1
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Tu W, Cramer SR, Zhang N. Disparity in temporal and spatial relationships between resting-state electrophysiological and fMRI signals. RESEARCH SQUARE 2024:rs.3.rs-3251741. [PMID: 37645880 PMCID: PMC10462190 DOI: 10.21203/rs.3.rs-3251741/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Resting-state brain networks (RSNs) have been widely applied in health and disease, but the interpretation of RSNs in terms of the underlying neural activity is unclear. To address this fundamental question, we conducted simultaneous recordings of whole-brain resting-state functional magnetic resonance imaging (rsfMRI) and electrophysiology signals in two separate brain regions of rats. Our data reveal that for both recording sites, spatial maps derived from band-specific local field potential (LFP) power can account for up to 90% of the spatial variability in RSNs derived from rsfMRI signals. Surprisingly, the time series of LFP band power can only explain to a maximum of 35% of the temporal variance of the local rsfMRI time course from the same site. In addition, regressing out time series of LFP power from rsfMRI signals has minimal impact on the spatial patterns of rsfMRI-based RSNs. This disparity in the spatial and temporal relationships between resting-state electrophysiology and rsfMRI signals suggests that electrophysiological activity alone does not fully explain the effects observed in the rsfMRI signal, implying the existence of an rsfMRI component contributed by "electrophysiology-invisible" signals. These findings offer a novel perspective on our understanding of RSN interpretation.
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Affiliation(s)
- Wenyu Tu
- The Neuroscience Graduate Program, The Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, USA
| | - Samuel R Cramer
- The Neuroscience Graduate Program, The Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, USA
| | - Nanyin Zhang
- The Neuroscience Graduate Program, The Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, USA
- Department of Biomedical Engineering, Pennsylvania State University, University Park, USA
- Center for Neural Engineering, Pennsylvania State University, University Park, USA
- Center for Neurotechnology in Mental Health Research, Pennsylvania State University, University Park, USA
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2
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Kim J, Tashjian SM, Mobbs D. The human hypothalamus coordinates switching between different survival actions. PLoS Biol 2024; 22:e3002624. [PMID: 38941452 PMCID: PMC11213486 DOI: 10.1371/journal.pbio.3002624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 04/11/2024] [Indexed: 06/30/2024] Open
Abstract
Comparative research suggests that the hypothalamus is critical in switching between survival behaviors, yet it is unclear if this is the case in humans. Here, we investigate the role of the human hypothalamus in survival switching by introducing a paradigm where volunteers switch between hunting and escape in response to encounters with a virtual predator or prey. Given the small size and low tissue contrast of the hypothalamus, we used deep learning-based segmentation to identify the individual-specific hypothalamus and its subnuclei as well as an imaging sequence optimized for hypothalamic signal acquisition. Across 2 experiments, we employed computational models with identical structures to explain internal movement generation processes associated with hunting and escaping. Despite the shared structure, the models exhibited significantly different parameter values where escaping or hunting were accurately decodable just by computing the parameters of internal movement generation processes. In experiment 2, multi-voxel pattern analyses (MVPA) showed that the hypothalamus, hippocampus, and periaqueductal gray encode switching of survival behaviors while not encoding simple motor switching outside of the survival context. Furthermore, multi-voxel connectivity analyses revealed a network including the hypothalamus as encoding survival switching and how the hypothalamus is connected to other regions in this network. Finally, model-based fMRI analyses showed that a strong hypothalamic multi-voxel pattern of switching is predictive of optimal behavioral coordination after switching, especially when this signal was synchronized with the multi-voxel pattern of switching in the amygdala. Our study is the first to identify the role of the human hypothalamus in switching between survival behaviors and action organization after switching.
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Affiliation(s)
- Jaejoong Kim
- Department of Humanities and Social Sciences and Computation, California Institute of Technology, Pasadena, California, United States of America
| | - Sarah M. Tashjian
- Department of Humanities and Social Sciences and Computation, California Institute of Technology, Pasadena, California, United States of America
| | - Dean Mobbs
- Department of Humanities and Social Sciences and Computation, California Institute of Technology, Pasadena, California, United States of America
- Neural Systems Program at the California, California Institute of Technology, Pasadena, California, United States of America
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3
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Kovács P, Beloate LN, Zhang N. Perturbing cortical networks: in vivo electrophysiological consequences of pan-neuronal chemogenetic manipulations using deschloroclozapine. Front Neurosci 2024; 18:1396978. [PMID: 38726028 PMCID: PMC11079238 DOI: 10.3389/fnins.2024.1396978] [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: 03/06/2024] [Accepted: 04/12/2024] [Indexed: 05/12/2024] Open
Abstract
Introduction Chemogenetic techniques, specifically the use of Designer Receptors Exclusively Activated by Designer Drugs (DREADDs), have become invaluable tools in neuroscience research. Yet, the understanding of how Gq- and Gicoupled DREADDs alter local field potential (LFP) oscillations in vivo remains incomplete. Methods This study investigates the in vivo electrophysiological effects of DREADD actuation by deschloroclozapine, on spontaneous firing rate and LFP oscillations recorded from the anterior cingulate cortex in lightly anesthetized male rats. Results Unexpectedly, in response to the administration of deschloroclozapine, we observed inhibitory effects with pan-neuronal hM3D(Gq) stimulation, and excitatory effects with pan-neuronal hM4D(Gi) stimulation in a significant portion of neurons. These results emphasize the need to account for indirect perturbation effects at the local neuronal network level in vivo, particularly when not all neurons express the chemogenetic receptors uniformly. In the current study, for instance, the majority of cells that were transduced with both hM3D(Gq) and hM4D(Gi) were GABAergic. Moreover, we found that panneuronal cortical chemogenetic modulation can profoundly alter oscillatory neuronal activity, presenting a potential research tool or therapeutic strategy in several neuropsychiatric models and diseases. Discussion These findings help to optimize the use of chemogenetic techniques in neuroscience research and open new possibilities for novel therapeutic strategies.
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Affiliation(s)
- Péter Kovács
- Department of Biomedical Engineering, Pennsylvania State University, University Park, PA, United States
| | - Lauren N. Beloate
- Department of Biomedical Engineering, Pennsylvania State University, University Park, PA, United States
| | - Nanyin Zhang
- Department of Biomedical Engineering, Pennsylvania State University, University Park, PA, United States
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, United States
- Center for Neural Engineering, Pennsylvania State University, University Park, PA, United States
- Center for Neurotechnology in Mental Health Research, Pennsylvania State University, University Park, PA, United States
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4
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Mandino F, Vujic S, Grandjean J, Lake EMR. Where do we stand on fMRI in awake mice? Cereb Cortex 2024; 34:bhad478. [PMID: 38100331 PMCID: PMC10793583 DOI: 10.1093/cercor/bhad478] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 11/17/2023] [Accepted: 11/18/2023] [Indexed: 12/17/2023] Open
Abstract
Imaging awake animals is quickly gaining traction in neuroscience as it offers a means to eliminate the confounding effects of anesthesia, difficulties of inter-species translation (when humans are typically imaged while awake), and the inability to investigate the full range of brain and behavioral states in unconscious animals. In this systematic review, we focus on the development of awake mouse blood oxygen level dependent functional magnetic resonance imaging (fMRI). Mice are widely used in research due to their fast-breeding cycle, genetic malleability, and low cost. Functional MRI yields whole-brain coverage and can be performed on both humans and animal models making it an ideal modality for comparing study findings across species. We provide an analysis of 30 articles (years 2011-2022) identified through a systematic literature search. Our conclusions include that head-posts are favorable, acclimation training for 10-14 d is likely ample under certain conditions, stress has been poorly characterized, and more standardization is needed to accelerate progress. For context, an overview of awake rat fMRI studies is also included. We make recommendations that will benefit a wide range of neuroscience applications.
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Affiliation(s)
- Francesca Mandino
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT 06520, United States
| | - Stella Vujic
- Department of Computer Science, Yale University, New Haven, CT 06520, United States
| | - Joanes Grandjean
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Evelyn M R Lake
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT 06520, United States
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, United States
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5
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Vafaii H, Mandino F, Desrosiers-Grégoire G, O'Connor D, Markicevic M, Shen X, Ge X, Herman P, Hyder F, Papademetris X, Chakravarty M, Crair MC, Constable RT, Lake EMR, Pessoa L. Multimodal measures of spontaneous brain activity reveal both common and divergent patterns of cortical functional organization. Nat Commun 2024; 15:229. [PMID: 38172111 PMCID: PMC10764905 DOI: 10.1038/s41467-023-44363-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Accepted: 12/11/2023] [Indexed: 01/05/2024] Open
Abstract
Large-scale functional networks have been characterized in both rodent and human brains, typically by analyzing fMRI-BOLD signals. However, the relationship between fMRI-BOLD and underlying neural activity is complex and incompletely understood, which poses challenges to interpreting network organization obtained using this technique. Additionally, most work has assumed a disjoint functional network organization (i.e., brain regions belong to one and only one network). Here, we employ wide-field Ca2+ imaging simultaneously with fMRI-BOLD in mice expressing GCaMP6f in excitatory neurons. We determine cortical networks discovered by each modality using a mixed-membership algorithm to test the hypothesis that functional networks exhibit overlapping organization. We find that there is considerable network overlap (both modalities) in addition to disjoint organization. Our results show that multiple BOLD networks are detected via Ca2+ signals, and networks determined by low-frequency Ca2+ signals are only modestly more similar to BOLD networks. In addition, the principal gradient of functional connectivity is nearly identical for BOLD and Ca2+ signals. Despite similarities, important differences are also detected across modalities, such as in measures of functional connectivity strength and diversity. In conclusion, Ca2+ imaging uncovers overlapping functional cortical organization in the mouse that reflects several, but not all, properties observed with fMRI-BOLD signals.
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Affiliation(s)
- Hadi Vafaii
- Department of Physics, University of Maryland, College Park, MD, 20742, USA.
| | - Francesca Mandino
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Gabriel Desrosiers-Grégoire
- Computional Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, QC, H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, H3A 0G4, Canada
| | - David O'Connor
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA
| | - Marija Markicevic
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Xilin Shen
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Xinxin Ge
- Department of Physiology, School of Medicine, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Peter Herman
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Fahmeed Hyder
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Xenophon Papademetris
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA
- Section of Biomedical Informatics & Data Science, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Mallar Chakravarty
- Computional Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, QC, H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, H3A 0G4, Canada
- Department of Psychiatry, McGill University, Montreal, QC, H3A 0G4, Canada
- Department of Biological and Biomedical Engineering, McGill University, Montreal, QC, H3A 0G4, Canada
| | - Michael C Crair
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, 06510, USA
- Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT, 06510, USA
- Department of Ophthalmology and Visual Science, Yale School of Medicine, New Haven, CT, 06510, USA
| | - R Todd Constable
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, 06510, USA
| | - Evelyn M R Lake
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA.
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA.
| | - Luiz Pessoa
- Department of Psychology, University of Maryland, College Park, MD, 20742, USA.
- Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, 20742, USA.
- Maryland Neuroimaging Center, University of Maryland, College Park, MD, 20742, USA.
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6
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Pagani M, Gutierrez-Barragan D, de Guzman AE, Xu T, Gozzi A. Mapping and comparing fMRI connectivity networks across species. Commun Biol 2023; 6:1238. [PMID: 38062107 PMCID: PMC10703935 DOI: 10.1038/s42003-023-05629-w] [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: 08/10/2023] [Accepted: 11/22/2023] [Indexed: 12/18/2023] Open
Abstract
Technical advances in neuroimaging, notably in fMRI, have allowed distributed patterns of functional connectivity to be mapped in the human brain with increasing spatiotemporal resolution. Recent years have seen a growing interest in extending this approach to rodents and non-human primates to understand the mechanism of fMRI connectivity and complement human investigations of the functional connectome. Here, we discuss current challenges and opportunities of fMRI connectivity mapping across species. We underscore the critical importance of physiologically decoding neuroimaging measures of brain (dys)connectivity via multiscale mechanistic investigations in animals. We next highlight a set of general principles governing the organization of mammalian connectivity networks across species. These include the presence of evolutionarily conserved network systems, a dominant cortical axis of functional connectivity, and a common repertoire of topographically conserved fMRI spatiotemporal modes. We finally describe emerging approaches allowing comparisons and extrapolations of fMRI connectivity findings across species. As neuroscientists gain access to increasingly sophisticated perturbational, computational and recording tools, cross-species fMRI offers novel opportunities to investigate the large-scale organization of the mammalian brain in health and disease.
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Affiliation(s)
- Marco Pagani
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
- Autism Center, Child Mind Institute, New York, NY, USA
- IMT School for Advanced Studies, Lucca, Italy
| | - Daniel Gutierrez-Barragan
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - A Elizabeth de Guzman
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Ting Xu
- Center for the Integrative Developmental Neuroscience, Child Mind Institute, New York, NY, USA
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy.
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7
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Kim H, Zhu X, Zhao Y, Bell SA, Gehrman PR, Cohen D, Devanand DP, Goldberg TE, Lee S. Resting-state functional connectivity changes in older adults with sleep disturbance and the role of amyloid burden. Mol Psychiatry 2023; 28:4399-4406. [PMID: 37596355 PMCID: PMC10842478 DOI: 10.1038/s41380-023-02214-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 07/19/2023] [Accepted: 08/02/2023] [Indexed: 08/20/2023]
Abstract
Sleep and related disorders could lead to changes in various brain networks, but little is known about the role of amyloid β (Aβ) burden-a key Alzheimer's disease (AD) biomarker-in the relationship between sleep disturbance and altered resting state functional connectivity (rsFC) in older adults. This cross-sectional study examined the association between sleep disturbance, Aβ burden, and rsFC using a large-scale dataset from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Sample included 489 individuals (53.6% cognitively normal, 32.5% mild cognitive impairment, and 13.9% AD) who had completed sleep measures (Neuropsychiatric Inventory), PET Aβ data, and resting-state fMRI scans at baseline. Within and between rsFC of the Salience (SN), the Default Mode (DMN) and the Frontal Parietal network (FPN) were compared between participants with sleep disturbance versus without sleep disturbance. The interaction between Aβ positivity and sleep disturbance was evaluated using the linear regressions, controlling for age, diagnosis status, gender, sedatives and hypnotics use, and hypertension. Although no significant main effect of sleep disturbance was found on rsFC, a significant interaction term emerged between sleep disturbance and Aβ burden on rsFC of SN (β = 0.11, P = 0.006). Specifically, sleep disturbance was associated with SN hyperconnectivity, only with the presence of Aβ burden. Sleep disturbance may lead to altered connectivity in the SN when Aβ is accumulated in the brain. Individuals with AD pathology may be at increased risk for sleep-related aberrant rsFC; therefore, identifying and treating sleep problems in these individuals may help prevent further disease progression.
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Affiliation(s)
- Hyun Kim
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA.
- Area Brain Aging and Mental Health, New York State Psychiatric Institute, New York, NY, USA.
| | - Xi Zhu
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
- Division of Anxiety, Mood, Eating, and Related Disorders, New York State Psychiatric Institute, New York, NY, USA
| | - Yiming Zhao
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Sophie A Bell
- Area Brain Aging and Mental Health, New York State Psychiatric Institute, New York, NY, USA
- Department of Psychology, University of Virginia, Charlottesville, VA, USA
| | - Philip R Gehrman
- Department of Psychiatry, Perelman School of Medicine of the University of Pennsylvania, Philadelphia, PA, USA
- Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Daniel Cohen
- Area Brain Aging and Mental Health, New York State Psychiatric Institute, New York, NY, USA
| | - D P Devanand
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
- Area Brain Aging and Mental Health, New York State Psychiatric Institute, New York, NY, USA
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
| | - Terry E Goldberg
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
- Area Brain Aging and Mental Health, New York State Psychiatric Institute, New York, NY, USA
- Department of Anesthesiology, Columbia University Irving Medical Center, New York, NY, USA
| | - Seonjoo Lee
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
- Area Brain Aging and Mental Health, New York State Psychiatric Institute, New York, NY, USA
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA
- Division of Mental Health Data Science, New York State Psychiatric Institute, New York, NY, USA
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8
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Lee SH, Shnitko TA, Hsu LM, Broadwater MA, Sardinas M, Wang TWW, Robinson DL, Vetreno RP, Crews FT, Shih YYI. Acute alcohol induces greater dose-dependent increase in the lateral cortical network functional connectivity in adult than adolescent rats. ADDICTION NEUROSCIENCE 2023; 7:100105. [PMID: 37576436 PMCID: PMC10421607 DOI: 10.1016/j.addicn.2023.100105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Alcohol misuse and, particularly adolescent drinking, is a major public health concern. While evidence suggests that adolescent alcohol use affects frontal brain regions that are important for cognitive control over behavior little is known about how acute alcohol exposure alters large-scale brain networks and how sex and age may moderate such effects. Here, we employ a recently developed functional magnetic resonance imaging (fMRI) protocol to acquire rat brain functional connectivity data and use an established analytical pipeline to examine the effect of sex, age, and alcohol dose on connectivity within and between three major rodent brain networks: defaul mode, salience, and lateral cortical network. We identify the intra- and inter-network connectivity differences and establish moderation models to reveal significant influences of age on acute alcohol-induced lateral cortical network connectivity. Through this work, we make brain-wide isotropic fMRI data with acute alcohol challenge publicly available, with the hope to facilitate future discovery of brain regions/circuits that are causally relevant to the impact of acute alcohol use.
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Affiliation(s)
- Sung-Ho Lee
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina, Chapel Hill, NC, USA
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA
| | - Tatiana A. Shnitko
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina, Chapel Hill, NC, USA
| | - Li-Ming Hsu
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina, Chapel Hill, NC, USA
| | - Margaret A. Broadwater
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina, Chapel Hill, NC, USA
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA
| | - Mabelle Sardinas
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina, Chapel Hill, NC, USA
| | - Tzu-Wen Winnie Wang
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina, Chapel Hill, NC, USA
| | - Donita L. Robinson
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Ryan P. Vetreno
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Fulton T. Crews
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
- Department of Pharmacology, University of North Carolina, Chapel Hill, NC, USA
| | - Yen-Yu Ian Shih
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina, Chapel Hill, NC, USA
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA
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9
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Li Q, Zhang N. Sex differences in resting-state functional networks in awake rats. Brain Struct Funct 2023; 228:1411-1423. [PMID: 37261489 DOI: 10.1007/s00429-023-02657-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Accepted: 05/18/2023] [Indexed: 06/02/2023]
Abstract
Sex-related differences can be found in many brain disorders and psychophysiological traits, highlighting the importance to systematically understand the sex differences in brain function in humans and animal models. Despite emerging effort to address sex differences in behaviors and disease models in rodents, how brain-wide functional connectivity (FC) patterns differ between male and female rats remains largely unknown. Here, we used resting-state functional magnetic resonance imaging (rsfMRI) to investigate regional and systems-level differences between female and male rats. Our data show that female rats display stronger hypothalamus connectivity, whereas male rats exhibit more prominent striatum-related connectivity. At the global scale, female rats demonstrate stronger segregation within the cortical and subcortical systems, while male rats display more prominent cortico-subcortical interactions, particularly between the cortex and striatum. Taken together, these data provide a comprehensive framework of sex differences in resting-state connectivity patterns in the awake rat brain, and offer a reference for studies aiming to reveal sex-related FC differences in different animal models of brain disorders.
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Affiliation(s)
- Qiong Li
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, State College, USA
| | - Nanyin Zhang
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, State College, USA.
- Center for Neurotechnology in Mental Health Research, The Pennsylvania State University, University Park, State College, 16802, USA.
- Center for Neural Engineering, The Pennsylvania State University, University Park, State College, 16802, USA.
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10
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Poplawsky AJ, Cover C, Reddy S, Chishti HB, Vazquez A, Fukuda M. Odor-evoked layer-specific fMRI activities in the awake mouse olfactory bulb. Neuroimage 2023; 274:120121. [PMID: 37080347 PMCID: PMC10240534 DOI: 10.1016/j.neuroimage.2023.120121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 03/22/2023] [Accepted: 04/17/2023] [Indexed: 04/22/2023] Open
Abstract
Awake rodent fMRI is increasingly common over the use of anesthesia since it permits behavioral paradigms and does not confound normal brain function or neurovascular coupling. It is well established that adequate acclimation to the loud fMRI environment and head fixation reduces stress in the rodents and allows for whole brain imaging with little contamination from motion. However, it is unknown whether high-resolution fMRI with increased susceptibility to motion and lower sensitivity can measure small, but spatially discrete, activations in awake mice. To examine this, we used contrast-enhanced cerebral blood volume-weighted (CBVw) fMRI in the mouse olfactory bulb for its enhanced sensitivity and neural specificity. We determined that activation patterns in the glomerular layer to four different odors were spatially distinct and were consistent with previously established histological patterns. In addition, odor-evoked laminar activations were greatest in superficial layers that decreased with laminar depth, similar to previous observations. Interestingly, the fMRI response strengths in the granule cell layer were greater in awake mice than our previous anesthetized rat studies, suggesting that feedback neural activities were intact with wakefulness. We finally determined that fMRI signal changes to repeated odor exposure (i.e., olfactory adaptation) attenuated relatively more in the feedback granule cell layer compared to the input glomerular layer, which is consistent with prior observations. We, therefore, conclude that high-resolution CBVw fMRI can measure odor-specific activation patterns and distinguish changes in laminar activity of head and body restrained awake mice.
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Affiliation(s)
- Alexander John Poplawsky
- Department of Radiology, University of Pittsburgh, McGowan Institute for Regenerative Medicine Building, 3025 E. Carson St., rm. 159, Pittsburgh, PA, 15203, United States.
| | - Christopher Cover
- Department of Radiology, University of Pittsburgh, McGowan Institute for Regenerative Medicine Building, 3025 E. Carson St., rm. 159, Pittsburgh, PA, 15203, United States; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Sujatha Reddy
- Department of Radiology, University of Pittsburgh, McGowan Institute for Regenerative Medicine Building, 3025 E. Carson St., rm. 159, Pittsburgh, PA, 15203, United States
| | - Harris B Chishti
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Alberto Vazquez
- Department of Radiology, University of Pittsburgh, McGowan Institute for Regenerative Medicine Building, 3025 E. Carson St., rm. 159, Pittsburgh, PA, 15203, United States; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Mitsuhiro Fukuda
- Department of Radiology, University of Pittsburgh, McGowan Institute for Regenerative Medicine Building, 3025 E. Carson St., rm. 159, Pittsburgh, PA, 15203, United States
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11
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Han X, Zhu Z, Luan J, Lv P, Xin X, Zhang X, Shmuel A, Yao Z, Ma G, Zhang B. Effects of repetitive transcranial magnetic stimulation and their underlying neural mechanisms evaluated with magnetic resonance imaging-based brain connectivity network analyses. Eur J Radiol Open 2023; 10:100495. [PMID: 37396489 PMCID: PMC10311181 DOI: 10.1016/j.ejro.2023.100495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 06/03/2023] [Indexed: 07/04/2023] Open
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive brain modulation and rehabilitation technique used in patients with neuropsychiatric diseases. rTMS can structurally remodel or functionally induce activities of specific cortical regions and has developed to an important therapeutic method in such patients. Magnetic resonance imaging (MRI) provides brain data that can be used as an explanation tool for the neural mechanisms underlying rTMS effects; brain alterations related to different functions or structures may be reflected in changes in the interaction and influence of brain connections within intrinsic specific networks. In this review, we discuss the technical details of rTMS and the biological interpretation of brain networks identified with MRI analyses, comprehensively summarize the neurobiological effects in rTMS-modulated individuals, and elaborate on changes in the brain network in patients with various neuropsychiatric diseases receiving rehabilitation treatment with rTMS. We conclude that brain connectivity network analysis based on MRI can reflect alterations in functional and structural connectivity networks comprising adjacent and separated brain regions related to stimulation sites, thus reflecting the occurrence of intrinsic functional integration and neuroplasticity. Therefore, MRI is a valuable tool for understanding the neural mechanisms of rTMS and practically tailoring treatment plans for patients with neuropsychiatric diseases.
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Affiliation(s)
- Xiaowei Han
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, China
- Medical Imaging Center, Affiliated Drum Tower Hospital, Medical School of Nanjing University, China
- Nanjing University Institute of Medical Imaging and Artificial Intelligence, Nanjing University, China
| | - Zhengyang Zhu
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, China
- Medical Imaging Center, Affiliated Drum Tower Hospital, Medical School of Nanjing University, China
- Nanjing University Institute of Medical Imaging and Artificial Intelligence, Nanjing University, China
| | - Jixin Luan
- China-Japan Friendship Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, China
| | - Pin Lv
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, China
- Medical Imaging Center, Affiliated Drum Tower Hospital, Medical School of Nanjing University, China
- Nanjing University Institute of Medical Imaging and Artificial Intelligence, Nanjing University, China
| | - Xiaoyan Xin
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, China
- Medical Imaging Center, Affiliated Drum Tower Hospital, Medical School of Nanjing University, China
- Nanjing University Institute of Medical Imaging and Artificial Intelligence, Nanjing University, China
| | - Xin Zhang
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, China
- Medical Imaging Center, Affiliated Drum Tower Hospital, Medical School of Nanjing University, China
- Nanjing University Institute of Medical Imaging and Artificial Intelligence, Nanjing University, China
| | - Amir Shmuel
- Montreal Neurological Institute, McGill University, Canada
| | - Zeshan Yao
- Biomedical Engineering Institute, Jingjinji National Center of Technology Innovation, China
| | - Guolin Ma
- Department of Radiology, China-Japan Friendship Hospital, China
| | - Bing Zhang
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, China
- Medical Imaging Center, Affiliated Drum Tower Hospital, Medical School of Nanjing University, China
- Nanjing University Institute of Medical Imaging and Artificial Intelligence, Nanjing University, China
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12
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Sydnor VJ, Larsen B, Seidlitz J, Adebimpe A, Alexander-Bloch AF, Bassett DS, Bertolero MA, Cieslak M, Covitz S, Fan Y, Gur RE, Gur RC, Mackey AP, Moore TM, Roalf DR, Shinohara RT, Satterthwaite TD. Intrinsic activity development unfolds along a sensorimotor-association cortical axis in youth. Nat Neurosci 2023; 26:638-649. [PMID: 36973514 PMCID: PMC10406167 DOI: 10.1038/s41593-023-01282-y] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 02/15/2023] [Indexed: 03/29/2023]
Abstract
Animal studies of neurodevelopment have shown that recordings of intrinsic cortical activity evolve from synchronized and high amplitude to sparse and low amplitude as plasticity declines and the cortex matures. Leveraging resting-state functional MRI (fMRI) data from 1,033 youths (ages 8-23 years), we find that this stereotyped refinement of intrinsic activity occurs during human development and provides evidence for a cortical gradient of neurodevelopmental change. Declines in the amplitude of intrinsic fMRI activity were initiated heterochronously across regions and were coupled to the maturation of intracortical myelin, a developmental plasticity regulator. Spatiotemporal variability in regional developmental trajectories was organized along a hierarchical, sensorimotor-association cortical axis from ages 8 to 18. The sensorimotor-association axis furthermore captured variation in associations between youths' neighborhood environments and intrinsic fMRI activity; associations suggest that the effects of environmental disadvantage on the maturing brain diverge most across this axis during midadolescence. These results uncover a hierarchical neurodevelopmental axis and offer insight into the progression of cortical plasticity in humans.
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Affiliation(s)
- Valerie J Sydnor
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Bart Larsen
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jakob Seidlitz
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Azeez Adebimpe
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Aaron F Alexander-Bloch
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Dani S Bassett
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA
- Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA
- Department of Physics and Astronomy, College of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Santa Fe Institute, Santa Fe, NM, USA
| | - Maxwell A Bertolero
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Matthew Cieslak
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sydney Covitz
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yong Fan
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA
| | - Raquel E Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Ruben C Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Allyson P Mackey
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
| | - Tyler M Moore
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - David R Roalf
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Russell T Shinohara
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Penn-CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA.
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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13
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Li Q, Zhang N. Sex differences in resting-state functional networks in awake rats. RESEARCH SQUARE 2023:rs.3.rs-2684325. [PMID: 36993730 PMCID: PMC10055639 DOI: 10.21203/rs.3.rs-2684325/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/13/2023]
Abstract
Sex-related differences can be found in many brain disorders and psychophysiological traits, highlighting the importance to systematically understand the sex differences in brain function in humans and animal models. Despite emerging effort to address sex differences in behaviors and disease models in rodents, how brain-wide functional connectivity (FC) patterns differ between male and female rats remains largely unknown. Here we used resting-state functional magnetic resonance imaging (rsfMRI) to investigate regional and systems-level differences between female and male rats. Our data show that female rats display stronger hypothalamus connectivity, whereas male rats exhibit more prominent striatum-related connectivity. At the global scale, female rats demonstrate stronger segregation within the cortical and subcortical systems, while male rats display more prominent cortico-subcortical interactions, particularly between the cortex and striatum. Taken together, these data provide a comprehensive framework of sex differences in resting-state connectivity patterns in the awake rat brain, and offer a reference for studies aiming to reveal sex-related FC differences in different animal models of brain disorders.
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Affiliation(s)
- Qiong Li
- The Pennsylvania State University
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14
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Han X, Cramer SR, Zhang N. Deriving causal relationships in resting-state functional connectivity using SSFO-based optogenetic fMRI. J Neural Eng 2022; 19:10.1088/1741-2552/ac9d66. [PMID: 36301683 PMCID: PMC9681600 DOI: 10.1088/1741-2552/ac9d66] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 10/25/2022] [Indexed: 01/07/2023]
Abstract
Objective.The brain network has been extensively studied as a collection of brain regions that are functionally inter-connected. However, the study of the causal relationship in brain-wide functional connectivity, which is critical to the brain function, remains challenging. We aim to examine the feasibility of using (SSFO)-based optogenetic functional magnetic resonance imaging to infer the causal relationship (i.e. directional information) in the brain network.Approach.We combined SSFO-based optogenetics with fMRI in a resting-state rodent model to study how a local increase of excitability affects brain-wide neural activity and resting-state functional connectivity (RSFC). We incorporated Pearson's correlation and partial correlation analyses in a graphic model to derive the directional information in connections exhibiting RSFC modulations.Main results. When the dentate gyrus (DG) was sensitized by SSFO activation, we found significantly changed activity and connectivity in several brain regions associated with the DG, particularly in the medial prefrontal cortex Our causal inference result shows an 84%-100% accuracy rate compared to the directional information based on anatomical tracing data.Significance.This study establishes a system to investigate the relationship between local region activity and RSFC modulation, and provides a way to analyze the underlying causal relationship between brain regions.
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Affiliation(s)
- Xu Han
- Graduate Program in Molecular, Cellular, and Integrative Biosciences, The Pennsylvania State University, University Park, USA
| | - Samuel R. Cramer
- The Neuroscience Graduate Program, The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, USA
| | - Nanyin Zhang
- Graduate Program in Molecular, Cellular, and Integrative Biosciences, The Pennsylvania State University, University Park, USA
- The Neuroscience Graduate Program, The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, USA
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, USA
- Center for Neurotechnology in Mental Health Research, The Pennsylvania State University, University Park, USA 16802
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15
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Weiss C, Bertolino N, Procissi D, Disterhoft JF. Brain activity studied with magnetic resonance imaging in awake rabbits. FRONTIERS IN NEUROIMAGING 2022; 1:965529. [PMID: 37555136 PMCID: PMC10406271 DOI: 10.3389/fnimg.2022.965529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 08/08/2022] [Indexed: 08/10/2023]
Abstract
We reviewed fMRI experiments from our previous work in conscious rabbits, an experimental preparation that is advantageous for measuring brain activation that is free of anesthetic modulation and which can address questions in a variety of areas in sensory, cognitive, and pharmacological neuroscience research. Rabbits do not struggle or move for several hours while sitting with their heads restrained inside the horizontal bore of a magnet. This greatly reduces movement artifacts in magnetic resonance (MR) images in comparison to other experimental animals such as rodents, cats, and monkeys. We have been able to acquire high-resolution anatomic as well as functional images that are free of movement artifacts during several hours of restraint. Results from conscious rabbit fMRI studies with whisker stimulation are provided to illustrate the feasibility of this conscious animal model for functional MRI and the reproducibility of data gained with it.
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Affiliation(s)
- Craig Weiss
- Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
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16
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Beloate LN, Zhang N. Connecting the dots between cell populations, whole-brain activity, and behavior. NEUROPHOTONICS 2022; 9:032208. [PMID: 35350137 PMCID: PMC8957372 DOI: 10.1117/1.nph.9.3.032208] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Accepted: 02/25/2022] [Indexed: 06/14/2023]
Abstract
Simultaneously manipulating and monitoring both microscopic and macroscopic brain activity in vivo and identifying the linkage to behavior are powerful tools in neuroscience research. These capabilities have been realized with the recent technical advances of optogenetics and its combination with fMRI, here termed "opto-fMRI." Opto-fMRI allows for targeted brain region-, cell-type-, or projection-specific manipulation and targeted Ca 2 + activity measurement to be linked with global brain signaling and behavior. We cover the history, technical advances, applications, and important considerations of opto-fMRI in anesthetized and awake rodents and the future directions of the combined techniques in neuroscience and neuroimaging.
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Affiliation(s)
- Lauren N. Beloate
- Pennsylvania State University, Department of Biomedical Engineering, Pennsylvania, United States
| | - Nanyin Zhang
- Pennsylvania State University, Department of Biomedical Engineering, Pennsylvania, United States
- Pennsylvania State University, Huck Institutes of the Life Sciences, Pennsylvania, United States
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17
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Cleppien D, Aedo-Jury F, Stroh A. Beyond correlation: functional OPTO-MAgnetic Integration Concept (OPTOMAIC) to reveal the brain-wide signature of local neuronal signals-of-interest. NEUROPHOTONICS 2022; 9:032213. [PMID: 35813935 PMCID: PMC9259002 DOI: 10.1117/1.nph.9.3.032213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 06/01/2022] [Indexed: 06/15/2023]
Abstract
Significance: Due to the vascular origin of the fMRI signal, the spatiotemporally precise interpretation of the blood oxygen level-dependent (BOLD) response as brain-wide correlate of neuronal activity is limited. Optical fiber-based neuronal calcium recordings provide a specific and temporally highly resolved signal yet lacking brain-wide coverage. The cross-modal integration of both modalities holds the potential for unique synergies. Aim: The OPTO-MAgnetic Integration Concept (OPTOMAIC) extracts the very fraction of the BOLD response that reacts to optically recorded neuronal signals-of-interest. Approach and Results: First, OPTOMAIC identifies the trials containing neuronal signal-of-interest (SoI) in the optical recordings. The long duration of the BOLD response is considered by calculating and thresholding neuronal interevent intervals. The resulting optical regression vector is probed for a positive BOLD response with single-event and single-voxel resolution, generating a BOLD response matrix containing only those events and voxels with both a neuronal SoI and a positive fMRI signal increase. Last, the onset of the BOLD response is being quantified, representing the section of the BOLD response most reliably reporting at least components of the neuronal signal. Conclusions: The seven OPTOMAIC steps result in a brain-wide BOLD signature reflecting the underlying neuronal SoI with utmost cross-modal integration depth and taking full advantage of the specific strengths of each method.
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Affiliation(s)
- Dirk Cleppien
- Leibniz Institute for Resilience Research, Mainz, Germany
| | | | - Albrecht Stroh
- Leibniz Institute for Resilience Research, Mainz, Germany
- Institute of Pathophysiology, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
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