1
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Mandino F, Shen X, Desrosiers-Grégoire G, O'Connor D, Mukherjee B, Owens A, Qu A, Onofrey J, Papademetris X, Chakravarty MM, Strittmatter SM, Lake EMR. Aging-dependent loss of functional connectivity in a mouse model of Alzheimer's disease and reversal by mGluR5 modulator. Mol Psychiatry 2025; 30:1730-1745. [PMID: 39424929 PMCID: PMC12015114 DOI: 10.1038/s41380-024-02779-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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Revised: 09/26/2024] [Accepted: 09/30/2024] [Indexed: 10/21/2024]
Abstract
Amyloid accumulation in Alzheimer's disease (AD) is associated with synaptic damage and altered connectivity in brain networks. While measures of amyloid accumulation and biochemical changes in mouse models have utility for translational studies of certain therapeutics, preclinical analysis of altered brain connectivity using clinically relevant fMRI measures has not been well developed for agents intended to improve neural networks. Here, we conduct a longitudinal study in a double knock-in mouse model for AD (AppNL-G-F/hMapt), monitoring brain connectivity by means of resting-state fMRI. While the 4-month-old AD mice are indistinguishable from wild-type controls (WT), decreased connectivity in the default-mode network is significant for the AD mice relative to WT mice by 6 months of age and is pronounced by 9 months of age. In a second cohort of 20-month-old mice with persistent functional connectivity deficits for AD relative to WT, we assess the impact of two-months of oral treatment with a silent allosteric modulator of mGluR5 (BMS-984923/ALX001) known to rescue synaptic density. Functional connectivity deficits in the aged AD mice are reversed by the mGluR5-directed treatment. The longitudinal application of fMRI has enabled us to define the preclinical time trajectory of AD-related changes in functional connectivity, and to demonstrate a translatable metric for monitoring disease emergence, progression, and response to synapse-rescuing treatment.
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Affiliation(s)
- Francesca Mandino
- 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
| | - Gabriel Desrosiers-Grégoire
- Computational 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, 06511, USA
| | - Bandhan Mukherjee
- Cellular Neuroscience, Neurodegeneration and Repair Program, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Ashley Owens
- Cellular Neuroscience, Neurodegeneration and Repair Program, Yale School of Medicine, New Haven, CT, 06520, USA
| | - An Qu
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - John Onofrey
- 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 Urology, 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, 06511, USA
- Department of Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, CT, 06520, USA
- Wu Tsai Institute, Yale University, New Haven, CT, 06510, USA
| | - M Mallar Chakravarty
- Computational 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
| | - Stephen M Strittmatter
- Cellular Neuroscience, Neurodegeneration and Repair Program, Yale School of Medicine, New Haven, CT, 06520, USA.
- Wu Tsai Institute, Yale University, New Haven, CT, 06510, USA.
- Department of Neurology, Yale University School of Medicine, New Haven, CT, 06510, USA.
- Kavli Institute of Neuroscience, Yale University School of Medicine, New Haven, CT, 06510, USA.
- Department of Neuroscience, Yale University 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, 06511, USA.
- Wu Tsai Institute, Yale University, New Haven, CT, 06510, USA.
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2
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Mandino F, Horien C, Shen X, Desrosiers-Grégoire G, Luo W, Markicevic M, Constable RT, Papademetris X, Chakravarty MM, Betzel RF, Lake EMR. Multimodal identification of the mouse brain using simultaneous Ca 2+ imaging and fMRI. Commun Biol 2025; 8:665. [PMID: 40287579 PMCID: PMC12033268 DOI: 10.1038/s42003-025-08037-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2024] [Accepted: 04/02/2025] [Indexed: 04/29/2025] Open
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 prevailing modality in this field-blood-oxygen-level-dependent (BOLD) 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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Affiliation(s)
- Francesca Mandino
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA.
| | - Corey Horien
- Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, CT, USA
- MD/PhD program, Yale University School of Medicine, New Haven, CT, USA
| | - Xilin Shen
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Gabriel Desrosiers-Grégoire
- Computational Brain Anatomy Laboratory, Douglas Mental Health University Institute, Montreal, QC, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada
| | - Wendy Luo
- Department of Biomedical Engineering, Yale University School of Medicine, New Haven, CT, USA
| | - Marija Markicevic
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - R Todd Constable
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, CT, USA
- MD/PhD program, Yale University School of Medicine, New Haven, CT, USA
- Department of Biomedical Engineering, Yale University School of Medicine, New Haven, CT, USA
- Department of Neurosurgery, Yale University School of Medicine, New Haven, CT, USA
| | - Xenophon Papademetris
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Department of Biomedical Engineering, Yale University School of Medicine, New Haven, CT, USA
- Deparment of Biomedical Informatics and Data Science, Yale University, New Haven, CT, USA
| | - Mallar M Chakravarty
- Computational Brain Anatomy Laboratory, Douglas Mental Health University Institute, Montreal, QC, Canada
| | - Richard F Betzel
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Evelyn M R Lake
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA.
- Department of Biomedical Engineering, Yale University School of Medicine, New Haven, CT, USA.
- Wu Tsai Institute, Yale University, New Haven, CT, USA.
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3
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MacDowell CJ, Libby A, Jahn CI, Tafazoli S, Ardalan A, Buschman TJ. Multiplexed subspaces route neural activity across brain-wide networks. Nat Commun 2025; 16:3359. [PMID: 40204762 PMCID: PMC11982558 DOI: 10.1038/s41467-025-58698-2] [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: 05/06/2024] [Accepted: 03/28/2025] [Indexed: 04/11/2025] Open
Abstract
Cognition is flexible, allowing behavior to change on a moment-by-moment basis. Such flexibility relies on the brain's ability to route information through different networks of brain regions to perform different cognitive computations. However, the mechanisms that determine which network of regions is active are not well understood. Here, we combined cortex-wide calcium imaging with high-density electrophysiological recordings in eight cortical and subcortical regions of mice to understand the interactions between regions. We found different dimensions within the population activity of each region were functionally connected with different cortex-wide 'subspace networks' of regions. These subspace networks were multiplexed; each region was functionally connected with multiple independent, yet overlapping, subspace networks. The subspace network that was active changed from moment-to-moment. These changes were associated with changes in the geometric relationship between the neural response within a region and the subspace dimensions: when neural responses were aligned with (i.e., projected along) a subspace dimension, neural activity was increased in the associated regions. Together, our results suggest that changing the geometry of neural representations within a brain region may allow the brain to flexibly engage different brain-wide networks, thereby supporting cognitive flexibility.
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Affiliation(s)
- Camden J MacDowell
- Princeton Neuroscience Institute, Princeton University, Washington Rd, Princeton, NJ, USA
| | - Alexandra Libby
- Princeton Neuroscience Institute, Princeton University, Washington Rd, Princeton, NJ, USA
| | - Caroline I Jahn
- Princeton Neuroscience Institute, Princeton University, Washington Rd, Princeton, NJ, USA
| | - Sina Tafazoli
- Princeton Neuroscience Institute, Princeton University, Washington Rd, Princeton, NJ, USA
| | - Adel Ardalan
- Princeton Neuroscience Institute, Princeton University, Washington Rd, Princeton, NJ, USA
| | - Timothy J Buschman
- Princeton Neuroscience Institute, Princeton University, Washington Rd, Princeton, NJ, USA.
- Department of Psychology, Princeton University, Washington Rd, Princeton, NJ, USA.
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4
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DeSpenza T, Kiziltug E, Allington G, Barson DG, McGee S, O'Connor D, Robert SM, Mekbib KY, Nanda P, Greenberg ABW, Singh A, Duy PQ, Mandino F, Zhao S, Lynn A, Reeves BC, Marlier A, Getz SA, Nelson-Williams C, Shimelis H, Walsh LK, Zhang J, Wang W, Prina ML, OuYang A, Abdulkareem AF, Smith H, Shohfi J, Mehta NH, Dennis E, Reduron LR, Hong J, Butler W, Carter BS, Deniz E, Lake EMR, Constable RT, Sahin M, Srivastava S, Winden K, Hoffman EJ, Carlson M, Gunel M, Lifton RP, Alper SL, Jin SC, Crair MC, Moreno-De-Luca A, Luikart BW, Kahle KT. PTEN mutations impair CSF dynamics and cortical networks by dysregulating periventricular neural progenitors. Nat Neurosci 2025; 28:536-557. [PMID: 39994410 PMCID: PMC12038823 DOI: 10.1038/s41593-024-01865-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Accepted: 12/05/2024] [Indexed: 02/26/2025]
Abstract
Enlargement of the cerebrospinal fluid (CSF)-filled brain ventricles (ventriculomegaly) is a defining feature of congenital hydrocephalus (CH) and an under-recognized concomitant of autism. Here, we show that de novo mutations in the autism risk gene PTEN are among the most frequent monogenic causes of CH and primary ventriculomegaly. Mouse Pten-mutant ventriculomegaly results from aqueductal stenosis due to hyperproliferation of periventricular Nkx2.1+ neural progenitor cells (NPCs) and increased CSF production from hyperplastic choroid plexus. Pten-mutant ventriculomegalic cortices exhibit network dysfunction from increased activity of Nkx2.1+ NPC-derived inhibitory interneurons. Raptor deletion or postnatal everolimus treatment corrects ventriculomegaly, rescues cortical deficits and increases survival by antagonizing mTORC1-dependent Nkx2.1+ NPC pathology. Thus, PTEN mutations concurrently alter CSF dynamics and cortical networks by dysregulating Nkx2.1+ NPCs. These results implicate a nonsurgical treatment for CH, demonstrate a genetic association of ventriculomegaly and ASD, and help explain neurodevelopmental phenotypes refractory to CSF shunting in select individuals with CH.
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Affiliation(s)
- Tyrone DeSpenza
- Interdepartmental Neuroscience Program, Yale School of Medicine, Yale University, New Haven, CT, USA
- Medical Scientist Training Program, Yale School of Medicine, Yale University, New Haven, CT, USA
- Department of Neurosurgery, Yale School of Medicine, Yale University, New Haven, CT, USA
- Department of Neurosurgery, Duke University Medical Center, Durham, NC, USA
| | - Emre Kiziltug
- Department of Neurosurgery, Yale School of Medicine, Yale University, New Haven, CT, USA
- Department of Neurosurgery, University of Michigan, Ann Arbor, MI, USA
| | - Garrett Allington
- Department of Pathology, Yale School of Medicine, Yale University, New Haven, CT, USA
- Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Neurology, Columbia University Vagelos College of Physicians and Surgeons and New York Presbyterian Hospital, New York, NY, USA
| | - Daniel G Barson
- Interdepartmental Neuroscience Program, Yale School of Medicine, Yale University, New Haven, CT, USA
- Medical Scientist Training Program, Yale School of Medicine, Yale University, New Haven, CT, USA
| | | | - David O'Connor
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Stephanie M Robert
- Department of Neurosurgery, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Kedous Y Mekbib
- Department of Neurosurgery, Yale School of Medicine, Yale University, New Haven, CT, USA
- Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Pranav Nanda
- Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Ana B W Greenberg
- Department of Neurosurgery, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Amrita Singh
- Department of Neurosurgery, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Phan Q Duy
- Interdepartmental Neuroscience Program, Yale School of Medicine, Yale University, New Haven, CT, USA
- Medical Scientist Training Program, Yale School of Medicine, Yale University, New Haven, CT, USA
- Department of Neurosurgery, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Francesca Mandino
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Shujuan Zhao
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Anna Lynn
- Medical Scientist Training Program, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Benjamin C Reeves
- Department of Neurosurgery, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Arnaud Marlier
- Department of Neurosurgery, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Stephanie A Getz
- Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
| | - Carol Nelson-Williams
- Department of Neurosurgery, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Hermela Shimelis
- Autism & Developmental Medicine Institute, Geisinger, Lewisburg, PA, USA
| | - Lauren K Walsh
- Autism & Developmental Medicine Institute, Geisinger, Lewisburg, PA, USA
| | - Junhui Zhang
- Department of Neurosurgery, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Wei Wang
- Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
| | - Mackenzi L Prina
- Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
- Department of Neurobiology, UAB Heersink School of Medicine, Birmingham, AL, USA
| | - Annaliese OuYang
- Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
| | - Asan F Abdulkareem
- Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
- Department of Neurobiology, UAB Heersink School of Medicine, Birmingham, AL, USA
| | - Hannah Smith
- Department of Neurosurgery, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - John Shohfi
- Department of Neurosurgery, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Neel H Mehta
- Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Evan Dennis
- Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Laetitia R Reduron
- Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
| | - Jennifer Hong
- Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
| | - William Butler
- Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Bob S Carter
- Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Engin Deniz
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT, USA
| | - Evelyn M R Lake
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - R Todd Constable
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Mustafa Sahin
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Siddharth Srivastava
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Kellen Winden
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ellen J Hoffman
- Child Study Center, Yale School of Medicine, New Haven, CT, USA
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
| | - Marina Carlson
- Interdepartmental Neuroscience Program, Yale School of Medicine, Yale University, New Haven, CT, USA
- Child Study Center, Yale School of Medicine, New Haven, CT, USA
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
| | - Murat Gunel
- Department of Neurosurgery, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Richard P Lifton
- Laboratory of Human Genetics and Genomics, The Rockefeller University, New York, NY, USA
| | - Seth L Alper
- Division of Nephrology and Center for Vascular Biology Research, Beth Israel Deaconess Medical Center, and Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Diagnostic Medicine Institute, Geisinger, Danville, PA, USA
| | - Sheng Chih Jin
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Michael C Crair
- Interdepartmental Neuroscience Program, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Andres Moreno-De-Luca
- Autism & Developmental Medicine Institute, Geisinger, Lewisburg, PA, USA
- Department of Radiology, Diagnostic Medicine Institute, Geisinger, Danville, PA, USA
| | - Bryan W Luikart
- Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA.
- Department of Neurobiology, UAB Heersink School of Medicine, Birmingham, AL, USA.
| | - Kristopher T Kahle
- Department of Neurosurgery, Yale School of Medicine, Yale University, New Haven, CT, USA.
- Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
- Broad Institute of Harvard and MIT, Cambridge, MA, USA.
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA.
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5
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Mandino F, Horien C, Shen X, Desrosiers-Grégoire G, Luo W, Markicevic M, Todd Constable R, 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 2025:2024.05.24.594620. [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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6
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Markicevic M, Mandino F, Toyonaga T, Cai Z, Fesharaki-Zadeh A, Shen X, Strittmatter SM, Lake EM. Repetitive Mild Closed-Head Injury Induced Synapse Loss and Increased Local BOLD-fMRI Signal Homogeneity. J Neurotrauma 2024; 41:2528-2544. [PMID: 39096127 PMCID: PMC11698675 DOI: 10.1089/neu.2024.0095] [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] [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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7
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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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8
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Mandino F, Shen X, Desrosiers-Gregoire G, O'Connor D, Mukherjee B, Owens A, Qu A, Onofrey J, Papademetris X, Chakravarty MM, Strittmatter SM, Lake EM. Aging-Dependent Loss of Connectivity in Alzheimer's Model Mice with Rescue by mGluR5 Modulator. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.15.571715. [PMID: 38260465 PMCID: PMC10802481 DOI: 10.1101/2023.12.15.571715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Amyloid accumulation in Alzheimer's disease (AD) is associated with synaptic damage and altered connectivity in brain networks. While measures of amyloid accumulation and biochemical changes in mouse models have utility for translational studies of certain therapeutics, preclinical analysis of altered brain connectivity using clinically relevant fMRI measures has not been well developed for agents intended to improve neural networks. Here, we conduct a longitudinal study in a double knock-in mouse model for AD ( App NL-G-F /hMapt ), monitoring brain connectivity by means of resting-state fMRI. While the 4-month-old AD mice are indistinguishable from wild-type controls (WT), decreased connectivity in the default-mode network is significant for the AD mice relative to WT mice by 6 months of age and is pronounced by 9 months of age. In a second cohort of 20-month-old mice with persistent functional connectivity deficits for AD relative to WT, we assess the impact of two-months of oral treatment with a silent allosteric modulator of mGluR5 (BMS-984923) known to rescue synaptic density. Functional connectivity deficits in the aged AD mice are reversed by the mGluR5-directed treatment. The longitudinal application of fMRI has enabled us to define the preclinical time trajectory of AD-related changes in functional connectivity, and to demonstrate a translatable metric for monitoring disease emergence, progression, and response to synapse-rescuing treatment.
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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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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: 0.5] [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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11
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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: 0.5] [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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