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Luo Y, Li X, Zhou C, Liu G, Jia X, Yang X, Li A, Gong H, Feng Z. Mapping sagittal-plane reference brain atlas of the cynomolgus macaque (Macaca fascicularis) based on consecutive cytoarchitectonic images. Brain Struct Funct 2024; 229:2045-2057. [PMID: 39192084 PMCID: PMC11485111 DOI: 10.1007/s00429-024-02851-y] [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: 05/15/2024] [Accepted: 08/13/2024] [Indexed: 08/29/2024]
Abstract
The brain atlas is essential for exploring the anatomical structure and function of the brain. Non-human primates, such as cynomolgus macaque, have received increasing attention due to their genetic similarity to humans. However, current macaque brain atlases only offer coarse sections with intervals along the coronal direction, failing to meet the needs of single-cell resolution studies in functional and multi-omics research of the macaque brain. To address this issue, we utilized fluorescence micro-optical sectioning tomography to obtain sub-micron resolution cytoarchitectonic images of the macaque brain at the sagittal plane. Based on the obtained 8000 image sequences, a reference brain atlas comprising 45 sagittal sections was created, delineating 270 brain regions other than the cortex. Additionally, a website was established to share the reference atlas corresponding image data. This study is expected to provide an essential dataset and tool for scientists studying the macaque brain.
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Affiliation(s)
- Yue Luo
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Xiangning Li
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou, 570228, China
| | - Can Zhou
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Guangcai Liu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Xueyan Jia
- HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, 215123, China
| | - Xiaoquan Yang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, 430074, China
- HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, 215123, China
| | - Anan Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, 430074, China
- HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, 215123, China
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou, 570228, China
| | - Hui Gong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, 430074, China
- HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, 215123, China
| | - Zhao Feng
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou, 570228, China.
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2
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Charbonneau JA, Davis B, Raven EP, Patwardhan B, Grebosky C, Halteh L, Bennett JL, Bliss-Moreau E. Evaluation of registration-based vs. manual segmentation of rhesus macaque brain MRIs. Brain Struct Funct 2024; 229:2029-2043. [PMID: 39136727 PMCID: PMC11483197 DOI: 10.1007/s00429-024-02848-7] [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: 04/02/2024] [Accepted: 08/01/2024] [Indexed: 10/18/2024]
Abstract
With increasing numbers of magnetic resonance imaging (MRI) datasets becoming publicly available, researchers and clinicians alike have turned to automated methods of segmentation to enable population-level analyses of these data. Although prior research has evaluated the extent to which automated methods recapitulate "gold standard" manual segmentation methods in the human brain, such an evaluation has not yet been carried out for segmentation of MRIs of the macaque brain. Macaques offer the important opportunity to bridge gaps between microanatomical studies using invasive methods like tract tracing, neural recordings, and high-resolution histology and non-invasive macroanatomical studies using methods like MRI. As such, it is important to evaluate whether automated tools derive data of sufficient quality from macaque MRIs to bridge these gaps. We tested the relationship between automated registration-based segmentation using an open source and actively maintained NHP imaging analysis pipeline (AFNI) and gold standard manual segmentation of 4 structures (2 cortical: anterior cingulate cortex and insula; 2 subcortical: amygdala and caudate) across 37 rhesus macaques (Macaca mulatta). We identified some variability in the strength of correlation between automated and manual segmentations across neural regions and differences in relationships with demographic variables like age and sex between the two techniques.
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Affiliation(s)
- Joey A Charbonneau
- Neuroscience Graduate Program, University of California Davis, Davis, CA, USA.
- California National Primate Research Center, University of California Davis, Davis, CA, USA.
| | - Brittany Davis
- Neuroscience Graduate Program, University of California Davis, Davis, CA, USA
- California National Primate Research Center, University of California Davis, Davis, CA, USA
| | - Erika P Raven
- Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Bhakti Patwardhan
- California National Primate Research Center, University of California Davis, Davis, CA, USA
| | - Carson Grebosky
- California National Primate Research Center, University of California Davis, Davis, CA, USA
| | - Lucas Halteh
- California National Primate Research Center, University of California Davis, Davis, CA, USA
| | - Jeffrey L Bennett
- California National Primate Research Center, University of California Davis, Davis, CA, USA
- Department of Psychology, University of California Davis, Davis, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, Davis School of Medicine, Sacramento, CA, USA
- The MIND Institute, University of California Davis, Sacramento, CA, USA
| | - Eliza Bliss-Moreau
- California National Primate Research Center, University of California Davis, Davis, CA, USA.
- Department of Psychology, University of California Davis, Davis, CA, USA.
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3
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Gutierrez-Barragan D, Ramirez JSB, Panzeri S, Xu T, Gozzi A. Evolutionarily conserved fMRI network dynamics in the mouse, macaque, and human brain. Nat Commun 2024; 15:8518. [PMID: 39353895 PMCID: PMC11445567 DOI: 10.1038/s41467-024-52721-8] [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: 01/19/2024] [Accepted: 09/13/2024] [Indexed: 10/03/2024] Open
Abstract
Evolutionarily relevant networks have been previously described in several mammalian species using time-averaged analyses of fMRI time-series. However, fMRI network activity is highly dynamic and continually evolves over timescales of seconds. Whether the dynamic organization of resting-state fMRI network activity is conserved across mammalian species remains unclear. Using frame-wise clustering of fMRI time-series, we find that intrinsic fMRI network dynamics in awake male macaques and humans is characterized by recurrent transitions between a set of 4 dominant, neuroanatomically homologous fMRI coactivation modes (C-modes), three of which are also plausibly represented in the male rodent brain. Importantly, in all species C-modes exhibit species-invariant dynamic features, including preferred occurrence at specific phases of fMRI global signal fluctuations, and a state transition structure compatible with infraslow coupled oscillator dynamics. Moreover, dominant C-mode occurrence reconstitutes the static organization of the fMRI connectome in all species, and is predictive of ranking of corresponding fMRI connectivity gradients. These results reveal a set of species-invariant principles underlying the dynamic organization of fMRI networks in mammalian species, and offer novel opportunities to relate fMRI network findings across the phylogenetic tree.
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Affiliation(s)
- Daniel Gutierrez-Barragan
- Functional Neuroimaging Lab, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, Rovereto, Italy
| | - Julian S B Ramirez
- Center for the Developing Brain. Child Mind Institute, New York, NY, USA
| | - Stefano Panzeri
- Institute for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Ting Xu
- Center for the Developing Brain. Child Mind Institute, New York, NY, USA
| | - Alessandro Gozzi
- Functional Neuroimaging Lab, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, Rovereto, Italy.
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4
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Dong D, Hosomi K, Shimizu T, Okada KI, Kadono Y, Mori N, Hori Y, Yahata N, Hirabayashi T, Kishima H, Saitoh Y. Cross-Species Convergence of Functional Connectivity Changes in Thalamic Pain Across Human Patients and Model Macaques. THE JOURNAL OF PAIN 2024:104661. [PMID: 39182537 DOI: 10.1016/j.jpain.2024.104661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 08/12/2024] [Accepted: 08/19/2024] [Indexed: 08/27/2024]
Abstract
Thalamic pain can be understood as a network reorganization disorder. This study aimed to investigate functional connectivity (FC) in human patients and a macaque model of thalamic pain. In humans, resting-state FC was compared between patients with thalamic pain and healthy individuals. Furthermore, resting-state FC was compared in macaques, before and after the induction of thalamic pain in the same individuals. FC between the amygdala of the unaffected hemisphere and the brainstem was significantly higher in patients with thalamic pain. More specifically, a significantly higher FC was observed between the basolateral amygdala and the ventral tegmental area, which also significantly predicted the value of a visual analog scale of pain intensity in individual patients. The macaque model of thalamic pain also exhibited a significantly higher FC between the amygdala of the unaffected hemisphere and the brainstem, particularly between the basolateral amygdala and the midbrain. Furthermore, the previously reported significantly higher FC between the amygdala and the mediodorsal nucleus of the thalamus in macaques with thalamic pain was also reproduced in the human patients. Therefore, the present results suggest that the FC changes in the regions associated with emotion, memory, motivation, and reward are part of the underlying mechanisms of thalamic pain onset present in both human patients and model macaques. This cross-species convergence provides new insights into the neurological mechanisms underlying thalamic pain, paving the way for further studies and the development of therapeutic strategies. PERSPECTIVE: This article presents that the FC changes in the regions associated with emotion, motivation, and reward are part of the underlying mechanisms of thalamic pain in humans and macaques.
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Affiliation(s)
- Dong Dong
- Department of Neurosurgery, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Koichi Hosomi
- Department of Neurosurgery, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan; Department of Neurosurgery, Toyonaka Municipal Hospital, Toyonaka, Osaka, Japan.
| | - Takeshi Shimizu
- Department of Neurosurgery, Asahikawa Medical University, Asahikawa, Hokkaido, Japan
| | - Ken-Ichi Okada
- Department of Physiology, Hokkaido University School of Medicine, Sapporo, Hokkaido, Japan
| | - Yoshinori Kadono
- Department of Neurosurgery, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan; Department of Neurosurgery, Takatsuki General Hospital, Takatsuki, Osaka, Japan
| | - Nobuhiko Mori
- Department of Neurosurgery, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Yuki Hori
- Advanced Neuroimaging Center, National Institutes for Quantum Science and Technology, Inage Ward, Chiba, Japan
| | - Noriaki Yahata
- Institute for Quantum Life Science, National Institutes for Quantum Science and Technology, Inage Ward, Chiba, Japan; Department of Quantum Life Science, Graduate School of Science and Engineering, Chiba University, Chiba, Japan
| | - Toshiyuki Hirabayashi
- Advanced Neuroimaging Center, National Institutes for Quantum Science and Technology, Inage Ward, Chiba, Japan
| | - Haruhiko Kishima
- Department of Neurosurgery, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Youichi Saitoh
- Department of Mechanical Science and Bioengineering, Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka, Japan; Tokuyukai Rehabilitation Clinic, Toyonaka, Osaka, Japan
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5
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Zhu J, Garin CM, Qi XL, Machado A, Wang Z, Hamed SB, Stanford TR, Salinas E, Whitlow CT, Anderson AW, Zhou XM, Calabro FJ, Luna B, Constantinidis C. Brain structure and activity predicting cognitive maturation in adolescence. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.23.608315. [PMID: 39229176 PMCID: PMC11370567 DOI: 10.1101/2024.08.23.608315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
Cognitive abilities of primates, including humans, continue to improve through adolescence 1,2. While a range of changes in brain structure and connectivity have been documented 3,4, how they affect neuronal activity that ultimately determines performance of cognitive functions remains unknown. Here, we conducted a multilevel longitudinal study of monkey adolescent neurocognitive development. The developmental trajectory of neural activity in the prefrontal cortex accounted remarkably well for working memory improvements. While complex aspects of activity changed progressively during adolescence, such as the rotation of stimulus representation in multidimensional neuronal space, which has been implicated in cognitive flexibility, even simpler attributes, such as the baseline firing rate in the period preceding a stimulus appearance had predictive power over behavior. Unexpectedly, decreases in brain volume and thickness, which are widely thought to underlie cognitive changes in humans 5 did not predict well the trajectory of neural activity or cognitive performance changes. Whole brain cortical volume in particular, exhibited an increase and reached a local maximum in late adolescence, at a time of rapid behavioral improvement. Maturation of long-distance white matter tracts linking the frontal lobe with areas of the association cortex and subcortical regions best predicted changes in neuronal activity and behavior. Our results provide evidence that optimization of neural activity depending on widely distributed circuitry effects cognitive development in adolescence.
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Affiliation(s)
- Junda Zhu
- Program in Neuroscience, Vanderbilt University, Nashville TN 37235 USA
| | - Clément M Garin
- Department of Biomedical Engineering, Vanderbilt University, Nashville TN 37235 USA
- Institut des Sciences Cognitives Marc Jeannerod, UMR5229 CNRS Université de Lyon, 69675 Bron Cedex, France
| | - Xue-Lian Qi
- Department of Translational Neuroscience, Wake Forest University School of Medicine, Winston Salem, NC 27203, USA
| | - Anna Machado
- Department of Biomedical Engineering, Vanderbilt University, Nashville TN 37235 USA
| | - Zhengyang Wang
- Program in Neuroscience, Vanderbilt University, Nashville TN 37235 USA
| | - Suliann Ben Hamed
- Institut des Sciences Cognitives Marc Jeannerod, UMR5229 CNRS Université de Lyon, 69675 Bron Cedex, France
| | - Terrence R Stanford
- Department of Translational Neuroscience, Wake Forest University School of Medicine, Winston Salem, NC 27203, USA
| | - Emilio Salinas
- Department of Translational Neuroscience, Wake Forest University School of Medicine, Winston Salem, NC 27203, USA
| | - Christopher T Whitlow
- Department of Radiology, Wake Forest University School of Medicine, Winston Salem, NC 27203, USA
| | - Adam W Anderson
- Department of Biomedical Engineering, Vanderbilt University, Nashville TN 37235 USA
| | - Xin Maizie Zhou
- Department of Biomedical Engineering, Vanderbilt University, Nashville TN 37235 USA
| | - Finnegan J Calabro
- Department of Psychiatry, University of Pittsburgh, Pittsburgh PA 15213 USA
| | - Beatriz Luna
- Department of Psychiatry, University of Pittsburgh, Pittsburgh PA 15213 USA
| | - Christos Constantinidis
- Program in Neuroscience, Vanderbilt University, Nashville TN 37235 USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville TN 37235 USA
- Department of Ophthalmology and Visual Sciences, Vanderbilt University Medical Center, Nashville TN 37232, USA
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6
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Zhang Z, Huang Y, Chen X, Li J, Yang Y, Lv L, Wang J, Wang M, Wang Y, Wang Z. State-specific Regulation of Electrical Stimulation in the Intralaminar Thalamus of Macaque Monkeys: Network and Transcriptional Insights into Arousal. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2402718. [PMID: 38938001 PMCID: PMC11434125 DOI: 10.1002/advs.202402718] [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: 03/15/2024] [Revised: 06/03/2024] [Indexed: 06/29/2024]
Abstract
Long-range thalamocortical communication is central to anesthesia-induced loss of consciousness and its reversal. However, isolating the specific neural networks connecting thalamic nuclei with various cortical regions for state-specific anesthesia regulation is challenging, with the biological underpinnings still largely unknown. Here, simultaneous electroencephalogram-fuctional magnetic resonance imaging (EEG-fMRI) and deep brain stimulation are applied to the intralaminar thalamus in macaques under finely-tuned propofol anesthesia. This approach led to the identification of an intralaminar-driven network responsible for rapid arousal during slow-wave oscillations. A network-based RNA-sequencing analysis is conducted of region-, layer-, and cell-specific gene expression data from independent transcriptomic atlases and identifies 2489 genes preferentially expressed within this arousal network, notably enriched in potassium channels and excitatory, parvalbumin-expressing neurons, and oligodendrocytes. Comparison with human RNA-sequencing data highlights conserved molecular and cellular architectures that enable the matching of homologous genes, protein interactions, and cell types across primates, providing novel insight into network-focused transcriptional signatures of arousal.
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Affiliation(s)
- Zhao Zhang
- Department of Anesthesiology, Huashan Hospital, Fudan University, 12 Urumqi Middle Rd, Jing'an District, Shanghai, 200040, China
| | - Yichun Huang
- School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, State Key Laboratory of General Artificial Intelligence, IDG/McGovern Institute for Brain Research, Peking-Tsinghua Center for Life Sciences, Peking University, 5 Yiheyuan Rd, Haidian District, Beijing, 100871, China
| | - Xiaoyu Chen
- Institute of Natural Sciences and School of Mathematical Sciences, Shanghai Jiao Tong University, 800 Dongchuan RD, Minhang District, Shanghai, 200240, China
| | - Jiahui Li
- School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, State Key Laboratory of General Artificial Intelligence, IDG/McGovern Institute for Brain Research, Peking-Tsinghua Center for Life Sciences, Peking University, 5 Yiheyuan Rd, Haidian District, Beijing, 100871, China
| | - Yi Yang
- Department of Neurosurgery, Brain Computer Interface Transition Research Center, Beijing Tiantan Hospital, Capital Medical University, 119 South Fourth Ring Rd West, Fengtai District, Beijing, 100070, China
| | - Longbao Lv
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, 32 East of Jiaochang Rd, Kunming, Yunnan, 650223, China
| | - Jianhong Wang
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, 32 East of Jiaochang Rd, Kunming, Yunnan, 650223, China
| | - Meiyun Wang
- Department of Medical Imaging, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan, 450003, China
| | - Yingwei Wang
- Department of Anesthesiology, Huashan Hospital, Fudan University, 12 Urumqi Middle Rd, Jing'an District, Shanghai, 200040, China
| | - Zheng Wang
- School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, State Key Laboratory of General Artificial Intelligence, IDG/McGovern Institute for Brain Research, Peking-Tsinghua Center for Life Sciences, Peking University, 5 Yiheyuan Rd, Haidian District, Beijing, 100871, China
- School of Biomedical Engineering, Hainan University, 58 Renmin Avenue, Haikou, Hainan, 570228, China
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Zhong T, Wang Y, Xu X, Wu X, Liang S, Ning Z, Wang L, Niu Y, Li G, Zhang Y. A brain subcortical segmentation tool based on anatomy attentional fusion network for developing macaques. Comput Med Imaging Graph 2024; 116:102404. [PMID: 38870599 DOI: 10.1016/j.compmedimag.2024.102404] [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: 01/31/2024] [Revised: 05/21/2024] [Accepted: 05/22/2024] [Indexed: 06/15/2024]
Abstract
Magnetic Resonance Imaging (MRI) plays a pivotal role in the accurate measurement of brain subcortical structures in macaques, which is crucial for unraveling the complexities of brain structure and function, thereby enhancing our understanding of neurodegenerative diseases and brain development. However, due to significant differences in brain size, structure, and imaging characteristics between humans and macaques, computational tools developed for human neuroimaging studies often encounter obstacles when applied to macaques. In this context, we propose an Anatomy Attentional Fusion Network (AAF-Net), which integrates multimodal MRI data with anatomical constraints in a multi-scale framework to address the challenges posed by the dynamic development, regional heterogeneity, and age-related size variations of the juvenile macaque brain, thus achieving precise subcortical segmentation. Specifically, we generate a Signed Distance Map (SDM) based on the initial rough segmentation of the subcortical region by a network as an anatomical constraint, providing comprehensive information on positions, structures, and morphology. Then we construct AAF-Net to fully fuse the SDM anatomical constraints and multimodal images for refined segmentation. To thoroughly evaluate the performance of our proposed tool, over 700 macaque MRIs from 19 datasets were used in this study. Specifically, we employed two manually labeled longitudinal macaque datasets to develop the tool and complete four-fold cross-validations. Furthermore, we incorporated various external datasets to demonstrate the proposed tool's generalization capabilities and promise in brain development research. We have made this tool available as an open-source resource at https://github.com/TaoZhong11/Macaque_subcortical_segmentation for direct application.
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Affiliation(s)
- Tao Zhong
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, China
| | - Ya Wang
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, USA
| | - Xiaotong Xu
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, China
| | - Xueyang Wu
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, China
| | - Shujun Liang
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, China
| | - Zhenyuan Ning
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, China
| | - Li Wang
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, USA
| | - Yuyu Niu
- Yunnan Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, China
| | - Gang Li
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, USA.
| | - Yu Zhang
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, China.
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8
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Lu Y, Cui Y, Cao L, Dong Z, Cheng L, Wu W, Wang C, Liu X, Liu Y, Zhang B, Li D, Zhao B, Wang H, Li K, Ma L, Shi W, Li W, Ma Y, Du Z, Zhang J, Xiong H, Luo N, Liu Y, Hou X, Han J, Sun H, Cai T, Peng Q, Feng L, Wang J, Paxinos G, Yang Z, Fan L, Jiang T. Macaque Brainnetome Atlas: A multifaceted brain map with parcellation, connection, and histology. Sci Bull (Beijing) 2024; 69:2241-2259. [PMID: 38580551 DOI: 10.1016/j.scib.2024.03.031] [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: 10/12/2023] [Revised: 01/18/2024] [Accepted: 03/11/2024] [Indexed: 04/07/2024]
Abstract
The rhesus macaque (Macaca mulatta) is a crucial experimental animal that shares many genetic, brain organizational, and behavioral characteristics with humans. A macaque brain atlas is fundamental to biomedical and evolutionary research. However, even though connectivity is vital for understanding brain functions, a connectivity-based whole-brain atlas of the macaque has not previously been made. In this study, we created a new whole-brain map, the Macaque Brainnetome Atlas (MacBNA), based on the anatomical connectivity profiles provided by high angular and spatial resolution ex vivo diffusion MRI data. The new atlas consists of 248 cortical and 56 subcortical regions as well as their structural and functional connections. The parcellation and the diffusion-based tractography were evaluated with invasive neuronal-tracing and Nissl-stained images. As a demonstrative application, the structural connectivity divergence between macaque and human brains was mapped using the Brainnetome atlases of those two species to uncover the genetic underpinnings of the evolutionary changes in brain structure. The resulting resource includes: (1) the thoroughly delineated Macaque Brainnetome Atlas (MacBNA), (2) regional connectivity profiles, (3) the postmortem high-resolution macaque diffusion and T2-weighted MRI dataset (Brainnetome-8), and (4) multi-contrast MRI, neuronal-tracing, and histological images collected from a single macaque. MacBNA can serve as a common reference frame for mapping multifaceted features across modalities and spatial scales and for integrative investigation and characterization of brain organization and function. Therefore, it will enrich the collaborative resource platform for nonhuman primates and facilitate translational and comparative neuroscience research.
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Affiliation(s)
- Yuheng Lu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yue Cui
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Long Cao
- Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou 450001, China; Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Zhenwei Dong
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Luqi Cheng
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin 541004, China; Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China
| | - Wen Wu
- Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China
| | - Changshuo Wang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China; Sino-Danish College, University of Chinese Academy of Science, Beijing 100049, China
| | - Xinyi Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Youtong Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Baogui Zhang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Deying Li
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Bokai Zhao
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Haiyan Wang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Kaixin Li
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin 150080, China
| | - Liang Ma
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Weiyang Shi
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wen Li
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yawei Ma
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China; Sino-Danish College, University of Chinese Academy of Science, Beijing 100049, China
| | - Zongchang Du
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jiaqi Zhang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hui Xiong
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Na Luo
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Yanyan Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Xiaoxiao Hou
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Jinglu Han
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China; Sino-Danish College, University of Chinese Academy of Science, Beijing 100049, China
| | - Hongji Sun
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Tao Cai
- Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China
| | - Qiang Peng
- Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China
| | - Linqing Feng
- Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China
| | - Jiaojian Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
| | - George Paxinos
- Neuroscience Research Australia and The University of New South Wales, Sydney NSW 2031, Australia
| | - Zhengyi Yang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; Xiaoxiang Institute for Brain Health and Yongzhou Central Hospital, Yongzhou 425000, China.
| | - Lingzhong Fan
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Tianzi Jiang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China; Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China; Xiaoxiang Institute for Brain Health and Yongzhou Central Hospital, Yongzhou 425000, China.
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9
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Fujimoto SH, Fujimoto A, Elorette C, Seltzer A, Andraka E, Verma G, Janssen WGM, Fleysher L, Folloni D, Choi KS, Russ BE, Mayberg HS, Rudebeck PH. Deep brain stimulation induces white matter remodeling and functional changes to brain-wide networks. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.13.598710. [PMID: 38915600 PMCID: PMC11195276 DOI: 10.1101/2024.06.13.598710] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
Deep brain stimulation (DBS) is an emerging therapeutic option for treatment resistant neurological and psychiatric disorders, most notably depression. Despite this, little is known about the anatomical and functional mechanisms that underlie this therapy. Here we targeted stimulation to the white matter adjacent to the subcallosal anterior cingulate cortex (SCC-DBS) in macaques, modeling the location in the brain proven effective for depression. We demonstrate that SCC-DBS has a selective effect on white matter macro- and micro-structure in the cingulum bundle distant to where stimulation was delivered. SCC-DBS also decreased functional connectivity between subcallosal and posterior cingulate cortex, two areas linked by the cingulum bundle and implicated in depression. Our data reveal that white matter remodeling as well as functional effects contribute to DBS's therapeutic efficacy.
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Affiliation(s)
- Satoka H. Fujimoto
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai; New York, NY 10029, USA
- Lipschultz Center for Cognitive Neuroscience, Icahn School of Medicine at Mount Sinai; New York, NY 10029, USA
| | - Atsushi Fujimoto
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai; New York, NY 10029, USA
- Lipschultz Center for Cognitive Neuroscience, Icahn School of Medicine at Mount Sinai; New York, NY 10029, USA
| | - Catherine Elorette
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai; New York, NY 10029, USA
- Lipschultz Center for Cognitive Neuroscience, Icahn School of Medicine at Mount Sinai; New York, NY 10029, USA
| | - Adela Seltzer
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai; New York, NY 10029, USA
- Lipschultz Center for Cognitive Neuroscience, Icahn School of Medicine at Mount Sinai; New York, NY 10029, USA
| | - Emma Andraka
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai; New York, NY 10029, USA
- Lipschultz Center for Cognitive Neuroscience, Icahn School of Medicine at Mount Sinai; New York, NY 10029, USA
| | - Gaurav Verma
- Nash Family Center for Advanced Circuit Therapeutics, Mount Sinai West Hospital; New York, NY 10019, USA
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai; New York, NY 10029, USA
| | - William GM Janssen
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai; New York, NY 10029, USA
| | - Lazar Fleysher
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai; New York, NY 10029, USA
| | - Davide Folloni
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai; New York, NY 10029, USA
- Lipschultz Center for Cognitive Neuroscience, Icahn School of Medicine at Mount Sinai; New York, NY 10029, USA
| | - Ki Sueng Choi
- Nash Family Center for Advanced Circuit Therapeutics, Mount Sinai West Hospital; New York, NY 10019, USA
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai; New York, NY 10029, USA
| | - Brian E. Russ
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai; New York, NY 10029, USA
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute; Orangeburg, NY 10962, USA
- Department of Psychiatry, New York University at Langone; New York, NY 10016, USA
| | - Helen S. Mayberg
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai; New York, NY 10029, USA
- Nash Family Center for Advanced Circuit Therapeutics, Mount Sinai West Hospital; New York, NY 10019, USA
| | - Peter H. Rudebeck
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai; New York, NY 10029, USA
- Lipschultz Center for Cognitive Neuroscience, Icahn School of Medicine at Mount Sinai; New York, NY 10029, USA
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10
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Ensel S, Uhrig L, Ozkirli A, Hoffner G, Tasserie J, Dehaene S, Van De Ville D, Jarraya B, Pirondini E. Transient brain activity dynamics discriminate levels of consciousness during anesthesia. Commun Biol 2024; 7:716. [PMID: 38858589 PMCID: PMC11164921 DOI: 10.1038/s42003-024-06335-x] [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: 10/20/2023] [Accepted: 05/15/2024] [Indexed: 06/12/2024] Open
Abstract
The awake mammalian brain is functionally organized in terms of large-scale distributed networks that are constantly interacting. Loss of consciousness might disrupt this temporal organization leaving patients unresponsive. We hypothesize that characterizing brain activity in terms of transient events may provide a signature of consciousness. For this, we analyze temporal dynamics of spatiotemporally overlapping functional networks obtained from fMRI transient activity across different anesthetics and levels of anesthesia. We first show a striking homology in spatial organization of networks between monkeys and humans, indicating cross-species similarities in resting-state fMRI structure. We then track how network organization shifts under different anesthesia conditions in macaque monkeys. While the spatial aspect of the networks is preserved, their temporal dynamics are highly affected by anesthesia. Networks express for longer durations and co-activate in an anesthetic-specific configuration. Additionally, hierarchical brain organization is disrupted with a consciousness-level-signature role of the default mode network. In conclusion, large-scale brain network temporal dynamics capture differences in anesthetic-specific consciousness-level, paving the way towards a clinical translation of these cortical signature.
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Affiliation(s)
- Scott Ensel
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Lynn Uhrig
- NeuroSpin Center, Institute of BioImaging Commissariat à l'Energie Atomique, Gif/Yvette, France
- Cognitive Neuroimaging Unit, INSERM, U992, Gif/Yvette, France
- Department of Anesthesiology and Critical Care, Necker Hospital, AP-HP, Université Paris Cité, Paris, France
| | - Ayberk Ozkirli
- Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland
| | - Guylaine Hoffner
- NeuroSpin Center, Institute of BioImaging Commissariat à l'Energie Atomique, Gif/Yvette, France
- Cognitive Neuroimaging Unit, INSERM, U992, Gif/Yvette, France
| | - Jordy Tasserie
- Harvard Medical School, Boston, MA, USA
- Center for Brain Circuit Therapeutics Department of Neurology Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Stanislas Dehaene
- Cognitive Neuroimaging Unit, INSERM, U992, Gif/Yvette, France
- Collège de France, Paris, France
| | - Dimitri Van De Ville
- Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
| | - Béchir Jarraya
- NeuroSpin Center, Institute of BioImaging Commissariat à l'Energie Atomique, Gif/Yvette, France
- Cognitive Neuroimaging Unit, INSERM, U992, Gif/Yvette, France
- Université Paris-Saclay (UVSQ), Saclay, France
- Neuroscience Pole, Foch Hospital, Suresnes, France
| | - Elvira Pirondini
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA.
- Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland.
- Department of Physical Medicine & Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA.
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11
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Taubert J, Wardle SG, Patterson A, Baker CI. Beyond faces: the contribution of the amygdala to visual processing in the macaque brain. Cereb Cortex 2024; 34:bhae245. [PMID: 38864574 PMCID: PMC11485272 DOI: 10.1093/cercor/bhae245] [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: 02/07/2024] [Revised: 05/03/2024] [Accepted: 05/25/2024] [Indexed: 06/13/2024] Open
Abstract
The amygdala is present in a diverse range of vertebrate species, such as lizards, rodents, and primates; however, its structure and connectivity differs across species. The increased connections to visual sensory areas in primate species suggests that understanding the visual selectivity of the amygdala in detail is critical to revealing the principles underlying its function in primate cognition. Therefore, we designed a high-resolution, contrast-agent enhanced, event-related fMRI experiment, and scanned 3 adult rhesus macaques, while they viewed 96 naturalistic stimuli. Half of these stimuli were social (defined by the presence of a conspecific), the other half were nonsocial. We also nested manipulations of emotional valence (positive, neutral, and negative) and visual category (faces, nonfaces, animate, and inanimate) within the stimulus set. The results reveal widespread effects of emotional valence, with the amygdala responding more on average to inanimate objects and animals than faces, bodies, or social agents in this experimental context. These findings suggest that the amygdala makes a contribution to primate vision that goes beyond an auxiliary role in face or social perception. Furthermore, the results highlight the importance of stimulus selection and experimental design when probing the function of the amygdala and other visually responsive brain regions.
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Affiliation(s)
- Jessica Taubert
- Laboratory of Brain and Cognition, National Institute of Mental Health, 10 Center Dr, Bethesda, MD 20892 USA
- School of Psychology, Level 3, McElwain Building (24A), The University of Queensland, Brisbane, QLD 4072, Australia
| | - Susan G Wardle
- Laboratory of Brain and Cognition, National Institute of Mental Health, 10 Center Dr, Bethesda, MD 20892 USA
| | - Amanda Patterson
- Laboratory of Brain and Cognition, National Institute of Mental Health, 10 Center Dr, Bethesda, MD 20892 USA
| | - Chris I Baker
- Laboratory of Brain and Cognition, National Institute of Mental Health, 10 Center Dr, Bethesda, MD 20892 USA
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12
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Froesel M, Gacoin M, Clavagnier S, Hauser M, Goudard Q, Ben Hamed S. Macaque claustrum, pulvinar and putative dorsolateral amygdala support the cross-modal association of social audio-visual stimuli based on meaning. Eur J Neurosci 2024; 59:3203-3223. [PMID: 38637993 DOI: 10.1111/ejn.16328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 02/14/2024] [Accepted: 03/07/2024] [Indexed: 04/20/2024]
Abstract
Social communication draws on several cognitive functions such as perception, emotion recognition and attention. The association of audio-visual information is essential to the processing of species-specific communication signals. In this study, we use functional magnetic resonance imaging in order to identify the subcortical areas involved in the cross-modal association of visual and auditory information based on their common social meaning. We identified three subcortical regions involved in audio-visual processing of species-specific communicative signals: the dorsolateral amygdala, the claustrum and the pulvinar. These regions responded to visual, auditory congruent and audio-visual stimulations. However, none of them was significantly activated when the auditory stimuli were semantically incongruent with the visual context, thus showing an influence of visual context on auditory processing. For example, positive vocalization (coos) activated the three subcortical regions when presented in the context of positive facial expression (lipsmacks) but not when presented in the context of negative facial expression (aggressive faces). In addition, the medial pulvinar and the amygdala presented multisensory integration such that audiovisual stimuli resulted in activations that were significantly higher than those observed for the highest unimodal response. Last, the pulvinar responded in a task-dependent manner, along a specific spatial sensory gradient. We propose that the dorsolateral amygdala, the claustrum and the pulvinar belong to a multisensory network that modulates the perception of visual socioemotional information and vocalizations as a function of the relevance of the stimuli in the social context. SIGNIFICANCE STATEMENT: Understanding and correctly associating socioemotional information across sensory modalities, such that happy faces predict laughter and escape scenes predict screams, is essential when living in complex social groups. With the use of functional magnetic imaging in the awake macaque, we identify three subcortical structures-dorsolateral amygdala, claustrum and pulvinar-that only respond to auditory information that matches the ongoing visual socioemotional context, such as hearing positively valenced coo calls and seeing positively valenced mutual grooming monkeys. We additionally describe task-dependent activations in the pulvinar, organizing along a specific spatial sensory gradient, supporting its role as a network regulator.
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Affiliation(s)
- Mathilda Froesel
- Institut des Sciences Cognitives Marc Jeannerod, UMR5229 CNRS Université de Lyon, Bron Cedex, France
| | - Maëva Gacoin
- Institut des Sciences Cognitives Marc Jeannerod, UMR5229 CNRS Université de Lyon, Bron Cedex, France
| | - Simon Clavagnier
- Institut des Sciences Cognitives Marc Jeannerod, UMR5229 CNRS Université de Lyon, Bron Cedex, France
| | - Marc Hauser
- Risk-Eraser, West Falmouth, Massachusetts, USA
| | - Quentin Goudard
- Institut des Sciences Cognitives Marc Jeannerod, UMR5229 CNRS Université de Lyon, Bron Cedex, France
| | - Suliann Ben Hamed
- Institut des Sciences Cognitives Marc Jeannerod, UMR5229 CNRS Université de Lyon, Bron Cedex, France
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13
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Elorette C, Fujimoto A, Stoll FM, Fujimoto SH, Bienkowska N, London L, Fleysher L, Russ BE, Rudebeck PH. The neural basis of resting-state fMRI functional connectivity in fronto-limbic circuits revealed by chemogenetic manipulation. Nat Commun 2024; 15:4669. [PMID: 38821963 PMCID: PMC11143237 DOI: 10.1038/s41467-024-49140-0] [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: 06/30/2023] [Accepted: 05/23/2024] [Indexed: 06/02/2024] Open
Abstract
Measures of fMRI resting-state functional connectivity (rs-FC) are an essential tool for basic and clinical investigations of fronto-limbic circuits. Understanding the relationship between rs-FC and the underlying patterns of neural activity in these circuits is therefore vital. Here we introduced inhibitory designer receptors exclusively activated by designer drugs (DREADDs) into the amygdala of two male macaques. We evaluated the causal effect of activating the DREADD receptors on rs-FC and neural activity within circuits connecting amygdala and frontal cortex. Activating the inhibitory DREADD increased rs-FC between amygdala and ventrolateral prefrontal cortex. Neurophysiological recordings revealed that the DREADD-induced increase in fMRI rs-FC was associated with increased local field potential coherency in the alpha band (6.5-14.5 Hz) between amygdala and ventrolateral prefrontal cortex. Thus, our multi-modal approach reveals the specific signature of neuronal activity that underlies rs-FC in fronto-limbic circuits.
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Affiliation(s)
- Catherine Elorette
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
- Lipschultz Center for Cognitive Neuroscience, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
| | - Atsushi Fujimoto
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
- Lipschultz Center for Cognitive Neuroscience, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
| | - Frederic M Stoll
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
- Lipschultz Center for Cognitive Neuroscience, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
| | - Satoka H Fujimoto
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
- Lipschultz Center for Cognitive Neuroscience, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
| | - Niranjana Bienkowska
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
- Lipschultz Center for Cognitive Neuroscience, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
| | - Liza London
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
- Lipschultz Center for Cognitive Neuroscience, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
| | - Lazar Fleysher
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
| | - Brian E Russ
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA.
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, 140 Old Orangeburg Road, Orangeburg, NY, 10962, USA.
- Department of Psychiatry, New York University at Langone, 550 1st Avenue, New York, NY, 10016, USA.
| | - Peter H Rudebeck
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA.
- Lipschultz Center for Cognitive Neuroscience, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA.
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14
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Charbonneau JA, Santistevan AC, Raven EP, Bennett JL, Russ BE, Bliss-Moreau E. Evolutionarily conserved neural responses to affective touch in monkeys transcend consciousness and change with age. Proc Natl Acad Sci U S A 2024; 121:e2322157121. [PMID: 38648473 PMCID: PMC11067024 DOI: 10.1073/pnas.2322157121] [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: 12/15/2023] [Accepted: 03/05/2024] [Indexed: 04/25/2024] Open
Abstract
Affective touch-a slow, gentle, and pleasant form of touch-activates a different neural network than which is activated during discriminative touch in humans. Affective touch perception is enabled by specialized low-threshold mechanoreceptors in the skin with unmyelinated fibers called C tactile (CT) afferents. These CT afferents are conserved across mammalian species, including macaque monkeys. However, it is unknown whether the neural representation of affective touch is the same across species and whether affective touch's capacity to activate the hubs of the brain that compute socioaffective information requires conscious perception. Here, we used functional MRI to assess the preferential activation of neural hubs by slow (affective) vs. fast (discriminative) touch in anesthetized rhesus monkeys (Macaca mulatta). The insula, anterior cingulate cortex (ACC), amygdala, and secondary somatosensory cortex were all significantly more active during slow touch relative to fast touch, suggesting homologous activation of the interoceptive-allostatic network across primate species during affective touch. Further, we found that neural responses to affective vs. discriminative touch in the insula and ACC (the primary cortical hubs for interoceptive processing) changed significantly with age. Insula and ACC in younger animals differentiated between slow and fast touch, while activity was comparable between conditions for aged monkeys (equivalent to >70 y in humans). These results, together with prior studies establishing conserved peripheral nervous system mechanisms of affective touch transduction, suggest that neural responses to affective touch are evolutionarily conserved in monkeys, significantly impacted in old age, and do not necessitate conscious experience of touch.
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Affiliation(s)
- Joey A. Charbonneau
- Neuroscience Graduate Program, University of California, Davis, CA95616
- Neuroscience and Behavior Unit, California National Primate Research Center, University of California, Davis, CA95616
| | - Anthony C. Santistevan
- Neuroscience and Behavior Unit, California National Primate Research Center, University of California, Davis, CA95616
- Department of Psychology, University of California, Davis, CA95616
| | - Erika P. Raven
- Department of Radiology, Center for Biomedical Imaging, New York University Grossman School of Medicine, New York, NY10016
| | - Jeffrey L. Bennett
- Neuroscience and Behavior Unit, California National Primate Research Center, University of California, Davis, CA95616
- Department of Psychology, University of California, Davis, CA95616
- Department of Psychiatry and Behavioral Sciences, University of California, Davis School of Medicine, Sacramento, CA95817
- The Medical Investigation of Neurodevelopmental Disorders Institute, University of California, Sacramento, CA95817
| | - Brian E. Russ
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY10962
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY10029
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY10029
- Department of Psychiatry, New York University Langone, New York, NY10016
| | - Eliza Bliss-Moreau
- Neuroscience and Behavior Unit, California National Primate Research Center, University of California, Davis, CA95616
- Department of Psychology, University of California, Davis, CA95616
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15
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Yoshida A, Hikosaka O. Involvement of neurons in the non-human primate anterior striatum in proactive inhibition. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.24.591009. [PMID: 38712157 PMCID: PMC11071629 DOI: 10.1101/2024.04.24.591009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Behaving as desired requires selecting the appropriate behavior and inhibiting the selection of inappropriate behavior. This inhibitory function involves multiple processes, such as reactive and proactive inhibition, instead of a single process. In this study, macaque monkeys were required to perform a task in which they had to sequentially select (accept) or refuse (reject) a choice. Neural activity was recorded from the anterior striatum, which is considered to be involved in behavioral inhibition, focusing on the distinction between proactive and reactive inhibitions. We identified neurons with significant activity changes during the rejection of bad objects. Cluster analysis revealed three distinct groups, of which one showed obviously increased activity during object rejection, suggesting its involvement in proactive inhibition. This activity pattern was consistent irrespective of the rejection method, indicating a role beyond mere saccadic suppression. Furthermore, minimal activity changes during the fixation task indicated that these neurons were not primarily involved in reactive inhibition. In conclusion, these findings suggest that the anterior striatum plays a crucial role in cognitive control and orchestrates goal-directed behavior through proactive inhibition, which may be critical in understanding the mechanisms of behavioral inhibition dysfunction that occur in patients with basal ganglia disease.
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Affiliation(s)
- Atsushi Yoshida
- Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Okihide Hikosaka
- Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA
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16
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Giacometti C, Autran-Clavagnier D, Dureux A, Viñales L, Lamberton F, Procyk E, Wilson CRE, Amiez C, Hadj-Bouziane F. Differential functional organization of amygdala-medial prefrontal cortex networks in macaque and human. Commun Biol 2024; 7:269. [PMID: 38443489 PMCID: PMC10914752 DOI: 10.1038/s42003-024-05918-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 02/14/2024] [Indexed: 03/07/2024] Open
Abstract
Over the course of evolution, the amygdala (AMG) and medial frontal cortex (mPFC) network, involved in behavioral adaptation, underwent structural changes in the old-world monkey and human lineages. Yet, whether and how the functional organization of this network differs remains poorly understood. Using resting-state functional magnetic resonance imagery, we show that the functional connectivity (FC) between AMG nuclei and mPFC regions differs between humans and awake macaques. In humans, the AMG-mPFC FC displays U-shaped pattern along the corpus callosum: a positive FC with the ventromedial prefrontal (vmPFC) and anterior cingulate cortex (ACC), a negative FC with the anterior mid-cingulate cortex (MCC), and a positive FC with the posterior MCC. Conversely, in macaques, the negative FC shifted more ventrally at the junction between the vmPFC and the ACC. The functional organization divergence of AMG-mPFC network between humans and macaques might help understanding behavioral adaptation abilities differences in their respective socio-ecological niches.
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Affiliation(s)
- Camille Giacometti
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500, Bron, France.
| | - Delphine Autran-Clavagnier
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500, Bron, France
- Inovarion, 75005, Paris, France
| | - Audrey Dureux
- Integrative Multisensory Perception Action & Cognition Team (ImpAct), INSERM U1028, CNRS UMR5292, Lyon Neuroscience Research Center (CRNL); Université Lyon 1, 69500, Bron, France
| | - Laura Viñales
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500, Bron, France
| | - Franck Lamberton
- La Structure Fédérative de Recherche Santé Lyon-Est, CNRS UAR 3453, INSERM US7, Lyon 1 University, 69008, Lyon, France
- Centre d'Etude et de Recherche Multimodal et Pluridisciplinaire en Imagerie du Vivant (CERMEP), 69677, Bron, France
| | - Emmanuel Procyk
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500, Bron, France
| | - Charles R E Wilson
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500, Bron, France
| | - Céline Amiez
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500, Bron, France.
| | - Fadila Hadj-Bouziane
- Integrative Multisensory Perception Action & Cognition Team (ImpAct), INSERM U1028, CNRS UMR5292, Lyon Neuroscience Research Center (CRNL); Université Lyon 1, 69500, Bron, France.
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17
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Qiu L, Xu E, Chambule S, LaTourette P, Dyer CD, Wallace CK, Donocoff R, Wilson JM, Lucas TH, Chen HI. Magnetic Resonance Imaging-Guided Frameless Stereotactic Injections of the Bilateral Cerebellar Dentate Nuclei in Nonhuman Primates: Technical Note. Oper Neurosurg (Hagerstown) 2024:01787389-990000000-01040. [PMID: 38310346 DOI: 10.1227/ons.0000000000001050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 10/20/2023] [Indexed: 02/05/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Nonhuman primates (NHPs) are important preclinical models for evaluating therapeutics because of their anatomophysiological similarities to humans, and can be especially useful for testing new delivery targets. With the growing promise of cell and gene therapies for the treatment of neurological diseases, it is important to ensure the accurate and safe delivery of these agents to target structures in the brain. However, a standard guideline or method has not been developed for stereotactic targeting in NHPs. In this article, we describe the safe use of a magnetic resonance imaging-guided frameless stereotactic system to target bilateral cerebellar dentate nuclei for accurate, real-time delivery of viral vector in NHPs. METHODS Seventeen rhesus macaques (Macaca mulatta) underwent stereotactic surgery under real-time MRI guidance using the ClearPoint® system. Bilateral cerebellar dentate nuclei were targeted through a single parietal entry point with a transtentorial approach. Fifty microliters of contrast-impregnated infusate was delivered to each dentate nucleus, and adjustments were made as necessary according to real-time MRI monitoring of delivery. Perioperative clinical outcomes and postoperative volumes of distribution were recorded. RESULTS All macaques underwent bilateral surgery successfully. Superficial pin site infection occurred in 4/17 (23.5%) subjects, which resolved with antibiotics. Two episodes of transient neurological deficit (anisocoria and unilateral weakness) were recorded, which did not require additional postoperative treatment and resolved over time. Volume of distribution of infusate achieved satisfactory coverage of target dentate nuclei, and only 1 incidence (2.9%) of cerebrospinal fluid penetration was recorded. Mean volume of distribution was 161.22 ± 39.61 mm3 (left, 173.65 ± 48.29; right, 148.80 ± 23.98). CONCLUSION MRI-guided frameless stereotactic injection of bilateral cerebellar dentate nuclei in NHPs is safe and feasible. The use of this technique enables real-time modification of the surgical plan to achieve adequate target coverage and can be readily translated to clinical use.
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Affiliation(s)
- Liming Qiu
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Emily Xu
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sydney Chambule
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Philip LaTourette
- Gene Therapy Program, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Current Affiliation: Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Cecilia D Dyer
- Gene Therapy Program, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Chelsea K Wallace
- Gene Therapy Program, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Rachel Donocoff
- Gene Therapy Program, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Current Affiliation: Bristol Myers Squibb, Princeton, New Jersey, USA
| | - James M Wilson
- Gene Therapy Program, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Timothy H Lucas
- Department of Neurosurgery, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA
| | - H Isaac Chen
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Surgery, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania, USA
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18
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Fujimoto A, Elorette C, Fujimoto SH, Fleysher L, Rudebeck PH, Russ BE. Pharmacological modulation of dopamine D1 and D2 receptors reveals distinct neural networks related to probabilistic learning in non-human primates. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.27.573487. [PMID: 38234858 PMCID: PMC10793459 DOI: 10.1101/2023.12.27.573487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
The neurotransmitter dopamine (DA) has a multifaceted role in healthy and disordered brains through its action on multiple subtypes of dopaminergic receptors. How modulation of these receptors controls behavior by altering connectivity across intrinsic brain-wide networks remains elusive. Here we performed parallel behavioral and resting-state functional MRI experiments after administration of two different DA receptor antagonists in macaque monkeys. Systemic administration of SCH-23390 (D1 antagonist) disrupted probabilistic learning when subjects had to learn new stimulus-reward associations and diminished functional connectivity (FC) in cortico-cortical and fronto-striatal connections. By contrast, haloperidol (D2 antagonist) improved learning and broadly enhanced FC in cortical connections. Further comparison between the effect of SCH-23390/haloperidol on behavioral and resting-state FC revealed specific cortical and subcortical networks associated with the cognitive and motivational effects of DA, respectively. Thus, we reveal the distinct brain-wide networks that are associated with the dopaminergic control of learning and motivation via DA receptors.
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Affiliation(s)
- Atsushi Fujimoto
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
- Lipschultz Center for Cognitive Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, 10029
| | - Catherine Elorette
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
- Lipschultz Center for Cognitive Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, 10029
| | - Satoka H. Fujimoto
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
- Lipschultz Center for Cognitive Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, 10029
| | - Lazar Fleysher
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
| | - Peter H. Rudebeck
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
- Lipschultz Center for Cognitive Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, 10029
| | - Brian E. Russ
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, 140 Old Orangeburg Road, Orangeburg, NY 10962
- Department of Psychiatry, New York University at Langone, One, 8, Park Ave, New York, NY 10016
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19
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Shan L, Yuan L, Zhang B, Ma J, Xu X, Gu F, Jiang Y, Dai J. Neural Integration of Audiovisual Sensory Inputs in Macaque Amygdala and Adjacent Regions. Neurosci Bull 2023; 39:1749-1761. [PMID: 36920645 PMCID: PMC10661144 DOI: 10.1007/s12264-023-01043-8] [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: 01/16/2023] [Accepted: 02/13/2023] [Indexed: 03/16/2023] Open
Abstract
Integrating multisensory inputs to generate accurate perception and guide behavior is among the most critical functions of the brain. Subcortical regions such as the amygdala are involved in sensory processing including vision and audition, yet their roles in multisensory integration remain unclear. In this study, we systematically investigated the function of neurons in the amygdala and adjacent regions in integrating audiovisual sensory inputs using a semi-chronic multi-electrode array and multiple combinations of audiovisual stimuli. From a sample of 332 neurons, we showed the diverse response patterns to audiovisual stimuli and the neural characteristics of bimodal over unimodal modulation, which could be classified into four types with differentiated regional origins. Using the hierarchical clustering method, neurons were further clustered into five groups and associated with different integrating functions and sub-regions. Finally, regions distinguishing congruent and incongruent bimodal sensory inputs were identified. Overall, visual processing dominates audiovisual integration in the amygdala and adjacent regions. Our findings shed new light on the neural mechanisms of multisensory integration in the primate brain.
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Affiliation(s)
- Liang Shan
- CAS Key Laboratory of Brain Connectome and Manipulation, the Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
- Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China
| | - Liu Yuan
- CAS Key Laboratory of Brain Connectome and Manipulation, the Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Bo Zhang
- CAS Key Laboratory of Brain Connectome and Manipulation, the Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
- Key Laboratory of Brain Science, Zunyi Medical University, Zunyi, 563000, China
| | - Jian Ma
- CAS Key Laboratory of Brain Connectome and Manipulation, the Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Xiao Xu
- CAS Key Laboratory of Brain Connectome and Manipulation, the Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Fei Gu
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Yi Jiang
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China.
- Chinese Institute for Brain Research, Beijing, 102206, China.
| | - Ji Dai
- CAS Key Laboratory of Brain Connectome and Manipulation, the Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
- Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Shenzhen Technological Research Center for Primate Translational Medicine, Shenzhen, 518055, China.
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20
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Schira MM, Isherwood ZJ, Kassem MS, Barth M, Shaw TB, Roberts MM, Paxinos G. HumanBrainAtlas: an in vivo MRI dataset for detailed segmentations. Brain Struct Funct 2023; 228:1849-1863. [PMID: 37277567 PMCID: PMC10516788 DOI: 10.1007/s00429-023-02653-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 05/13/2023] [Indexed: 06/07/2023]
Abstract
We introduce HumanBrainAtlas, an initiative to construct a highly detailed, open-access atlas of the living human brain that combines high-resolution in vivo MR imaging and detailed segmentations previously possible only in histological preparations. Here, we present and evaluate the first step of this initiative: a comprehensive dataset of two healthy male volunteers reconstructed to a 0.25 mm isotropic resolution for T1w, T2w, and DWI contrasts. Multiple high-resolution acquisitions were collected for each contrast and each participant, followed by averaging using symmetric group-wise normalisation (Advanced Normalisation Tools). The resulting image quality permits structural parcellations rivalling histology-based atlases, while maintaining the advantages of in vivo MRI. For example, components of the thalamus, hypothalamus, and hippocampus are often impossible to identify using standard MRI protocols-can be identified within the present data. Our data are virtually distortion free, fully 3D, and compatible with the existing in vivo Neuroimaging analysis tools. The dataset is suitable for teaching and is publicly available via our website (hba.neura.edu.au), which also provides data processing scripts. Instead of focusing on coordinates in an averaged brain space, our approach focuses on providing an example segmentation at great detail in the high-quality individual brain. This serves as an illustration on what features contrasts and relations can be used to interpret MRI datasets, in research, clinical, and education settings.
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Affiliation(s)
- Mark M Schira
- School of Psychology, University of Wollongong, Wollongong, NSW, 2522, Australia.
- Neuroscience Research Australia, Randwick, NSW, 2031, Australia.
| | - Zoey J Isherwood
- School of Psychology, University of Wollongong, Wollongong, NSW, 2522, Australia
- Department of Psychology, University of Nevada, Reno, NV, 89557, USA
| | - Mustafa S Kassem
- Neuroscience Research Australia, Randwick, NSW, 2031, Australia
- School of Psychology, The University of New South Wales, Sydney, NSW, 2052, Australia
| | - Markus Barth
- Centre for Advanced Imaging, The University of Queensland, St Lucia, QLD, 4067, Australia
- School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, QLD, 7067, Australia
| | - Thomas B Shaw
- Centre for Advanced Imaging, The University of Queensland, St Lucia, QLD, 4067, Australia
- School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, QLD, 7067, Australia
| | - Michelle M Roberts
- School of Psychology, University of Wollongong, Wollongong, NSW, 2522, Australia
- School of Psychology, The University of New South Wales, Sydney, NSW, 2052, Australia
| | - George Paxinos
- Neuroscience Research Australia, Randwick, NSW, 2031, Australia
- School of Psychology, The University of New South Wales, Sydney, NSW, 2052, Australia
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21
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Zhai R, Tong G, Li Z, Song W, Hu Y, Xu S, Wei Q, Zhang X, Li Y, Liao B, Yuan C, Fan Y, Song G, Ouyang Y, Zhang W, Tang Y, Jin M, Zhang Y, Li H, Yang Z, Lin GN, Stein DJ, Xiong ZQ, Wang Z. Rhesus monkeys exhibiting spontaneous ritualistic behaviors resembling obsessive-compulsive disorder. Natl Sci Rev 2023; 10:nwad312. [PMID: 38152386 PMCID: PMC10751879 DOI: 10.1093/nsr/nwad312] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 12/05/2023] [Accepted: 12/06/2023] [Indexed: 12/29/2023] Open
Abstract
Obsessive-compulsive disorder (OCD) is a chronic and debilitating psychiatric disorder that affects ∼2%-3% of the population globally. Studying spontaneous OCD-like behaviors in non-human primates may improve our understanding of the disorder. In large rhesus monkey colonies, we found 10 monkeys spontaneously exhibiting persistent sequential motor behaviors (SMBs) in individual-specific sequences that were repetitive, time-consuming and stable over prolonged periods. Genetic analysis revealed severely damaging mutations in genes associated with OCD risk in humans. Brain imaging showed that monkeys with SMBs had larger gray matter (GM) volumes in the left caudate nucleus and lower fractional anisotropy of the corpus callosum. The GM volume of the left caudate nucleus correlated positively with the daily duration of SMBs. Notably, exposure to a stressor (human presence) significantly increased SMBs. In addition, fluoxetine, a serotonergic medication commonly used for OCD, decreased SMBs in these monkeys. These findings provide a novel foundation for developing better understanding and treatment of OCD.
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Affiliation(s)
- Rongwei Zhai
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
- Lingang Laboratory, Shanghai 200031, China
- Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 201602, China
| | - Geya Tong
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Zheqin Li
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Weichen Song
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Yang Hu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Sha Xu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
- Lingang Laboratory, Shanghai 200031, China
| | - Qiqi Wei
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
- Lingang Laboratory, Shanghai 200031, China
| | - Xiaocheng Zhang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
- Lingang Laboratory, Shanghai 200031, China
| | - Yi Li
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Bingbing Liao
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Chenyu Yuan
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Yinqing Fan
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Ge Song
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Yinyin Ouyang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Wenxuan Zhang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Yaqiu Tang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Minghui Jin
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Yuxian Zhang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - He Li
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Zhi Yang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Guan Ning Lin
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Dan J Stein
- Translational Neuropsychiatry Unit (TNU), Department of Clinical Medicine, Aarhus University, Aarhus 8200, Denmark
| | - Zhi-Qi Xiong
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
- Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 201602, China
| | - Zhen Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
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22
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Elorette C, Fujimoto A, Stoll FM, Fujimoto SH, Fleysher L, Bienkowska N, Russ BE, Rudebeck PH. The neural basis of resting-state fMRI functional connectivity in fronto-limbic circuits revealed by chemogenetic manipulation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.21.545778. [PMID: 37745436 PMCID: PMC10515745 DOI: 10.1101/2023.06.21.545778] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Measures of fMRI resting-state functional connectivity (rs-FC) are an essential tool for basic and clinical investigations of fronto-limbic circuits. Understanding the relationship between rs-FC and neural activity in these circuits is therefore vital. Here we introduced inhibitory designer receptors exclusively activated by designer drugs (DREADDs) into the macaque amygdala and activated them with a highly selective and potent DREADD agonist, deschloroclozapine. We evaluated the causal effect of activating the DREADD receptors on rs-FC and neural activity within circuits connecting amygdala and frontal cortex. Interestingly, activating the inhibitory DREADD increased rs-FC between amygdala and ventrolateral prefrontal cortex. Neurophysiological recordings revealed that the DREADD-induced increase in fMRI rs-FC was associated with increased local field potential coherency in the alpha band (6.5-14.5Hz) between amygdala and ventrolateral prefrontal cortex. Thus, our multi-disciplinary approach reveals the specific signature of neuronal activity that underlies rs-FC in fronto-limbic circuits.
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Affiliation(s)
- Catherine Elorette
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
| | - Atsushi Fujimoto
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
| | - Frederic M. Stoll
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
| | - Satoka H. Fujimoto
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
| | - Lazar Fleysher
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
| | - Niranjana Bienkowska
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
| | - Brian E. Russ
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, 140 Old Orangeburg Road, Orangeburg, NY 10962
- Department of Psychiatry, New York University at Langone, One, 8, Park Ave, New York, NY 10016
| | - Peter H. Rudebeck
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
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23
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Nieuwland JM, Nutma E, Philippens IHCHM, Böszörményi KP, Remarque EJ, Bakker J, Meijer L, Woerdman N, Fagrouch ZC, Verstrepen BE, Langermans JAM, Verschoor EJ, Windhorst AD, Bontrop RE, de Vries HE, Stammes MA, Middeldorp J. Longitudinal positron emission tomography and postmortem analysis reveals widespread neuroinflammation in SARS-CoV-2 infected rhesus macaques. J Neuroinflammation 2023; 20:179. [PMID: 37516868 PMCID: PMC10387202 DOI: 10.1186/s12974-023-02857-z] [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] [Received: 04/06/2023] [Accepted: 07/19/2023] [Indexed: 07/31/2023] Open
Abstract
BACKGROUND Coronavirus disease 2019 (COVID-19) patients initially develop respiratory symptoms, but they may also suffer from neurological symptoms. People with long-lasting effects after acute infections with severe respiratory syndrome coronavirus 2 (SARS-CoV-2), i.e., post-COVID syndrome or long COVID, may experience a variety of neurological manifestations. Although we do not fully understand how SARS-CoV-2 affects the brain, neuroinflammation likely plays a role. METHODS To investigate neuroinflammatory processes longitudinally after SARS-CoV-2 infection, four experimentally SARS-CoV-2 infected rhesus macaques were monitored for 7 weeks with 18-kDa translocator protein (TSPO) positron emission tomography (PET) using [18F]DPA714, together with computed tomography (CT). The baseline scan was compared to weekly PET-CTs obtained post-infection (pi). Brain tissue was collected following euthanasia (50 days pi) to correlate the PET signal with TSPO expression, and glial and endothelial cell markers. Expression of these markers was compared to brain tissue from uninfected animals of comparable age, allowing the examination of the contribution of these cells to the neuroinflammatory response following SARS-CoV-2 infection. RESULTS TSPO PET revealed an increased tracer uptake throughout the brain of all infected animals already from the first scan obtained post-infection (day 2), which increased to approximately twofold until day 30 pi. Postmortem immunohistochemical analysis of the hippocampus and pons showed TSPO expression in cells expressing ionized calcium-binding adaptor molecule 1 (IBA1), glial fibrillary acidic protein (GFAP), and collagen IV. In the hippocampus of SARS-CoV-2 infected animals the TSPO+ area and number of TSPO+ cells were significantly increased compared to control animals. This increase was not cell type specific, since both the number of IBA1+TSPO+ and GFAP+TSPO+ cells was increased, as well as the TSPO+ area within collagen IV+ blood vessels. CONCLUSIONS This study manifests [18F]DPA714 as a powerful radiotracer to visualize SARS-CoV-2 induced neuroinflammation. The increased uptake of [18F]DPA714 over time implies an active neuroinflammatory response following SARS-CoV-2 infection. This inflammatory signal coincides with an increased number of TSPO expressing cells, including glial and endothelial cells, suggesting neuroinflammation and vascular dysregulation. These results demonstrate the long-term neuroinflammatory response following a mild SARS-CoV-2 infection, which potentially precedes long-lasting neurological symptoms.
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Affiliation(s)
- Juliana M Nieuwland
- Department of Neurobiology and Aging, Biomedical Primate Research Centre (BPRC), Lange Kleiweg 161, 2288GJ, Rijswijk, The Netherlands
| | - Erik Nutma
- Department of Neurobiology and Aging, Biomedical Primate Research Centre (BPRC), Lange Kleiweg 161, 2288GJ, Rijswijk, The Netherlands
| | - Ingrid H C H M Philippens
- Department of Neurobiology and Aging, Biomedical Primate Research Centre (BPRC), Lange Kleiweg 161, 2288GJ, Rijswijk, The Netherlands
| | - Kinga P Böszörményi
- Department of Virology, Biomedical Primate Research Centre (BPRC), Rijswijk, The Netherlands
| | - Edmond J Remarque
- Department of Virology, Biomedical Primate Research Centre (BPRC), Rijswijk, The Netherlands
| | - Jaco Bakker
- Department of Radiology, Biomedical Primate Research Centre (BPRC), Rijswijk, The Netherlands
| | - Lisette Meijer
- Department of Radiology, Biomedical Primate Research Centre (BPRC), Rijswijk, The Netherlands
| | - Noor Woerdman
- Department of Radiology, Biomedical Primate Research Centre (BPRC), Rijswijk, The Netherlands
| | - Zahra C Fagrouch
- Department of Virology, Biomedical Primate Research Centre (BPRC), Rijswijk, The Netherlands
| | - Babs E Verstrepen
- Department of Virology, Biomedical Primate Research Centre (BPRC), Rijswijk, The Netherlands
| | - Jan A M Langermans
- Department of Animal Sciences, Biomedical Primate Research Centre (BPRC), Rijswijk, The Netherlands
- Department Population Health Sciences, Unit Animals in Science and Society, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Ernst J Verschoor
- Department of Virology, Biomedical Primate Research Centre (BPRC), Rijswijk, The Netherlands
| | - Albert D Windhorst
- Department of Radiology and Nuclear Medicine, Tracer Center Amsterdam (TCA), Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Ronald E Bontrop
- Department of Comparative Genetics and Refinement, Biomedical Primate Research Centre (BPRC), Rijswijk, The Netherlands
- Department of Biology, Theoretical Biology and Bioinformatics, Utrecht University, Utrecht, The Netherlands
| | - Helga E de Vries
- Department of Molecular Cell Biology and Immunology, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Marieke A Stammes
- Department of Radiology, Biomedical Primate Research Centre (BPRC), Rijswijk, The Netherlands
| | - Jinte Middeldorp
- Department of Neurobiology and Aging, Biomedical Primate Research Centre (BPRC), Lange Kleiweg 161, 2288GJ, Rijswijk, The Netherlands.
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Giacometti C, Amiez C, Hadj-Bouziane F. Multiple routes of communication within the amygdala-mPFC network: A comparative approach in humans and macaques. CURRENT RESEARCH IN NEUROBIOLOGY 2023; 5:100103. [PMID: 37601951 PMCID: PMC10432920 DOI: 10.1016/j.crneur.2023.100103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 06/14/2023] [Accepted: 07/15/2023] [Indexed: 08/22/2023] Open
Abstract
The network formed by the amygdala (AMG) and the medial Prefrontal Cortex (mPFC), at the interface between our internal and external environment, has been shown to support some important aspects of behavioral adaptation. Whether and how the anatomo-functional organization of this network evolved across primates remains unclear. Here, we compared AMG nuclei morphological characteristics and their functional connectivity with the mPFC in humans and macaques to identify potential homologies and differences between these species. Based on selected studies, we highlight two subsystems within the AMG-mPFC circuits, likely involved in distinct temporal dynamics of integration during behavioral adaptation. We also show that whereas the mPFC displays a large expansion but a preserved intrinsic anatomo-functional organization, the AMG displays a volume reduction and morphological changes related to specific nuclei. We discuss potential commonalities and differences in the dialogue between AMG nuclei and mPFC in humans and macaques based on available data.
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Affiliation(s)
- C. Giacometti
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500, Bron, France
| | - C. Amiez
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500, Bron, France
| | - F. Hadj-Bouziane
- Integrative Multisensory Perception Action & Cognition Team (ImpAct), INSERM U1028, CNRS UMR5292, Lyon Neuroscience Research Center (CRNL), University of Lyon 1, Lyon, France
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Zeisler ZR, London L, Janssen WG, Fredericks JM, Elorette C, Fujimoto A, Zhan H, Russ BE, Clem RL, Hof PR, Stoll FM, Rudebeck PH. High-throughput sequencing of macaque basolateral amygdala projections reveals dissociable connectional motifs with frontal cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.18.524407. [PMID: 36711708 PMCID: PMC9882200 DOI: 10.1101/2023.01.18.524407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
The basolateral amygdala (BLA) projects widely across the macaque frontal cortex1-4, and amygdalo-frontal projections are critical for optimal emotional responding5 and decision-making6. Yet, little is known about the single-neuron architecture of these projections: namely, whether single BLA neurons project to multiple parts of the frontal cortex. Here, we use MAPseq7 to determine the projection patterns of over 3000 macaque BLA neurons. We found that one-third of BLA neurons have two or more distinct targets in parts of frontal cortex and of subcortical structures. Further, we reveal non-random structure within these branching patterns such that neurons with four targets are more frequently observed than those with two or three, indicative of widespread networks. Consequently, these multi-target single neurons form distinct networks within medial and ventral frontal cortex consistent with their known functions in regulating mood and decision-making. Additionally, we show that branching patterns of single neurons shape functional networks in the brain as assessed by fMRI-based functional connectivity. These results provide a neuroanatomical basis for the role of the BLA in coordinating brain-wide responses to valent stimuli8 and highlight the importance of high-resolution neuroanatomical data for understanding functional networks in the brain.
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Affiliation(s)
- Zachary R Zeisler
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
| | - Liza London
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
| | - William G Janssen
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
- Microscopy and Advanced Bioimaging CoRE, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
| | - J Megan Fredericks
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
| | - Catherine Elorette
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
| | - Atsushi Fujimoto
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
| | - Huiqing Zhan
- Cold Spring Harbor Laboratory, 1 Bungtown Rd, Syosset, NY 11791
| | - Brian E Russ
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, 140 Old Orangeburg Road, 10 Orangeburg, NY 10962
- Department of Psychiatry, New York University at Langone, One, 8 Park Ave, New York, NY 10016
| | - Roger L Clem
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
| | - Patrick R Hof
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
| | - Frederic M Stoll
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
| | - Peter H Rudebeck
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029
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A multimodal imaging-guided software for access to primate brains. Heliyon 2023; 9:e12675. [PMID: 36685404 PMCID: PMC9852658 DOI: 10.1016/j.heliyon.2022.e12675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 11/15/2022] [Accepted: 12/19/2022] [Indexed: 01/06/2023] Open
Abstract
Background Imaging-guided access to the brain has become a routine procedure for various research and clinical applications, including drug administration, neurophysiological recording, and sampling tissue. Therefore, open-source software is required to handle such datasets in these specific applications. New methods Here, we proposed an open-source tool utilizing different imaging modalities for automating the steps to access the brain. This tool provides means for easily calculating the coordination of the area of interest concerning a specific point of entry. The source and documentation are available at this link. Results We have used this software for three different applications: electrophysiological recording, drug infusion in the nonhuman primate brain, and guided biopsy procedure in the human brain. We performed a neural recording of two monkeys' prefrontal cortex and inferior temporal cortex using this software in submillimeter resolution. We also applied our procedure for infusion in the putamen and caudate nuclei in both hemispheres of another group of rhesus monkeys with histological proof in one animal. More so, we validated this software in the human subjects that underwent biopsy surgery with the commercial software used in human biopsy surgery. Comparison with existing methods Our software uses different imaging modalities by co-registering them. This will provide structural details of the skull and brain tissue. We can calculate each brain region's coordination at the point of entry by re-slicing the images. Atlas-based image segmentation were implemented in our software. Three mentioned applications of our software in neuroscience will be further discussed in this paper. Conclusion In our procedure, working with different imaging modalities provides a precise estimation of the specific region in the brain related to the location of implants or stereotaxic frames. There is no limitation to using metal implants in this procedure.
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Cushnie AK, Bullock DN, Manea AM, Tang W, Zimmermann J, Heilbronner SR. The use of chemogenetic actuator ligands in nonhuman primate DREADDs-fMRI. CURRENT RESEARCH IN NEUROBIOLOGY 2022; 4:100072. [PMID: 36691404 PMCID: PMC9860110 DOI: 10.1016/j.crneur.2022.100072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 12/01/2022] [Accepted: 12/26/2022] [Indexed: 12/31/2022] Open
Abstract
Designer Receptors Exclusively Activated by Designer Drugs (DREADDs) are engineered receptors that allow for genetically targeted, reversible manipulation of cellular activity via systemic drug administration. DREADD induced manipulations are initiated via the binding of an actuator ligand. Therefore, the use of DREADDs is contingent on the availability of actuator ligands. Actuator ligands low-dose clozapine (CLZ) and deschloroclozapine (DCZ) are highly selective for DREADDs, and, upon binding, induce physiological and behavioral changes in rodents and nonhuman primates (NHPs). Despite this reported specificity, both CLZ and DCZ have partial affinity for a variety of endogenous receptors and can induce dose-specific changes even in naïve animals. As such, this study aimed to examine the effects of CLZ and DCZ on resting-state functional connectivity (rs-FC) and intrinsic neural timescales (INTs) in naïve NHPs. In doing so, we evaluated whether CLZ and DCZ - in the absence of DREADDs - are inert by examining these ligands' effects on the intrinsic functional properties of the brain. Low-dose DCZ did not induce consistent changes in rs-FC or INTs prior to the expression of DREADDs; however, a high dose resulted in subject-specific changes in rs-FC and INTs. In contrast, CLZ administration induced consistent changes in rs-FC and INTs prior to DREADD expression in our subjects. Our results caution against the use of CLZ by explicitly demonstrating the impact of off-target effects that can confound experimental results. Altogether, these data endorse the use of low dose DCZ for future DREADD-based experiments.
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Affiliation(s)
- Adriana K. Cushnie
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Daniel N. Bullock
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Ana M.G. Manea
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Wei Tang
- Department of Computer Science, Program in Neuroscience, Indiana University Bloomington, Bloomington, IN, 47408, USA
| | - Jan Zimmermann
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, 55455, USA
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Sarah R. Heilbronner
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, 55455, USA
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Dadarwal R, Ortiz-Rios M, Boretius S. Fusion of quantitative susceptibility maps and T1-weighted images improve brain tissue contrast in primates. Neuroimage 2022; 264:119730. [PMID: 36332851 DOI: 10.1016/j.neuroimage.2022.119730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 10/12/2022] [Accepted: 11/01/2022] [Indexed: 11/06/2022] Open
Abstract
Recent progress in quantitative susceptibility mapping (QSM) has enabled the accurate delineation of submillimeter-scale subcortical brain structures in humans. However, the simultaneous visualization of cortical, subcortical, and white matter structure remains challenging, utilizing QSM data solely. Here we present TQ-SILiCON, a fusion method that enhances the contrast of cortex and subcortical structures and provides an excellent white matter delineation by combining QSM and conventional T1-weighted (T1w) images. In this study, we first applied QSM in the macaque monkey to map iron-rich subcortical structures. Implementing the same QSM acquisition and analysis methods allowed a similar accurate delineation of subcortical structures in humans. However, the QSM contrast of white and cortical gray matter was not sufficient for appropriate segmentation. Applying automatic brain tissue segmentation to TQ-SILiCON images of the macaque improved the classification of subcortical brain structures as compared to the single T1 contrast by maintaining an excellent white to cortical gray matter contrast. Furthermore, we validated our dual-contrast fusion approach in humans and similarly demonstrated improvements in automated segmentation of the cortex and subcortical structures. We believe the proposed contrast will facilitate translational studies in nonhuman primates to investigate the pathophysiology of neurodegenerative diseases that affect subcortical structures such as the basal ganglia in humans.
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Affiliation(s)
- Rakshit Dadarwal
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany; Georg-August University of Göttingen, Göttingen, Germany.
| | - Michael Ortiz-Rios
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany; Leibniz Science Campus Primate Cognition, Göttingen, Germany
| | - Susann Boretius
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany; Georg-August University of Göttingen, Göttingen, Germany; Leibniz Science Campus Primate Cognition, Göttingen, Germany
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Taubert J, Japee S, Patterson A, Wild H, Goyal S, Yu D, Ungerleider LG. A broadly tuned network for affective body language in the macaque brain. SCIENCE ADVANCES 2022; 8:eadd6865. [PMID: 36427322 PMCID: PMC9699662 DOI: 10.1126/sciadv.add6865] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 10/27/2022] [Indexed: 06/16/2023]
Abstract
Body language is a powerful tool that we use to communicate how we feel, but it is unclear whether other primates also communicate in this way. Here, we use functional magnetic resonance imaging to show that the body-selective patches in macaques are activated by affective body language. Unexpectedly, we found these regions to be tolerant of naturalistic variation in posture as well as species; the bodies of macaques, humans, and domestic cats all evoked a stronger response when they conveyed fear than when they conveyed no affect. Multivariate analyses confirmed that the neural representation of fear-related body expressions was species-invariant. Collectively, these findings demonstrate that, like humans, macaques have body-selective brain regions in the ventral visual pathway for processing affective body language. These data also indicate that representations of body stimuli in these regions are built on the basis of emergent properties, such as socio-affective meaning, and not just putative image properties.
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Affiliation(s)
- Jessica Taubert
- Section on Neurocircuitry, Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD 20892, USA
- School of Psychology, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Shruti Japee
- Section on Neurocircuitry, Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Amanda Patterson
- Section on Neurocircuitry, Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Hannah Wild
- Section on Neurocircuitry, Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Shivani Goyal
- Section on Neurocircuitry, Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - David Yu
- Section on Neurocircuitry, Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Leslie G. Ungerleider
- Section on Neurocircuitry, Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD 20892, USA
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Yu H, Zhang C, Cai Y, Wu N, Duan K, Bo W, Liu Y, Xu Z. Abnormal regional homogeneity and amplitude of low frequency fluctuation in chronic kidney patients with and without dialysis. Front Neurosci 2022; 16. [PMID: 36483180 PMCID: PMC9723135 DOI: 10.3389/fnins.2022.1064813] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2023] Open
Abstract
PurposeThe study characterizes regional homogeneity (ReHo) and amplitude of low frequency fluctuations (ALFF) in abnormal regions of brain in patients of chronic kidney disease (CKD).Materials and methodsA total of 64 patients of CKD were divided into 26 cases of non-dialysis-dependent chronic kidney disease (NDD-CKD), and 38 cases of dialysis-dependent chronic kidney disease (DD-CKD). A total of 43 healthy controls (normal control, NC) were also included. All subjects underwent resting-state functional magnetic resonance imaging (rs-fMRI). ALFF and ReHo data was processed for monitoring the differences in spontaneous brain activity between the three groups. ALFF and ReHo values of extracted differential brain regions were correlated to the clinical data and cognitive scores of CKD patients.ResultsNon-dialysis-dependent group has increased ALFF levels in 13 brain regions while that of DD group in 28 brain regions as compared with NC group. ReHo values are altered in six brain regions of DD group. ALFF is correlated with urea nitrogen and ReHo with urea nitrogen and creatinine. DD group has altered ReHo in two brain regions compared with NDD group. The differences are located in basal ganglia, cerebellar, and hippocampus regions.ConclusionAbnormal activity in basal ganglia, cerebellar, and hippocampal regions may be involved in the cognitive decline of CKD patients. This link can provide theoretical basis for understanding the cognitive decline.
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Goda N, Hasegawa T, Koketsu D, Chiken S, Kikuta S, Sano H, Kobayashi K, Nambu A, Sadato N, Fukunaga M. Cerebro-cerebellar interactions in nonhuman primates examined by optogenetic functional magnetic resonance imaging. Cereb Cortex Commun 2022; 3:tgac022. [PMID: 35769971 PMCID: PMC9233902 DOI: 10.1093/texcom/tgac022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 05/19/2022] [Accepted: 05/19/2022] [Indexed: 11/14/2022] Open
Abstract
Functional magnetic resonance imaging (fMRI) is a promising approach for the simultaneous and extensive scanning of whole-brain activities. Optogenetics is free from electrical and magnetic artifacts and is an ideal stimulation method for combined use with fMRI. However, the application of optogenetics in nonhuman primates (NHPs) remains limited. Recently, we developed an efficient optogenetic intracortical microstimulation method of the primary motor cortex (M1), which successfully induced forelimb movements in macaque monkeys. Here, we aimed to investigate how optogenetic M1 stimulation causes neural modulation in the local and remote brain regions in anesthetized monkeys using 7-tesla fMRI. We demonstrated that optogenetic stimulation of the M1 forelimb and hindlimb regions successfully evoked robust direct and remote fMRI activities. Prominent remote activities were detected in the anterior and posterior lobes in the contralateral cerebellum, which receive projections polysynaptically from the M1. We further demonstrated that the cerebro-cerebellar projections from these M1 regions were topographically organized, which is concordant with the somatotopic map in the cerebellar cortex previously reported in macaques and humans. The present study significantly enhances optogenetic fMRI in NHPs, resulting in profound understanding of the brain network, thereby accelerating the translation of findings from animal models to humans.
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Affiliation(s)
- Naokazu Goda
- Division of Cerebral Integration, National Institute for Physiological Sciences, 38 Nishigonaka, Myodaiji, Okazaki, Aichi 444-8585, Japan
- Department of Physiological Sciences, SOKENDAI (The Graduate University for Advanced Studies), 38 Nishigonaka, Myodaiji, Okazaki, Aichi 444-8585, Japan
| | - Taku Hasegawa
- Division of System Neurophysiology, National Institute for Physiological Sciences, 38 Nishigonaka, Myodaiji, Okazaki, Aichi 444-8585, Japan
- Laboratory for Imagination and Executive Functions, RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
| | - Daisuke Koketsu
- Division of System Neurophysiology, National Institute for Physiological Sciences, 38 Nishigonaka, Myodaiji, Okazaki, Aichi 444-8585, Japan
| | - Satomi Chiken
- Department of Physiological Sciences, SOKENDAI (The Graduate University for Advanced Studies), 38 Nishigonaka, Myodaiji, Okazaki, Aichi 444-8585, Japan
- Division of System Neurophysiology, National Institute for Physiological Sciences, 38 Nishigonaka, Myodaiji, Okazaki, Aichi 444-8585, Japan
| | - Satomi Kikuta
- Division of System Neurophysiology, National Institute for Physiological Sciences, 38 Nishigonaka, Myodaiji, Okazaki, Aichi 444-8585, Japan
- Department of Neurophysiology, National Institute of Neuroscience, National Center of Neurology and Psychiatry, 4-1-1 Ogawa-Higashi, Kodaira, Tokyo 187-8502, Japan
| | - Hiromi Sano
- Department of Physiological Sciences, SOKENDAI (The Graduate University for Advanced Studies), 38 Nishigonaka, Myodaiji, Okazaki, Aichi 444-8585, Japan
- Division of System Neurophysiology, National Institute for Physiological Sciences, 38 Nishigonaka, Myodaiji, Okazaki, Aichi 444-8585, Japan
- Division of Behavioral Neuropharmacology, International Center for Brain Science, Fujita Health University, 1-98 Dengakugakubo, Kutsukake, Toyoake, Aichi 470-1192, Japan
| | - Kenta Kobayashi
- Department of Physiological Sciences, SOKENDAI (The Graduate University for Advanced Studies), 38 Nishigonaka, Myodaiji, Okazaki, Aichi 444-8585, Japan
- Section of Viral Vector Development, National Institute for Physiological Sciences, 38 Nishigonaka, Myodaiji, Okazaki, Aichi 444-8585, Japan
| | - Atsushi Nambu
- Department of Physiological Sciences, SOKENDAI (The Graduate University for Advanced Studies), 38 Nishigonaka, Myodaiji, Okazaki, Aichi 444-8585, Japan
- Division of System Neurophysiology, National Institute for Physiological Sciences, 38 Nishigonaka, Myodaiji, Okazaki, Aichi 444-8585, Japan
- Section of Viral Vector Development, National Institute for Physiological Sciences, 38 Nishigonaka, Myodaiji, Okazaki, Aichi 444-8585, Japan
| | - Norihiro Sadato
- Division of Cerebral Integration, National Institute for Physiological Sciences, 38 Nishigonaka, Myodaiji, Okazaki, Aichi 444-8585, Japan
- Department of Physiological Sciences, SOKENDAI (The Graduate University for Advanced Studies), 38 Nishigonaka, Myodaiji, Okazaki, Aichi 444-8585, Japan
| | - Masaki Fukunaga
- Division of Cerebral Integration, National Institute for Physiological Sciences, 38 Nishigonaka, Myodaiji, Okazaki, Aichi 444-8585, Japan
- Department of Physiological Sciences, SOKENDAI (The Graduate University for Advanced Studies), 38 Nishigonaka, Myodaiji, Okazaki, Aichi 444-8585, Japan
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Sirmpilatze N, Mylius J, Ortiz-Rios M, Baudewig J, Paasonen J, Golkowski D, Ranft A, Ilg R, Gröhn O, Boretius S. Spatial signatures of anesthesia-induced burst-suppression differ between primates and rodents. eLife 2022; 11:e74813. [PMID: 35607889 PMCID: PMC9129882 DOI: 10.7554/elife.74813] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 05/01/2022] [Indexed: 01/19/2023] Open
Abstract
During deep anesthesia, the electroencephalographic (EEG) signal of the brain alternates between bursts of activity and periods of relative silence (suppressions). The origin of burst-suppression and its distribution across the brain remain matters of debate. In this work, we used functional magnetic resonance imaging (fMRI) to map the brain areas involved in anesthesia-induced burst-suppression across four mammalian species: humans, long-tailed macaques, common marmosets, and rats. At first, we determined the fMRI signatures of burst-suppression in human EEG-fMRI data. Applying this method to animal fMRI datasets, we found distinct burst-suppression signatures in all species. The burst-suppression maps revealed a marked inter-species difference: in rats, the entire neocortex engaged in burst-suppression, while in primates most sensory areas were excluded-predominantly the primary visual cortex. We anticipate that the identified species-specific fMRI signatures and whole-brain maps will guide future targeted studies investigating the cellular and molecular mechanisms of burst-suppression in unconscious states.
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Affiliation(s)
- Nikoloz Sirmpilatze
- Functional Imaging Laboratory, German Primate Center – Leibniz Institute for Primate ResearchGöttingenGermany
- Georg-August University of GöttingenGöttingenGermany
- International Max Planck Research School for NeurosciencesGöttingenGermany
| | - Judith Mylius
- Functional Imaging Laboratory, German Primate Center – Leibniz Institute for Primate ResearchGöttingenGermany
| | - Michael Ortiz-Rios
- Functional Imaging Laboratory, German Primate Center – Leibniz Institute for Primate ResearchGöttingenGermany
| | - Jürgen Baudewig
- Functional Imaging Laboratory, German Primate Center – Leibniz Institute for Primate ResearchGöttingenGermany
| | - Jaakko Paasonen
- A.I.V. Institute for Molecular Sciences, University of Eastern FinlandKuopioFinland
| | - Daniel Golkowski
- Department of Neurology, Klinikum Rechts der Isar der Technischen Universität MünchenMunichGermany
- Department of Neurology, Heidelberg University HospitalHeidelbergGermany
| | - Andreas Ranft
- Department of Anesthesiology and Intensive Care Medicine, Klinikum Rechts der Isar der Technischen Universität MünchenMunichGermany
| | - Rüdiger Ilg
- Department of Neurology, Klinikum Rechts der Isar der Technischen Universität MünchenMunichGermany
- Department of Neurology, Asklepios Stadtklinik Bad TölzBad TölzGermany
| | - Olli Gröhn
- A.I.V. Institute for Molecular Sciences, University of Eastern FinlandKuopioFinland
| | - Susann Boretius
- Functional Imaging Laboratory, German Primate Center – Leibniz Institute for Primate ResearchGöttingenGermany
- Georg-August University of GöttingenGöttingenGermany
- International Max Planck Research School for NeurosciencesGöttingenGermany
- Leibniz Science Campus Primate CognitionGöttingenGermany
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Manea AMG, Zilverstand A, Ugurbil K, Heilbronner SR, Zimmermann J. Intrinsic timescales as an organizational principle of neural processing across the whole rhesus macaque brain. eLife 2022; 11:e75540. [PMID: 35234612 PMCID: PMC8923667 DOI: 10.7554/elife.75540] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2021] [Accepted: 02/28/2022] [Indexed: 11/13/2022] Open
Abstract
Hierarchical temporal dynamics are a fundamental computational property of the brain; however, there are no whole brain, noninvasive investigations into timescales of neural processing in animal models. To that end, we used the spatial resolution and sensitivity of ultrahigh field functional magnetic resonance imaging (fMRI) performed at 10.5 T to probe timescales across the whole macaque brain. We uncovered within-species consistency between timescales estimated from fMRI and electrophysiology. Crucially, we extended existing electrophysiological hierarchies to whole-brain topographies. Our results validate the complementary use of hemodynamic and electrophysiological intrinsic timescales, establishing a basis for future translational work. Further, with these results in hand, we were able to show that one facet of the high-dimensional functional connectivity (FC) topography of any region in the brain is closely related to hierarchical temporal dynamics. We demonstrated that intrinsic timescales are organized along spatial gradients that closely match FC gradient topographies across the whole brain. We conclude that intrinsic timescales are a unifying organizational principle of neural processing across the whole brain.
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Affiliation(s)
- Ana MG Manea
- Department of Neuroscience, University of MinnesotaMinneapolisUnited States
- Center for Magnetic Resonance Research, University of MinnesotaMinneapolisUnited States
| | - Anna Zilverstand
- Department of Psychiatry & Behavioral Sciences , University of MinnesotaMinneapolisUnited States
- Medical Discovery Team on Addiction, University of MinnesotaMinneapolisUnited States
| | - Kamil Ugurbil
- Center for Magnetic Resonance Research, University of MinnesotaMinneapolisUnited States
- Center for Neuroengineering, University of MinnesotaMinneapolisUnited States
- Department of Radiology, University of MinnesotaMinneapolisUnited States
| | - Sarah R Heilbronner
- Department of Neuroscience, University of MinnesotaMinneapolisUnited States
- Medical Discovery Team on Addiction, University of MinnesotaMinneapolisUnited States
- Center for Neuroengineering, University of MinnesotaMinneapolisUnited States
| | - Jan Zimmermann
- Department of Neuroscience, University of MinnesotaMinneapolisUnited States
- Center for Magnetic Resonance Research, University of MinnesotaMinneapolisUnited States
- Medical Discovery Team on Addiction, University of MinnesotaMinneapolisUnited States
- Center for Neuroengineering, University of MinnesotaMinneapolisUnited States
- Department of Biomedical Engineering, University of MinnesotaMinneapolisUnited States
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Ose T, Autio JA, Ohno M, Frey S, Uematsu A, Kawasaki A, Takeda C, Hori Y, Nishigori K, Nakako T, Yokoyama C, Nagata H, Yamamori T, Van Essen DC, Glasser MF, Watabe H, Hayashi T. Anatomical variability, multi-modal coordinate systems, and precision targeting in the marmoset brain. Neuroimage 2022; 250:118965. [PMID: 35122965 PMCID: PMC8948178 DOI: 10.1016/j.neuroimage.2022.118965] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Revised: 01/31/2022] [Accepted: 02/01/2022] [Indexed: 01/02/2023] Open
Abstract
Localising accurate brain regions needs careful evaluation in each experimental species due to their individual variability. However, the function and connectivity of brain areas is commonly studied using a single-subject cranial landmark-based stereotactic atlas in animal neuroscience. Here, we address this issue in a small primate, the common marmoset, which is increasingly widely used in systems neuroscience. We developed a non-invasive multi-modal neuroimaging-based targeting pipeline, which accounts for intersubject anatomical variability in cranial and cortical landmarks in marmosets. This methodology allowed creation of multi-modal templates (MarmosetRIKEN20) including head CT and brain MR images, embedded in coordinate systems of anterior and posterior commissures (AC-PC) and CIFTI grayordinates. We found that the horizontal plane of the stereotactic coordinate was significantly rotated in pitch relative to the AC-PC coordinate system (10 degrees, frontal downwards), and had a significant bias and uncertainty due to positioning procedures. We also found that many common cranial and brain landmarks (e.g., bregma, intraparietal sulcus) vary in location across subjects and are substantial relative to average marmoset cortical area dimensions. Combining the neuroimaging-based targeting pipeline with robot-guided surgery enabled proof-of-concept targeting of deep brain structures with an accuracy of 0.2 mm. Altogether, our findings demonstrate substantial intersubject variability in marmoset brain and cranial landmarks, implying that subject-specific neuroimaging-based localization is needed for precision targeting in marmosets. The population-based templates and atlases in grayordinates, created for the first time in marmoset monkeys, should help bridging between macroscale and microscale analyses.
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Affiliation(s)
- Takayuki Ose
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan; Graduate School of Biomedical Engineering, Tohoku University, Sendai, Japan.
| | - Joonas A Autio
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan.
| | - Masahiro Ohno
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan.
| | | | - Akiko Uematsu
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan.
| | - Akihiro Kawasaki
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan.
| | - Chiho Takeda
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan.
| | - Yuki Hori
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan; Department of Functional Brain Imaging, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan.
| | - Kantaro Nishigori
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan; Sumitomo Dainippon Pharma Co., Ltd., Osaka, Japan.
| | - Tomokazu Nakako
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan; Sumitomo Dainippon Pharma Co., Ltd., Osaka, Japan.
| | - Chihiro Yokoyama
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan; Faculty of Human life and Environmental Science, Nara women's University, Nara, Japan.
| | | | - Tetsuo Yamamori
- Laboratory for Molecular Analysis of Higher Brain Function, RIKEN Center for Brain Science, Wako, Japan.
| | - David C Van Essen
- Department of Neuroscience, Washington University Medical School, St Louis, MO USA.
| | - Matthew F Glasser
- Department of Neuroscience, Washington University Medical School, St Louis, MO USA; Department of Radiology, Washington University Medical School, St Louis, MO USA.
| | - Hiroshi Watabe
- Graduate School of Biomedical Engineering, Tohoku University, Sendai, Japan.
| | - Takuya Hayashi
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan; Department of Brain Connectomics, Kyoto University Graduate School of Medicine, Kyoto, Japan.
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Hartig R, Karimi A, Evrard HC. Interconnected sub-networks of the macaque monkey gustatory connectome. Front Neurosci 2022; 16:818800. [PMID: 36874640 PMCID: PMC9978403 DOI: 10.3389/fnins.2022.818800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2021] [Accepted: 08/24/2022] [Indexed: 02/18/2023] Open
Abstract
Macroscopic taste processing connectivity was investigated using functional magnetic resonance imaging during the presentation of sour, salty, and sweet tastants in anesthetized macaque monkeys. This examination of taste processing affords the opportunity to study the interactions between sensory regions, central integrators, and effector areas. Here, 58 brain regions associated with gustatory processing in primates were aggregated, collectively forming the gustatory connectome. Regional regression coefficients (or β-series) obtained during taste stimulation were correlated to infer functional connectivity. This connectivity was then evaluated by assessing its laterality, modularity and centrality. Our results indicate significant correlations between same region pairs across hemispheres in a bilaterally interconnected scheme for taste processing throughout the gustatory connectome. Using unbiased community detection, three bilateral sub-networks were detected within the graph of the connectome. This analysis revealed clustering of 16 medial cortical structures, 24 lateral structures, and 18 subcortical structures. Across the three sub-networks, a similar pattern was observed in the differential processing of taste qualities. In all cases, the amplitude of the response was greatest for sweet, but the network connectivity was strongest for sour and salty tastants. The importance of each region in taste processing was computed using node centrality measures within the connectome graph, showing centrality to be correlated across hemispheres and, to a smaller extent, region volume. Connectome hubs exhibited varying degrees of centrality with a prominent leftward increase in insular cortex centrality. Taken together, these criteria illustrate quantifiable characteristics of the macaque monkey gustatory connectome and its organization as a tri-modular network, which may reflect the general medial-lateral-subcortical organization of salience and interoception processing networks.
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Affiliation(s)
- Renée Hartig
- Max Planck Institute for Biological Cybernetics, Tübingen, Germany.,Functional and Comparative Neuroanatomy Laboratory, Werner Reichardt Centre for Integrative Neuroscience, Eberhard Karl University of Tübingen, Tübingen, Germany.,Department of Psychiatry and Psychotherapy, University Medical Center, Johannes Gutenberg University Mainz, Mainz, Germany.,Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, United States
| | - Ali Karimi
- Department of Connectomics, Max Planck Institute for Brain Research, Frankfurt, Germany
| | - Henry C Evrard
- Max Planck Institute for Biological Cybernetics, Tübingen, Germany.,Functional and Comparative Neuroanatomy Laboratory, Werner Reichardt Centre for Integrative Neuroscience, Eberhard Karl University of Tübingen, Tübingen, Germany.,Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, United States.,International Center for Primate Brain Research, Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China
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36
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Saleem KS, Avram AV, Glen D, Yen CCC, Ye FQ, Komlosh M, Basser PJ. High-resolution mapping and digital atlas of subcortical regions in the macaque monkey based on matched MAP-MRI and histology. Neuroimage 2021; 245:118759. [PMID: 34838750 PMCID: PMC8815330 DOI: 10.1016/j.neuroimage.2021.118759] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 11/21/2021] [Accepted: 11/23/2021] [Indexed: 12/21/2022] Open
Abstract
Subcortical nuclei and other deep brain structures are known to play an important role in the regulation of the central and peripheral nervous systems. It can be difficult to identify and delineate many of these nuclei and their finer subdivisions in conventional MRI due to their small size, buried location, and often subtle contrast compared to neighboring tissue. To address this problem, we applied a multi-modal approach in ex vivo non-human primate (NHP) brain that includes high-resolution mean apparent propagator (MAP)-MRI and five different histological stains imaged with high-resolution microscopy in the brain of the same subject. By registering these high-dimensional MRI data to high-resolution histology data, we can map the location, boundaries, subdivisions, and micro-architectural features of subcortical gray matter regions in the macaque monkey brain. At high spatial resolution, diffusion MRI in general, and MAP-MRI in particular, can distinguish a large number of deep brain structures, including the larger and smaller white matter fiber tracts as well as architectonic features within various nuclei. Correlation with histology from the same brain enables a thorough validation of the structures identified with MAP-MRI. Moreover, anatomical details that are evident in images of MAP-MRI parameters are not visible in conventional T1-weighted images. We also derived subcortical template "SC21" from segmented MRI slices in three-dimensions and registered this volume to a previously published anatomical template with cortical parcellation (Reveley et al., 2017; Saleem and Logothetis, 2012), thereby integrating the 3D segmentation of both cortical and subcortical regions into the same volume. This newly updated three-dimensional D99 digital brain atlas (V2.0) is intended for use as a reference standard for macaque neuroanatomical, functional, and connectional imaging studies, involving both cortical and subcortical targets. The SC21 and D99 digital templates are available as volumes and surfaces in standard NIFTI and GIFTI formats.
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Affiliation(s)
- Kadharbatcha S Saleem
- Center for Neuroscience and Regenerative Medicine (CNRM), Henry M. Jackson Foundation (HJF) for the Advancement of Military Medicine, 6720A Rockledge Drive, Bethesda, MD 20817, United States; Section on Quantitative Imaging and Tissue Sciences (SQITS), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), NIH, Bethesda, MD 20892, United States.
| | - Alexandru V Avram
- Center for Neuroscience and Regenerative Medicine (CNRM), Henry M. Jackson Foundation (HJF) for the Advancement of Military Medicine, 6720A Rockledge Drive, Bethesda, MD 20817, United States; Section on Quantitative Imaging and Tissue Sciences (SQITS), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), NIH, Bethesda, MD 20892, United States
| | - Daniel Glen
- Scientific and Statistical Computing Core, National Institute of Mental Health (NIMH), United States
| | | | - Frank Q Ye
- Neurophysiology Imaging Facility, NIMH and NINDS, NIH, , United States
| | - Michal Komlosh
- Center for Neuroscience and Regenerative Medicine (CNRM), Henry M. Jackson Foundation (HJF) for the Advancement of Military Medicine, 6720A Rockledge Drive, Bethesda, MD 20817, United States; Section on Quantitative Imaging and Tissue Sciences (SQITS), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), NIH, Bethesda, MD 20892, United States
| | - Peter J Basser
- Center for Neuroscience and Regenerative Medicine (CNRM), Henry M. Jackson Foundation (HJF) for the Advancement of Military Medicine, 6720A Rockledge Drive, Bethesda, MD 20817, United States; Section on Quantitative Imaging and Tissue Sciences (SQITS), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), NIH, Bethesda, MD 20892, United States
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Yoshida A, Ye FQ, Yu DK, Leopold DA, Hikosaka O. Visualization of iron-rich subcortical structures in non-human primates in vivo by quantitative susceptibility mapping at 3T MRI. Neuroimage 2021; 241:118429. [PMID: 34311068 PMCID: PMC11479656 DOI: 10.1016/j.neuroimage.2021.118429] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 07/13/2021] [Accepted: 07/22/2021] [Indexed: 02/06/2023] Open
Abstract
Magnetic resonance imaging (MRI) is now an essential tool in the field of neuroscience involving non-human primates (NHP). Structural MRI scanning using T1-weighted (T1w) or T2-weighted (T2w) images provides anatomical information, particularly for experiments involving deep structures such as the basal ganglia and cerebellum. However, for certain subcortical structures, T1w and T2w image contrasts are insufficient for their detection of important anatomical details. To better visualize such structures in the macaque brain, we applied a relatively new method called quantitative susceptibility mapping (QSM), which enhances tissue contrast based on the local tissue magnetic susceptibility. The QSM significantly improved the visualization of important structures, including the ventral pallidum (VP), globus pallidus external and internal segments (GPe and GPi), substantia nigra (SN), subthalamic nucleus (STN) in the basal ganglia and the dentate nucleus (DN) in the cerebellum. We quantified this the contrast enhancement by systematically comparing of contrast-to-noise ratios (CNRs) of QSM images relative to the corresponding T1w and T2w images. In addition, QSM values of some structures were correlated to the age of the macaque subjects. These results identify the QSM method as a straightforward and useful tool for clearly visualizing details of subcortical structures that are invisible with more traditional scanning sequences.
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Affiliation(s)
- Atsushi Yoshida
- Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, United States.
| | - Frank Q Ye
- Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute for Neurological Disorders and Stroke, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, United States
| | - David K Yu
- Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute for Neurological Disorders and Stroke, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, United States
| | - David A Leopold
- Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute for Neurological Disorders and Stroke, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, United States; Laboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, United States
| | - Okihide Hikosaka
- Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, United States
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38
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Jung B, Taylor PA, Seidlitz J, Sponheim C, Perkins P, Ungerleider LG, Glen D, Messinger A. A comprehensive macaque fMRI pipeline and hierarchical atlas. Neuroimage 2021; 235:117997. [PMID: 33789138 PMCID: PMC9272767 DOI: 10.1016/j.neuroimage.2021.117997] [Citation(s) in RCA: 65] [Impact Index Per Article: 21.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Revised: 01/27/2021] [Accepted: 03/23/2021] [Indexed: 12/14/2022] Open
Abstract
Functional neuroimaging research in the non-human primate (NHP) has been advancing at a remarkable rate. The increase in available data establishes a need for robust analysis pipelines designed for NHP neuroimaging and accompanying template spaces to standardize the localization of neuroimaging results. Our group recently developed the NIMH Macaque Template (NMT), a high-resolution population average anatomical template and associated neuroimaging resources, providing researchers with a standard space for macaque neuroimaging . Here, we release NMT v2, which includes both symmetric and asymmetric templates in stereotaxic orientation, with improvements in spatial contrast, processing efficiency, and segmentation. We also introduce the Cortical Hierarchy Atlas of the Rhesus Macaque (CHARM), a hierarchical parcellation of the macaque cerebral cortex with varying degrees of detail. These tools have been integrated into the neuroimaging analysis software AFNI to provide a comprehensive and robust pipeline for fMRI processing, visualization and analysis of NHP data. AFNI's new @animal_warper program can be used to efficiently align anatomical scans to the NMT v2 space, and afni_proc.py integrates these results with full fMRI processing using macaque-specific parameters: from motion correction through regression modeling. Taken together, the NMT v2 and AFNI represent an all-in-one package for macaque functional neuroimaging analysis, as demonstrated with available demos for both task and resting state fMRI.
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Affiliation(s)
- Benjamin Jung
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD, USA; Department of Neuroscience, Brown University, Providence, RI, USA
| | - Paul A Taylor
- Scientific and Statistical Computing Core, National Institute of Mental Health, Bethesda, MD, USA
| | - Jakob Seidlitz
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Caleb Sponheim
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL, USA
| | - Pierce Perkins
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD, USA
| | - Leslie G Ungerleider
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD, USA
| | - Daniel Glen
- Scientific and Statistical Computing Core, National Institute of Mental Health, Bethesda, MD, USA.
| | - Adam Messinger
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD, USA.
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