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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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2
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Montani C, Balasco L, Pagani M, Alvino FG, Barsotti N, de Guzman AE, Galbusera A, de Felice A, Nickl-Jockschat TK, Migliarini S, Casarosa S, Lau P, Mattioni L, Pasqualetti M, Provenzano G, Bozzi Y, Lombardo MV, Gozzi A. Sex-biasing influence of autism-associated Ube3a gene overdosage at connectomic, behavioral, and transcriptomic levels. SCIENCE ADVANCES 2024; 10:eadg1421. [PMID: 38996019 PMCID: PMC11244557 DOI: 10.1126/sciadv.adg1421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 06/07/2024] [Indexed: 07/14/2024]
Abstract
Genomic mechanisms enhancing risk in males may contribute to sex bias in autism. The ubiquitin protein ligase E3A gene (Ube3a) affects cellular homeostasis via control of protein turnover and by acting as transcriptional coactivator with steroid hormone receptors. Overdosage of Ube3a via duplication or triplication of chromosomal region 15q11-13 causes 1 to 2% of autistic cases. Here, we test the hypothesis that increased dosage of Ube3a may influence autism-relevant phenotypes in a sex-biased manner. We show that mice with extra copies of Ube3a exhibit sex-biasing effects on brain connectomics and autism-relevant behaviors. These effects are associated with transcriptional dysregulation of autism-associated genes, as well as genes differentially expressed in 15q duplication and in autistic people. Increased Ube3a dosage also affects expression of genes on the X chromosome, genes influenced by sex steroid hormone, and genes sex-differentially regulated by transcription factors. These results suggest that Ube3a overdosage can contribute to sex bias in neurodevelopmental conditions via influence on sex-differential mechanisms.
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Affiliation(s)
- Caterina Montani
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, CNCS@UNITN, Rovereto, Italy
| | - Luigi Balasco
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy
| | - Marco Pagani
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, CNCS@UNITN, Rovereto, Italy
- Autism Center, Child Mind Institute, New York, NY, USA
- IMT School for Advanced Studies, Lucca, Italy
| | - Filomena Grazia Alvino
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, CNCS@UNITN, Rovereto, Italy
| | - Noemi Barsotti
- Unit of Cell and Developmental Biology, Department of Biology, University of Pisa, Pisa, Italy
| | - A. Elizabeth de Guzman
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, CNCS@UNITN, Rovereto, Italy
| | - Alberto Galbusera
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, CNCS@UNITN, Rovereto, Italy
| | - Alessia de Felice
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, CNCS@UNITN, Rovereto, Italy
| | - Thomas K. Nickl-Jockschat
- Department of Psychiatry and Psychotherapy, Otto-von-Guericke University, Magdeburg, Germany
- German Center for Mental Health (DZPG), partner site Halle-Jena-Magdeburg, Germany
- Center for Intervention and Research on adaptive and maladaptive brain Circuits underlying mental health (C-I-R-C), Halle-Jena-Magdeburg, Germany
| | - Sara Migliarini
- Unit of Cell and Developmental Biology, Department of Biology, University of Pisa, Pisa, Italy
| | - Simona Casarosa
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy
- Centre for Medical Sciences (CISMed), University of Trento, Trento, Italy
| | - Pierre Lau
- Istituto Italiano di Tecnologia, Center for Human Technologies, Genova, Italy
| | - Lorenzo Mattioni
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy
| | - Massimo Pasqualetti
- Unit of Cell and Developmental Biology, Department of Biology, University of Pisa, Pisa, Italy
| | - Giovanni Provenzano
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy
| | - Yuri Bozzi
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Rovereto, Italy
- CNR Neuroscience Institute, Pisa, Italy
| | - Michael V. Lombardo
- Laboratory for Autism and Neurodevelopmental Disorders, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, CNCS@UNITN, Rovereto, Italy
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, CNCS@UNITN, Rovereto, Italy
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3
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Winter S, Mahzarnia A, Anderson RJ, Han ZY, Tremblay J, Stout J, Moon HS, Marcellino D, Dunson DB, Badea A. APOE, Immune Factors, Sex, and Diet Interact to Shape Brain Networks in Mouse Models of Aging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.10.04.560954. [PMID: 39005377 PMCID: PMC11244909 DOI: 10.1101/2023.10.04.560954] [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: 07/16/2024]
Abstract
Alzheimer's disease (AD) presents complex challenges due to its multifactorial nature, poorly understood etiology, and late detection. The mechanisms through which genetic, fixed and modifiable risk factors influence susceptibility to AD are under intense investigation, yet the impact of unique risk factors on brain networks is difficult to disentangle, and their interactions remain unclear. To model multiple risk factors including APOE genotype, age, sex, diet, and immunity we leveraged mice expressing the human APOE and NOS2 genes, conferring a reduced immune response compared to mouse Nos2. Employing graph analyses of brain connectomes derived from accelerated diffusion-weighted MRI, we assessed the global and local impact of risk factors in the absence of AD pathology. Aging and a high-fat diet impacted extensive networks comprising AD-vulnerable regions, including the temporal association cortex, amygdala, and the periaqueductal gray, involved in stress responses. Sex impacted networks including sexually dimorphic regions (thalamus, insula, hypothalamus) and key memory-processing areas (fimbria, septum). APOE genotypes modulated connectivity in memory, sensory, and motor regions, while diet and immunity both impacted the insula and hypothalamus. Notably, these risk factors converged on a circuit comprising 63 of 54,946 total connections (0.11% of the connectome), highlighting shared vulnerability amongst multiple AD risk factors in regions essential for sensory integration, emotional regulation, decision making, motor coordination, memory, homeostasis, and interoception. These network-based biomarkers hold translational value for distinguishing high-risk versus low-risk participants at preclinical AD stages, suggest circuits as potential therapeutic targets, and advance our understanding of network fingerprints associated with AD risk. Significance Statement Current interventions for Alzheimer's disease (AD) do not provide a cure, and are delivered years after neuropathological onset. Addressing the impact of risk factors on brain networks holds promises for early detection, prevention, and revealing putative therapeutic targets at preclinical stages. We utilized six mouse models to investigate the impact of factors, including APOE genotype, age, sex, immunity, and diet, on brain networks. Large structural connectomes were derived from high resolution compressed sensing diffusion MRI. A highly parallelized graph classification identified subnetworks associated with unique risk factors, revealing their network fingerprints, and a common network composed of 63 connections with shared vulnerability to all risk factors. APOE genotype specific immune signatures support the design of interventions tailored to risk profiles.
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Affiliation(s)
- Steven Winter
- Statistical Science, Trinity School, Duke University, Durham, NC, 27710 USA
| | - Ali Mahzarnia
- Department of Radiology, Duke University School of Medicine. Durham, NC, 27710. USA
| | - Robert J Anderson
- Department of Radiology, Duke University School of Medicine. Durham, NC, 27710. USA
| | - Zay Yar Han
- Department of Radiology, Duke University School of Medicine. Durham, NC, 27710. USA
| | - Jessica Tremblay
- Department of Radiology, Duke University School of Medicine. Durham, NC, 27710. USA
| | - Jacques Stout
- Duke UNC Brain Imaging and Analysis Center, Duke University School of Medicine, Durham, NC, 27710, USA
| | - Hae Sol Moon
- Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC 27710, USA
| | - Daniel Marcellino
- Department of Medical and Translational Biology, Umeå University, Umeå, 901 87, Sweden
- Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, 22184, Sweden
| | - David B. Dunson
- Statistical Science, Trinity School, Duke University, Durham, NC, 27710 USA
| | - Alexandra Badea
- Department of Radiology, Duke University School of Medicine. Durham, NC, 27710. USA
- Duke UNC Brain Imaging and Analysis Center, Duke University School of Medicine, Durham, NC, 27710, USA
- Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC 27710, USA
- Department of Neurology, Duke University School of Medicine. Durham, NC, 27710, USA
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4
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Lokossou HA, Rabuffo G, Bernard M, Bernard C, Viola A, Perles-Barbacaru TA. Impact of the day/night cycle on functional connectome in ageing male and female mice. Neuroimage 2024; 290:120576. [PMID: 38490583 DOI: 10.1016/j.neuroimage.2024.120576] [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: 04/27/2023] [Revised: 03/07/2024] [Accepted: 03/12/2024] [Indexed: 03/17/2024] Open
Abstract
To elucidate how time of day, sex, and age affect functional connectivity (FC) in mice, we aimed to examine whether the mouse functional connectome varied with the day/night cycle and whether it depended on sex and age. We explored C57Bl6/J mice (6♀ and 6♂) at mature age (5 ± 1 months) and middle-age (14 ± 1 months). Each mouse underwent Blood Oxygen-Level-Dependent (BOLD) resting-state functional MRI (rs-fMRI) on a 7T scanner at four different times of the day, two under the light condition and two under the dark condition. Data processing consisted of group independent component analysis (ICA) and region-level analysis using resting-state networks (RSNs) derived from literature. Linear mixed-effect models (LMEM) were used to assess the effects of sex, lighting condition and their interactions for each RSN obtained with group-ICA (RSNs-GICA) and six bilateral RSNs adapted from literature (RSNs-LIT). Our study highlighted new RSNs in mice related to day/night alternation in addition to other networks already reported in the literature. In mature mice, we found sex-related differences in brain activation only in one RSNs-GICA comprising the cortical, hippocampal, midbrain and cerebellar regions of the right hemisphere. In males, brain activity was significantly higher in the left hippocampus, the retrosplenial cortex, the superior colliculus, and the cerebellum regardless of lighting condition; consistent with the role of these structures in memory formation and integration, sleep, and sex-differences in memory processing. Experimental constraints limited the analysis to the impact of light/dark cycle on the RSNs for middle-aged females. We detected significant activation in the pineal gland during the dark condition, a finding in line with the nocturnal activity of this gland. For the analysis of RSNs-LIT, new variables "sexage" (sex and age combined) and "edges" (pairs of RSNs) were introduced. FC was calculated as the Pearson correlation between two RSNs. LMEM revealed no effect of sexage or lighting condition. The FC depended on the edges, but there were no interaction effects between sexage, lighting condition and edges. Interaction effects were detected between i) sex and lighting condition, with higher FC in males under the dark condition, ii) sexage and edges with higher FC in male brain regions related to vision, memory, and motor action. We conclude that time of day and sex should be taken into account when designing, analyzing, and interpreting functional imaging studies in rodents.
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Affiliation(s)
- Houéfa Armelle Lokossou
- Centre for Magnetic Resonance in Biology and Medicine, CRMBM UMR 7339, Aix-Marseille University-CNRS, Marseille, France; Institute of Systems Neuroscience, INS UMR 1106, Aix-Marseille University-INSERM, Marseille, France.
| | - Giovanni Rabuffo
- Institute of Systems Neuroscience, INS UMR 1106, Aix-Marseille University-INSERM, Marseille, France
| | - Monique Bernard
- Centre for Magnetic Resonance in Biology and Medicine, CRMBM UMR 7339, Aix-Marseille University-CNRS, Marseille, France
| | - Christophe Bernard
- Institute of Systems Neuroscience, INS UMR 1106, Aix-Marseille University-INSERM, Marseille, France.
| | - Angèle Viola
- Centre for Magnetic Resonance in Biology and Medicine, CRMBM UMR 7339, Aix-Marseille University-CNRS, Marseille, France
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5
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Alvino FG, Gini S, Minetti A, Pagani M, Sastre-Yagüe D, Barsotti N, De Guzman E, Schleifer C, Stuefer A, Kushan L, Montani C, Galbusera A, Papaleo F, Lombardo MV, Pasqualetti M, Bearden CE, Gozzi A. Synaptic-dependent developmental dysconnectivity in 22q11.2 deletion syndrome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.29.587339. [PMID: 38585897 PMCID: PMC10996624 DOI: 10.1101/2024.03.29.587339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Chromosome 22q11.2 deletion is among the strongest known genetic risk factors for neuropsychiatric disorders, including autism and schizophrenia. Brain imaging studies have reported disrupted large-scale functional connectivity in people with 22q11 deletion syndrome (22q11DS). However, the significance and biological determinants of these functional alterations remain unclear. Here, we use a cross-species design to investigate the developmental trajectory and neural underpinnings of brain dysconnectivity in 22q11DS. We find that LgDel mice, an established mouse model of 22q11DS, exhibit age-specific patterns of functional MRI (fMRI) dysconnectivity, with widespread fMRI hyper-connectivity in juvenile mice reverting to focal hippocampal hypoconnectivity over puberty. These fMRI connectivity alterations are mirrored by co-occurring developmental alterations in dendritic spine density, and are both transiently normalized by developmental GSK3β inhibition, suggesting a synaptic origin for this phenomenon. Notably, analogous hyper- to hypoconnectivity reconfiguration occurs also in human 22q11DS, where it affects hippocampal and cortical regions spatially enriched for synaptic genes that interact with GSK3β, and autism-relevant transcripts. Functional dysconnectivity in somatomotor components of this network is predictive of age-dependent social alterations in 22q11.2 deletion carriers. Taken together, these findings suggest that synaptic-related mechanisms underlie developmentally mediated functional dysconnectivity in 22q11DS.
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Affiliation(s)
- F G Alvino
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @UniTn, Rovereto, Italy
| | - S Gini
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @UniTn, Rovereto, Italy
- Center for Mind and Brain Sciences, University of Trento, Rovereto, Italy
| | - A Minetti
- Department of Biology, Unit of Cell and Developmental Biology, University of Pisa, Pisa, Italy
| | - M Pagani
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @UniTn, Rovereto, Italy
- IMT School for Advanced Studies, Lucca, Italy
| | - D Sastre-Yagüe
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @UniTn, Rovereto, Italy
- Center for Mind and Brain Sciences, University of Trento, Rovereto, Italy
| | - N Barsotti
- Centro per l'Integrazione della Strumentazione Scientifica dell'Universita di Pisa (CISUP), Pisa, Italy
| | - E De Guzman
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @UniTn, Rovereto, Italy
| | - C Schleifer
- Departments of Psychiatry and Biobehavioral Sciences and Psychology, Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, California
| | - A Stuefer
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @UniTn, Rovereto, Italy
- Center for Mind and Brain Sciences, University of Trento, Rovereto, Italy
| | - L Kushan
- Departments of Psychiatry and Biobehavioral Sciences and Psychology, Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, California
| | - C Montani
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @UniTn, Rovereto, Italy
| | - A Galbusera
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @UniTn, Rovereto, Italy
| | - F Papaleo
- Genetics of Cognition Laboratory, Neuroscience area, Istituto Italiano di Tecnologia, Genova, Italy
| | - M V Lombardo
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - M Pasqualetti
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @UniTn, Rovereto, Italy
- Centro per l'Integrazione della Strumentazione Scientifica dell'Universita di Pisa (CISUP), Pisa, Italy
| | - C E Bearden
- Departments of Psychiatry and Biobehavioral Sciences and Psychology, Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, California
| | - A Gozzi
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @UniTn, Rovereto, Italy
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6
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Qian P, Manubens-Gil L, Jiang S, Peng H. Non-homogenous axonal bouton distribution in whole-brain single-cell neuronal networks. Cell Rep 2024; 43:113871. [PMID: 38451816 DOI: 10.1016/j.celrep.2024.113871] [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: 09/09/2023] [Revised: 01/08/2024] [Accepted: 02/09/2024] [Indexed: 03/09/2024] Open
Abstract
We examined the distribution of pre-synaptic contacts in axons of mouse neurons and constructed whole-brain single-cell neuronal networks using an extensive dataset of 1,891 fully reconstructed neurons. We found that bouton locations were not homogeneous throughout the axon and among brain regions. As our algorithm was able to generate whole-brain single-cell connectivity matrices from full morphology reconstruction datasets, we further found that non-homogeneous bouton locations have a significant impact on network wiring, including degree distribution, triad census, and community structure. By perturbing neuronal morphology, we further explored the link between anatomical details and network topology. In our in silico exploration, we found that dendritic and axonal tree span would have the greatest impact on network wiring, followed by synaptic contact deletion. Our results suggest that neuroanatomical details must be carefully addressed in studies of whole-brain networks at the single-cell level.
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Affiliation(s)
- Penghao Qian
- New Cornerstone Science Laboratory, SEU-ALLEN Joint Center, State Key Laboratory of Digital Medical Engineering, Institute for Brain and Intelligence, Southeast University, Nanjing, Jiangsu 210096, China; School of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu 210096, China
| | - Linus Manubens-Gil
- New Cornerstone Science Laboratory, SEU-ALLEN Joint Center, State Key Laboratory of Digital Medical Engineering, Institute for Brain and Intelligence, Southeast University, Nanjing, Jiangsu 210096, China.
| | - Shengdian Jiang
- New Cornerstone Science Laboratory, SEU-ALLEN Joint Center, State Key Laboratory of Digital Medical Engineering, Institute for Brain and Intelligence, Southeast University, Nanjing, Jiangsu 210096, China; School of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu 210096, China
| | - Hanchuan Peng
- New Cornerstone Science Laboratory, SEU-ALLEN Joint Center, State Key Laboratory of Digital Medical Engineering, Institute for Brain and Intelligence, Southeast University, Nanjing, Jiangsu 210096, China.
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7
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Benozzo D, Baron G, Coletta L, Chiuso A, Gozzi A, Bertoldo A. Macroscale coupling between structural and effective connectivity in the mouse brain. Sci Rep 2024; 14:3142. [PMID: 38326324 PMCID: PMC10850485 DOI: 10.1038/s41598-024-51613-7] [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: 07/27/2023] [Accepted: 01/07/2024] [Indexed: 02/09/2024] Open
Abstract
Exploring how the emergent functional connectivity (FC) relates to the underlying anatomy (structural connectivity, SC) is one of the major goals of modern neuroscience. At the macroscale level, no one-to-one correspondence between structural and functional links seems to exist. And we posit that to better understand their coupling, two key aspects should be considered: the directionality of the structural connectome and limitations in explaining networks functions through an undirected measure such as FC. Here, we employed an accurate directed SC of the mouse brain acquired through viral tracers and compared it with single-subject effective connectivity (EC) matrices derived from a dynamic causal model (DCM) applied to whole-brain resting-state fMRI data. We analyzed how SC deviates from EC and quantified their respective couplings by conditioning on the strongest SC links and EC links. We found that when conditioning on the strongest EC links, the obtained coupling follows the unimodal-transmodal functional hierarchy. Whereas the reverse is not true, as there are strong SC links within high-order cortical areas with no corresponding strong EC links. This mismatch is even more clear across networks; only within sensory motor networks did we observe connections that align in terms of both effective and structural strength.
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Affiliation(s)
- Danilo Benozzo
- Department of Information Engineering, University of Padova, Padua, Italy.
| | - Giorgia Baron
- Department of Information Engineering, University of Padova, Padua, Italy
| | - Ludovico Coletta
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems @ UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Alessandro Chiuso
- Department of Information Engineering, University of Padova, Padua, Italy
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems @ UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Alessandra Bertoldo
- Department of Information Engineering, University of Padova, Padua, Italy.
- Padova Neuroscience Center (PNC), Padua, Italy.
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8
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Endepols H, Anglada-Huguet M, Mandelkow E, Neumaier B, Mandelkow EM, Drzezga A. Fragmentation of functional resting state brain networks in a transgenic mouse model of tau pathology: A metabolic connectivity study using [ 18F]FDG-PET. Exp Neurol 2024; 372:114632. [PMID: 38052272 DOI: 10.1016/j.expneurol.2023.114632] [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: 08/24/2023] [Revised: 11/07/2023] [Accepted: 11/29/2023] [Indexed: 12/07/2023]
Abstract
In a previous study, regional reductions in cerebral glucose metabolism have been demonstrated in the tauopathy mouse model rTg4510 (Endepols et al., 2022). Notably, glucose hypometabolism was present in some brain regions without co-localized synaptic degeneration measured with [18F]UCB-H. We hypothesized that in those regions hypometabolism may reflect reduced functional connectivity rather than synaptic damage. To test this hypothesis, we performed seed-based metabolic connectivity analyses using [18F]FDG-PET data in this mouse model. Eight rTg4510 mice at the age of seven months and 8 non-transgenic littermates were injected intraperitoneally with 11.1 ± 0.8 MBq [18F]FDG and spent a 35-min uptake period awake in single cages. Subsequently, they were anesthetized and measured in a small animal PET scanner for 30 min. Three seed-based connectivity analyses were performed per group. Seeds were selected for apparent mismatch between [18F]FDG and [18F]UCB-H. A seed was placed either in the medial orbitofrontal cortex, dorsal hippocampus or dorsal thalamus, and correlated with all other voxels of the brain across animals. In the control group, the emerging correlative pattern was strongly overlapping for all three seed locations, indicating a uniform fronto-thalamo-hippocampal resting state network. In contrast, rTg4510 mice showed three distinct networks with minimal overlap. Frontal and thalamic networks were greatly diminished. The hippocampus, however, formed a new network with the whole parietal cortex. We conclude that resting-state functional networks are fragmented in the brain of rTg4510 mice. Thus, hypometabolism can be explained by reduced functional connectivity of brain areas devoid of tau-related pathology, such as the thalamus.
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Affiliation(s)
- Heike Endepols
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Institute of Radiochemistry and Experimental Molecular Imaging, Cologne, Germany; Forschungszentrum Jülich GmbH, Institute of Neuroscience and Medicine, Nuclear Chemistry (INM-5), Wilhelm-Johnen-Straße, Jülich 52428, Germany; University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Nuclear Medicine, Cologne, Germany
| | | | - Eckhard Mandelkow
- German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany; Department Neurodegenerative Diseases & Gerontopsychiatry, University Hospital Bonn, Germany
| | - Bernd Neumaier
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Institute of Radiochemistry and Experimental Molecular Imaging, Cologne, Germany; Forschungszentrum Jülich GmbH, Institute of Neuroscience and Medicine, Nuclear Chemistry (INM-5), Wilhelm-Johnen-Straße, Jülich 52428, Germany.
| | - Eva-Maria Mandelkow
- German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany; Department Neurodegenerative Diseases & Gerontopsychiatry, University Hospital Bonn, Germany
| | - Alexander Drzezga
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Nuclear Medicine, Cologne, Germany; German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany; Forschungszentrum Jülich GmbH, Institute of Neuroscience and Medicine, Molecular Organization of the Brain (INM-2), Wilhelm-Johnen-Straße, Jülich 52428, Germany
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9
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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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10
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Sourty M, Champagnol-Di Liberti C, Nasseef MT, Welsch L, Noblet V, Darcq E, Kieffer BL. Chronic Morphine Leaves a Durable Fingerprint on Whole-Brain Functional Connectivity. Biol Psychiatry 2023:S0006-3223(23)01765-1. [PMID: 38104648 PMCID: PMC11178678 DOI: 10.1016/j.biopsych.2023.12.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 11/23/2023] [Accepted: 12/11/2023] [Indexed: 12/19/2023]
Abstract
BACKGROUND Opioid use disorder is a chronic relapsing disorder. The brain adapts to opioids that are taken for pain treatment or recreational use so that abstinence becomes a true challenge for individuals with opioid use disorder. Studying brain dysfunction at this stage is difficult, and human neuroimaging has provided highly heterogeneous information. METHODS Here, we took advantage of an established mouse model of morphine abstinence together with functional magnetic resonance imaging to investigate whole-brain functional connectivity (FC) first at rest and then in response to an acute morphine challenge during image acquisition. RESULTS Hierarchical clustering of seed pair correlation coefficients showed modified FC in abstinent animals, brainwide and regardless of the condition. Seed-to-voxel analysis and random forest classification, performed on data at rest, indicated that the retrosplenial cortex (a core component of the default mode network) and the amygdala (a major aversion center) are the best markers of abstinence, thus validating the translatability of the study. Seed pair network clustering confirmed disruption of a retrosplenial cortex-centered network, reflecting major reorganization of brain FC. The latter analysis also identified a persistent but unreported morphine signature in abstinent mice at rest, which involves cortical and midbrain components and characterizes the enduring morphine footprint. Finally, dynamic FC analysis revealed that the intrascanner acute morphine challenge modified FC faster and more broadly in abstinent animals, demonstrating brainwide adaptations of FC reactivity to an acute opioid challenge. CONCLUSIONS This study used a unique experimental design to demonstrate that a prior history of chronic opioid exposure leaves a durable pharmacological signature on brain communication, with implications for pain management and recovery from opioid use disorder.
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Affiliation(s)
- Marion Sourty
- University of Strasbourg, French Institute of Health and Medical Research UMR-S 1329, Strasbourg Translational Neuroscience and Psychiatry, Centre de Recherche en Biomedicine de Strasbourg, Strasbourg, France; iCube, University of Strasbourg, National Centre for Scientific Research, Strasbourg, France
| | - Cédric Champagnol-Di Liberti
- University of Strasbourg, French Institute of Health and Medical Research UMR-S 1329, Strasbourg Translational Neuroscience and Psychiatry, Centre de Recherche en Biomedicine de Strasbourg, Strasbourg, France
| | - Md Taufiq Nasseef
- Douglas Research Center, Department of Psychiatry, McGill University, Montréal, Quebec, Canada; Department of Mathematics, College of Science and Humanity Studies, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
| | - Lola Welsch
- University of Strasbourg, French Institute of Health and Medical Research UMR-S 1329, Strasbourg Translational Neuroscience and Psychiatry, Centre de Recherche en Biomedicine de Strasbourg, Strasbourg, France; Douglas Research Center, Department of Psychiatry, McGill University, Montréal, Quebec, Canada
| | - Vincent Noblet
- iCube, University of Strasbourg, National Centre for Scientific Research, Strasbourg, France
| | - Emmanuel Darcq
- University of Strasbourg, French Institute of Health and Medical Research UMR-S 1329, Strasbourg Translational Neuroscience and Psychiatry, Centre de Recherche en Biomedicine de Strasbourg, Strasbourg, France; Douglas Research Center, Department of Psychiatry, McGill University, Montréal, Quebec, Canada
| | - Brigitte L Kieffer
- University of Strasbourg, French Institute of Health and Medical Research UMR-S 1329, Strasbourg Translational Neuroscience and Psychiatry, Centre de Recherche en Biomedicine de Strasbourg, Strasbourg, France; Douglas Research Center, Department of Psychiatry, McGill University, Montréal, Quebec, Canada.
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11
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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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12
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Matsuda K, Shirakami A, Nakajima R, Akutsu T, Shimono M. Whole-Brain Evaluation of Cortical Microconnectomes. eNeuro 2023; 10:ENEURO.0094-23.2023. [PMID: 37903612 PMCID: PMC10616907 DOI: 10.1523/eneuro.0094-23.2023] [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: 03/22/2023] [Revised: 09/08/2023] [Accepted: 09/30/2023] [Indexed: 11/01/2023] Open
Abstract
The brain is an organ that functions as a network of many elements connected in a nonuniform manner. In the brain, the neocortex is evolutionarily newest and is thought to be primarily responsible for the high intelligence of mammals. In the mature mammalian brain, all cortical regions are expected to have some degree of homology, but have some variations of local circuits to achieve specific functions performed by individual regions. However, few cellular-level studies have examined how the networks within different cortical regions differ. This study aimed to find rules for systematic changes of connectivity (microconnectomes) across 16 different cortical region groups. We also observed unknown trends in basic parameters in vitro such as firing rate and layer thickness across brain regions. Results revealed that the frontal group shows unique characteristics such as dense active neurons, thick cortex, and strong connections with deeper layers. This suggests the frontal side of the cortex is inherently capable of driving, even in isolation and that frontal nodes provide the driving force generating a global pattern of spontaneous synchronous activity, such as the default mode network. This finding provides a new hypothesis explaining why disruption in the frontal region causes a large impact on mental health.
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Affiliation(s)
- Kouki Matsuda
- Graduate Schools of Medicine, Kyoto University, 53 Kawaramachi, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan
| | - Arata Shirakami
- Graduate Schools of Medicine, Kyoto University, 53 Kawaramachi, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan
| | - Ryota Nakajima
- Graduate Schools of Medicine, Kyoto University, 53 Kawaramachi, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan
| | - Tatsuya Akutsu
- Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan
| | - Masanori Shimono
- Graduate Schools of Medicine, Kyoto University, 53 Kawaramachi, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan
- Graduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita-shi, Osaka 565-0871
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13
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Zhu W, Ou L, Zhang L, Clark IH, Zhang Y, Zhu XH, Whitley CB, Hackett PB, Low WC, Chen W. Mapping brain networks in MPS I mice and their restoration following gene therapy. Sci Rep 2023; 13:12716. [PMID: 37543633 PMCID: PMC10404260 DOI: 10.1038/s41598-023-39939-0] [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: 02/09/2023] [Accepted: 08/02/2023] [Indexed: 08/07/2023] Open
Abstract
Mucopolysaccharidosis type I (MPS I) is an inherited lysosomal disorder that causes syndromes characterized by physiological dysfunction in many organs and tissues. Despite the recognizable morphological and behavioral deficits associated with MPS I, neither the underlying alterations in functional neural connectivity nor its restoration following gene therapy have been shown. By employing high-resolution resting-state fMRI (rs-fMRI), we found significant reductions in functional neural connectivity in the limbic areas of the brain that play key roles in learning and memory in MPS I mice, and that adeno-associated virus (AAV)-mediated gene therapy can reestablish most brain connectivity. Using logistic regression in MPS I and treated animals, we identified functional networks with the most alterations. The rs-fMRI and statistical methods should be translatable into clinical evaluation of humans with neurological disorders.
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Affiliation(s)
- Wei Zhu
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, 55455, USA
- Department of Radiology, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Li Ou
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, 55455, USA
- Genemagic Biosciences, Media, PA, 19063, USA
| | - Lin Zhang
- Division of Biostatistics, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Isaac H Clark
- Biomedical Engineering Graduate Program, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Ying Zhang
- Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Xiao-Hong Zhu
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, 55455, USA
- Department of Radiology, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Chester B Whitley
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Perry B Hackett
- Department of Genetics, Cell Biology Development, University of Minnesota, Minneapolis, MN, 55455, USA
- Stem Cell Institute, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Walter C Low
- Biomedical Engineering Graduate Program, University of Minnesota, Minneapolis, MN, 55455, USA.
- Stem Cell Institute, University of Minnesota, Minneapolis, MN, 55455, USA.
- Department of Neurosurgery, University of Minnesota, Minneapolis, MN, 55455, USA.
- Graduate Program in Neuroscience, University of Minnesota, Minneapolis, MN, 55455, USA.
| | - Wei Chen
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, 55455, USA.
- Department of Radiology, University of Minnesota, Minneapolis, MN, 55455, USA.
- Biomedical Engineering Graduate Program, University of Minnesota, Minneapolis, MN, 55455, USA.
- Stem Cell Institute, University of Minnesota, Minneapolis, MN, 55455, USA.
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14
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Dai T, Seewoo BJ, Hennessy LA, Bolland SJ, Rosenow T, Rodger J. Identifying reproducible resting state networks and functional connectivity alterations following chronic restraint stress in anaesthetized rats. Front Neurosci 2023; 17:1151525. [PMID: 37284657 PMCID: PMC10239969 DOI: 10.3389/fnins.2023.1151525] [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: 01/26/2023] [Accepted: 04/27/2023] [Indexed: 06/08/2023] Open
Abstract
Background Resting-state functional MRI (rs-fMRI) in rodent models have the potential to bridge invasive experiments and observational human studies, increasing our understanding of functional alterations in the brains of patients with depression. A major limitation in current rodent rs-fMRI studies is that there has been no consensus on healthy baseline resting-state networks (RSNs) that are reproducible in rodents. Therefore, the present study aimed to construct reproducible RSNs in a large dataset of healthy rats and then evaluate functional connectivity changes within and between these RSNs following a chronic restraint stress (CRS) model within the same animals. Methods A combined MRI dataset of 109 Sprague Dawley rats at baseline and after two weeks of CRS, collected during four separate experiments conducted by our lab in 2019 and 2020, was re-analysed. The mICA and gRAICAR toolbox were first applied to detect optimal and reproducible ICA components and then a hierarchical clustering algorithm (FSLNets) was applied to construct reproducible RSNs. Ridge-regularized partial correlation (FSLNets) was used to evaluate the changes in the direct connection between and within identified networks in the same animals following CRS. Results Four large-scale networks in anesthetised rats were identified: the DMN-like, spatial attention-limbic, corpus striatum, and autonomic network, which are homologous across species. CRS decreased the anticorrelation between DMN-like and autonomic network. CRS decreased the correlation between amygdala and a functional complex (nucleus accumbens and ventral pallidum) in the right hemisphere within the corpus striatum network. However, a high individual variability in the functional connectivity before and after CRS within RSNs was observed. Conclusion The functional connectivity changes detected in rodents following CRS differ from reported functional connectivity alterations in patients with depression. A simple interpretation of this difference is that the rodent response to CRS does not reflect the complexity of depression as it is experienced by humans. Nonetheless, the high inter-subject variability of functional connectivity within networks suggests that rats demonstrate different neural phenotypes, like humans. Therefore, future efforts in classifying neural phenotypes in rodents might improve the sensitivity and translational impact of models used to address aetiology and treatment of psychiatric conditions including depression.
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Affiliation(s)
- Twain Dai
- School of Biological Sciences, University of Western Australia, Perth, WA, Australia
- Perron Institute for Neurological and Translational Science, University of Western Australia, Perth, WA, Australia
| | - Bhedita J. Seewoo
- School of Biological Sciences, University of Western Australia, Perth, WA, Australia
- Minderoo Foundation, Perth, WA, Australia
| | - Lauren A. Hennessy
- School of Biological Sciences, University of Western Australia, Perth, WA, Australia
- Perron Institute for Neurological and Translational Science, University of Western Australia, Perth, WA, Australia
| | - Samuel J. Bolland
- School of Biological Sciences, University of Western Australia, Perth, WA, Australia
- Perron Institute for Neurological and Translational Science, University of Western Australia, Perth, WA, Australia
| | - Tim Rosenow
- Centre for Microscopy, Characterisation and Analysis, Research Infrastructure Centres, University of Western Australia, Perth, WA, Australia
| | - Jennifer Rodger
- School of Biological Sciences, University of Western Australia, Perth, WA, Australia
- Perron Institute for Neurological and Translational Science, University of Western Australia, Perth, WA, Australia
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15
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Vasilkovska T, Adhikari M, Van Audekerke J, Salajeghe S, Pustina D, Cachope R, Tang H, Liu L, Munoz-Sanjuan I, Van der Linden A, Verhoye M. Resting-state fMRI reveals longitudinal alterations in brain network connectivity in the zQ175DN mouse model of Huntington's disease. Neurobiol Dis 2023; 181:106095. [PMID: 36963694 DOI: 10.1016/j.nbd.2023.106095] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Revised: 03/13/2023] [Accepted: 03/20/2023] [Indexed: 03/26/2023] Open
Abstract
Huntington's disease is an autosomal, dominantly inherited neurodegenerative disease caused by an expansion of the CAG repeats in exon 1 of the huntingtin gene. Neuronal degeneration and dysfunction that precedes regional atrophy result in the impairment of striatal and cortical circuits that affect the brain's large-scale network functionality. However, the evolution of these disease-driven, large-scale connectivity alterations is still poorly understood. Here we used resting-state fMRI to investigate functional connectivity changes in a mouse model of Huntington's disease in several relevant brain networks and how they are affected at different ages that follow a disease-like phenotypic progression. Towards this, we used the heterozygous (HET) form of the zQ175DN Huntington's disease mouse model that recapitulates aspects of human disease pathology. Seed- and Region-based analyses were performed at different ages, on 3-, 6-, 10-, and 12-month-old HET and age-matched wild-type mice. Our results demonstrate decreased connectivity starting at 6 months of age, most prominently in regions such as the retrosplenial and cingulate cortices, pertaining to the default mode-like network and auditory and visual cortices, part of the associative cortical network. At 12 months, we observe a shift towards decreased connectivity in regions such as the somatosensory cortices, pertaining to the lateral cortical network, and the caudate putamen, a constituent of the subcortical network. Moreover, we assessed the impact of distinct Huntington's Disease-like pathology of the zQ175DN HET mice on age-dependent connectivity between different brain regions and networks where we demonstrate that connectivity strength follows a nonlinear, inverted U-shape pattern, a well-known phenomenon of development and normal aging. Conversely, the neuropathologically driven alteration of connectivity, especially in the default mode and associative cortical networks, showed diminished age-dependent evolution of functional connectivity. These findings reveal that in this Huntington's disease model, altered connectivity starts with cortical network aberrations which precede striatal connectivity changes, that appear only at a later age. Taken together, these results suggest that the age-dependent cortical network dysfunction seen in rodents could represent a relevant pathological process in Huntington's disease progression.
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Affiliation(s)
- Tamara Vasilkovska
- Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Antwerp, Belgium; μNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium.
| | - Mohit Adhikari
- Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Antwerp, Belgium; μNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Johan Van Audekerke
- Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Antwerp, Belgium; μNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Somaie Salajeghe
- Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Antwerp, Belgium
| | | | | | - Haiying Tang
- CHDI Management/CHDI Foundation, Princeton, NJ, USA
| | - Longbin Liu
- CHDI Management/CHDI Foundation, Princeton, NJ, USA
| | | | - Annemie Van der Linden
- Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Antwerp, Belgium; μNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Marleen Verhoye
- Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Antwerp, Belgium; μNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
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16
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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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17
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Benozzo D, Baron G, Coletta L, Chiuso A, Gozzi A, Bertoldo A. Macroscale coupling between structural and effective connectivity in the mouse brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.22.529400. [PMID: 36865122 PMCID: PMC9980133 DOI: 10.1101/2023.02.22.529400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/24/2023]
Abstract
How the emergent functional connectivity (FC) relates to the underlying anatomy (structural connectivity, SC) is one of the biggest questions of modern neuroscience. At the macro-scale level, no one-to-one correspondence between structural and functional links seems to exist. And we posit that to better understand their coupling, two key aspects should be taken into account: the directionality of the structural connectome and the limitations of describing network functions in terms of FC. Here, we employed an accurate directed SC of the mouse brain obtained by means of viral tracers, and related it with single-subject effective connectivity (EC) matrices computed by applying a recently developed DCM to whole-brain resting-state fMRI data. We analyzed how SC deviates from EC and quantified their couplings by conditioning both on the strongest SC links and EC links. We found that when conditioning on the strongest EC links, the obtained coupling follows the unimodal-transmodal functional hierarchy. Whereas the reverse is not true, as there are strong SC links within high-order cortical areas with no corresponding strong EC links. This mismatch is even more clear across networks. Only the connections within sensory motor networks align both in terms of effective and structural strength.
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Affiliation(s)
- Danilo Benozzo
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Giorgia Baron
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Ludovico Coletta
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems @ UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Alessandro Chiuso
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems @ UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Alessandra Bertoldo
- Department of Information Engineering, University of Padova, Padova, Italy
- Padova Neuroscience Center, Padova, Italy
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18
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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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19
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Brain Macro-Structural Alterations in Aging Rats: A Longitudinal Lifetime Approach. Cells 2023; 12:cells12030432. [PMID: 36766774 PMCID: PMC9914014 DOI: 10.3390/cells12030432] [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: 11/30/2022] [Revised: 01/25/2023] [Accepted: 01/26/2023] [Indexed: 02/03/2023] Open
Abstract
Aging is accompanied by macro-structural alterations in the brain that may relate to age-associated cognitive decline. Animal studies could allow us to study this relationship, but so far it remains unclear whether their structural aging patterns correspond to those in humans. Therefore, by applying magnetic resonance imaging (MRI) and deformation-based morphometry (DBM), we longitudinally screened the brains of male RccHan:WIST rats for structural changes across their average lifespan. By combining dedicated region of interest (ROI) and voxel-wise approaches, we observed an increase in their global brain volume that was superimposed by divergent local morphologic alterations, with the largest aging effects in early and middle life. We detected a modality-dependent vulnerability to shrinkage across the visual, auditory, and somato-sensory cortical areas, whereas the piriform cortex showed partial resistance. Furthermore, shrinkage emerged in the amygdala, subiculum, and flocculus as well as in frontal, parietal, and motor cortical areas. Strikingly, we noticed the preservation of ectorhinal, entorhinal, retrosplenial, and cingulate cortical regions, which all represent higher-order brain areas and extraordinarily grew with increasing age. We think that the findings of this study will further advance aging research and may contribute to the establishment of interventional approaches to preserve cognitive health in advanced age.
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20
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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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21
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Mihelčić M. Redescription mining on data with background network information. Knowl Based Syst 2022. [DOI: 10.1016/j.knosys.2022.110109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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22
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Effects of chronic caffeine intake and withdrawal on neural activity assessed via resting-state functional magnetic resonance imaging in mice. Heliyon 2022; 8:e11714. [DOI: 10.1016/j.heliyon.2022.e11714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 06/23/2022] [Accepted: 11/11/2022] [Indexed: 11/21/2022] Open
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23
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Huang PH, Yang TY, Yeh CW, Huang SM, Chang HC, Hung YF, Chu WC, Cho KH, Lu TP, Kuo PH, Lee LJ, Kuo LW, Lien CC, Cheng HJ. Involvement of a BH3-only apoptosis sensitizer gene Blm-s in hippocampus-mediated mood control. Transl Psychiatry 2022; 12:411. [PMID: 36163151 PMCID: PMC9512807 DOI: 10.1038/s41398-022-02184-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 09/07/2022] [Accepted: 09/13/2022] [Indexed: 11/18/2022] Open
Abstract
Mood disorders are an important public health issue and recent advances in genomic studies have indicated that molecules involved in neurodevelopment are causally related to mood disorders. BLM-s (BCL-2-like molecule, small transcript isoform), a BH3-only proapoptotic BCL-2 family member, mediates apoptosis of postmitotic immature neurons during embryonic cortical development, but its role in the adult brain is unknown. To better understand the physiological role of Blm-s gene in vivo, we generated a Blm-s-knockout (Blm-s-/-) mouse. The Blm-s-/- mice breed normally and exhibit grossly normal development. However, global depletion of Blm-s is highly associated with depression- and anxiety-related behaviors in adult mutant mice with intact learning and memory capacity. Functional magnetic resonance imaging of adult Blm-s-/- mice reveals reduced connectivity mainly in the ventral dentate gyrus (vDG) of the hippocampus with no alteration in the dorsal DG connectivity and in total hippocampal volume. At the cellular level, BLM-s is expressed in DG granule cells (GCs), and Blm-s-/- mice show reduced dendritic complexity and decreased spine density in mature GCs. Electrophysiology study uncovers that mature vGCs in adult Blm-s-/- DG are intrinsically more excitable. Interestingly, certain genetic variants of the human Blm homologue gene (VPS50) are significantly associated with depression traits from publicly resourced UK Biobank data. Taken together, BLM-s is required for the hippocampal mood control function. Loss of BLM-s causes abnormality in the electrophysiology and morphology of GCs and a disrupted vDG neural network, which could underlie Blm-s-null-associated anxiety and depression.
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Affiliation(s)
- Pei-Hsin Huang
- Graduate Institute of Pathology, College of Medicine, National Taiwan University, 100, Taipei, Taiwan. .,Department of Pathology, National Taiwan University Hospital, 100, Taipei, Taiwan.
| | - Tsung-Ying Yang
- Graduate Institute of Pathology, College of Medicine, National Taiwan University, 100, Taipei, Taiwan
| | - Chia-Wei Yeh
- Institute of Neuroscience, College of Life Sciences, National Yang Ming Chiao Tung University, 112, Taipei, Taiwan
| | - Sheng-Min Huang
- Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, 350, Miaoli, Taiwan
| | - Ho-Ching Chang
- Institute of Molecular Biology, Academia Sinica, 115, Taipei, Taiwan
| | - Yun-Fen Hung
- Institute of Molecular Biology, Academia Sinica, 115, Taipei, Taiwan
| | - Wen-Chia Chu
- Graduate Institute of Pathology, College of Medicine, National Taiwan University, 100, Taipei, Taiwan
| | - Kuan-Hung Cho
- Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, 350, Miaoli, Taiwan
| | - Tzu-Pin Lu
- Department of Public Health & Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, 100, Taipei, Taiwan
| | - Po-Hsiu Kuo
- Department of Public Health & Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, 100, Taipei, Taiwan.,Department of Psychiatry, National Taiwan University Hospital, 100, Taipei, Taiwan
| | - Li-Jen Lee
- Graduate Institute of Anatomy and Cell Biology, College of Medicine, National Taiwan University, 100, Taipei, Taiwan.,Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, 100, Taipei, Taiwan
| | - Li-Wei Kuo
- Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, 350, Miaoli, Taiwan.,Institute of Medical Device and Imaging, College of Medicine, National Taiwan University, 100, Taipei, Taiwan
| | - Cheng-Chang Lien
- Institute of Neuroscience, College of Life Sciences, National Yang Ming Chiao Tung University, 112, Taipei, Taiwan.,Brain Research Center, National Yang Ming Chiao Tung University, 112, Taipei, Taiwan
| | - Hwai-Jong Cheng
- Institute of Molecular Biology, Academia Sinica, 115, Taipei, Taiwan
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24
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Scharwächter L, Schmitt FJ, Pallast N, Fink GR, Aswendt M. Network analysis of neuroimaging in mice. Neuroimage 2022; 253:119110. [PMID: 35311664 DOI: 10.1016/j.neuroimage.2022.119110] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 03/01/2022] [Accepted: 03/15/2022] [Indexed: 10/18/2022] Open
Abstract
Graph theory allows assessing changes of neuronal connectivity and interactions of brain regions in response to local lesions, e.g., after stroke, and global perturbations, e.g., due to psychiatric dysfunctions or neurodegenerative disorders. Consequently, network analysis based on constructing graphs from structural and functional MRI connectivity matrices is increasingly used in clinical studies. In contrast, in mouse neuroimaging, the focus is mainly on basic connectivity parameters, i.e., the correlation coefficient or fiber counts, whereas more advanced network analyses remain rarely used. This review summarizes graph theoretical measures and their interpretation to describe networks derived from recent in vivo mouse brain studies. To facilitate the entry into the topic, we explain the related mathematical definitions, provide a dedicated software toolkit, and discuss practical considerations for the application to rs-fMRI and DTI. This way, we aim to foster cross-species comparisons and the application of standardized measures to classify and interpret network changes in translational brain disease studies.
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Affiliation(s)
- Leon Scharwächter
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Dept. of Neurology, Cologne, Germany
| | - Felix J Schmitt
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Dept. of Neurology, Cologne, Germany; University of Cologne, Institute of Zoology, Dept. of Computational Systems Neuroscience, Cologne, Germany
| | - Niklas Pallast
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Dept. of Neurology, Cologne, Germany
| | - Gereon R Fink
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Dept. of Neurology, Cologne, Germany; Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Center Juelich, Germany
| | - Markus Aswendt
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Dept. of Neurology, Cologne, Germany; Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Center Juelich, Germany.
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25
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Xu N, LaGrow TJ, Anumba N, Lee A, Zhang X, Yousefi B, Bassil Y, Clavijo GP, Khalilzad Sharghi V, Maltbie E, Meyer-Baese L, Nezafati M, Pan WJ, Keilholz S. Functional Connectivity of the Brain Across Rodents and Humans. Front Neurosci 2022; 16:816331. [PMID: 35350561 PMCID: PMC8957796 DOI: 10.3389/fnins.2022.816331] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Accepted: 02/14/2022] [Indexed: 12/15/2022] Open
Abstract
Resting-state functional magnetic resonance imaging (rs-fMRI), which measures the spontaneous fluctuations in the blood oxygen level-dependent (BOLD) signal, is increasingly utilized for the investigation of the brain's physiological and pathological functional activity. Rodents, as a typical animal model in neuroscience, play an important role in the studies that examine the neuronal processes that underpin the spontaneous fluctuations in the BOLD signal and the functional connectivity that results. Translating this knowledge from rodents to humans requires a basic knowledge of the similarities and differences across species in terms of both the BOLD signal fluctuations and the resulting functional connectivity. This review begins by examining similarities and differences in anatomical features, acquisition parameters, and preprocessing techniques, as factors that contribute to functional connectivity. Homologous functional networks are compared across species, and aspects of the BOLD fluctuations such as the topography of the global signal and the relationship between structural and functional connectivity are examined. Time-varying features of functional connectivity, obtained by sliding windowed approaches, quasi-periodic patterns, and coactivation patterns, are compared across species. Applications demonstrating the use of rs-fMRI as a translational tool for cross-species analysis are discussed, with an emphasis on neurological and psychiatric disorders. Finally, open questions are presented to encapsulate the future direction of the field.
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Affiliation(s)
- Nan Xu
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Theodore J. LaGrow
- Electrical and Computer Engineering, Georgia Tech, Atlanta, GA, United States
| | - Nmachi Anumba
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Azalea Lee
- Neuroscience Graduate Program, Emory University, Atlanta, GA, United States
- Emory University School of Medicine, Atlanta, GA, United States
| | - Xiaodi Zhang
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Behnaz Yousefi
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Yasmine Bassil
- Neuroscience Graduate Program, Emory University, Atlanta, GA, United States
| | - Gloria P. Clavijo
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | | | - Eric Maltbie
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Lisa Meyer-Baese
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Maysam Nezafati
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Wen-Ju Pan
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
| | - Shella Keilholz
- Biomedical Engineering, Emory University and Georgia Tech, Atlanta, GA, United States
- Neuroscience Graduate Program, Emory University, Atlanta, GA, United States
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26
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Manno FAM, Kumar R, An Z, Khan MS, Su J, Liu J, Wu EX, He J, Feng Y, Lau C. Structural and Functional Hippocampal Correlations in Environmental Enrichment During the Adolescent to Adulthood Transition in Mice. Front Syst Neurosci 2022; 15:807297. [PMID: 35242015 PMCID: PMC8886042 DOI: 10.3389/fnsys.2021.807297] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 12/14/2021] [Indexed: 01/13/2023] Open
Abstract
Environmental enrichment is known to induce neuronal changes; however, the underlying structural and functional factors involved are not fully known and remain an active area of study. To investigate these factors, we assessed enriched environment (EE) and standard environment (SE) control mice over 30 days using structural and functional MRI methods. Naïve adult male mice (n = 30, ≈20 g, C57BL/B6J, postnatal day 60 initial scan) were divided into SE and EE groups and scanned before and after 30 days. Structural analyses included volumetry based on manual segmentation as well as diffusion tensor imaging (DTI). Functional analyses included seed-based analysis (SBA), independent component analysis (ICA), the amplitude of low-frequency fluctuation (ALFF), and fractional ALFF (fALFF). Structural results indicated that environmental enrichment led to an increase in the volumes of cornu ammonis 1 (CA1) and dentate gyrus. Structural results indicated changes in radial diffusivity and mean diffusivity in the visual cortex and secondary somatosensory cortex after EE. Furthermore, SBA and ICA indicated an increase in resting-state functional MRI (rsfMRI) functional connectivity in the hippocampus. Using parallel structural and functional analyses, we have demonstrated coexistent structural and functional changes in the hippocampal subdivision CA1. Future research should map alterations temporally during environmental enrichment to investigate the initiation of these structural and functional changes.
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Affiliation(s)
- Francis A M Manno
- Center for Imaging Science, Department of Biomedical Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States.,Department of Physics, City University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Rachit Kumar
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.,Medical Scientist Training Program, University of Pennsylvania, Philadelphia, PA, United States
| | - Ziqi An
- Guangdong Provincial Key Laboratory of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, China.,Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Key Laboratory of Mental Health of the Ministry of Education, Southern Medical University, Guangzhou, China
| | - Muhammad Shehzad Khan
- Department of Physics, City University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Junfeng Su
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Harvard University, Boston, MA, United States
| | - Jiaming Liu
- Guangdong Provincial Key Laboratory of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, China.,Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Key Laboratory of Mental Health of the Ministry of Education, Southern Medical University, Guangzhou, China
| | - Ed X Wu
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, Hong Kong SAR, China.,Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Jufang He
- Department of Neuroscience, City University of Hong Kong, Hong Kong, Hong Kong SAR, China.,Department of Biomedical Sciences, City University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Yanqiu Feng
- Guangdong Provincial Key Laboratory of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, China.,Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Key Laboratory of Mental Health of the Ministry of Education, Southern Medical University, Guangzhou, China
| | - Condon Lau
- Department of Physics, City University of Hong Kong, Hong Kong, Hong Kong SAR, China
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27
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Rocchi F, Canella C, Noei S, Gutierrez-Barragan D, Coletta L, Galbusera A, Stuefer A, Vassanelli S, Pasqualetti M, Iurilli G, Panzeri S, Gozzi A. Increased fMRI connectivity upon chemogenetic inhibition of the mouse prefrontal cortex. Nat Commun 2022; 13:1056. [PMID: 35217677 PMCID: PMC8881459 DOI: 10.1038/s41467-022-28591-3] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Accepted: 01/27/2022] [Indexed: 12/25/2022] Open
Abstract
While shaped and constrained by axonal connections, fMRI-based functional connectivity reorganizes in response to varying interareal input or pathological perturbations. However, the causal contribution of regional brain activity to whole-brain fMRI network organization remains unclear. Here we combine neural manipulations, resting-state fMRI and in vivo electrophysiology to probe how inactivation of a cortical node causally affects brain-wide fMRI coupling in the mouse. We find that chronic inhibition of the medial prefrontal cortex (PFC) via overexpression of a potassium channel increases fMRI connectivity between the inhibited area and its direct thalamo-cortical targets. Acute chemogenetic inhibition of the PFC produces analogous patterns of fMRI overconnectivity. Using in vivo electrophysiology, we find that chemogenetic inhibition of the PFC enhances low frequency (0.1–4 Hz) oscillatory power via suppression of neural firing not phase-locked to slow rhythms, resulting in increased slow and δ band coherence between areas that exhibit fMRI overconnectivity. These results provide causal evidence that cortical inactivation can counterintuitively increase fMRI connectivity via enhanced, less-localized slow oscillatory processes. Pathological perturbation affects whole brain network activity. Here the authors show in mice that cortical inactivation unexpectedly results in increased fMRI connectivity between the manipulated regions and its direct axonal targets.
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Affiliation(s)
- Federico Rocchi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy.,Center for Mind and Brain Sciences, University of Trento, Rovereto, Italy
| | - Carola Canella
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy.,Center for Mind and Brain Sciences, University of Trento, Rovereto, Italy
| | - Shahryar Noei
- Center for Mind and Brain Sciences, University of Trento, Rovereto, Italy.,Neural Computational Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Daniel Gutierrez-Barragan
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Ludovico Coletta
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy.,Center for Mind and Brain Sciences, University of Trento, Rovereto, Italy
| | - Alberto Galbusera
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Alexia Stuefer
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy.,Center for Mind and Brain Sciences, University of Trento, Rovereto, Italy
| | - Stefano Vassanelli
- Dept. of Biomedical Sciences and Padua Neuroscience Center, University of Padova, Padova, Italy
| | - Massimo Pasqualetti
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy.,Biology Department, University of Pisa, Pisa, Italy
| | - Giuliano Iurilli
- Systems Neurobiology Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Stefano Panzeri
- Neural Computational Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy. .,Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy.
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28
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Gutierrez-Barragan D, Singh NA, Alvino FG, Coletta L, Rocchi F, De Guzman E, Galbusera A, Uboldi M, Panzeri S, Gozzi A. Unique spatiotemporal fMRI dynamics in the awake mouse brain. Curr Biol 2022; 32:631-644.e6. [PMID: 34998465 PMCID: PMC8837277 DOI: 10.1016/j.cub.2021.12.015] [Citation(s) in RCA: 47] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 12/06/2021] [Accepted: 12/07/2021] [Indexed: 12/15/2022]
Abstract
Human imaging studies have shown that spontaneous brain activity exhibits stereotypic spatiotemporal reorganization in awake, conscious conditions with respect to minimally conscious states. However, whether and how this phenomenon can be generalized to lower mammalian species remains unclear. Leveraging a robust protocol for resting-state fMRI (rsfMRI) mapping in non-anesthetized, head-fixed mice, we investigated functional network topography and dynamic structure of spontaneous brain activity in wakeful animals. We found that rsfMRI networks in the awake state, while anatomically comparable to those observed under anesthesia, are topologically configured to maximize interregional communication, departing from the underlying community structure of the mouse axonal connectome. We further report that rsfMRI activity in wakeful animals exhibits unique spatiotemporal dynamics characterized by a state-dependent, dominant occurrence of coactivation patterns encompassing a prominent participation of arousal-related forebrain nuclei and functional anti-coordination between visual-auditory and polymodal cortical areas. We finally show that rsfMRI dynamics in awake mice exhibits a stereotypical temporal structure, in which state-dominant coactivation patterns are configured as network attractors. These findings suggest that spontaneous brain activity in awake mice is critically shaped by state-specific involvement of basal forebrain arousal systems and document that its dynamic structure recapitulates distinctive, evolutionarily relevant principles that are predictive of conscious states in higher mammalian species. fMRI networks in awake mice depart from underlying anatomical structure fMRI dynamics in wakeful mice is critically shaped by arousal-related nuclei Occurrence and topography of rsfMRI coactivation patterns define conscious states fMRI coactivation dynamics defines a signature of consciousness in the mouse brain
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Affiliation(s)
- Daniel Gutierrez-Barragan
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Neha Atulkumar Singh
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Filomena Grazia Alvino
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Ludovico Coletta
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy; Center for Mind and Brain Sciences, University of Trento, Rovereto, Italy
| | - Federico Rocchi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy; Center for Mind and Brain Sciences, University of Trento, Rovereto, Italy
| | - Elizabeth De Guzman
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Alberto Galbusera
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | | | - Stefano Panzeri
- Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany; Neural Computation Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy.
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He Z, Du L, Huang Y, Jiang X, Lv J, Guo L, Zhang S, Zhang T. Gyral Hinges Account for the Highest Cost and the Highest Communication Capacity in a Corticocortical Network. Cereb Cortex 2021; 32:3359-3376. [PMID: 34875041 DOI: 10.1093/cercor/bhab420] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 10/22/2021] [Accepted: 10/23/2021] [Indexed: 12/11/2022] Open
Abstract
Prior studies reported the global structure of brain networks exhibits the "small-world" and "rich-world" attributes. However, the underlying structural and functional architecture highlighted by these graph theory findings hasn't been explicitly related to the morphology of the cortex. This could be attributed to the lower resolution of used folding patterns, such as gyro-sulcal patterns. By defining a novel gyral folding pattern, termed gyral hinge (GH), which is the conjunction of ordinary gyri from multiple directions, we found GHs possess the highest length and cost in the white matter fiber connective network, and the shortest paths in the network tend to travel through GHs in their middle part. Based on these findings, we would hypothesize GHs could reside in the centers of a network core, thereby accounting for the highest cost and the highest communication capacity in a corticocortical network. The following results further support our hypothesis: 1) GHs possess stronger functional network integration capacity. 2) Higher cost is found on the connection with GHs to hinges and GHs to GHs. 3) Moving GHs introduces higher extra network cost. Our findings and hypotheses could reveal a profound relationship among the cortical folding patterns, axonal wiring architectures, and brain functions.
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Affiliation(s)
- Zhibin He
- School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
| | - Lei Du
- School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
| | - Ying Huang
- School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
| | - Xi Jiang
- School of Life Science and Technology, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Jinglei Lv
- School of Biomedical Engineering, Sydney Imaging, Brain and Mind Centre, The University of Sydney, Camperdown, NSW 2050, Australia
| | - Lei Guo
- School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
| | - Shu Zhang
- School of Computer Science, Northwestern Polytechnical University, Xi'an 710072, China
| | - Tuo Zhang
- School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
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30
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Lee SH, Broadwater MA, Ban W, Wang TWW, Kim HJ, Dumas JS, Vetreno RP, Herman MA, Morrow AL, Besheer J, Kash TL, Boettiger CA, Robinson DL, Crews FT, Shih YYI. An isotropic EPI database and analytical pipelines for rat brain resting-state fMRI. Neuroimage 2021; 243:118541. [PMID: 34478824 PMCID: PMC8561231 DOI: 10.1016/j.neuroimage.2021.118541] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 08/08/2021] [Accepted: 08/30/2021] [Indexed: 12/24/2022] Open
Abstract
Resting-state functional magnetic resonance imaging (fMRI) has drastically expanded the scope of brain research by advancing our knowledge about the topologies, dynamics, and interspecies translatability of functional brain networks. Several databases have been developed and shared in accordance with recent key initiatives in the rodent fMRI community to enhance the transparency, reproducibility, and interpretability of data acquired at various sites. Despite these pioneering efforts, one notable challenge preventing efficient standardization in the field is the customary choice of anisotropic echo planar imaging (EPI) schemes with limited spatial coverage. Imaging with anisotropic resolution and/or reduced brain coverage has significant shortcomings including reduced registration accuracy and increased deviation in brain feature detection. Here we proposed a high-spatial-resolution (0.4 mm), isotropic, whole-brain EPI protocol for the rat brain using a horizontal slicing scheme that can maintain a functionally relevant repetition time (TR), avoid high gradient duty cycles, and offer unequivocal whole-brain coverage. Using this protocol, we acquired resting-state EPI fMRI data from 87 healthy rats under the widely used dexmedetomidine sedation supplemented with low-dose isoflurane on a 9.4 T MRI system. We developed an EPI template that closely approximates the Paxinos and Watson's rat brain coordinate system and demonstrated its ability to improve the accuracy of group-level approaches and streamline fMRI data pre-processing. Using this database, we employed a multi-scale dictionary-learning approach to identify reliable spatiotemporal features representing rat brain intrinsic activity. Subsequently, we performed k-means clustering on those features to obtain spatially discrete, functional regions of interest (ROIs). Using Euclidean-based hierarchical clustering and modularity-based partitioning, we identified the topological organizations of the rat brain. Additionally, the identified group-level FC network appeared robust across strains and sexes. The "triple-network" commonly adapted in human fMRI were resembled in the rat brain. Through this work, we disseminate raw and pre-processed isotropic EPI data, a rat brain EPI template, as well as identified functional ROIs and networks in standardized rat brain coordinates. We also make our analytical pipelines and scripts publicly available, with the hope of facilitating rat brain resting-state fMRI study standardization.
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Affiliation(s)
- Sung-Ho Lee
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA,Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA,Department of Neurology, University of North Carolina, Chapel Hill, NC, USA,Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Corresponding authors at: Center for Animal MRI, 125 Mason Farm Road, CB# 7513, University of North Carolina, Chapel Hill, NC 27599, USA. (S.-H. Lee), (Y.-Y.I. Shih)
| | - Margaret A. Broadwater
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA,Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA,Department of Neurology, University of North Carolina, Chapel Hill, NC, USA,Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA
| | - Woomi Ban
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA,Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA
| | - Tzu-Wen Winnie Wang
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA,Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA
| | - Hyeon-Joong Kim
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA,Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA,Department of Neurology, University of North Carolina, Chapel Hill, NC, USA
| | - Jaiden Seongmi Dumas
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA,Department of Neurology, University of North Carolina, Chapel Hill, NC, USA,Department of Quantitative Biology, University of North Carolina, Chapel Hill, NC, USA
| | - Ryan P. Vetreno
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Pharmacology, University of North Carolina, Chapel Hill, NC, USA
| | - Melissa A. Herman
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Pharmacology, University of North Carolina, Chapel Hill, NC, USA
| | - A. Leslie Morrow
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA,Department of Pharmacology, University of North Carolina, Chapel Hill, NC, USA
| | - Joyce Besheer
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Thomas L. Kash
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Pharmacology, University of North Carolina, Chapel Hill, NC, USA
| | - Charlotte A. Boettiger
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA,Department of Psychology and Neuroscience, University of North Carolina, Chapel Hill, NC, USA
| | - Donita L. Robinson
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Fulton T. Crews
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA,Department of Pharmacology, University of North Carolina, Chapel Hill, NC, USA
| | - Yen-Yu Ian Shih
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA,Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA,Department of Neurology, University of North Carolina, Chapel Hill, NC, USA,Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Corresponding authors at: Center for Animal MRI, 125 Mason Farm Road, CB# 7513, University of North Carolina, Chapel Hill, NC 27599, USA. (S.-H. Lee), (Y.-Y.I. Shih)
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31
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Rezaei Z, Jafari Z, Afrashteh N, Torabi R, Singh S, Kolb BE, Davidsen J, Mohajerani MH. Prenatal stress dysregulates resting-state functional connectivity and sensory motifs. Neurobiol Stress 2021; 15:100345. [PMID: 34124321 PMCID: PMC8173309 DOI: 10.1016/j.ynstr.2021.100345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Revised: 05/16/2021] [Accepted: 05/17/2021] [Indexed: 11/24/2022] Open
Abstract
Prenatal stress (PS) can impact fetal brain structure and function and contribute to higher vulnerability to neurodevelopmental and neuropsychiatric disorders. To understand how PS alters evoked and spontaneous neocortical activity and intrinsic brain functional connectivity, mesoscale voltage imaging was performed in adult C57BL/6NJ mice that had been exposed to auditory stress on gestational days 12-16, the age at which neocortex is developing. PS mice had a four-fold higher basal corticosterone level and reduced amplitude of cortical sensory-evoked responses to visual, auditory, whisker, forelimb, and hindlimb stimuli. Relative to control animals, PS led to a general reduction of resting-state functional connectivity, as well as reduced inter-modular connectivity, enhanced intra-modular connectivity, and altered frequency of auditory and forelimb spontaneous sensory motifs. These resting-state changes resulted in a cortical connectivity pattern featuring disjoint but tight modules and a decline in network efficiency. The findings demonstrate that cortical connectivity is sensitive to PS and exposed offspring may be at risk for adult stress-related neuropsychiatric disorders.
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Affiliation(s)
- Zahra Rezaei
- Department of Neuroscience, Canadian Centre for Behavioural Neuroscience, University of Lethbridge, Lethbridge, AB, Canada, T1K 3M4
| | - Zahra Jafari
- Department of Neuroscience, Canadian Centre for Behavioural Neuroscience, University of Lethbridge, Lethbridge, AB, Canada, T1K 3M4
| | - Navvab Afrashteh
- Department of Neuroscience, Canadian Centre for Behavioural Neuroscience, University of Lethbridge, Lethbridge, AB, Canada, T1K 3M4
| | - Reza Torabi
- Department of Neuroscience, Canadian Centre for Behavioural Neuroscience, University of Lethbridge, Lethbridge, AB, Canada, T1K 3M4
| | - Surjeet Singh
- Department of Neuroscience, Canadian Centre for Behavioural Neuroscience, University of Lethbridge, Lethbridge, AB, Canada, T1K 3M4
| | - Bryan E. Kolb
- Department of Neuroscience, Canadian Centre for Behavioural Neuroscience, University of Lethbridge, Lethbridge, AB, Canada, T1K 3M4
| | - Jörn Davidsen
- Complexity Science Group, Department of Physics and Astronomy, Faculty of Science, University of Calgary, Calgary, AB, Canada, T2N 1N4
| | - Majid H. Mohajerani
- Department of Neuroscience, Canadian Centre for Behavioural Neuroscience, University of Lethbridge, Lethbridge, AB, Canada, T1K 3M4
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32
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Pagani M, Barsotti N, Bertero A, Trakoshis S, Ulysse L, Locarno A, Miseviciute I, De Felice A, Canella C, Supekar K, Galbusera A, Menon V, Tonini R, Deco G, Lombardo MV, Pasqualetti M, Gozzi A. mTOR-related synaptic pathology causes autism spectrum disorder-associated functional hyperconnectivity. Nat Commun 2021; 12:6084. [PMID: 34667149 PMCID: PMC8526836 DOI: 10.1038/s41467-021-26131-z] [Citation(s) in RCA: 67] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 09/17/2021] [Indexed: 11/24/2022] Open
Abstract
Postmortem studies have revealed increased density of excitatory synapses in the brains of individuals with autism spectrum disorder (ASD), with a putative link to aberrant mTOR-dependent synaptic pruning. ASD is also characterized by atypical macroscale functional connectivity as measured with resting-state fMRI (rsfMRI). These observations raise the question of whether excess of synapses causes aberrant functional connectivity in ASD. Using rsfMRI, electrophysiology and in silico modelling in Tsc2 haploinsufficient mice, we show that mTOR-dependent increased spine density is associated with ASD -like stereotypies and cortico-striatal hyperconnectivity. These deficits are completely rescued by pharmacological inhibition of mTOR. Notably, we further demonstrate that children with idiopathic ASD exhibit analogous cortical-striatal hyperconnectivity, and document that this connectivity fingerprint is enriched for ASD-dysregulated genes interacting with mTOR or Tsc2. Finally, we show that the identified transcriptomic signature is predominantly expressed in a subset of children with autism, thereby defining a segregable autism subtype. Our findings causally link mTOR-related synaptic pathology to large-scale network aberrations, revealing a unifying multi-scale framework that mechanistically reconciles developmental synaptopathy and functional hyperconnectivity in autism.
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Affiliation(s)
- Marco Pagani
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @ University of Trento, Rovereto, Italy
- Autism Center, Child Mind Institute, New York, NY, USA
| | - Noemi Barsotti
- Department of Biology, Unit of Cell and Developmental Biology, University of Pisa, Pisa, Italy
| | - Alice Bertero
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @ University of Trento, Rovereto, Italy
- Department of Biology, Unit of Cell and Developmental Biology, University of Pisa, Pisa, Italy
| | - Stavros Trakoshis
- Department of Psychology, University of Cyprus, Nicosia, Cyprus
- Laboratory for Autism and Neurodevelopmental Disorders, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @ University of Trento, Rovereto, Italy
| | - Laura Ulysse
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Barcelona, Spain
| | - Andrea Locarno
- Neuromodulation of Cortical and Subcortical Circuits Laboratory, Istituto Italiano di Tecnologia, Genova, Italy
| | - Ieva Miseviciute
- Neuromodulation of Cortical and Subcortical Circuits Laboratory, Istituto Italiano di Tecnologia, Genova, Italy
| | - Alessia De Felice
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @ University of Trento, Rovereto, Italy
| | - Carola Canella
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @ University of Trento, Rovereto, Italy
| | | | - Alberto Galbusera
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @ University of Trento, Rovereto, Italy
| | | | - Raffaella Tonini
- Neuromodulation of Cortical and Subcortical Circuits Laboratory, Istituto Italiano di Tecnologia, Genova, Italy
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Barcelona, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Universitat Pompeu Fabra, Barcelona, Spain
| | - Michael V Lombardo
- Laboratory for Autism and Neurodevelopmental Disorders, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @ University of Trento, Rovereto, Italy
- Autism Research Centre, University of Cambridge, Cambridge, UK
| | - Massimo Pasqualetti
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @ University of Trento, Rovereto, Italy
- Department of Biology, Unit of Cell and Developmental Biology, University of Pisa, Pisa, Italy
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @ University of Trento, Rovereto, Italy.
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33
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Pradier B, Wachsmuth L, Nagelmann N, Segelcke D, Kreitz S, Hess A, Pogatzki-Zahn EM, Faber C. Combined resting state-fMRI and calcium recordings show stable brain states for task-induced fMRI in mice under combined ISO/MED anesthesia. Neuroimage 2021; 245:118626. [PMID: 34637903 DOI: 10.1016/j.neuroimage.2021.118626] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 09/27/2021] [Indexed: 11/28/2022] Open
Abstract
For fMRI in animal models, the combination of low-dose anesthetic, isoflurane (ISO), and the sedative medetomidine (MED) has recently become an advocated regimen to achieve stable neuronal states and brain networks in rats that are required for reliable task-induced BOLD fMRI. However, in mice the temporal stability of neuronal states and networks in resting-state (rs)-fMRI experiments during the combined ISO/MED regimen has not been systematically investigated. Using a multimodal approach with optical calcium (Ca2+) recordings and rs-fMRI, we investigated cortical neuronal/astrocytic Ca2+activity states and brain networks at multiple time points while switching from anesthesia with 1% ISO to a combined ISO/MED regimen. We found that cortical activity states reached a steady-state 45 min following start of MED infusion as indicated by stable Ca2+ transients. Similarly, rs-networks were not statistically different between anesthesia with ISO and the combined ISO/MED regimen 45 and 100 min after start of MED. Importantly, during the transition time we identified changed rs-network signatures that likely reflect the different mode of action of the respective anesthetic; these included a dose-dependent increase in cortico-cortical functional connectivity (FC) presumably caused by reduction of ISO concentration and decreased FC in subcortical arousal nuclei due to MED infusion. Furthermore, we report detection of visual stimulation-induced BOLD fMRI during the stable ISO/MED neuronal state 45 min after induction. Based on our findings, we recommend a 45-minute waiting period after switching from ISO anesthesia to the combined ISO/MED regimen before performing rs- or task-induced fMRI experiments.
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Affiliation(s)
- Bruno Pradier
- Department of Clinical Radiology, Translational Research Imaging Center, University Hospital Münster, Münster 48149, Germany; Department of Anesthesiology Intensive Care and Pain Medicine, University Hospital Münster, Germany
| | - Lydia Wachsmuth
- Department of Clinical Radiology, Translational Research Imaging Center, University Hospital Münster, Münster 48149, Germany
| | - Nina Nagelmann
- Department of Clinical Radiology, Translational Research Imaging Center, University Hospital Münster, Münster 48149, Germany
| | - Daniel Segelcke
- Department of Anesthesiology Intensive Care and Pain Medicine, University Hospital Münster, Germany
| | - Silke Kreitz
- Institute of Experimental and Clinical Pharmacology and Toxicology, Emil Fischer Center, University of Erlangen-Nuremberg, Erlangen, Germany
| | - Andreas Hess
- Institute of Experimental and Clinical Pharmacology and Toxicology, Emil Fischer Center, University of Erlangen-Nuremberg, Erlangen, Germany
| | - Esther M Pogatzki-Zahn
- Department of Anesthesiology Intensive Care and Pain Medicine, University Hospital Münster, Germany
| | - Cornelius Faber
- Department of Clinical Radiology, Translational Research Imaging Center, University Hospital Münster, Münster 48149, Germany.
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Markicevic M, Savvateev I, Grimm C, Zerbi V. Emerging imaging methods to study whole-brain function in rodent models. Transl Psychiatry 2021; 11:457. [PMID: 34482367 PMCID: PMC8418612 DOI: 10.1038/s41398-021-01575-5] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 08/05/2021] [Accepted: 08/23/2021] [Indexed: 02/07/2023] Open
Abstract
In the past decade, the idea that single populations of neurons support cognition and behavior has gradually given way to the realization that connectivity matters and that complex behavior results from interactions between remote yet anatomically connected areas that form specialized networks. In parallel, innovation in brain imaging techniques has led to the availability of a broad set of imaging tools to characterize the functional organization of complex networks. However, each of these tools poses significant technical challenges and faces limitations, which require careful consideration of their underlying anatomical, physiological, and physical specificity. In this review, we focus on emerging methods for measuring spontaneous or evoked activity in the brain. We discuss methods that can measure large-scale brain activity (directly or indirectly) with a relatively high temporal resolution, from milliseconds to seconds. We further focus on methods designed for studying the mammalian brain in preclinical models, specifically in mice and rats. This field has seen a great deal of innovation in recent years, facilitated by concomitant innovation in gene-editing techniques and the possibility of more invasive recordings. This review aims to give an overview of currently available preclinical imaging methods and an outlook on future developments. This information is suitable for educational purposes and for assisting scientists in choosing the appropriate method for their own research question.
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Affiliation(s)
- Marija Markicevic
- Neural Control of Movement Lab, HEST, ETH Zürich, Zürich, Switzerland
- Neuroscience Center Zurich, University and ETH Zürich, Zürich, Switzerland
| | - Iurii Savvateev
- Neural Control of Movement Lab, HEST, ETH Zürich, Zürich, Switzerland
- Neuroscience Center Zurich, University and ETH Zürich, Zürich, Switzerland
- Decision Neuroscience Lab, HEST, ETH Zürich, Zürich, Switzerland
| | - Christina Grimm
- Neural Control of Movement Lab, HEST, ETH Zürich, Zürich, Switzerland
- Neuroscience Center Zurich, University and ETH Zürich, Zürich, Switzerland
| | - Valerio Zerbi
- Neural Control of Movement Lab, HEST, ETH Zürich, Zürich, Switzerland.
- Neuroscience Center Zurich, University and ETH Zürich, Zürich, Switzerland.
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Tu W, Ma Z, Zhang N. Brain network reorganization after targeted attack at a hub region. Neuroimage 2021; 237:118219. [PMID: 34052466 PMCID: PMC8289586 DOI: 10.1016/j.neuroimage.2021.118219] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Revised: 04/14/2021] [Accepted: 05/26/2021] [Indexed: 01/01/2023] Open
Abstract
The architecture of brain networks has been extensively studied in multiple species. However, exactly how the brain network reconfigures when a local region, particularly a hub region, stops functioning remains elusive. By combining chemogenetics and resting-state functional magnetic resonance imaging (rsfMRI) in an awake rodent model, we investigated the causal impact of acutely inactivating a hub region (i.e. the dorsal anterior cingulate cortex) on brain network properties. We found that suppressing neural activity in a hub could have a ripple effect that went beyond the hub-related connections and propagated to other neural connections across multiple brain systems. In addition, hub dysfunction affected the topological architecture of the whole-brain network in terms of the network resilience and segregation. Selectively inhibiting excitatory neurons in the hub further changed network integration. None of these changes were observed in sham rats or when a non-hub region (i.e. the primary visual cortex) was perturbed. This study has established a system that allows for mechanistically dissecting the relationship between local regions and brain network properties. Our data provide direct evidence supporting the hypothesis that acute dysfunction of a brain hub can cause large-scale network changes. These results also provide a comprehensive framework documenting the differential impact of hub versus non-hub nodes on network dynamics.
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Affiliation(s)
- Wenyu Tu
- Neuroscience Program, The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA 16802, USA
| | - Zilu Ma
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Nanyin Zhang
- Neuroscience Program, The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA 16802, USA; Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA.
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36
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Wiring of higher-order cortical areas: Spatiotemporal development of cortical hierarchy. Semin Cell Dev Biol 2021; 118:35-49. [PMID: 34034988 DOI: 10.1016/j.semcdb.2021.05.010] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 04/27/2021] [Accepted: 05/08/2021] [Indexed: 01/04/2023]
Abstract
A hierarchical development of cortical areas was suggested over a century ago, but the diversity and complexity of cortical hierarchy properties have so far prevented a formal demonstration. The aim of this review is to clarify the similarities and differences in the developmental processes underlying cortical development of primary and higher-order areas. We start by recapitulating the historical and recent advances underlying the biological principle of cortical hierarchy in adults. We then revisit the arguments for a hierarchical maturation of cortical areas, and further integrate the principles of cortical areas specification during embryonic and postnatal development. We highlight how the dramatic expansion in cortical size might have contributed to the increased number of association areas sustaining cognitive complexification in evolution. Finally, we summarize the recent observations of an alteration of cortical hierarchy in neuropsychiatric disorders and discuss their potential developmental origins.
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Mann K, Deny S, Ganguli S, Clandinin TR. Coupling of activity, metabolism and behaviour across the Drosophila brain. Nature 2021; 593:244-248. [PMID: 33911283 PMCID: PMC10544789 DOI: 10.1038/s41586-021-03497-0] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 03/26/2021] [Indexed: 12/21/2022]
Abstract
Coordinated activity across networks of neurons is a hallmark of both resting and active behavioural states in many species1-5. These global patterns alter energy metabolism over seconds to hours, which underpins the widespread use of oxygen consumption and glucose uptake as proxies of neural activity6,7. However, whether changes in neural activity are causally related to metabolic flux in intact circuits on the timescales associated with behaviour is unclear. Here we combine two-photon microscopy of the fly brain with sensors that enable the simultaneous measurement of neural activity and metabolic flux, across both resting and active behavioural states. We demonstrate that neural activity drives changes in metabolic flux, creating a tight coupling between these signals that can be measured across brain networks. Using local optogenetic perturbation, we demonstrate that even transient increases in neural activity result in rapid and persistent increases in cytosolic ATP, which suggests that neuronal metabolism predictively allocates resources to anticipate the energy demands of future activity. Finally, our studies reveal that the initiation of even minimal behavioural movements causes large-scale changes in the pattern of neural activity and energy metabolism, which reveals a widespread engagement of the brain. As the relationship between neural activity and energy metabolism is probably evolutionarily ancient and highly conserved, our studies provide a critical foundation for using metabolic proxies to capture changes in neural activity.
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Affiliation(s)
- Kevin Mann
- Department of Neurobiology, Stanford University, Stanford, CA, USA
| | - Stephane Deny
- Department of Applied Physics, Stanford University, Stanford, CA, USA
| | - Surya Ganguli
- Department of Neurobiology, Stanford University, Stanford, CA, USA.
- Department of Applied Physics, Stanford University, Stanford, CA, USA.
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Mapping the living mouse brain neural architecture: strain-specific patterns of brain structural and functional connectivity. Brain Struct Funct 2021; 226:647-669. [PMID: 33635426 DOI: 10.1007/s00429-020-02190-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Accepted: 11/27/2020] [Indexed: 10/22/2022]
Abstract
Mapping brain structural and functional connectivity (FC) became an essential approach in neuroscience as network properties can underlie behavioral phenotypes. In mouse models, revealing strain-related patterns of brain wiring is crucial, since these animals are used to answer questions related to neurological or neuropsychiatric disorders. C57BL/6 and BALB/cJ strains are two of the primary "genetic backgrounds" for modeling brain disease and testing therapeutic approaches. However, extensive literature describes basal differences in the behavioral, neuroanatomical and neurochemical profiles of the two strains, which raises questions on whether the observed effects are pathology specific or depend on the genetic background of each strain. Here, we performed a systematic comparative exploration of brain structure and function of C57BL/6 and BALB/cJ mice using Magnetic Resonance Imaging (MRI). We combined deformation-based morphometry (DBM), diffusion MRI and high-resolution fiber mapping (hrFM) along with resting-state functional MRI (rs-fMRI) and demonstrated brain-wide differences in the morphology and "connectome" features of the two strains. Essential inter-strain differences were depicted regarding the size and the fiber density (FD) within frontal cortices, along cortico-striatal, thalamic and midbrain pathways as well as genu and splenium of corpus callosum. Structural dissimilarities were accompanied by specific FC patterns, emphasizing strain differences in frontal and basal forebrain functional networks as well as hubness characteristics. Rs-fMRI data further indicated differences of reward-aversion circuitry and default mode network (DMN) patterns. The inter-hemispherical FC showed flexibility and strain-specific adjustment of their patterns in agreement with the structural characteristics.
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Zhou G, Olofsson JK, Koubeissi MZ, Menelaou G, Rosenow J, Schuele SU, Xu P, Voss JL, Lane G, Zelano C. Human hippocampal connectivity is stronger in olfaction than other sensory systems. Prog Neurobiol 2021; 201:102027. [PMID: 33640412 DOI: 10.1016/j.pneurobio.2021.102027] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Revised: 01/20/2021] [Accepted: 02/21/2021] [Indexed: 12/17/2022]
Abstract
During mammalian evolution, primate neocortex expanded, shifting hippocampal functional networks away from primary sensory cortices, towards association cortices. Reflecting this rerouting, human resting hippocampal functional networks preferentially include higher association cortices, while those in rodents retained primary sensory cortices. Research on human visual, auditory and somatosensory systems shows evidence of this rerouting. Olfaction, however, is unique among sensory systems in its relative structural conservation throughout mammalian evolution, and it is unknown whether human primary olfactory cortex was subject to the same rerouting. We combined functional neuroimaging and intracranial electrophysiology to directly compare hippocampal functional networks across human sensory systems. We show that human primary olfactory cortex-including the anterior olfactory nucleus, olfactory tubercle and piriform cortex-has stronger functional connectivity with hippocampal networks at rest, compared to other sensory systems. This suggests that unlike other sensory systems, olfactory-hippocampal connectivity may have been retained in mammalian evolution. We further show that olfactory-hippocampal connectivity oscillates with nasal breathing. Our findings suggest olfaction might provide insight into how memory and cognition depend on hippocampal interactions.
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Affiliation(s)
- Guangyu Zhou
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
| | - Jonas K Olofsson
- Department of Psychology, Stockholm University, Stockholm, Sweden; Emotional Brain Institute, Nathan S. Kline Institute, Orangeburg, NY, USA; Department of Child and Adolescent Psychiatry, New York University School of Medicine, New York, NY, USA
| | | | | | - Joshua Rosenow
- Department of Neurosurgery, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Stephan U Schuele
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Pengfei Xu
- Beijing Key Laboratory of Applied Experimental Psychology, Faculty of Psychology, Beijing Normal University, Beijing, China; Center for Neuroimaging, Shenzhen Institute of Neuroscience, Shenzhen, China; Guangdong-Hong Kong-Macao Greater Bay Area Research Institute for Neuroscience and Neurotechnologies, Kwun Tong, Hong Kong, China
| | - Joel L Voss
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA; Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA; Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Gregory Lane
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Christina Zelano
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
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Adhikari MH, Belloy ME, Van der Linden A, Keliris GA, Verhoye M. Resting-State Co-activation Patterns as Promising Candidates for Prediction of Alzheimer's Disease in Aged Mice. Front Neural Circuits 2021; 14:612529. [PMID: 33551755 PMCID: PMC7862346 DOI: 10.3389/fncir.2020.612529] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 12/28/2020] [Indexed: 11/13/2022] Open
Abstract
Alzheimer’s disease (AD), a neurodegenerative disorder marked by accumulation of extracellular amyloid-β (Aβ) plaques leads to progressive loss of memory and cognitive function. Resting-state fMRI (RS-fMRI) studies have provided links between these two observations in terms of disruption of default mode and task-positive resting-state networks (RSNs). Important insights underlying these disruptions were recently obtained by investigating dynamic fluctuations in RS-fMRI signals in old TG2576 mice (a mouse model of amyloidosis) using a set of quasi-periodic patterns (QPP). QPPs represent repeating spatiotemporal patterns of neural activity of predefined temporal length. In this article, we used an alternative methodology of co-activation patterns (CAPs) that represent instantaneous and transient brain configurations that are likely contributors to the emergence of commonly observed RSNs and QPPs. We followed a recently published approach for obtaining CAPs that divided all time frames, instead of those corresponding to supra-threshold activations of a seed region as done traditionally, to extract CAPs from RS-fMRI recordings in 10 TG2576 female mice and eight wild type littermates at 18 months of age. Subsequently, we matched the CAPs from the two groups using the Hungarian method and compared the temporal (duration, occurrence rate) and the spatial (lateralization of significantly co-activated and co-deactivated voxels) properties of matched CAPs. We found robust differences in the spatial components of matched CAPs. Finally, we used supervised learning to train a classifier using either the temporal or the spatial component of CAPs to distinguish the transgenic mice from the WT. We found that while duration and occurrence rates of all CAPs performed the classification with significantly higher accuracy than the chance-level, blood oxygen level-dependent (BOLD) signals of significantly activated voxels from individual CAPs turned out to be a significantly better predictive feature demonstrating a near-perfect classification accuracy. Our results demonstrate resting-state co-activation patterns are a promising candidate in the development of a diagnostic, and potentially, prognostic RS-fMRI biomarker of AD.
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Affiliation(s)
- Mohit H Adhikari
- Bio-Imaging Lab, Department of Bio-medical Sciences, University of Antwerp, Antwerp, Belgium
| | - Michaël E Belloy
- Bio-Imaging Lab, Department of Bio-medical Sciences, University of Antwerp, Antwerp, Belgium
| | - Annemie Van der Linden
- Bio-Imaging Lab, Department of Bio-medical Sciences, University of Antwerp, Antwerp, Belgium
| | - Georgios A Keliris
- Bio-Imaging Lab, Department of Bio-medical Sciences, University of Antwerp, Antwerp, Belgium
| | - Marleen Verhoye
- Bio-Imaging Lab, Department of Bio-medical Sciences, University of Antwerp, Antwerp, Belgium
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Whitesell JD, Liska A, Coletta L, Hirokawa KE, Bohn P, Williford A, Groblewski PA, Graddis N, Kuan L, Knox JE, Ho A, Wakeman W, Nicovich PR, Nguyen TN, van Velthoven CTJ, Garren E, Fong O, Naeemi M, Henry AM, Dee N, Smith KA, Levi B, Feng D, Ng L, Tasic B, Zeng H, Mihalas S, Gozzi A, Harris JA. Regional, Layer, and Cell-Type-Specific Connectivity of the Mouse Default Mode Network. Neuron 2020; 109:545-559.e8. [PMID: 33290731 PMCID: PMC8150331 DOI: 10.1016/j.neuron.2020.11.011] [Citation(s) in RCA: 64] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Revised: 10/08/2020] [Accepted: 11/13/2020] [Indexed: 12/28/2022]
Abstract
The evolutionarily conserved default mode network (DMN) is a distributed set of brain regions coactivated during resting states that is vulnerable to brain disorders. How disease affects the DMN is unknown, but detailed anatomical descriptions could provide clues. Mice offer an opportunity to investigate structural connectivity of the DMN across spatial scales with cell-type resolution. We co-registered maps from functional magnetic resonance imaging and axonal tracing experiments into the 3D Allen mouse brain reference atlas. We find that the mouse DMN consists of preferentially interconnected cortical regions. As a population, DMN layer 2/3 (L2/3) neurons project almost exclusively to other DMN regions, whereas L5 neurons project in and out of the DMN. In the retrosplenial cortex, a core DMN region, we identify two L5 projection types differentiated by in- or out-DMN targets, laminar position, and gene expression. These results provide a multi-scale description of the anatomical correlates of the mouse DMN. Mouse resting-state default mode network anatomy described at high resolution in 3D Systematic axon tracing shows cortical DMN regions are preferentially interconnected Layer 2/3 DMN neurons project mostly in the DMN; layer 5 neurons project in and out Retrosplenial cortex contains distinct types of in- and out-DMN projection neurons
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Affiliation(s)
| | - Adam Liska
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @ UniTn, 38068 Rovereto, Italy; DeepMind, London EC4A 3TW, UK
| | - Ludovico Coletta
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @ UniTn, 38068 Rovereto, Italy; Center for Mind/Brain Sciences (CIMeC), University of Trento, 38068 Rovereto, Italy
| | | | - Phillip Bohn
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Ali Williford
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Nile Graddis
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Leonard Kuan
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Joseph E Knox
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Anh Ho
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Wayne Wakeman
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | | | | | - Emma Garren
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Olivia Fong
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Maitham Naeemi
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Alex M Henry
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Nick Dee
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Boaz Levi
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - David Feng
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Lydia Ng
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Bosiljka Tasic
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Stefan Mihalas
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @ UniTn, 38068 Rovereto, Italy
| | - Julie A Harris
- Allen Institute for Brain Science, Seattle, WA 98109, USA.
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Coletta L, Pagani M, Whitesell JD, Harris JA, Bernhardt B, Gozzi A. Network structure of the mouse brain connectome with voxel resolution. SCIENCE ADVANCES 2020; 6:eabb7187. [PMID: 33355124 PMCID: PMC11206455 DOI: 10.1126/sciadv.abb7187] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Accepted: 11/04/2020] [Indexed: 06/12/2023]
Abstract
Fine-grained descriptions of brain connectivity are required to understand how neural information is processed and relayed across spatial scales. Previous investigations of the mouse brain connectome have used discrete anatomical parcellations, limiting spatial resolution and potentially concealing network attributes critical to connectome organization. Here, we provide a voxel-level description of the network and hierarchical structure of the directed mouse connectome, unconstrained by regional partitioning. We report a number of previously unappreciated organizational principles in the mammalian brain, including a directional segregation of hub regions into neural sink and sources, and a strategic wiring of neuromodulatory nuclei as connector hubs and critical orchestrators of network communication. We also find that the mouse cortical connectome is hierarchically organized along two superimposed cortical gradients reflecting unimodal-transmodal functional processing and a modality-specific sensorimotor axis, recapitulating a phylogenetically conserved feature of higher mammals. These findings advance our understanding of the foundational wiring principles of the mammalian connectome.
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Affiliation(s)
- Ludovico Coletta
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems @ UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy
- Center for Mind/Brain Sciences, University of Trento, 38068 Rovereto TN, Italy
| | - Marco Pagani
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems @ UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy
| | | | | | - Boris Bernhardt
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems @ UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy.
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Garin CM, Nadkarni NA, Landeau B, Chételat G, Picq JL, Bougacha S, Dhenain M. Resting state functional atlas and cerebral networks in mouse lemur primates at 11.7 Tesla. Neuroimage 2020; 226:117589. [PMID: 33248260 DOI: 10.1016/j.neuroimage.2020.117589] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 11/13/2020] [Accepted: 11/19/2020] [Indexed: 10/22/2022] Open
Abstract
Measures of resting-state functional connectivity allow the description of neuronal networks in humans and provide a window on brain function in normal and pathological conditions. Characterizing neuronal networks in animals is complementary to studies in humans to understand how evolution has modelled network architecture. The mouse lemur (Microcebus murinus) is one of the smallest and more phylogenetically distant primates as compared to humans. Characterizing the functional organization of its brain is critical for scientists studying this primate as well as to add a link for comparative animal studies. Here, we created the first functional atlas of mouse lemur brain and describe for the first time its cerebral networks. They were classified as two primary cortical networks (somato-motor and visual), two high-level cortical networks (fronto-parietal and fronto-temporal) and two limbic networks (sensory-limbic and evaluative-limbic). Comparison of mouse lemur and human networks revealed similarities between mouse lemur high-level cortical networks and human networks as the dorsal attentional (DAN), executive control (ECN), and default-mode networks (DMN). These networks were however not homologous, possibly reflecting differential organization of high-level networks. Finally, cerebral hubs were evaluated. They were grouped along an antero-posterior axis in lemurs while they were split into parietal and frontal clusters in humans.
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Affiliation(s)
- Clément M Garin
- Centre National de la Recherche Scientifique (CNRS), Université Paris-Saclay, UMR 9199, Neurodegenerative Diseases Laboratory, 18 Route du Panorama, F-92265 Fontenay-aux-Roses, France; Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), Direction de la Recherche Fondamentale (DRF), Institut François Jacob, MIRCen, 18 Route du Panorama, F-92265 Fontenay-aux-Roses, France.
| | - Nachiket A Nadkarni
- Centre National de la Recherche Scientifique (CNRS), Université Paris-Saclay, UMR 9199, Neurodegenerative Diseases Laboratory, 18 Route du Panorama, F-92265 Fontenay-aux-Roses, France; Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), Direction de la Recherche Fondamentale (DRF), Institut François Jacob, MIRCen, 18 Route du Panorama, F-92265 Fontenay-aux-Roses, France.
| | - Brigitte Landeau
- Inserm, Inserm UMR-S U1237, Normandie University, UNICAEN, GIP Cyceron, Caen, France; UNICAEN, EPHE, INSERM, U1077, CHU de Caen, Neuropsychologie et Imagerie de la Mémoire Humaine, Normandie University, 14000 Caen, France.
| | - Gaël Chételat
- Inserm, Inserm UMR-S U1237, Normandie University, UNICAEN, GIP Cyceron, Caen, France; UNICAEN, EPHE, INSERM, U1077, CHU de Caen, Neuropsychologie et Imagerie de la Mémoire Humaine, Normandie University, 14000 Caen, France.
| | - Jean-Luc Picq
- Centre National de la Recherche Scientifique (CNRS), Université Paris-Saclay, UMR 9199, Neurodegenerative Diseases Laboratory, 18 Route du Panorama, F-92265 Fontenay-aux-Roses, France; Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), Direction de la Recherche Fondamentale (DRF), Institut François Jacob, MIRCen, 18 Route du Panorama, F-92265 Fontenay-aux-Roses, France; Laboratoire de Psychopathologie et de Neuropsychologie, EA 2027, Université Paris 8, 2 Rue de la Liberté, 93000 St Denis, France.
| | - Salma Bougacha
- Centre National de la Recherche Scientifique (CNRS), Université Paris-Saclay, UMR 9199, Neurodegenerative Diseases Laboratory, 18 Route du Panorama, F-92265 Fontenay-aux-Roses, France; Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), Direction de la Recherche Fondamentale (DRF), Institut François Jacob, MIRCen, 18 Route du Panorama, F-92265 Fontenay-aux-Roses, France; Inserm, Inserm UMR-S U1237, Normandie University, UNICAEN, GIP Cyceron, Caen, France; UNICAEN, EPHE, INSERM, U1077, CHU de Caen, Neuropsychologie et Imagerie de la Mémoire Humaine, Normandie University, 14000 Caen, France.
| | - Marc Dhenain
- Centre National de la Recherche Scientifique (CNRS), Université Paris-Saclay, UMR 9199, Neurodegenerative Diseases Laboratory, 18 Route du Panorama, F-92265 Fontenay-aux-Roses, France; Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), Direction de la Recherche Fondamentale (DRF), Institut François Jacob, MIRCen, 18 Route du Panorama, F-92265 Fontenay-aux-Roses, France.
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Experience selectively alters functional connectivity within a neural network to predict learned behavior in juvenile songbirds. Neuroimage 2020; 222:117218. [PMID: 32745678 DOI: 10.1016/j.neuroimage.2020.117218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Revised: 07/06/2020] [Accepted: 07/28/2020] [Indexed: 11/22/2022] Open
Abstract
One of the central questions of neuroethology is how specialized brain areas communicate to form dynamic networks that support complex cognitive and behavioral processes. Developmental song learning in the male zebra finch songbird (Taeniopygia guttata) provides a unique window into the complex interplay among sensory, sensorimotor, and motor network nodes. The foundation of a young male's song structure is the sensory memory he forms during interactions with an adult "tutor." However, even in the absence of tutoring, juveniles produce a song-like behavior. Thus, by controlling a juvenile male's tutor exposure, we can examine how tutor experience affects distributed neural networks and how network properties predict behavior. Here, we used longitudinal, resting-state fMRI (rs-fMRI) functional connectivity (FC) and song analyses to examine known nodes of the song network, and to allow discovery of additional areas functionally related to song learning. We present three major novel findings. First, tutor deprivation significantly reduced the global FC strength of the caudomedial nidopallium (NCM) subregion of the auditory forebrain required for sensory song learning. Second, tutor deprivation resulted in reduced FC between NCM and cerebellar lobule VI, a region analogous to areas that regulate limbic, social, and language functions in humans. Third, NCM FC strength predicted song stereotypy and mediated the relationship between tutoring and stereotypy, thus completing the link between experience, neural network properties, and complex learned behavior.
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Belloy ME, Billings J, Abbas A, Kashyap A, Pan WJ, Hinz R, Vanreusel V, Van Audekerke J, Van der Linden A, Keilholz SD, Verhoye M, Keliris GA. Resting Brain Fluctuations Are Intrinsically Coupled to Visual Response Dynamics. Cereb Cortex 2020; 31:1511-1522. [PMID: 33108464 PMCID: PMC7869084 DOI: 10.1093/cercor/bhaa305] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 08/17/2020] [Accepted: 09/16/2020] [Indexed: 01/09/2023] Open
Abstract
How do intrinsic brain dynamics interact with processing of external sensory stimuli? We sought new insights using functional magnetic resonance imaging to track spatiotemporal activity patterns at the whole brain level in lightly anesthetized mice, during both resting conditions and visual stimulation trials. Our results provide evidence that quasiperiodic patterns (QPPs) are the most prominent component of mouse resting brain dynamics. These QPPs captured the temporal alignment of anticorrelation between the default mode (DMN)- and task-positive (TPN)-like networks, with global brain fluctuations, and activity in neuromodulatory nuclei of the reticular formation. Specifically, the phase of QPPs prior to stimulation could significantly stratify subsequent visual response magnitude, suggesting QPPs relate to brain state fluctuations. This is the first observation in mice that dynamics of the DMN- and TPN-like networks, and particularly their anticorrelation, capture a brain state dynamic that affects sensory processing. Interestingly, QPPs also displayed transient onset response properties during visual stimulation, which covaried with deactivations in the reticular formation. We conclude that QPPs appear to capture a brain state fluctuation that may be orchestrated through neuromodulation. Our findings provide new frontiers to understand the neural processes that shape functional brain states and modulate sensory input processing.
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Affiliation(s)
- Michaël E Belloy
- Department of Pharmaceutical, Veterinary and Biomedical Sciences, University of Antwerp, 2610 Antwerp, Belgium.,Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA 30322, USA
| | - Jacob Billings
- Department of Neuroscience, Emory University, Atlanta, GA 30322, USA
| | - Anzar Abbas
- Department of Neuroscience, Emory University, Atlanta, GA 30322, USA
| | - Amrit Kashyap
- Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA 30322, USA
| | - Wen-Ju Pan
- Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA 30322, USA
| | - Rukun Hinz
- Department of Pharmaceutical, Veterinary and Biomedical Sciences, University of Antwerp, 2610 Antwerp, Belgium
| | - Verdi Vanreusel
- Department of Pharmaceutical, Veterinary and Biomedical Sciences, University of Antwerp, 2610 Antwerp, Belgium
| | - Johan Van Audekerke
- Department of Pharmaceutical, Veterinary and Biomedical Sciences, University of Antwerp, 2610 Antwerp, Belgium
| | - Annemie Van der Linden
- Department of Pharmaceutical, Veterinary and Biomedical Sciences, University of Antwerp, 2610 Antwerp, Belgium
| | - Shella D Keilholz
- Department of Neuroscience, Emory University, Atlanta, GA 30322, USA
| | - Marleen Verhoye
- Department of Pharmaceutical, Veterinary and Biomedical Sciences, University of Antwerp, 2610 Antwerp, Belgium
| | - Georgios A Keliris
- Department of Pharmaceutical, Veterinary and Biomedical Sciences, University of Antwerp, 2610 Antwerp, Belgium
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Becq GJPC, Habet T, Collomb N, Faucher M, Delon-Martin C, Coizet V, Achard S, Barbier EL. Functional connectivity is preserved but reorganized across several anesthetic regimes. Neuroimage 2020; 219:116945. [DOI: 10.1016/j.neuroimage.2020.116945] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2019] [Revised: 04/21/2020] [Accepted: 05/11/2020] [Indexed: 12/12/2022] Open
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Behroozi M, Helluy X, Ströckens F, Gao M, Pusch R, Tabrik S, Tegenthoff M, Otto T, Axmacher N, Kumsta R, Moser D, Genc E, Güntürkün O. Event-related functional MRI of awake behaving pigeons at 7T. Nat Commun 2020; 11:4715. [PMID: 32948772 PMCID: PMC7501281 DOI: 10.1038/s41467-020-18437-1] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Accepted: 08/20/2020] [Indexed: 11/08/2022] Open
Abstract
Animal-fMRI is a powerful method to understand neural mechanisms of cognition, but it remains a major challenge to scan actively participating small animals under low-stress conditions. Here, we present an event-related functional MRI platform in awake pigeons using single-shot RARE fMRI to investigate the neural fundaments for visually-guided decision making. We established a head-fixated Go/NoGo paradigm, which the animals quickly learned under low-stress conditions. The animals were motivated by water reward and behavior was assessed by logging mandibulations during the fMRI experiment with close to zero motion artifacts over hundreds of repeats. To achieve optimal results, we characterized the species-specific hemodynamic response function. As a proof-of-principle, we run a color discrimination task and discovered differential neural networks for Go-, NoGo-, and response execution-phases. Our findings open the door to visualize the neural fundaments of perceptual and cognitive functions in birds-a vertebrate class of which some clades are cognitively on par with primates.
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Affiliation(s)
- Mehdi Behroozi
- Department of Biopsychology, Faculty of Psychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Universitätsstraße 150, 44780, Bochum, Germany.
| | - Xavier Helluy
- Department of Biopsychology, Faculty of Psychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Universitätsstraße 150, 44780, Bochum, Germany
- Department of Neurophysiology, Faculty of Medicine, Ruhr University Bochum, Universitätsstraße 150, 44780, Bochum, Germany
| | - Felix Ströckens
- Department of Biopsychology, Faculty of Psychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Universitätsstraße 150, 44780, Bochum, Germany
| | - Meng Gao
- Department of Biopsychology, Faculty of Psychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Universitätsstraße 150, 44780, Bochum, Germany
| | - Roland Pusch
- Department of Biopsychology, Faculty of Psychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Universitätsstraße 150, 44780, Bochum, Germany
| | - Sepideh Tabrik
- Department of Neurology, BG-University Hospital Bergmannsheil, Ruhr University Bochum, Bürkle-de-la-Camp-Platz 1, 44789, Bochum, Germany
| | - Martin Tegenthoff
- Department of Neurology, BG-University Hospital Bergmannsheil, Ruhr University Bochum, Bürkle-de-la-Camp-Platz 1, 44789, Bochum, Germany
| | - Tobias Otto
- Department of Cognitive Psychology, Faculty of Psychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Universitätsstraße 150, 44780, Bochum, Germany
| | - Nikolai Axmacher
- Department of Neuropsychology, Faculty of Psychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Universitätsstraße 150, 44780, Bochum, Germany
| | - Robert Kumsta
- Department of Genetic Psychology, Faculty of Psychology, Ruhr University Bochum, Universitätsstraße 150, 44780, Bochum, Germany
| | - Dirk Moser
- Department of Genetic Psychology, Faculty of Psychology, Ruhr University Bochum, Universitätsstraße 150, 44780, Bochum, Germany
| | - Erhan Genc
- Department of Biopsychology, Faculty of Psychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Universitätsstraße 150, 44780, Bochum, Germany
- Department of Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors (IfADo), 44139, Dortmund, Germany
| | - Onur Güntürkün
- Department of Biopsychology, Faculty of Psychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Universitätsstraße 150, 44780, Bochum, Germany.
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Brain-wide structural and functional disruption in mice with oligodendrocyte-specific Nf1 deletion is rescued by inhibition of nitric oxide synthase. Proc Natl Acad Sci U S A 2020; 117:22506-22513. [PMID: 32839340 PMCID: PMC7486714 DOI: 10.1073/pnas.2008391117] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
This study assessed the effects of myelin decompaction on motor behavior and brain-wide structural and functional connectivity, and the effect of nitric oxide synthase inhibition by N-nitro-l-arginine methyl ester (L-NAME) on these imaging measures. We report that inducible oligodendrocyte-specific inactivation of the Nf1 gene, which causes myelin decompaction, results in reduced initial motor coordination. Using diffusion-based magnetic resonance imaging (MRI), we show reduced myelin integrity, and using functional MRI, we show reduced functional connectivity in awake passive mice. L-NAME administration results in rescue of the pathology at the mesoscopic level, as measured using imaging procedures that can be directly applied to humans to study treatment efficacy in clinical trials. Neurofibromin gene (NF1) mutation causes neurofibromatosis type 1 (NF1), a disorder in which brain white matter deficits identified by neuroimaging are common, yet of unknown cellular etiology. In mice, Nf1 loss in adult oligodendrocytes causes myelin decompaction and increases oligodendrocyte nitric oxide (NO) levels. Nitric oxide synthase (NOS) inhibitors rescue this pathology. Whether oligodendrocyte pathology is sufficient to affect brain-wide structure and account for NF1 imaging findings is unknown. Here we show that Nf1 gene inactivation in adult oligodendrocytes (Plp-Nf1fl/+ mice) results in a motor coordination deficit. Magnetic resonance imaging in awake mice showed that fractional anisotropy is reduced in Plp-Nf1fl/+ corpus callosum and that interhemispheric functional connectivity in the motor cortex is also reduced, consistent with disrupted myelin integrity. Furthermore, NOS-specific inhibition rescued both measures. These results suggest that oligodendrocyte defects account for aspects of brain dysfunction in NF1 that can be identified by neuroimaging and ameliorated by NOS inhibition.
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Trakoshis S, Martínez-Cañada P, Rocchi F, Canella C, You W, Chakrabarti B, Ruigrok ANV, Bullmore ET, Suckling J, Markicevic M, Zerbi V, Baron-Cohen S, Gozzi A, Lai MC, Panzeri S, Lombardo MV. Intrinsic excitation-inhibition imbalance affects medial prefrontal cortex differently in autistic men versus women. eLife 2020; 9:e55684. [PMID: 32746967 PMCID: PMC7402681 DOI: 10.7554/elife.55684] [Citation(s) in RCA: 70] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2020] [Accepted: 06/29/2020] [Indexed: 12/22/2022] Open
Abstract
Excitation-inhibition (E:I) imbalance is theorized as an important pathophysiological mechanism in autism. Autism affects males more frequently than females and sex-related mechanisms (e.g., X-linked genes, androgen hormones) can influence E:I balance. This suggests that E:I imbalance may affect autism differently in males versus females. With a combination of in-silico modeling and in-vivo chemogenetic manipulations in mice, we first show that a time-series metric estimated from fMRI BOLD signal, the Hurst exponent (H), can be an index for underlying change in the synaptic E:I ratio. In autism we find that H is reduced, indicating increased excitation, in the medial prefrontal cortex (MPFC) of autistic males but not females. Increasingly intact MPFC H is also associated with heightened ability to behaviorally camouflage social-communicative difficulties, but only in autistic females. This work suggests that H in BOLD can index synaptic E:I ratio and that E:I imbalance affects autistic males and females differently.
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Affiliation(s)
- Stavros Trakoshis
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di TecnologiaRoveretoItaly
- Department of Psychology, University of CyprusNicosiaCyprus
| | - Pablo Martínez-Cañada
- Neural Computation Laboratory, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di TecnologiaRoveretoItaly
- Optical Approaches to Brain Function Laboratory, Department of Neuroscience and Brain Technologies, Istituto Italiano di TecnologiaGenovaItaly
| | - Federico Rocchi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di TecnologiaRoveretoItaly
| | - Carola Canella
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di TecnologiaRoveretoItaly
| | - Wonsang You
- Artificial Intelligence and Image Processing Laboratory, Department of Information and Communications Engineering, Sun Moon UniversityAsanRepublic of Korea
| | - Bhismadev Chakrabarti
- Autism Research Centre, Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
- Centre for Integrative Neuroscience and Neurodynamics, School of Psychology and Clinical Language Sciences, University of ReadingReadingUnited Kingdom
| | - Amber NV Ruigrok
- Autism Research Centre, Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
| | - Edward T Bullmore
- Cambridgeshire and Peterborough National Health Service Foundation TrustCambridgeUnited Kingdom
- Brain Mapping Unit, Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
| | - John Suckling
- Brain Mapping Unit, Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
| | - Marija Markicevic
- Neural Control of Movement Lab, D-HEST, ETH ZurichZurichSwitzerland
- Neuroscience Center Zurich, University and ETH ZurichZurichSwitzerland
| | - Valerio Zerbi
- Neural Control of Movement Lab, D-HEST, ETH ZurichZurichSwitzerland
- Neuroscience Center Zurich, University and ETH ZurichZurichSwitzerland
| | | | - Simon Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
- Cambridgeshire and Peterborough National Health Service Foundation TrustCambridgeUnited Kingdom
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di TecnologiaRoveretoItaly
| | - Meng-Chuan Lai
- Autism Research Centre, Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
- The Margaret and Wallace McCain Centre for Child, Youth & Family Mental Health, Azrieli Adult Neurodevelopmental Centre, and Campbell Family Mental Health Research Institute, Centre for Addiction and Mental HealthTorontoCanada
- Department of Psychiatry and Autism Research Unit, The Hospital for Sick ChildrenTorontoCanada
- Department of Psychiatry, Faculty of Medicine, University of TorontoTorontoCanada
- Department of Psychiatry, National Taiwan University Hospital and College of MedicineTaipeiTaiwan
| | - Stefano Panzeri
- Neural Computation Laboratory, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di TecnologiaRoveretoItaly
| | - Michael V Lombardo
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di TecnologiaRoveretoItaly
- Autism Research Centre, Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
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Becq GJPC, Barbier EL, Achard S. Brain networks of rats under anesthesia using resting-state fMRI: comparison with dead rats, random noise and generative models of networks. J Neural Eng 2020; 17:045012. [PMID: 32580176 DOI: 10.1088/1741-2552/ab9fec] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
OBJECTIVE Connectivity networks are crucial to understand the brain resting-state activity using functional magnetic resonance imaging (rs-fMRI). Alterations of these brain networks may highlight important findings concerning the resilience of the brain to different disorders. The focus of this paper is to evaluate the robustness of brain network estimations, discriminate them under anesthesia and compare them to generative models. APPROACH The extraction of brain functional connectivity (FC) networks is difficult and biased due to the properties of the data: low signal to noise ratio, high dimension low sample size. We propose to use wavelet correlations to assess FC between brain areas under anesthesia using four anesthetics (isoflurane, etomidate, medetomidine, urethane). The networks are then deduced from the functional connectivity matrices by applying statistical thresholds computed using the number of samples at a given scale of wavelet decomposition. Graph measures are extracted and extensive comparisons with generative models of structured networks are conducted. MAIN RESULTS The sample size and filtering are critical to obtain significant correlations values and thereby detect connections between regions. This is necessary to construct networks different from random ones as shown using rs-fMRI brain networks of dead rats. Brain networks under anesthesia on rats have topological features that are mixing small-world, scale-free and random networks. Betweenness centrality indicates that hubs are present in brain networks obtained from anesthetized rats but locations of these hubs are altered by anesthesia. SIGNIFICANCE Understanding the effects of anesthesia on brain areas is of particular importance in the context of animal research since animal models are commonly used to explore functions, evaluate lesions or illnesses, and test new drugs. More generally, results indicate that the use of correlations in the context of fMRI signals is robust but must be treated with caution. Solutions are proposed in order to control spurious correlations by setting them to zero.
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Affiliation(s)
- G J-P C Becq
- University Grenoble Alpes, CNRS, Grenoble INP, Gipsa-lab, 38000, Grenoble, France
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