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Dong J, Wei X, Huang Z, Tian J, Zhang W. Age-related changes of dopamine D1 and D2 receptors expression in parvalbumin-positive cells of the orbitofrontal and prelimbic cortices of mice. Front Neurosci 2024; 18:1364067. [PMID: 38903598 PMCID: PMC11187244 DOI: 10.3389/fnins.2024.1364067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2024] [Accepted: 05/28/2024] [Indexed: 06/22/2024] Open
Abstract
Dopamine (DA) plays a pivotal role in reward processing, cognitive functions, and emotional regulation. The prefrontal cortex (PFC) is a critical brain region for these processes. Parvalbumin-positive (PV+) neurons are one of the major classes of inhibitory GABAergic neurons in the cortex, they modulate the activity of neighboring neurons, influencing various brain functions. While DA receptor expression exhibits age-related changes, the age-related changes of these receptors in PV+ neurons, especially in the PFC, remain unclear. To address this, we investigated the expression of DA D1 (D1R) and D2 (D2R) receptors in PV+ neurons within the orbitofrontal (OFC) and prelimbic (PrL) cortices at different postnatal ages (P28, P42, P56, and P365). We found that the expression of D1R and D2R in PV+ neurons showed both age- and region-related changes. PV+ neurons in the OFC expressed a higher abundance of D1 than those in the PrL, and those neurons in the OFC also showed higher co-expression of D1R and D2R than those in the PrL. In the OFC and PrL, D1R in PV+ neurons increased from P28 and reached a plateau at P42, then receded to express at P365. Meanwhile, D2R did not show significant age-related changes between the two regions except at P56. These results showed dopamine receptors in the prefrontal cortex exhibit age- and region-specific changes, which may contribute to the difference of these brain regions in reward-related brain functions.
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Affiliation(s)
- Jihui Dong
- Department of Neurobiology, School of Basic Medical Sciences, National Institute on Drug Dependence, Peking University, Beijing, China
- Beijing Key Laboratory of Drug Dependence Research, Peking University, Beijing, China
| | - Xiaoyan Wei
- Department of Neurobiology, School of Basic Medical Sciences, National Institute on Drug Dependence, Peking University, Beijing, China
- Beijing Key Laboratory of Drug Dependence Research, Peking University, Beijing, China
| | - Ziran Huang
- Department of Neurobiology, School of Basic Medical Sciences, National Institute on Drug Dependence, Peking University, Beijing, China
- Beijing Key Laboratory of Drug Dependence Research, Peking University, Beijing, China
| | - Jing Tian
- Department of Neurobiology, School of Basic Medical Sciences, National Institute on Drug Dependence, Peking University, Beijing, China
- Beijing Key Laboratory of Drug Dependence Research, Peking University, Beijing, China
| | - Wen Zhang
- Department of Neurobiology, School of Basic Medical Sciences, National Institute on Drug Dependence, Peking University, Beijing, China
- Beijing Key Laboratory of Drug Dependence Research, Peking University, Beijing, China
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2
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Bontempi P, Piccolantonio G, Busato A, Conti A, Angelini G, Lopez N, Bani A, Constantin G, Marzola P. Resting-state functional magnetic resonance imaging reveals functional connectivity alteration in the experimental autoimmune encephalomyelitis model of multiple sclerosis. NMR IN BIOMEDICINE 2024; 37:e5127. [PMID: 38450807 DOI: 10.1002/nbm.5127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 01/08/2024] [Accepted: 01/25/2024] [Indexed: 03/08/2024]
Abstract
Multiple sclerosis (MS) is an autoimmune degenerative disease targeting white matter in the central nervous system. The most common animal model that mimics MS is experimental autoimmune encephalomyelitis (EAE) and it plays a crucial role in pharmacological research, from the identification of a therapeutic target to the in vivo validation of efficacy. Magnetic resonance imaging (MRI) is largely used to detect MS lesions, and resting-state functional MRI (rsfMRI) to investigate alterations in the brain functional connectivity (FC). MRI was mainly used in EAE studies to detect lesions in the spinal cord and brain. The current longitudinal MRI study aims to validate rsfMRI as a biomarker of the disease progression in the myelin oligodendrocyte glycoprotein 35-55 induced EAE animal model of MS. MR images were acquired 14, 25, and 50 days postimmunization. Seed-based analysis was used to investigate the whole-brain FC with some predefined areas, such as the thalamic regions, cerebellum, motor and somatosensory cortex. When compared with the control group, the EAE group exhibited a slightly altered FC and a decreasing trend in the total number of activated voxels along the disease progression. The most interesting result regards the whole-brain FC with the cerebellum. A hyperconnectivity behavior was found at an early phase and a significant reduced connectivity at a late phase. Moreover, we found a negative correlation between the total number of activated voxels during the late phase and the cumulative disease index. The results obtained provide a clinically relevant experimental platform that may be pivotal for the elucidation of the key mechanisms of accumulation of irreversible disability, as well as the development of innovative therapies for MS. Moreover, the negative correlation between the disease severity and the size of the activated area suggests a possible research pathway to follow for the resolution of the clinico-radiological paradox.
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Affiliation(s)
- Pietro Bontempi
- Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy
| | - Giusi Piccolantonio
- Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy
| | - Alice Busato
- Department of Computer Science, University of Verona, Verona, Italy
- Evotec Company, Verona, Italy
| | - Anita Conti
- Department of Diagnostics and Public Health, University of Verona, Verona, Italy
| | | | - Nicola Lopez
- Department of Medicine, University of Verona, Verona, Italy
| | | | | | - Pasquina Marzola
- Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy
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3
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Curic D, Singh S, Nazari M, Mohajerani MH, Davidsen J. Spatial-Temporal Analysis of Neural Desynchronization in Sleeplike States Reveals Critical Dynamics. PHYSICAL REVIEW LETTERS 2024; 132:218403. [PMID: 38856286 DOI: 10.1103/physrevlett.132.218403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 02/26/2024] [Accepted: 04/10/2024] [Indexed: 06/11/2024]
Abstract
Sleep is characterized by nonrapid eye movement sleep, originating from widespread neuronal synchrony, and rapid eye movement sleep, with neuronal desynchronization akin to waking behavior. While these were thought to be global brain states, recent research suggests otherwise. Using time-frequency analysis of mesoscopic voltage-sensitive dye recordings of mice in a urethane-anesthetized model of sleep, we find transient neural desynchronization occurring heterogeneously across the cortex within a background of synchronized neural activity, in a manner reminiscent of a critical spreading process and indicative of an "edge-of-synchronization" phase transition.
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Affiliation(s)
- Davor Curic
- Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, Alberta T2N 1N4, Canada
| | - Surjeet Singh
- Canadian Centre for Behavioral Neuroscience, University of Lethbridge, Lethbridge, Alberta T1K 3M4, Canada
| | - Mojtaba Nazari
- Canadian Centre for Behavioral Neuroscience, University of Lethbridge, Lethbridge, Alberta T1K 3M4, Canada
| | - Majid H Mohajerani
- Canadian Centre for Behavioral Neuroscience, University of Lethbridge, Lethbridge, Alberta T1K 3M4, Canada
| | - Jörn Davidsen
- Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, Alberta T2N 1N4, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta T2N 4N1, Canada
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4
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Dautan D, Monai A, Maltese F, Chang X, Molent C, Mauro D, Galbusera A, Vecchia D, Antonelli F, Benedetti A, Drago F, Leggio GM, Pagani M, Fellin T, Gozzi A, Schumann G, Managò F, Papaleo F. Cortico-cortical transfer of socially derived information gates emotion recognition. Nat Neurosci 2024:10.1038/s41593-024-01647-x. [PMID: 38769153 DOI: 10.1038/s41593-024-01647-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 04/09/2024] [Indexed: 05/22/2024]
Abstract
Emotion recognition and the resulting responses are important for survival and social functioning. However, how socially derived information is processed for reliable emotion recognition is incompletely understood. Here, we reveal an evolutionarily conserved long-range inhibitory/excitatory brain network mediating these socio-cognitive processes. Anatomical tracing in mice revealed the existence of a subpopulation of somatostatin (SOM) GABAergic neurons projecting from the medial prefrontal cortex (mPFC) to the retrosplenial cortex (RSC). Through optogenetic manipulations and Ca2+ imaging fiber photometry in mice and functional imaging in humans, we demonstrate the specific participation of these long-range SOM projections from the mPFC to the RSC, and an excitatory feedback loop from the RSC to the mPFC, in emotion recognition. Notably, we show that mPFC-to-RSC SOM projections are dysfunctional in mouse models relevant to psychiatric vulnerability and can be targeted to rescue emotion recognition deficits in these mice. Our findings demonstrate a cortico-cortical circuit underlying emotion recognition.
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Affiliation(s)
- Daniel Dautan
- Genetics of Cognition Laboratory, Neuroscience area, Istituto Italiano di Tecnologia, Genova, Italy
- Bioclinicum, Karolinska Institute, Stockholm, Sweden
| | - Anna Monai
- Genetics of Cognition Laboratory, Neuroscience area, Istituto Italiano di Tecnologia, Genova, Italy
| | - Federica Maltese
- Genetics of Cognition Laboratory, Neuroscience area, Istituto Italiano di Tecnologia, Genova, Italy
| | - Xiao Chang
- Centre for Population Neuroscience and Stratified Medicine (PONS), Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, P. R. China
| | - Cinzia Molent
- Genetics of Cognition Laboratory, Neuroscience area, Istituto Italiano di Tecnologia, Genova, Italy
| | - Daniele Mauro
- Genetics of Cognition Laboratory, Neuroscience area, Istituto Italiano di Tecnologia, Genova, Italy
| | - Alberto Galbusera
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Dania Vecchia
- Optical Approaches to Brain Function Laboratory, Istituto Italiano di Tecnologia, Genova, Italy
| | - Federica Antonelli
- Genetics of Cognition Laboratory, Neuroscience area, Istituto Italiano di Tecnologia, Genova, Italy
| | - Arianna Benedetti
- Genetics of Cognition Laboratory, Neuroscience area, Istituto Italiano di Tecnologia, Genova, Italy
| | - Filippo Drago
- Department of Biomedical and Biotechnological Sciences, University of Catania, Catania, Italy
| | - Gian Marco Leggio
- Department of Biomedical and Biotechnological Sciences, University of Catania, Catania, Italy
| | - Marco Pagani
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Tommaso Fellin
- Optical Approaches to Brain Function Laboratory, Istituto Italiano di Tecnologia, Genova, Italy
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, P. R. China
- Centre for Population Neuroscience and Stratified Medicine (PONS), Charite Mental Health, Department of Psychiatry and Psychotherapy, CCM, Charite Universitätsmedizin Berlin, Berlin, Germany
| | - Francesca Managò
- Genetics of Cognition Laboratory, Neuroscience area, Istituto Italiano di Tecnologia, Genova, Italy
| | - Francesco Papaleo
- Genetics of Cognition Laboratory, Neuroscience area, Istituto Italiano di Tecnologia, Genova, Italy.
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5
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Scaglione A, Resta F, Goretti F, Pavone FS. Group ICA of wide-field calcium imaging data reveals the retrosplenial cortex as a major contributor to cortical activity during anesthesia. Front Cell Neurosci 2024; 18:1258793. [PMID: 38799987 PMCID: PMC11116703 DOI: 10.3389/fncel.2024.1258793] [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: 07/14/2023] [Accepted: 03/14/2024] [Indexed: 05/29/2024] Open
Abstract
Large-scale cortical dynamics play a crucial role in many cognitive functions such as goal-directed behaviors, motor learning and sensory processing. It is well established that brain states including wakefulness, sleep, and anesthesia modulate neuronal firing and synchronization both within and across different brain regions. However, how the brain state affects cortical activity at the mesoscale level is less understood. This work aimed to identify the cortical regions engaged in different brain states. To this end, we employed group ICA (Independent Component Analysis) to wide-field imaging recordings of cortical activity in mice during different anesthesia levels and the awake state. Thanks to this approach we identified independent components (ICs) representing elements of the cortical networks that are common across subjects under decreasing levels of anesthesia toward the awake state. We found that ICs related to the retrosplenial cortices exhibited a pronounced dependence on brain state, being most prevalent in deeper anesthesia levels and diminishing during the transition to the awake state. Analyzing the occurrence of the ICs we found that activity in deeper anesthesia states was characterized by a strong correlation between the retrosplenial components and this correlation decreases when transitioning toward wakefulness. Overall these results indicate that during deeper anesthesia states coactivation of the posterior-medial cortices is predominant over other connectivity patterns, whereas a richer repertoire of dynamics is expressed in lighter anesthesia levels and the awake state.
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Affiliation(s)
- Alessandro Scaglione
- Department of Physics and Astronomy, University of Florence, Florence, Italy
- European Laboratory for Non-Linear Spectroscopy (LENS), Florence, Italy
| | - Francesco Resta
- European Laboratory for Non-Linear Spectroscopy (LENS), Florence, Italy
- National Institute of Optics, National Research Council (INO-CNR), Sesto Fiorentino, Italy
| | - Francesco Goretti
- European Laboratory for Non-Linear Spectroscopy (LENS), Florence, Italy
| | - Francesco S. Pavone
- Department of Physics and Astronomy, University of Florence, Florence, Italy
- European Laboratory for Non-Linear Spectroscopy (LENS), Florence, Italy
- National Institute of Optics, National Research Council (INO-CNR), Sesto Fiorentino, Italy
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6
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Nghiem TAE, Lee B, Chao THH, Branigan NK, Mistry PK, Shih YYI, Menon V. Space wandering in the rodent default mode network. Proc Natl Acad Sci U S A 2024; 121:e2315167121. [PMID: 38557177 PMCID: PMC11009630 DOI: 10.1073/pnas.2315167121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Accepted: 01/17/2024] [Indexed: 04/04/2024] Open
Abstract
The default mode network (DMN) is a large-scale brain network known to be suppressed during a wide range of cognitive tasks. However, our comprehension of its role in naturalistic and unconstrained behaviors has remained elusive because most research on the DMN has been conducted within the restrictive confines of MRI scanners. Here, we use multisite GCaMP (a genetically encoded calcium indicator) fiber photometry with simultaneous videography to probe DMN function in awake, freely exploring rats. We examined neural dynamics in three core DMN nodes-the retrosplenial cortex, cingulate cortex, and prelimbic cortex-as well as the anterior insula node of the salience network, and their association with the rats' spatial exploration behaviors. We found that DMN nodes displayed a hierarchical functional organization during spatial exploration, characterized by stronger coupling with each other than with the anterior insula. Crucially, these DMN nodes encoded the kinematics of spatial exploration, including linear and angular velocity. Additionally, we identified latent brain states that encoded distinct patterns of time-varying exploration behaviors and found that higher linear velocity was associated with enhanced DMN activity, heightened synchronization among DMN nodes, and increased anticorrelation between the DMN and anterior insula. Our findings highlight the involvement of the DMN in collectively and dynamically encoding spatial exploration in a real-world setting. Our findings challenge the notion that the DMN is primarily a "task-negative" network disengaged from the external world. By illuminating the DMN's role in naturalistic behaviors, our study underscores the importance of investigating brain network function in ecologically valid contexts.
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Affiliation(s)
| | - Byeongwook Lee
- Department of Psychiatry & Behavioral Sciences, Stanford University, Palo Alto, CA94304
| | - Tzu-Hao Harry Chao
- Center for Animal MRI, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC27599
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC27599
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC27599
| | - Nicholas K. Branigan
- Department of Psychiatry & Behavioral Sciences, Stanford University, Palo Alto, CA94304
| | - Percy K. Mistry
- Department of Psychiatry & Behavioral Sciences, Stanford University, Palo Alto, CA94304
| | - Yen-Yu Ian Shih
- Center for Animal MRI, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC27599
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC27599
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC27599
- Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC27514
| | - Vinod Menon
- Department of Psychiatry & Behavioral Sciences, Stanford University, Palo Alto, CA94304
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA94304
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA94305
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7
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Shi L, Fu X, Gui S, Wan T, Zhuo J, Lu J, Li P. Global spatiotemporal synchronizing structures of spontaneous neural activities in different cell types. Nat Commun 2024; 15:2884. [PMID: 38570488 PMCID: PMC10991327 DOI: 10.1038/s41467-024-46975-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 03/13/2024] [Indexed: 04/05/2024] Open
Abstract
Increasing evidence has revealed the large-scale nonstationary synchronizations as traveling waves in spontaneous neural activity. However, the interplay of various cell types in fine-tuning these spatiotemporal patters remains unclear. Here, we performed comprehensive exploration of spatiotemporal synchronizing structures across different cell types, states (awake, anesthesia, motion) and developmental axis in male mice. We found traveling waves in glutamatergic neurons exhibited greater variety than those in GABAergic neurons. Moreover, the synchronizing structures of GABAergic neurons converged toward those of glutamatergic neurons during development, but the evolution of waves exhibited varying timelines for different sub-type interneurons. Functional connectivity arises from both standing and traveling waves, and negative connections can be elucidated by the spatial propagation of waves. In addition, some traveling waves were correlated with the spatial distribution of gene expression. Our findings offer further insights into the neural underpinnings of traveling waves, functional connectivity, and resting-state networks, with cell-type specificity and developmental perspectives.
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Affiliation(s)
- Liang Shi
- Britton Chance Center for Biomedical Photonics and MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Science, HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, 215100, China
| | - Xiaoxi Fu
- Britton Chance Center for Biomedical Photonics and MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Science, HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, 215100, China
| | - Shen Gui
- Britton Chance Center for Biomedical Photonics and MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Science, HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, 215100, China
| | - Tong Wan
- State Key Laboratory of Digital Medical Engineering, School of Biomedical Engineering, Hainan University, Sanya, 572025, China
| | - Junjie Zhuo
- State Key Laboratory of Digital Medical Engineering, School of Biomedical Engineering, Hainan University, Sanya, 572025, China
| | - Jinling Lu
- Britton Chance Center for Biomedical Photonics and MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Science, HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, 215100, China.
| | - Pengcheng Li
- Britton Chance Center for Biomedical Photonics and MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Science, HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, 215100, China.
- State Key Laboratory of Digital Medical Engineering, School of Biomedical Engineering, Hainan University, Sanya, 572025, China.
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Koga K, Kobayashi K, Tsuda M, Pickering AE, Furue H. Anterior cingulate cross-hemispheric inhibition via the claustrum resolves painful sensory conflict. Commun Biol 2024; 7:330. [PMID: 38491200 PMCID: PMC10943010 DOI: 10.1038/s42003-024-06008-9] [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: 12/08/2022] [Accepted: 03/04/2024] [Indexed: 03/18/2024] Open
Abstract
The anterior cingulate cortex (ACC) responds to noxious and innocuous sensory inputs, and integrates them to coordinate appropriate behavioral reactions. However, the role of the projections of ACC neurons to subcortical areas and their influence on sensory processing are not fully investigated. Here, we identified that ACC neurons projecting to the contralateral claustrum (ACC→contraCLA) preferentially respond to contralateral mechanical sensory stimulation. These sensory responses were enhanced during attending behavior. Optogenetic activation of ACC→contraCLA neurons silenced pyramidal neurons in the contralateral ACC by recruiting local circuit fast-spiking interneuron activation via an excitatory relay in the CLA. This circuit activation suppressed withdrawal behavior to mechanical stimuli ipsilateral to the ACC→contraCLA neurons. Chemogenetic silencing showed that the cross-hemispheric circuit has an important role in the suppression of contralateral nociceptive behavior during sensory-driven attending behavior. Our findings identify a cross-hemispheric cortical-subcortical-cortical arc allowing the brain to give attentional priority to competing innocuous and noxious inputs.
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Affiliation(s)
- Keisuke Koga
- Department of Neurophysiology, Hyogo Medical University, Nishinomiya, Japan.
| | - Kenta Kobayashi
- Section of Viral Vector Development, National Institute for Physiological Sciences, Okazaki, Japan
| | - Makoto Tsuda
- Department of Molecular and System Pharmacology, Graduate School of Pharmaceutical Sciences, Kyushu University, Fukuoka, Japan
| | - Anthony E Pickering
- Anesthesia, Pain and Critical Care Research, School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, UK
| | - Hidemasa Furue
- Department of Neurophysiology, Hyogo Medical University, Nishinomiya, Japan.
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9
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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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10
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Yu Z, Pang H, Yang Y, Luo D, Zheng H, Huang Z, Zhang M, Ren K. Microglia dysfunction drives disrupted hippocampal amplitude of low frequency after acute kidney injury. CNS Neurosci Ther 2024; 30:e14363. [PMID: 37469216 PMCID: PMC10848109 DOI: 10.1111/cns.14363] [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: 02/14/2023] [Revised: 06/20/2023] [Accepted: 06/24/2023] [Indexed: 07/21/2023] Open
Abstract
AIMS Acute kidney injury (AKI) has been associated with a variety of neurological problems, while the neurobiological mechanism remains unclear. In the present study, we utilized resting-state functional magnetic resonance imaging (rs-fMRI) to detect brain injury at an early stage and investigated the impact of microglia on the neuropathological mechanism of AKI. METHODS Rs-fMRI data were collected from AKI rats and the control group with a 9.4-Tesla scanner at 24, 48, and 72 h post administration of contrast medium or saline. The amplitude of low-frequency fluctuations (ALFF) was then compared across the groups at each time course. Additionally, flow cytometry and SMART-seq2 were employed to evaluate microglia. Furthermore, pathological staining and Western blot were used to analyze the samples. RESULTS MRI results revealed that AKI led to a decreased ALFF in the hippocampus, particularly in the 48 h and 72 h groups. Additionally, western blot suggested that AKI-induced the neuronal apoptosis at 48 h and 72 h. Flow cytometry and confocal microscopy images demonstrated that AKI activated the aggregation of microglia into neurons at 24 h, with a strong upregulation of M1 polarization at 48 h and peaking at 72 h, accompanying with the release of proinflammatory cytokines. The ALFF value was strongly correlated with the proportion of microglia (|r| > 0.80, p < 0.001). CONCLUSIONS Our study demonstrated that microglia aggregation and inflammatory factor upregulation are significant mechanisms of AKI-induced neuronal apoptosis. We used fMRI to detect the alterations in hippocampal function, which may provide a noninvasive method for the early detection of brain injury after AKI.
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Affiliation(s)
- Ziyang Yu
- School of MedicineXiamen UniversityXiamenChina
| | - Huize Pang
- Department of RadiologyThe First Hospital of China Medical UniversityShenyangChina
| | - Yifan Yang
- School of MedicineXiamen UniversityXiamenChina
| | - Doudou Luo
- School of MedicineXiamen UniversityXiamenChina
| | - Haiping Zheng
- State Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network, School of Life SciencesXiamen UniversityXiamenChina
| | - Zicheng Huang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics and Center for Molecular Imaging and Translational Medicine, School of Public HealthXiamen UniversityXiamenChina
| | - Mingxia Zhang
- State Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network, School of Life SciencesXiamen UniversityXiamenChina
| | - Ke Ren
- School of MedicineXiamen UniversityXiamenChina
- Department of RadiologyThe First Hospital of China Medical UniversityShenyangChina
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11
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Ragone E, Tanner J, Jo Y, Zamani Esfahlani F, Faskowitz J, Pope M, Coletta L, Gozzi A, Betzel R. Modular subgraphs in large-scale connectomes underpin spontaneous co-fluctuation events in mouse and human brains. Commun Biol 2024; 7:126. [PMID: 38267534 PMCID: PMC10810083 DOI: 10.1038/s42003-024-05766-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 01/02/2024] [Indexed: 01/26/2024] Open
Abstract
Previous studies have adopted an edge-centric framework to study fine-scale network dynamics in human fMRI. To date, however, no studies have applied this framework to data collected from model organisms. Here, we analyze structural and functional imaging data from lightly anesthetized mice through an edge-centric lens. We find evidence of "bursty" dynamics and events - brief periods of high-amplitude network connectivity. Further, we show that on a per-frame basis events best explain static FC and can be divided into a series of hierarchically-related clusters. The co-fluctuation patterns associated with each cluster centroid link distinct anatomical areas and largely adhere to the boundaries of algorithmically detected functional brain systems. We then investigate the anatomical connectivity undergirding high-amplitude co-fluctuation patterns. We find that events induce modular bipartitions of the anatomical network of inter-areal axonal projections. Finally, we replicate these same findings in a human imaging dataset. In summary, this report recapitulates in a model organism many of the same phenomena observed in previously edge-centric analyses of human imaging data. However, unlike human subjects, the murine nervous system is amenable to invasive experimental perturbations. Thus, this study sets the stage for future investigation into the causal origins of fine-scale brain dynamics and high-amplitude co-fluctuations. Moreover, the cross-species consistency of the reported findings enhances the likelihood of future translation.
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Affiliation(s)
| | - Jacob Tanner
- Cognitive Science Program, Indiana University, Bloomington, IN, 47401, USA
- School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, 47401, USA
| | - Youngheun Jo
- Department of Psychological and Brain Sciences and Cognitive Science Program, Indiana University, Bloomington, IN, 47401, USA
| | - Farnaz Zamani Esfahlani
- Stephenson School of Biomedical Engineering, The University of Oklahoma, Norman, OK, 73019, USA
| | - Joshua Faskowitz
- Department of Psychological and Brain Sciences and Cognitive Science Program, Indiana University, Bloomington, IN, 47401, USA
| | - Maria Pope
- School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, 47401, USA
- Program in Neuroscience, Indiana University, Bloomington, IN, 47401, USA
| | | | - Alessandro Gozzi
- Functional Neuroimaging Lab, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, Rovereto, Italy
| | - Richard Betzel
- Cognitive Science Program, Indiana University, Bloomington, IN, 47401, USA.
- Department of Psychological and Brain Sciences and Cognitive Science Program, Indiana University, Bloomington, IN, 47401, USA.
- Program in Neuroscience, Indiana University, Bloomington, IN, 47401, USA.
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12
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Mandino F, Shen X, Desrosiers-Gregoire G, O'Connor D, Mukherjee B, Owens A, Qu A, Onofrey J, Papademetris X, Chakravarty MM, Strittmatter SM, Lake EM. Aging-Dependent Loss of Connectivity in Alzheimer's Model Mice with Rescue by mGluR5 Modulator. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.15.571715. [PMID: 38260465 PMCID: PMC10802481 DOI: 10.1101/2023.12.15.571715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Amyloid accumulation in Alzheimer's disease (AD) is associated with synaptic damage and altered connectivity in brain networks. While measures of amyloid accumulation and biochemical changes in mouse models have utility for translational studies of certain therapeutics, preclinical analysis of altered brain connectivity using clinically relevant fMRI measures has not been well developed for agents intended to improve neural networks. Here, we conduct a longitudinal study in a double knock-in mouse model for AD ( App NL-G-F /hMapt ), monitoring brain connectivity by means of resting-state fMRI. While the 4-month-old AD mice are indistinguishable from wild-type controls (WT), decreased connectivity in the default-mode network is significant for the AD mice relative to WT mice by 6 months of age and is pronounced by 9 months of age. In a second cohort of 20-month-old mice with persistent functional connectivity deficits for AD relative to WT, we assess the impact of two-months of oral treatment with a silent allosteric modulator of mGluR5 (BMS-984923) known to rescue synaptic density. Functional connectivity deficits in the aged AD mice are reversed by the mGluR5-directed treatment. The longitudinal application of fMRI has enabled us to define the preclinical time trajectory of AD-related changes in functional connectivity, and to demonstrate a translatable metric for monitoring disease emergence, progression, and response to synapse-rescuing treatment.
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13
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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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14
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Gong L, Huang X, Hu Z, Chen C, Zhang Z, Liao H, Xiao Y, Fan J, Zeng L, Chen S, Xie Y. Altered functional connectivity after pilocarpine-induced seizures revealed by intrinsic optical signals imaging in awake mice. NEUROPHOTONICS 2024; 11:015001. [PMID: 38125610 PMCID: PMC10729166 DOI: 10.1117/1.nph.11.1.015001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 11/05/2023] [Accepted: 11/28/2023] [Indexed: 12/23/2023]
Abstract
Significance Comorbidities such as mood and cognitive disorders are often found in individuals with epilepsy after seizures. Cortex processes sensory, motor, and cognitive information. Brain circuit changes can be studied by observing functional network changes in epileptic mice's cortex. Aim The cortex is easily accessible for non-invasive brain imaging and electroencephalogram recording (EEG). However, the impact of seizures on cortical activity and functional connectivity has been rarely studied in vivo. Approach Intrinsic optical signal and EEG were used to monitor cortical activity in awake mice within 4 h after pilocarpine induction. It was divided into three periods according to the behavior and EEG of the mice: baseline, onset of seizures (onset, including seizures and resting in between seizure events), and after seizures (post, without seizures). Changes in cortical activity were compared between the baseline and after seizures. Results Hemoglobin levels increased significantly, particularly in the parietal association cortex (PT), retrosplenial cortex (RS), primary visual cortex (V1), and secondary visual cortex (V2). The network-wide functional connectivity changed post seizures, e.g., hypoconnectivity between PT and visual-associated cortex (e.g., V1 and V2). In contrast, connectivity between the motor-associated cortex and most other regions increased. In addition, the default mode network (DMN) also changed after seizures, with decreased connectivity between primary somatosensory region (SSp) and visual region (VIS), but increased connectivity involving anterior cingulate cortex (AC) and RS. Conclusions Our results provide references for understanding the mechanisms behind changes in brain circuits, which may explain the profound effects of seizures on comorbid health conditions.
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Affiliation(s)
- Lifen Gong
- Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Department of Neonatal Surgery, Hangzhou, China
- The First Affiliated Hospital, Zhejiang University School of Medicine, Department of Neurosurgery and Pediatrics, Hangzhou, China
| | - Xin Huang
- The First Affiliated Hospital, Zhejiang University School of Medicine, Department of Neurosurgery and Pediatrics, Hangzhou, China
| | - Zhe Hu
- Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Department of Neonatal Surgery, Hangzhou, China
| | - Chen Chen
- Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Department of Neonatal Surgery, Hangzhou, China
| | - Ziqi Zhang
- Huazhong University of Science and Technology, Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Wuhan, China
| | - Hongxuan Liao
- Huazhong University of Science and Technology, Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Wuhan, China
| | - Yinglin Xiao
- Huazhong University of Science and Technology, Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Wuhan, China
| | - Jianchen Fan
- Hangzhou City University, School of Medicine, Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, Hangzhou, China
| | - Linghui Zeng
- Hangzhou City University, School of Medicine, Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, Hangzhou, China
| | - Shangbin Chen
- Huazhong University of Science and Technology, Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Wuhan, China
| | - Yicheng Xie
- Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Department of Neonatal Surgery, Hangzhou, China
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15
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Griffa A, Mach M, Dedelley J, Gutierrez-Barragan D, Gozzi A, Allali G, Grandjean J, Van De Ville D, Amico E. Evidence for increased parallel information transmission in human brain networks compared to macaques and male mice. Nat Commun 2023; 14:8216. [PMID: 38081838 PMCID: PMC10713651 DOI: 10.1038/s41467-023-43971-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 11/24/2023] [Indexed: 12/18/2023] Open
Abstract
Brain communication, defined as information transmission through white-matter connections, is at the foundation of the brain's computational capacities that subtend almost all aspects of behavior: from sensory perception shared across mammalian species, to complex cognitive functions in humans. How did communication strategies in macroscale brain networks adapt across evolution to accomplish increasingly complex functions? By applying a graph- and information-theory approach to assess information-related pathways in male mouse, macaque and human brains, we show a brain communication gap between selective information transmission in non-human mammals, where brain regions share information through single polysynaptic pathways, and parallel information transmission in humans, where regions share information through multiple parallel pathways. In humans, parallel transmission acts as a major connector between unimodal and transmodal systems. The layout of information-related pathways is unique to individuals across different mammalian species, pointing at the individual-level specificity of information routing architecture. Our work provides evidence that different communication patterns are tied to the evolution of mammalian brain networks.
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Affiliation(s)
- Alessandra Griffa
- Leenaards Memory Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
- Medical Image Processing Laboratory, Neuro-X Institute, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland.
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland.
| | - Mathieu Mach
- Medical Image Processing Laboratory, Neuro-X Institute, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland
| | - Julien Dedelley
- Medical Image Processing Laboratory, Neuro-X Institute, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland
| | - Daniel Gutierrez-Barragan
- Functional Neuroimaging 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
| | - Gilles Allali
- Leenaards Memory Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Joanes Grandjean
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, 6525 EN, Nijmegen, The Netherlands
| | - Dimitri Van De Ville
- Medical Image Processing Laboratory, Neuro-X Institute, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
| | - Enrico Amico
- Medical Image Processing Laboratory, Neuro-X Institute, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland.
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland.
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16
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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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17
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Urushihata T, Goto M, Kabetani K, Kiyozuka M, Maruyama S, Tsuji S, Tada H, Satoh A. Evaluation of cellular activity in response to sleep deprivation by a comprehensive analysis of the whole mouse brain. Front Neurosci 2023; 17:1252689. [PMID: 37928729 PMCID: PMC10620513 DOI: 10.3389/fnins.2023.1252689] [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: 07/04/2023] [Accepted: 09/12/2023] [Indexed: 11/07/2023] Open
Abstract
Sleep deprivation (SD) causes several adverse functional outcomes, and understanding the associated processes can improve quality of life. Although the effects of SD on neuronal activity in several brain regions have been identified, a comprehensive evaluation of the whole brain is still lacking. Hence, we performed SD using two different methods, gentle handling and a dedicated chamber, in targeted recombination in active populations 2 (TRAP2) mice crossed with Rosa-ZsGreen reporter mice and visualized cellular activity in the whole brain. Using the semi-automated post-imaging analysis tool Slice Histology Alignment, Registration, and Cell Quantification (SHARCQ), the number of activated cells was quantified. From the analysis of 14 brain regions, cellular activity was significantly increased in the olfactory areas and decreased in the medulla by the two SD methods. From the analysis of the further subdivided 348 regions, cellular activity was significantly increased in the vascular organ of the lamina terminalis, lateral hypothalamic area, parabigeminal nucleus, ventral tegmental area, and magnocellular reticular nucleus, and decreased in the anterior part of the basolateral amygdalar nucleus, nucleus accumbens, septohippocampal nucleus, reticular nucleus of the thalamus, preoptic part of the periventricular hypothalamic nucleus, ventromedial preoptic nucleus, rostral linear nucleus raphe, facial motor nucleus, vestibular nuclei, and some fiber tracts (oculomotor nerve, genu of corpus callosum, and rubrospinal tract) by the two SD methods. Two subdivided regions of the striatum (caudoputamen and other striatum), epithalamus, vascular organ of the lamina terminalis, anteroventral preoptic nucleus, superior colliculus optic layer, medial terminal nucleus of the accessory optic tract, pontine gray, and fiber tracts (medial lemniscus, columns of the fornix, brachium of the inferior colliculus, and mammillary peduncle) were differentially affected by the two SD methods. Most brain regions detected from these analyses have been reported to be involved in regulating sleep/wake regulatory circuits. Moreover, the results from the connectivity analysis indicated that the connectivity of cellular activity among brain regions was altered by SD. Together, such a comprehensive analysis of the whole brain is useful for understanding the mechanisms by which SD and/or sleep disruption affects brain function.
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Affiliation(s)
- Takuya Urushihata
- Department of Integrative Physiology, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
- Department of Integrative Physiology, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Mio Goto
- Department of Integrative Physiology, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Keiko Kabetani
- Department of Integrative Physiology, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Mai Kiyozuka
- Department of Integrative Physiology, National Center for Geriatrics and Gerontology, Obu, Japan
- Department of Nutrition, Faculty of Wellness, Shigakkan University, Obu, Japan
| | - Shiho Maruyama
- Department of Integrative Physiology, National Center for Geriatrics and Gerontology, Obu, Japan
- Department of Nutrition, Faculty of Wellness, Shigakkan University, Obu, Japan
| | - Shogo Tsuji
- Department of Integrative Physiology, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Hirobumi Tada
- Department of Integrative Physiology, National Center for Geriatrics and Gerontology, Obu, Japan
- Department of Nutrition, Faculty of Wellness, Shigakkan University, Obu, Japan
- Department of Physiology, Yokohama City University Graduate School of Medicine, Yokohama, Japan
| | - Akiko Satoh
- Department of Integrative Physiology, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
- Department of Integrative Physiology, National Center for Geriatrics and Gerontology, Obu, Japan
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18
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Deivasigamani S, Miteva MT, Natale S, Gutierrez-Barragan D, Basilico B, Di Angelantonio S, Weinhard L, Molotkov D, Deb S, Pape C, Bolasco G, Galbusera A, Asari H, Gozzi A, Ragozzino D, Gross CT. Microglia complement signaling promotes neuronal elimination and normal brain functional connectivity. Cereb Cortex 2023; 33:10750-10760. [PMID: 37718159 PMCID: PMC10629900 DOI: 10.1093/cercor/bhad313] [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: 12/05/2022] [Revised: 08/10/2023] [Accepted: 08/11/2023] [Indexed: 09/19/2023] Open
Abstract
Complement signaling is thought to serve as an opsonization signal to promote the phagocytosis of synapses by microglia. However, while its role in synaptic remodeling has been demonstrated in the retino-thalamic system, it remains unclear whether complement signaling mediates synaptic pruning in the brain more generally. Here we found that mice lacking the Complement receptor 3, the major microglia complement receptor, failed to show a deficit in either synaptic pruning or axon elimination in the developing mouse cortex. Instead, mice lacking Complement receptor 3 exhibited a deficit in the perinatal elimination of neurons in the cortex, a deficit that is associated with increased cortical thickness and enhanced functional connectivity in these regions in adulthood. These data demonstrate a role for complement in promoting neuronal elimination in the developing cortex.
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Affiliation(s)
- Senthilkumar Deivasigamani
- Epigenetics & Neurobiology Unit, EMBL Rome, European Molecular Biology Laboratory, Via Ramarini 32, 00015 Monterotondo, Italy
| | - Mariya T Miteva
- Epigenetics & Neurobiology Unit, EMBL Rome, European Molecular Biology Laboratory, Via Ramarini 32, 00015 Monterotondo, Italy
- Neuroscience Masters Programme, Sapienza University, Piazza Aldo Moro 1, 00185 Roma, Italy
| | - Silvia Natale
- Epigenetics & Neurobiology Unit, EMBL Rome, European Molecular Biology Laboratory, Via Ramarini 32, 00015 Monterotondo, Italy
- Division of Pharmacology, Department of Neuroscience, Reproductive and Odontostomatologic Sciences, School of Medicine, University of Naples Federico II, Via Pansini 5, 80131 Naples, Italy
| | - Daniel Gutierrez-Barragan
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @ UNITN, 38068 Rovereto, Italy
| | - Bernadette Basilico
- Department of Physiology and Pharmacology, Sapienza University of Rome, 00185 Rome, Italy
- Center for Life Nano- & Neuro-Science, Istituto Italiano di Tecnologia, 00161 Rome, Italy
| | - Silvia Di Angelantonio
- Department of Physiology and Pharmacology, Sapienza University of Rome, 00185 Rome, Italy
- Center for Life Nano- & Neuro-Science, Istituto Italiano di Tecnologia, 00161 Rome, Italy
| | - Laetitia Weinhard
- Epigenetics & Neurobiology Unit, EMBL Rome, European Molecular Biology Laboratory, Via Ramarini 32, 00015 Monterotondo, Italy
| | - Dmitry Molotkov
- Epigenetics & Neurobiology Unit, EMBL Rome, European Molecular Biology Laboratory, Via Ramarini 32, 00015 Monterotondo, Italy
| | - Sukrita Deb
- Epigenetics & Neurobiology Unit, EMBL Rome, European Molecular Biology Laboratory, Via Ramarini 32, 00015 Monterotondo, Italy
| | - Constantin Pape
- Cell Biology and Biophysics Unit, EMBL Heidelberg, Meyerhofstraße 1, 69117 Heidelberg, Germany
| | - Giulia Bolasco
- Epigenetics & Neurobiology Unit, EMBL Rome, European Molecular Biology Laboratory, Via Ramarini 32, 00015 Monterotondo, Italy
| | - Alberto Galbusera
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @ UNITN, 38068 Rovereto, Italy
| | - Hiroki Asari
- Epigenetics & Neurobiology Unit, EMBL Rome, European Molecular Biology Laboratory, Via Ramarini 32, 00015 Monterotondo, Italy
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @ UNITN, 38068 Rovereto, Italy
| | - Davide Ragozzino
- Department of Physiology and Pharmacology, Sapienza University of Rome, 00185 Rome, Italy
- Santa Lucia Foundation (IRCCS Fondazione Santa Lucia), Via Ardeatina, 00179 Rome, Italy
| | - Cornelius T Gross
- Epigenetics & Neurobiology Unit, EMBL Rome, European Molecular Biology Laboratory, Via Ramarini 32, 00015 Monterotondo, Italy
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19
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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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20
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Hikishima K, Tsurugizawa T, Kasahara K, Takagi R, Yoshinaka K, Nitta N. Brain-wide mapping of resting-state networks in mice using high-frame rate functional ultrasound. Neuroimage 2023; 279:120297. [PMID: 37500027 DOI: 10.1016/j.neuroimage.2023.120297] [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: 04/21/2023] [Revised: 06/21/2023] [Accepted: 07/25/2023] [Indexed: 07/29/2023] Open
Abstract
Functional ultrasound (fUS) imaging is a method for visualizing deep brain activity based on cerebral blood volume changes coupled with neural activity, while functional MRI (fMRI) relies on the blood-oxygenation-level-dependent signal coupled with neural activity. Low-frequency fluctuations (LFF) of fMRI signals during resting-state can be measured by resting-state fMRI (rsfMRI), which allows functional imaging of the whole brain, and the distributions of resting-state network (RSN) can then be estimated from these fluctuations using independent component analysis (ICA). This procedure provides an important method for studying cognitive and psychophysiological diseases affecting specific brain networks. The distributions of RSNs in the brain-wide area has been reported primarily by rsfMRI. RSNs using rsfMRI are generally computed from the time-course of fMRI signals for more than 5 min. However, a recent dynamic functional connectivity study revealed that RSNs are still not perfectly stable even after 10 min. Importantly, fUS has a higher temporal resolution and stronger correlation with neural activity compared with fMRI. Therefore, we hypothesized that fUS applied during the resting-state for a shorter than 5 min would provide similar RSNs compared to fMRI. High temporal resolution rsfUS data were acquired at 10 Hz in awake mice. The quality of the default mode network (DMN), a well-known RSN, was evaluated using signal-noise separation (SNS) applied to different measurement durations of rsfUS. The results showed that the SNS did not change when the measurement duration was increased to more than 210 s. Next, we measured short-duration rsfUS multi-slice measurements in the brain-wide area. The results showed that rsfUS with the short duration succeeded in detecting RSNs distributed in the brain-wide area consistent with RSNs detected by 11.7-T MRI under awake conditions (medial prefrontal cortex and cingulate cortex in the anterior DMN, retrosplenial cortex and visual cortex in the posterior DMN, somatosensory and motor cortexes in the lateral cortical network, thalamus, dorsal hippocampus, and medial cerebellum), confirming the reliability of the RSNs detected by rsfUS. However, bilateral RSNs located in the secondary somatosensory cortex, ventral hippocampus, auditory cortex, and lateral cerebellum extracted from rsfUS were different from the unilateral RSNs extracted from rsfMRI. These findings indicate the potential of rsfUS as a method for analyzing functional brain networks and should encourage future research to elucidate functional brain networks and their relationships with disease model mice.
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Affiliation(s)
- Keigo Hikishima
- Health and Medical Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Ibaraki, Japan; Okinawa Institute of Science and Technology Graduate University (OIST), Okinawa, Japan.
| | - Tomokazu Tsurugizawa
- Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Ibaraki, Japan
| | - Kazumi Kasahara
- Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Ibaraki, Japan
| | - Ryo Takagi
- Health and Medical Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Ibaraki, Japan
| | - Kiyoshi Yoshinaka
- Health and Medical Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Ibaraki, Japan
| | - Naotaka Nitta
- Health and Medical Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Ibaraki, Japan
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21
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Reznik D, Trampel R, Weiskopf N, Witter MP, Doeller CF. Dissociating distinct cortical networks associated with subregions of the human medial temporal lobe using precision neuroimaging. Neuron 2023; 111:2756-2772.e7. [PMID: 37390820 DOI: 10.1016/j.neuron.2023.05.029] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 05/26/2023] [Accepted: 05/27/2023] [Indexed: 07/02/2023]
Abstract
Tract-tracing studies in primates indicate that different subregions of the medial temporal lobe (MTL) are connected with multiple brain regions. However, no clear framework defining the distributed anatomy associated with the human MTL exists. This gap in knowledge originates in notoriously low MRI data quality in the anterior human MTL and in group-level blurring of idiosyncratic anatomy between adjacent brain regions, such as entorhinal and perirhinal cortices, and parahippocampal areas TH/TF. Using MRI, we intensively scanned four human individuals and collected whole-brain data with unprecedented MTL signal quality. Following detailed exploration of cortical networks associated with MTL subregions within each individual, we discovered three biologically meaningful networks associated with the entorhinal cortex, perirhinal cortex, and parahippocampal area TH, respectively. Our findings define the anatomical constraints within which human mnemonic functions must operate and are insightful for examining the evolutionary trajectory of the MTL connectivity across species.
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Affiliation(s)
- Daniel Reznik
- Department of Psychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Robert Trampel
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany
| | - Menno P Witter
- Kavli Institute for Systems Neuroscience, Centre for Neural Computation, Egil and Pauline Braathen and Fred Kavli Centre for Cortical Microcircuits, Jebsen Centre for Alzheimer's Disease, NTNU Norwegian University of Science and Technology, Trondheim, Norway
| | - Christian F Doeller
- Department of Psychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Kavli Institute for Systems Neuroscience, Centre for Neural Computation, Egil and Pauline Braathen and Fred Kavli Centre for Cortical Microcircuits, Jebsen Centre for Alzheimer's Disease, NTNU Norwegian University of Science and Technology, Trondheim, Norway; Wilhelm Wundt Institute of Psychology, Leipzig University, Leipzig, Germany; Department of Psychology, Technische Universität Dresden, Dresden, Germany.
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22
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Nghiem TAE, Lee B, Chao THH, Branigan NK, Mistry PK, Shih YYI, Menon V. Space wandering in the rodent default mode network. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.31.555793. [PMID: 37693501 PMCID: PMC10491169 DOI: 10.1101/2023.08.31.555793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
The default mode network (DMN) is a large-scale brain network known to be suppressed during a wide range of cognitive tasks. However, our comprehension of its role in naturalistic and unconstrained behaviors has remained elusive because most research on the DMN has been conducted within the restrictive confines of MRI scanners. Here we use multisite GCaMP fiber photometry with simultaneous videography to probe DMN function in awake, freely exploring rats. We examined neural dynamics in three core DMN nodes- the retrosplenial cortex, cingulate cortex, and prelimbic cortex- as well as the anterior insula node of the salience network, and their association with the rats' spatial exploration behaviors. We found that DMN nodes displayed a hierarchical functional organization during spatial exploration, characterized by stronger coupling with each other than with the anterior insula. Crucially, these DMN nodes encoded the kinematics of spatial exploration, including linear and angular velocity. Additionally, we identified latent brain states that encoded distinct patterns of time-varying exploration behaviors and discovered that higher linear velocity was associated with enhanced DMN activity, heightened synchronization among DMN nodes, and increased anticorrelation between the DMN and anterior insula. Our findings highlight the involvement of the DMN in collectively and dynamically encoding spatial exploration in a real-world setting. Our findings challenge the notion that the DMN is primarily a "task-negative" network disengaged from the external world. By illuminating the DMN's role in naturalistic behaviors, our study underscores the importance of investigating brain network function in ecologically valid contexts.
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Affiliation(s)
| | - Byeongwook Lee
- Department of Psychiatry & Behavioral Sciences, Stanford University
| | - Tzu-Hao Harry Chao
- Center for Animal MRI, University of North Carolina at Chapel Hill
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill
- Department of Neurology, University of North Carolina at Chapel Hill
| | | | - Percy K. Mistry
- Department of Psychiatry & Behavioral Sciences, Stanford University
| | - Yen-Yu Ian Shih
- Center for Animal MRI, University of North Carolina at Chapel Hill
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill
- Department of Neurology, University of North Carolina at Chapel Hill
- Department of Biomedical Engineering, University of North Carolina at Chapel Hill
| | - Vinod Menon
- Department of Psychiatry & Behavioral Sciences, Stanford University
- Department of Neurology & Neurological Sciences, Stanford University
- Wu Tsai Neurosciences Institute, Stanford University
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23
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Lee SH, Shnitko TA, Hsu LM, Broadwater MA, Sardinas M, Wang TWW, Robinson DL, Vetreno RP, Crews FT, Shih YYI. Acute alcohol induces greater dose-dependent increase in the lateral cortical network functional connectivity in adult than adolescent rats. ADDICTION NEUROSCIENCE 2023; 7:100105. [PMID: 37576436 PMCID: PMC10421607 DOI: 10.1016/j.addicn.2023.100105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Alcohol misuse and, particularly adolescent drinking, is a major public health concern. While evidence suggests that adolescent alcohol use affects frontal brain regions that are important for cognitive control over behavior little is known about how acute alcohol exposure alters large-scale brain networks and how sex and age may moderate such effects. Here, we employ a recently developed functional magnetic resonance imaging (fMRI) protocol to acquire rat brain functional connectivity data and use an established analytical pipeline to examine the effect of sex, age, and alcohol dose on connectivity within and between three major rodent brain networks: defaul mode, salience, and lateral cortical network. We identify the intra- and inter-network connectivity differences and establish moderation models to reveal significant influences of age on acute alcohol-induced lateral cortical network connectivity. Through this work, we make brain-wide isotropic fMRI data with acute alcohol challenge publicly available, with the hope to facilitate future discovery of brain regions/circuits that are causally relevant to the impact of acute alcohol use.
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Affiliation(s)
- Sung-Ho Lee
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina, Chapel Hill, NC, USA
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA
| | - Tatiana A. Shnitko
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina, Chapel Hill, NC, USA
| | - Li-Ming Hsu
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina, Chapel Hill, NC, USA
| | - Margaret A. Broadwater
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina, Chapel Hill, NC, USA
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA
| | - Mabelle Sardinas
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina, Chapel Hill, NC, USA
| | - Tzu-Wen Winnie Wang
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina, Chapel Hill, NC, USA
| | - Donita L. Robinson
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Ryan P. Vetreno
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Fulton T. Crews
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
- Department of Pharmacology, University of North Carolina, Chapel Hill, NC, USA
| | - Yen-Yu Ian Shih
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina, Chapel Hill, NC, USA
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA
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24
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Brynildsen JK, Rajan K, Henderson MX, Bassett DS. Network models to enhance the translational impact of cross-species studies. Nat Rev Neurosci 2023; 24:575-588. [PMID: 37524935 PMCID: PMC10634203 DOI: 10.1038/s41583-023-00720-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/17/2023] [Indexed: 08/02/2023]
Abstract
Neuroscience studies are often carried out in animal models for the purpose of understanding specific aspects of the human condition. However, the translation of findings across species remains a substantial challenge. Network science approaches can enhance the translational impact of cross-species studies by providing a means of mapping small-scale cellular processes identified in animal model studies to larger-scale inter-regional circuits observed in humans. In this Review, we highlight the contributions of network science approaches to the development of cross-species translational research in neuroscience. We lay the foundation for our discussion by exploring the objectives of cross-species translational models. We then discuss how the development of new tools that enable the acquisition of whole-brain data in animal models with cellular resolution provides unprecedented opportunity for cross-species applications of network science approaches for understanding large-scale brain networks. We describe how these tools may support the translation of findings across species and imaging modalities and highlight future opportunities. Our overarching goal is to illustrate how the application of network science tools across human and animal model studies could deepen insight into the neurobiology that underlies phenomena observed with non-invasive neuroimaging methods and could simultaneously further our ability to translate findings across species.
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Affiliation(s)
- Julia K Brynildsen
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Kanaka Rajan
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Michael X Henderson
- Parkinson's Disease Center, Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, USA
| | - Dani S Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
- Santa Fe Institute, Santa Fe, NM, USA.
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25
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Parkes L, Kim JZ, Stiso J, Brynildsen JK, Cieslak M, Covitz S, Gur RE, Gur RC, Pasqualetti F, Shinohara RT, Zhou D, Satterthwaite TD, Bassett DS. Using network control theory to study the dynamics of the structural connectome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.23.554519. [PMID: 37662395 PMCID: PMC10473719 DOI: 10.1101/2023.08.23.554519] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Network control theory (NCT) is a simple and powerful tool for studying how network topology informs and constrains dynamics. Compared to other structure-function coupling approaches, the strength of NCT lies in its capacity to predict the patterns of external control signals that may alter dynamics in a desired way. We have extensively developed and validated the application of NCT to the human structural connectome. Through these efforts, we have studied (i) how different aspects of connectome topology affect neural dynamics, (ii) whether NCT outputs cohere with empirical data on brain function and stimulation, and (iii) how NCT outputs vary across development and correlate with behavior and mental health symptoms. In this protocol, we introduce a framework for applying NCT to structural connectomes following two main pathways. Our primary pathway focuses on computing the control energy associated with transitioning between specific neural activity states. Our second pathway focuses on computing average controllability, which indexes nodes' general capacity to control dynamics. We also provide recommendations for comparing NCT outputs against null network models. Finally, we support this protocol with a Python-based software package called network control theory for python (nctpy).
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Affiliation(s)
- Linden Parkes
- Department of Bioengineering, University of Pennsylvania, PA 19104, USA
- Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, Rutgers University, Piscataway, NJ 08854, USA
| | - Jason Z Kim
- Department of Physics, Cornell University, Ithaca, NY 14853, USA
| | - Jennifer Stiso
- Department of Bioengineering, University of Pennsylvania, PA 19104, USA
| | | | - Matthew Cieslak
- Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn/CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sydney Covitz
- Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn/CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Raquel E Gur
- Penn/CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Ruben C Gur
- Penn/CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Fabio Pasqualetti
- Department of Mechanical Engineering, University of California, Riverside, Riverside, CA 92521, USA
| | - Russell T Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, Philadelphia, PA 19104, USA
- Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Dale Zhou
- Department of Bioengineering, University of Pennsylvania, PA 19104, USA
| | - Theodore D Satterthwaite
- Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn/CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Dani S Bassett
- Department of Bioengineering, University of Pennsylvania, PA 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, Philadelphia, PA 19104, USA
- Department of Electrical and Systems Engineering, University of Pennsylvania, PA 19104, USA
- Department of Physics and Astronomy, University of Pennsylvania, PA 19104, USA
- Santa Fe Institute, Santa Fe, NM 87501, USA
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26
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Liu Y, Jiang S, Li Y, Zhao S, Yun Z, Zhao ZH, Zhang L, Wang G, Chen X, Manubens-Gil L, Hang Y, Garcia-Forn M, Wang W, Rubeis SD, Wu Z, Osten P, Gong H, Hawrylycz M, Mitra P, Dong H, Luo Q, Ascoli GA, Zeng H, Liu L, Peng H. Full-Spectrum Neuronal Diversity and Stereotypy through Whole Brain Morphometry. RESEARCH SQUARE 2023:rs.3.rs-3146034. [PMID: 37546984 PMCID: PMC10402258 DOI: 10.21203/rs.3.rs-3146034/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
We conducted a large-scale study of whole-brain morphometry, analyzing 3.7 peta-voxels of mouse brain images at the single-cell resolution, producing one of the largest multi-morphometry databases of mammalian brains to date. We spatially registered 205 mouse brains and associated data from six Brain Initiative Cell Census Network (BICCN) data sources covering three major imaging modalities from five collaborative projects to the Allen Common Coordinate Framework (CCF) atlas, annotated 3D locations of cell bodies of 227,581 neurons, modeled 15,441 dendritic microenvironments, characterized the full morphology of 1,891 neurons along with their axonal motifs, and detected 2.58 million putative synaptic boutons. Our analysis covers six levels of information related to neuronal populations, dendritic microenvironments, single-cell full morphology, sub-neuronal dendritic and axonal arborization, axonal boutons, and structural motifs, along with a quantitative characterization of the diversity and stereotypy of patterns at each level. We identified 16 modules consisting of highly intercorrelated brain regions in 13 functional brain areas corresponding to 314 anatomical regions in CCF. Our analysis revealed the dendritic microenvironment as a powerful method for delineating brain regions of cell types and potential subtypes. We also found that full neuronal morphologies can be categorized into four distinct classes based on spatially tuned morphological features, with substantial cross-areal diversity in apical dendrites, basal dendrites, and axonal arbors, along with quantified stereotypy within cortical, thalamic and striatal regions. The lamination of somas was found to be more effective in differentiating neuron arbors within the cortex. Further analysis of diverging and converging projections of individual neurons in 25 regions throughout the brain reveals branching preferences in the brain-wide and local distributions of axonal boutons. Overall, our study provides a comprehensive description of key anatomical structures of neurons and their types, covering a wide range of scales and features, and contributes to our understanding of neuronal diversity and its function in the mammalian brain.
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Affiliation(s)
- Yufeng Liu
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Shengdian Jiang
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Yingxin Li
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Sujun Zhao
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Zhixi Yun
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Zuo-Han Zhao
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Lingli Zhang
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Gaoyu Wang
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Xin Chen
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Linus Manubens-Gil
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Yuning Hang
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Marta Garcia-Forn
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Alper Center for Neural Development and Regeneration, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Wei Wang
- Appel Alzheimer’s Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
- Department of Cell, Developmental & Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Silvia De Rubeis
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Alper Center for Neural Development and Regeneration, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Zhuhao Wu
- Appel Alzheimer’s Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
- Department of Cell, Developmental & Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Pavel Osten
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Hui Gong
- HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, China
| | | | - Partha Mitra
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Hongwei Dong
- Center for Integrative Connectomics, Department of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Qingming Luo
- State Key Laboratory of Digital Medical Engineering, School of Biomedical Engineering, Hainan University, Haikou, China
- Key Laboratory of Biomedical Engineering of Hainan Province, One Health Institute, Hainan University, Haikou, China
| | - Giorgio A. Ascoli
- Volgenau School of Engineering, George Mason University, Fairfax, VA, USA
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Lijuan Liu
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Hanchuan Peng
- SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China
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Choi S, Chen Y, Zeng H, Biswal B, Yu X. Identifying the distinct spectral dynamics of laminar-specific interhemispheric connectivity with bilateral line-scanning fMRI. J Cereb Blood Flow Metab 2023; 43:1115-1129. [PMID: 36803280 PMCID: PMC10291453 DOI: 10.1177/0271678x231158434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 11/30/2022] [Accepted: 12/12/2022] [Indexed: 02/23/2023]
Abstract
Despite extensive efforts to identify interhemispheric functional connectivity (FC) with resting-state (rs-) fMRI, correlated low-frequency rs-fMRI signal fluctuation across homotopic cortices originates from multiple sources. It remains challenging to differentiate circuit-specific FC from global regulation. Here, we developed a bilateral line-scanning fMRI method to detect laminar-specific rs-fMRI signals from homologous forepaw somatosensory cortices with high spatial and temporal resolution in rat brains. Based on spectral coherence analysis, two distinct bilateral fluctuation spectral features were identified: ultra-slow fluctuation (<0.04 Hz) across all cortical laminae versus Layer (L) 2/3-specific evoked BOLD at 0.05 Hz based on 4 s on/16 s off block design and resting-state fluctuations at 0.08-0.1 Hz. Based on the measurements of evoked BOLD signal at corpus callosum (CC), this L2/3-specific 0.05 Hz signal is likely associated with neuronal circuit-specific activity driven by the callosal projection, which dampened ultra-slow oscillation less than 0.04 Hz. Also, the rs-fMRI power variability clustering analysis showed that the appearance of L2/3-specific 0.08-0.1 Hz signal fluctuation is independent of the ultra-slow oscillation across different trials. Thus, distinct laminar-specific bilateral FC patterns at different frequency ranges can be identified by the bilateral line-scanning fMRI method.
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Affiliation(s)
- Sangcheon Choi
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA
- Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Yi Chen
- Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Hang Zeng
- Max Planck Institute for Biological Cybernetics, Tübingen, Germany
- Graduate Training Centre of Neuroscience, University of Tübingen, Tübingen, Germany
| | - Bharat Biswal
- Department of Biomedical Engineering, NJIT, Newark, NJ, USA
| | - Xin Yu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA
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28
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Zhang Q, Jing W, Wu S, Zhu M, Jiang J, Liu X, Yu D, Cheng L, Feng B, Wen J, Xiong F, Lu Y, Du H. Development of a synchronous recording and photo-stimulating electrode in multiple brain neurons. Front Neurosci 2023; 17:1195095. [PMID: 37383109 PMCID: PMC10293621 DOI: 10.3389/fnins.2023.1195095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 05/25/2023] [Indexed: 06/30/2023] Open
Abstract
The investigation of brain networks and neural circuits involves the crucial aspects of observing and modulating neurophysiological activity. Recently, opto-electrodes have emerged as an efficient tool for electrophysiological recording and optogenetic stimulation, which has greatly facilitated the analysis of neural coding. However, implantation and electrode weight control have posed significant challenges in achieving long-term and multi-regional brain recording and stimulation. To address this issue, we have developed a mold and custom-printed circuit board-based opto-electrode. We report successful opto-electrode placement and high-quality electrophysiological recordings from the default mode network (DMN) of the mouse brain. This novel opto-electrode facilitates synchronous recording and stimulation in multiple brain regions and holds promise for advancing future research on neural circuits and networks.
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Affiliation(s)
- Qingping Zhang
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Wuhan Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Department of Pathophysiology, School of Basic Medicine, Huazhong University of Science and Technology, Wuhan, China
| | - Wei Jing
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Wuhan Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Department of Pathophysiology, School of Basic Medicine, Huazhong University of Science and Technology, Wuhan, China
| | - Shiping Wu
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Wuhan Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Department of Pathophysiology, School of Basic Medicine, Huazhong University of Science and Technology, Wuhan, China
| | - Mengzheng Zhu
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Wuhan Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Department of Pathophysiology, School of Basic Medicine, Huazhong University of Science and Technology, Wuhan, China
| | - Jingrui Jiang
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Wuhan Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Department of Pathophysiology, School of Basic Medicine, Huazhong University of Science and Technology, Wuhan, China
| | - Xiang Liu
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Wuhan Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Department of Pathophysiology, School of Basic Medicine, Huazhong University of Science and Technology, Wuhan, China
| | - Dian Yu
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Wuhan Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Department of Pathophysiology, School of Basic Medicine, Huazhong University of Science and Technology, Wuhan, China
| | - Long Cheng
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Wuhan Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Department of Pathophysiology, School of Basic Medicine, Huazhong University of Science and Technology, Wuhan, China
| | - Bin Feng
- Wuhan Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Department of Neurobiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jianbin Wen
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Wuhan Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Department of Pathophysiology, School of Basic Medicine, Huazhong University of Science and Technology, Wuhan, China
| | - Feng Xiong
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Wuhan Institute of Physics and Mathematics, National Center for Magnetic Resonance in Wuhan, Innovation Academy of Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, China
| | - Youming Lu
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Wuhan Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Department of Pathophysiology, School of Basic Medicine, Huazhong University of Science and Technology, Wuhan, China
| | - Huiyun Du
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Wuhan Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Drug Target Research and Pharmacodynamic Evaluation, Wuhan, China
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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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Pais-Roldán P, Yun SD, Palomero-Gallagher N, Shah NJ. Cortical depth-dependent human fMRI of resting-state networks using EPIK. Front Neurosci 2023; 17:1151544. [PMID: 37274214 PMCID: PMC10232833 DOI: 10.3389/fnins.2023.1151544] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 04/26/2023] [Indexed: 06/06/2023] Open
Abstract
Introduction Recent laminar-fMRI studies have substantially improved understanding of the evoked cortical responses in multiple sub-systems; in contrast, the laminar component of resting-state networks spread over the whole brain has been less studied due to technical limitations. Animal research strongly suggests that the supragranular layers of the cortex play a critical role in maintaining communication within the default mode network (DMN); however, whether this is true in this and other human cortical networks remains unclear. Methods Here, we used EPIK, which offers unprecedented coverage at sub-millimeter resolution, to investigate cortical broad resting-state dynamics with depth specificity in healthy volunteers. Results Our results suggest that human DMN connectivity is primarily supported by intermediate and superficial layers of the cortex, and furthermore, the preferred cortical depth used for communication can vary from one network to another. In addition, the laminar connectivity profile of some networks showed a tendency to change upon engagement in a motor task. In line with these connectivity changes, we observed that the amplitude of the low-frequency-fluctuations (ALFF), as well as the regional homogeneity (ReHo), exhibited a different laminar slope when subjects were either performing a task or were in a resting state (less variation among laminae, i.e., lower slope, during task performance compared to rest). Discussion The identification of varied laminar profiles concerning network connectivity, ALFF, and ReHo, observed across two brain states (task vs. rest) has major implications for the characterization of network-related diseases and suggests the potential diagnostic value of laminar fMRI in psychiatric disorders, e.g., to differentiate the cortical dynamics associated with disease stages linked, or not linked, to behavioral changes. The evaluation of laminar-fMRI across the brain encompasses computational challenges; nonetheless, it enables the investigation of a new dimension of the human neocortex, which may be key to understanding neurological disorders from a novel perspective.
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Affiliation(s)
- Patricia Pais-Roldán
- Institute of Neuroscience and Medicine 4, Medical Imaging Physics, Forschungszentrum Jülich, Jülich, Germany
| | - Seong Dae Yun
- Institute of Neuroscience and Medicine 4, Medical Imaging Physics, Forschungszentrum Jülich, Jülich, Germany
| | - Nicola Palomero-Gallagher
- Institute of Neuroscience and Medicine 1, Structural and Functional Organisation of the Brain, Forschungszentrum Jülich, Jülich, Germany
- C. and O. Vogt Institute for Brain Research, Heinrich-Heine-University, Düsseldorf, Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen, Aachen, Germany
| | - N. Jon Shah
- Institute of Neuroscience and Medicine 4, Medical Imaging Physics, Forschungszentrum Jülich, Jülich, Germany
- Institute of Neuroscience and Medicine 11, Molecular Neuroscience and Neuroimaging, JARA, Forschungszentrum Jülich, Jülich, Germany
- JARA–BRAIN–Translational Medicine, Aachen, Germany
- Department of Neurology, RWTH Aachen University, Aachen, Germany
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31
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Padmanabhan P, Götz J. Clinical relevance of animal models in aging-related dementia research. NATURE AGING 2023; 3:481-493. [PMID: 37202516 DOI: 10.1038/s43587-023-00402-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 03/21/2023] [Indexed: 05/20/2023]
Abstract
Alzheimer's disease (AD) and other, less prevalent dementias are complex age-related disorders that exhibit multiple etiologies. Over the past decades, animal models have provided pathomechanistic insight and evaluated countless therapeutics; however, their value is increasingly being questioned due to the long history of drug failures. In this Perspective, we dispute this criticism. First, the utility of the models is limited by their design, as neither the etiology of AD nor whether interventions should occur at a cellular or network level is fully understood. Second, we highlight unmet challenges shared between animals and humans, including impeded drug transport across the blood-brain barrier, limiting effective treatment development. Third, alternative human-derived models also suffer from the limitations mentioned above and can only act as complementary resources. Finally, age being the strongest AD risk factor should be better incorporated into the experimental design, with computational modeling expected to enhance the value of animal models.
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Affiliation(s)
- Pranesh Padmanabhan
- Clem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, the University of Queensland, Brisbane, Queensland, Australia
| | - Jürgen Götz
- Clem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, the University of Queensland, Brisbane, Queensland, Australia.
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32
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Nazari M, Karimi Abadchi J, Naghizadeh M, Bermudez-Contreras EJ, McNaughton BL, Tatsuno M, Mohajerani MH. Regional variation in cholinergic terminal activity determines the non-uniform occurrence of cortical slow waves during REM sleep in mice. Cell Rep 2023; 42:112450. [PMID: 37126447 DOI: 10.1016/j.celrep.2023.112450] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 02/17/2023] [Accepted: 04/13/2023] [Indexed: 05/02/2023] Open
Abstract
Sleep consists of two basic stages: non-rapid eye movement (NREM) and rapid eye movement (REM) sleep. NREM sleep is characterized by slow high-amplitude cortical electroencephalogram (EEG) signals, while REM sleep is characterized by desynchronized cortical rhythms. Despite this, recent electrophysiological studies have suggested the presence of slow waves (SWs) in local cortical areas during REM sleep. Electrophysiological techniques, however, have been unable to resolve the regional structure of these activities because of relatively sparse sampling. Here, we map functional gradients in cortical activity during REM sleep using mesoscale imaging in mice and show local SW patterns occurring mainly in somatomotor and auditory cortical regions with minimum presence within the default mode network. The role of the cholinergic system in local desynchronization during REM sleep is also explored by calcium imaging of cholinergic activity within the cortex and analyzing structural data. We demonstrate weaker cholinergic projections and terminal activity in regions exhibiting frequent SWs during REM sleep.
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Affiliation(s)
- Mojtaba Nazari
- Canadian Centre for Behavioral Neuroscience, University of Lethbridge, Lethbridge, AB T1K 3M4, Canada
| | - Javad Karimi Abadchi
- Canadian Centre for Behavioral Neuroscience, University of Lethbridge, Lethbridge, AB T1K 3M4, Canada
| | - Milad Naghizadeh
- Canadian Centre for Behavioral Neuroscience, University of Lethbridge, Lethbridge, AB T1K 3M4, Canada
| | | | - Bruce L McNaughton
- Canadian Centre for Behavioral Neuroscience, University of Lethbridge, Lethbridge, AB T1K 3M4, Canada; Center for Neurobiology of Learning and Memory, Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA 92697, USA
| | - Masami Tatsuno
- Canadian Centre for Behavioral Neuroscience, University of Lethbridge, Lethbridge, AB T1K 3M4, Canada.
| | - Majid H Mohajerani
- Canadian Centre for Behavioral Neuroscience, University of Lethbridge, Lethbridge, AB T1K 3M4, Canada.
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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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Mohan H, An X, Xu XH, Kondo H, Zhao S, Matho KS, Wang BS, Musall S, Mitra P, Huang ZJ. Cortical glutamatergic projection neuron types contribute to distinct functional subnetworks. Nat Neurosci 2023; 26:481-494. [PMID: 36690901 PMCID: PMC10571488 DOI: 10.1038/s41593-022-01244-w] [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: 02/08/2022] [Accepted: 12/02/2022] [Indexed: 01/24/2023]
Abstract
The cellular basis of cerebral cortex functional architecture remains not well understood. A major challenge is to monitor and decipher neural network dynamics across broad cortical areas yet with projection-neuron-type resolution in real time during behavior. Combining genetic targeting and wide-field imaging, we monitored activity dynamics of subcortical-projecting (PTFezf2) and intratelencephalic-projecting (ITPlxnD1) types across dorsal cortex of mice during different brain states and behaviors. ITPlxnD1 and PTFezf2 neurons showed distinct activation patterns during wakeful resting, during spontaneous movements and upon sensory stimulation. Distinct ITPlxnD1 and PTFezf2 subnetworks were dynamically tuned to different sensorimotor components of a naturalistic feeding behavior, and optogenetic inhibition of ITsPlxnD1 and PTsFezf2 in subnetwork nodes disrupted distinct components of this behavior. Lastly, ITPlxnD1 and PTFezf2 projection patterns are consistent with their subnetwork activation patterns. Our results show that, in addition to the concept of columnar organization, dynamic areal and projection-neuron-type specific subnetworks are a key feature of cortical functional architecture linking microcircuit components with global brain networks.
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Affiliation(s)
- Hemanth Mohan
- Department of Neurobiology, Duke University Medical Center, Durham, NC, USA
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Xu An
- Department of Neurobiology, Duke University Medical Center, Durham, NC, USA
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - X Hermione Xu
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Hideki Kondo
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Shengli Zhao
- Department of Neurobiology, Duke University Medical Center, Durham, NC, USA
| | | | - Bor-Shuen Wang
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Simon Musall
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
- Institute of Biological information Processing, Forschungszentrum Julich, Julich, Germany
| | - Partha Mitra
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Z Josh Huang
- Department of Neurobiology, Duke University Medical Center, Durham, NC, USA.
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
- Department of Biomedical Engineering, Duke University, Durham, NC, USA.
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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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36
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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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37
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Menon V, Cerri D, Lee B, Yuan R, Lee SH, Shih YYI. Optogenetic stimulation of anterior insular cortex neurons in male rats reveals causal mechanisms underlying suppression of the default mode network by the salience network. Nat Commun 2023; 14:866. [PMID: 36797303 PMCID: PMC9935890 DOI: 10.1038/s41467-023-36616-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Accepted: 02/09/2023] [Indexed: 02/18/2023] Open
Abstract
The salience network (SN) and default mode network (DMN) play a crucial role in cognitive function. The SN, anchored in the anterior insular cortex (AI), has been hypothesized to modulate DMN activity during stimulus-driven cognition. However, the causal neural mechanisms underlying changes in DMN activity and its functional connectivity with the SN are poorly understood. Here we combine feedforward optogenetic stimulation with fMRI and computational modeling to dissect the causal role of AI neurons in dynamic functional interactions between SN and DMN nodes in the male rat brain. Optogenetic stimulation of Chronos-expressing AI neurons suppressed DMN activity, and decreased AI-DMN and intra-DMN functional connectivity. Our findings demonstrate that feedforward optogenetic stimulation of AI neurons induces dynamic suppression and decoupling of the DMN and elucidates previously unknown features of rodent brain network organization. Our study advances foundational knowledge of causal mechanisms underlying dynamic cross-network interactions and brain network switching.
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Grants
- R01 MH121069 NIMH NIH HHS
- P50 HD103573 NICHD NIH HHS
- T32 AA007573 NIAAA NIH HHS
- R01 NS091236 NINDS NIH HHS
- R01 MH126518 NIMH NIH HHS
- S10 MH124745 NIMH NIH HHS
- U01 AA020023 NIAAA NIH HHS
- R01 MH111429 NIMH NIH HHS
- S10 OD026796 NIH HHS
- R01 NS086085 NINDS NIH HHS
- R01 EB022907 NIBIB NIH HHS
- P60 AA011605 NIAAA NIH HHS
- RF1 NS086085 NINDS NIH HHS
- RF1 MH117053 NIMH NIH HHS
- This work was supported in part by the National Institute of Mental Health (R01MH121069 to V.M., and R01MH126518, RF1MH117053, R01MH111429, S10MH124745 to Y.-Y.I.S.), National Institute on Alcohol Abuse and Alcoholism (P60AA011605 and U01AA020023 to Y.-Y.I.S., T32AA007573 to D.C.), National Institute of Neurological Disorders and Stroke (R01NS086085 to V.M., R01NS091236 to Y.-Y.I.S.), National Institute of Child Health and Human Development (P50HD103573 to Y.-Y.I.S.), National Institute of Biomedical Imaging and Bioengineering (R01EB022907 to V.M.), and National Institute of Health Office of the Director (S10OD026796 to Y.-Y.I.S.).
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Affiliation(s)
- Vinod Menon
- Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, 94305, USA.
- Department of Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, CA, 94305, USA.
- Wu Tsai Neuroscience Institute, Stanford University School of Medicine, Stanford, CA, 94305, USA.
| | - Domenic Cerri
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Byeongwook Lee
- Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Rui Yuan
- Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Sung-Ho Lee
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Yen-Yu Ian Shih
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
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38
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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: 7] [Impact Index Per Article: 7.0] [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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Awad PN, Zerbi V, Johnson-Venkatesh EM, Damiani F, Pagani M, Markicevic M, Nickles S, Gozzi A, Umemori H, Fagiolini M. CDKL5 sculpts functional callosal connectivity to promote cognitive flexibility. Mol Psychiatry 2023:10.1038/s41380-023-01962-y. [PMID: 36737483 DOI: 10.1038/s41380-023-01962-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 01/02/2023] [Accepted: 01/13/2023] [Indexed: 02/05/2023]
Abstract
Functional and structural connectivity alterations in short- and long-range projections have been reported across neurodevelopmental disorders (NDD). Interhemispheric callosal projection neurons (CPN) represent one of the major long-range projections in the brain, which are particularly important for higher-order cognitive function and flexibility. However, whether a causal relationship exists between interhemispheric connectivity alterations and cognitive deficits in NDD remains elusive. Here, we focused on CDKL5 Deficiency Disorder (CDD), a severe neurodevelopmental disorder caused by mutations in the X-linked Cyclin-dependent kinase-like 5 (CDKL5) gene. We found an increase in homotopic interhemispheric connectivity and functional hyperconnectivity across higher cognitive areas in adult male and female CDKL5-deficient mice by resting-state functional MRI (rs-fMRI) analysis. This was accompanied by an increase in the number of callosal synaptic inputs but decrease in local synaptic connectivity in the cingulate cortex of juvenile CDKL5-deficient mice, suggesting an impairment in excitatory synapse development and a differential role of CDKL5 across excitatory neuron subtypes. These deficits were associated with significant cognitive impairments in CDKL5 KO mice. Selective deletion of CDKL5 in the largest subtype of CPN likewise resulted in an increase of functional callosal inputs, without however significantly altering intracortical cingulate networks. Notably, such callosal-specific changes were sufficient to cause cognitive deficits. Finally, when CDKL5 was selectively re-expressed only in this CPN subtype, in otherwise CDKL5-deficient mice, it was sufficient to prevent the cognitive impairments of CDKL5 mutants. Together, these results reveal a novel role of CDKL5 by demonstrating that it is both necessary and sufficient for proper CPN connectivity and cognitive function and flexibility, and further validates a causal relationship between CPN dysfunction and cognitive impairment in a model of NDD.
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Affiliation(s)
- Patricia Nora Awad
- F. M. Kirby Neurobiology Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Valerio Zerbi
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Neuro-X Institute, School of Engineering (STI), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
| | - Erin M Johnson-Venkatesh
- F. M. Kirby Neurobiology Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Francesca Damiani
- F. M. Kirby Neurobiology Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - 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
| | - Marija Markicevic
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Sarah Nickles
- F. M. Kirby Neurobiology Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Hisashi Umemori
- F. M. Kirby Neurobiology Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michela Fagiolini
- F. M. Kirby Neurobiology Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
- Hock E. Tan and K. Lisa Yang Center for Autism Research at Harvard University, Boston, MA, USA.
- International Research Center for Neurointelligence (IRCN), University of Tokyo Institutes for Advanced Study, Tokyo, Japan.
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40
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Durand S, Heller GR, Ramirez TK, Luviano JA, Williford A, Sullivan DT, Cahoon AJ, Farrell C, Groblewski PA, Bennett C, Siegle JH, Olsen SR. Acute head-fixed recordings in awake mice with multiple Neuropixels probes. Nat Protoc 2023; 18:424-457. [PMID: 36477710 DOI: 10.1038/s41596-022-00768-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 08/09/2022] [Indexed: 12/12/2022]
Abstract
Multi-electrode arrays such as Neuropixels probes enable electrophysiological recordings from large populations of single neurons with high temporal resolution. By using such probes, the activity from functionally interacting, yet distinct, brain regions can be measured simultaneously by inserting multiple probes into the same subject. However, the use of multiple probes in small animals such as mice requires the removal of a sizable fraction of the skull, while also minimizing tissue damage and keeping the brain stable during the recordings. Here, we describe a step-by-step process designed to facilitate reliable recordings from up to six Neuropixels probes simultaneously in awake, head-fixed mice. The procedure involves four stages: the implantation of a headframe and a removable glass coverslip, the precise positioning of the Neuropixels probes at targeted points on the brain surface, the placement of a perforated plastic imaging window and the insertion of the probes into the brain of an awake mouse. The approach provides access to multiple brain regions and has been successfully applied across hundreds of mice. The procedure has been optimized for dense recordings from the mouse visual system, but it can be adapted for alternative recording configurations to target multiple probes in other brain areas. The protocol is suitable for users with experience in stereotaxic surgery in mice.
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Affiliation(s)
| | - Greggory R Heller
- Allen Institute, Seattle, WA, USA.,Department of Brain and Cognitive Sciences, Massachussetts Institute of Technology, Cambridge, MA, USA
| | - Tamina K Ramirez
- Allen Institute, Seattle, WA, USA.,Department of Neurobiology and Behavior, Columbia University, New York, NY, USA
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41
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Hemodynamic transient and functional connectivity follow structural connectivity and cell type over the brain hierarchy. Proc Natl Acad Sci U S A 2023; 120:e2202435120. [PMID: 36693103 PMCID: PMC9945945 DOI: 10.1073/pnas.2202435120] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
The neural circuit of the brain is organized as a hierarchy of functional units with wide-ranging connections that support information flow and functional connectivity. Studies using MRI indicate a moderate coupling between structural and functional connectivity at the system level. However, how do connections of different directions (feedforward and feedback) and regions with different excitatory and inhibitory (E/I) neurons shape the hemodynamic activity and functional connectivity over the hierarchy are unknown. Here, we used functional MRI to detect optogenetic-evoked and resting-state activities over a somatosensory pathway in the mouse brain in relation to axonal projection and E/I distribution. Using a highly sensitive ultrafast imaging, we identified extensive activation in regions up to the third order of axonal projections following optogenetic excitation of the ventral posteriomedial nucleus of the thalamus. The evoked response and functional connectivity correlated with feedforward projections more than feedback projections and weakened with the hierarchy. The hemodynamic response exhibited regional and hierarchical differences, with slower and more variable responses in high-order areas and bipolar response predominantly in the contralateral cortex. Electrophysiological recordings suggest that these reflect differences in neural activity rather than neurovascular coupling. Importantly, the positive and negative parts of the hemodynamic response correlated with E/I neuronal densities, respectively. Furthermore, resting-state functional connectivity was more associated with E/I distribution, whereas stimulus-evoked effective connectivity followed structural wiring. These findings indicate that the structure-function relationship is projection-, cell-type- and hierarchy-dependent. Hemodynamic transients could reflect E/I activity and the increased complexity of hierarchical processing.
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42
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Influence of claustrum on cortex varies by area, layer, and cell type. Neuron 2023; 111:275-290.e5. [PMID: 36368317 DOI: 10.1016/j.neuron.2022.10.026] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 07/15/2022] [Accepted: 10/18/2022] [Indexed: 11/11/2022]
Abstract
The claustrum is a small subcortical structure with widespread connections to disparate regions of the cortex. However, the impact of the claustrum on cortical activity is not fully understood, particularly beyond frontal areas. Here, using optogenetics and multi-regional Neuropixels recordings from over 15,000 cortical neurons in awake mice, we demonstrate that the effect of claustrum input to the cortex differs depending on brain area, layer, and cell type. Brief claustrum stimulation, producing approximately 1 spike per claustrum neuron, affects many fast spiking (FS; putative inhibitory) but relatively fewer regular-spiking (RS; putative excitatory) cortical neurons and leads to a modest decrease in population activity in frontal cortical areas. Prolonged claustrum stimulation affects many more cortical neurons and can increase or decrease spiking activity. More excitation occurs in posterior regions and superficial layers, while inhibition predominates in frontal regions and deeper layers. These findings suggest that claustro-cortical circuits are organized into functional modules.
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43
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Karimi Abadchi J, Rezaei Z, Knöpfel T, McNaughton BL, Mohajerani MH. Inhibition is a prevalent mode of activity in the neocortex around awake hippocampal ripples in mice. eLife 2023; 12:79513. [PMID: 36645126 PMCID: PMC9876570 DOI: 10.7554/elife.79513] [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: 04/15/2022] [Accepted: 01/06/2023] [Indexed: 01/17/2023] Open
Abstract
Coordinated peri-ripple activity in the hippocampal-neocortical network is essential for mnemonic information processing in the brain. Hippocampal ripples likely serve different functions in sleep and awake states. Thus, the corresponding neocortical activity patterns may differ in important ways. We addressed this possibility by conducting voltage and glutamate wide-field imaging of the neocortex with concurrent hippocampal electrophysiology in awake mice. Contrary to our previously published sleep results, deactivation and activation were dominant in post-ripple neocortical voltage and glutamate activity, respectively, especially in the agranular retrosplenial cortex (aRSC). Additionally, the spiking activity of aRSC neurons, estimated by two-photon calcium imaging, revealed the existence of two subpopulations of excitatory neurons with opposite peri-ripple modulation patterns: one increases and the other decreases firing rate. These differences in peri-ripple spatiotemporal patterns of neocortical activity in sleep versus awake states might underlie the reported differences in the function of sleep versus awake ripples.
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Affiliation(s)
- Javad Karimi Abadchi
- Canadian Centre for Behavioral Neuroscience, University of LethbridgeLethbridgeCanada
| | - Zahra Rezaei
- Canadian Centre for Behavioral Neuroscience, University of LethbridgeLethbridgeCanada
| | - Thomas Knöpfel
- Laboratory for Neuronal Circuit Dynamics, Imperial College LondonLondonUnited Kingdom
- Department of Physics, Hong Kong Baptist UniversityKowloon TongHong Kong
| | - Bruce L McNaughton
- Canadian Centre for Behavioral Neuroscience, University of LethbridgeLethbridgeCanada
- Department of Neurobiology and Behavior, University of CaliforniaIrvineUnited States
| | - Majid H Mohajerani
- Canadian Centre for Behavioral Neuroscience, University of LethbridgeLethbridgeCanada
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44
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Qadir H, Stewart BW, VanRyzin JW, Wu Q, Chen S, Seminowicz DA, Mathur BN. The mouse claustrum synaptically connects cortical network motifs. Cell Rep 2022; 41:111860. [PMID: 36543121 PMCID: PMC9838879 DOI: 10.1016/j.celrep.2022.111860] [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: 06/15/2022] [Revised: 10/31/2022] [Accepted: 11/30/2022] [Indexed: 12/24/2022] Open
Abstract
Spatially distant areas of the cerebral cortex coordinate their activity into networks that are integral to cognitive processing. A common structural motif of cortical networks is co-activation of frontal and posterior cortical regions. The neural circuit mechanisms underlying such widespread inter-areal cortical coordination are unclear. Using a discovery based functional magnetic resonance imaging (fMRI) approach in mouse, we observe frontal and posterior cortical regions that demonstrate significant functional connectivity with the subcortical nucleus, the claustrum. Examining whether the claustrum synaptically supports such frontoposterior cortical network architecture, we observe cortico-claustro-cortical circuits reflecting the fMRI data: significant trans-claustral synaptic connectivity from frontal cortices to posteriorly lying sensory and sensory association cortices contralaterally. These data reveal discrete cortical pathways through the claustrum that are positioned to support cortical network motifs central to cognitive control functions and add to the canon of major extended cortico-subcortico-cortical systems in the mammalian brain.
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Affiliation(s)
- Houman Qadir
- Department of Pharmacology, University of Maryland School of Medicine, HSF III 9179, Baltimore, MD 21201, USA
| | - Brent W. Stewart
- Department of Neural and Pain Sciences, University of Maryland School of Dentistry, Baltimore, MD, USA
| | - Jonathan W. VanRyzin
- Department of Pharmacology, University of Maryland School of Medicine, HSF III 9179, Baltimore, MD 21201, USA
| | - Qiong Wu
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - Shuo Chen
- Division of Biostatistics and Bioinformatics, Department of Epidemiology & Public Health, University of Maryland School of Medicine, Baltimore, MD, USA
| | - David A. Seminowicz
- Department of Neural and Pain Sciences, University of Maryland School of Dentistry, Baltimore, MD, USA,Department of Medical Biophysics, Schulich School of Medicine & Dentistry, University of Western Ontario, London, ON, Canada
| | - Brian N. Mathur
- Department of Pharmacology, University of Maryland School of Medicine, HSF III 9179, Baltimore, MD 21201, USA,Lead contact,Correspondence:
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45
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Madden MB, Stewart BW, White MG, Krimmel SR, Qadir H, Barrett FS, Seminowicz DA, Mathur BN. A role for the claustrum in cognitive control. Trends Cogn Sci 2022; 26:1133-1152. [PMID: 36192309 PMCID: PMC9669149 DOI: 10.1016/j.tics.2022.09.006] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 09/02/2022] [Accepted: 09/07/2022] [Indexed: 01/12/2023]
Abstract
Early hypotheses of claustrum function were fueled by neuroanatomical data and yielded suggestions that the claustrum is involved in processes ranging from salience detection to multisensory integration for perceptual binding. While these hypotheses spurred useful investigations, incompatibilities inherent in these views must be reconciled to further conceptualize claustrum function amid a wealth of new data. Here, we review the varied models of claustrum function and synthesize them with developments in the field to produce a novel functional model: network instantiation in cognitive control (NICC). This model proposes that frontal cortices direct the claustrum to flexibly instantiate cortical networks to subserve cognitive control. We present literature support for this model and provide testable predictions arising from this conceptual framework.
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Affiliation(s)
- Maxwell B Madden
- Department of Pharmacology, School of Medicine, University of Maryland, Baltimore, MD 21201, USA
| | - Brent W Stewart
- Department of Pharmacology, School of Medicine, University of Maryland, Baltimore, MD 21201, USA; Department of Neural and Pain Sciences, School of Dentistry, University of Maryland, Baltimore, MD 21201, USA; Center to Advance Chronic Pain Research, University of Maryland, Baltimore, MD 21201, USA
| | - Michael G White
- Department of Pharmacology, School of Medicine, University of Maryland, Baltimore, MD 21201, USA
| | - Samuel R Krimmel
- Department of Neural and Pain Sciences, School of Dentistry, University of Maryland, Baltimore, MD 21201, USA; Center to Advance Chronic Pain Research, University of Maryland, Baltimore, MD 21201, USA
| | - Houman Qadir
- Department of Pharmacology, School of Medicine, University of Maryland, Baltimore, MD 21201, USA
| | - Frederick S Barrett
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21224, USA; Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21224, USA; Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD 21224, USA
| | - David A Seminowicz
- Department of Neural and Pain Sciences, School of Dentistry, University of Maryland, Baltimore, MD 21201, USA; Center to Advance Chronic Pain Research, University of Maryland, Baltimore, MD 21201, USA; Department of Medical Biophysics, Schulich School of Medicine & Dentistry, University of Western Ontario, London, Ontario, Canada
| | - Brian N Mathur
- Department of Pharmacology, School of Medicine, University of Maryland, Baltimore, MD 21201, USA; Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, MD 21201, USA.
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46
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Shah D, Gsell W, Wahis J, Luckett ES, Jamoulle T, Vermaercke B, Preman P, Moechars D, Hendrickx V, Jaspers T, Craessaerts K, Horré K, Wolfs L, Fiers M, Holt M, Thal DR, Callaerts-Vegh Z, D'Hooge R, Vandenberghe R, Himmelreich U, Bonin V, De Strooper B. Astrocyte calcium dysfunction causes early network hyperactivity in Alzheimer's disease. Cell Rep 2022; 40:111280. [PMID: 36001964 PMCID: PMC9433881 DOI: 10.1016/j.celrep.2022.111280] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 06/30/2022] [Accepted: 08/05/2022] [Indexed: 12/15/2022] Open
Abstract
Dysfunctions of network activity and functional connectivity (FC) represent early events in Alzheimer’s disease (AD), but the underlying mechanisms remain unclear. Astrocytes regulate local neuronal activity in the healthy brain, but their involvement in early network hyperactivity in AD is unknown. We show increased FC in the human cingulate cortex several years before amyloid deposition. We find the same early cingulate FC disruption and neuronal hyperactivity in AppNL-F mice. Crucially, these network disruptions are accompanied by decreased astrocyte calcium signaling. Recovery of astrocytic calcium activity normalizes neuronal hyperactivity and FC, as well as seizure susceptibility and day/night behavioral disruptions. In conclusion, we show that astrocytes mediate initial features of AD and drive clinically relevant phenotypes. The cingulate cortex of humans and mice shows early functional deficits in AD Astrocyte calcium signaling is decreased before the presence of amyloid plaques Recovery of astrocyte calcium signals mitigates neuronal hyperactivity Recovery of astrocytes normalizes cingulate connectivity and behavior disruptions
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Affiliation(s)
- Disha Shah
- Laboratory for the Research of Neurodegenerative Diseases, VIB Center for Brain and Disease Research, KU Leuven, 3000 Leuven, Belgium.
| | - Willy Gsell
- Biomedical MRI, Department of Imaging and Pathology, KU Leuven, 3000 Leuven, Belgium
| | - Jérôme Wahis
- Laboratory of Glia Biology, VIB Center for Brain and Disease Research, KU Leuven, 3000 Leuven, Belgium
| | - Emma S Luckett
- Laboratory for Cognitive Neurology, Department of Neurosciences, Leuven Brain Institute (LBI), KU Leuven, 3000 Leuven, Belgium
| | - Tarik Jamoulle
- Laboratory for Cognitive Neurology, Department of Neurosciences, Leuven Brain Institute (LBI), KU Leuven, 3000 Leuven, Belgium
| | - Ben Vermaercke
- Neuro-electronics Research Flanders, 3000 Leuven, Belgium
| | - Pranav Preman
- Laboratory for the Research of Neurodegenerative Diseases, VIB Center for Brain and Disease Research, KU Leuven, 3000 Leuven, Belgium
| | - Daan Moechars
- Laboratory for the Research of Neurodegenerative Diseases, VIB Center for Brain and Disease Research, KU Leuven, 3000 Leuven, Belgium
| | - Véronique Hendrickx
- Laboratory for the Research of Neurodegenerative Diseases, VIB Center for Brain and Disease Research, KU Leuven, 3000 Leuven, Belgium
| | - Tom Jaspers
- Laboratory for the Research of Neurodegenerative Diseases, VIB Center for Brain and Disease Research, KU Leuven, 3000 Leuven, Belgium
| | - Katleen Craessaerts
- Laboratory for the Research of Neurodegenerative Diseases, VIB Center for Brain and Disease Research, KU Leuven, 3000 Leuven, Belgium
| | - Katrien Horré
- Laboratory for the Research of Neurodegenerative Diseases, VIB Center for Brain and Disease Research, KU Leuven, 3000 Leuven, Belgium
| | - Leen Wolfs
- Laboratory for the Research of Neurodegenerative Diseases, VIB Center for Brain and Disease Research, KU Leuven, 3000 Leuven, Belgium
| | - Mark Fiers
- Laboratory for the Research of Neurodegenerative Diseases, VIB Center for Brain and Disease Research, KU Leuven, 3000 Leuven, Belgium
| | - Matthew Holt
- Laboratory of Glia Biology, VIB Center for Brain and Disease Research, KU Leuven, 3000 Leuven, Belgium
| | - Dietmar Rudolf Thal
- Laboratory for Neuropathology, Department of Imaging and Pathology, LBI, KU Leuven, 3000 Leuven, Belgium
| | | | - Rudi D'Hooge
- Laboratory of Biological Psychology, KU-Leuven, 3000 Leuven, Belgium
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of Neurosciences, Leuven Brain Institute (LBI), KU Leuven, 3000 Leuven, Belgium
| | - Uwe Himmelreich
- Biomedical MRI, Department of Imaging and Pathology, KU Leuven, 3000 Leuven, Belgium
| | - Vincent Bonin
- Neuro-electronics Research Flanders, 3000 Leuven, Belgium
| | - Bart De Strooper
- Laboratory for the Research of Neurodegenerative Diseases, VIB Center for Brain and Disease Research, KU Leuven, 3000 Leuven, Belgium; UK Dementia Research Institute at University College London, WC1E 6BT London, UK.
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47
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Subcortical control of the default mode network: Role of the basal forebrain and implications for neuropsychiatric disorders. Brain Res Bull 2022; 185:129-139. [PMID: 35562013 PMCID: PMC9290753 DOI: 10.1016/j.brainresbull.2022.05.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 04/29/2022] [Accepted: 05/04/2022] [Indexed: 01/03/2023]
Abstract
The precise interplay between large-scale functional neural systems throughout the brain is essential for performance of cognitive processes. In this review we focus on the default mode network (DMN), one such functional network that is active during periods of quiet wakefulness and believed to be involved in introspection and planning. Abnormalities in DMN functional connectivity and activation appear across many neuropsychiatric disorders, including schizophrenia. Recent evidence suggests subcortical regions including the basal forebrain are functionally and structurally important for regulation of DMN activity. Within the basal forebrain, subregions like the ventral pallidum may influence DMN activity and the nucleus basalis of Meynert can inhibit switching between brain networks. Interactions between DMN and other functional networks including the medial frontoparietal network (default), lateral frontoparietal network (control), midcingulo-insular network (salience), and dorsal frontoparietal network (attention) are also discussed in the context of neuropsychiatric disorders. Several subtypes of basal forebrain neurons have been identified including basal forebrain parvalbumin-containing or somatostatin-containing neurons which can regulate cortical gamma band oscillations and DMN-like behaviors, and basal forebrain cholinergic neurons which might gate access to sensory information during reinforcement learning. In this review, we explore this evidence, discuss the clinical implications on neuropsychiatric disorders, and compare neuroanatomy in the human vs rodent DMN. Finally, we address technological advancements which could help provide a more complete understanding of modulation of DMN function and describe newly identified BF therapeutic targets that could potentially help restore DMN-associated functional deficits in patients with a variety of neuropsychiatric disorders.
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48
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Oyarzabal EA, Hsu LM, Das M, Chao THH, Zhou J, Song S, Zhang W, Smith KG, Sciolino NR, Evsyukova IY, Yuan H, Lee SH, Cui G, Jensen P, Shih YYI. Chemogenetic stimulation of tonic locus coeruleus activity strengthens the default mode network. SCIENCE ADVANCES 2022; 8:eabm9898. [PMID: 35486721 PMCID: PMC9054017 DOI: 10.1126/sciadv.abm9898] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 03/15/2022] [Indexed: 05/31/2023]
Abstract
The default mode network (DMN) of the brain is functionally associated with a wide range of behaviors. In this study, we used functional magnetic resonance imaging (fMRI), positron emission tomography (PET), and spectral fiber photometry to investigate the selective neuromodulatory effect of norepinephrine (NE)-releasing noradrenergic neurons in the locus coeruleus (LC) on the mouse DMN. Chemogenetic-induced tonic LC activity decreased cerebral blood volume (CBV) and glucose uptake and increased synchronous low-frequency fMRI activity within the frontal cortices of the DMN. Fiber photometry results corroborated these findings, showing that LC-NE activation induced NE release, enhanced calcium-weighted neuronal spiking, and reduced CBV in the anterior cingulate cortex. These data suggest that LC-NE alters conventional coupling between neuronal activity and CBV in the frontal DMN. We also demonstrated that chemogenetic activation of LC-NE neurons strengthened functional connectivity within the frontal DMN, and this effect was causally mediated by reduced modulatory inputs from retrosplenial and hippocampal regions to the association cortices of the DMN.
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Affiliation(s)
- Esteban A. Oyarzabal
- 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
- Curriculum in Neurobiology, University of North Carolina, Chapel Hill, NC, USA
| | - Li-Ming Hsu
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina, Chapel Hill, NC, USA
| | - Manasmita Das
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina, Chapel Hill, NC, USA
| | - Tzu-Hao Harry Chao
- 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
| | - Jingheng Zhou
- In Vivo Neurobiology Group, Neurobiology Laboratory, NIEHS/NIH, Research Triangle Park, NC, USA
| | - Sheng Song
- 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
| | - Weiting Zhang
- 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
| | - Kathleen G. Smith
- Developmental Neurobiology Group, Neurobiology Laboratory, NIEHS/NIH, Research Triangle Park, NC, USA
| | - Natale R. Sciolino
- Developmental Neurobiology Group, Neurobiology Laboratory, NIEHS/NIH, Research Triangle Park, NC, USA
| | - Irina Y. Evsyukova
- Developmental Neurobiology Group, Neurobiology Laboratory, NIEHS/NIH, Research Triangle Park, NC, USA
| | - Hong Yuan
- Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA
| | - 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
| | - Guohong Cui
- In Vivo Neurobiology Group, Neurobiology Laboratory, NIEHS/NIH, Research Triangle Park, NC, USA
| | - Patricia Jensen
- Developmental Neurobiology Group, Neurobiology Laboratory, NIEHS/NIH, Research Triangle Park, 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
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49
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Watts AG, Kanoski SE, Sanchez-Watts G, Langhans W. The physiological control of eating: signals, neurons, and networks. Physiol Rev 2022; 102:689-813. [PMID: 34486393 PMCID: PMC8759974 DOI: 10.1152/physrev.00028.2020] [Citation(s) in RCA: 47] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Accepted: 08/30/2021] [Indexed: 02/07/2023] Open
Abstract
During the past 30 yr, investigating the physiology of eating behaviors has generated a truly vast literature. This is fueled in part by a dramatic increase in obesity and its comorbidities that has coincided with an ever increasing sophistication of genetically based manipulations. These techniques have produced results with a remarkable degree of cell specificity, particularly at the cell signaling level, and have played a lead role in advancing the field. However, putting these findings into a brain-wide context that connects physiological signals and neurons to behavior and somatic physiology requires a thorough consideration of neuronal connections: a field that has also seen an extraordinary technological revolution. Our goal is to present a comprehensive and balanced assessment of how physiological signals associated with energy homeostasis interact at many brain levels to control eating behaviors. A major theme is that these signals engage sets of interacting neural networks throughout the brain that are defined by specific neural connections. We begin by discussing some fundamental concepts, including ones that still engender vigorous debate, that provide the necessary frameworks for understanding how the brain controls meal initiation and termination. These include key word definitions, ATP availability as the pivotal regulated variable in energy homeostasis, neuropeptide signaling, homeostatic and hedonic eating, and meal structure. Within this context, we discuss network models of how key regions in the endbrain (or telencephalon), hypothalamus, hindbrain, medulla, vagus nerve, and spinal cord work together with the gastrointestinal tract to enable the complex motor events that permit animals to eat in diverse situations.
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Affiliation(s)
- Alan G Watts
- The Department of Biological Sciences, Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, California
| | - Scott E Kanoski
- The Department of Biological Sciences, Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, California
| | - Graciela Sanchez-Watts
- The Department of Biological Sciences, Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, California
| | - Wolfgang Langhans
- Physiology and Behavior Laboratory, Eidgenössische Technische Hochschule-Zürich, Schwerzenbach, Switzerland
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50
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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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