal nuclei in Alzheimer's disease and traumatic coma, respectively. We release the probabilistic atlas and Bayesian segmentation tool in FreeSurfer to advance the study of human consciousness and its disorders.
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7
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Hoffman LJ, Foley JM, Leong JK, Sullivan-Toole H, Elliott BL, Olson IR. A Virtual In Vivo Dissection and Analysis of Socioaffective Symptoms Related to Cerebellum-Midbrain Reward Circuitry in Humans. J Neurosci 2024; 44:e1031242024. [PMID: 39256045 PMCID: PMC11466071 DOI: 10.1523/jneurosci.1031-24.2024] [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: 06/03/2024] [Revised: 08/23/2024] [Accepted: 08/26/2024] [Indexed: 09/12/2024] Open
Abstract
Emerging research in nonhuman animals implicates cerebellar projections to the ventral tegmental area (VTA) in appetitive behaviors, but these circuits have not been characterized in humans. Here, we mapped cerebello-VTA white matter connectivity in a cohort of men and women using probabilistic tractography on diffusion imaging data from the Human Connectome Project. We uncovered the topographical organization of these connections by separately tracking from parcels of cerebellar lobule VI, crus I/II, vermis, paravermis, and cerebrocerebellum. Results revealed that connections between the cerebellum and VTA predominantly originate in the right cerebellar hemisphere, interposed nucleus, and paravermal cortex and terminate mostly ipsilaterally. Paravermal crus I sends the most connections to the VTA compared with other lobules. We discovered a mediolateral gradient of connectivity, such that the medial cerebellum has the highest connectivity with the VTA. Individual differences in microstructure were associated with measures of negative affect and social functioning. By splitting the tracts into quarters, we found that the socioaffective effects were driven by the third quarter of the tract, corresponding to the point at which the fibers leave the deep nuclei. Taken together, we produced detailed maps of cerebello-VTA structural connectivity for the first time in humans and established their relevance for trait differences in socioaffective regulation.
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Affiliation(s)
- Linda J Hoffman
- Department of Psychology and Neuroscience, Temple University, Philadelphia, Pennsylvania 19122
| | - Julia M Foley
- Department of Psychology and Neuroscience, Temple University, Philadelphia, Pennsylvania 19122
| | - Josiah K Leong
- Department of Psychological Science, University of Arkansas, Fayetteville, Arkansas 72701
| | - Holly Sullivan-Toole
- Department of Psychology and Neuroscience, Temple University, Philadelphia, Pennsylvania 19122
| | - Blake L Elliott
- Department of Psychology and Neuroscience, Temple University, Philadelphia, Pennsylvania 19122
| | - Ingrid R Olson
- Department of Psychology and Neuroscience, Temple University, Philadelphia, Pennsylvania 19122
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8
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Chandra NK, Sitek KR, Chandrasekaran B, Sarkar A. Functional connectivity across the human subcortical auditory system using an autoregressive matrix-Gaussian copula graphical model approach with partial correlations. IMAGING NEUROSCIENCE (CAMBRIDGE, MASS.) 2024; 2:10.1162/imag_a_00258. [PMID: 39421593 PMCID: PMC11485223 DOI: 10.1162/imag_a_00258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2024]
Abstract
The auditory system comprises multiple subcortical brain structures that process and refine incoming acoustic signals along the primary auditory pathway. Due to technical limitations of imaging small structures deep inside the brain, most of our knowledge of the subcortical auditory system is based on research in animal models using invasive methodologies. Advances in ultrahigh-field functional magnetic resonance imaging (fMRI) acquisition have enabled novel noninvasive investigations of the human auditory subcortex, including fundamental features of auditory representation such as tonotopy and periodotopy. However, functional connectivity across subcortical networks is still underexplored in humans, with ongoing development of related methods. Traditionally, functional connectivity is estimated from fMRI data with full correlation matrices. However, partial correlations reveal the relationship between two regions after removing the effects of all other regions, reflecting more direct connectivity. Partial correlation analysis is particularly promising in the ascending auditory system, where sensory information is passed in an obligatory manner, from nucleus to nucleus up the primary auditory pathway, providing redundant but also increasingly abstract representations of auditory stimuli. While most existing methods for learning conditional dependency structures based on partial correlations assume independently and identically Gaussian distributed data, fMRI data exhibit significant deviations from Gaussianity as well as high-temporal autocorrelation. In this paper, we developed an autoregressive matrix-Gaussian copula graphical model (ARMGCGM) approach to estimate the partial correlations and thereby infer the functional connectivity patterns within the auditory system while appropriately accounting for autocorrelations between successive fMRI scans. Our results show strong positive partial correlations between successive structures in the primary auditory pathway on each side (left and right), including between auditory midbrain and thalamus, and between primary and associative auditory cortex. These results are highly stable when splitting the data in halves according to the acquisition schemes and computing partial correlations separately for each half of the data, as well as across cross-validation folds. In contrast, full correlation-based analysis identified a rich network of interconnectivity that was not specific to adjacent nodes along the pathway. Overall, our results demonstrate that unique functional connectivity patterns along the auditory pathway are recoverable using novel connectivity approaches and that our connectivity methods are reliable across multiple acquisitions.
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Affiliation(s)
- Noirrit Kiran Chandra
- The University of Texas at Dallas, Department of Mathematical Sciences, Richardson, TX 76010, USA
| | - Kevin R. Sitek
- Northwestern University, Roxelyn and Richard Pepper Department of Communication Sciences and Disorders, Evanston, IL 60208, USA
| | - Bharath Chandrasekaran
- Northwestern University, Roxelyn and Richard Pepper Department of Communication Sciences and Disorders, Evanston, IL 60208, USA
| | - Abhra Sarkar
- The University of Texas at Austin, Department of Statistics and Data Sciences, Austin, TX 78712, USA
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9
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Hoffman LJ, Foley JM, Leong JK, Sullivan-Toole H, Elliott BL, Olson IR. An in vivo Dissection, and Analysis of Socio-Affective Symptoms related to Cerebellum-Midbrain Reward Circuitry in Humans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.09.29.560239. [PMID: 38798382 PMCID: PMC11118266 DOI: 10.1101/2023.09.29.560239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Emerging research in non-human animals implicates cerebellar projections to the ventral tegmental area (VTA) in appetitive behaviors, but these circuits have not been characterized in humans. Here, we mapped cerebello-VTA white-matter connectivity in humans using probabilistic tractography on diffusion imaging data from the Human Connectome Project. We uncovered the topographical organization of these connections by separately tracking from parcels of cerebellar lobule VI, crus I/II, vermis, paravermis, and cerebrocerebellum. Results revealed that connections from the cerebellum to the VTA predominantly originate in the right hemisphere, interposed nucleus, and paravermal cortex, and terminate mostly ipsilaterally. Paravermal crus I sends the most connections to the VTA compared to other lobules. We discovered a medial-to-lateral gradient of connectivity, such that the medial cerebellum has the highest connectivity with the VTA. Individual differences in microstructure were associated with measures of negative affect and social functioning. By splitting the tracts into quarters, we found that the socio-affective effects were driven by the third quarter of the tract, corresponding to the point at which the fibers leave the deep nuclei. Taken together, we produced detailed maps of cerebello-VTA structural connectivity for the first time in humans and established their relevance for trait differences in socio-affective regulation.
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Affiliation(s)
- Linda J. Hoffman
- Temple University, Department of Psychology and Neuroscience, Philadelphia, PA, USA
| | - Julia M. Foley
- Temple University, Department of Psychology and Neuroscience, Philadelphia, PA, USA
| | - Josiah K. Leong
- University of Arkansas, Department of Psychological Science, Fayetteville, AR, USA
| | - Holly Sullivan-Toole
- Temple University, Department of Psychology and Neuroscience, Philadelphia, PA, USA
| | - Blake L. Elliott
- Temple University, Department of Psychology and Neuroscience, Philadelphia, PA, USA
| | - Ingrid R. Olson
- Temple University, Department of Psychology and Neuroscience, Philadelphia, PA, USA
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10
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Ganesan S, Yang WFZ, Chowdhury A, Zalesky A, Sacchet MD. Within-subject reliability of brain networks during advanced meditation: An intensively sampled 7 Tesla MRI case study. Hum Brain Mapp 2024; 45:e26666. [PMID: 38726831 PMCID: PMC11082832 DOI: 10.1002/hbm.26666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 02/09/2024] [Accepted: 03/10/2024] [Indexed: 05/13/2024] Open
Abstract
Advanced meditation such as jhana meditation can produce various altered states of consciousness (jhanas) and cultivate rewarding psychological qualities including joy, peace, compassion, and attentional stability. Mapping the neurobiological substrates of jhana meditation can inform the development and application of advanced meditation to enhance well-being. Only two prior studies have attempted to investigate the neural correlates of jhana meditation, and the rarity of adept practitioners has largely restricted the size and extent of these studies. Therefore, examining the consistency and reliability of observed brain responses associated with jhana meditation can be valuable. In this study, we aimed to characterize functional magnetic resonance imaging (fMRI) reliability within a single subject over repeated runs in canonical brain networks during jhana meditation performed by an adept practitioner over 5 days (27 fMRI runs) inside an ultra-high field 7 Tesla MRI scanner. We found that thalamus and several cortical networks, that is, the somatomotor, limbic, default-mode, control, and temporo-parietal, demonstrated good within-subject reliability across all jhanas. Additionally, we found that several other relevant brain networks (e.g., attention, salience) showed noticeable increases in reliability when fMRI measurements were adjusted for variability in self-reported phenomenology related to jhana meditation. Overall, we present a preliminary template of reliable brain areas likely underpinning core neurocognitive elements of jhana meditation, and highlight the utility of neurophenomenological experimental designs for better characterizing neuronal variability associated with advanced meditative states.
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Affiliation(s)
- Saampras Ganesan
- Department of PsychiatryMelbourne Neuropsychiatry CentreCarltonVictoriaAustralia
- Department of Biomedical EngineeringThe University of MelbourneCarltonVictoriaAustralia
- Contemplative Studies Centre, Melbourne School of Psychological SciencesThe University of MelbourneMelbourneVictoriaAustralia
| | - Winson F. Z. Yang
- Meditation Research Program, Department of Psychiatry, Massachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Avijit Chowdhury
- Meditation Research Program, Department of Psychiatry, Massachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Andrew Zalesky
- Department of PsychiatryMelbourne Neuropsychiatry CentreCarltonVictoriaAustralia
- Department of Biomedical EngineeringThe University of MelbourneCarltonVictoriaAustralia
| | - Matthew D. Sacchet
- Meditation Research Program, Department of Psychiatry, Massachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
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11
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Yang WFZ, Chowdhury A, Bianciardi M, van Lutterveld R, Sparby T, Sacchet MD. Intensive whole-brain 7T MRI case study of volitional control of brain activity in deep absorptive meditation states. Cereb Cortex 2024; 34:bhad408. [PMID: 37943791 PMCID: PMC10793575 DOI: 10.1093/cercor/bhad408] [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: 08/07/2023] [Revised: 10/09/2023] [Accepted: 10/10/2023] [Indexed: 11/12/2023] Open
Abstract
Jhanas are profound states of mind achieved through advanced meditation, offering valuable insights into the nature of consciousness and tools to enhance well-being. Yet, its neurophenomenology remains limited due to methodological difficulties and the rarity of advanced meditation practitioners. We conducted a highly exploratory study to investigate the neurophenomenology of jhanas in an intensively sampled adept meditator case study (4 hr 7T fMRI collected in 27 sessions) who performed jhana meditation and rated specific aspects of experience immediately thereafter. Linear mixed models and correlations were used to examine relations among brain activity and jhana phenomenology. We identified distinctive patterns of brain activity in specific cortical, subcortical, brainstem, and cerebellar regions associated with jhana. Furthermore, we observed correlations between brain activity and phenomenological qualities of attention, jhanic qualities, and narrative processing, highlighting the distinct nature of jhanas compared to non-meditative states. Our study presents the most rigorous evidence yet that jhana practice deconstructs consciousness, offering unique insights into consciousness and significant implications for mental health and well-being.
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Affiliation(s)
- Winson Fu Zun Yang
- Meditation Research Program, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA
| | - Avijit Chowdhury
- Meditation Research Program, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA
| | - Marta Bianciardi
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02129, USA
- Division of Sleep Medicine, Harvard University, Boston, MA 02115, USA
| | - Remko van Lutterveld
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, CX Utrecht 3584, the Netherlands
- Brain Research & Innovation Centre, Ministry of Defence, AA Utrecht 3509, the Netherlands
| | - Terje Sparby
- Steiner University College, Oslo 0260, Norway
- Department of Psychology and Psychotherapy, Witten/Herdecke University, Witten 58448, Germany
- Integrated Curriculum for Anthroposophic Psychology, Witten/Herdecke University, 58448 Witten, Germany
| | - Matthew D Sacchet
- Meditation Research Program, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA
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12
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Hansen JY, Cauzzo S, Singh K, García-Gomar MG, Shine JM, Bianciardi M, Misic B. Integrating brainstem and cortical functional architectures. RESEARCH SQUARE 2023:rs.3.rs-3569352. [PMID: 38076888 PMCID: PMC10705693 DOI: 10.21203/rs.3.rs-3569352/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
The brainstem is a fundamental component of the central nervous system yet it is typically excluded from in vivo human brain mapping efforts, precluding a complete understanding of how the brainstem influences cortical function. Here we use high-resolution 7 Tesla fMRI to derive a functional connectome encompassing cortex as well as 58 brainstem nuclei spanning the midbrain, pons and medulla. We identify a compact set of integrative hubs in the brainstem with widespread connectivity with cerebral cortex. Patterns of connectivity between brainstem and cerebral cortex manifest as multiple emergent phenomena including neurophysiological oscillatory rhythms, patterns of cognitive functional specialization, and the unimodal-transmodal functional hierarchy. This persistent alignment between cortical functional topographies and brainstem nuclei is shaped by the spatial arrangement of multiple neurotransmitter receptors and transporters. We replicate all findings using 3 Tesla data from the same participants. Collectively, we find that multiple organizational features of cortical activity can be traced back to the brainstem.
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Affiliation(s)
- Justine Y. Hansen
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Simone Cauzzo
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Parkinson’s Disease and Movement Disorders Unit, Center for Rare Neurological Diseases (ERN-RND), University of Padova, Padova, Italy
| | - Kavita Singh
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIH, Baltimore, MD, USA
| | - María Guadalupe García-Gomar
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Escuela Nacional de Estudios Superiores, Unidad Juriquilla, Universidad Nacional Autónoma de México, Querétaro, México
| | - James M. Shine
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
| | - Marta Bianciardi
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Division of Sleep Medicine, Harvard University, Boston, MA, USA
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
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13
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Hansen JY, Cauzzo S, Singh K, García-Gomar MG, Shine JM, Bianciardi M, Misic B. Integrating brainstem and cortical functional architectures. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.26.564245. [PMID: 37961347 PMCID: PMC10634864 DOI: 10.1101/2023.10.26.564245] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
The brainstem is a fundamental component of the central nervous system yet it is typically excluded from in vivo human brain mapping efforts, precluding a complete understanding of how the brainstem influences cortical function. Here we use high-resolution 7 Tesla fMRI to derive a functional connectome encompassing cortex as well as 58 brainstem nuclei spanning the midbrain, pons and medulla. We identify a compact set of integrative hubs in the brainstem with widespread connectivity with cerebral cortex. Patterns of connectivity between brainstem and cerebral cortex manifest as multiple emergent phenomena including neurophysiological oscillatory rhythms, patterns of cognitive functional specialization, and the unimodal-transmodal functional hierarchy. This persistent alignment between cortical functional topographies and brainstem nuclei is shaped by the spatial arrangement of multiple neurotransmitter receptors and transporters. We replicate all findings using 3 Tesla data from the same participants. Collectively, we find that multiple organizational features of cortical activity can be traced back to the brainstem.
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Affiliation(s)
- Justine Y. Hansen
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Simone Cauzzo
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Parkinson’s Disease and Movement Disorders Unit, Center for Rare Neurological Diseases (ERN-RND), University of Padova, Padova, Italy
| | - Kavita Singh
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIH, Baltimore, MD, USA
| | - María Guadalupe García-Gomar
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Escuela Nacional de Estudios Superiores, Unidad Juriquilla, Universidad Nacional Autónoma de México, Querétaro, México
| | - James M. Shine
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
| | - Marta Bianciardi
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Division of Sleep Medicine, Harvard University, Boston, MA, USA
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
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14
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Gavazzi G, Giovannelli F, Noferini C, Cincotta M, Cavaliere C, Salvatore M, Mascalchi M, Viggiano MP. Subregional prefrontal cortex recruitment as a function of inhibitory demand: an fMRI metanalysis. Neurosci Biobehav Rev 2023; 152:105285. [PMID: 37327836 DOI: 10.1016/j.neubiorev.2023.105285] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 05/26/2023] [Accepted: 06/11/2023] [Indexed: 06/18/2023]
Abstract
Convergent studies corroborated the idea that the right prefrontal cortex is the crucial brain region responsible for inhibiting our actions. However, which sub-regions of the right prefrontal cortex are involved is still a matter of debate. To map the inhibitory function of the sub-regions of the right prefrontal cortex, we performed Activation Likelihood Estimation (ALE) meta-analyses and meta-regressions (ES-SDM) of fMRI studies exploring inhibitory control. Sixty-eight studies (1684 subjects, 912 foci) were identified and divided in three groups depending on the incremental demand. Overall, our results showed that higher was the inhibitory demand based on the individual differences in performances, more the upper portion of the right prefrontal cortex was activated to achieve a successful inhibition. Conversely, a lower demand of the inhibitory function, was associated with the inferior portions of the right prefrontal cortex recruitment. Notably, in the latter case, we also observed activation of areas associated with working memory and responsible for cognitive strategies.
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Affiliation(s)
- Gioele Gavazzi
- Department of Neuroscience, Psychology, Drug Research, Child Health, University of Florence, Florence, Italy
| | - Fabio Giovannelli
- Department of Neuroscience, Psychology, Drug Research, Child Health, University of Florence, Florence, Italy
| | - Chiara Noferini
- Department of Neuroscience, Psychology, Drug Research, Child Health, University of Florence, Florence, Italy
| | - Massimo Cincotta
- Unit of Neurology of Florence, Central Tuscany Local Health Authority, Firenze, Italy
| | | | | | - Mario Mascalchi
- "Mario Serio" Department of Experimental and Clinical Biomedical Sciences, University of Florence, Italy; Division of Epidemiology, Institute for Study, Prevention and network in Oncology (ISPRO), Florence, Italy
| | - Maria Pia Viggiano
- Department of Neuroscience, Psychology, Drug Research, Child Health, University of Florence, Florence, Italy.
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15
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Edlow BL, Olchanyi M, Freeman HJ, Li J, Maffei C, Snider SB, Zöllei L, Iglesias JE, Augustinack J, Bodien YG, Haynes RL, Greve DN, Diamond BR, Stevens A, Giacino JT, Destrieux C, van der Kouwe A, Brown EN, Folkerth RD, Fischl B, Kinney HC. Sustaining wakefulness: Brainstem connectivity in human consciousness. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.13.548265. [PMID: 37502983 PMCID: PMC10369992 DOI: 10.1101/2023.07.13.548265] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Consciousness is comprised of arousal (i.e., wakefulness) and awareness. Substantial progress has been made in mapping the cortical networks that modulate awareness in the human brain, but knowledge about the subcortical networks that sustain arousal is lacking. We integrated data from ex vivo diffusion MRI, immunohistochemistry, and in vivo 7 Tesla functional MRI to map the connectivity of a subcortical arousal network that we postulate sustains wakefulness in the resting, conscious human brain, analogous to the cortical default mode network (DMN) that is believed to sustain self-awareness. We identified nodes of the proposed default ascending arousal network (dAAN) in the brainstem, hypothalamus, thalamus, and basal forebrain by correlating ex vivo diffusion MRI with immunohistochemistry in three human brain specimens from neurologically normal individuals scanned at 600-750 μm resolution. We performed deterministic and probabilistic tractography analyses of the diffusion MRI data to map dAAN intra-network connections and dAAN-DMN internetwork connections. Using a newly developed network-based autopsy of the human brain that integrates ex vivo MRI and histopathology, we identified projection, association, and commissural pathways linking dAAN nodes with one another and with cortical DMN nodes, providing a structural architecture for the integration of arousal and awareness in human consciousness. We release the ex vivo diffusion MRI data, corresponding immunohistochemistry data, network-based autopsy methods, and a new brainstem dAAN atlas to support efforts to map the connectivity of human consciousness.
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Affiliation(s)
- Brian L. Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown MA 02129, USA
| | - Mark Olchanyi
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Holly J. Freeman
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown MA 02129, USA
| | - Jian Li
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown MA 02129, USA
| | - Chiara Maffei
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown MA 02129, USA
| | - Samuel B. Snider
- Department of Neurology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Lilla Zöllei
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown MA 02129, USA
| | - J. Eugenio Iglesias
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown MA 02129, USA
| | - Jean Augustinack
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown MA 02129, USA
| | - Yelena G. Bodien
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital and Harvard Medical School, Charlestown, MA 02129 USA
| | - Robin L. Haynes
- Department of Pathology, Boston Children’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Douglas N. Greve
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown MA 02129, USA
| | - Bram R. Diamond
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown MA 02129, USA
| | - Allison Stevens
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown MA 02129, USA
| | - Joseph T. Giacino
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital and Harvard Medical School, Charlestown, MA 02129 USA
| | - Christophe Destrieux
- UMR 1253, iBrain, Université de Tours, Inserm, 10 Boulevard Tonnellé, 37032, Tours, France
- CHRU de Tours, 2 Boulevard Tonnellé, Tours, France
| | - Andre van der Kouwe
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown MA 02129, USA
| | - Emery N. Brown
- Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | | | - Bruce Fischl
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown MA 02129, USA
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Hannah C. Kinney
- Department of Pathology, Boston Children’s Hospital and Harvard Medical School, Boston, MA 02115, USA
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16
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You Y, Park JS. A Novel Human Brainstem Map Based on True-Color Sectioned Images. J Korean Med Sci 2023; 38:e76. [PMID: 36918030 PMCID: PMC10010912 DOI: 10.3346/jkms.2023.38.e76] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Accepted: 12/14/2022] [Indexed: 03/06/2023] Open
Abstract
BACKGROUND Existing atlases for the human brainstem were generated from magnetic resonance images or traditional histologically stained slides, but both are insufficient for the identification of detailed brainstem structures at uniform intervals. METHODS A total of 319 sectioned images of the brainstem were selected from whole-body axial sectioned images, then coronal and sagittal sectioned images were reconstructed from the horizontal images. The fine and detailed structures were annotated in PowerPoint slides, then the volume model was produced and some white matter fibers were traced using MRIcroGL. RESULTS In this study, a novel brainstem atlas based on sectioned images was generated that shows the true color and shape, as well as the accurate location of the nuclei and tracts; it reveals the striking contrast between gray and white matter, as well as fine structures. In total, 212 structures, including nuclei and tracts, were annotated in axial, coronal, and sagittal plane views of sectioned images (48-bit true color; 0.2 mm intervals, 0.06 mm × 0.06 mm pixel size). To verify the accuracy of the annotations, a volume model of the brainstem was constructed for independent observations of the three planes. CONCLUSION In this paper, we describe several interesting structures included in the atlas. By depicting the fine structures of the human brainstem in detail, this atlas allows comprehensive understanding of the complicated topographies of the brainstem. As such, it will be of value for neuroanatomy education and research, in addition to enriching the literature on the human brain.
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Affiliation(s)
- Yaqian You
- Department of Anatomy, Dongguk University School of Medicine, Gyeongju, Korea
| | - Jin Seo Park
- Department of Anatomy, Dongguk University School of Medicine, Gyeongju, Korea.
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17
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Demiral ŞB, Kure Liu C, Benveniste H, Tomasi D, Volkow ND. Activation of brain arousal networks coincident with eye blinks during resting state. Cereb Cortex 2023:6991186. [PMID: 36653022 DOI: 10.1093/cercor/bhad001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 12/27/2022] [Accepted: 12/28/2022] [Indexed: 01/20/2023] Open
Abstract
Eye-blinking has been implicated in arousal and attention. Here we test the hypothesis that blinking-moments represent arousal surges associated with activation of the ascending arousal network (AAN) and its thalamic projections. For this purpose, we explored the temporal relationship between eye-blinks and fMRI BOLD activity in AAN and thalamic nuclei, as well as whole brain cluster corrected activations during eyes-open, resting-state fMRI scanning. We show that BOLD activations in the AAN nuclei peaked prior to the eye blinks and in thalamic nuclei peaked prior to and during the blink, consistent with the role of eye blinking in arousal surges. Additionally, we showed visual cortex peak activation prior to the eye blinks, providing further evidence of the visual cortex's role in arousal, and document cerebellar peak activation post eye blinks, which might reflect downstream engagement from arousal surges.
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Affiliation(s)
- Şükrü Barış Demiral
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda 20892, MD, USA
| | - Christopher Kure Liu
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda 20892, MD, USA
| | - Helene Benveniste
- Department of Anesthesiology, Yale University, New Haven, CT 06510, USA
| | - Dardo Tomasi
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda 20892, MD, USA
| | - Nora D Volkow
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda 20892, MD, USA.,National Institute on Drug Abuse, National Institutes of Health, Bethesda, MD 20892, USA
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18
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Levinson S, Miller M, Iftekhar A, Justo M, Arriola D, Wei W, Hazany S, Avecillas-Chasin JM, Kuhn TP, Horn A, Bari AA. A structural connectivity atlas of limbic brainstem nuclei. FRONTIERS IN NEUROIMAGING 2023; 1:1009399. [PMID: 37555163 PMCID: PMC10406319 DOI: 10.3389/fnimg.2022.1009399] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 12/13/2022] [Indexed: 08/10/2023]
Abstract
Background Understanding the structural connectivity of key brainstem nuclei with limbic cortical regions is essential to the development of therapeutic neuromodulation for depression, chronic pain, addiction, anxiety and movement disorders. Several brainstem nuclei have been identified as the primary central nervous system (CNS) source of important monoaminergic ascending fibers including the noradrenergic locus coeruleus, serotonergic dorsal raphe nucleus, and dopaminergic ventral tegmental area. However, due to practical challenges to their study, there is limited data regarding their in vivo anatomic connectivity in humans. Objective To evaluate the structural connectivity of the following brainstem nuclei with limbic cortical areas: locus coeruleus, ventral tegmental area, periaqueductal grey, dorsal raphe nucleus, and nucleus tractus solitarius. Additionally, to develop a group average atlas of these limbic brainstem structures to facilitate future analyses. Methods Each nucleus was manually masked from 197 Human Connectome Project (HCP) structural MRI images using FSL software. Probabilistic tractography was performed using FSL's FMRIB Diffusion Toolbox. Connectivity with limbic cortical regions was calculated and compared between brainstem nuclei. Results were aggregated to produce a freely available MNI structural atlas of limbic brainstem structures. Results A general trend was observed for a high probability of connectivity to the amygdala, hippocampus and DLPFC with relatively lower connectivity to the orbitofrontal cortex, NAc, hippocampus and insula. The locus coeruleus and nucleus tractus solitarius demonstrated significantly greater connectivity to the DLPFC than amygdala while the periaqueductal grey, dorsal raphe nucleus, and ventral tegmental area did not demonstrate a significant difference between these two structures. Conclusion Monoaminergic and other modulatory nuclei in the brainstem project widely to cortical limbic regions. We describe the structural connectivity across the several key brainstem nuclei theorized to influence emotion, reward, and cognitive functions. An increased understanding of the anatomic basis of the brainstem's role in emotion and other reward-related processing will support targeted neuromodulatary therapies aimed at alleviating the symptoms of neuropsychiatric disorders.
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Affiliation(s)
- Simon Levinson
- Department of Neurosurgery, David Geffen School of Medicine at the University of California, Los Angeles, Los Angeles, CA, United States
- Stanford Department of Neurosurgery, Stanford University, Palo Alto CA, United States
| | - Michelle Miller
- Department of Neurosurgery, David Geffen School of Medicine at the University of California, Los Angeles, Los Angeles, CA, United States
| | - Ahmed Iftekhar
- Department of Neurosurgery, David Geffen School of Medicine at the University of California, Los Angeles, Los Angeles, CA, United States
| | - Monica Justo
- Department of Neurosurgery, David Geffen School of Medicine at the University of California, Los Angeles, Los Angeles, CA, United States
| | - Daniel Arriola
- Department of Neurosurgery, David Geffen School of Medicine at the University of California, Los Angeles, Los Angeles, CA, United States
| | - Wenxin Wei
- Department of Neurosurgery, David Geffen School of Medicine at the University of California, Los Angeles, Los Angeles, CA, United States
| | - Saman Hazany
- Department of Radiology, VA Greater Los Angeles Healthcare System, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | | | - Taylor P. Kuhn
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
| | - Andreas Horn
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt–Universität zu Berlin, Berlin, Germany
- Department of Neurology, Center for Brain Circuit Therapeutics, Harvard Medical School, Brigham and Women's Hospital, Boston, MA, United States
- Massachusetts General Hospital Neurosurgery and Center for Neurotechnology and Neurorecovery (CNTR) at MGH Neurology Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Ausaf A. Bari
- Department of Neurosurgery, David Geffen School of Medicine at the University of California, Los Angeles, Los Angeles, CA, United States
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19
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Zhang Y, Huang CC, Zhao J, Liu Y, Xia M, Wang X, Wei D, Chen Y, Liu B, Zheng Y, Wu Y, Chen T, Cheng Y, Xu X, Gong Q, Si T, Qiu S, Cheng J, Tang Y, Wang F, Qiu J, Xie P, Li L, He Y, Lin CP, Zac Lo CY. Resting-state functional connectivity of the raphe nuclei in major depressive Disorder: A Multi-site study. Neuroimage Clin 2023; 37:103359. [PMID: 36878150 PMCID: PMC9999207 DOI: 10.1016/j.nicl.2023.103359] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 11/06/2022] [Accepted: 02/20/2023] [Indexed: 03/06/2023]
Abstract
Accumulating evidence showed that major depressive disorder (MDD) is characterized by a dysfunction of serotonin neurotransmission. Raphe nuclei are the sources of most serotonergic neurons that project throughout the brain. Incorporating measurements of activity within the raphe nuclei into the analysis of connectivity characteristics may contribute to understanding how neurotransmitter synthesized centers are involved in thepathogenesisof MDD. Here, we analyzed the resting-state functional magnetic resonance imaging (RS-fMRI) dataset from 1,148 MDD patients and 1,079 healthy individuals recruited across nine centers. A seed-based analysis with the dorsal raphe and median raphe nuclei was performed to explore the functional connectivity (FC) alterations. Compared to controls, for dorsal raphe, the significantly decreased FC linking with the right precuneus and median cingulate cortex were found; for median raphe, the increased FC linking with right superior cerebellum (lobules V/VI) was found in MDD patients. In further exploratory analyzes, MDD-related connectivity alterations in dorsal and median raphe nuclei in different clinical factors remained highly similar to the main findings, indicating these abnormal connectivities are a disease-related alteration. Our study highlights a functional dysconnection pattern of raphe nuclei in MDD with multi-site big data. These findings help improve our understanding of the pathophysiology of depression and provide evidence of the theoretical foundation for the development of novel pharmacotherapies.
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Affiliation(s)
- Yajuan Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China; School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
| | - Chu-Chung Huang
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China; Shanghai Changning Mental Health Center, Shanghai, China.
| | - Jiajia Zhao
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
| | - Yuchen Liu
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
| | - Mingrui Xia
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Xiaoqin Wang
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China; Department of Psychology, Southwest University, Chongqing, China
| | - Dongtao Wei
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China; Department of Psychology, Southwest University, Chongqing, China
| | - Yuan Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Bangshan Liu
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Key Laboratory of Psychiatry and Mental Health, Hunan Medical Center for Mental Health, Changsha, Hunan, China
| | - Yanting Zheng
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yankun Wu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Taolin Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China
| | - Yuqi Cheng
- Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Xiufeng Xu
- Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China
| | - Tianmei Si
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Shijun Qiu
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yanqing Tang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Fei Wang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Jiang Qiu
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China; Department of Psychology, Southwest University, Chongqing, China
| | - Peng Xie
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China; NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China; Chongqing Key Laboratory of Neurobiology, Chongqing, China
| | - Lingjiang Li
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Key Laboratory of Psychiatry and Mental Health, Hunan Medical Center for Mental Health, Changsha, Hunan, China
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Institute for Brain Research, Beijing, China
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, 11221, Taiwan
| | | | - Chun-Yi Zac Lo
- Department of Biomedical Engineering, Chung Yuan Christian University, Taoyuan, 32023, Taiwan.
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20
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García-Gomar MG, Singh K, Cauzzo S, Bianciardi M. In vivo structural connectome of arousal and motor brainstem nuclei by 7 Tesla and 3 Tesla MRI. Hum Brain Mapp 2022; 43:4397-4421. [PMID: 35633277 PMCID: PMC9435015 DOI: 10.1002/hbm.25962] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 05/08/2022] [Accepted: 05/16/2022] [Indexed: 11/17/2022] Open
Abstract
Brainstem nuclei are key participants in the generation and maintenance of arousal, which is a basic function that modulates wakefulness/sleep, autonomic responses, affect, attention, and consciousness. Their mechanism is based on diffuse pathways ascending from the brainstem to the thalamus, hypothalamus, basal forebrain and cortex. Several arousal brainstem nuclei also participate in motor functions that allow humans to respond and interact with the surrounding through a multipathway motor network. Yet, little is known about the structural connectivity of arousal and motor brainstem nuclei in living humans. This is due to the lack of appropriate tools able to accurately visualize brainstem nuclei in conventional imaging. Using a recently developed in vivo probabilistic brainstem nuclei atlas and 7 Tesla diffusion‐weighted images (DWI), we built the structural connectome of 18 arousal and motor brainstem nuclei in living humans (n = 19). Furthermore, to investigate the translatability of our findings to standard clinical MRI, we acquired 3 Tesla DWI on the same subjects, and measured the association of the connectome across scanners. For both arousal and motor circuits, our results showed high connectivity within brainstem nuclei, and with expected subcortical and cortical structures based on animal studies. The association between 3 Tesla and 7 Tesla connectivity values was good, especially within the brainstem. The resulting structural connectome might be used as a baseline to better understand arousal and motor functions in health and disease in humans.
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Affiliation(s)
- María Guadalupe García-Gomar
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.,Escuela Nacional de Estudios Superiores, Juriquilla, Universidad Nacional Autónoma de México, Querétaro, Mexico
| | - Kavita Singh
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Simone Cauzzo
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.,Life Sciences Institute, Sant'Anna School of Advanced Studies, Pisa, Italy
| | - Marta Bianciardi
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.,Division of Sleep Medicine, Harvard University, Boston, Massachusetts, USA
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21
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Singh K, García-Gomar MG, Cauzzo S, Staab JP, Indovina I, Bianciardi M. Structural connectivity of autonomic, pain, limbic, and sensory brainstem nuclei in living humans based on 7 Tesla and 3 Tesla MRI. Hum Brain Mapp 2022; 43:3086-3112. [PMID: 35305272 PMCID: PMC9188976 DOI: 10.1002/hbm.25836] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 02/09/2022] [Accepted: 03/06/2022] [Indexed: 11/18/2022] Open
Abstract
Autonomic, pain, limbic, and sensory processes are mainly governed by the central nervous system, with brainstem nuclei as relay centers for these crucial functions. Yet, the structural connectivity of brainstem nuclei in living humans remains understudied. These tiny structures are difficult to locate using conventional in vivo MRI, and ex vivo brainstem nuclei atlases lack precise and automatic transformability to in vivo images. To fill this gap, we mapped our recently developed probabilistic brainstem nuclei atlas developed in living humans to high‐spatial resolution (1.7 mm isotropic) and diffusion weighted imaging (DWI) at 7 Tesla in 20 healthy participants. To demonstrate clinical translatability, we also acquired 3 Tesla DWI with conventional resolution (2.5 mm isotropic) in the same participants. Results showed the structural connectome of 15 autonomic, pain, limbic, and sensory (including vestibular) brainstem nuclei/nuclei complex (superior/inferior colliculi, ventral tegmental area‐parabrachial pigmented, microcellular tegmental–parabigeminal, lateral/medial parabrachial, vestibular, superior olivary, superior/inferior medullary reticular formation, viscerosensory motor, raphe magnus/pallidus/obscurus, parvicellular reticular nucleus‐alpha part), derived from probabilistic tractography computation. Through graph measure analysis, we identified network hubs and demonstrated high intercommunity communication in these nuclei. We found good (r = .5) translational capability of the 7 Tesla connectome to clinical (i.e., 3 Tesla) datasets. Furthermore, we validated the structural connectome by building diagrams of autonomic/pain/limbic connectivity, vestibular connectivity, and their interactions, and by inspecting the presence of specific links based on human and animal literature. These findings offer a baseline for studies of these brainstem nuclei and their functions in health and disease, including autonomic dysfunction, chronic pain, psychiatric, and vestibular disorders.
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Affiliation(s)
- Kavita Singh
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - María Guadalupe García-Gomar
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.,Escuela Nacional de Estudios Superiores, Juriquilla, Universidad Nacional Autónoma de México, Querétaro, Mexico
| | - Simone Cauzzo
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.,Life Sciences Institute, Sant'Anna School of Advanced Studies, Pisa, Italy.,Research Center E. Piaggio, University of Pisa, Pisa, Italy
| | - Jeffrey P Staab
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota, USA.,Department of Otorhinolaryngology - Head and Neck Surgery, Mayo Clinic, Rochester, Minnesota, USA
| | - Iole Indovina
- Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Italy.,Laboratory of Neuromotor Physiology, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Marta Bianciardi
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.,Division of Sleep Medicine, Harvard University, Boston, Massachusetts, USA
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22
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Guardia T, Geerligs L, Tsvetanov KA, Ye R, Campbell KL. The role of the arousal system in age-related differences in cortical functional network architecture. Hum Brain Mapp 2022; 43:985-997. [PMID: 34713955 PMCID: PMC8764482 DOI: 10.1002/hbm.25701] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 10/04/2021] [Accepted: 10/17/2021] [Indexed: 01/10/2023] Open
Abstract
A common finding in the aging literature is that of the brain's decreased within- and increased between-network functional connectivity. However, it remains unclear what is causing this shift in network organization with age. Given the essential role of the ascending arousal system (ARAS) in cortical activation and previous findings of disrupted ARAS functioning with age, it is possible that age differences in ARAS functioning contribute to disrupted cortical connectivity. We test this possibility here using resting state fMRI data from over 500 individuals across the lifespan from the Cambridge Center for Aging and Neuroscience (Cam-CAN) population-based cohort. Our results show that ARAS-cortical connectivity declines with age and, consistent with our expectations, significantly mediates some age-related differences in connectivity within and between association networks (specifically, within the default mode and between the default mode and salience networks). Additionally, connectivity between the ARAS and association networks predicted cognitive performance across several tasks over and above the effects of age and connectivity within the cortical networks themselves. These findings suggest that age differences in cortical connectivity may be driven, at least in part, by altered arousal signals from the brainstem and that ARAS-cortical connectivity relates to cognitive performance with age.
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Affiliation(s)
- Tiago Guardia
- Department of PsychologyBrock UniversitySt. CatharinesOntarioCanada
| | - Linda Geerligs
- Donders Institute for Brain, Cognition, and BehaviourRadboud UniversityNijmegenThe Netherlands
| | | | - Rong Ye
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
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23
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Cauzzo S, Singh K, Stauder M, García-Gomar MG, Vanello N, Passino C, Staab J, Indovina I, Bianciardi M. Functional connectome of brainstem nuclei involved in autonomic, limbic, pain and sensory processing in living humans from 7 Tesla resting state fMRI. Neuroimage 2022; 250:118925. [PMID: 35074504 DOI: 10.1016/j.neuroimage.2022.118925] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 11/24/2021] [Accepted: 01/18/2022] [Indexed: 12/13/2022] Open
Abstract
Despite remarkable advances in mapping the functional connectivity of the cortex, the functional connectivity of subcortical regions is understudied in living humans. This is the case for brainstem nuclei that control vital processes, such as autonomic, limbic, nociceptive and sensory functions. This is because of the lack of precise brainstem nuclei localization, of adequate sensitivity and resolution in the deepest brain regions, as well as of optimized processing for the brainstem. To close the gap between the cortex and the brainstem, on 20 healthy subjects, we computed a correlation-based functional connectome of 15 brainstem nuclei involved in autonomic, limbic, nociceptive, and sensory function (superior and inferior colliculi, ventral tegmental area-parabrachial pigmented nucleus complex, microcellular tegmental nucleus-prabigeminal nucleus complex, lateral and medial parabrachial nuclei, vestibular and superior olivary complex, superior and inferior medullary reticular formation, viscerosensory motor nucleus, raphe magnus, pallidus, and obscurus, and parvicellular reticular nucleus - alpha part) with the rest of the brain. Specifically, we exploited 1.1mm isotropic resolution 7 Tesla resting-state fMRI, ad-hoc coregistration and physiological noise correction strategies, and a recently developed probabilistic template of brainstem nuclei. Further, we used 2.5mm isotropic resolution resting-state fMRI data acquired on a 3 Tesla scanner to assess the translatability of our results to conventional datasets. We report highly consistent correlation coefficients across subjects, confirming available literature on autonomic, limbic, nociceptive and sensory pathways, as well as high interconnectivity within the central autonomic network and the vestibular network. Interestingly, our results showed evidence of vestibulo-autonomic interactions in line with previous work. Comparison of 7 Tesla and 3 Tesla findings showed high translatability of results to conventional settings for brainstem-cortical connectivity and good yet weaker translatability for brainstem-brainstem connectivity. The brainstem functional connectome might bring new insight in the understanding of autonomic, limbic, nociceptive and sensory function in health and disease.
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Affiliation(s)
- Simone Cauzzo
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States; Life Sciences Institute, Sant'Anna School of Advanced Studies, Pisa, Italy.
| | - Kavita Singh
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Matthew Stauder
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - María Guadalupe García-Gomar
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Nicola Vanello
- Dipartimento di Ingegneria dell'Informazione, University of Pisa, Pisa, Italy
| | - Claudio Passino
- Life Sciences Institute, Sant'Anna School of Advanced Studies, Pisa, Italy; Dipartimento di Ingegneria dell'Informazione, University of Pisa, Pisa, Italy; Fondazione Toscana Gabriele Monasterio, Pisa, Italy
| | - Jeffrey Staab
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States; Department of Otorhinolaryngology - Head and Neck Surgery, Mayo Clinic, Rochester, MN, United States
| | - Iole Indovina
- Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Italy; Laboratory of Neuromotor Physiology, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Marta Bianciardi
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States; Division of Sleep Medicine, Harvard University, Boston, MA.
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24
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Singh K, Cauzzo S, García-Gomar MG, Stauder M, Vanello N, Passino C, Bianciardi M. Functional connectome of arousal and motor brainstem nuclei in living humans by 7 Tesla resting-state fMRI. Neuroimage 2022; 249:118865. [PMID: 35031472 DOI: 10.1016/j.neuroimage.2021.118865] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 11/30/2021] [Accepted: 12/27/2021] [Indexed: 01/21/2023] Open
Abstract
Brainstem nuclei play a pivotal role in many functions, such as arousal and motor control. Nevertheless, the connectivity of arousal and motor brainstem nuclei is understudied in living humans due to the limited sensitivity and spatial resolution of conventional imaging, and to the lack of atlases of these deep tiny regions of the brain. For a holistic comprehension of sleep, arousal and associated motor processes, we investigated in 20 healthy subjects the resting-state functional connectivity of 18 arousal and motor brainstem nuclei in living humans. To do so, we used high spatial-resolution 7 Tesla resting-state fMRI, as well as a recently developed in-vivo probabilistic atlas of these nuclei in stereotactic space. Further, we verified the translatability of our brainstem connectome approach to conventional (e.g. 3 Tesla) fMRI. Arousal brainstem nuclei displayed high interconnectivity, as well as connectivity to the thalamus, hypothalamus, basal forebrain and frontal cortex, in line with animal studies and as expected for arousal regions. Motor brainstem nuclei showed expected connectivity to the cerebellum, basal ganglia and motor cortex, as well as high interconnectivity. Comparison of 3 Tesla to 7 Tesla connectivity results indicated good translatability of our brainstem connectome approach to conventional fMRI, especially for cortical and subcortical (non-brainstem) targets and to a lesser extent for brainstem targets. The functional connectome of 18 arousal and motor brainstem nuclei with the rest of the brain might provide a better understanding of arousal, sleep and accompanying motor function in living humans in health and disease.
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Affiliation(s)
- Kavita Singh
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
| | - Simone Cauzzo
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States; Institute of Life Sciences, Sant'Anna School of Advanced Studies, Pisa, Italy
| | - María Guadalupe García-Gomar
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Matthew Stauder
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Nicola Vanello
- Dipartimento di Ingegneria dell'Informazione, University of Pisa, Pisa, Italy
| | - Claudio Passino
- Institute of Life Sciences, Sant'Anna School of Advanced Studies, Pisa, Italy; Fondazione Toscana Gabriele Monasterio, Pisa, Italy
| | - Marta Bianciardi
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States; Division of Sleep Medicine, Harvard University, Boston, MA.
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25
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Demchenko I, Tassone VK, Kennedy SH, Dunlop K, Bhat V. Intrinsic Connectivity Networks of Glutamate-Mediated Antidepressant Response: A Neuroimaging Review. Front Psychiatry 2022; 13:864902. [PMID: 35722550 PMCID: PMC9199367 DOI: 10.3389/fpsyt.2022.864902] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Accepted: 04/12/2022] [Indexed: 11/23/2022] Open
Abstract
Conventional monoamine-based pharmacotherapy, considered the first-line treatment for major depressive disorder (MDD), has several challenges, including high rates of non-response. To address these challenges, preclinical and clinical studies have sought to characterize antidepressant response through monoamine-independent mechanisms. One striking example is glutamate, the brain's foremost excitatory neurotransmitter: since the 1990s, studies have consistently reported altered levels of glutamate in MDD, as well as antidepressant effects following molecular targeting of glutamatergic receptors. Therapeutically, this has led to advances in the discovery, testing, and clinical application of a wide array of glutamatergic agents, particularly ketamine. Notably, ketamine has been demonstrated to rapidly improve mood symptoms, unlike monoamine-based interventions, and the neurobiological basis behind this rapid antidepressant response is under active investigation. Advances in brain imaging techniques, including functional magnetic resonance imaging, magnetic resonance spectroscopy, and positron emission tomography, enable the identification of the brain network-based characteristics distinguishing rapid glutamatergic modulation from the effect of slow-acting conventional monoamine-based pharmacology. Here, we review brain imaging studies that examine brain connectivity features associated with rapid antidepressant response in MDD patients treated with glutamatergic pharmacotherapies in contrast with patients treated with slow-acting monoamine-based treatments. Trends in recent brain imaging literature suggest that the activity of brain regions is organized into coherent functionally distinct networks, termed intrinsic connectivity networks (ICNs). We provide an overview of major ICNs implicated in depression and explore how treatment response following glutamatergic modulation alters functional connectivity of limbic, cognitive, and executive nodes within ICNs, with well-characterized anti-anhedonic effects and the enhancement of "top-down" executive control. Alterations within and between the core ICNs could potentially exert downstream effects on the nodes within other brain networks of relevance to MDD that are structurally and functionally interconnected through glutamatergic synapses. Understanding similarities and differences in brain ICNs features underlying treatment response will positively impact the trajectory and outcomes for adults suffering from MDD and will facilitate the development of biomarkers to enable glutamate-based precision therapeutics.
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Affiliation(s)
- Ilya Demchenko
- Interventional Psychiatry Program, Mental Health and Addictions Service, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Center for Depression and Suicide Studies, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
| | - Vanessa K Tassone
- Interventional Psychiatry Program, Mental Health and Addictions Service, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
| | - Sidney H Kennedy
- Interventional Psychiatry Program, Mental Health and Addictions Service, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Center for Depression and Suicide Studies, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Keenan Research Center for Biomedical Science, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Katharine Dunlop
- Interventional Psychiatry Program, Mental Health and Addictions Service, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Center for Depression and Suicide Studies, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Keenan Research Center for Biomedical Science, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Venkat Bhat
- Interventional Psychiatry Program, Mental Health and Addictions Service, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Center for Depression and Suicide Studies, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Keenan Research Center for Biomedical Science, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
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26
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Zhang L, Wang L, Xia H, Tan Y, Li C, Fang C. Connectomic mapping of brain-spinal cord neural networks: future directions in assessing spinal cord injury at rest. Neurosci Res 2021; 176:9-17. [PMID: 34699861 DOI: 10.1016/j.neures.2021.10.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 10/20/2021] [Accepted: 10/20/2021] [Indexed: 12/01/2022]
Abstract
Following spinal cord injury (SCI), the central nervous system undergoes significant reconstruction. The dynamic change in the interaction of the brain-spinal cord axis as well as in structure-function relations plays a vital role in the determination of neurological functions, which might have important clinical implications for the treatment and its efficacy evaluation of patients with SCI. Brain connectomes based on neuroimaging data is a relatively new field of research that maps the brain's large-scale structural and functional networks at rest. Importantly, increasing evidence shows that such resting-state signals can also be seen in the spinal cord. In the present review, we focus on the reconstruction of multi-level neural circuits after SCI. We also describe how the connectome concept could further our understanding of neuroplasticity after SCI. We propose that mapping the cortical-subcortical-spinal cord networks can provide novel insights into the pathologies of SCI.
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Affiliation(s)
- Lijian Zhang
- Postdoctoral Research Station of Neurosurgery, Affiliated Hospital of Hebei University, Hebei University, China; Department of Neurosurgery, Affiliated Hospital of Hebei University, Hebei University, China; Key Laboratory of Precise Diagnosis and Treatment of Glioma in Hebei Province, Affiliated Hospital of Hebei University, Hebei University, China
| | - Luxuan Wang
- Department of Neurology, Affiliated Hospital of Hebei University, Hebei University, China
| | - Hechun Xia
- Department of Neurosurgery, General Hospital of Ningxia Medical University, Ningxia Medical University, China
| | - Yanli Tan
- Key Laboratory of Precise Diagnosis and Treatment of Glioma in Hebei Province, Affiliated Hospital of Hebei University, Hebei University, China; Department of Pathology, Affiliated Hospital of Hebei University, Hebei University, China.
| | - Chunhui Li
- Department of Neurosurgery, Affiliated Hospital of Hebei University, Hebei University, China.
| | - Chuan Fang
- Postdoctoral Research Station of Neurosurgery, Affiliated Hospital of Hebei University, Hebei University, China; Department of Neurosurgery, Affiliated Hospital of Hebei University, Hebei University, China; Key Laboratory of Precise Diagnosis and Treatment of Glioma in Hebei Province, Affiliated Hospital of Hebei University, Hebei University, China.
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27
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Singh K, García-Gomar MG, Bianciardi M. Probabilistic Atlas of the Mesencephalic Reticular Formation, Isthmic Reticular Formation, Microcellular Tegmental Nucleus, Ventral Tegmental Area Nucleus Complex, and Caudal-Rostral Linear Raphe Nucleus Complex in Living Humans from 7 Tesla Magnetic Resonance Imaging. Brain Connect 2021; 11:613-623. [PMID: 33926237 PMCID: PMC8817713 DOI: 10.1089/brain.2020.0975] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Introduction: The mesencephalic reticular formation, isthmic reticular formation, microcellular tegmental nucleus, ventral tegmental area-parabrachial pigmented nucleus complex, and caudal-rostral linear nucleus of the raphe are small brainstem regions crucially involved in arousal, sleep, and reward. Yet, these nuclei are difficult to identify with magnetic resonance imaging (MRI) of living humans. In the current work, we developed a probabilistic atlas of these brainstem nuclei in living humans, using noninvasive ultra-high-field MRI. Methods: We acquired single-subject, multicontrast (diffusion and T2-weighted), 1.1-mm isotropic resolution, 7 Tesla MRI images of 12 healthy subjects. After preprocessing and alignment to the stereotactic space, these images were used to delineate (in each subject) the nuclei of interest based on the image contrast as well as on neighboring nuclei and landmarks. Nucleus labels were averaged across subjects to yield probabilistic labels. The latter were further validated by assessment of the label inter-rater agreement, internal consistency, and volume. Results: Labels were delineated for each nucleus with good overlap across subjects. The inter-rater agreement and internal consistency were below (p < 10-8) the linear spatial imaging resolution (1.1 mm), thus validating the generated probabilistic atlas labels. The volumes of our labels did not differ from literature volumes (p < 0.05), further validating our atlas. Discussion and Conclusion: The probabilistic atlas of these five mesopontine nuclei expands current in vivo brainstem nuclei atlases and can be used as a tool to identify the location of these areas in conventional (e.g., 3 Tesla) images. This might serve to unravel the brainstem structure-to-function link and thus improve clinical outcomes. Impact statement The mesencephalic reticular formation, isthmic reticular formation, microcellular tegmental nucleus, ventral tegmental area-parabrachial pigmented nucleus complex, and caudal-rostral linear nucleus of the raphe are small brainstem regions crucially involved in arousal, sleep, and reward. In the current work, we developed a probabilistic atlas of these brainstem nuclei in living humans, using noninvasive, ultra-high-field magnetic resonance imaging. The probabilistic atlas of these five mesopontine nuclei expands current in vivo brainstem nuclei atlases and can be used as a tool to identify the location of these areas in conventional (e.g., 3 Tesla) images. This might serve to unravel the brainstem structure-to-function link and thus improve clinical outcomes.
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Affiliation(s)
- Kavita Singh
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.,Address correspondence to: Kavita Singh, Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Building 149, Room 2301, 13th Street, Charlestown, Boston, MA 02129, USA
| | - María Guadalupe García-Gomar
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Marta Bianciardi
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.,Address correspondence to: Marta Bianciardi, Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Building 149, Room 2301, 13th Street, Charlestown, Boston, MA 02129, USA
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28
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In vivo evidence of functional disconnection between brainstem monoaminergic nuclei and brain networks in multiple sclerosis. Mult Scler Relat Disord 2021; 56:103224. [PMID: 34461571 DOI: 10.1016/j.msard.2021.103224] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 08/09/2021] [Accepted: 08/22/2021] [Indexed: 11/24/2022]
Abstract
BACKGROUND brainstem monoaminergic (dopaminergic, noradrenergic, and serotoninergic) nuclei (BrMn) contain a variety of ascending neurons that diffusely project to the whole brain, crucially regulating normal brain function. BrMn are directly affected in multiple sclerosis (MS) by inflammation and neurodegeneration. Moreover, inflammation reduces the synthesis of monoamines. Aberrant monoaminergic neurotransmission contributes to the pathogenesis of MS and explains some clinical features of MS. We used resting-state functional MRI (RS-fMRI) to characterize abnormal patterns of BrMn functional connectivity (FC) in MS. METHODS BrMn FC was studied with multi-echo RS-fMRI in n = 68 relapsing-remitting MS patients and n = 39 healthy controls (HC), by performing a seed-based analysis, after producing standard space seed masks of the BrMn. FC was assessed between ventral tegmental area (VTA), locus coeruleus (LC), median raphe (MR), dorsal raphe (DR), and the rest of the brain and compared between MS patients and HC. Between-group comparisons were carried out only within the main effect observed in HC, setting p<0.05 family-wise-error corrected (FWE). RESULTS in HC, VTA displayed FC with the core regions of the default-mode network. As compared to HC, MS patients showed altered FC between VTA and posterior cingulate cortex (p<0.05FWE). LC displayed FC with core regions of the executive-control network with a reduced functional connection between LC and right prefrontal cortex in MS patients (p<0.05FWE). Raphe nuclei was functionally connected with cerebellar cortex, with a significantly lower FC between these nuclei and cerebellum in MS patients, as compared to HC (p<0.05FWE). CONCLUSIONS our study demonstrated in MS patients a functional disconnection between BrMn and cortical/subcortical efferent targets of central brain networks, possibly due to a loss or a dysregulation of BrMn neurons. This adds new information about how monoaminergic systems contribute to MS pathogenesis and suggests new potential therapeutic targets.
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29
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Adil SM, Calabrese E, Charalambous LT, Cook JJ, Rahimpour S, Atik AF, Cofer GP, Parente BA, Johnson GA, Lad SP, White LE. A high-resolution interactive atlas of the human brainstem using magnetic resonance imaging. Neuroimage 2021; 237:118135. [PMID: 33951517 PMCID: PMC8480283 DOI: 10.1016/j.neuroimage.2021.118135] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 04/15/2021] [Accepted: 04/28/2021] [Indexed: 12/30/2022] Open
Abstract
Conventional atlases of the human brainstem are limited by the inflexible, sparsely-sampled, two-dimensional nature of histology, or the low spatial resolution of conventional magnetic resonance imaging (MRI). Postmortem high-resolution MRI circumvents the challenges associated with both modalities. A single human brainstem specimen extending from the rostral diencephalon through the caudal medulla was prepared for imaging after the brain was removed from a 65-year-old male within 24 h of death. The specimen was formalin-fixed for two weeks, then rehydrated and placed in a custom-made MRI compatible tube and immersed in liquid fluorocarbon. MRI was performed in a 7-Tesla scanner with 120 unique diffusion directions. Acquisition time for anatomic and diffusion images were 14 h and 208 h, respectively. Segmentation was performed manually. Deterministic fiber tractography was done using strategically chosen regions of interest and avoidance, with manual editing using expert knowledge of human neuroanatomy. Anatomic and diffusion images were rendered with isotropic resolutions of 50 μm and 200 μm, respectively. Ninety different structures were segmented and labeled, and 11 different fiber bundles were rendered with tractography. The complete atlas is available online for interactive use at https://www.civmvoxport.vm.duke.edu/voxbase/login.php?return_url=%2Fvoxbase%2F. This atlas presents multiple contrasting datasets and selected tract reconstruction with unprecedented resolution for MR imaging of the human brainstem. There are immediate applications in neuroanatomical education, with the potential to serve future applications for neuroanatomical research and enhanced neurosurgical planning through "safe" zones of entry into the human brainstem.
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Affiliation(s)
- Syed M Adil
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, United States; Center for In Vivo Microscopy, Duke University Medical Center, Durham, NC, United States.
| | - Evan Calabrese
- University of California San Francisco, Department of Radiology & Biomedical Imaging, San Francisco, CA, United States.
| | - Lefko T Charalambous
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, United States; Center for In Vivo Microscopy, Duke University Medical Center, Durham, NC, United States.
| | - James J Cook
- Center for In Vivo Microscopy, Duke University Medical Center, Durham, NC, United States.
| | - Shervin Rahimpour
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, United States.
| | - Ahmet F Atik
- Department of Neurosurgery, Cleveland Clinic, Cleveland, OH, United States.
| | - Gary P Cofer
- Center for In Vivo Microscopy, Duke University Medical Center, Durham, NC, United States.
| | - Beth A Parente
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, United States.
| | - G Allan Johnson
- Center for In Vivo Microscopy, Duke University Medical Center, Durham, NC, United States.
| | - Shivanand P Lad
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, United States.
| | - Leonard E White
- Department of Neurology, Duke University Medical Center, Durham, NC, United States; Duke Institute for Brain Sciences, Duke University, Durham NC, United States.
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30
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Cauzzo S, Callara AL, Morelli MS, Hartwig V, Esposito F, Montanaro D, Passino C, Emdin M, Giannoni A, Vanello N. Mapping dependencies of BOLD signal change to end-tidal CO 2: linear and nonlinear modeling, and effect of physiological noise correction. J Neurosci Methods 2021; 362:109317. [PMID: 34380051 DOI: 10.1016/j.jneumeth.2021.109317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 07/28/2021] [Accepted: 08/06/2021] [Indexed: 11/30/2022]
Abstract
BACKGROUND Disentangling physiological noise and signal of interest is a major issue when evaluating BOLD-signal changes in response to breath holding. Currently-adopted approaches for retrospective noise correction are general-purpose, and have non-negligible effects in studies on hypercapnic challenges. NEW METHOD We provide a novel approach to the analysis of specific and non-specific BOLD-signal changes related to end-tidal CO2 (PETCO2) in breath-hold fMRI studies. Multiple-order nonlinear predictors for PETCO2 model a region-dependent nonlinear input-output relationship hypothesized in literature and possibly playing a crucial role in disentangling noise. We explore Retrospective Image-based Correction (RETROICOR) effects on the estimated BOLD response, applying our analysis both with and without RETROICOR and analyzing the linear and non-linear correlation between PETCO2 and RETROICOR regressors. RESULTS The RETROICOR model of noise related to respiratory activity correlated with PETCO2 both linearly and non-linearly. The correction affected the shape of the estimated BOLD response to hypercapnia but allowed to discard spurious activity in ventricles and white matter. Activation clusters were best detected using non-linear components in the BOLD response model. COMPARISON WITH EXISTING METHOD We evaluated the side-effects of standard physiological noise correction procedure, tailoring our analysis on challenging understudied brainstem and subcortical regions. Our novel approach allowed to characterize delays and non-linearities in BOLD response. CONCLUSIONS RETROICOR successfully avoided false positives, still broadly affecting the estimated non-linear BOLD responses. Non-linearities in the model better explained CO2-related BOLD signal fluctuations. The necessity to modify the standard procedure for physiological-noise correction in breath-hold studies was addressed, stating its crucial importance.
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Affiliation(s)
- Simone Cauzzo
- Institute of Life Sciences, Sant'Anna School of Advanced Studies, Pisa, Italy.
| | | | - Maria Sole Morelli
- Institute of Life Sciences, Sant'Anna School of Advanced Studies, Pisa, Italy
| | - Valentina Hartwig
- Institute of Clinical Physiology, National Research Council, Pisa, Italy
| | - Fabrizio Esposito
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Napoli, Italy
| | | | - Claudio Passino
- Institute of Life Sciences, Sant'Anna School of Advanced Studies, Pisa, Italy
| | - Michele Emdin
- Institute of Life Sciences, Sant'Anna School of Advanced Studies, Pisa, Italy
| | - Alberto Giannoni
- Institute of Life Sciences, Sant'Anna School of Advanced Studies, Pisa, Italy; Fondazione Toscana Gabriele Monasterio, Pisa, Italy
| | - Nicola Vanello
- Dipartimento di Ingegneria dell'Informazione, University of Pisa, Pisa, Italy
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31
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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.
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32
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Ishibashi K, Ishii D, Yamamoto S, Okamoto Y, Wakatabi M, Kohno Y. Asymmetry of Interhemispheric Connectivity during Rapid Movements of Right and Left Hands: A TMS-EEG Study. J Mot Behav 2021; 54:135-145. [PMID: 34180775 DOI: 10.1080/00222895.2021.1930993] [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] [Indexed: 10/21/2022]
Abstract
The interhemispheric signal propagation (ISP) obtained by electroencephalography during transcranial magnetic stimulation (TMS) allows for the assessment of the interhemispheric connectivity involved in inhibitory processes. To investigate the functional asymmetry of hemispheres during rapid movement, we compared ISP in the left and right hemispheres during rapid hand movements. In 11 healthy right-handed adults, we delivered TMS to the M1 and recorded ISP from the M1 to the contralateral hemisphere. We found that ISP from the left to right hemisphere during right-hand rapid movement was higher than ISP from the right to left hemisphere during the left-hand rapid movement. These results indicate that the left M1 strongly inhibits the right M1, and that the left hemisphere is dominant for rapid movements as well as sequential movements.
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Affiliation(s)
- Kiyoshige Ishibashi
- Department of Physical Therapy, Ibaraki Prefectural University of Health Sciences Hospital, Ibaraki, Japan.,Graduate School of Health Sciences, Ibaraki Prefectural University of Health Sciences, Ibaraki, Japan
| | - Daisuke Ishii
- Center for Medical Sciences, Ibaraki Prefectural University of Health Sciences, Ibaraki, Japan.,Department of Cognitive Behavioral Physiology, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Satoshi Yamamoto
- Department of Physical Therapy, Ibaraki Prefectural University of Health Sciences, Ibaraki, Japan
| | - Yoshitaka Okamoto
- Department of Rehabilitation, University of Tsukuba Hospital, Ibaraki, Japan
| | - Masahiro Wakatabi
- Department of Physical Therapy, Ibaraki Prefectural University of Health Sciences Hospital, Ibaraki, Japan
| | - Yutaka Kohno
- Center for Medical Sciences, Ibaraki Prefectural University of Health Sciences, Ibaraki, Japan
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33
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Carandini T, Cercignani M, Galimberti D, Scarpini E, Bozzali M. The distinct roles of monoamines in multiple sclerosis: A bridge between the immune and nervous systems? Brain Behav Immun 2021; 94:381-391. [PMID: 33662501 DOI: 10.1016/j.bbi.2021.02.030] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 02/24/2021] [Accepted: 02/25/2021] [Indexed: 12/20/2022] Open
Abstract
The monoaminergic neurotransmitters dopamine, noradrenaline, and serotonin are pivotal actors of the interplay between the nervous and the immune system due to their ability of binding to cell-receptors of both systems, crucially regulating their function within the central nervous system and the periphery. As monoamines are dysfunctional in many neurological and psychiatric diseases, they have been successfully used as pharmacological targets. Multiple sclerosis (MS) is one of the best examples of neurological disease caused by an altered interaction between the nervous and immune system and emerging evidence supports a dysregulation of monoaminergic systems in the pathogenesis of MS, secondary to both inflammation-induced reduction of monoamines' synthesis and structural damage to monoaminergic pathways within the brain. Here we review the evidence for monoamines being key mediators of neuroimmune interaction, affecting MS pathogenesis and course. Moreover, we discuss how the reduction/dysfunction of monoamines in MS may contribute to some clinical features typical of the disease, particularly fatigue and depression. Finally, we summarize different drugs targeting monoamines that are currently under evaluation for their potential efficacy to treat MS, as well as to alleviate fatigue and depression in MS.
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Affiliation(s)
- Tiziana Carandini
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
| | - Mara Cercignani
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, UK; Neuroimaging Laboratory, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Daniela Galimberti
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy; University of Milan, Dino Ferrari Center, Milan, Italy
| | - Elio Scarpini
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy; University of Milan, Dino Ferrari Center, Milan, Italy
| | - Marco Bozzali
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, UK; Rita Levi Montalcini Department of Neuroscience, University of Torino, Turin, Italy
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34
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Gottlieb E, Egorova N, Khlif MS, Khan W, Werden E, Pase MP, Howard M, Brodtmann A. Regional neurodegeneration correlates with sleep-wake dysfunction after stroke. Sleep 2021; 43:5813630. [PMID: 32249910 DOI: 10.1093/sleep/zsaa054] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2019] [Revised: 03/19/2020] [Indexed: 12/13/2022] Open
Abstract
Sleep-wake disruption is a key modifiable risk factor and sequela of stroke. The pathogenesis of poststroke sleep dysfunction is unclear. It is not known whether poststroke sleep pathology is due to focal infarction to sleep-wake hubs or to accelerated poststroke neurodegeneration in subcortical structures after stroke. We characterize the first prospective poststroke regional brain volumetric and whole-brain, fiber-specific, white matter markers of objectively measured sleep-wake dysfunction. We hypothesized that excessively long sleep (>8 h) duration and poor sleep efficiency (<80%) measured using the SenseWear Armband 3-months poststroke (n = 112) would be associated with reduced regional brain volumes of a priori-selected sleep-wake regions of interest when compared to healthy controls with optimal sleep characteristics (n = 35). We utilized a novel technique known as a whole-brain fixel-based analysis to investigate the fiber-specific white matter differences in participants with long sleep duration. Stroke participants with long sleep (n = 24) duration exhibited reduced regional volumes of the ipsilesional thalamus and contralesional amygdala when compared with controls. Poor sleep efficiency after stroke (n = 29) was associated with reduced ipsilesional thalamus, contralesional hippocampus, and contralesional amygdala volumes. Whole-brain fixel-based analyses revealed widespread macrostructural degeneration to the corticopontocerebellar tract in stroke participants with long sleep duration, with fiber reductions of up to 40%. Neurodegeneration to subcortical structures, which appear to be vulnerable to accelerated brain volume loss after stroke, may drive sleep-wake deficiencies poststroke, independent of lesion characteristics and confounding comorbidities. We discuss these findings in the context of the clinicopathological implications of sleep-related neurodegeneration and attempt to corroborate previous mechanistic-neuroanatomical findings.
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Affiliation(s)
- Elie Gottlieb
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia.,University of Melbourne, Melbourne, Victoria, Australia
| | - Natalia Egorova
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia.,University of Melbourne, Melbourne, Victoria, Australia
| | - Mohamed S Khlif
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia.,University of Melbourne, Melbourne, Victoria, Australia
| | - Wasim Khan
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia.,University of Melbourne, Melbourne, Victoria, Australia.,Department of Neuroimaging, Institute of Psychiatry, Psychology, and Neuroscience (IoPPN), King's College, London, UK
| | - Emilio Werden
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia.,University of Melbourne, Melbourne, Victoria, Australia
| | - Matthew P Pase
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia.,Harvard T.H. Chan School of Public Health, Harvard University, MA
| | - Mark Howard
- University of Melbourne, Melbourne, Victoria, Australia.,Austin Health, Heidelberg, Victoria, Australia.,Institute for Breathing and Sleep, Heidelberg, Victoria, Australia
| | - Amy Brodtmann
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia.,University of Melbourne, Melbourne, Victoria, Australia
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35
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Arsalidou M, Vijayarajah S, Sharaev M. Basal ganglia lateralization in different types of reward. Brain Imaging Behav 2021; 14:2618-2646. [PMID: 31927758 DOI: 10.1007/s11682-019-00215-3] [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] [Indexed: 12/23/2022]
Abstract
Reward processing is a fundamental human activity. The basal ganglia are recognized for their role in reward processes; however, specific roles of the different nuclei (e.g., nucleus accumbens, caudate, putamen and globus pallidus) remain unclear. Using quantitative meta-analyses we assessed whole-brain and basal ganglia specific contributions to money, erotic, and food reward processing. We analyzed data from 190 fMRI studies which reported stereotaxic coordinates of whole-brain, within-group results from healthy adult participants. Results showed concordance in overlapping and distinct cortical and sub-cortical brain regions as a function of reward type. Common to all reward types was concordance in basal ganglia nuclei, with distinct differences in hemispheric dominance and spatial extent in response to the different reward types. Food reward processing favored the right hemisphere; erotic rewards favored the right lateral globus pallidus and left caudate body. Money rewards engaged the basal ganglia bilaterally including its most anterior part, nucleus accumbens. We conclude by proposing a model of common reward processing in the basal ganglia and separate models for money, erotic, and food rewards.
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Affiliation(s)
- Marie Arsalidou
- Department of Psychology, National Research University Higher School of Economics, Moscow, Russian Federation. .,Department of Psychology, Faculty of Health, York University, Toronto, ON, Canada.
| | - Sagana Vijayarajah
- Department of Psychology, Faculty of Arts and Science, University of Toronto, Toronto, ON, Canada
| | - Maksim Sharaev
- Skolkovo Institute of Science and Technology, Moscow, Russian Federation
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36
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Edlow BL, Claassen J, Schiff ND, Greer DM. Recovery from disorders of consciousness: mechanisms, prognosis and emerging therapies. Nat Rev Neurol 2021; 17:135-156. [PMID: 33318675 PMCID: PMC7734616 DOI: 10.1038/s41582-020-00428-x] [Citation(s) in RCA: 359] [Impact Index Per Article: 89.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/23/2020] [Indexed: 12/16/2022]
Abstract
Substantial progress has been made over the past two decades in detecting, predicting and promoting recovery of consciousness in patients with disorders of consciousness (DoC) caused by severe brain injuries. Advanced neuroimaging and electrophysiological techniques have revealed new insights into the biological mechanisms underlying recovery of consciousness and have enabled the identification of preserved brain networks in patients who seem unresponsive, thus raising hope for more accurate diagnosis and prognosis. Emerging evidence suggests that covert consciousness, or cognitive motor dissociation (CMD), is present in up to 15-20% of patients with DoC and that detection of CMD in the intensive care unit can predict functional recovery at 1 year post injury. Although fundamental questions remain about which patients with DoC have the potential for recovery, novel pharmacological and electrophysiological therapies have shown the potential to reactivate injured neural networks and promote re-emergence of consciousness. In this Review, we focus on mechanisms of recovery from DoC in the acute and subacute-to-chronic stages, and we discuss recent progress in detecting and predicting recovery of consciousness. We also describe the developments in pharmacological and electrophysiological therapies that are creating new opportunities to improve the lives of patients with DoC.
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Affiliation(s)
- Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Jan Claassen
- Department of Neurology, Columbia University Medical Center, New York Presbyterian Hospital, New York, NY, USA
| | - Nicholas D Schiff
- Feil Family Brain Mind Research Institute, Weill Cornell Medical College, New York, NY, USA
| | - David M Greer
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA.
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37
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Identifying Diurnal Variability of Brain Connectivity Patterns Using Graph Theory. Brain Sci 2021; 11:brainsci11010111. [PMID: 33467070 PMCID: PMC7830976 DOI: 10.3390/brainsci11010111] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 01/11/2021] [Accepted: 01/13/2021] [Indexed: 11/18/2022] Open
Abstract
Significant differences exist in human brain functions affected by time of day and by people’s diurnal preferences (chronotypes) that are rarely considered in brain studies. In the current study, using network neuroscience and resting-state functional MRI (rs-fMRI) data, we examined the effect of both time of day and the individual’s chronotype on whole-brain network organization. In this regard, 62 participants (39 women; mean age: 23.97 ± 3.26 years; half morning- versus half evening-type) were scanned about 1 and 10 h after wake-up time for morning and evening sessions, respectively. We found evidence for a time-of-day effect on connectivity profiles but not for the effect of chronotype. Compared with the morning session, we found relatively higher small-worldness (an index that represents more efficient network organization) in the evening session, which suggests the dominance of sleep inertia over the circadian and homeostatic processes in the first hours after waking. Furthermore, local graph measures were changed, predominantly across the left hemisphere, in areas such as the precentral gyrus, putamen, inferior frontal gyrus (orbital part), inferior temporal gyrus, as well as the bilateral cerebellum. These findings show the variability of the functional neural network architecture during the day and improve our understanding of the role of time of day in resting-state functional networks.
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38
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Rushmore RJ, Wilson-Braun P, Papadimitriou G, Ng I, Rathi Y, Zhang F, O’Donnell LJ, Kubicki M, Bouix S, Yeterian E, Lemaire JJ, Calabrese E, Johnson GA, Kikinis R, Makris N. 3D Exploration of the Brainstem in 50-Micron Resolution MRI. Front Neuroanat 2020; 14:40. [PMID: 33071761 PMCID: PMC7538715 DOI: 10.3389/fnana.2020.00040] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Accepted: 06/16/2020] [Indexed: 12/25/2022] Open
Abstract
The brainstem, a structure of vital importance in mammals, is currently becoming a principal focus in cognitive, affective, and clinical neuroscience. Midbrain, pontine and medullary structures serve as the conduit for signals between the forebrain and spinal cord, are the epicenter of cranial nerve-circuits and systems, and subserve such integrative functions as consciousness, emotional processing, pain, and motivation. In this study, we parcellated the nuclear masses and the principal fiber pathways that were visible in a high-resolution T2-weighted MRI dataset of 50-micron isotropic voxels of a postmortem human brainstem. Based on this analysis, we generated a detailed map of the human brainstem. To assess the validity of our maps, we compared our observations with histological maps of traditional human brainstem atlases. Given the unique capability of MRI-based morphometric analysis in generating and preserving the morphology of 3D objects from individual 2D sections, we reconstructed the motor, sensory and integrative neural systems of the brainstem and rendered them in 3D representations. We anticipate the utilization of these maps by the neuroimaging community for applications in basic neuroscience as well as in neurology, psychiatry, and neurosurgery, due to their versatile computational nature in 2D and 3D representations in a publicly available capacity.
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Affiliation(s)
- Richard Jarrett Rushmore
- Departments of Psychiatry and Neurology, Center for Morphometric Analysis, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Psychiatric Neuroimaging Laboratory, Brigham and Women’s Hospital, Boston, MA, United States
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, United States
| | - Peter Wilson-Braun
- Departments of Psychiatry and Neurology, Center for Morphometric Analysis, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Psychiatric Neuroimaging Laboratory, Brigham and Women’s Hospital, Boston, MA, United States
| | - George Papadimitriou
- Departments of Psychiatry and Neurology, Center for Morphometric Analysis, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
| | - Isaac Ng
- Departments of Psychiatry and Neurology, Center for Morphometric Analysis, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
| | - Yogesh Rathi
- Departments of Psychiatry and Neurology, Center for Morphometric Analysis, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Psychiatric Neuroimaging Laboratory, Brigham and Women’s Hospital, Boston, MA, United States
| | - Fan Zhang
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- Laboratory for Mathematics and Imaging, Brigham and Women’s Hospital, Boston, MA, United States
- Surgical Planning Laboratory, Department of Radiology, Brigham and Women’s Hospital, Boston, MA, United States
| | - Lauren Jean O’Donnell
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- Laboratory for Mathematics and Imaging, Brigham and Women’s Hospital, Boston, MA, United States
- Surgical Planning Laboratory, Department of Radiology, Brigham and Women’s Hospital, Boston, MA, United States
| | - Marek Kubicki
- Departments of Psychiatry and Neurology, Center for Morphometric Analysis, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Psychiatric Neuroimaging Laboratory, Brigham and Women’s Hospital, Boston, MA, United States
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Sylvain Bouix
- Psychiatric Neuroimaging Laboratory, Brigham and Women’s Hospital, Boston, MA, United States
| | - Edward Yeterian
- Department of Psychology, Colby College, Waterville, ME, United States
| | - Jean-Jacques Lemaire
- Service de Neurochirurgie, CHU Clermont-Ferrand, Universite Clermont Auvergne, CNRS, SIGMA Clermont, Clermont-Ferrand, France
| | - Evan Calabrese
- Department of Radiology, Center for In Vivo Microscopy, Duke University Medical Center, Durham, NC, United States
| | - G. Allan Johnson
- Department of Radiology, Center for In Vivo Microscopy, Duke University Medical Center, Durham, NC, United States
| | - Ron Kikinis
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- Surgical Planning Laboratory, Department of Radiology, Brigham and Women’s Hospital, Boston, MA, United States
- Computer Science Department, University of Bremen, Institutsleiter, Fraunhofer MEVIS, Bremen, Germany
| | - Nikos Makris
- Departments of Psychiatry and Neurology, Center for Morphometric Analysis, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Psychiatric Neuroimaging Laboratory, Brigham and Women’s Hospital, Boston, MA, United States
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, United States
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
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39
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Matt E, Fischmeister FPS, Amini A, Robinson SD, Weber A, Foki T, Gizewski ER, Beisteiner R. Improving sensitivity, specificity, and reproducibility of individual brainstem activation. Brain Struct Funct 2019; 224:2823-2838. [PMID: 31435738 PMCID: PMC6778541 DOI: 10.1007/s00429-019-01936-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Accepted: 08/07/2019] [Indexed: 12/20/2022]
Abstract
Functional imaging of the brainstem may open new avenues for clinical diagnostics. However, for reliable assessments of brainstem activation, further efforts improving signal quality are needed. Six healthy subjects performed four repeated functional magnetic resonance imaging (fMRI) sessions on different days with jaw clenching as a motor task to elicit activation in the trigeminal motor nucleus. Functional images were acquired with a 7 T MR scanner using an optimized multiband EPI sequence. Activation measures in the trigeminal nucleus and a control region were assessed using different physiological noise correction methods (aCompCor and RETROICOR-based approaches with variable numbers of regressors) combined with cerebrospinal fluid or brainstem masking. Receiver-operating characteristic analyses accounting for sensitivity and specificity, activation overlap analyses to estimate the reproducibility between sessions, and intraclass correlation analyses (ICC) for testing reliability between subjects and sessions were used to systematically compare the physiological noise correction approaches. Masking the brainstem led to increased activation in the target ROI and resulted in higher values for the area under the curve (AUC) as a combined measure for sensitivity and specificity. With the highest values for AUC, activation overlap, and ICC, the most favorable physiological noise correction method was to control for the cerebrospinal fluid time series (aCompCor with one regressor). Brainstem motor nuclei activation can be reliably identified using high-field fMRI with optimized acquisition and processing strategies-even on single-subject level. Applying specific physiological noise correction methods improves reproducibility and reliability of brainstem activation encouraging future clinical applications.
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Affiliation(s)
- Eva Matt
- Department of Neurology, Medical University of Vienna, Spitalgasse 23, 1090, Vienna, Austria
- High Field Magnetic Resonance Centre, Medical University of Vienna, Spitalgasse 23, 1090, Vienna, Austria
| | - Florian Ph S Fischmeister
- Department of Neurology, Medical University of Vienna, Spitalgasse 23, 1090, Vienna, Austria
- High Field Magnetic Resonance Centre, Medical University of Vienna, Spitalgasse 23, 1090, Vienna, Austria
- Institute of Psychology, University of Graz, Universitätsplatz 3, 8010, Graz, Austria
| | - Ahmad Amini
- Department of Neurology, Medical University of Vienna, Spitalgasse 23, 1090, Vienna, Austria
- High Field Magnetic Resonance Centre, Medical University of Vienna, Spitalgasse 23, 1090, Vienna, Austria
| | - Simon D Robinson
- High Field Magnetic Resonance Centre, Medical University of Vienna, Spitalgasse 23, 1090, Vienna, Austria
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Spitalgasse 23, 1090, Vienna, Austria
| | - Alexandra Weber
- Department of Neurology, Medical University of Vienna, Spitalgasse 23, 1090, Vienna, Austria
- High Field Magnetic Resonance Centre, Medical University of Vienna, Spitalgasse 23, 1090, Vienna, Austria
| | - Thomas Foki
- Department of Neurology, Medical University of Vienna, Spitalgasse 23, 1090, Vienna, Austria
- High Field Magnetic Resonance Centre, Medical University of Vienna, Spitalgasse 23, 1090, Vienna, Austria
| | - Elke R Gizewski
- Department of Neuroradiology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria
| | - Roland Beisteiner
- Department of Neurology, Medical University of Vienna, Spitalgasse 23, 1090, Vienna, Austria.
- High Field Magnetic Resonance Centre, Medical University of Vienna, Spitalgasse 23, 1090, Vienna, Austria.
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40
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Bell PT, Gilat M, Shine JM, McMahon KL, Lewis SJG, Copland DA. Neural correlates of emotional valence processing in Parkinson's disease: dysfunction in the subcortex. Brain Imaging Behav 2019; 13:189-199. [PMID: 28812218 DOI: 10.1007/s11682-017-9754-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Parkinson's disease (PD) is frequently accompanied by cognitive and neuropsychiatric symptoms including impairments in affective processing. Despite this, mechanisms underlying vulnerability to deficits in affective processing remain unclear. In this study, we utilized functional Magnetic Resonance Imaging (fMRI) and an Affective Go-NoGo paradigm, to examine the neural correlates of emotional valence processing in PD. Results suggest that PD is associated with aberrant processing of emotional valence in subcortical limbic structures. Specifically, we found significant group-by-valence interactions in the ventral striatum and amygdala in response to words of differing emotional valence. Our findings contribute to a broader understanding of affective processing in PD and may provide insights into the mechanisms underlying vulnerability to mood disorders in PD.
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Affiliation(s)
- Peter T Bell
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia. .,University of Queensland Centre for Clinical Research, University of Queensland, Brisbane, QLD, Australia.
| | - Moran Gilat
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
| | - James M Shine
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
| | - Katie L McMahon
- Centre for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
| | - Simon J G Lewis
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
| | - David A Copland
- University of Queensland Centre for Clinical Research, University of Queensland, Brisbane, QLD, Australia.,School of Health & Rehabilitation Sciences, University of Queensland, Brisbane, QLD, Australia
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41
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Chevrier A, Bhaijiwala M, Lipszyc J, Cheyne D, Graham S, Schachar R. Disrupted reinforcement learning during post-error slowing in ADHD. PLoS One 2019; 14:e0206780. [PMID: 30785885 PMCID: PMC6382150 DOI: 10.1371/journal.pone.0206780] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2018] [Accepted: 01/30/2019] [Indexed: 11/19/2022] Open
Abstract
ADHD is associated with altered dopamine regulated reinforcement learning on prediction errors. Despite evidence of categorically altered error processing in ADHD, neuroimaging advances have largely investigated models of normal reinforcement learning in greater detail. Further, although reinforcement leaning critically relies on ventral striatum exerting error magnitude related thresholding influences on substantia nigra (SN) and dorsal striatum, these thresholding influences have never been identified with neuroimaging. To identify such thresholding influences, we propose that error magnitude related activities must first be separated from opposite activities in overlapping neural regions during error detection. Here we separate error detection from magnitude related adjustment (post-error slowing) during inhibition errors in the stop signal task in typically developing (TD) and ADHD adolescents using fMRI. In TD, we predicted that: 1) deactivation of dorsal striatum on error detection interrupts ongoing processing, and should be proportional to right frontoparietal response phase activity that has been observed in the SST; 2) deactivation of ventral striatum on post-error slowing exerts thresholding influences on, and should be proportional to activity in dorsal striatum. In ADHD, we predicted that ventral striatum would instead correlate with heightened amygdala responses to errors. We found deactivation of dorsal striatum on error detection correlated with response-phase activity in both groups. In TD, post-error slowing deactivation of ventral striatum correlated with activation of dorsal striatum. In ADHD, ventral striatum correlated with heightened amygdala activity. Further, heightened activities in locus coeruleus (norepinephrine), raphe nucleus (serotonin) and medial septal nuclei (acetylcholine), which all compete for control of DA, and are altered in ADHD, exhibited altered correlations with SN. All correlations in TD were replicated in healthy adults. Results in TD are consistent with dopamine regulated reinforcement learning on post-error slowing. In ADHD, results are consistent with heightened activities in the amygdala and non-dopaminergic neurotransmitter nuclei preventing reinforcement learning.
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Affiliation(s)
- Andre Chevrier
- The Hospital for Sick Children, Department of Psychiatry, Toronto, Ontario, Canada
| | - Mehereen Bhaijiwala
- The Hospital for Sick Children, Department of Psychiatry, Toronto, Ontario, Canada
| | - Jonathan Lipszyc
- University of Ottawa, Department of Family Medicine, Ottawa, Ontario, Canada
| | - Douglas Cheyne
- University of Toronto, Department of Medical Imaging, Toronto, Ontario, Canada
| | - Simon Graham
- University of Toronto, Department of Medical Biophysics, Toronto, Ontario, Canada
| | - Russell Schachar
- The Hospital for Sick Children, Department of Psychiatry, Toronto, Ontario, Canada
- * E-mail:
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42
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Sklerov M, Dayan E, Browner N. Functional neuroimaging of the central autonomic network: recent developments and clinical implications. Clin Auton Res 2018; 29:555-566. [PMID: 30470943 PMCID: PMC6858471 DOI: 10.1007/s10286-018-0577-0] [Citation(s) in RCA: 92] [Impact Index Per Article: 13.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Accepted: 11/07/2018] [Indexed: 12/08/2023]
Abstract
Purpose The central autonomic network (CAN) is an intricate system of brainstem, subcortical, and cortical structures that play key roles in the function of the autonomic nervous system. Prior to the advent of functional neuroimaging, in vivo studies of the human CAN were limited. The purpose of this review is to highlight the contribution of functional neuroimaging, specifically functional magnetic resonance imaging (fMRI), to the study of the CAN, and to discuss recent advances in this area. Additionally, we aim to emphasize exciting areas for future research. Methods We reviewed the existing literature in functional neuroimaging of the CAN. Here, we focus on fMRI research conducted in healthy human subjects, as well as research that has been done in disease states, to understand CAN function. To minimize confounding, papers examining CAN function in the context of cognition, emotion, pain, and affective disorders were excluded. Results fMRI has led to significant advances in the understanding of human CAN function. The CAN is composed of widespread brainstem and forebrain structures that are intricately connected and play key roles in reflexive and modulatory control of autonomic function. Conclusions fMRI technology has contributed extensively to current knowledge of CAN function. It holds promise to serve as a biomarker in disease states. With ongoing advancements in fMRI technology, there is great opportunity and need for future research involving the CAN.
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Affiliation(s)
- Miriam Sklerov
- Department of Neurology, University of North Carolina, 170 Manning Drive, CB# 7025, Chapel Hill, NC, 27599, USA.
| | - Eran Dayan
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina, 130 Mason Farm Road, CB# 7513, Chapel Hill, NC, 27599, USA
| | - Nina Browner
- Department of Neurology, University of North Carolina, 170 Manning Drive, CB# 7025, Chapel Hill, NC, 27599, USA
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43
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Curvilinear locus coeruleus functional connectivity trajectories over the adult lifespan: a 7T MRI study. Neurobiol Aging 2018; 69:167-176. [PMID: 29908415 DOI: 10.1016/j.neurobiolaging.2018.05.021] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2017] [Revised: 05/16/2018] [Accepted: 05/17/2018] [Indexed: 10/16/2022]
Abstract
The locus coeruleus (LC) plays a crucial role in modulating several higher order cognitive functions via its widespread projections to the entire brain. We set out to investigate the hypothesis that LC functional connectivity (FC) may fluctuate nonlinearly with age and explored its relation to memory function. To that end, 49 cognitively healthy individuals (19-74 years) underwent ultra high-resolution 7T resting-state functional magnetic resonance imaging and cognitive testing. FC patterns from the LC to regions of the isodendritic core network and cortical regions were examined using region of interest-to-region of interest analyses. Curvilinear patterns with age were observed for FC between the left LC and cortical regions and the nucleus basalis of Meynert. A linear negative association was observed between age and LC-FC and ventral tegmental area. Higher levels of FC between the LC and nucleus basalis of Meynert or ventral tegmental area were associated with lower memory performance from age of 40 years onward. Thus, different LC-FC patterns early in life can signal subtle memory deficits. Furthermore, these results highlight the importance of intact interactions between neurotransmitter systems for optimal cognitive aging.
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44
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Satpute AB, Kragel PA, Barrett LF, Wager TD, Bianciardi M. Deconstructing arousal into wakeful, autonomic and affective varieties. Neurosci Lett 2018; 693:19-28. [PMID: 29378297 DOI: 10.1016/j.neulet.2018.01.042] [Citation(s) in RCA: 58] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2017] [Revised: 01/13/2018] [Accepted: 01/22/2018] [Indexed: 12/11/2022]
Abstract
Arousal plays a central role in a wide variety of phenomena, including wakefulness, autonomic function, affect and emotion. Despite its importance, it remains unclear as to how the neural mechanisms for arousal are organized across them. In this article, we review neuroscience findings for three of the most common origins of arousal: wakeful arousal, autonomic arousal, and affective arousal. Our review makes two overarching points. First, research conducted primarily in non-human animals underscores the importance of several subcortical nuclei that contribute to various sources of arousal, motivating the need for an integrative framework. Thus, we outline an integrative neural reference space as a key first step in developing a more systematic understanding of central nervous system contributions to arousal. Second, there is a translational gap between research on non-human animals, which emphasizes subcortical nuclei, and research on humans using non-invasive neuroimaging techniques, which focuses more on gross anatomical characterizations of cortical (e.g. network architectures including the default mode network) and subcortical structures. We forecast the importance of high-field neuroimaging in bridging this gap to examine how the various networks within the neural reference space for arousal operate across varieties of arousal-related phenomena.
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Affiliation(s)
- Ajay B Satpute
- Departments of Psychology and Neuroscience, Pomona College, Claremont, CA, USA; Department of Psychology, Northeastern University, Boston, MA, USA.
| | - Philip A Kragel
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, USA; The Institute of Cognitive Science, University of Colorado Boulder, Boulder, USA
| | - Lisa Feldman Barrett
- Department of Psychology, Northeastern University, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA; Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Tor D Wager
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, USA; The Institute of Cognitive Science, University of Colorado Boulder, Boulder, USA
| | - Marta Bianciardi
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA.
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45
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Englot DJ, D'Haese PF, Konrad PE, Jacobs ML, Gore JC, Abou-Khalil BW, Morgan VL. Functional connectivity disturbances of the ascending reticular activating system in temporal lobe epilepsy. J Neurol Neurosurg Psychiatry 2017; 88. [PMID: 28630376 PMCID: PMC5634927 DOI: 10.1136/jnnp-2017-315732] [Citation(s) in RCA: 49] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
OBJECTIVE Seizures in temporal lobe epilepsy (TLE) disturb brain networks and lead to connectivity disturbances. We previously hypothesised that recurrent seizures in TLE may lead to abnormal connections involving subcortical activating structures including the ascending reticular activating system (ARAS), contributing to neocortical dysfunction and neurocognitive impairments. However, no studies of ARAS connectivity have been previously reported in patients with epilepsy. METHODS We used resting-state functional MRI recordings in 27 patients with TLE (67% right sided) and 27 matched controls to examine functional connectivity (partial correlation) between eight brainstem ARAS structures and 105 cortical/subcortical regions. ARAS nuclei included: cuneiform/subcuneiform, dorsal raphe, locus coeruleus, median raphe, parabrachial complex, pontine oralis, pedunculopontine and ventral tegmental area. Connectivity patterns were related to disease and neuropsychological parameters. RESULTS In control subjects, regions showing highest connectivity to ARAS structures included limbic structures, thalamus and certain neocortical areas, which is consistent with prior studies of ARAS projections. Overall, ARAS connectivity was significantly lower in patients with TLE than controls (p<0.05, paired t-test), particularly to neocortical regions including insular, lateral frontal, posterior temporal and opercular cortex. Diminished ARAS connectivity to these regions was related to increased frequency of consciousness-impairing seizures (p<0.01, Pearson's correlation) and was associated with impairments in verbal IQ, attention, executive function, language and visuospatial memory on neuropsychological evaluation (p<0.05, Spearman's rho or Kendell's tau-b). CONCLUSIONS Recurrent seizures in TLE are associated with disturbances in ARAS connectivity, which are part of the widespread network dysfunction that may be related to neurocognitive problems in this devastating disorder.
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Affiliation(s)
- Dario J Englot
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Pierre-Francois D'Haese
- Department of Electrical Engineering, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Peter E Konrad
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Monica L Jacobs
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - John C Gore
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Bassel W Abou-Khalil
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Victoria L Morgan
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
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Abstract
Severe brain injury may cause disruption of neural networks that sustain arousal and awareness, the two essential components of consciousness. Despite the potentially devastating immediate and long-term consequences, disorders of consciousness (DoC) are poorly understood in terms of their underlying neurobiology, the relationship between pathophysiology and recovery, and the predictors of treatment efficacy. Recent advances in neuroimaging techniques have enabled the study of network connectivity, providing great potential to improve the clinical care of patients with DoC. Initial discoveries in this field were made using positron emission tomography (PET). More recently, functional magnetic resonance (fMRI) techniques have added to our understanding of functional network dynamics in this population. Both methods have shown that whether at rest or performing a goal-oriented task, functional networks essential for processing intrinsic thoughts and extrinsic stimuli are disrupted in patients with DoC compared with healthy subjects. Atypical connectivity has been well established in the default mode network as well as in other cortical and subcortical networks that may be required for consciousness. Moreover, the degree of altered connectivity may be related to the severity of impaired consciousness, and recovery of consciousness has been shown to be associated with restoration of connectivity. In this review, we discuss PET and fMRI studies of functional and effective connectivity in patients with DoC and suggest how this field can move toward clinical application of functional network mapping in the future.
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Affiliation(s)
- Yelena G. Bodien
- Center for Neurotechnology and Neurorecovery, Department of
Neurology, Massachusetts General Hospital, Boston, MA
- Department of Physical Medicine and Rehabilitation, Spaulding
Rehabilitation Hospital, Charlestown, MA
- Harvard Medical School, Boston, MA
| | - Camille Chatelle
- Center for Neurotechnology and Neurorecovery, Department of
Neurology, Massachusetts General Hospital, Boston, MA
- Coma Science Group, GIGA-Research, University of Liège
& Neurology Department, University Hospital of Liège, Liège,
Belgium
| | - Brian L. Edlow
- Center for Neurotechnology and Neurorecovery, Department of
Neurology, Massachusetts General Hospital, Boston, MA
- Harvard Medical School, Boston, MA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts
General Hospital, Charlestown, MA
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47
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Pace-Schott EF. Exploring the brain bases of dreaming. Commentary on “Beyond the neuropsychology of dreaming: Insights into the neural basis of dreaming with new techniques of sleep recording and analysis.” Sleep Medicine Reviews. Sleep Med Rev 2017; 35:124-126. [DOI: 10.1016/j.smrv.2016.11.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2016] [Accepted: 11/17/2016] [Indexed: 10/20/2022]
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48
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Metzger FL, Auer T, Helms G, Paulus W, Frahm J, Sommer M, Neef NE. Shifted dynamic interactions between subcortical nuclei and inferior frontal gyri during response preparation in persistent developmental stuttering. Brain Struct Funct 2017; 223:165-182. [PMID: 28741037 PMCID: PMC5772149 DOI: 10.1007/s00429-017-1476-1] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2016] [Accepted: 07/07/2017] [Indexed: 11/29/2022]
Abstract
Persistent developmental stuttering is associated with basal ganglia dysfunction or dopamine dysregulation. Here, we studied whole-brain functional connectivity to test how basal ganglia structures coordinate and reorganize sensorimotor brain networks in stuttering. To this end, adults who stutter and fluent speakers (control participants) performed a response anticipation paradigm in the MRI scanner. The preparation of a manual Go/No-Go response reliably produced activity in the basal ganglia and thalamus and particularly in the substantia nigra. Strikingly, in adults who stutter, substantia nigra activity correlated positively with stuttering severity. Furthermore, functional connectivity analyses yielded altered task-related network formations in adults who stutter compared to fluent speakers. Specifically, in adults who stutter, the globus pallidus and the thalamus showed increased network synchronization with the inferior frontal gyrus. This implies dynamic shifts in the response preparation-related network organization through the basal ganglia in the context of a non-speech motor task in stuttering. Here we discuss current findings in the traditional framework of how D1 and D2 receptor activity shapes focused movement selection, thereby suggesting a disproportional involvement of the direct and the indirect pathway in stuttering.
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Affiliation(s)
- F Luise Metzger
- Department of Clinical Neurophysiology, Georg August University, Göttingen, Germany
| | - Tibor Auer
- Biomedizinische NMR Forschungs GmbH am Max-Planck-Institut für Biophysikalische Chemie, Göttingen, Germany.,MRC Cognition and Brain Sciences Unit, Cambridge, UK.,Department of Psychology, Royal Holloway, University of London, Egham, UK
| | - Gunther Helms
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | - Walter Paulus
- Department of Clinical Neurophysiology, Georg August University, Göttingen, Germany
| | - Jens Frahm
- Biomedizinische NMR Forschungs GmbH am Max-Planck-Institut für Biophysikalische Chemie, Göttingen, Germany
| | - Martin Sommer
- Department of Clinical Neurophysiology, Georg August University, Göttingen, Germany
| | - Nicole E Neef
- Department of Clinical Neurophysiology, Georg August University, Göttingen, Germany. .,Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103, Leipzig, Germany.
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49
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Niendorf T, Barth M, Kober F, Trattnig S. From ultrahigh to extreme field magnetic resonance: where physics, biology and medicine meet. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2017; 29:309-11. [PMID: 27221262 DOI: 10.1007/s10334-016-0564-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Affiliation(s)
- Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrueck Center for Molecular Medicine in the Helmholtz Association, Robert Roessle Strasse 10, 13125, Berlin, Germany.
| | - Markus Barth
- Centre for Advanced Imaging, The University of Queensland, Building 57, Research Road, St Lucia, QLD, 4072, Australia
| | - Frank Kober
- Centre de Résonance Magnétique Biologique et Médicale (CRMBM), Aix-Marseille Université, CNRS UMR7339, 13385, Marseille Cedex 05, France
| | - Siegfried Trattnig
- High Field MR Center, Department of Biomedical Imaging and Image Guided Therapy, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
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50
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Bianciardi M, Strong C, Toschi N, Edlow BL, Fischl B, Brown EN, Rosen BR, Wald LL. A probabilistic template of human mesopontine tegmental nuclei from in vivo 7T MRI. Neuroimage 2017; 170:222-230. [PMID: 28476663 DOI: 10.1016/j.neuroimage.2017.04.070] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2017] [Revised: 04/07/2017] [Accepted: 04/29/2017] [Indexed: 10/19/2022] Open
Abstract
Mesopontine tegmental nuclei such as the cuneiform, pedunculotegmental, oral pontine reticular, paramedian raphe and caudal linear raphe nuclei, are deep brain structures involved in arousal and motor function. Dysfunction of these nuclei is implicated in the pathogenesis of disorders of consciousness and sleep, as well as in neurodegenerative diseases. However, their localization in conventional neuroimages of living humans is difficult due to limited image sensitivity and contrast, and a stereotaxic probabilistic neuroimaging template of these nuclei in humans does not exist. We used semi-automatic segmentation of single-subject 1.1mm-isotropic 7T diffusion-fractional-anisotropy and T2-weighted images in healthy adults to generate an in vivo probabilistic neuroimaging structural template of these nuclei in standard stereotaxic (Montreal Neurological Institute, MNI) space. The template was validated through independent manual delineation, as well as leave-one-out validation and evaluation of nuclei volumes. This template can enable localization of five mesopontine tegmental nuclei in conventional images (e.g. 1.5T, 3T) in future studies of arousal and motor physiology (e.g. sleep, anesthesia, locomotion) and pathology (e.g. disorders of consciousness, sleep disorders, Parkinson's disease). The 7T magnetic resonance imaging procedure for single-subject delineation of these nuclei may also prove useful for future 7T studies of arousal and motor mechanisms.
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Affiliation(s)
- Marta Bianciardi
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
| | - Christian Strong
- Department of Neurosurgery, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States.
| | - Nicola Toschi
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States; Medical Physics Section, Department of Biomedicine and Prevention, Faculty of Medicine, University of Rome "Tor Vergata", Rome, Italy.
| | - Brian L Edlow
- Department of Neurology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
| | - Bruce Fischl
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States; HST/CSAIL, MIT, Cambridge, MA, United States.
| | - Emery N Brown
- Department of Anesthesia, Critical Care and Pain Medicine, MGH, Boston, MA, United States; Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, United States; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, United States; MIT-Harvard Health Science and Technology, Institute of Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, United States.
| | - Bruce R Rosen
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
| | - Lawrence L Wald
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
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