1
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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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2
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Khan AF, Zhang F, Shou G, Yuan H, Ding L. Transient brain-wide coactivations and structured transitions revealed in hemodynamic imaging data. Neuroimage 2022; 260:119460. [PMID: 35868615 PMCID: PMC9472706 DOI: 10.1016/j.neuroimage.2022.119460] [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: 12/14/2021] [Revised: 06/28/2022] [Accepted: 07/08/2022] [Indexed: 11/17/2022] Open
Abstract
Brain-wide patterns in resting human brains, as either structured functional connectivity (FC) or recurring brain states, have been widely studied in the neuroimaging literature. In particular, resting-state FCs estimated over windowed timeframe neuroimaging data from sub-minutes to minutes using correlation or blind source separation techniques have reported many brain-wide patterns of significant behavioral and disease correlates. The present pilot study utilized a novel whole-head cap-based high-density diffuse optical tomography (DOT) technology, together with data-driven analysis methods, to investigate recurring transient brain-wide patterns in spontaneous fluctuations of hemodynamic signals at the resolution of single timeframes from thirteen healthy adults in resting conditions. Our results report that a small number, i.e., six, of brain-wide coactivation patterns (CAPs) describe major spatiotemporal dynamics of spontaneous hemodynamic signals recorded by DOT. These CAPs represent recurring brain states, showing spatial topographies of hemispheric symmetry, and exhibit highly anticorrelated pairs. Moreover, a structured transition pattern among the six brain states is identified, where two CAPs with anterior-posterior spatial patterns are significantly involved in transitions among all brain states. Our results further elucidate two brain states of global positive and negative patterns, indicating transient neuronal coactivations and co-deactivations, respectively, over the entire cortex. We demonstrate that these two brain states are responsible for the generation of a subset of peaks and troughs in global signals (GS), supporting the recent reports on neuronal relevance of hemodynamic GS. Collectively, our results suggest that transient neuronal events (i.e., CAPs), global brain activity, and brain-wide structured transitions co-exist in humans and these phenomena are closely related, which extend the observations of similar neuronal events recently reported in animal hemodynamic data. Future studies on the quantitative relationship among these transient events and their relationships to windowed FCs along with larger sample size are needed to understand their changes with behaviors and diseased conditions.
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Affiliation(s)
- Ali Fahim Khan
- Stephenson School of Biomedical Engineering, University of Oklahoma, 110 W. Boyd St. DEH room 150, Norman, OK 73019, USA
| | - Fan Zhang
- Stephenson School of Biomedical Engineering, University of Oklahoma, 110 W. Boyd St. DEH room 150, Norman, OK 73019, USA
| | - Guofa Shou
- Stephenson School of Biomedical Engineering, University of Oklahoma, 110 W. Boyd St. DEH room 150, Norman, OK 73019, USA
| | - Han Yuan
- Stephenson School of Biomedical Engineering, University of Oklahoma, 110 W. Boyd St. DEH room 150, Norman, OK 73019, USA; Institute for Biomedical Engineering, Science, and Technology, University of Oklahoma, Norman, USA
| | - Lei Ding
- Stephenson School of Biomedical Engineering, University of Oklahoma, 110 W. Boyd St. DEH room 150, Norman, OK 73019, USA; Institute for Biomedical Engineering, Science, and Technology, University of Oklahoma, Norman, USA.
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3
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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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4
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Lake EMR, Higley MJ. Building bridges: simultaneous multimodal neuroimaging approaches for exploring the organization of brain networks. NEUROPHOTONICS 2022; 9:032202. [PMID: 36159712 PMCID: PMC9506627 DOI: 10.1117/1.nph.9.3.032202] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 09/07/2022] [Indexed: 06/16/2023]
Abstract
Brain organization is evident across spatiotemporal scales as well as from structural and functional data. Yet, translating from micro- to macroscale (vice versa) as well as between different measures is difficult. Reconciling disparate observations from different modes is challenging because each specializes within a restricted spatiotemporal milieu, usually has bounded organ coverage, and has access to different contrasts. True intersubject biological heterogeneity, variation in experiment implementation (e.g., use of anesthesia), and true moment-to-moment variations in brain activity (maybe attributable to different brain states) also contribute to variability between studies. Ultimately, for a deeper and more actionable understanding of brain organization, an ability to translate across scales, measures, and species is needed. Simultaneous multimodal methods can contribute to bettering this understanding. We consider four modes, three optically based: multiphoton imaging, single-photon (wide-field) imaging, and fiber photometry, as well as magnetic resonance imaging. We discuss each mode as well as their pairwise combinations with regard to the definition and study of brain networks.
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Affiliation(s)
- Evelyn M. R. Lake
- Yale School of Medicine, Department of Radiology and Biomedical Imaging, New Haven, Connecticut, United States
| | - Michael J. Higley
- Yale School of Medicine, Departments of Neuroscience and Psychiatry, New Haven, Connecticut, United States
- Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, Connecticut, United States
- Program in Cellular Neuroscience, Neurodegeneration, and Repair, New Haven, Connecticut, United States
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5
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Xu N, LaGrow TJ, Anumba N, Lee A, Zhang X, Yousefi B, Bassil Y, Clavijo GP, Khalilzad Sharghi V, Maltbie E, Meyer-Baese L, Nezafati M, Pan WJ, Keilholz S. Functional Connectivity of the Brain Across Rodents and Humans. Front Neurosci 2022; 16:816331. [PMID: 35350561 PMCID: PMC8957796 DOI: 10.3389/fnins.2022.816331] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Accepted: 02/14/2022] [Indexed: 12/15/2022] Open
Abstract
Resting-state functional magnetic resonance imaging (rs-fMRI), which measures the spontaneous fluctuations in the blood oxygen level-dependent (BOLD) signal, is increasingly utilized for the investigation of the brain's physiological and pathological functional activity. Rodents, as a typical animal model in neuroscience, play an important role in the studies that examine the neuronal processes that underpin the spontaneous fluctuations in the BOLD signal and the functional connectivity that results. Translating this knowledge from rodents to humans requires a basic knowledge of the similarities and differences across species in terms of both the BOLD signal fluctuations and the resulting functional connectivity. This review begins by examining similarities and differences in anatomical features, acquisition parameters, and preprocessing techniques, as factors that contribute to functional connectivity. Homologous functional networks are compared across species, and aspects of the BOLD fluctuations such as the topography of the global signal and the relationship between structural and functional connectivity are examined. Time-varying features of functional connectivity, obtained by sliding windowed approaches, quasi-periodic patterns, and coactivation patterns, are compared across species. Applications demonstrating the use of rs-fMRI as a translational tool for cross-species analysis are discussed, with an emphasis on neurological and psychiatric disorders. Finally, open questions are presented to encapsulate the future direction of the field.
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Affiliation(s)
- Nan Xu
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Theodore J. LaGrow
- Electrical and Computer Engineering, Georgia Tech, Atlanta, GA, United States
| | - Nmachi Anumba
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Azalea Lee
- Neuroscience Graduate Program, Emory University, Atlanta, GA, United States
- Emory University School of Medicine, Atlanta, GA, United States
| | - Xiaodi Zhang
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Behnaz Yousefi
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Yasmine Bassil
- Neuroscience Graduate Program, Emory University, Atlanta, GA, United States
| | - Gloria P. Clavijo
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | | | - Eric Maltbie
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Lisa Meyer-Baese
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Maysam Nezafati
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Wen-Ju Pan
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Shella Keilholz
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
- Neuroscience Graduate Program, Emory University, Atlanta, GA, United States
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6
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Ma Z, Zhang Q, Tu W, Zhang N. Gaining insight into the neural basis of resting-state fMRI signal. Neuroimage 2022; 250:118960. [PMID: 35121182 PMCID: PMC8935501 DOI: 10.1016/j.neuroimage.2022.118960] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 01/30/2022] [Accepted: 01/31/2022] [Indexed: 01/01/2023] Open
Abstract
The blood oxygenation level-dependent (BOLD)-based resting-state functional magnetic resonance imaging (rsfMRI) has been widely used as a non-invasive tool to map brain-wide connectivity architecture. However, the neural basis underpinning the resting-state BOLD signal remains elusive. In this study, we combined simultaneous calcium-based fiber photometry with rsfMRI in awake animals to examine the relationship of the BOLD signal and spiking activity at the resting state. We observed robust couplings between calcium and BOLD signals in the dorsal hippocampus as well as other distributed areas in the default mode network (DMN), suggesting that the calcium measurement can reliably predict the rsfMRI signal. In addition, using the calcium signal recorded as the ground truth, we assessed the impacts of different rsfMRI data preprocessing pipelines on functional connectivity mapping. Overall, our results provide important evidence suggesting that spiking activity measured by the calcium signal plays a key role in the neural mechanism of resting-state BOLD signal.
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Affiliation(s)
- Zilu Ma
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, USA
| | - Qingqing Zhang
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, USA
| | - Wenyu Tu
- The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, USA
| | - Nanyin Zhang
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, USA; The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, USA.
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7
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Russo G, Helluy X, Behroozi M, Manahan-Vaughan D. Gradual Restraint Habituation for Awake Functional Magnetic Resonance Imaging Combined With a Sparse Imaging Paradigm Reduces Motion Artifacts and Stress Levels in Rodents. Front Neurosci 2022; 15:805679. [PMID: 34992520 PMCID: PMC8724036 DOI: 10.3389/fnins.2021.805679] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Accepted: 11/30/2021] [Indexed: 02/06/2023] Open
Abstract
Functional magnetic resonance imaging, as a non-invasive technique, offers unique opportunities to assess brain function and connectivity under a broad range of applications, ranging from passive sensory stimulation to high-level cognitive abilities, in awake animals. This approach is confounded, however, by the fact that physical restraint and loud unpredictable acoustic noise must inevitably accompany fMRI recordings. These factors induce marked stress in rodents, and stress-related elevations of corticosterone levels are known to alter information processing and cognition in the rodent. Here, we propose a habituation strategy that spans specific stages of adaptation to restraint, MRI noise, and confinement stress in awake rats and circumvents the need for surgical head restraint. This habituation protocol results in stress levels during awake fMRI that do not differ from pre-handling levels and enables stable image acquisition with very low motion artifacts. For this, rats were gradually trained over a period of three weeks and eighteen training sessions. Stress levels were assessed by analysis of fecal corticosterone metabolite levels and breathing rates. We observed significant drops in stress levels to below pre-handling levels at the end of the habituation procedure. During fMRI in awake rats, after the conclusion of habituation and using a non-invasive head-fixation device, breathing was stable and head motion artifacts were minimal. A task-based fMRI experiment, using acoustic stimulation, conducted 2 days after the end of habituation, resulted in precise whole brain mapping of BOLD signals in the brain, with clear delineation of the expected auditory-related structures. The active discrimination by the animals of the acoustic stimuli from the backdrop of scanner noise was corroborated by significant increases in BOLD signals in the thalamus and reticular formation. Taken together, these data show that effective habituation to awake fMRI can be achieved by gradual and incremental acclimatization to the experimental conditions. Subsequent BOLD recordings, even during superimposed acoustic stimulation, reflect low stress-levels, low motion and a corresponding high-quality image acquisition. Furthermore, BOLD signals obtained during fMRI indicate that effective habituation facilitates selective attention to sensory stimuli that can in turn support the discrimination of cognitive processes in the absence of stress confounds.
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Affiliation(s)
- Gabriele Russo
- Department of Neurophysiology, Medical Faculty, Ruhr University Bochum, Bochum, Germany.,International Graduate School of Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Xavier Helluy
- Department of Neurophysiology, Medical Faculty, Ruhr University Bochum, Bochum, Germany.,Department of Biopsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Bochum, Germany
| | - Mehdi Behroozi
- Department of Biopsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Bochum, Germany
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8
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Lee SH, Broadwater MA, Ban W, Wang TWW, Kim HJ, Dumas JS, Vetreno RP, Herman MA, Morrow AL, Besheer J, Kash TL, Boettiger CA, Robinson DL, Crews FT, Shih YYI. An isotropic EPI database and analytical pipelines for rat brain resting-state fMRI. Neuroimage 2021; 243:118541. [PMID: 34478824 PMCID: PMC8561231 DOI: 10.1016/j.neuroimage.2021.118541] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 08/08/2021] [Accepted: 08/30/2021] [Indexed: 12/24/2022] Open
Abstract
Resting-state functional magnetic resonance imaging (fMRI) has drastically expanded the scope of brain research by advancing our knowledge about the topologies, dynamics, and interspecies translatability of functional brain networks. Several databases have been developed and shared in accordance with recent key initiatives in the rodent fMRI community to enhance the transparency, reproducibility, and interpretability of data acquired at various sites. Despite these pioneering efforts, one notable challenge preventing efficient standardization in the field is the customary choice of anisotropic echo planar imaging (EPI) schemes with limited spatial coverage. Imaging with anisotropic resolution and/or reduced brain coverage has significant shortcomings including reduced registration accuracy and increased deviation in brain feature detection. Here we proposed a high-spatial-resolution (0.4 mm), isotropic, whole-brain EPI protocol for the rat brain using a horizontal slicing scheme that can maintain a functionally relevant repetition time (TR), avoid high gradient duty cycles, and offer unequivocal whole-brain coverage. Using this protocol, we acquired resting-state EPI fMRI data from 87 healthy rats under the widely used dexmedetomidine sedation supplemented with low-dose isoflurane on a 9.4 T MRI system. We developed an EPI template that closely approximates the Paxinos and Watson's rat brain coordinate system and demonstrated its ability to improve the accuracy of group-level approaches and streamline fMRI data pre-processing. Using this database, we employed a multi-scale dictionary-learning approach to identify reliable spatiotemporal features representing rat brain intrinsic activity. Subsequently, we performed k-means clustering on those features to obtain spatially discrete, functional regions of interest (ROIs). Using Euclidean-based hierarchical clustering and modularity-based partitioning, we identified the topological organizations of the rat brain. Additionally, the identified group-level FC network appeared robust across strains and sexes. The "triple-network" commonly adapted in human fMRI were resembled in the rat brain. Through this work, we disseminate raw and pre-processed isotropic EPI data, a rat brain EPI template, as well as identified functional ROIs and networks in standardized rat brain coordinates. We also make our analytical pipelines and scripts publicly available, with the hope of facilitating rat brain resting-state fMRI study standardization.
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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,Corresponding authors at: Center for Animal MRI, 125 Mason Farm Road, CB# 7513, University of North Carolina, Chapel Hill, NC 27599, USA. (S.-H. Lee), (Y.-Y.I. Shih)
| | - 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
| | - Woomi Ban
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA,Biomedical Research Imaging Center, 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
| | - Hyeon-Joong Kim
- 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
| | - Jaiden Seongmi Dumas
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA,Department of Neurology, University of North Carolina, Chapel Hill, NC, USA,Department of Quantitative Biology, 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 Pharmacology, University of North Carolina, Chapel Hill, NC, USA
| | - Melissa A. Herman
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Pharmacology, University of North Carolina, Chapel Hill, NC, USA
| | - A. Leslie Morrow
- 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
| | - Joyce Besheer
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Thomas L. Kash
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Pharmacology, University of North Carolina, Chapel Hill, NC, USA
| | - Charlotte A. Boettiger
- 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 Psychology and Neuroscience, 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
| | - 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,Corresponding authors at: Center for Animal MRI, 125 Mason Farm Road, CB# 7513, University of North Carolina, Chapel Hill, NC 27599, USA. (S.-H. Lee), (Y.-Y.I. Shih)
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9
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Wang Y, DeMarco EM, Witzel LS, Keighron JD. A selected review of recent advances in the study of neuronal circuits using fiber photometry. Pharmacol Biochem Behav 2021; 201:173113. [PMID: 33444597 DOI: 10.1016/j.pbb.2021.173113] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 12/17/2020] [Accepted: 01/06/2021] [Indexed: 12/21/2022]
Abstract
To understand the correlation between animal behaviors and the underlying neuronal circuits, it is important to monitor and record neurotransmission in the brain of freely moving animals. With the development of fiber photometry, based on genetically encoded biosensors, and novel electrochemical biosensors, it is possible to measure some key neuronal transmission events specific to cell types or neurotransmitters of interest with high temporospatial resolution. This review discusses the recent advances and achievements of these two techniques in the study of neurotransmission in animal models and how they can be used to complement other techniques in the neuroscientist's toolbox.
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Affiliation(s)
- Yuanmo Wang
- Department of Chemistry and Chemical Engineering, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden
| | - Emily M DeMarco
- Department of Physiology, University of Maryland School of Medicine, Baltimore, MD 21201, USA; Program in Neuroscience, University of Maryland, Baltimore, MD 21201, USA
| | - Lisa Sophia Witzel
- Department of Biological and Chemical Sciences, New York Institute of Technology, Old Westbury, NY 11568, USA
| | - Jacqueline D Keighron
- Department of Biological and Chemical Sciences, New York Institute of Technology, Old Westbury, NY 11568, USA.
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10
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Marshall E, Nomi JS, Dirks B, Romero C, Kupis L, Chang C, Uddin LQ. Coactivation pattern analysis reveals altered salience network dynamics in children with autism spectrum disorder. Netw Neurosci 2020; 4:1219-1234. [PMID: 33409437 PMCID: PMC7781614 DOI: 10.1162/netn_a_00163] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Accepted: 07/29/2020] [Indexed: 12/17/2022] Open
Abstract
Brain connectivity studies of autism spectrum disorder (ASD) have historically relied on static measures of functional connectivity. Recent work has focused on identifying transient configurations of brain activity, yet several open questions remain regarding the nature of specific brain network dynamics in ASD. We used a dynamic coactivation pattern (CAP) approach to investigate the salience/midcingulo-insular (M-CIN) network, a locus of dysfunction in ASD, in a large multisite resting-state fMRI dataset collected from 172 children (ages 6–13 years; n = 75 ASD; n = 138 male). Following brain parcellation by using independent component analysis, dynamic CAP analyses were conducted and k-means clustering was used to determine transient activation patterns of the M-CIN. The frequency of occurrence of different dynamic CAP brain states was then compared between children with ASD and typically developing (TD) children. Dynamic brain configurations characterized by coactivation of the M-CIN with central executive/lateral fronto-parietal and default mode/medial fronto-parietal networks appeared less frequently in children with ASD compared with TD children. This study highlights the utility of time-varying approaches for studying altered M-CIN function in prevalent neurodevelopmental disorders. We speculate that altered M-CIN dynamics in ASD may underlie the inflexible behaviors commonly observed in children with the disorder. Autism spectrum disorder (ASD) is a neurodevelopmental disorder associated with altered patterns of functional brain connectivity. Little is currently known about how moment-to-moment brain dynamics differ in children with ASD and typically developing (TD) children. Altered functional integrity of the midcingulo-insular network (M-CIN) has been implicated in the neurobiology of ASD. Here we use a novel coactivation analysis approach applied to a large sample of resting-state fMRI data collected from children with ASD and TD children to demonstrate altered patterns of M-CIN dynamics in children with the disorder. We speculate that these atypical patterns of brain dynamics may underlie behavioral inflexibility in ASD.
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Affiliation(s)
- Emily Marshall
- Department of Psychology, University of Miami, Coral Gables, FL, USA
| | - Jason S Nomi
- Department of Psychology, University of Miami, Coral Gables, FL, USA
| | - Bryce Dirks
- Department of Psychology, University of Miami, Coral Gables, FL, USA
| | - Celia Romero
- Department of Psychology, University of Miami, Coral Gables, FL, USA
| | - Lauren Kupis
- Department of Psychology, University of Miami, Coral Gables, FL, USA
| | - Catie Chang
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Lucina Q Uddin
- Department of Psychology, University of Miami, Coral Gables, FL, USA
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11
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Uddin LQ. Bring the Noise: Reconceptualizing Spontaneous Neural Activity. Trends Cogn Sci 2020; 24:734-746. [PMID: 32600967 PMCID: PMC7429348 DOI: 10.1016/j.tics.2020.06.003] [Citation(s) in RCA: 69] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Revised: 06/04/2020] [Accepted: 06/05/2020] [Indexed: 12/17/2022]
Abstract
Definitions of what constitutes the 'signal of interest' in neuroscience can be controversial, due in part to continuously evolving notions regarding the significance of spontaneous neural activity. This review highlights how the challenge of separating brain signal from noise has led to new conceptualizations of brain functional organization at both the micro- and macroscopic level. Recent debates in the functional neuroimaging community surrounding artifact removal processes have revived earlier discussions surrounding how to appropriately isolate and measure neuronal signals against a background of noise from various sources. Insights from electrophysiological studies and computational modeling can inform current theory and data analytic practices in human functional neuroimaging, given that signal and noise may be inextricably linked in the brain.
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Affiliation(s)
- Lucina Q Uddin
- Department of Psychology, University of Miami, PO Box 248185-0751, Coral Gables, FL 33124, USA; Neuroscience Program, University of Miami Miller School of Medicine, Miami, FL 33136, USA.
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Liu Y, Perez PD, Ma Z, Ma Z, Dopfel D, Cramer S, Tu W, Zhang N. An open database of resting-state fMRI in awake rats. Neuroimage 2020; 220:117094. [PMID: 32610063 PMCID: PMC7605641 DOI: 10.1016/j.neuroimage.2020.117094] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2020] [Revised: 06/10/2020] [Accepted: 06/18/2020] [Indexed: 12/15/2022] Open
Abstract
Rodent models are essential to translational research in health and disease. Investigation in rodent brain function and organization at the systems level using resting-state functional magnetic resonance imaging (rsfMRI) has become increasingly popular. Due to this rapid progress, publicly shared rodent rsfMRI databases can be of particular interest and importance to the scientific community, as inspired by human neuroscience and psychiatric research that are substantially facilitated by open human neuroimaging datasets. However, such databases in rats are still rare. In this paper, we share an open rsfMRI database acquired in 90 rats with a well-established awake imaging paradigm that avoids anesthesia interference. Both raw and preprocessed data are made publicly available. Procedures in data preprocessing to remove artefacts induced by the scanner, head motion and non-neural physiological noise are described in details. We also showcase inter-regional functional connectivity and functional networks obtained from the database.
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Affiliation(s)
- Yikang Liu
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Pablo D Perez
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Zilu Ma
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Zhiwei Ma
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA, 16802, USA
| | - David Dopfel
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Samuel Cramer
- Neuroscience Program, The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Wenyu Tu
- Neuroscience Program, The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Nanyin Zhang
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA, 16802, USA; Neuroscience Program, The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, 16802, USA.
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