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Hike D, Liu X, Xie Z, Zhang B, Choi S, Zhou XA, Liu A, Murstein A, Jiang Y, Devor A, Yu X. High-resolution awake mouse fMRI at 14 Tesla. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.08.570803. [PMID: 38106227 PMCID: PMC10723470 DOI: 10.1101/2023.12.08.570803] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
High-resolution awake mouse fMRI remains challenging despite extensive efforts to address motion-induced artifacts and stress. This study introduces an implantable radiofrequency (RF) surface coil design that minimizes image distortion caused by the air/tissue interface of mouse brains while simultaneously serving as a headpost for fixation during scanning. Furthermore, this study provides a thorough acclimation method used to accustom animals to the MRI environment minimizing motion induced artifacts. Using a 14T scanner, high-resolution fMRI enabled brain-wide functional mapping of visual and vibrissa stimulation at 100x100x200μm resolution with a 2s per frame sampling rate. Besides activated ascending visual and vibrissa pathways, robust BOLD responses were detected in the anterior cingulate cortex upon visual stimulation and spread through the ventral retrosplenial area (VRA) with vibrissa air-puff stimulation, demonstrating higher-order sensory processing in association cortices of awake mice. In particular, the rapid hemodynamic responses in VRA upon vibrissa stimulation showed a strong correlation with the hippocampus, thalamus, and prefrontal cortical areas. Cross-correlation analysis with designated VRA responses revealed early positive BOLD signals at the contralateral barrel cortex (BC) occurring 2 seconds prior to the air-puff in awake mice with repetitive stimulation, which was not detected using a randomized stimulation paradigm. This early BC activation indicated a learned anticipation through the vibrissa system and association cortices in awake mice under continuous training of repetitive air-puff stimulation. This work establishes a high-resolution awake mouse fMRI platform, enabling brain-wide functional mapping of sensory signal processing in higher association cortical areas.
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Affiliation(s)
- David Hike
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 Thirteenth Street, Charlestown, Massachusetts, USA 02129
| | - Xiaochen Liu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 Thirteenth Street, Charlestown, Massachusetts, USA 02129
| | - Zeping Xie
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 Thirteenth Street, Charlestown, Massachusetts, USA 02129
| | - Bei Zhang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 Thirteenth Street, Charlestown, Massachusetts, USA 02129
| | - Sangcheon Choi
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 Thirteenth Street, Charlestown, Massachusetts, USA 02129
| | - Xiaoqing Alice Zhou
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 Thirteenth Street, Charlestown, Massachusetts, USA 02129
| | - Andy Liu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 Thirteenth Street, Charlestown, Massachusetts, USA 02129
- Graduate program in Neuroscience, Boston University, Commonwealth Ave, Boston, Massachusetts, USA, 02215
| | - Alyssa Murstein
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 Thirteenth Street, Charlestown, Massachusetts, USA 02129
- Graduate program in Neuroscience, Boston University, Commonwealth Ave, Boston, Massachusetts, USA, 02215
| | - Yuanyuan Jiang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 Thirteenth Street, Charlestown, Massachusetts, USA 02129
| | - Anna Devor
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 Thirteenth Street, Charlestown, Massachusetts, USA 02129
- Department of Biomedical Engineering, Boston University, 610 Commonwealth Avenue, Boston, Massachusetts, USA, 02215
| | - Xin Yu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 Thirteenth Street, Charlestown, Massachusetts, USA 02129
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2
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Markicevic M, Mandino F, Toyonaga T, Cai Z, Fesharaki-Zadeh A, Shen X, Strittmatter SM, Lake EMR. Repetitive Mild Closed-Head Injury Induced Synapse Loss and Increased Local BOLD-fMRI Signal Homogeneity. J Neurotrauma 2024. [PMID: 39096127 DOI: 10.1089/neu.2024.0095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/04/2024] Open
Abstract
Repeated mild head injuries due to sports, or domestic violence and military service are increasingly linked to debilitating symptoms in the long term. Although symptoms may take decades to manifest, potentially treatable neurobiological alterations must begin shortly after injury. Better means to diagnose and treat traumatic brain injuries requires an improved understanding of the mechanisms underlying progression and means through which they can be measured. Here, we employ a repetitive mild traumatic brain injury (rmTBI) and chronic variable stress mouse model to investigate emergent structural and functional brain abnormalities. Brain imaging is achieved with [18F]SynVesT-1 positron emission tomography, with the synaptic vesicle glycoprotein 2A ligand marking synapse density and BOLD (blood-oxygen-level-dependent) functional magnetic resonance imaging (fMRI). Animals were scanned six weeks after concluding rmTBI/Stress procedures. Injured mice showed widespread decreases in synaptic density coupled with an increase in local BOLD-fMRI synchrony detected as regional homogeneity. Injury-affected regions with higher synapse density showed a greater increase in fMRI regional homogeneity. Taken together, these observations may reflect compensatory mechanisms following injury. Multimodal studies are needed to provide deeper insights into these observations.
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Affiliation(s)
- Marija Markicevic
- Department of Radiology and Biomedical Imaging, School of Medicine, Yale University, New Haven, Connecticut, USA
| | - Francesca Mandino
- Department of Radiology and Biomedical Imaging, School of Medicine, Yale University, New Haven, Connecticut, USA
| | - Takuya Toyonaga
- Department of Radiology and Biomedical Imaging, School of Medicine, Yale University, New Haven, Connecticut, USA
| | - Zhengxin Cai
- Department of Radiology and Biomedical Imaging, School of Medicine, Yale University, New Haven, Connecticut, USA
| | - Arman Fesharaki-Zadeh
- Department of Neurology, School of Medicine, Yale University, New Haven, Connecticut, USA
- Department of Psychiatry, School of Medicine, Yale University, New Haven, Connecticut, USA
| | - Xilin Shen
- Department of Radiology and Biomedical Imaging, School of Medicine, Yale University, New Haven, Connecticut, USA
| | - Stephen M Strittmatter
- Department of Neurology, School of Medicine, Yale University, New Haven, Connecticut, USA
- Department of Neuroscience, School of Medicine, Yale University, New Haven, Connecticut, USA
- Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, Connecticut, USA
| | - Evelyn M R Lake
- Department of Radiology and Biomedical Imaging, School of Medicine, Yale University, New Haven, Connecticut, USA
- Department of Biomedical Engineering, Yale University, New Haven, Connecticut, USA
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3
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Lewis CM, Hoffmann A, Helmchen F. Linking brain activity across scales with simultaneous opto- and electrophysiology. NEUROPHOTONICS 2024; 11:033403. [PMID: 37662552 PMCID: PMC10472193 DOI: 10.1117/1.nph.11.3.033403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 07/19/2023] [Accepted: 07/24/2023] [Indexed: 09/05/2023]
Abstract
The brain enables adaptive behavior via the dynamic coordination of diverse neuronal signals across spatial and temporal scales: from fast action potential patterns in microcircuits to slower patterns of distributed activity in brain-wide networks. Understanding principles of multiscale dynamics requires simultaneous monitoring of signals in multiple, distributed network nodes. Combining optical and electrical recordings of brain activity is promising for collecting data across multiple scales and can reveal aspects of coordinated dynamics invisible to standard, single-modality approaches. We review recent progress in combining opto- and electrophysiology, focusing on mouse studies that shed new light on the function of single neurons by embedding their activity in the context of brain-wide activity patterns. Optical and electrical readouts can be tailored to desired scales to tackle specific questions. For example, fast dynamics in single cells or local populations recorded with multi-electrode arrays can be related to simultaneously acquired optical signals that report activity in specified subpopulations of neurons, in non-neuronal cells, or in neuromodulatory pathways. Conversely, two-photon imaging can be used to densely monitor activity in local circuits while sampling electrical activity in distant brain areas at the same time. The refinement of combined approaches will continue to reveal previously inaccessible and under-appreciated aspects of coordinated brain activity.
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Affiliation(s)
| | - Adrian Hoffmann
- University of Zurich, Brain Research Institute, Zurich, Switzerland
- University of Zurich, Neuroscience Center Zurich, Zurich, Switzerland
| | - Fritjof Helmchen
- University of Zurich, Brain Research Institute, Zurich, Switzerland
- University of Zurich, Neuroscience Center Zurich, Zurich, Switzerland
- University of Zurich, University Research Priority Program, Adaptive Brain Circuits in Development and Learning, Zurich, Switzerland
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4
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Drossel G, Heilbronner SR, Zimmermann J, Zilverstand A. Neuroimaging of the effects of drug exposure or self-administration in rodents: A systematic review. Neurosci Biobehav Rev 2024; 164:105823. [PMID: 39094280 PMCID: PMC11374361 DOI: 10.1016/j.neubiorev.2024.105823] [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: 03/19/2024] [Revised: 06/19/2024] [Accepted: 07/20/2024] [Indexed: 08/04/2024]
Abstract
A systematic review of functional neuroimaging studies on drug (self-) administration in rodents is lacking. Here, we summarized effects of acute or chronic drug administration of various classes of drugs on brain function and determined consistency with human literature. We performed a systematic literature search and identified 125 studies on in vivo rodent resting-state functional magnetic resonance imaging (n = 84) or positron emission tomography (n = 41) spanning depressants (n = 27), opioids (n = 23), stimulants (n = 72), and cannabis (n = 3). Results primarily showed alterations in the striatum, consistent with the human literature. The anterior cingulate cortex and (nonspecific) prefrontal cortex were also frequently implicated. Upregulation was most often found after shorter administration and downregulation after long chronic administration, particularly in the striatum. Importantly, results were consistent across study design, administration models, imaging method, and animal states. Results provide evidence of altered resting-state brain function in rodents upon drug administration, implicating the brain's reward network analogous to human studies. However, alterations were more dynamic than previously known, with dynamic adaptation depending on the length of drug administration.
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Affiliation(s)
- Gunner Drossel
- Graduate Program in Neuroscience, University of Minnesota, Minneapolis, MN, USA; Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | | | - Jan Zimmermann
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA; Center for Neuroengineering, University of Minnesota, Minneapolis, MN, USA
| | - Anna Zilverstand
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA; Medical Discovery Team on Addiction, University of Minnesota, Minneapolis, MN, USA.
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5
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Desrosiers-Grégoire G, Devenyi GA, Grandjean J, Chakravarty MM. A standardized image processing and data quality platform for rodent fMRI. Nat Commun 2024; 15:6708. [PMID: 39112455 PMCID: PMC11306392 DOI: 10.1038/s41467-024-50826-8] [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: 10/13/2023] [Accepted: 07/22/2024] [Indexed: 08/10/2024] Open
Abstract
Functional magnetic resonance imaging in rodents holds great potential for advancing our understanding of brain networks. Unlike the human community, there remains no standardized resource in rodents for image processing, analysis and quality control, posing significant reproducibility limitations. Our software platform, Rodent Automated Bold Improvement of EPI Sequences, is a pipeline designed to address these limitations for preprocessing, quality control, and confound correction, along with best practices for reproducibility and transparency. We demonstrate the robustness of the preprocessing workflow by validating performance across multiple acquisition sites and both mouse and rat data. Building upon a thorough investigation into data quality metrics across acquisition sites, we introduce guidelines for the quality control of network analysis and offer recommendations for addressing issues. Taken together, this software platform will allow the emerging community to adopt reproducible practices and foster progress in translational neuroscience.
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Affiliation(s)
- Gabriel Desrosiers-Grégoire
- Computational Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, QC, Canada.
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada.
| | - Gabriel A Devenyi
- Computational Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Joanes Grandjean
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - M Mallar Chakravarty
- Computational Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, QC, Canada.
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada.
- Department of Psychiatry, McGill University, Montreal, QC, Canada.
- Department of Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada.
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6
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Herzberg MP, Nielsen AN, Luby J, Sylvester CM. Measuring neuroplasticity in human development: the potential to inform the type and timing of mental health interventions. Neuropsychopharmacology 2024:10.1038/s41386-024-01947-7. [PMID: 39103496 DOI: 10.1038/s41386-024-01947-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Revised: 06/17/2024] [Accepted: 07/15/2024] [Indexed: 08/07/2024]
Abstract
Neuroplasticity during sensitive periods, the molecular and cellular process of enduring neural change in response to external stimuli during windows of high environmental sensitivity, is crucial for adaptation to expected environments and has implications for psychiatry. Animal research has characterized the developmental sequence and neurobiological mechanisms that govern neuroplasticity, yet gaps in our ability to measure neuroplasticity in humans limit the clinical translation of these principles. Here, we present a roadmap for the development and validation of neuroimaging and electrophysiology measures that index neuroplasticity to begin to address these gaps. We argue that validation of measures to track neuroplasticity in humans will elucidate the etiology of mental illness and inform the type and timing of mental health interventions to optimize effectiveness. We outline criteria for evaluating putative neuroimaging measures of plasticity in humans including links to neurobiological mechanisms shown to govern plasticity in animal models, developmental change that reflects heightened early life plasticity, and prediction of neural and/or behavior change. These criteria are applied to three putative measures of neuroplasticity using electroencephalography (gamma oscillations, aperiodic exponent of power/frequency) or functional magnetic resonance imaging (amplitude of low frequency fluctuations). We discuss the use of these markers in psychiatry, envision future uses for clinical and developmental translation, and suggest steps to address the limitations of the current putative neuroimaging measures of plasticity. With additional work, we expect these markers will significantly impact mental health and be used to characterize mechanisms, devise new interventions, and optimize developmental trajectories to reduce psychopathology risk.
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Affiliation(s)
- Max P Herzberg
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA.
| | - Ashley N Nielsen
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA.
| | - Joan Luby
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | - Chad M Sylvester
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
- Taylor Family Institute for Innovative Psychiatric Research, Washington University in St. Louis, St. Louis, MO, USA
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7
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Broggini T, Duckworth J, Ji X, Liu R, Xia X, Mächler P, Shaked I, Munting LP, Iyengar S, Kotlikoff M, van Veluw SJ, Vergassola M, Mishne G, Kleinfeld D. Long-wavelength traveling waves of vasomotion modulate the perfusion of cortex. Neuron 2024; 112:2349-2367.e8. [PMID: 38781972 PMCID: PMC11257831 DOI: 10.1016/j.neuron.2024.04.034] [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: 10/17/2023] [Revised: 03/28/2024] [Accepted: 04/30/2024] [Indexed: 05/25/2024]
Abstract
Brain arterioles are active, multicellular complexes whose diameters oscillate at ∼ 0.1 Hz. We assess the physiological impact and spatiotemporal dynamics of vaso-oscillations in the awake mouse. First, vaso-oscillations in penetrating arterioles, which source blood from pial arterioles to the capillary bed, profoundly impact perfusion throughout neocortex. The modulation in flux during resting-state activity exceeds that of stimulus-induced activity. Second, the change in perfusion through arterioles relative to the change in their diameter is weak. This implies that the capillary bed dominates the hydrodynamic resistance of brain vasculature. Lastly, the phase of vaso-oscillations evolves slowly along arterioles, with a wavelength that exceeds the span of the cortical mantle and sufficient variability to establish functional cortical areas as parcels of uniform phase. The phase-gradient supports traveling waves in either direction along both pial and penetrating arterioles. This implies that waves along penetrating arterioles can mix, but not directionally transport, interstitial fluids.
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Affiliation(s)
- Thomas Broggini
- Department of Physics, University of California, San Diego, La Jolla, CA 92093, USA; Goethe University Frankfurt, Department of Neurosurgery, 60528 Frankfurt am Main, Germany; Frankfurt Cancer Institute, Goethe University Frankfurt, 60528 Frankfurt am Main, Germany
| | - Jacob Duckworth
- Department of Physics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Xiang Ji
- Department of Physics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Rui Liu
- Department of Physics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Xinyue Xia
- Halıcıoğlu Data Science Institute, University of California, San Diego, La Jolla, CA 92093, USA
| | - Philipp Mächler
- Department of Physics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Iftach Shaked
- Department of Physics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Leon Paul Munting
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Satish Iyengar
- Department of Statistics, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Michael Kotlikoff
- College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA
| | - Susanne J van Veluw
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA
| | | | - Gal Mishne
- Halıcıoğlu Data Science Institute, University of California, San Diego, La Jolla, CA 92093, USA
| | - David Kleinfeld
- Department of Physics, University of California, San Diego, La Jolla, CA 92093, USA; Department of Neurobiology, University of California, San Diego, La Jolla, CA 92093, USA.
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8
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Doran PR, Fomin-Thunemann N, Tang RP, Balog D, Zimmerman B, Kılıç K, Martin EA, Kura S, Fisher HP, Chabbott G, Herbert J, Rauscher BC, Jiang JX, Sakadzic S, Boas DA, Devor A, Chen IA, Thunemann M. Widefield in vivo imaging system with two fluorescence and two reflectance channels, a single sCMOS detector, and shielded illumination. NEUROPHOTONICS 2024; 11:034310. [PMID: 38881627 PMCID: PMC11177117 DOI: 10.1117/1.nph.11.3.034310] [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: 11/07/2023] [Revised: 05/17/2024] [Accepted: 05/21/2024] [Indexed: 06/18/2024]
Abstract
Significance Widefield microscopy of the entire dorsal part of mouse cerebral cortex enables large-scale ("mesoscopic") imaging of different aspects of neuronal activity with spectrally compatible fluorescent indicators as well as hemodynamics via oxy- and deoxyhemoglobin absorption. Versatile and cost-effective imaging systems are needed for large-scale, color-multiplexed imaging of multiple fluorescent and intrinsic contrasts. Aim We aim to develop a system for mesoscopic imaging of two fluorescent and two reflectance channels. Approach Excitation of red and green fluorescence is achieved through epi-illumination. Hemoglobin absorption imaging is achieved using 525- and 625-nm light-emitting diodes positioned around the objective lens. An aluminum hemisphere placed between objective and cranial window provides diffuse illumination of the brain. Signals are recorded sequentially by a single sCMOS detector. Results We demonstrate the performance of our imaging system by recording large-scale spontaneous and stimulus-evoked neuronal, cholinergic, and hemodynamic activity in awake, head-fixed mice with a curved "crystal skull" window expressing the red calcium indicator jRGECO1a and the green acetylcholine sensorGRAB ACh 3.0 . Shielding of illumination light through the aluminum hemisphere enables concurrent recording of pupil diameter changes. Conclusions Our widefield microscope design with a single camera can be used to acquire multiple aspects of brain physiology and is compatible with behavioral readouts of pupil diameter.
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Affiliation(s)
- Patrick R. Doran
- Boston University, Graduate Program in Biomedical Engineering, Boston, Massachusetts, United States
| | - Natalie Fomin-Thunemann
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Rockwell P. Tang
- Boston University, Graduate Program in Biomedical Engineering, Boston, Massachusetts, United States
| | - Dora Balog
- Boston University, Graduate Program in Biomedical Engineering, Boston, Massachusetts, United States
| | - Bernhard Zimmerman
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Kıvılcım Kılıç
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Emily A. Martin
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Sreekanth Kura
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Harrison P. Fisher
- Boston University, Graduate Program in Biomedical Engineering, Boston, Massachusetts, United States
| | - Grace Chabbott
- Boston University, Undergraduate Program in Biomedical Engineering, Boston, Massachusetts, United States
| | - Joel Herbert
- Boston University, Undergraduate Program in Neuroscience, Boston, Massachusetts, United States
| | - Bradley C. Rauscher
- Boston University, Graduate Program in Biomedical Engineering, Boston, Massachusetts, United States
| | - John X. Jiang
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Sava Sakadzic
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
| | - David A. Boas
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Anna Devor
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
| | - Ichun Anderson Chen
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Martin Thunemann
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
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9
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Mandino F, Horien C, Shen X, Desrosiers-Gregoire G, Luo W, Markicevic M, Constable RX, Papademetris X, Chakravarty MM, Betzel RF, Lake EMR. Multimodal identification of the mouse brain using simultaneous Ca 2+ imaging and fMRI. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.24.594620. [PMID: 38826324 PMCID: PMC11142213 DOI: 10.1101/2024.05.24.594620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Individual differences in neuroimaging are of interest to clinical and cognitive neuroscientists based on their potential for guiding the personalized treatment of various heterogeneous neurological conditions and diseases. Despite many advantages, the workhorse in this arena, BOLD (blood-oxygen-level-dependent) functional magnetic resonance imaging (fMRI) suffers from low spatiotemporal resolution and specificity as well as a propensity for noise and spurious signal corruption. To better understand individual differences in BOLD-fMRI data, we can use animal models where fMRI, alongside complementary but more invasive contrasts, can be accessed. Here, we apply simultaneous wide-field fluorescence calcium imaging and BOLD-fMRI in mice to interrogate individual differences using a connectome-based identification framework adopted from the human fMRI literature. This approach yields high spatiotemporal resolution cell-type specific signals (here, from glia, excitatory, as well as inhibitory interneurons) from the whole cortex. We found mouse multimodal connectome- based identification to be successful and explored various features of these data.
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10
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Markicevic M, Mandino F, Toyonaga T, Cai Z, Fesharaki-Zadeh A, Shen X, Strittmatter SM, Lake E. Repetitive mild closed-head injury induced synapse loss and increased local BOLD-fMRI signal homogeneity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.24.595651. [PMID: 38826468 PMCID: PMC11142233 DOI: 10.1101/2024.05.24.595651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Repeated mild head injuries due to sports, or domestic violence and military service are increasingly linked to debilitating symptoms in the long term. Although symptoms may take decades to manifest, potentially treatable neurobiological alterations must begin shortly after injury. Better means to diagnose and treat traumatic brain injuries, requires an improved understanding of the mechanisms underlying progression and means through which they can be measured. Here, we employ a repetitive mild closed-head injury (rmTBI) and chronic variable stress (CVS) mouse model to investigate emergent structural and functional brain abnormalities. Brain imaging is achieved with [ 18 F]SynVesT-1 positron emission tomography, with the synaptic vesicle glycoprotein 2A ligand marking synapse density and BOLD (blood-oxygen-level-dependent) functional magnetic resonance imaging (fMRI). Animals were scanned six weeks after concluding rmTBI/Stress procedures. Injured mice showed widespread decreases in synaptic density coupled with an i ncrease in local BOLD-fMRI synchrony detected as regional homogeneity. Injury-affected regions with higher synapse density showed a greater increase in fMRI regional homogeneity. Taken together, these observations may reflect compensatory mechanisms following injury. Multimodal studies are needed to provide deeper insights into these observations.
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11
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Zhou Q, Glück C, Tang L, Glandorf L, Droux J, El Amki M, Wegener S, Weber B, Razansky D, Chen Z. Cortex-wide transcranial localization microscopy with fluorescently labeled red blood cells. Nat Commun 2024; 15:3526. [PMID: 38664419 PMCID: PMC11045747 DOI: 10.1038/s41467-024-47892-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 04/15/2024] [Indexed: 04/28/2024] Open
Abstract
Large-scale imaging of brain activity with high spatio-temporal resolution is crucial for advancing our understanding of brain function. The existing neuroimaging techniques are largely limited by restricted field of view, slow imaging speed, or otherwise do not have the adequate spatial resolution to capture brain activities on a capillary and cellular level. To address these limitations, we introduce fluorescence localization microscopy aided with sparsely-labeled red blood cells for cortex-wide morphological and functional cerebral angiography with 4.9 µm spatial resolution and 1 s temporal resolution. When combined with fluorescence calcium imaging, the proposed method enables extended recordings of stimulus-evoked neuro-vascular changes in the murine brain while providing simultaneous multiparametric readings of intracellular neuronal activity, blood flow velocity/direction/volume, and vessel diameter. Owing to its simplicity and versatility, the proposed approach will become an invaluable tool for deciphering the regulation of cortical microcirculation and neurovascular coupling in health and disease.
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Affiliation(s)
- Quanyu Zhou
- Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich, Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Zurich, Switzerland
| | - Chaim Glück
- Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich, Switzerland
- Zurich Neuroscience Center, Zurich, Switzerland
| | - Lin Tang
- Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich, Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Zurich, Switzerland
| | - Lukas Glandorf
- Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich, Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Zurich, Switzerland
| | - Jeanne Droux
- Zurich Neuroscience Center, Zurich, Switzerland
- Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Mohamad El Amki
- Zurich Neuroscience Center, Zurich, Switzerland
- Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Susanne Wegener
- Zurich Neuroscience Center, Zurich, Switzerland
- Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Bruno Weber
- Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich, Switzerland
- Zurich Neuroscience Center, Zurich, Switzerland
| | - Daniel Razansky
- Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich, Switzerland.
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Zurich, Switzerland.
- Zurich Neuroscience Center, Zurich, Switzerland.
| | - Zhenyue Chen
- Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich, Switzerland.
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Zurich, Switzerland.
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12
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Fei Y, Wu Q, Zhao S, Song K, Han J, Liu C. Diverse and asymmetric patterns of single-neuron projectome in regulating interhemispheric connectivity. Nat Commun 2024; 15:3403. [PMID: 38649683 PMCID: PMC11035633 DOI: 10.1038/s41467-024-47762-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 04/11/2024] [Indexed: 04/25/2024] Open
Abstract
The corpus callosum, historically considered primarily for homotopic connections, supports many heterotopic connections, indicating complex interhemispheric connectivity. Understanding this complexity is crucial yet challenging due to diverse cell-specific wiring patterns. Here, we utilized public AAV bulk tracing and single-neuron tracing data to delineate the anatomical connection patterns of mouse brains and conducted wide-field calcium imaging to assess functional connectivity across various brain states in male mice. The single-neuron data uncovered complex and dense interconnected patterns, particularly for interhemispheric-heterotopic connections. We proposed a metric "heterogeneity" to quantify the complexity of the connection patterns. Computational modeling of these patterns suggested that the heterogeneity of upstream projections impacted downstream homotopic functional connectivity. Furthermore, higher heterogeneity observed in interhemispheric-heterotopic projections would cause lower strength but higher stability in functional connectivity than their intrahemispheric counterparts. These findings were corroborated by our wide-field functional imaging data, underscoring the important role of heterotopic-projection heterogeneity in interhemispheric communication.
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Affiliation(s)
- Yao Fei
- School of Automation, Northwestern Polytechnical University, Xi'an, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Qihang Wu
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Shijie Zhao
- School of Automation, Northwestern Polytechnical University, Xi'an, China.
- Research & Development, Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, China.
| | - Kun Song
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Junwei Han
- School of Automation, Northwestern Polytechnical University, Xi'an, China.
- Research & Development, Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, China.
| | - Cirong Liu
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Shanghai, China.
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13
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Shi L, Fu X, Gui S, Wan T, Zhuo J, Lu J, Li P. Global spatiotemporal synchronizing structures of spontaneous neural activities in different cell types. Nat Commun 2024; 15:2884. [PMID: 38570488 PMCID: PMC10991327 DOI: 10.1038/s41467-024-46975-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 03/13/2024] [Indexed: 04/05/2024] Open
Abstract
Increasing evidence has revealed the large-scale nonstationary synchronizations as traveling waves in spontaneous neural activity. However, the interplay of various cell types in fine-tuning these spatiotemporal patters remains unclear. Here, we performed comprehensive exploration of spatiotemporal synchronizing structures across different cell types, states (awake, anesthesia, motion) and developmental axis in male mice. We found traveling waves in glutamatergic neurons exhibited greater variety than those in GABAergic neurons. Moreover, the synchronizing structures of GABAergic neurons converged toward those of glutamatergic neurons during development, but the evolution of waves exhibited varying timelines for different sub-type interneurons. Functional connectivity arises from both standing and traveling waves, and negative connections can be elucidated by the spatial propagation of waves. In addition, some traveling waves were correlated with the spatial distribution of gene expression. Our findings offer further insights into the neural underpinnings of traveling waves, functional connectivity, and resting-state networks, with cell-type specificity and developmental perspectives.
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Affiliation(s)
- Liang Shi
- Britton Chance Center for Biomedical Photonics and MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Science, HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, 215100, China
| | - Xiaoxi Fu
- Britton Chance Center for Biomedical Photonics and MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Science, HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, 215100, China
| | - Shen Gui
- Britton Chance Center for Biomedical Photonics and MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Science, HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, 215100, China
| | - Tong Wan
- State Key Laboratory of Digital Medical Engineering, School of Biomedical Engineering, Hainan University, Sanya, 572025, China
| | - Junjie Zhuo
- State Key Laboratory of Digital Medical Engineering, School of Biomedical Engineering, Hainan University, Sanya, 572025, China
| | - Jinling Lu
- Britton Chance Center for Biomedical Photonics and MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Science, HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, 215100, China.
| | - Pengcheng Li
- Britton Chance Center for Biomedical Photonics and MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Science, HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, 215100, China.
- State Key Laboratory of Digital Medical Engineering, School of Biomedical Engineering, Hainan University, Sanya, 572025, China.
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14
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Doran PR, Fomin-Thunemann N, Tang RP, Balog D, Zimmerman B, Kilic K, Martin EA, Kura S, Fisher HP, Chabbott G, Herbert J, Rauscher BC, Jiang JX, Sakadzic S, Boas DA, Devor A, Chen IA, Thunemann M. Widefield in vivo imaging system with two fluorescence and two reflectance channels, a single sCMOS detector, and shielded illumination. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.11.07.566086. [PMID: 37986755 PMCID: PMC10659277 DOI: 10.1101/2023.11.07.566086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
SIGNIFICANCE Widefield microscopy of the entire dorsal part of mouse cerebral cortex enables large-scale (mesoscopic) imaging of neuronal activity with fluorescent indicators as well as hemodynamics via oxy- and deoxyhemoglobin absorption. Versatile and cost-effective imaging systems are needed for large-scale, color-multiplexed imaging of multiple fluorescent and intrinsic contrasts. AIM Develop a system for mesoscopic imaging of two fluorescent and two reflectance channels. APPROACH Excitation of red and green fluorescence is achieved through epi-illumination. Hemoglobin absorption imaging is achieved using 525- and 625nm LEDs positioned around the objective lens. An aluminum hemisphere placed between objective and cranial window provides diffuse illumination of the brain. Signals are recorded sequentially by a single sCMOS detector. RESULTS We demonstrate performance of our imaging system by recording large-scale spontaneous and stimulus-evoked neuronal, cholinergic, and hemodynamic activity in awake head-fixed mice with a curved crystal skull window expressing the red calcium indicator jRGECO1a and the green acetylcholine sensor GRABACh3.0 . Shielding of illumination light through the aluminum hemisphere enables concurrent recording of pupil diameter changes. CONCLUSIONS Our widefield microscope design with single camera can be used to acquire multiple aspects of brain physiology and is compatible with behavioral readouts of pupil diameter.
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15
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Grandjean J, Lake EMR, Pagani M, Mandino F. What N Is N-ough for MRI-Based Animal Neuroimaging? eNeuro 2024; 11:ENEURO.0531-23.2024. [PMID: 38499355 PMCID: PMC10950324 DOI: 10.1523/eneuro.0531-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 02/08/2024] [Accepted: 02/13/2024] [Indexed: 03/20/2024] Open
Abstract
Fueled by the recent and controversial brain-wide association studies in humans, the animal neuroimaging community has also begun questioning whether using larger sample sizes is necessary for ethical and effective scientific progress. In this opinion piece, we illustrate two opposing views on sample size extremes in MRI-based animal neuroimaging.
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Affiliation(s)
- Joanes Grandjean
- Donders Institute for Brain, Cognition, and Behaviour, Nijmegen 6500HB, The Netherlands
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen 6500HB, The Netherlands
| | - Evelyn M R Lake
- Departments of Radiology and Biomedical Imaging, New Haven, Connecticut 06519
- Biomedical Engineering, Yale School of Medicine, New Haven, Connecticut 06519
| | - Marco Pagani
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto 38068, Italy
- IMT School for Advanced Studies, Lucca 55100, Italy
| | - Francesca Mandino
- Departments of Radiology and Biomedical Imaging, New Haven, Connecticut 06519
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16
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Cerri DH, Albaugh DL, Walton LR, Katz B, Wang TW, Chao THH, Zhang W, Nonneman RJ, Jiang J, Lee SH, Etkin A, Hall CN, Stuber GD, Shih YYI. Distinct neurochemical influences on fMRI response polarity in the striatum. Nat Commun 2024; 15:1916. [PMID: 38429266 PMCID: PMC10907631 DOI: 10.1038/s41467-024-46088-z] [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: 03/30/2023] [Accepted: 02/13/2024] [Indexed: 03/03/2024] Open
Abstract
The striatum, known as the input nucleus of the basal ganglia, is extensively studied for its diverse behavioral roles. However, the relationship between its neuronal and vascular activity, vital for interpreting functional magnetic resonance imaging (fMRI) signals, has not received comprehensive examination within the striatum. Here, we demonstrate that optogenetic stimulation of dorsal striatal neurons or their afferents from various cortical and subcortical regions induces negative striatal fMRI responses in rats, manifesting as vasoconstriction. These responses occur even with heightened striatal neuronal activity, confirmed by electrophysiology and fiber-photometry. In parallel, midbrain dopaminergic neuron optogenetic modulation, coupled with electrochemical measurements, establishes a link between striatal vasodilation and dopamine release. Intriguingly, in vivo intra-striatal pharmacological manipulations during optogenetic stimulation highlight a critical role of opioidergic signaling in generating striatal vasoconstriction. This observation is substantiated by detecting striatal vasoconstriction in brain slices after synthetic opioid application. In humans, manipulations aimed at increasing striatal neuronal activity likewise elicit negative striatal fMRI responses. Our results emphasize the necessity of considering vasoactive neurotransmission alongside neuronal activity when interpreting fMRI signal.
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Affiliation(s)
- Domenic H Cerri
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Daniel L Albaugh
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Lindsay R Walton
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Brittany Katz
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Tzu-Wen Wang
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Tzu-Hao Harry Chao
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Weiting Zhang
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Randal J Nonneman
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jing Jiang
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Department of Pediatrics, University of Iowa Carver College of Medicine, Iowa City, IA, USA
- Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA, USA
- Iowa Neuroscience Institute, University of Iowa Carver College of Medicine, Iowa City, IA, USA
| | - Sung-Ho Lee
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Amit Etkin
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Alto Neuroscience, Los Altos, CA, USA
| | - Catherine N Hall
- Sussex Neuroscience, University of Sussex, Falmer, United Kingdom
- School of Psychology, University of Sussex, Falmer, United Kingdom
| | - Garret D Stuber
- Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA, USA
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA
- Department of Pharmacology, University of Washington, Seattle, WA, USA
| | - Yen-Yu Ian Shih
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
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17
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Wu J, Chen Y, Veeraraghavan A, Seidemann E, Robinson JT. Mesoscopic calcium imaging in a head-unrestrained male non-human primate using a lensless microscope. Nat Commun 2024; 15:1271. [PMID: 38341403 PMCID: PMC10858944 DOI: 10.1038/s41467-024-45417-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 01/22/2024] [Indexed: 02/12/2024] Open
Abstract
Mesoscopic calcium imaging enables studies of cell-type specific neural activity over large areas. A growing body of literature suggests that neural activity can be different when animals are free to move compared to when they are restrained. Unfortunately, existing systems for imaging calcium dynamics over large areas in non-human primates (NHPs) are table-top devices that require restraint of the animal's head. Here, we demonstrate an imaging device capable of imaging mesoscale calcium activity in a head-unrestrained male non-human primate. We successfully miniaturize our system by replacing lenses with an optical mask and computational algorithms. The resulting lensless microscope can fit comfortably on an NHP, allowing its head to move freely while imaging. We are able to measure orientation columns maps over a 20 mm2 field-of-view in a head-unrestrained macaque. Our work establishes mesoscopic imaging using a lensless microscope as a powerful approach for studying neural activity under more naturalistic conditions.
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Affiliation(s)
- Jimin Wu
- Department of Bioengineering, Rice University, 6100 Main Street, Houston, TX, 77005, USA
| | - Yuzhi Chen
- Department of Neuroscience, University of Texas at Austin, 100 E 24th St., Austin, TX, 78712, USA
- Department of Psychology, University of Texas at Austin, 108 E Dean Keeton St., Austin, TX, 78712, USA
| | - Ashok Veeraraghavan
- Department of Electrical and Computer Engineering, Rice University, 6100 Main Street, Houston, TX, 77005, USA
- Department of Computer Science, Rice University, 6100 Main Street, Houston, TX, 77005, USA
| | - Eyal Seidemann
- Department of Neuroscience, University of Texas at Austin, 100 E 24th St., Austin, TX, 78712, USA.
- Department of Psychology, University of Texas at Austin, 108 E Dean Keeton St., Austin, TX, 78712, USA.
| | - Jacob T Robinson
- Department of Bioengineering, Rice University, 6100 Main Street, Houston, TX, 77005, USA.
- Department of Electrical and Computer Engineering, Rice University, 6100 Main Street, Houston, TX, 77005, USA.
- Department of Neuroscience, Baylor College of Medicine, One Baylor Plaza, Houston, TX, 77030, USA.
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18
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Jacob LPL, Bailes SM, Williams SD, Stringer C, Lewis LD. Distributed fMRI dynamics predict distinct EEG rhythms across sleep and wakefulness. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.29.577429. [PMID: 38352426 PMCID: PMC10862763 DOI: 10.1101/2024.01.29.577429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
The brain exhibits rich oscillatory dynamics that vary across tasks and states, such as the EEG oscillations that define sleep. These oscillations play critical roles in cognition and arousal, but the brainwide mechanisms underlying them are not yet described. Using simultaneous EEG and fast fMRI in subjects drifting between sleep and wakefulness, we developed a machine learning approach to investigate which brainwide fMRI dynamics predict alpha (8-12 Hz) and delta (1-4 Hz) rhythms. We predicted moment-by-moment EEG power from fMRI activity in held-out subjects, and found that information about alpha power was represented by a remarkably small set of regions, segregated in two distinct networks linked to arousal and visual systems. Conversely, delta rhythms were diffusely represented on a large spatial scale across the cortex. These results identify distributed networks that predict delta and alpha rhythms, and establish a computational framework for investigating fMRI brainwide dynamics underlying EEG oscillations.
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Affiliation(s)
- Leandro P L Jacob
- Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Sydney M Bailes
- Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Boston University, Boston, MA, USA
| | - Stephanie D Williams
- Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Boston University, Boston, MA, USA
| | | | - Laura D Lewis
- Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston MA USA
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19
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Ragone E, Tanner J, Jo Y, Zamani Esfahlani F, Faskowitz J, Pope M, Coletta L, Gozzi A, Betzel R. Modular subgraphs in large-scale connectomes underpin spontaneous co-fluctuation events in mouse and human brains. Commun Biol 2024; 7:126. [PMID: 38267534 PMCID: PMC10810083 DOI: 10.1038/s42003-024-05766-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 01/02/2024] [Indexed: 01/26/2024] Open
Abstract
Previous studies have adopted an edge-centric framework to study fine-scale network dynamics in human fMRI. To date, however, no studies have applied this framework to data collected from model organisms. Here, we analyze structural and functional imaging data from lightly anesthetized mice through an edge-centric lens. We find evidence of "bursty" dynamics and events - brief periods of high-amplitude network connectivity. Further, we show that on a per-frame basis events best explain static FC and can be divided into a series of hierarchically-related clusters. The co-fluctuation patterns associated with each cluster centroid link distinct anatomical areas and largely adhere to the boundaries of algorithmically detected functional brain systems. We then investigate the anatomical connectivity undergirding high-amplitude co-fluctuation patterns. We find that events induce modular bipartitions of the anatomical network of inter-areal axonal projections. Finally, we replicate these same findings in a human imaging dataset. In summary, this report recapitulates in a model organism many of the same phenomena observed in previously edge-centric analyses of human imaging data. However, unlike human subjects, the murine nervous system is amenable to invasive experimental perturbations. Thus, this study sets the stage for future investigation into the causal origins of fine-scale brain dynamics and high-amplitude co-fluctuations. Moreover, the cross-species consistency of the reported findings enhances the likelihood of future translation.
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Affiliation(s)
| | - Jacob Tanner
- Cognitive Science Program, Indiana University, Bloomington, IN, 47401, USA
- School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, 47401, USA
| | - Youngheun Jo
- Department of Psychological and Brain Sciences and Cognitive Science Program, Indiana University, Bloomington, IN, 47401, USA
| | - Farnaz Zamani Esfahlani
- Stephenson School of Biomedical Engineering, The University of Oklahoma, Norman, OK, 73019, USA
| | - Joshua Faskowitz
- Department of Psychological and Brain Sciences and Cognitive Science Program, Indiana University, Bloomington, IN, 47401, USA
| | - Maria Pope
- School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, 47401, USA
- Program in Neuroscience, Indiana University, Bloomington, IN, 47401, USA
| | | | - Alessandro Gozzi
- Functional Neuroimaging Lab, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, Rovereto, Italy
| | - Richard Betzel
- Cognitive Science Program, Indiana University, Bloomington, IN, 47401, USA.
- Department of Psychological and Brain Sciences and Cognitive Science Program, Indiana University, Bloomington, IN, 47401, USA.
- Program in Neuroscience, Indiana University, Bloomington, IN, 47401, USA.
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20
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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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21
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Benisty H, Barson D, Moberly AH, Lohani S, Tang L, Coifman RR, Crair MC, Mishne G, Cardin JA, Higley MJ. Rapid fluctuations in functional connectivity of cortical networks encode spontaneous behavior. Nat Neurosci 2024; 27:148-158. [PMID: 38036743 PMCID: PMC11316935 DOI: 10.1038/s41593-023-01498-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 10/16/2023] [Indexed: 12/02/2023]
Abstract
Experimental work across species has demonstrated that spontaneously generated behaviors are robustly coupled to variations in neural activity within the cerebral cortex. Functional magnetic resonance imaging data suggest that temporal correlations in cortical networks vary across distinct behavioral states, providing for the dynamic reorganization of patterned activity. However, these data generally lack the temporal resolution to establish links between cortical signals and the continuously varying fluctuations in spontaneous behavior observed in awake animals. Here, we used wide-field mesoscopic calcium imaging to monitor cortical dynamics in awake mice and developed an approach to quantify rapidly time-varying functional connectivity. We show that spontaneous behaviors are represented by fast changes in both the magnitude and correlational structure of cortical network activity. Combining mesoscopic imaging with simultaneous cellular-resolution two-photon microscopy demonstrated that correlations among neighboring neurons and between local and large-scale networks also encode behavior. Finally, the dynamic functional connectivity of mesoscale signals revealed subnetworks not predicted by traditional anatomical atlas-based parcellation of the cortex. These results provide new insights into how behavioral information is represented across the neocortex and demonstrate an analytical framework for investigating time-varying functional connectivity in neural networks.
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Affiliation(s)
- Hadas Benisty
- Department of Neuroscience, Kavli Institute for Neuroscience, Yale University School of Medicine, New Haven, CT, USA
| | - Daniel Barson
- Department of Neuroscience, Kavli Institute for Neuroscience, Yale University School of Medicine, New Haven, CT, USA
| | - Andrew H Moberly
- Department of Neuroscience, Kavli Institute for Neuroscience, Yale University School of Medicine, New Haven, CT, USA
| | - Sweyta Lohani
- Department of Neuroscience, Kavli Institute for Neuroscience, Yale University School of Medicine, New Haven, CT, USA
| | - Lan Tang
- Department of Neuroscience, Kavli Institute for Neuroscience, Yale University School of Medicine, New Haven, CT, USA
| | - Ronald R Coifman
- Program in Applied Mathematics, Yale University, New Haven, CT, USA
| | - Michael C Crair
- Department of Neuroscience, Kavli Institute for Neuroscience, Yale University School of Medicine, New Haven, CT, USA
| | - Gal Mishne
- Halıcıoğlu Data Science Institute, University of California, San Diego, La Jolla, CA, USA
| | - Jessica A Cardin
- Department of Neuroscience, Kavli Institute for Neuroscience, Yale University School of Medicine, New Haven, CT, USA
| | - Michael J Higley
- Department of Neuroscience, Kavli Institute for Neuroscience, Yale University School of Medicine, New Haven, CT, USA.
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22
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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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23
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James S, Sanggaard S, Akif A, Mishra SK, Sanganahalli BG, Blumenfeld H, Verhagen JV, Hyder F, Herman P. Spatiotemporal features of neurovascular (un)coupling with stimulus-induced activity and hypercapnia challenge in cerebral cortex and olfactory bulb. J Cereb Blood Flow Metab 2023; 43:1891-1904. [PMID: 37340791 PMCID: PMC10676132 DOI: 10.1177/0271678x231183887] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 05/12/2023] [Accepted: 05/15/2023] [Indexed: 06/22/2023]
Abstract
Carbon dioxide (CO2) is traditionally considered as metabolic waste, yet its regulation is critical for brain function. It is well accepted that hypercapnia initiates vasodilation, but its effect on neuronal activity is less clear. Distinguishing how stimulus- and CO2-induced vasodilatory responses are (dis)associated with neuronal activity has profound clinical and experimental relevance. We used an optical method in mice to simultaneously image fluorescent calcium (Ca2+) transients from neurons and reflectometric hemodynamic signals during brief sensory stimuli (i.e., hindpaw, odor) and CO2 exposure (i.e., 5%). Stimuli-induced neuronal and hemodynamic responses swiftly increased within locally activated regions exhibiting robust neurovascular coupling. However, hypercapnia produced slower global vasodilation which was temporally uncoupled to neuronal deactivation. With trends consistent across cerebral cortex and olfactory bulb as well as data from GCaMP6f/jRGECO1a mice (i.e., green/red Ca2+ fluorescence), these results unequivocally reveal that stimuli and CO2 generate comparable vasodilatory responses but contrasting neuronal responses. In summary, observations of stimuli-induced regional neurovascular coupling and CO2-induced global neurovascular uncoupling call for careful appraisal when using CO2 in gas mixtures to affect vascular tone and/or neuronal excitability, because CO2 is both a potent vasomodulator and a neuromodulator.
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Affiliation(s)
- Shaun James
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA
| | - Simon Sanggaard
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Adil Akif
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Sandeep K Mishra
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA
| | | | - Hal Blumenfeld
- Department of Neurology, Yale University, New Haven, CT, USA
- Department of Neuroscience, Yale University, New Haven, CT, USA
| | - Justus V Verhagen
- Department of Neuroscience, Yale University, New Haven, CT, USA
- John B. Pierce Laboratory, New Haven, CT, USA
| | - Fahmeed Hyder
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Peter Herman
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA
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24
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Finn ES, Poldrack RA, Shine JM. Functional neuroimaging as a catalyst for integrated neuroscience. Nature 2023; 623:263-273. [PMID: 37938706 DOI: 10.1038/s41586-023-06670-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 09/22/2023] [Indexed: 11/09/2023]
Abstract
Functional magnetic resonance imaging (fMRI) enables non-invasive access to the awake, behaving human brain. By tracking whole-brain signals across a diverse range of cognitive and behavioural states or mapping differences associated with specific traits or clinical conditions, fMRI has advanced our understanding of brain function and its links to both normal and atypical behaviour. Despite this headway, progress in human cognitive neuroscience that uses fMRI has been relatively isolated from rapid advances in other subdomains of neuroscience, which themselves are also somewhat siloed from one another. In this Perspective, we argue that fMRI is well-placed to integrate the diverse subfields of systems, cognitive, computational and clinical neuroscience. We first summarize the strengths and weaknesses of fMRI as an imaging tool, then highlight examples of studies that have successfully used fMRI in each subdomain of neuroscience. We then provide a roadmap for the future advances that will be needed to realize this integrative vision. In this way, we hope to demonstrate how fMRI can help usher in a new era of interdisciplinary coherence in neuroscience.
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Affiliation(s)
- Emily S Finn
- Department of Psychological and Brain Sciences, Dartmouth College, Dartmouth, NH, USA.
| | | | - James M Shine
- School of Medical Sciences, University of Sydney, Sydney, New South Wales, Australia.
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25
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Betzel RF, Faskowitz J, Sporns O. Living on the edge: network neuroscience beyond nodes. Trends Cogn Sci 2023; 27:1068-1084. [PMID: 37716895 PMCID: PMC10592364 DOI: 10.1016/j.tics.2023.08.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 07/14/2023] [Accepted: 08/10/2023] [Indexed: 09/18/2023]
Abstract
Network neuroscience has emphasized the connectional properties of neural elements - cells, populations, and regions. This has come at the expense of the anatomical and functional connections that link these elements to one another. A new perspective - namely one that emphasizes 'edges' - may prove fruitful in addressing outstanding questions in network neuroscience. We highlight one recently proposed 'edge-centric' method and review its current applications, merits, and limitations. We also seek to establish conceptual and mathematical links between this method and previously proposed approaches in the network science and neuroimaging literature. We conclude by presenting several avenues for future work to extend and refine existing edge-centric analysis.
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Affiliation(s)
- Richard F Betzel
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA; Cognitive Science Program, Indiana University, Bloomington, IN 47405, USA; Program in Neuroscience, Indiana University, Bloomington, IN 47405, USA; Network Science Institute, Indiana University, Bloomington, IN 47405, USA.
| | - Joshua Faskowitz
- Section on Functional Imaging Methods, National Institute of Mental Health, Bethesda, MD, USA
| | - Olaf Sporns
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA; Cognitive Science Program, Indiana University, Bloomington, IN 47405, USA; Program in Neuroscience, Indiana University, Bloomington, IN 47405, USA; Network Science Institute, Indiana University, Bloomington, IN 47405, USA
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26
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Dembitskaya Y, Boyce AKJ, Idziak A, Pourkhalili Langeroudi A, Arizono M, Girard J, Le Bourdellès G, Ducros M, Sato-Fitoussi M, Ochoa de Amezaga A, Oizel K, Bancelin S, Mercier L, Pfeiffer T, Thompson RJ, Kim SK, Bikfalvi A, Nägerl UV. Shadow imaging for panoptical visualization of brain tissue in vivo. Nat Commun 2023; 14:6411. [PMID: 37828018 PMCID: PMC10570379 DOI: 10.1038/s41467-023-42055-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Accepted: 09/25/2023] [Indexed: 10/14/2023] Open
Abstract
Progress in neuroscience research hinges on technical advances in visualizing living brain tissue with high fidelity and facility. Current neuroanatomical imaging approaches either require tissue fixation (electron microscopy), do not have cellular resolution (magnetic resonance imaging) or only give a fragmented view (fluorescence microscopy). Here, we show how regular light microscopy together with fluorescence labeling of the interstitial fluid in the extracellular space provide comprehensive optical access in real-time to the anatomical complexity and dynamics of living brain tissue at submicron scale. Using several common fluorescence microscopy modalities (confocal, light-sheet and 2-photon microscopy) in mouse organotypic and acute brain slices and the intact mouse brain in vivo, we demonstrate the value of this straightforward 'shadow imaging' approach by revealing neurons, microglia, tumor cells and blood capillaries together with their complete anatomical tissue contexts. In addition, we provide quantifications of perivascular spaces and the volume fraction of the extracellular space of brain tissue in vivo.
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Affiliation(s)
- Yulia Dembitskaya
- Interdisciplinary Institute for Neuroscience, CNRS UMR 5297 and University of Bordeaux, F-33000, Bordeaux, France
| | - Andrew K J Boyce
- Interdisciplinary Institute for Neuroscience, CNRS UMR 5297 and University of Bordeaux, F-33000, Bordeaux, France
- Department of Cell Biology and Anatomy, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Agata Idziak
- Interdisciplinary Institute for Neuroscience, CNRS UMR 5297 and University of Bordeaux, F-33000, Bordeaux, France
| | | | - Misa Arizono
- Interdisciplinary Institute for Neuroscience, CNRS UMR 5297 and University of Bordeaux, F-33000, Bordeaux, France
- Department of Pharmacology, Kyoto University Graduate School of Medicine/The Hakubi Center for Advanced Research, Kyoto University, Kyoto, Japan
| | - Jordan Girard
- Interdisciplinary Institute for Neuroscience, CNRS UMR 5297 and University of Bordeaux, F-33000, Bordeaux, France
| | - Guillaume Le Bourdellès
- Interdisciplinary Institute for Neuroscience, CNRS UMR 5297 and University of Bordeaux, F-33000, Bordeaux, France
| | - Mathieu Ducros
- Université de Bordeaux, CNRS, INSERM, Bordeaux Imaging Center (BIC), UAR 3420, US 4, F-33000, Bordeaux, France
| | - Marie Sato-Fitoussi
- Interdisciplinary Institute for Neuroscience, CNRS UMR 5297 and University of Bordeaux, F-33000, Bordeaux, France
| | - Amaia Ochoa de Amezaga
- Interdisciplinary Institute for Neuroscience, CNRS UMR 5297 and University of Bordeaux, F-33000, Bordeaux, France
| | - Kristell Oizel
- Université de Bordeaux, INSERM, Bordeaux Institute of Oncology (BRIC), U1312, Bat B2, Allée Geoffroy St Hilaire, 33615, Pessac, France
| | - Stephane Bancelin
- Interdisciplinary Institute for Neuroscience, CNRS UMR 5297 and University of Bordeaux, F-33000, Bordeaux, France
| | - Luc Mercier
- Interdisciplinary Institute for Neuroscience, CNRS UMR 5297 and University of Bordeaux, F-33000, Bordeaux, France
| | - Thomas Pfeiffer
- Interdisciplinary Institute for Neuroscience, CNRS UMR 5297 and University of Bordeaux, F-33000, Bordeaux, France
| | - Roger J Thompson
- Department of Cell Biology and Anatomy, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Sun Kwang Kim
- Interdisciplinary Institute for Neuroscience, CNRS UMR 5297 and University of Bordeaux, F-33000, Bordeaux, France
- Department of Physiology, College of Korean Medicine, Kyung Hee University, Seoul, 02447, Korea
| | - Andreas Bikfalvi
- Université de Bordeaux, INSERM, Bordeaux Institute of Oncology (BRIC), U1312, Bat B2, Allée Geoffroy St Hilaire, 33615, Pessac, France
| | - U Valentin Nägerl
- Interdisciplinary Institute for Neuroscience, CNRS UMR 5297 and University of Bordeaux, F-33000, Bordeaux, France.
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27
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Brynildsen JK, Rajan K, Henderson MX, Bassett DS. Network models to enhance the translational impact of cross-species studies. Nat Rev Neurosci 2023; 24:575-588. [PMID: 37524935 PMCID: PMC10634203 DOI: 10.1038/s41583-023-00720-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/17/2023] [Indexed: 08/02/2023]
Abstract
Neuroscience studies are often carried out in animal models for the purpose of understanding specific aspects of the human condition. However, the translation of findings across species remains a substantial challenge. Network science approaches can enhance the translational impact of cross-species studies by providing a means of mapping small-scale cellular processes identified in animal model studies to larger-scale inter-regional circuits observed in humans. In this Review, we highlight the contributions of network science approaches to the development of cross-species translational research in neuroscience. We lay the foundation for our discussion by exploring the objectives of cross-species translational models. We then discuss how the development of new tools that enable the acquisition of whole-brain data in animal models with cellular resolution provides unprecedented opportunity for cross-species applications of network science approaches for understanding large-scale brain networks. We describe how these tools may support the translation of findings across species and imaging modalities and highlight future opportunities. Our overarching goal is to illustrate how the application of network science tools across human and animal model studies could deepen insight into the neurobiology that underlies phenomena observed with non-invasive neuroimaging methods and could simultaneously further our ability to translate findings across species.
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Affiliation(s)
- Julia K Brynildsen
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Kanaka Rajan
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Michael X Henderson
- Parkinson's Disease Center, Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, USA
| | - Dani S Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
- Santa Fe Institute, Santa Fe, NM, USA.
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28
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Guillamón-Vivancos T, Vandael D, Torres D, López-Bendito G, Martini FJ. Mesoscale calcium imaging in vivo: evolution and contribution to developmental neuroscience. Front Neurosci 2023; 17:1210199. [PMID: 37592948 PMCID: PMC10427507 DOI: 10.3389/fnins.2023.1210199] [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: 04/21/2023] [Accepted: 07/14/2023] [Indexed: 08/19/2023] Open
Abstract
Calcium imaging is commonly used to visualize neural activity in vivo. In particular, mesoscale calcium imaging provides large fields of view, allowing for the simultaneous interrogation of neuron ensembles across the neuraxis. In the field of Developmental Neuroscience, mesoscopic imaging has recently yielded intriguing results that have shed new light on the ontogenesis of neural circuits from the first stages of life. We summarize here the technical approaches, basic notions for data analysis and the main findings provided by this technique in the last few years, with a focus on brain development in mouse models. As new tools develop to optimize calcium imaging in vivo, basic principles of neural development should be revised from a mesoscale perspective, that is, taking into account widespread activation of neuronal ensembles across the brain. In the future, combining mesoscale imaging of the dorsal surface of the brain with imaging of deep structures would ensure a more complete understanding of the construction of circuits. Moreover, the combination of mesoscale calcium imaging with other tools, like electrophysiology or high-resolution microscopy, will make up for the spatial and temporal limitations of this technique.
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Affiliation(s)
- Teresa Guillamón-Vivancos
- Instituto de Neurociencias de Alicante, Universidad Miguel Hernández-Consejo Superior de Investigaciones Científicas (UMH-CSIC), Sant Joan d’Alacant, Spain
| | | | | | | | - Francisco J. Martini
- Instituto de Neurociencias de Alicante, Universidad Miguel Hernández-Consejo Superior de Investigaciones Científicas (UMH-CSIC), Sant Joan d’Alacant, Spain
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29
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Dadashkarimi J, Karbasi A, Liang Q, Rosenblatt M, Noble S, Foster M, Rodriguez R, Adkinson B, Ye J, Sun H, Camp C, Farruggia M, Tejavibulya L, Dai W, Jiang R, Pollatou A, Scheinost D. Cross Atlas Remapping via Optimal Transport (CAROT): Creating connectomes for different atlases when raw data is not available. Med Image Anal 2023; 88:102864. [PMID: 37352650 PMCID: PMC10526726 DOI: 10.1016/j.media.2023.102864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 02/10/2023] [Accepted: 05/31/2023] [Indexed: 06/25/2023]
Abstract
Open-source, publicly available neuroimaging datasets - whether from large-scale data collection efforts or pooled from multiple smaller studies - offer unprecedented sample sizes and promote generalization efforts. Releasing data can democratize science, increase the replicability of findings, and lead to discoveries. Partly due to patient privacy, computational, and data storage concerns, researchers typically release preprocessed data with the voxelwise time series parcellated into a map of predefined regions, known as an atlas. However, releasing preprocessed data also limits the choices available to the end-user. This is especially true for connectomics, as connectomes created from different atlases are not directly comparable. Since there exist several atlases with no gold standards, it is unrealistic to have processed, open-source data available from all atlases. Together, these limitations directly inhibit the potential benefits of open-source neuroimaging data. To address these limitations, we introduce Cross Atlas Remapping via Optimal Transport (CAROT) to find a mapping between two atlases. This approach allows data processed from one atlas to be directly transformed into a connectome based on another atlas without the need for raw data access. To validate CAROT, we compare reconstructed connectomes against their original counterparts (i.e., connectomes generated directly from an atlas), demonstrate the utility of transformed connectomes in downstream analyses, and show how a connectome-based predictive model can generalize to publicly available data that was processed with different atlases. Overall, CAROT can reconstruct connectomes from an extensive set of atlases - without needing the raw data - allowing already processed connectomes to be easily reused in a wide range of analyses while eliminating redundant processing efforts. We share this tool as both source code and as a stand-alone web application (http://carotproject.com/).
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Affiliation(s)
| | - Amin Karbasi
- Computer Science Department, Yale University, New Haven, CT, USA; Department of Electrical Engineering, Yale University, New Haven, CT, USA; Department of Statistics & Data Science, Yale University, New Haven, CT, USA
| | - Qinghao Liang
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Matthew Rosenblatt
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Stephanie Noble
- Department of Radiology and Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Maya Foster
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Raimundo Rodriguez
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA
| | - Brendan Adkinson
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA
| | - Jean Ye
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA
| | - Huili Sun
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Chris Camp
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA
| | - Michael Farruggia
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA
| | - Link Tejavibulya
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA
| | - Wei Dai
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Rongtao Jiang
- Department of Radiology and Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Angeliki Pollatou
- Developing Brain Institute, Children's National Hospital, Washington DC, USA
| | - Dustin Scheinost
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA; Department of Statistics & Data Science, Yale University, New Haven, CT, USA; Child Study Center, Yale School of Medicine, New Haven, CT, USA; Department of Radiology and Biomedical Engineering, Yale University, New Haven, CT, USA
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30
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Carvalho J, Fernandes FF, Shemesh N. Extensive topographic remapping and functional sharpening in the adult rat visual pathway upon first visual experience. PLoS Biol 2023; 21:e3002229. [PMID: 37590177 PMCID: PMC10434970 DOI: 10.1371/journal.pbio.3002229] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 07/03/2023] [Indexed: 08/19/2023] Open
Abstract
Understanding the dynamics of stability/plasticity balances during adulthood is pivotal for learning, disease, and recovery from injury. However, the brain-wide topography of sensory remapping remains unknown. Here, using a first-of-its-kind setup for delivering patterned visual stimuli in a rodent magnetic resonance imaging (MRI) scanner, coupled with biologically inspired computational models, we noninvasively mapped brain-wide properties-receptive fields (RFs) and spatial frequency (SF) tuning curves-that were insofar only available from invasive electrophysiology or optical imaging. We then tracked the RF dynamics in the chronic visual deprivation model (VDM) of plasticity and found that light exposure progressively promoted a large-scale topographic remapping in adult rats. Upon light exposure, the initially unspecialized visual pathway progressively evidenced sharpened RFs (smaller and more spatially selective) and enhanced SF tuning curves. Our findings reveal that visual experience following VDM reshapes both structure and function of the visual system and shifts the stability/plasticity balance in adults.
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Affiliation(s)
- Joana Carvalho
- Laboratory of Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Francisca F. Fernandes
- Laboratory of Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Noam Shemesh
- Laboratory of Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
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31
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Greene AS, Horien C, Barson D, Scheinost D, Constable RT. Why is everyone talking about brain state? Trends Neurosci 2023; 46:508-524. [PMID: 37164869 PMCID: PMC10330476 DOI: 10.1016/j.tins.2023.04.001] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 03/17/2023] [Accepted: 04/07/2023] [Indexed: 05/12/2023]
Abstract
The rapid and coordinated propagation of neural activity across the brain provides the foundation for complex behavior and cognition. Technical advances across neuroscience subfields have advanced understanding of these dynamics, but points of convergence are often obscured by semantic differences, creating silos of subfield-specific findings. In this review we describe how a parsimonious conceptualization of brain state as the fundamental building block of whole-brain activity offers a common framework to relate findings across scales and species. We present examples of the diverse techniques commonly used to study brain states associated with physiology and higher-order cognitive processes, and discuss how integration across them will enable a more comprehensive and mechanistic characterization of the neural dynamics that are crucial to survival but are disrupted in disease.
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Affiliation(s)
- Abigail S Greene
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT 06520, USA; MD/PhD program, Yale School of Medicine, New Haven, CT 06520, USA.
| | - Corey Horien
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT 06520, USA; MD/PhD program, Yale School of Medicine, New Haven, CT 06520, USA.
| | - Daniel Barson
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT 06520, USA; MD/PhD program, Yale School of Medicine, New Haven, CT 06520, USA; Department of Neuroscience, Yale School of Medicine, New Haven, CT 06520, USA.
| | - Dustin Scheinost
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT 06520, USA; Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT 06520, USA; Department of Biomedical Engineering, Yale School of Engineering and Applied Science, New Haven, CT 06520, USA; Department of Statistics and Data Science, Yale University, New Haven, CT 06511, USA; Child Study Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - R Todd Constable
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT 06520, USA; Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT 06520, USA; Department of Biomedical Engineering, Yale School of Engineering and Applied Science, New Haven, CT 06520, USA; Department of Neurosurgery, Yale School of Medicine, New Haven, CT 06520, USA
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32
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Shahsavarani S, Thibodeaux DN, Xu W, Kim SH, Lodgher F, Nwokeabia C, Cambareri M, Yagielski AJ, Zhao HT, Handwerker DA, Gonzalez-Castillo J, Bandettini PA, Hillman EMC. Cortex-wide neural dynamics predict behavioral states and provide a neural basis for resting-state dynamic functional connectivity. Cell Rep 2023; 42:112527. [PMID: 37243588 PMCID: PMC10592480 DOI: 10.1016/j.celrep.2023.112527] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 03/14/2023] [Accepted: 05/01/2023] [Indexed: 05/29/2023] Open
Abstract
Although resting-state functional magnetic resonance imaging (fMRI) studies have observed dynamically changing brain-wide networks of correlated activity, fMRI's dependence on hemodynamic signals makes results challenging to interpret. Meanwhile, emerging techniques for real-time recording of large populations of neurons have revealed compelling fluctuations in neuronal activity across the brain that are obscured by traditional trial averaging. To reconcile these observations, we use wide-field optical mapping to simultaneously record pan-cortical neuronal and hemodynamic activity in awake, spontaneously behaving mice. Some components of observed neuronal activity clearly represent sensory and motor function. However, particularly during quiet rest, strongly fluctuating patterns of activity across diverse brain regions contribute greatly to interregional correlations. Dynamic changes in these correlations coincide with changes in arousal state. Simultaneously acquired hemodynamics depict similar brain-state-dependent correlation shifts. These results support a neural basis for dynamic resting-state fMRI, while highlighting the importance of brain-wide neuronal fluctuations in the study of brain state.
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Affiliation(s)
- Somayeh Shahsavarani
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Biomedical Engineering, Columbia University, New York, NY, USA; Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - David N Thibodeaux
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Weihao Xu
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Sharon H Kim
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Fatema Lodgher
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Chinwendu Nwokeabia
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Morgan Cambareri
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Alexis J Yagielski
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Hanzhi T Zhao
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Daniel A Handwerker
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Javier Gonzalez-Castillo
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Peter A Bandettini
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA; Functional MRI Core Facility, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Elizabeth M C Hillman
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Biomedical Engineering, Columbia University, New York, NY, USA; Department of Radiology, Columbia University Irving Medical Center, New York, NY, USA.
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33
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Kim S, Moon HS, Vo TT, Kim CH, Im GH, Lee S, Choi M, Kim SG. Whole-brain mapping of effective connectivity by fMRI with cortex-wide patterned optogenetics. Neuron 2023; 111:1732-1747.e6. [PMID: 37001524 DOI: 10.1016/j.neuron.2023.03.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 11/23/2022] [Accepted: 03/02/2023] [Indexed: 04/03/2023]
Abstract
Functional magnetic resonance imaging (fMRI) with optogenetic neural manipulation is a powerful tool that enables brain-wide mapping of effective functional networks. To achieve flexible manipulation of neural excitation throughout the mouse cortex, we incorporated spatiotemporal programmable optogenetic stimuli generated by a digital micromirror device into an MRI scanner via an optical fiber bundle. This approach offered versatility in space and time in planning the photostimulation pattern, combined with in situ optical imaging and cell-type-specific or circuit-specific genetic targeting in individual mice. Brain-wide effective connectivity obtained by fMRI with optogenetic stimulation of atlas-based cortical regions is generally congruent with anatomically defined axonal tracing data but is affected by the types of anesthetics that act selectively on specific connections. fMRI combined with flexible optogenetics opens a new path to investigate dynamic changes in functional brain states in the same animal through high-throughput brain-wide effective connectivity mapping.
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Affiliation(s)
- Seonghoon Kim
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea; School of Biological Sciences, Seoul National University, Seoul, Republic of Korea
| | - Hyun Seok Moon
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea; Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea; Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Republic of Korea
| | - Thanh Tan Vo
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea; Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea; Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Republic of Korea
| | - Chang-Ho Kim
- School of Biological Sciences, Seoul National University, Seoul, Republic of Korea; Institute of Molecular Biology and Genetics, Seoul National University, Seoul, Republic of Korea
| | - Geun Ho Im
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
| | - Sungho Lee
- School of Biological Sciences, Seoul National University, Seoul, Republic of Korea
| | - Myunghwan Choi
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea; School of Biological Sciences, Seoul National University, Seoul, Republic of Korea; Institute of Molecular Biology and Genetics, Seoul National University, Seoul, Republic of Korea.
| | - Seong-Gi Kim
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea; Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea; Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Republic of Korea.
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34
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Ahanonu B, Crowther A, Kania A, Casillas MR, Basbaum A. Long-term optical imaging of the spinal cord in awake, behaving animals. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.22.541477. [PMID: 37292913 PMCID: PMC10245895 DOI: 10.1101/2023.05.22.541477] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Advances in optical imaging approaches and fluorescent biosensors have enabled an understanding of the spatiotemporal and long-term neural dynamics in the brain of awake animals. However, methodological difficulties and the persistence of post-laminectomy fibrosis have greatly limited similar advances in the spinal cord. To overcome these technical obstacles, we combined in vivo application of fluoropolymer membranes that inhibit fibrosis; a redesigned, cost-effective implantable spinal imaging chamber; and improved motion correction methods that together permit imaging of the spinal cord in awake, behaving mice, for months to over a year. We also demonstrate a robust ability to monitor axons, identify a spinal cord somatotopic map, conduct Ca2+ imaging of neural dynamics in behaving animals responding to pain-provoking stimuli, and observe persistent microglial changes after nerve injury. The ability to couple neural activity and behavior at the spinal cord level will drive insights not previously possible at a key location for somatosensory transmission to the brain.
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Affiliation(s)
- Biafra Ahanonu
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94158, USA
- These authors contributed equally
| | - Andrew Crowther
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94158, USA
- These authors contributed equally
| | - Artur Kania
- Institut de Recherches Cliniques de Montréal (IRCM), Montréal, QC, H2W 1R7, Canada
- Department of Cell Biology and Anatomy, and Division of Experimental Medicine, McGill University, Montréal, QC, H3A 2B2, Canada
| | - Mariela Rosa Casillas
- Neuroscience Graduate Program, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Allan Basbaum
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94158, USA
- Lead Contact
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35
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Nazari M, Karimi Abadchi J, Naghizadeh M, Bermudez-Contreras EJ, McNaughton BL, Tatsuno M, Mohajerani MH. Regional variation in cholinergic terminal activity determines the non-uniform occurrence of cortical slow waves during REM sleep in mice. Cell Rep 2023; 42:112450. [PMID: 37126447 DOI: 10.1016/j.celrep.2023.112450] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 02/17/2023] [Accepted: 04/13/2023] [Indexed: 05/02/2023] Open
Abstract
Sleep consists of two basic stages: non-rapid eye movement (NREM) and rapid eye movement (REM) sleep. NREM sleep is characterized by slow high-amplitude cortical electroencephalogram (EEG) signals, while REM sleep is characterized by desynchronized cortical rhythms. Despite this, recent electrophysiological studies have suggested the presence of slow waves (SWs) in local cortical areas during REM sleep. Electrophysiological techniques, however, have been unable to resolve the regional structure of these activities because of relatively sparse sampling. Here, we map functional gradients in cortical activity during REM sleep using mesoscale imaging in mice and show local SW patterns occurring mainly in somatomotor and auditory cortical regions with minimum presence within the default mode network. The role of the cholinergic system in local desynchronization during REM sleep is also explored by calcium imaging of cholinergic activity within the cortex and analyzing structural data. We demonstrate weaker cholinergic projections and terminal activity in regions exhibiting frequent SWs during REM sleep.
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Affiliation(s)
- Mojtaba Nazari
- Canadian Centre for Behavioral Neuroscience, University of Lethbridge, Lethbridge, AB T1K 3M4, Canada
| | - Javad Karimi Abadchi
- Canadian Centre for Behavioral Neuroscience, University of Lethbridge, Lethbridge, AB T1K 3M4, Canada
| | - Milad Naghizadeh
- Canadian Centre for Behavioral Neuroscience, University of Lethbridge, Lethbridge, AB T1K 3M4, Canada
| | | | - Bruce L McNaughton
- Canadian Centre for Behavioral Neuroscience, University of Lethbridge, Lethbridge, AB T1K 3M4, Canada; Center for Neurobiology of Learning and Memory, Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA 92697, USA
| | - Masami Tatsuno
- Canadian Centre for Behavioral Neuroscience, University of Lethbridge, Lethbridge, AB T1K 3M4, Canada.
| | - Majid H Mohajerani
- Canadian Centre for Behavioral Neuroscience, University of Lethbridge, Lethbridge, AB T1K 3M4, Canada.
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36
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Vafaii H, Mandino F, Desrosiers-Grégoire G, O’Connor D, 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. RESEARCH SQUARE 2023:rs.3.rs-2823802. [PMID: 37162818 PMCID: PMC10168440 DOI: 10.21203/rs.3.rs-2823802/v1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
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 employed wide-field Ca2+ imaging simultaneously with fMRI-BOLD in mice expressing GCaMP6f in excitatory neurons. We determined cortical networks discovered by each modality using a mixed-membership algorithm to test the hypothesis that functional networks are overlapping rather than disjoint. Our results show that multiple BOLD networks are detected via Ca2+ signals; there is considerable network overlap (both modalities); networks determined by low-frequency Ca2+ signals are only modestly more similar to BOLD networks; and, despite similarities, important differences are detected across modalities (e.g., brain region "network diversity"). In conclusion, Ca2+ imaging uncovered overlapping functional cortical organization in the mouse that reflected 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
- Comp. Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health Univ. 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, 06511, 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
| | - Mallar Chakravarty
- Comp. Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health Univ. 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, 06511, USA
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, 06510, USA
| | - Evelyn MR. Lake
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 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
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37
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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: 36] [Impact Index Per Article: 36.0] [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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38
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Sunil S, Jiang J, Shah S, Kura S, Kilic K, Erdener SE, Ayata C, Devor A, Boas DA. Neurovascular coupling is preserved in chronic stroke recovery after targeted photothrombosis. Neuroimage Clin 2023; 38:103377. [PMID: 36948140 PMCID: PMC10034641 DOI: 10.1016/j.nicl.2023.103377] [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: 10/13/2022] [Revised: 03/07/2023] [Accepted: 03/09/2023] [Indexed: 03/17/2023]
Abstract
Functional neuroimaging, which measures hemodynamic responses to brain activity, has great potential for monitoring recovery in stroke patients and guiding rehabilitation during recovery. However, hemodynamic responses after stroke are almost always altered relative to responses in healthy subjects and it is still unclear if these alterations reflect the underlying brain physiology or if the alterations are purely due to vascular injury. In other words, we do not know the effect of stroke on neurovascular coupling and are therefore limited in our ability to use functional neuroimaging to accurately interpret stroke pathophysiology. To address this challenge, we simultaneously captured neural activity, through fluorescence calcium imaging, and hemodynamics, through intrinsic optical signal imaging, during longitudinal stroke recovery. Our data suggest that neurovascular coupling was preserved in the chronic phase of recovery (2 weeks and 4 weeks post-stoke) and resembled pre-stroke neurovascular coupling. This indicates that functional neuroimaging faithfully represents the underlying neural activity in chronic stroke. Further, neurovascular coupling in the sub-acute phase of stroke recovery was predictive of long-term behavioral outcomes. Stroke also resulted in increases in global brain oscillations, which showed distinct patterns between neural activity and hemodynamics. Increased neural excitability in the contralesional hemisphere was associated with increased contralesional intrahemispheric connectivity. Additionally, sub-acute increases in hemodynamic oscillations were associated with improved sensorimotor outcomes. Collectively, these results support the use of hemodynamic measures of brain activity post-stroke for predicting functional and behavioral outcomes.
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Affiliation(s)
- Smrithi Sunil
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA.
| | - John Jiang
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Shashwat Shah
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Sreekanth Kura
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Kivilcim Kilic
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Sefik Evren Erdener
- Institute of Neurological Sciences and Psychiatry, Hacettepe University, Ankara, Turkey
| | - Cenk Ayata
- Departments of Neurology and Radiology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Anna Devor
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA 02114, USA
| | - David A Boas
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA.
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39
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Ren W, Deán-Ben XL, Skachokova Z, Augath MA, Ni R, Chen Z, Razansky D. Monitoring mouse brain perfusion with hybrid magnetic resonance optoacoustic tomography. BIOMEDICAL OPTICS EXPRESS 2023; 14:1192-1204. [PMID: 36950237 PMCID: PMC10026577 DOI: 10.1364/boe.482205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 01/10/2023] [Accepted: 01/10/2023] [Indexed: 06/18/2023]
Abstract
Progress in brain research critically depends on the development of next-generation multi-modal imaging tools capable of capturing transient functional events and multiplexed contrasts noninvasively and concurrently, thus enabling a holistic view of dynamic events in vivo. Here we report on a hybrid magnetic resonance and optoacoustic tomography (MROT) system for murine brain imaging, which incorporates an MR-compatible spherical matrix array transducer and fiber-based light illumination into a 9.4 T small animal scanner. An optimized radiofrequency coil has further been devised for whole-brain interrogation. System's utility is showcased by acquiring complementary angiographic and soft tissue anatomical contrast along with simultaneous dual-modality visualization of contrast agent dynamics in vivo.
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Affiliation(s)
- Wuwei Ren
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich 8052, Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Zurich 8093, Switzerland
- Present address: School of Information Science and Technology, ShanghaiTech University, Shanghai 201210, China
- equal contribution
| | - Xosé Luís Deán-Ben
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich 8052, Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Zurich 8093, Switzerland
- equal contribution
| | - Zhiva Skachokova
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich 8052, Switzerland
| | - Mark-Aurel Augath
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich 8052, Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Zurich 8093, Switzerland
| | - Ruiqing Ni
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich 8052, Switzerland
- Zurich Neuroscience Center, University of Zurich and ETH Zurich, Zurich 8093, Switzerland
- Institute for Regenerative Medicine, Faculty of Medicine, University of Zurich, Zurich 8952, Switzerland
| | - Zhenyue Chen
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich 8052, Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Zurich 8093, Switzerland
| | - Daniel Razansky
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich 8052, Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Zurich 8093, Switzerland
- Zurich Neuroscience Center, University of Zurich and ETH Zurich, Zurich 8093, Switzerland
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Gozzi A, Zerbi V. Modeling Brain Dysconnectivity in Rodents. Biol Psychiatry 2023; 93:419-429. [PMID: 36517282 DOI: 10.1016/j.biopsych.2022.09.008] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 08/19/2022] [Accepted: 09/10/2022] [Indexed: 02/04/2023]
Abstract
Altered or atypical functional connectivity as measured with functional magnetic resonance imaging (fMRI) is a hallmark feature of brain connectopathy in psychiatric, developmental, and neurological disorders. However, the biological underpinnings and etiopathological significance of this phenomenon remain unclear. The recent development of MRI-based techniques for mapping brain function in rodents provides a powerful platform to uncover the determinants of functional (dys)connectivity, whether they are genetic mutations, environmental risk factors, or specific cellular and circuit dysfunctions. Here, we summarize the recent contribution of rodent fMRI toward a deeper understanding of network dysconnectivity in developmental and psychiatric disorders. We highlight substantial correspondences in the spatiotemporal organization of rodent and human fMRI networks, supporting the translational relevance of this approach. We then show how this research platform might help us comprehend the importance of connectional heterogeneity in complex brain disorders and causally relate multiscale pathogenic contributors to functional dysconnectivity patterns. Finally, we explore how perturbational techniques can be used to dissect the fundamental aspects of fMRI coupling and reveal the causal contribution of neuromodulatory systems to macroscale network activity, as well as its altered dynamics in brain diseases. These examples outline how rodent functional imaging is poised to advance our understanding of the bases and determinants of human functional dysconnectivity.
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Affiliation(s)
- Alessandro Gozzi
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, Rovereto, Italy.
| | - Valerio Zerbi
- Neuro-X Institute, School of Engineering, École polytechnique fédérale de Lausanne, Lausanne, Switzerland; CIBM Center for Biomedical Imaging, Lausanne, Switzerland.
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41
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Chao THH, Lee B, Hsu LM, Cerri DH, Zhang WT, Wang TWW, Ryali S, Menon V, Shih YYI. Neuronal dynamics of the default mode network and anterior insular cortex: Intrinsic properties and modulation by salient stimuli. SCIENCE ADVANCES 2023; 9:eade5732. [PMID: 36791185 PMCID: PMC9931216 DOI: 10.1126/sciadv.ade5732] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 01/19/2023] [Indexed: 05/26/2023]
Abstract
The default mode network (DMN) is critical for self-referential mental processes, and its dysfunction is implicated in many neuropsychiatric disorders. However, the neurophysiological properties and task-based functional organization of the rodent DMN are poorly understood, limiting its translational utility. Here, we combine fiber photometry with functional magnetic resonance imaging (fMRI) and computational modeling to characterize dynamics of putative rat DMN nodes and their interactions with the anterior insular cortex (AI) of the salience network. Our analysis revealed neuronal activity changes in AI and DMN nodes preceding fMRI-derived DMN activations and cyclical transitions between brain network states. Furthermore, we demonstrate that salient oddball stimuli suppress the DMN and enhance AI neuronal activity and that the AI causally inhibits the retrosplenial cortex, a prominent DMN node. These findings elucidate the neurophysiological foundations of the rodent DMN, its spatiotemporal dynamical properties, and modulation by salient stimuli, paving the way for future translational studies.
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Affiliation(s)
- Tzu-Hao Harry Chao
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Byeongwook Lee
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Li-Ming Hsu
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Domenic Hayden Cerri
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Wei-Ting Zhang
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Tzu-Wen Winnie Wang
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Srikanth Ryali
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Vinod Menon
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
- Wu Tsai Neuroscience Institute, Stanford University, Stanford, CA, USA
| | - Yen-Yu Ian Shih
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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42
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Cabral J, Fernandes FF, Shemesh N. Intrinsic macroscale oscillatory modes driving long range functional connectivity in female rat brains detected by ultrafast fMRI. Nat Commun 2023; 14:375. [PMID: 36746938 PMCID: PMC9902553 DOI: 10.1038/s41467-023-36025-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Accepted: 01/12/2023] [Indexed: 02/08/2023] Open
Abstract
Spontaneous fluctuations in functional magnetic resonance imaging (fMRI) signals correlate across distant brain areas, shaping functionally relevant intrinsic networks. However, the generative mechanism of fMRI signal correlations, and in particular the link with locally-detected ultra-slow oscillations, are not fully understood. To investigate this link, we record ultrafast ultrahigh field fMRI signals (9.4 Tesla, temporal resolution = 38 milliseconds) from female rats across three anesthesia conditions. Power at frequencies extending up to 0.3 Hz is detected consistently across rat brains and is modulated by anesthesia level. Principal component analysis reveals a repertoire of modes, in which transient oscillations organize with fixed phase relationships across distinct cortical and subcortical structures. Oscillatory modes are found to vary between conditions, resonating at faster frequencies under medetomidine sedation and reducing both in number, frequency, and duration with the addition of isoflurane. Peaking in power within clear anatomical boundaries, these oscillatory modes point to an emergent systemic property. This work provides additional insight into the origin of oscillations detected in fMRI and the organizing principles underpinning spontaneous long-range functional connectivity.
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Affiliation(s)
- Joana Cabral
- Preclinical MRI Lab, Champalimaud Research, Champalimaud Foundation, Lisbon, Portugal.
- Life and Health Sciences Research Institute, School of Medicine, University of Minho, Braga, Portugal.
- ICVS/3B's - Portuguese Government Associate Laboratory, Braga/Guimarães, Portugal.
| | - Francisca F Fernandes
- Preclinical MRI Lab, Champalimaud Research, Champalimaud Foundation, Lisbon, Portugal
| | - Noam Shemesh
- Preclinical MRI Lab, Champalimaud Research, Champalimaud Foundation, Lisbon, Portugal.
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Nietz AK, Streng ML, Popa LS, Carter RE, Flaherty EB, Aronson JD, Ebner TJ. To be and not to be: wide-field Ca2+ imaging reveals neocortical functional segmentation combines stability and flexibility. Cereb Cortex 2023:7024718. [PMID: 36734268 DOI: 10.1093/cercor/bhac523] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 12/09/2022] [Accepted: 12/10/2022] [Indexed: 02/04/2023] Open
Abstract
The stability and flexibility of the functional parcellation of the cerebral cortex is fundamental to how familiar and novel information is both represented and stored. We leveraged new advances in Ca2+ sensors and microscopy to understand the dynamics of functional segmentation in the dorsal cerebral cortex. We performed wide-field Ca2+ imaging in head-fixed mice and used spatial independent component analysis (ICA) to identify independent spatial sources of Ca2+ fluorescence. The imaging data were evaluated over multiple timescales and discrete behaviors including resting, walking, and grooming. When evaluated over the entire dataset, a set of template independent components (ICs) were identified that were common across behaviors. Template ICs were present across a range of timescales, from days to 30 seconds, although with lower occurrence probability at shorter timescales, highlighting the stability of the functional segmentation. Importantly, unique ICs emerged at the shorter duration timescales that could act to transiently refine the cortical network. When data were evaluated by behavior, both common and behavior-specific ICs emerged. Each behavior is composed of unique combinations of common and behavior-specific ICs. These observations suggest that cerebral cortical functional segmentation exhibits considerable spatial stability over time and behaviors while retaining the flexibility for task-dependent reorganization.
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Affiliation(s)
- Angela K Nietz
- Department of Neuroscience, University of Minnesota, 2001 Sixth Street S.E., Minneapolis 55455, MN, United States
| | - Martha L Streng
- Department of Neuroscience, University of Minnesota, 2001 Sixth Street S.E., Minneapolis 55455, MN, United States
| | - Laurentiu S Popa
- Department of Neuroscience, University of Minnesota, 2001 Sixth Street S.E., Minneapolis 55455, MN, United States
| | - Russell E Carter
- Department of Neuroscience, University of Minnesota, 2001 Sixth Street S.E., Minneapolis 55455, MN, United States
| | - Evelyn B Flaherty
- Department of Neuroscience, University of Minnesota, 2001 Sixth Street S.E., Minneapolis 55455, MN, United States
| | - Justin D Aronson
- Department of Neuroscience, University of Minnesota, 2001 Sixth Street S.E., Minneapolis 55455, MN, United States
| | - Timothy J Ebner
- Department of Neuroscience, University of Minnesota, 2001 Sixth Street S.E., Minneapolis 55455, MN, United States
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Real-time denoising enables high-sensitivity fluorescence time-lapse imaging beyond the shot-noise limit. Nat Biotechnol 2023; 41:282-292. [PMID: 36163547 PMCID: PMC9931589 DOI: 10.1038/s41587-022-01450-8] [Citation(s) in RCA: 34] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 07/29/2022] [Indexed: 11/09/2022]
Abstract
A fundamental challenge in fluorescence microscopy is the photon shot noise arising from the inevitable stochasticity of photon detection. Noise increases measurement uncertainty and limits imaging resolution, speed and sensitivity. To achieve high-sensitivity fluorescence imaging beyond the shot-noise limit, we present DeepCAD-RT, a self-supervised deep learning method for real-time noise suppression. Based on our previous framework DeepCAD, we reduced the number of network parameters by 94%, memory consumption by 27-fold and processing time by a factor of 20, allowing real-time processing on a two-photon microscope. A high imaging signal-to-noise ratio can be acquired with tenfold fewer photons than in standard imaging approaches. We demonstrate the utility of DeepCAD-RT in a series of photon-limited experiments, including in vivo calcium imaging of mice, zebrafish larva and fruit flies, recording of three-dimensional (3D) migration of neutrophils after acute brain injury and imaging of 3D dynamics of cortical ATP release. DeepCAD-RT will facilitate the morphological and functional interrogation of biological dynamics with a minimal photon budget.
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Chen Z, Gezginer I, Augath M, Liu Y, Ni R, Deán‐Ben XL, Razansky D. Simultaneous Functional Magnetic Resonance and Optoacoustic Imaging of Brain-Wide Sensory Responses in Mice. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2205191. [PMID: 36437110 PMCID: PMC9875624 DOI: 10.1002/advs.202205191] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 10/26/2022] [Indexed: 05/30/2023]
Abstract
Functional magnetic resonance imaging (fMRI) has massively contributed to the understanding of mammalian brain function. However, the origin and interpretation of the blood oxygen level-dependent (BOLD) signals retrieved by fMRI remain highly disputed. This article reports on the development of a fully hybridized system enabling concurrent functional magnetic resonance optoacoustic tomography (MROT) measurements of stimulus-evoked brain-wide sensory responses in mice. The highly complementary angiographic and soft tissue contrasts of both modalities along with simultaneous multi-parametric readings of stimulus-evoked hemodynamic responses are leveraged in order to establish unequivocal links between the various counteracting physiological and metabolic processes in the brain. The results indicate that the BOLD signals are highly correlated, both spatially and temporally, with the total hemoglobin readings resolved with volumetric multi-spectral optoacoustic tomography. Furthermore, the differential oxygenated and deoxygenated hemoglobin optoacoustic readings exhibit superior sensitivity as compared to the BOLD signals when detecting stimulus-evoked hemodynamic responses. The fully hybridized MROT approach greatly expands the neuroimaging toolset to comprehensively study neurovascular and neurometabolic coupling mechanisms and related diseases.
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Affiliation(s)
- Zhenyue Chen
- Institute for Biomedical Engineering and Institute of Pharmacology and ToxicologyFaculty of MedicineUniversity of ZurichZurich8057Switzerland
- Institute for Biomedical EngineeringDepartment of Information Technology and Electrical EngineeringETH ZurichZurich8093Switzerland
| | - Irmak Gezginer
- Institute for Biomedical Engineering and Institute of Pharmacology and ToxicologyFaculty of MedicineUniversity of ZurichZurich8057Switzerland
- Institute for Biomedical EngineeringDepartment of Information Technology and Electrical EngineeringETH ZurichZurich8093Switzerland
| | - Mark‐Aurel Augath
- Institute for Biomedical Engineering and Institute of Pharmacology and ToxicologyFaculty of MedicineUniversity of ZurichZurich8057Switzerland
- Institute for Biomedical EngineeringDepartment of Information Technology and Electrical EngineeringETH ZurichZurich8093Switzerland
| | - Yu‐Hang Liu
- Institute for Biomedical Engineering and Institute of Pharmacology and ToxicologyFaculty of MedicineUniversity of ZurichZurich8057Switzerland
- Institute for Biomedical EngineeringDepartment of Information Technology and Electrical EngineeringETH ZurichZurich8093Switzerland
| | - Ruiqing Ni
- Institute for Biomedical Engineering and Institute of Pharmacology and ToxicologyFaculty of MedicineUniversity of ZurichZurich8057Switzerland
- Institute for Biomedical EngineeringDepartment of Information Technology and Electrical EngineeringETH ZurichZurich8093Switzerland
- Zurich Neuroscience Center (ZNZ)ZurichSwitzerland
| | - Xosé Luís Deán‐Ben
- Institute for Biomedical Engineering and Institute of Pharmacology and ToxicologyFaculty of MedicineUniversity of ZurichZurich8057Switzerland
- Institute for Biomedical EngineeringDepartment of Information Technology and Electrical EngineeringETH ZurichZurich8093Switzerland
| | - Daniel Razansky
- Institute for Biomedical Engineering and Institute of Pharmacology and ToxicologyFaculty of MedicineUniversity of ZurichZurich8057Switzerland
- Institute for Biomedical EngineeringDepartment of Information Technology and Electrical EngineeringETH ZurichZurich8093Switzerland
- Zurich Neuroscience Center (ZNZ)ZurichSwitzerland
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Ramandi D, Michelson NJ, Raymond LA, Murphy TH. Chronic multiscale resolution of mouse brain networks using combined mesoscale cortical imaging and subcortical fiber photometry. NEUROPHOTONICS 2023; 10:015001. [PMID: 36694618 PMCID: PMC9867602 DOI: 10.1117/1.nph.10.1.015001] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 01/03/2023] [Indexed: 06/17/2023]
Abstract
SIGNIFICANCE Genetically encoded optical probes to image calcium levels in neurons in vivo are used widely as a real-time measure of neuronal activity in the brain. Mesoscale calcium imaging through a cranial window provides a method of studying the interaction of circuit activity between cortical areas but lacks access to subcortical regions. AIM We have developed an optical and surgical preparation that preserves wide-field imaging of the cortical surface while also permitting access to specific subcortical networks. APPROACH This was achieved using an optical fiber implanted in the striatum, along with a bilateral widefield cranial window, enabling simultaneous mesoscale cortical imaging and subcortical fiber photometry recording of calcium signals in a transgenic animal expressing GCaMP. Subcortical signals were collected from the dorsal regions of the striatum. We combined this approach with multiple sensory-motor tasks, including specific auditory and visual stimulation, and video monitoring of animal movements and pupillometry during head-fixed behaviors. RESULTS We found high correlations between cortical and striatal activity in response to sensory stimulation or movement. Furthermore, spontaneous activity recordings revealed that specific motifs of cortical activity are correlated with presynaptic activity recorded in the striatum, enabling us to select for corticostriatal activity motifs. CONCLUSION We believe that this method can be utilized to reveal not only global patterns but also cell-specific connectivity that provides insight into corticobasal ganglia circuit organization.
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Affiliation(s)
- Daniel Ramandi
- University of British Columbia, Djavad Mowafaghian Centre for Brain Health, Department of Psychiatry, Vancouver, British Columbia, Canada
| | - Nicholas J. Michelson
- University of British Columbia, Djavad Mowafaghian Centre for Brain Health, Department of Psychiatry, Vancouver, British Columbia, Canada
| | - Lynn A. Raymond
- University of British Columbia, Djavad Mowafaghian Centre for Brain Health, Department of Psychiatry, Vancouver, British Columbia, Canada
| | - Timothy H. Murphy
- University of British Columbia, Djavad Mowafaghian Centre for Brain Health, Department of Psychiatry, Vancouver, British Columbia, Canada
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47
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Lambers H, Wachsmuth L, Lippe C, Faber C. The impact of vasomotion on analysis of rodent fMRI data. Front Neurosci 2023; 17:1064000. [PMID: 36908777 PMCID: PMC9998505 DOI: 10.3389/fnins.2023.1064000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 02/06/2023] [Indexed: 03/14/2023] Open
Abstract
Introduction Small animal fMRI is an essential part of translational research in the cognitive neurosciences. Due to small dimensions and animal physiology preclinical fMRI is prone to artifacts that may lead to misinterpretation of the data. To reach unbiased translational conclusions, it is, therefore, crucial to identify potential sources of experimental noise and to develop correction methods for contributions that cannot be avoided such as physiological noise. Aim of this study was to assess origin and prevalence of hemodynamic oscillations (HDO) in preclinical fMRI in rat, as well as their impact on data analysis. Methods Following the development of algorithms for HDO detection and suppression, HDO prevalence in fMRI measurements was investigated for different anesthetic regimens, comprising isoflurane and medetomidine, and for both gradient echo and spin echo fMRI sequences. In addition to assessing the effect of vasodilation on HDO, it was studied if HDO have a direct neuronal correlate using local field potential (LFP) recordings. Finally, the impact of HDO on analysis of fMRI data was assessed, studying both the impact on calculation of activation maps as well as the impact on brain network analysis. Overall, 303 fMRI measurements and 32 LFP recordings were performed in 71 rats. Results In total, 62% of the fMRI measurements showed HDO with a frequency of (0.20 ± 0.02) Hz. This frequent occurrence indicated that HDO cannot be generally neglected in fMRI experiments. Using the developed algorithms, HDO were detected with a specificity of 95%, and removed efficiently from the signal time courses. HDO occurred brain-wide under vasoconstrictive conditions in both small and large blood vessels. Vasodilation immediately interrupted HDO, which, however, returned within 1 h under vasoconstrictive conditions. No direct neuronal correlate of HDO was observed in LFP recordings. HDO significantly impacted analysis of fMRI data, leading to altered cluster sizes and F-values for activated voxels, as well as altered brain networks, when comparing data with and without HDO. Discussion We therefore conclude that HDO are caused by vasomotion under certain anesthetic conditions and should be corrected during fMRI data analysis to avoid bias.
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Affiliation(s)
| | - Lydia Wachsmuth
- Clinic of Radiology, University of Münster, Münster, Germany
| | - Chris Lippe
- Clinic of Radiology, University of Münster, Münster, Germany
| | - Cornelius Faber
- Clinic of Radiology, University of Münster, Münster, Germany
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Mishra SK, Herman P, Crair M, Constable RT, Walsh JJ, Akif A, Verhagen JV, Hyder F. Fluorescently-tagged magnetic protein nanoparticles for high-resolution optical and ultra-high field magnetic resonance dual-modal cerebral angiography. NANOSCALE 2022; 14:17770-17788. [PMID: 36437785 PMCID: PMC9850399 DOI: 10.1039/d2nr04878g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Extremely small paramagnetic iron oxide nanoparticles (FeMNPs) (<5 nm) can enhance positive magnetic resonance imaging (MRI) contrast by shortening the longitudinal relaxation time of water (T1), but these nanoparticles experience rapid renal clearance. Here, magnetic protein nanoparticles (MPNPs) are synthesized from protein-conjugated citric acid coated FeMNPs (c-FeMNPs) without loss of the T1 MRI properties and tagged with fluorescent dye (f-MPNPs) for optical cerebrovascular imaging. The c-FeMNPs shows average size 3.8 ± 0.7 nm with T1 relaxivity (r1) of 1.86 mM-1 s-1 and transverse/longitudinal relaxivity ratio (r2/r1) of 2.53 at 11.7 T. The f-MPNPs show a higher r1 value of 2.18 mM-1 s-1 and r2/r1 ratio of 2.88 at 11.7 T, which generates excellent positive MRI contrast. In vivo cerebral angiography with f-MPNPs enables detailed microvascular contrast enhancement for differentiation of major blood vessels of murine brain, which corresponds well with whole brain three-dimensional time-of-flight MRI angiograms (17 min imaging time with 60 ms repetition time and 40 μm isotropic voxels). The real-time fluorescence angiography enables unambiguous detection of brain capillaries with diameter < 40 μm. Biodistribution examination revealed that f-MPNPs were safely cleared by the organs like the liver, spleen, and kidneys within a day after injection. Blood biochemical assays demonstrated no risk of iron overload in both rats and mice. With hybrid neuroimaging technologies (e.g., MRI-optical) on the rise, f-MPNPs built on this platform can generate exciting neuroscience applications.
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Affiliation(s)
- Sandeep K Mishra
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA
- The Anlyan Center (TAC), Magnetic Resonance Research Center, Yale University, 300 Cedar Street, New Haven, CT, 06520, USA.
| | - Peter Herman
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA
- The Anlyan Center (TAC), Magnetic Resonance Research Center, Yale University, 300 Cedar Street, New Haven, CT, 06520, USA.
| | - Michael Crair
- Department of Neuroscience, Yale University, New Haven, CT, USA
| | - R Todd Constable
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA
- Department of Neurosurgery, Yale University, New Haven, CT, USA
| | - John J Walsh
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Adil Akif
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Justus V Verhagen
- Department of Neuroscience, Yale University, New Haven, CT, USA
- The John B. Pierce Laboratory, New Haven, CT, USA
| | - Fahmeed Hyder
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA
- The Anlyan Center (TAC), Magnetic Resonance Research Center, Yale University, 300 Cedar Street, New Haven, CT, 06520, USA.
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
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O'Connor D, Mandino F, Shen X, Horien C, Ge X, Herman P, Hyder F, Crair M, Papademetris X, Lake E, Constable RT. Functional network properties derived from wide-field calcium imaging differ with wakefulness and across cell type. Neuroimage 2022; 264:119735. [PMID: 36347441 PMCID: PMC9808917 DOI: 10.1016/j.neuroimage.2022.119735] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 10/21/2022] [Accepted: 11/04/2022] [Indexed: 11/08/2022] Open
Abstract
To improve 'bench-to-bedside' translation, it is integral that knowledge flows bidirectionally-from animal models to humans, and vice versa. This requires common analytical frameworks, as well as open software and data sharing practices. We share a new pipeline (and test dataset) for the preprocessing of wide-field optical fluorescence imaging data-an emerging mode applicable in animal models-as well as results from a functional connectivity and graph theory analysis inspired by recent work in the human neuroimaging field. The approach is demonstrated using a dataset comprised of two test-cases: (1) data from animals imaged during awake and anesthetized conditions with excitatory neurons labeled, and (2) data from awake animals with different genetically encoded fluorescent labels that target either excitatory neurons or inhibitory interneuron subtypes. Both seed-based connectivity and graph theory measures (global efficiency, transitivity, modularity, and characteristic path-length) are shown to be useful in quantifying differences between wakefulness states and cell populations. Wakefulness state and cell type show widespread effects on canonical network connectivity with variable frequency band dependence. Differences between excitatory neurons and inhibitory interneurons are observed, with somatostatin expressing inhibitory interneurons emerging as notably dissimilar from parvalbumin and vasoactive polypeptide expressing cells. In sum, we demonstrate that our pipeline can be used to examine brain state and cell-type differences in mesoscale imaging data, aiding translational neuroscience efforts. In line with open science practices, we freely release the pipeline and data to encourage other efforts in the community.
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Affiliation(s)
- D O'Connor
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA.
| | - F Mandino
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - X Shen
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - C Horien
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, USA
| | - X Ge
- Department of Physiology, School of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - P Herman
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - F Hyder
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA; Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - M Crair
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA; Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT, USA; Department of Ophthalmology and Visual Science, Yale School of Medicine, New Haven, CT, USA
| | - X Papademetris
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA; Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Emr Lake
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - R T Constable
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA; Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, USA; Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
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50
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Wang Y, LeDue JM, Murphy TH. Multiscale imaging informs translational mouse modeling of neurological disease. Neuron 2022; 110:3688-3710. [PMID: 36198319 DOI: 10.1016/j.neuron.2022.09.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 05/26/2022] [Accepted: 09/06/2022] [Indexed: 11/05/2022]
Abstract
Multiscale neurophysiology reveals that simple motor actions are associated with changes in neuronal firing in virtually every brain region studied. Accordingly, the assessment of focal pathology such as stroke or progressive neurodegenerative diseases must also extend widely across brain areas. To derive mechanistic information through imaging, multiple resolution scales and multimodal factors must be included, such as the structure and function of specific neurons and glial cells and the dynamics of specific neurotransmitters. Emerging multiscale methods in preclinical animal studies that span micro- to macroscale examinations fill this gap, allowing a circuit-based understanding of pathophysiological mechanisms. Combined with high-performance computation and open-source data repositories, these emerging multiscale and large field-of-view techniques include live functional ultrasound, multi- and single-photon wide-scale light microscopy, video-based miniscopes, and tissue-penetrating fiber photometry, as well as variants of post-mortem expansion microscopy. We present these technologies and outline use cases and data pipelines to uncover new knowledge within animal models of stroke, Alzheimer's disease, and movement disorders.
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Affiliation(s)
- Yundi Wang
- University of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Detwiller Pavilion, 2255 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada; Djavad Mowafaghian Centre for Brain Health, University of British Columbia, 2215 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada
| | - Jeffrey M LeDue
- University of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Detwiller Pavilion, 2255 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada; Djavad Mowafaghian Centre for Brain Health, University of British Columbia, 2215 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada
| | - Timothy H Murphy
- University of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Detwiller Pavilion, 2255 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada; Djavad Mowafaghian Centre for Brain Health, University of British Columbia, 2215 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada.
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