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Sihn D, Chae S, Kim SP. A method to find temporal structure of neuronal coactivity patterns with across-trial correlations. J Neurosci Methods 2024; 408:110172. [PMID: 38782124 DOI: 10.1016/j.jneumeth.2024.110172] [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: 02/05/2024] [Revised: 05/08/2024] [Accepted: 05/17/2024] [Indexed: 05/25/2024]
Abstract
BACKGROUND The across-trial correlation of neurons' coactivity patterns emerges to be important for information coding, but methods for finding their temporal structures remain largely unexplored. NEW METHOD In the present study, we propose a method to find time clusters in which coactivity patterns of neurons are correlated across trials. We transform the multidimensional neural activity at each timing into a coactivity pattern of binary states, and predict the coactivity patterns at different timings. We devise a method suitable for these coactivity pattern predictions, call general event prediction. Cross-temporal prediction accuracy is then used to estimate across-trial correlations between coactivity patterns at two timings. We extract time clusters from the cross-temporal prediction accuracy by a modified k-means algorithm. RESULTS The feasibility of the proposed method is verified through simulations based on ground truth. We apply the proposed method to a calcium imaging dataset recorded from the motor cortex of mice, and demonstrate time clusters of motor cortical coactivity patterns during a motor task. COMPARISON WITH EXISTING METHODS While the existing cosine similarity method, which does not account for across-trial correlation, shows temporal structures only for contralateral neural responses, the proposed method reveals those for both contralateral and ipsilateral neural responses, demonstrating the effect of across-trial correlations. CONCLUSIONS This study introduces a novel method for measuring the temporal structure of neuronal ensemble activity.
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Affiliation(s)
- Duho Sihn
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, the Republic of Korea
| | - Soyoung Chae
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, the Republic of Korea
| | - Sung-Phil Kim
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, the Republic of Korea.
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2
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Imai F, Matsuura K, Yang E, Klinefelter K, Alexandrou G, Letelier A, Takatani H, Osakada F, Yoshida Y. Layer Va neurons, as major presynaptic partners of corticospinal neurons, play critical roles in skilled movements. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.28.601172. [PMID: 38979259 PMCID: PMC11230360 DOI: 10.1101/2024.06.28.601172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Corticospinal neurons (CSNs) are located in the cortex and projecting into the spinal cord. The activation of CSNs, which is associated with skilled motor behaviors, induces the activation of interneurons in the spinal cord. Eventually, motor neuron activation is induced by corticospinal circuits to coordinate muscle activation. Therefore, elucidating how the activation of CSNs in the brain is regulated is necessary for understanding the roles of CSNs in skilled motor behaviors. However, the presynaptic partners of CSNs in the brain remain to be identified. Here, we performed transsynaptic rabies virus-mediated brain-wide mapping to identify presynaptic partners of CSNs (pre-CSNs). We found that pre-CSNs are located in all cortical layers, but major pre-CSNs are located in layer Va. A small population of pre-CSNs are also located outside the cortex, such as in the thalamus. Inactivation of layer Va neurons in Tlx3-Cre mice results in deficits in skilled reaching and grasping behaviors, suggesting that, similar to CSNs, layer Va neurons are critical for skilled movements. Finally, we examined whether the connectivity of CSNs is altered after spinal cord injury (SCI). We found that unlike connections between CNSs and postsynaptic neurons, connections between pre-CSNs and CSNs do not change after SCI.
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3
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Zhang Z, Su J, Tang J, Chung L, Page JC, Winter CC, Liu Y, Kegeles E, Conti S, Zhang Y, Biundo J, Chalif JI, Hua CY, Yang Z, Yao X, Yang Y, Chen S, Schwab JM, Wang KH, Chen C, Prerau MJ, He Z. Spinal projecting neurons in rostral ventromedial medulla co-regulate motor and sympathetic tone. Cell 2024; 187:3427-3444.e21. [PMID: 38733990 PMCID: PMC11193620 DOI: 10.1016/j.cell.2024.04.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 02/27/2024] [Accepted: 04/17/2024] [Indexed: 05/13/2024]
Abstract
Many behaviors require the coordinated actions of somatic and autonomic functions. However, the underlying mechanisms remain elusive. By opto-stimulating different populations of descending spinal projecting neurons (SPNs) in anesthetized mice, we show that stimulation of excitatory SPNs in the rostral ventromedial medulla (rVMM) resulted in a simultaneous increase in somatomotor and sympathetic activities. Conversely, opto-stimulation of rVMM inhibitory SPNs decreased both activities. Anatomically, these SPNs innervate both sympathetic preganglionic neurons and motor-related regions in the spinal cord. Fiber-photometry recording indicated that the activities of rVMM SPNs correlate with different levels of muscle and sympathetic tone during distinct arousal states. Inhibiting rVMM excitatory SPNs reduced basal muscle and sympathetic tone, impairing locomotion initiation and high-speed performance. In contrast, silencing the inhibitory population abolished muscle atonia and sympathetic hypoactivity during rapid eye movement (REM) sleep. Together, these results identify rVMM SPNs as descending spinal projecting pathways controlling the tone of both the somatomotor and sympathetic systems.
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Affiliation(s)
- Zicong Zhang
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA; Department of Neurology and Ophthalmology, Harvard Medical School, Boston, MA, USA
| | - Junfeng Su
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA; Department of Neurology and Ophthalmology, Harvard Medical School, Boston, MA, USA
| | - Jing Tang
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA; Department of Neurology and Ophthalmology, Harvard Medical School, Boston, MA, USA
| | - Leeyup Chung
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA; Department of Neurology and Ophthalmology, Harvard Medical School, Boston, MA, USA
| | - Jessica C Page
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA; Department of Neurology and Ophthalmology, Harvard Medical School, Boston, MA, USA
| | - Carla C Winter
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA; Department of Neurology and Ophthalmology, Harvard Medical School, Boston, MA, USA; Harvard/MIT MD-PhD Program, Harvard Medical School, Boston, MA, USA
| | - Yuchu Liu
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA; Department of Neurology and Ophthalmology, Harvard Medical School, Boston, MA, USA
| | - Evgenii Kegeles
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA; Department of Neurology and Ophthalmology, Harvard Medical School, Boston, MA, USA; PhD Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA, USA
| | - Sara Conti
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA; Department of Neurology and Ophthalmology, Harvard Medical School, Boston, MA, USA
| | - Yu Zhang
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA; Department of Neurology and Ophthalmology, Harvard Medical School, Boston, MA, USA
| | - Jason Biundo
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA; Department of Neurology and Ophthalmology, Harvard Medical School, Boston, MA, USA
| | - Joshua I Chalif
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA; Department of Neurosurgery, Brigham and Women's Hospital, Boston, MA, USA
| | - Charles Y Hua
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA; Department of Neurology and Ophthalmology, Harvard Medical School, Boston, MA, USA
| | - Zhiyun Yang
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA; Department of Neurology and Ophthalmology, Harvard Medical School, Boston, MA, USA
| | - Xue Yao
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA; Department of Neurology and Ophthalmology, Harvard Medical School, Boston, MA, USA
| | - Yang Yang
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA; Department of Neurology and Ophthalmology, Harvard Medical School, Boston, MA, USA
| | - Shuqiang Chen
- Graduate Program for Neuroscience, Boston University, Boston, MA, USA
| | - Jan M Schwab
- Belford Center for Spinal Cord Injury, The Ohio State University, Columbus, OH, USA; Departments of Neurology and Neuroscience, College of Medicine, The Ohio State University, Columbus, OH, USA
| | - Kuan Hong Wang
- Department of Neuroscience, University of Rochester Medical Center, Rochester, NY, USA
| | - Chinfei Chen
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA; Department of Neurology and Ophthalmology, Harvard Medical School, Boston, MA, USA
| | - Michael J Prerau
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Zhigang He
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA; Department of Neurology and Ophthalmology, Harvard Medical School, Boston, MA, USA.
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4
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Koster KP, Sherman SM. Convergence of inputs from the basal ganglia with layer 5 of motor cortex and cerebellum in mouse motor thalamus. eLife 2024; 13:e97489. [PMID: 38856045 PMCID: PMC11208046 DOI: 10.7554/elife.97489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Accepted: 06/06/2024] [Indexed: 06/11/2024] Open
Abstract
A key to motor control is the motor thalamus, where several inputs converge. One excitatory input originates from layer 5 of primary motor cortex (M1L5), while another arises from the deep cerebellar nuclei (Cb). M1L5 terminals distribute throughout the motor thalamus and overlap with GABAergic inputs from the basal ganglia output nuclei, the internal segment of the globus pallidus (GPi), and substantia nigra pars reticulata (SNr). In contrast, it is thought that Cb and basal ganglia inputs are segregated. Therefore, we hypothesized that one potential function of the GABAergic inputs from basal ganglia is to selectively inhibit, or gate, excitatory signals from M1L5 in the motor thalamus. Here, we tested this possibility and determined the circuit organization of mouse (both sexes) motor thalamus using an optogenetic strategy in acute slices. First, we demonstrated the presence of a feedforward transthalamic pathway from M1L5 through motor thalamus. Importantly, we discovered that GABAergic inputs from the GPi and SNr converge onto single motor thalamic cells with excitatory synapses from M1L5. Separately, we also demonstrate that, perhaps unexpectedly, GABAergic GPi and SNr inputs converge with those from the Cb. We interpret these results to indicate that a role of the basal ganglia is to gate the thalamic transmission of M1L5 and Cb information to cortex.
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Affiliation(s)
- Kevin P Koster
- Department of Neurobiology, University of ChicagoChicagoUnited States
| | - S Murray Sherman
- Department of Neurobiology, University of ChicagoChicagoUnited States
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5
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Liu X, Qi S, Hou L, Liu Y, Wang X. Noninvasive Deep Brain Stimulation via Temporal Interference Electric Fields Enhanced Motor Performance of Mice and Its Neuroplasticity Mechanisms. Mol Neurobiol 2024; 61:3314-3329. [PMID: 37987957 DOI: 10.1007/s12035-023-03721-0] [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: 06/02/2023] [Accepted: 10/17/2023] [Indexed: 11/22/2023]
Abstract
A noninvasive deep brain stimulation via temporal interference (TI) electric fields is a novel neuromodulation technology, but few advances about TI stimulation effectiveness and mechanisms have been reported. One hundred twenty-six mice were selected for the experiment by power analysis. In the present study, TI stimulation was proved to stimulate noninvasively primary motor cortex (M1) of mice, and 7-day TI stimulation with an envelope frequency of 20 Hz (∆f =20 Hz), instead of an envelope frequency of 10 Hz (∆f =10 Hz), could obviously improve mice motor performance. The mechanism of action may be related to enhancing the strength of synaptic connections, improving synaptic transmission efficiency, increasing dendritic spine density, promoting neurotransmitter release, and increasing the expression and activity of synapse-related proteins, such as brain-derived neurotrophic factor (BDNF), postsynaptic density protein-95 (PSD-95), and glutamate receptor protein. Furthermore, the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) signaling pathway and its upstream BDNF play an important role in the enhancement of locomotor performance in mice by TI stimulation. To our knowledge, it is the first report about TI stimulation promoting multiple motor performances and describing its mechanisms. TI stimulation might serve as a novel promising approach to enhance motor performance and treat dysfunction in deep brain regions.
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Affiliation(s)
- Xiaodong Liu
- School of Exercise and Health, Shanghai University of Sport, Shanghai, China
| | - Shuo Qi
- School of Exercise and Health, Shanghai University of Sport, Shanghai, China
| | - Lijuan Hou
- College of Physical Education and Sports, Beijing Normal University, Beijing, China
| | - Yu Liu
- School of Exercise and Health, Shanghai University of Sport, Shanghai, China.
| | - Xiaohui Wang
- School of Exercise and Health, Shanghai University of Sport, Shanghai, China.
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6
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Liu Y, Zhang J, Jiang Z, Qin M, Xu M, Zhang S, Ma G. Organization of corticocortical and thalamocortical top-down inputs in the primary visual cortex. Nat Commun 2024; 15:4495. [PMID: 38802410 PMCID: PMC11130321 DOI: 10.1038/s41467-024-48924-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 05/16/2024] [Indexed: 05/29/2024] Open
Abstract
Unified visual perception requires integration of bottom-up and top-down inputs in the primary visual cortex (V1), yet the organization of top-down inputs in V1 remains unclear. Here, we used optogenetics-assisted circuit mapping to identify how multiple top-down inputs from higher-order cortical and thalamic areas engage V1 excitatory and inhibitory neurons. Top-down inputs overlap in superficial layers yet segregate in deep layers. Inputs from the medial secondary visual cortex (V2M) and anterior cingulate cortex (ACA) converge on L6 Pyrs, whereas ventrolateral orbitofrontal cortex (ORBvl) and lateral posterior thalamic nucleus (LP) inputs are processed in parallel in Pyr-type-specific subnetworks (Pyr←ORBvl and Pyr←LP) and drive mutual inhibition between them via local interneurons. Our study deepens understanding of the top-down modulation mechanisms of visual processing and establishes that V2M and ACA inputs in L6 employ integrated processing distinct from the parallel processing of LP and ORBvl inputs in L5.
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Affiliation(s)
- Yanmei Liu
- Songjiang Hospital and Songjiang Research Institute, Shanghai Key Laboratory of Emotions and Affective Disorders, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
- Department of Anatomy and Physiology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Jiahe Zhang
- Songjiang Hospital and Songjiang Research Institute, Shanghai Key Laboratory of Emotions and Affective Disorders, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
- Department of Anatomy and Physiology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Zhishan Jiang
- Songjiang Hospital and Songjiang Research Institute, Shanghai Key Laboratory of Emotions and Affective Disorders, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
- Department of Anatomy and Physiology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Meiling Qin
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Min Xu
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Siyu Zhang
- Songjiang Hospital and Songjiang Research Institute, Shanghai Key Laboratory of Emotions and Affective Disorders, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China.
- Department of Anatomy and Physiology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Guofen Ma
- Songjiang Hospital and Songjiang Research Institute, Shanghai Key Laboratory of Emotions and Affective Disorders, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China.
- Department of Anatomy and Physiology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
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7
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Li H, Feng J, Chen M, Xin M, Chen X, Liu W, Wang L, Wang KH, He J. Cholecystokinin facilitates motor skill learning by modulating neuroplasticity in the motor cortex. eLife 2024; 13:e83897. [PMID: 38700136 PMCID: PMC11068356 DOI: 10.7554/elife.83897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Accepted: 04/01/2024] [Indexed: 05/05/2024] Open
Abstract
Cholecystokinin (CCK) is an essential modulator for neuroplasticity in sensory and emotional domains. Here, we investigated the role of CCK in motor learning using a single pellet reaching task in mice. Mice with a knockout of Cck gene (Cck-/-) or blockade of CCK-B receptor (CCKBR) showed defective motor learning ability; the success rate of retrieving reward remained at the baseline level compared to the wildtype mice with significantly increased success rate. We observed no long-term potentiation upon high-frequency stimulation in the motor cortex of Cck-/- mice, indicating a possible association between motor learning deficiency and neuroplasticity in the motor cortex. In vivo calcium imaging demonstrated that the deficiency of CCK signaling disrupted the refinement of population neuronal activity in the motor cortex during motor skill training. Anatomical tracing revealed direct projections from CCK-expressing neurons in the rhinal cortex to the motor cortex. Inactivation of the CCK neurons in the rhinal cortex that project to the motor cortex bilaterally using chemogenetic methods significantly suppressed motor learning, and intraperitoneal application of CCK4, a tetrapeptide CCK agonist, rescued the motor learning deficits of Cck-/- mice. In summary, our results suggest that CCK, which could be provided from the rhinal cortex, may surpport motor skill learning by modulating neuroplasticity in the motor cortex.
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Affiliation(s)
- Hao Li
- Departments of Neuroscience and Biomedical Sciences, City University of Hong KongHong KongChina
- Centre for Regenerative Medicine and Health, Hong Kong Institute of Science & Innovation, Chinese Academy of SciencesHong KongChina
| | - Jingyu Feng
- Departments of Neuroscience and Biomedical Sciences, City University of Hong KongHong KongChina
| | - Mengying Chen
- Departments of Neuroscience and Biomedical Sciences, City University of Hong KongHong KongChina
| | - Min Xin
- Departments of Neuroscience and Biomedical Sciences, City University of Hong KongHong KongChina
- Centre for Regenerative Medicine and Health, Hong Kong Institute of Science & Innovation, Chinese Academy of SciencesHong KongChina
| | - Xi Chen
- Departments of Neuroscience and Biomedical Sciences, City University of Hong KongHong KongChina
| | - Wenhao Liu
- Departments of Neuroscience and Biomedical Sciences, City University of Hong KongHong KongChina
| | - Liping Wang
- The Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institutes of Advanced Technology, Chinese Academy of SciencesShenzhenChina
| | - Kuan Hong Wang
- Department of Neuroscience, Del Monte Institute for Neuroscience, University of Rochester Medical CenterRochesterUnited States
| | - Jufang He
- Departments of Neuroscience and Biomedical Sciences, City University of Hong KongHong KongChina
- Centre for Regenerative Medicine and Health, Hong Kong Institute of Science & Innovation, Chinese Academy of SciencesHong KongChina
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8
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Mao X, Staiger JF. Multimodal cortical neuronal cell type classification. Pflugers Arch 2024; 476:721-733. [PMID: 38376567 PMCID: PMC11033238 DOI: 10.1007/s00424-024-02923-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Revised: 02/01/2024] [Accepted: 02/07/2024] [Indexed: 02/21/2024]
Abstract
Since more than a century, neuroscientists have distinguished excitatory (glutamatergic) neurons with long-distance projections from inhibitory (GABAergic) neurons with local projections and established layer-dependent schemes for the ~ 80% excitatory (principal) cells as well as the ~ 20% inhibitory neurons. Whereas, in the early days, mainly morphological criteria were used to define cell types, later supplemented by electrophysiological and neurochemical properties, nowadays. single-cell transcriptomics is the method of choice for cell type classification. Bringing recent insight together, we conclude that despite all established layer- and area-dependent differences, there is a set of reliably identifiable cortical cell types that were named (among others) intratelencephalic (IT), extratelencephalic (ET), and corticothalamic (CT) for the excitatory cells, which altogether comprise ~ 56 transcriptomic cell types (t-types). By the same means, inhibitory neurons were subdivided into parvalbumin (PV), somatostatin (SST), vasoactive intestinal polypeptide (VIP), and "other (i.e. Lamp5/Sncg)" subpopulations, which altogether comprise ~ 60 t-types. The coming years will show which t-types actually translate into "real" cell types that show a common set of multimodal features, including not only transcriptome but also physiology and morphology as well as connectivity and ultimately function. Only with the better knowledge of clear-cut cell types and experimental access to them, we will be able to reveal their specific functions, a task which turned out to be difficult in a part of the brain being so much specialized for cognition as the cerebral cortex.
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Affiliation(s)
- Xiaoyi Mao
- Institute for Neuroanatomy, University Medical Center Göttingen, Georg-August-University, Kreuzbergring 36, 37075, Göttingen, Germany
| | - Jochen F Staiger
- Institute for Neuroanatomy, University Medical Center Göttingen, Georg-August-University, Kreuzbergring 36, 37075, Göttingen, Germany.
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9
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Yang L, Liu F, Hahm H, Okuda T, Li X, Zhang Y, Kalyanaraman V, Heitmeier MR, Samineni VK. Projection-TAGs enable multiplex projection tracing and multi-modal profiling of projection neurons. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.24.590975. [PMID: 38712231 PMCID: PMC11071495 DOI: 10.1101/2024.04.24.590975] [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
Single-cell multiomic techniques have sparked immense interest in developing a comprehensive multi-modal map of diverse neuronal cell types and their brain wide projections. However, investigating the spatial organization, transcriptional and epigenetic landscapes of brain wide projection neurons is hampered by the lack of efficient and easily adoptable tools. Here we introduce Projection-TAGs, a retrograde AAV platform that allows multiplex tagging of projection neurons using RNA barcodes. By using Projection-TAGs, we performed multiplex projection tracing of the mouse cortex and high-throughput single-cell profiling of the transcriptional and epigenetic landscapes of the cortical projection neurons. Projection-TAGs can be leveraged to obtain a snapshot of activity-dependent recruitment of distinct projection neurons and their molecular features in the context of a specific stimulus. Given its flexibility, usability, and compatibility, we envision that Projection-TAGs can be readily applied to build a comprehensive multi-modal map of brain neuronal cell types and their projections.
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Affiliation(s)
- Lite Yang
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
- Neuroscience Graduate Program, Division of Biology & Biomedical Sciences, Washington University School of Medicine, St. Louis, MO, United States
| | - Fang Liu
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
| | - Hannah Hahm
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
| | - Takao Okuda
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
| | - Xiaoyue Li
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
| | - Yufen Zhang
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
| | - Vani Kalyanaraman
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
| | - Monique R. Heitmeier
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
| | - Vijay K. Samineni
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
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10
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Huang J, He B, Yang X, Long X, Wei Y, Li L, Tang M, Gao Y, Fang Y, Ying W, Wang Z, Li C, Zhou Y, Li S, Shi L, Choi S, Zhou H, Guo F, Yang H, Wu J. Generation of rat forebrain tissues in mice. Cell 2024; 187:2129-2142.e17. [PMID: 38670071 DOI: 10.1016/j.cell.2024.03.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 11/14/2023] [Accepted: 03/13/2024] [Indexed: 04/28/2024]
Abstract
Interspecies blastocyst complementation (IBC) provides a unique platform to study development and holds the potential to overcome worldwide organ shortages. Despite recent successes, brain tissue has not been achieved through IBC. Here, we developed an optimized IBC strategy based on C-CRISPR, which facilitated rapid screening of candidate genes and identified that Hesx1 deficiency supported the generation of rat forebrain tissue in mice via IBC. Xenogeneic rat forebrain tissues in adult mice were structurally and functionally intact. Cross-species comparative analyses revealed that rat forebrain tissues developed at the same pace as the mouse host but maintained rat-like transcriptome profiles. The chimeric rate of rat cells gradually decreased as development progressed, suggesting xenogeneic barriers during mid-to-late pre-natal development. Interspecies forebrain complementation opens the door for studying evolutionarily conserved and divergent mechanisms underlying brain development and cognitive function. The C-CRISPR-based IBC strategy holds great potential to broaden the study and application of interspecies organogenesis.
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Affiliation(s)
- Jia Huang
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Research Center for Brain Science and Brain-Inspired Intelligence, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Bingbing He
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Research Center for Brain Science and Brain-Inspired Intelligence, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Xiali Yang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518000, China
| | - Xin Long
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China
| | - Yinghui Wei
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Research Center for Brain Science and Brain-Inspired Intelligence, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Leijie Li
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Min Tang
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Yanxia Gao
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Research Center for Brain Science and Brain-Inspired Intelligence, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yuan Fang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Research Center for Brain Science and Brain-Inspired Intelligence, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Wenqin Ying
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Research Center for Brain Science and Brain-Inspired Intelligence, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Zikang Wang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Research Center for Brain Science and Brain-Inspired Intelligence, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Chao Li
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Research Center for Brain Science and Brain-Inspired Intelligence, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yingsi Zhou
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Research Center for Brain Science and Brain-Inspired Intelligence, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Shuaishuai Li
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Research Center for Brain Science and Brain-Inspired Intelligence, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Linyu Shi
- Huidagene Therapeutics Co., Ltd, Shanghai 200131, China
| | - Seungwon Choi
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Haibo Zhou
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Research Center for Brain Science and Brain-Inspired Intelligence, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
| | - Fan Guo
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China.
| | - Hui Yang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Research Center for Brain Science and Brain-Inspired Intelligence, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
| | - Jun Wu
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; Hamon Center for Regenerative Science and Medicine, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
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11
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Lakshminarasimhan KJ, Xie M, Cohen JD, Sauerbrei BA, Hantman AW, Litwin-Kumar A, Escola S. Specific connectivity optimizes learning in thalamocortical loops. Cell Rep 2024; 43:114059. [PMID: 38602873 PMCID: PMC11104520 DOI: 10.1016/j.celrep.2024.114059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 01/04/2024] [Accepted: 03/20/2024] [Indexed: 04/13/2024] Open
Abstract
Thalamocortical loops have a central role in cognition and motor control, but precisely how they contribute to these processes is unclear. Recent studies showing evidence of plasticity in thalamocortical synapses indicate a role for the thalamus in shaping cortical dynamics through learning. Since signals undergo a compression from the cortex to the thalamus, we hypothesized that the computational role of the thalamus depends critically on the structure of corticothalamic connectivity. To test this, we identified the optimal corticothalamic structure that promotes biologically plausible learning in thalamocortical synapses. We found that corticothalamic projections specialized to communicate an efference copy of the cortical output benefit motor control, while communicating the modes of highest variance is optimal for working memory tasks. We analyzed neural recordings from mice performing grasping and delayed discrimination tasks and found corticothalamic communication consistent with these predictions. These results suggest that the thalamus orchestrates cortical dynamics in a functionally precise manner through structured connectivity.
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Affiliation(s)
| | - Marjorie Xie
- Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA
| | - Jeremy D Cohen
- Neuroscience Center, University of North Carolina, Chapel Hill, NC 27559, USA
| | - Britton A Sauerbrei
- Department of Neurosciences, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Adam W Hantman
- Neuroscience Center, University of North Carolina, Chapel Hill, NC 27559, USA
| | - Ashok Litwin-Kumar
- Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA.
| | - Sean Escola
- Department of Psychiatry, Columbia University, New York, NY 10032, USA.
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12
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Mansuri S, Jain A, Singh R, Rawat S, Mondal D, Raychaudhuri S. Widespread nuclear lamina injuries defeat proteostatic purposes of α-synuclein amyloid inclusions. J Cell Sci 2024; 137:jcs261935. [PMID: 38477372 DOI: 10.1242/jcs.261935] [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: 12/31/2023] [Accepted: 03/03/2024] [Indexed: 03/14/2024] Open
Abstract
Biogenesis of inclusion bodies (IBs) facilitates protein quality control (PQC). Canonical aggresomes execute degradation of misfolded proteins while non-degradable amyloids sequester into insoluble protein deposits. Lewy bodies (LBs) are filamentous amyloid inclusions of α-synuclein, but PQC benefits and drawbacks associated with LB-like IBs remain underexplored. Here, we report that crosstalk between filamentous LB-like IBs and aggresome-like IBs of α-synuclein (Syn-aggresomes) buffer the load, aggregation state, and turnover of the amyloidogenic protein in mouse primary neurons and HEK293T cells. Filamentous LB-like IBs possess unorthodox PQC capacities of self-quarantining α-synuclein amyloids and being degradable upon receding fresh amyloidogenesis. Syn-aggresomes equilibrate biogenesis of filamentous LB-like IBs by facilitating spontaneous degradation of α-synuclein and conditional turnover of disintegrated α-synuclein amyloids. Thus, both types of IB primarily contribute to PQC. Incidentally, the overgrown perinuclear LB-like IBs become degenerative once these are misidentified by BICD2, a cargo-adapter for the cytosolic motor-protein dynein. Microscopy indicates that microtubules surrounding the perinuclear filamentous inclusions are also distorted, misbalancing the cytoskeleton-nucleoskeleton tension leading to widespread lamina injuries. Together, nucleocytoplasmic mixing, DNA damage, and deregulated transcription of stress chaperones defeat the proteostatic purposes of the filamentous amyloids of α-synuclein.
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Affiliation(s)
- Shemin Mansuri
- CSIR-Centre for Cellular and Molecular Biology, Uppal Road, Hyderabad 500007, India
| | - Aanchal Jain
- CSIR-Centre for Cellular and Molecular Biology, Uppal Road, Hyderabad 500007, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Richa Singh
- CSIR-Centre for Cellular and Molecular Biology, Uppal Road, Hyderabad 500007, India
| | - Shivali Rawat
- CSIR-Centre for Cellular and Molecular Biology, Uppal Road, Hyderabad 500007, India
| | - Debodyuti Mondal
- CSIR-Centre for Cellular and Molecular Biology, Uppal Road, Hyderabad 500007, India
| | - Swasti Raychaudhuri
- CSIR-Centre for Cellular and Molecular Biology, Uppal Road, Hyderabad 500007, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
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13
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Hasnain MA, Birnbaum JE, Nunez JLU, Hartman EK, Chandrasekaran C, Economo MN. Separating cognitive and motor processes in the behaving mouse. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.08.23.554474. [PMID: 37662199 PMCID: PMC10473744 DOI: 10.1101/2023.08.23.554474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
The cognitive processes supporting complex animal behavior are closely associated with ubiquitous movements responsible for our posture, facial expressions, ability to actively sample our sensory environments, and other critical processes. These movements are strongly related to neural activity across much of the brain and are often highly correlated with ongoing cognitive processes, making it challenging to dissociate the neural dynamics that support cognitive processes from those supporting related movements. In such cases, a critical issue is whether cognitive processes are separable from related movements, or if they are driven by common neural mechanisms. Here, we demonstrate how the separability of cognitive and motor processes can be assessed, and, when separable, how the neural dynamics associated with each component can be isolated. We establish a novel two-context behavioral task in mice that involves multiple cognitive processes and show that commonly observed dynamics taken to support cognitive processes are strongly contaminated by movements. When cognitive and motor components are isolated using a novel approach for subspace decomposition, we find that they exhibit distinct dynamical trajectories. Further, properly accounting for movement revealed that largely separate populations of cells encode cognitive and motor variables, in contrast to the 'mixed selectivity' often reported. Accurately isolating the dynamics associated with particular cognitive and motor processes will be essential for developing conceptual and computational models of neural circuit function and evaluating the function of the cell types of which neural circuits are composed.
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Affiliation(s)
- Munib A. Hasnain
- Department of Biomedical Engineering, Boston University, Boston, MA
- Center for Neurophotonics, Boston University, Boston, MA
| | - Jaclyn E. Birnbaum
- Graduate Program for Neuroscience, Boston University, Boston, MA
- Center for Neurophotonics, Boston University, Boston, MA
| | | | - Emma K. Hartman
- Department of Biomedical Engineering, Boston University, Boston, MA
| | - Chandramouli Chandrasekaran
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
- Department of Neurobiology & Anatomy, Boston University, Boston, MA
- Center for Systems Neuroscience, Boston University, Boston, MA
| | - Michael N. Economo
- Department of Biomedical Engineering, Boston University, Boston, MA
- Center for Neurophotonics, Boston University, Boston, MA
- Center for Systems Neuroscience, Boston University, Boston, MA
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14
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Qian P, Manubens-Gil L, Jiang S, Peng H. Non-homogenous axonal bouton distribution in whole-brain single-cell neuronal networks. Cell Rep 2024; 43:113871. [PMID: 38451816 DOI: 10.1016/j.celrep.2024.113871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Revised: 01/08/2024] [Accepted: 02/09/2024] [Indexed: 03/09/2024] Open
Abstract
We examined the distribution of pre-synaptic contacts in axons of mouse neurons and constructed whole-brain single-cell neuronal networks using an extensive dataset of 1,891 fully reconstructed neurons. We found that bouton locations were not homogeneous throughout the axon and among brain regions. As our algorithm was able to generate whole-brain single-cell connectivity matrices from full morphology reconstruction datasets, we further found that non-homogeneous bouton locations have a significant impact on network wiring, including degree distribution, triad census, and community structure. By perturbing neuronal morphology, we further explored the link between anatomical details and network topology. In our in silico exploration, we found that dendritic and axonal tree span would have the greatest impact on network wiring, followed by synaptic contact deletion. Our results suggest that neuroanatomical details must be carefully addressed in studies of whole-brain networks at the single-cell level.
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Affiliation(s)
- Penghao Qian
- New Cornerstone Science Laboratory, SEU-ALLEN Joint Center, State Key Laboratory of Digital Medical Engineering, Institute for Brain and Intelligence, Southeast University, Nanjing, Jiangsu 210096, China; School of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu 210096, China
| | - Linus Manubens-Gil
- New Cornerstone Science Laboratory, SEU-ALLEN Joint Center, State Key Laboratory of Digital Medical Engineering, Institute for Brain and Intelligence, Southeast University, Nanjing, Jiangsu 210096, China.
| | - Shengdian Jiang
- New Cornerstone Science Laboratory, SEU-ALLEN Joint Center, State Key Laboratory of Digital Medical Engineering, Institute for Brain and Intelligence, Southeast University, Nanjing, Jiangsu 210096, China; School of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu 210096, China
| | - Hanchuan Peng
- New Cornerstone Science Laboratory, SEU-ALLEN Joint Center, State Key Laboratory of Digital Medical Engineering, Institute for Brain and Intelligence, Southeast University, Nanjing, Jiangsu 210096, China.
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15
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Huang L, Li Q, He D, Cheng Z, Zhang H, Shen W, Zhan L, Zhang J, Hao Z, Ding Q. Modulatory effects of aerobic training on the degree centrality of brain functional activity in subthreshold depression. Brain Res 2024; 1827:148767. [PMID: 38224827 DOI: 10.1016/j.brainres.2024.148767] [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: 10/19/2023] [Revised: 12/07/2023] [Accepted: 01/12/2024] [Indexed: 01/17/2024]
Abstract
BACKGROUND Aerobic training has been shown to effectively prevent the progression of depressive symptoms from subthreshold depression (StD) to major depressive disorder (MDD), and understanding how aerobic training promotes changes in neuroplasticity is essential to comprehending its antidepressant effects. Few studies, however, have quantified the alterations in spontaneous brain activity before and after aerobic training for StD. METHODS Participants included 44 individuals with StD and 34 healthy controls (HCs). Both groups underwent moderate aerobic training for eight weeks, and resting state functional magnetic resonance imaging (rs-fMRI) data were collected before and after training. The degree centrality (DC) changes between the two groups and the DC changes in each group before and after training were quantified. RESULTS The rs-fMRI results showed that compared with the HCs, the DC values of the StD group in the orbital region of the left inferior frontal gyrus significantly depreciated at baseline. After aerobic training, the results of the follow-up examination revealed no significant difference in the DC values between the two groups. In addition, compared with baseline, the StD group exhibited an significant decrease in the DC values of the left dorsolateral superior frontal gyrus; while the HCs group exhibited an significant decrease in the DC values of the left thalamus. No statistically significant connection was seen between changes in DC values and psychological scale scores in the StD group. CONCLUSIONS Our findings suggest that regular aerobic training can enhance brain plasticity in StD. In addition, we demonstrated that DC is a relevant and accessible method for evaluating the functional plasticity of the brain induced by aerobic training in StD.
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Affiliation(s)
- Lina Huang
- Department of Radiology, Changshu Hospital Affiliated to Nantong University, Jiangsu, China
| | - Qin Li
- Department of Radiology, Changshu Hospital Affiliated to Nantong University, Jiangsu, China
| | - Di He
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Zhixiang Cheng
- School of Information Science and Engineering, Dalian Polytechnic University, Dalian 116030, Liaoning, China
| | - Hongqiang Zhang
- Department of Radiology, Changshu Hospital Affiliated to Nantong University, Jiangsu, China
| | - Wenbin Shen
- Department of Radiology, Changshu Hospital Affiliated to Nantong University, Jiangsu, China
| | - Linlin Zhan
- School of Western Studies, Heilongjiang University, Harbin, China
| | - Jun Zhang
- Department of Psychiatry, Changshu Third People's Hospital, Changshu, Jiangsu, China
| | - Zeqi Hao
- School of Psychology, Zhejiang Normal University, Jinhua, China.
| | - Qingguo Ding
- Department of Radiology, Changshu Hospital Affiliated to Nantong University, Jiangsu, China.
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16
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Koster KP, Sherman SM. Convergence of inputs from the basal ganglia with layer 5 of motor cortex and cerebellum in mouse motor thalamus. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.14.584958. [PMID: 38559179 PMCID: PMC10979938 DOI: 10.1101/2024.03.14.584958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
A key to motor control is the motor thalamus, where several inputs converge. One excitatory input originates from layer 5 of primary motor cortex (M1L5), while another arises from the deep cerebellar nuclei (Cb). M1L5 terminals distribute throughout the motor thalamus and overlap with GABAergic inputs from the basal ganglia output nuclei, the internal segment of the globus pallidus (GPi) and substantia nigra pars reticulata (SNr). In contrast, it is thought that Cb and basal ganglia inputs are segregated. Therefore, we hypothesized that one potential function of the GABAergic inputs from basal ganglia is to selectively inhibit, or gate, excitatory signals from M1L5 in the motor thalamus. Here, we tested this possibility and determined the circuit organization of mouse (both sexes) motor thalamus using an optogenetic strategy in acute slices. First, we demonstrated the presence of a feedforward transthalamic pathway from M1L5 through motor thalamus. Importantly, we discovered that GABAergic inputs from the GPi and SNr converge onto single motor thalamic cells with excitatory synapses from M1L5 and, unexpectedly, Cb as well. We interpret these results to indicate that a role of the basal ganglia is to gate the thalamic transmission of M1L5 and Cb information to cortex.
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Affiliation(s)
- Kevin P. Koster
- Department of Neurobiology, University of Chicago, Chicago, IL 60637
| | - S. Murray Sherman
- Department of Neurobiology, University of Chicago, Chicago, IL 60637
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17
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Banerjee A, Chen F, Druckmann S, Long MA. Temporal scaling of motor cortical dynamics reveals hierarchical control of vocal production. Nat Neurosci 2024; 27:527-535. [PMID: 38291282 DOI: 10.1038/s41593-023-01556-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 12/13/2023] [Indexed: 02/01/2024]
Abstract
Neocortical activity is thought to mediate voluntary control over vocal production, but the underlying neural mechanisms remain unclear. In a highly vocal rodent, the male Alston's singing mouse, we investigate neural dynamics in the orofacial motor cortex (OMC), a structure critical for vocal behavior. We first describe neural activity that is modulated by component notes (~100 ms), probably representing sensory feedback. At longer timescales, however, OMC neurons exhibit diverse and often persistent premotor firing patterns that stretch or compress with song duration (~10 s). Using computational modeling, we demonstrate that such temporal scaling, acting through downstream motor production circuits, can enable vocal flexibility. These results provide a framework for studying hierarchical control circuits, a common design principle across many natural and artificial systems.
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Affiliation(s)
- Arkarup Banerjee
- NYU Neuroscience Institute, New York University Langone Health, New York, NY, USA.
- Department of Otolaryngology, New York University Langone Health, New York, NY, USA.
- Center for Neural Science, New York University, New York, NY, USA.
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
| | - Feng Chen
- Department of Applied Physics, Stanford University, Stanford, CA, USA
| | - Shaul Druckmann
- Department of Neurobiology, Stanford University, Stanford, CA, USA
| | - Michael A Long
- NYU Neuroscience Institute, New York University Langone Health, New York, NY, USA.
- Department of Otolaryngology, New York University Langone Health, New York, NY, USA.
- Center for Neural Science, New York University, New York, NY, USA.
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18
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Zhang A, Jin L, Yao S, Matsuyama M, van Velthoven CTJ, Sullivan HA, Sun N, Kellis M, Tasic B, Wickersham I, Chen X. Rabies virus-based barcoded neuroanatomy resolved by single-cell RNA and in situ sequencing. eLife 2024; 12:RP87866. [PMID: 38319699 PMCID: PMC10942611 DOI: 10.7554/elife.87866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2024] Open
Abstract
Mapping the connectivity of diverse neuronal types provides the foundation for understanding the structure and function of neural circuits. High-throughput and low-cost neuroanatomical techniques based on RNA barcode sequencing have the potential to map circuits at cellular resolution and a brain-wide scale, but existing Sindbis virus-based techniques can only map long-range projections using anterograde tracing approaches. Rabies virus can complement anterograde tracing approaches by enabling either retrograde labeling of projection neurons or monosynaptic tracing of direct inputs to genetically targeted postsynaptic neurons. However, barcoded rabies virus has so far been only used to map non-neuronal cellular interactions in vivo and synaptic connectivity of cultured neurons. Here we combine barcoded rabies virus with single-cell and in situ sequencing to perform retrograde labeling and transsynaptic labeling in the mouse brain. We sequenced 96 retrogradely labeled cells and 295 transsynaptically labeled cells using single-cell RNA-seq, and 4130 retrogradely labeled cells and 2914 transsynaptically labeled cells in situ. We found that the transcriptomic identities of rabies virus-infected cells can be robustly identified using both single-cell RNA-seq and in situ sequencing. By associating gene expression with connectivity inferred from barcode sequencing, we distinguished long-range projecting cortical cell types from multiple cortical areas and identified cell types with converging or diverging synaptic connectivity. Combining in situ sequencing with barcoded rabies virus complements existing sequencing-based neuroanatomical techniques and provides a potential path for mapping synaptic connectivity of neuronal types at scale.
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Affiliation(s)
- Aixin Zhang
- Allen Institute for Brain ScienceSeattleUnited States
| | - Lei Jin
- McGovern Institute for Brain Research, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Shenqin Yao
- Allen Institute for Brain ScienceSeattleUnited States
| | - Makoto Matsuyama
- McGovern Institute for Brain Research, Massachusetts Institute of TechnologyCambridgeUnited States
| | | | - Heather Anne Sullivan
- McGovern Institute for Brain Research, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Na Sun
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Broad Institute of MIT and HarvardCambridgeUnited States
- Broad Institute of MIT and HarvardCambridgeUnited States
| | - Manolis Kellis
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Broad Institute of MIT and HarvardCambridgeUnited States
- Broad Institute of MIT and HarvardCambridgeUnited States
| | | | - Ian Wickersham
- McGovern Institute for Brain Research, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Xiaoyin Chen
- Allen Institute for Brain ScienceSeattleUnited States
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19
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Chen S, Liu Y, Wang ZA, Colonell J, Liu LD, Hou H, Tien NW, Wang T, Harris T, Druckmann S, Li N, Svoboda K. Brain-wide neural activity underlying memory-guided movement. Cell 2024; 187:676-691.e16. [PMID: 38306983 DOI: 10.1016/j.cell.2023.12.035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 09/19/2023] [Accepted: 12/27/2023] [Indexed: 02/04/2024]
Abstract
Behavior relies on activity in structured neural circuits that are distributed across the brain, but most experiments probe neurons in a single area at a time. Using multiple Neuropixels probes, we recorded from multi-regional loops connected to the anterior lateral motor cortex (ALM), a circuit node mediating memory-guided directional licking. Neurons encoding sensory stimuli, choices, and actions were distributed across the brain. However, choice coding was concentrated in the ALM and subcortical areas receiving input from the ALM in an ALM-dependent manner. Diverse orofacial movements were encoded in the hindbrain; midbrain; and, to a lesser extent, forebrain. Choice signals were first detected in the ALM and the midbrain, followed by the thalamus and other brain areas. At movement initiation, choice-selective activity collapsed across the brain, followed by new activity patterns driving specific actions. Our experiments provide the foundation for neural circuit models of decision-making and movement initiation.
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Affiliation(s)
- Susu Chen
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Yi Liu
- Stanford University, Palo Alto, CA, USA
| | | | - Jennifer Colonell
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Liu D Liu
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; Baylor College of Medicine, Houston, TX, USA
| | - Han Hou
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; Allen Institute for Neural Dynamics, Seattle, WA, USA
| | - Nai-Wen Tien
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Tim Wang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; Allen Institute for Neural Dynamics, Seattle, WA, USA
| | - Timothy Harris
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; Johns Hopkins University, Baltimore, MD, USA
| | - Shaul Druckmann
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; Stanford University, Palo Alto, CA, USA.
| | - Nuo Li
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; Baylor College of Medicine, Houston, TX, USA.
| | - Karel Svoboda
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; Allen Institute for Neural Dynamics, Seattle, WA, USA.
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20
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Liu S, Gao L, Chen J, Yan J. Single-neuron analysis of axon arbors reveals distinct presynaptic organizations between feedforward and feedback projections. Cell Rep 2024; 43:113590. [PMID: 38127620 DOI: 10.1016/j.celrep.2023.113590] [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: 02/23/2023] [Revised: 07/18/2023] [Accepted: 11/30/2023] [Indexed: 12/23/2023] Open
Abstract
The morphology and spatial distribution of axon arbors and boutons are crucial for neuron presynaptic functions. However, the principles governing their whole-brain organization at the single-neuron level remain unclear. We developed a machine-learning method to separate axon arbors from passing axons in single-neuron reconstruction from fluorescence micro-optical sectioning tomography imaging data and obtained 62,374 axon arbors that displayed distinct morphology, spatial patterns, and scaling laws dependent on neuron types and targeted brain areas. Focusing on the axon arbors in the thalamus and cortex, we revealed the segregated spatial distributions and distinct morphology but shared topographic gradients between feedforward and feedback projections. Furthermore, we uncovered an association between arbor complexity and microglia density. Finally, we found that the boutons on terminal arbors show branch-specific clustering with a log-normal distribution that again differed between feedforward and feedback terminal arbors. Together, our study revealed distinct presynaptic structural organizations underlying diverse functional innervation of single projection neurons.
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Affiliation(s)
- Sang Liu
- 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; School of Future Technology, University of Chinese Academy of Sciences, Beijing 101408, China
| | - Le Gao
- 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
| | - Jiu Chen
- 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
| | - Jun Yan
- 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; School of Future Technology, University of Chinese Academy of Sciences, Beijing 101408, China; Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai 201210, China.
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21
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Gulledge AT. Cholinergic Activation of Corticofugal Circuits in the Adult Mouse Prefrontal Cortex. J Neurosci 2024; 44:e1388232023. [PMID: 38050146 PMCID: PMC10860659 DOI: 10.1523/jneurosci.1388-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 10/10/2023] [Accepted: 11/08/2023] [Indexed: 12/06/2023] Open
Abstract
Acetylcholine (ACh) promotes neocortical output to the thalamus and brainstem by preferentially enhancing the postsynaptic excitability of layer 5 pyramidal tract (PT) neurons relative to neighboring intratelencephalic (IT) neurons. Less is known about how ACh regulates the excitatory synaptic drive of IT and PT neurons. To address this question, spontaneous excitatory postsynaptic potentials (sEPSPs) were recorded in dual recordings of IT and PT neurons in slices of prelimbic cortex from adult female and male mice. ACh (20 µM) enhanced sEPSP amplitudes, frequencies, rise-times, and half-widths preferentially in PT neurons. These effects were blocked by the muscarinic receptor antagonist atropine (1 µM). When challenged with pirenzepine (1 µM), an antagonist selective for M1-type muscarinic receptors, ACh instead reduced sEPSP frequencies, suggesting that ACh may generally suppress synaptic transmission in the cortex via non-M1 receptors. Cholinergic enhancement of sEPSPs in PT neurons was not sensitive to antagonism of GABA receptors with gabazine (10 µM) and CGP52432 (2.5 µM) but was blocked by tetrodotoxin (1 µM), suggesting that ACh enhances action-potential-dependent excitatory synaptic transmission in PT neurons. ACh also preferentially promoted the occurrence of synchronous sEPSPs in dual recordings of PT neurons relative to IT-PT and IT-IT parings. Finally, selective chemogenetic silencing of hM4Di-expressing PT, but not commissural IT, neurons blocked cholinergic enhancement of sEPSP amplitudes and frequencies in PT neurons. These data suggest that, in addition to selectively enhancing the postsynaptic excitability of PT neurons, M1 receptor activation promotes corticofugal output by amplifying recurrent excitation within networks of PT neurons.
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Affiliation(s)
- Allan T Gulledge
- Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth College, Hanover 03755, New Hampshire
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22
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Gonzalo-Martín E, Alonso-Martínez C, Sepúlveda LP, Clasca F. Micropopulation mapping of the mouse parafascicular nucleus connections reveals diverse input-output motifs. Front Neuroanat 2024; 17:1305500. [PMID: 38260117 PMCID: PMC10800635 DOI: 10.3389/fnana.2023.1305500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2023] [Accepted: 11/10/2023] [Indexed: 01/24/2024] Open
Abstract
Introduction In primates, including humans, the centromedian/parafascicular (CM-Pf) complex is a key thalamic node of the basal ganglia system. Deep brain stimulation in CM-Pf has been applied for the treatment of motor disorders such as Parkinson's disease or Tourette syndrome. Rodents have become widely used models for the study of the cellular and genetic mechanisms of these and other motor disorders. However, the equivalence between the primate CM-Pf and the nucleus regarded as analogous in rodents (Parafascicular, Pf) remains unclear. Methods Here, we analyzed the neurochemical architecture and carried out a brain-wide mapping of the input-output motifs in the mouse Pf at micropopulation level using anterograde and retrograde labeling methods. Specifically, we mapped and quantified the sources of cortical and subcortical input to different Pf subregions, and mapped and compared the distribution and terminal structure of their axons. Results We found that projections to Pf arise predominantly (>75%) from the cerebral cortex, with an unusually strong (>45%) Layer 5b component, which is, in part, contralateral. The intermediate layers of the superior colliculus are the main subcortical input source to Pf. On its output side, Pf neuron axons predominantly innervate the striatum. In a sparser fashion, they innervate other basal ganglia nuclei, including the subthalamic nucleus (STN), and the cerebral cortex. Differences are evident between the lateral and medial portions of Pf, both in chemoarchitecture and in connectivity. Lateral Pf axons innervate territories of the striatum, STN and cortex involved in the sensorimotor control of different parts of the contralateral hemibody. In contrast, the mediodorsal portion of Pf innervates oculomotor-limbic territories in the above three structures. Discussion Our data thus indicate that the mouse Pf consists of several neurochemically and connectively distinct domains whose global organization bears a marked similarity to that described in the primate CM-Pf complex.
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Affiliation(s)
| | | | | | - Francisco Clasca
- Department of Anatomy and Neuroscience, Autónoma de Madrid University, Madrid, Spain
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23
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Sohn J. Synaptic configuration and reconfiguration in the neocortex are spatiotemporally selective. Anat Sci Int 2024; 99:17-33. [PMID: 37837522 PMCID: PMC10771605 DOI: 10.1007/s12565-023-00743-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Accepted: 09/14/2023] [Indexed: 10/16/2023]
Abstract
Brain computation relies on the neural networks. Neurons extend the neurites such as dendrites and axons, and the contacts of these neurites that form chemical synapses are the biological basis of signal transmissions in the central nervous system. Individual neuronal outputs can influence the other neurons within the range of the axonal spread, while the activities of single neurons can be affected by the afferents in their somatodendritic fields. The morphological profile, therefore, binds the functional role each neuron can play. In addition, synaptic connectivity among neurons displays preference based on the characteristics of presynaptic and postsynaptic neurons. Here, the author reviews the "spatial" and "temporal" connection selectivity in the neocortex. The histological description of the neocortical circuitry depends primarily on the classification of cell types, and the development of gene engineering techniques allows the cell type-specific visualization of dendrites and axons as well as somata. Using genetic labeling of particular cell populations combined with immunohistochemistry and imaging at a subcellular spatial resolution, we revealed the "spatial selectivity" of cortical wirings in which synapses are non-uniformly distributed on the subcellular somatodendritic domains in a presynaptic cell type-specific manner. In addition, cortical synaptic dynamics in learning exhibit presynaptic cell type-dependent "temporal selectivity": corticocortical synapses appear only transiently during the learning phase, while learning-induced new thalamocortical synapses persist, indicating that distinct circuits may supervise learning-specific ephemeral synapse and memory-specific immortal synapse formation. The selectivity of spatial configuration and temporal reconfiguration in the neural circuitry may govern diverse functions in the neocortex.
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Affiliation(s)
- Jaerin Sohn
- Department of Systematic Anatomy and Neurobiology, Graduate School of Dentistry, Osaka University, Suita, Osaka, 565-0871, Japan.
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24
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Vincent JP, Economo MN. Assessing cross-contamination in spike-sorted electrophysiology data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.21.572882. [PMID: 38187738 PMCID: PMC10769346 DOI: 10.1101/2023.12.21.572882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Recent advances in extracellular electrophysiology now facilitate the recording of spikes from hundreds or thousands of neurons simultaneously. This has necessitated both the development of new computational methods for spike sorting and better methods to determine spike sorting accuracy. One longstanding method of assessing the false discovery rate (FDR) of spike sorting - the rate at which spikes are misassigned to the wrong cluster - has been the rate of inter-spike-interval (ISI) violations. Despite their near ubiquitous usage in spike sorting, our understanding of how exactly ISI violations relate to FDR, as well as best practices for using ISI violations as a quality metric, remain limited. Here, we describe an analytical solution that can be used to predict FDR from ISI violation rate. We test this model in silico through Monte Carlo simulation, and apply it to publicly available spike-sorted electrophysiology datasets. We find that the relationship between ISI violation rate and FDR is highly nonlinear, with additional dependencies on firing rate, the correlation in activity between neurons, and contaminant neuron count. Predicted median FDRs in public datasets were found to range from 3.1% to 50.0%. We find that stochasticity in the occurrence of ISI violations as well as uncertainty in cluster-specific parameters make it difficult to predict FDR for single clusters with high confidence, but that FDR can be estimated accurately across a population of clusters. Our findings will help the growing community of researchers using extracellular electrophysiology assess spike sorting accuracy in a principled manner.
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Affiliation(s)
- Jack P. Vincent
- Department of Biomedical Engineering, Boston University, Boston, MA
- Center for Neurophotonics, Boston University, Boston, MA
| | - Michael N. Economo
- Department of Biomedical Engineering, Boston University, Boston, MA
- Center for Neurophotonics, Boston University, Boston, MA
- Center for Systems Neuroscience, Boston University, Boston, MA
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25
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Huang D, Ma YY. Increased Excitability of Layer 2 Cortical Pyramidal Neurons in the Supplementary Motor Cortex Underlies High Cocaine-Seeking Behaviors. Biol Psychiatry 2023; 94:875-887. [PMID: 37330163 PMCID: PMC10721734 DOI: 10.1016/j.biopsych.2023.06.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 05/29/2023] [Accepted: 06/07/2023] [Indexed: 06/19/2023]
Abstract
BACKGROUND Most efforts in addiction research have focused on the involvement of the medial prefrontal cortex, including the infralimbic, prelimbic, and anterior cingulate cortical areas, in cocaine-seeking behaviors. However, no effective prevention or treatment for drug relapse is available. METHODS We focused instead on the motor cortex, including both the primary and supplementary motor areas (M1 and M2, respectively). Addiction risk was evaluated by testing cocaine seeking after intravenous self-administration (IVSA) of cocaine in Sprague Dawley rats. The causal relationship between the excitability of cortical pyramidal neurons (CPNs) in M1/M2 and addiction risk was explored by ex vivo whole-cell patch clamp recordings and in vivo pharmacological or chemogenetic manipulation. RESULTS Our recordings showed that on withdrawal day 45 (WD45) after IVSA, cocaine, but not saline, increased the excitability of CPNs in the cortical superficial layers (primarily layer 2, denoted L2) but not in layer 5 (L5) in M2. Bilateral microinjection of the GABAA (gamma-aminobutyric acid A) receptor agonist muscimol to the M2 area attenuated cocaine seeking on WD45. More specifically, chemogenetic inhibition of CPN excitability in L2 of M2 (denoted M2-L2) by the DREADD (designer receptor exclusively activated by designer drugs) agonist compound 21 prevented drug seeking on WD45 after cocaine IVSA. This chemogenetic inhibition of M2-L2 CPNs had no effects on sucrose seeking. In addition, neither pharmacological nor chemogenetic inhibition manipulations altered general locomotor activity. CONCLUSIONS Our results indicate that cocaine IVSA induces hyperexcitability in the motor cortex on WD45. Importantly, the increased excitability in M2, particularly in L2, could be a novel target for preventing drug relapse during withdrawal.
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Affiliation(s)
- Donald Huang
- Department of Pharmacology and Toxicology, Indiana University School of Medicine, Indianapolis, Indiana; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, Indiana
| | - Yao-Ying Ma
- Department of Pharmacology and Toxicology, Indiana University School of Medicine, Indianapolis, Indiana; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, Indiana.
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26
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Zhou J, Zhang Z, Wu M, Liu H, Pang Y, Bartlett A, Peng Z, Ding W, Rivkin A, Lagos WN, Williams E, Lee CT, Miyazaki PA, Aldridge A, Zeng Q, Salinda JLA, Claffey N, Liem M, Fitzpatrick C, Boggeman L, Yao Z, Smith KA, Tasic B, Altshul J, Kenworthy MA, Valadon C, Nery JR, Castanon RG, Patne NS, Vu M, Rashid M, Jacobs M, Ito T, Osteen J, Emerson N, Lee J, Cho S, Rink J, Huang HH, Pinto-Duartec A, Dominguez B, Smith JB, O'Connor C, Zeng H, Chen S, Lee KF, Mukamel EA, Jin X, Margarita Behrens M, Ecker JR, Callaway EM. Brain-wide correspondence of neuronal epigenomics and distant projections. Nature 2023; 624:355-365. [PMID: 38092919 PMCID: PMC10719087 DOI: 10.1038/s41586-023-06823-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 11/01/2023] [Indexed: 12/17/2023]
Abstract
Single-cell analyses parse the brain's billions of neurons into thousands of 'cell-type' clusters residing in different brain structures1. Many cell types mediate their functions through targeted long-distance projections allowing interactions between specific cell types. Here we used epi-retro-seq2 to link single-cell epigenomes and cell types to long-distance projections for 33,034 neurons dissected from 32 different regions projecting to 24 different targets (225 source-to-target combinations) across the whole mouse brain. We highlight uses of these data for interrogating principles relating projection types to transcriptomics and epigenomics, and for addressing hypotheses about cell types and connections related to genetics. We provide an overall synthesis with 926 statistical comparisons of discriminability of neurons projecting to each target for every source. We integrate this dataset into the larger BRAIN Initiative Cell Census Network atlas, composed of millions of neurons, to link projection cell types to consensus clusters. Integration with spatial transcriptomics further assigns projection-enriched clusters to smaller source regions than the original dissections. We exemplify this by presenting in-depth analyses of projection neurons from the hypothalamus, thalamus, hindbrain, amygdala and midbrain to provide insights into properties of those cell types, including differentially expressed genes, their associated cis-regulatory elements and transcription-factor-binding motifs, and neurotransmitter use.
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Affiliation(s)
- Jingtian Zhou
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, USA
| | - Zhuzhu Zhang
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Department of Human Genetics, The University of Chicago, Chicago, IL, USA
| | - May Wu
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Division of Biological Sciences, University of California San Diego, La Jolla, CA, USA
| | - Hanqing Liu
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Yan Pang
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Anna Bartlett
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Zihao Peng
- School of Mathematics and Computer Science, Nanchang University, Nanchang, China
- Henan Engineering Research Center of Intelligent Technology and Application, Henan University, Kaifeng, China
| | - Wubin Ding
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Angeline Rivkin
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Will N Lagos
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Elora Williams
- Molecular Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Cheng-Ta Lee
- Peptide Biology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Paula Assakura Miyazaki
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Andrew Aldridge
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Qiurui Zeng
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Division of Biological Sciences, University of California San Diego, La Jolla, CA, USA
| | - J L Angelo Salinda
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Naomi Claffey
- Flow Cytometry Core Facility, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Michelle Liem
- Flow Cytometry Core Facility, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Conor Fitzpatrick
- Flow Cytometry Core Facility, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Lara Boggeman
- Flow Cytometry Core Facility, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Zizhen Yao
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Jordan Altshul
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Mia A Kenworthy
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Cynthia Valadon
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Joseph R Nery
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Rosa G Castanon
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Neelakshi S Patne
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Minh Vu
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Mohammad Rashid
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Matthew Jacobs
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Tony Ito
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Julia Osteen
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Nora Emerson
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Jasper Lee
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Silvia Cho
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Jon Rink
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Hsiang-Hsuan Huang
- Molecular Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - António Pinto-Duartec
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Bertha Dominguez
- Peptide Biology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Jared B Smith
- Molecular Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Carolyn O'Connor
- Flow Cytometry Core Facility, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Shengbo Chen
- Henan Engineering Research Center of Intelligent Technology and Application, Henan University, Kaifeng, China
- School of Computer and Information Engineering, Henan University, Kaifeng, China
| | - Kuo-Fen Lee
- Peptide Biology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Eran A Mukamel
- Department of Cognitive Science, University of California San Diego, La Jolla, CA, USA
| | - Xin Jin
- Center for Motor Control and Disease, Key Laboratory of Brain Functional Genomics, East China Normal University, Shanghai, China
- NYU-ECNU Institute of Brain and Cognitive Science, New York University Shanghai, Shanghai, China
| | - M Margarita Behrens
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Joseph R Ecker
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA.
- Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA, USA.
| | - Edward M Callaway
- Division of Biological Sciences, University of California San Diego, La Jolla, CA, USA.
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA.
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27
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Sorensen SA, Gouwens NW, Wang Y, Mallory M, Budzillo A, Dalley R, Lee B, Gliko O, Kuo HC, Kuang X, Mann R, Ahmadinia L, Alfiler L, Baftizadeh F, Baker K, Bannick S, Bertagnolli D, Bickley K, Bohn P, Brown D, Bomben J, Brouner K, Chen C, Chen K, Chvilicek M, Collman F, Daigle T, Dawes T, de Frates R, Dee N, DePartee M, Egdorf T, El-Hifnawi L, Enstrom R, Esposito L, Farrell C, Gala R, Glomb A, Gamlin C, Gary A, Goldy J, Gu H, Hadley K, Hawrylycz M, Henry A, Hill D, Hirokawa KE, Huang Z, Johnson K, Juneau Z, Kebede S, Kim L, Lee C, Lesnar P, Li A, Glomb A, Li Y, Liang E, Link K, Maxwell M, McGraw M, McMillen DA, Mukora A, Ng L, Ochoa T, Oldre A, Park D, Pom CA, Popovich Z, Potekhina L, Rajanbabu R, Ransford S, Reding M, Ruiz A, Sandman D, Siverts L, Smith KA, Stoecklin M, Sulc J, Tieu M, Ting J, Trinh J, Vargas S, Vumbaco D, Walker M, Wang M, Wanner A, Waters J, Williams G, Wilson J, Xiong W, Lein E, Berg J, Kalmbach B, Yao S, Gong H, Luo Q, Ng L, Sümbül U, Jarsky T, Yao Z, Tasic B, Zeng H. Connecting single-cell transcriptomes to projectomes in mouse visual cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.25.568393. [PMID: 38168270 PMCID: PMC10760188 DOI: 10.1101/2023.11.25.568393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
The mammalian brain is composed of diverse neuron types that play different functional roles. Recent single-cell RNA sequencing approaches have led to a whole brain taxonomy of transcriptomically-defined cell types, yet cell type definitions that include multiple cellular properties can offer additional insights into a neuron's role in brain circuits. While the Patch-seq method can investigate how transcriptomic properties relate to the local morphological and electrophysiological properties of cell types, linking transcriptomic identities to long-range projections is a major unresolved challenge. To address this, we collected coordinated Patch-seq and whole brain morphology data sets of excitatory neurons in mouse visual cortex. From the Patch-seq data, we defined 16 integrated morpho-electric-transcriptomic (MET)-types; in parallel, we reconstructed the complete morphologies of 300 neurons. We unified the two data sets with a multi-step classifier, to integrate cell type assignments and interrogate cross-modality relationships. We find that transcriptomic variations within and across MET-types correspond with morphological and electrophysiological phenotypes. In addition, this variation, along with the anatomical location of the cell, can be used to predict the projection targets of individual neurons. We also shed new light on infragranular cell types and circuits, including cell-type-specific, interhemispheric projections. With this approach, we establish a comprehensive, integrated taxonomy of excitatory neuron types in mouse visual cortex and create a system for integrated, high-dimensional cell type classification that can be extended to the whole brain and potentially across species.
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Affiliation(s)
| | | | - Yun Wang
- Allen Institute for Brain Science
| | | | | | | | | | | | | | - Xiuli Kuang
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | | | | | | | | | | | | | | | | | | | | | | | | | - Chao Chen
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | - Kai Chen
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | | | | | | | | | | | - Nick Dee
- Allen Institute for Brain Science
| | | | | | | | | | | | | | | | | | | | | | | | - Hong Gu
- Allen Institute for Brain Science
| | | | | | | | | | | | - Zili Huang
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | | | | | | | - Lisa Kim
- Allen Institute for Brain Science
| | | | | | - 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, China
- HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, China
| | | | - Yaoyao Li
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | | | | | | | | | | | | | | | | | | | | | | | - Zoran Popovich
- University of Washington, Dept. of Computer Science and Engineering
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Wei Xiong
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | - Ed Lein
- Allen Institute for Brain Science
| | - Jim Berg
- Allen Institute for Brain Science
| | | | | | - 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, China
- HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, China
| | - Qingming Luo
- State Key Laboratory of Digital Medical Engineering, School of Biomedical Engineering, Hainan University, Haikou, China
| | - Lydia Ng
- Allen Institute for Brain Science
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28
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Golan N, Ehrlich D, Bonanno J, O'Brien RF, Murillo M, Kauer SD, Ravindra N, Van Dijk D, Cafferty WB. Anatomical Diversity of the Adult Corticospinal Tract Revealed by Single-Cell Transcriptional Profiling. J Neurosci 2023; 43:7929-7945. [PMID: 37748862 PMCID: PMC10669816 DOI: 10.1523/jneurosci.0811-22.2023] [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: 04/26/2022] [Revised: 07/28/2023] [Accepted: 08/01/2023] [Indexed: 09/27/2023] Open
Abstract
The corticospinal tract (CST) forms a central part of the voluntary motor apparatus in all mammals. Thus, injury, disease, and subsequent degeneration within this pathway result in chronic irreversible functional deficits. Current strategies to repair the damaged CST are suboptimal in part because of underexplored molecular heterogeneity within the adult tract. Here, we combine spinal retrograde CST tracing with single-cell RNA sequencing (scRNAseq) in adult male and female mice to index corticospinal neuron (CSN) subtypes that differentially innervate the forelimb and hindlimb. We exploit publicly available datasets to confer anatomic specialization among CSNs and show that CSNs segregate not only along the forelimb and hindlimb axis but also by supraspinal axon collateralization. These anatomically defined transcriptional data allow us to use machine learning tools to build classifiers that discriminate between CSNs and cortical layer 2/3 and nonspinally terminating layer 5 neurons in M1 and separately identify limb-specific CSNs. Using these tools, CSN subtypes can be differentially identified to study postnatal patterning of the CST in vivo, leveraged to screen for novel limb-specific axon growth survival and growth activators in vitro, and ultimately exploited to repair the damaged CST after injury and disease.SIGNIFICANCE STATEMENT Therapeutic interventions designed to repair the damaged CST after spinal cord injury have remained functionally suboptimal in part because of an incomplete understanding of the molecular heterogeneity among subclasses of CSNs. Here, we combine spinal retrograde labeling with scRNAseq and annotate a CSN index by the termination pattern of their primary axon in the cervical or lumbar spinal cord and supraspinal collateral terminal fields. Using machine learning we have confirmed the veracity of our CSN gene lists to train classifiers to identify CSNs among all classes of neurons in primary motor cortex to study the development, patterning, homeostasis, and response to injury and disease, and ultimately target streamlined repair strategies to this critical motor pathway.
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Affiliation(s)
- Noa Golan
- Interdepartmental Neuroscience Program, Yale University School, New Haven, Connecticut 06511
- Department of Neurology, Yale University School, New Haven, Connecticut 06511
| | - Daniel Ehrlich
- Interdepartmental Neuroscience Program, Yale University School, New Haven, Connecticut 06511
- Department of Psychiatry, Yale University School, New Haven, Connecticut 06511
| | - James Bonanno
- Interdepartmental Neuroscience Program, Yale University School, New Haven, Connecticut 06511
- Department of Neurology, Yale University School, New Haven, Connecticut 06511
| | - Rory F O'Brien
- Department of Neurology, Yale University School, New Haven, Connecticut 06511
| | - Matias Murillo
- Interdepartmental Neuroscience Program, Yale University School, New Haven, Connecticut 06511
- Department of Neurology, Yale University School, New Haven, Connecticut 06511
| | - Sierra D Kauer
- Department of Neurology, Yale University School, New Haven, Connecticut 06511
| | - Neal Ravindra
- Department of Internal Medicine, Yale University School, New Haven, Connecticut 06511
- Department of Computer Science, Yale University School, New Haven, Connecticut 06511
| | - David Van Dijk
- Department of Internal Medicine, Yale University School, New Haven, Connecticut 06511
- Department of Computer Science, Yale University School, New Haven, Connecticut 06511
| | - William B Cafferty
- Department of Neurology, Yale University School, New Haven, Connecticut 06511
- Department of Neuroscience, Yale University School, New Haven, Connecticut 06511
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29
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Zhang A, Jin L, Yao S, Matsuyama M, van Velthoven C, Sullivan H, Sun N, Kellis M, Tasic B, Wickersham IR, Chen X. Rabies virus-based barcoded neuroanatomy resolved by single-cell RNA and in situ sequencing. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.16.532873. [PMID: 36993334 PMCID: PMC10055146 DOI: 10.1101/2023.03.16.532873] [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: 06/19/2023]
Abstract
Mapping the connectivity of diverse neuronal types provides the foundation for understanding the structure and function of neural circuits. High-throughput and low-cost neuroanatomical techniques based on RNA barcode sequencing have the potential to map circuits at cellular resolution and a brain-wide scale, but existing Sindbis virus-based techniques can only map long-range projections using anterograde tracing approaches. Rabies virus can complement anterograde tracing approaches by enabling either retrograde labeling of projection neurons or monosynaptic tracing of direct inputs to genetically targeted postsynaptic neurons. However, barcoded rabies virus has so far been only used to map non-neuronal cellular interactions in vivo and synaptic connectivity of cultured neurons. Here we combine barcoded rabies virus with single-cell and in situ sequencing to perform retrograde labeling and transsynaptic labeling in the mouse brain. We sequenced 96 retrogradely labeled cells and 295 transsynaptically labeled cells using single-cell RNA-seq, and 4,130 retrogradely labeled cells and 2,914 transsynaptically labeled cells in situ. We found that the transcriptomic identities of rabies virus-infected cells can be robustly identified using both single-cell RNA-seq and in situ sequencing. By associating gene expression with connectivity inferred from barcode sequencing, we distinguished long-range projecting cortical cell types from multiple cortical areas and identified cell types with converging or diverging synaptic connectivity. Combining in situ sequencing with barcoded rabies virus complements existing sequencing-based neuroanatomical techniques and provides a potential path for mapping synaptic connectivity of neuronal types at scale.
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Affiliation(s)
- Aixin Zhang
- Allen Institute for Brain Science, Seattle, WA
| | - Lei Jin
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA
- Current address: Lingang Laboratory, Shanghai, China
| | - Shenqin Yao
- Allen Institute for Brain Science, Seattle, WA
| | - Makoto Matsuyama
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA
- Current address: Metcela Inc., Kawasaki, Kanagawa, Japan
| | | | - Heather Sullivan
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA
| | - Na Sun
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Manolis Kellis
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Ian R. Wickersham
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA
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30
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Maristany de Las Casas E, Takahashi N. Synaptic crossroads: navigating the circuits of movement. Trends Neurosci 2023; 46:895-897. [PMID: 37690954 PMCID: PMC10591950 DOI: 10.1016/j.tins.2023.08.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 08/17/2023] [Indexed: 09/12/2023]
Abstract
The anterior lateral motor area (ALM) is crucial in preparing and executing voluntary movements through its diverse neuronal subpopulations that target different subcortical areas. A recent study by Xu et al. utilized an elaborate viral tracing strategy in mice to provide comprehensive whole-brain maps of monosynaptic inputs to the major descending pathways of ALM.
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Affiliation(s)
| | - Naoya Takahashi
- University of Bordeaux, CNRS, Interdisciplinary Institute for Neuroscience, IINS, UMR 5297, 33000 Bordeaux, France.
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31
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Li Y, An X, Qian Y, Xu XH, Zhao S, Mohan H, Bachschmid-Romano L, Brunel N, Whishaw IQ, Huang ZJ. Cortical network and projection neuron types that articulate serial order in a skilled motor behavior. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.25.563871. [PMID: 37961483 PMCID: PMC10634836 DOI: 10.1101/2023.10.25.563871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Skilled motor behaviors require orderly coordination of multiple constituent movements with sensory cues towards achieving a goal, but the underlying brain circuit mechanisms remain unclear. Here we show that target-guided reach-grasp-to-drink (RGD) in mice involves the ordering and coordination of a set of forelimb and oral actions. Cortex-wide activity imaging of multiple glutamatergic projection neuron (PN) types uncovered a network, involving the secondary motor cortex (MOs), forelimb primary motor and somatosensory cortex, that tracked RGD movements. Photo-inhibition highlighted MOs in coordinating RGD movements. Within the MOs, population neural trajectories tracked RGD progression and single neuron activities integrated across constituent movements. Notably, MOs intratelencephalic, pyramidal tract, and corticothalamic PN activities correlated with action coordination, showed distinct neural dynamics trajectories, and differentially contributed to movement coordination. Our results delineate a cortical network and key areas, PN types, and neural dynamics therein that articulate the serial order and coordination of a skilled behavior.
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Affiliation(s)
- Yi Li
- Department of Neurobiology, Duke University, Durham, NC 27710, USA
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 1 1724, USA
| | - Xu An
- Department of Neurobiology, Duke University, Durham, NC 27710, USA
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 1 1724, USA
| | - Yongjun Qian
- Department of Neurobiology, Duke University, Durham, NC 27710, USA
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 1 1724, USA
| | - X. Hermione Xu
- Department of Biomedical Engineering, Duke University, Durham, NC 27710, USA
| | - Shengli Zhao
- Department of Neurobiology, Duke University, Durham, NC 27710, USA
| | - Hemanth Mohan
- Department of Neurobiology, Duke University, Durham, NC 27710, USA
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 1 1724, USA
| | | | - Nicolas Brunel
- Department of Neurobiology, Duke University, Durham, NC 27710, USA
| | - Ian Q. Whishaw
- Department of Neuroscience, Canadian Centre for Behavioural Research, University of Lethbridge, Lethbridge, AB, TIK 3M4, Canada
| | - Z. Josh Huang
- Department of Neurobiology, Duke University, Durham, NC 27710, USA
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 1 1724, USA
- Department of Biomedical Engineering, Duke University, Durham, NC 27710, USA
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32
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Liu J, Liu D, Pu X, Zou K, Xie T, Li Y, Yao H. The Secondary Motor Cortex-striatum Circuit Contributes to Suppressing Inappropriate Responses in Perceptual Decision Behavior. Neurosci Bull 2023; 39:1544-1560. [PMID: 37253985 PMCID: PMC10533474 DOI: 10.1007/s12264-023-01073-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Accepted: 03/08/2023] [Indexed: 06/01/2023] Open
Abstract
The secondary motor cortex (M2) encodes choice-related information and plays an important role in cue-guided actions. M2 neurons innervate the dorsal striatum (DS), which also contributes to decision-making behavior, yet how M2 modulates signals in the DS to influence perceptual decision-making is unclear. Using mice performing a visual Go/No-Go task, we showed that inactivating M2 projections to the DS impaired performance by increasing the false alarm (FA) rate to the reward-irrelevant No-Go stimulus. The choice signal of M2 neurons correlated with behavioral performance, and the inactivation of M2 neurons projecting to the DS reduced the choice signal in the DS. By measuring and manipulating the responses of direct or indirect pathway striatal neurons defined by M2 inputs, we found that the indirect pathway neurons exhibited a shorter response latency to the No-Go stimulus, and inactivating their early responses increased the FA rate. These results demonstrate that the M2-to-DS pathway is crucial for suppressing inappropriate responses in perceptual decision behavior.
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Affiliation(s)
- Jing Liu
- 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
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Dechen Liu
- 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
| | - Xiaotian Pu
- 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
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Kexin Zou
- 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
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Taorong Xie
- 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
| | - Yaping 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
| | - Haishan Yao
- 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 Intelligence Technology, Shanghai, 201210, China.
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33
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Cai B, Wu D, Xie H, Chen Y, Wang H, Jin S, Song Y, Li A, Huang S, Wang S, Lu Y, Bao L, Xu F, Gong H, Li C, Zhang X. A direct spino-cortical circuit bypassing the thalamus modulates nociception. Cell Res 2023; 33:775-789. [PMID: 37311832 PMCID: PMC10542357 DOI: 10.1038/s41422-023-00832-0] [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: 11/02/2021] [Accepted: 05/19/2023] [Indexed: 06/15/2023] Open
Abstract
Nociceptive signals are usually transmitted to layer 4 neurons in somatosensory cortex via the spinothalamic-thalamocortical pathway. The layer 5 corticospinal neurons in sensorimotor cortex are reported to receive the output of neurons in superficial layers; and their descending axons innervate the spinal cord to regulate basic sensorimotor functions. Here, we show that a subset of layer 5 neurons receives spinal inputs through a direct spino-cortical circuit bypassing the thalamus, and thus define these neurons as spino-cortical recipient neurons (SCRNs). Morphological studies revealed that the branches from spinal ascending axons formed a kind of disciform structure with the descending axons from SCRNs in the basilar pontine nucleus (BPN). Electron microscopy and calcium imaging further confirmed that the axon terminals from spinal ascending neurons and SCRNs made functional synaptic contacts in the BPN, linking the ascending sensory pathway to the descending motor control pathway. Furthermore, behavioral tests indicated that the spino-cortical connection in the BPN was involved in nociceptive responses. In vivo calcium imaging showed that SCRNs responded to peripheral noxious stimuli faster than neighboring layer 4 cortical neurons in awake mice. Manipulating activities of SCRNs could modulate nociceptive behaviors. Therefore, this direct spino-cortical circuit represents a noncanonical pathway, allowing a fast sensory-motor transition of the brain in response to noxious stimuli.
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Affiliation(s)
- Bing Cai
- Guangdong Institute of Intelligence Science and Technology, Hengqin, Zhuhai, Guangdong, China
- SIMR Joint Lab of Drug Innovation, Shanghai Advanced Research Institute, Chinese Academy of Sciences (CAS); Xuhui Central Hospital, Shanghai, China
- Research Unit of Pain Medicine, Chinese Academy of Medical Sciences, Hengqin, Zhuhai, Guangdong, China
| | - Dan Wu
- Institute of Neuroscience and State Key Laboratory of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, CAS, Shanghai, China
| | - Hong Xie
- SIMR Joint Lab of Drug Innovation, Shanghai Advanced Research Institute, Chinese Academy of Sciences (CAS); Xuhui Central Hospital, Shanghai, China
- Institute of Photonic Chips; School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Yan Chen
- Guangdong Institute of Intelligence Science and Technology, Hengqin, Zhuhai, Guangdong, China
- SIMR Joint Lab of Drug Innovation, Shanghai Advanced Research Institute, Chinese Academy of Sciences (CAS); Xuhui Central Hospital, Shanghai, China
- Research Unit of Pain Medicine, Chinese Academy of Medical Sciences, Hengqin, Zhuhai, Guangdong, China
| | - Huadong Wang
- Shenzhen Key Laboratory of Viral Vectors for Biomedicine, Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, CAS, Shenzhen, Guangdong, China
| | - Sen Jin
- Shenzhen Key Laboratory of Viral Vectors for Biomedicine, Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, CAS, Shenzhen, Guangdong, China
| | - Yuran Song
- Guangdong Institute of Intelligence Science and Technology, Hengqin, Zhuhai, Guangdong, China
- SIMR Joint Lab of Drug Innovation, Shanghai Advanced Research Institute, Chinese Academy of Sciences (CAS); Xuhui Central Hospital, Shanghai, China
- Research Unit of Pain Medicine, Chinese Academy of Medical Sciences, Hengqin, Zhuhai, Guangdong, China
| | - Anan Li
- HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, Jiangsu, China
| | - Shiqi Huang
- SIMR Joint Lab of Drug Innovation, Shanghai Advanced Research Institute, Chinese Academy of Sciences (CAS); Xuhui Central Hospital, Shanghai, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China
| | - Sashuang Wang
- Department of Pain Medicine and Shenzhen Municipal Key Laboratory for Pain Medicine, Shenzhen Nanshan People's Hospital, Shenzhen, Guangdong, China
| | - Yingjin Lu
- Guangdong Institute of Intelligence Science and Technology, Hengqin, Zhuhai, Guangdong, China
| | - Lan Bao
- Guangdong Institute of Intelligence Science and Technology, Hengqin, Zhuhai, Guangdong, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, CAS, Shanghai, China
| | - Fuqiang Xu
- Shenzhen Key Laboratory of Viral Vectors for Biomedicine, Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, CAS, Shenzhen, Guangdong, China
| | - Hui Gong
- HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, Jiangsu, China
| | - Changlin Li
- Guangdong Institute of Intelligence Science and Technology, Hengqin, Zhuhai, Guangdong, China.
- Department of Pain Medicine and Shenzhen Municipal Key Laboratory for Pain Medicine, Shenzhen Nanshan People's Hospital, Shenzhen, Guangdong, China.
| | - Xu Zhang
- Guangdong Institute of Intelligence Science and Technology, Hengqin, Zhuhai, Guangdong, China.
- SIMR Joint Lab of Drug Innovation, Shanghai Advanced Research Institute, Chinese Academy of Sciences (CAS); Xuhui Central Hospital, Shanghai, China.
- Research Unit of Pain Medicine, Chinese Academy of Medical Sciences, Hengqin, Zhuhai, Guangdong, China.
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
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34
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Safaai H, Wang AY, Kira S, Malerba SB, Panzeri S, Harvey CD. Specialized structure of neural population codes in parietal cortex outputs. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.24.554635. [PMID: 37662297 PMCID: PMC10473762 DOI: 10.1101/2023.08.24.554635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Do cortical neurons that send axonal projections to the same target area form specialized population codes for transmitting information? We used calcium imaging in mouse posterior parietal cortex (PPC), retrograde labeling, and statistical multivariate models to address this question during a delayed match-to-sample task. We found that PPC broadcasts sensory, choice, and locomotion signals widely, but sensory information is enriched in the output to anterior cingulate cortex. Neurons projecting to the same area have elevated pairwise activity correlations. These correlations are structured as information-limiting and information-enhancing interaction networks that collectively enhance information levels. This network structure is unique to sub-populations projecting to the same target and strikingly absent in surrounding neural populations with unidentified projections. Furthermore, this structure is only present when mice make correct, but not incorrect, behavioral choices. Therefore, cortical neurons comprising an output pathway form uniquely structured population codes that enhance information transmission to guide accurate behavior.
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Affiliation(s)
- Houman Safaai
- Department of Neurobiology, Harvard Medical School, Boston, USA
- Neural Computation Laboratory, Istituto Italiano di Tecnologia, Genova, Italy
| | - Alice Y. Wang
- Department of Neurobiology, Harvard Medical School, Boston, USA
| | - Shinichiro Kira
- Department of Neurobiology, Harvard Medical School, Boston, USA
| | - Simone Blanco Malerba
- Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Stefano Panzeri
- Neural Computation Laboratory, Istituto Italiano di Tecnologia, Genova, Italy
- Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
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35
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Wang Y, Chen Z, Ma G, Wang L, Liu Y, Qin M, Fei X, Wu Y, Xu M, Zhang S. A frontal transcallosal inhibition loop mediates interhemispheric balance in visuospatial processing. Nat Commun 2023; 14:5213. [PMID: 37626171 PMCID: PMC10457336 DOI: 10.1038/s41467-023-40985-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 08/17/2023] [Indexed: 08/27/2023] Open
Abstract
Interhemispheric communication through the corpus callosum is required for both sensory and cognitive processes. Impaired transcallosal inhibition causing interhemispheric imbalance is believed to underlie visuospatial bias after frontoparietal cortical damage, but the synaptic circuits involved remain largely unknown. Here, we show that lesions in the mouse anterior cingulate area (ACA) cause severe visuospatial bias mediated by a transcallosal inhibition loop. In a visual-change-detection task, ACA callosal-projection neurons (CPNs) were more active with contralateral visual field changes than with ipsilateral changes. Unilateral CPN inactivation impaired contralateral change detection but improved ipsilateral detection by altering interhemispheric interaction through callosal projections. CPNs strongly activated contralateral parvalbumin-positive (PV+) neurons, and callosal-input-driven PV+ neurons preferentially inhibited ipsilateral CPNs, thus mediating transcallosal inhibition. Unilateral PV+ neuron activation caused a similar behavioral bias to contralateral CPN activation and ipsilateral CPN inactivation, and bilateral PV+ neuron activation eliminated this bias. Notably, restoring interhemispheric balance by activating contralesional PV+ neurons significantly improved contralesional detection in ACA-lesioned animals. Thus, a frontal transcallosal inhibition loop comprising CPNs and callosal-input-driven PV+ neurons mediates interhemispheric balance in visuospatial processing, and enhancing contralesional transcallosal inhibition restores interhemispheric balance while also reversing lesion-induced bias.
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Affiliation(s)
- Yanjie Wang
- Songjiang Research Institute, Shanghai Songjiang District Central Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, 200025, China
- Center for Brain Science of Shanghai Children's Medical Center, Department of Anatomy and Physiology, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Zhaonan Chen
- Songjiang Research Institute, Shanghai Songjiang District Central Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, 200025, China
- Center for Brain Science of Shanghai Children's Medical Center, Department of Anatomy and Physiology, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Guofen Ma
- Songjiang Research Institute, Shanghai Songjiang District Central Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, 200025, China
- Center for Brain Science of Shanghai Children's Medical Center, Department of Anatomy and Physiology, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Lizhao Wang
- Songjiang Research Institute, Shanghai Songjiang District Central Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, 200025, China
- Center for Brain Science of Shanghai Children's Medical Center, Department of Anatomy and Physiology, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Yanmei Liu
- Songjiang Research Institute, Shanghai Songjiang District Central Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, 200025, China
- Center for Brain Science of Shanghai Children's Medical Center, Department of Anatomy and Physiology, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Meiling Qin
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Xiang Fei
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yifan Wu
- Songjiang Research Institute, Shanghai Songjiang District Central Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, 200025, China
- Center for Brain Science of Shanghai Children's Medical Center, Department of Anatomy and Physiology, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Min Xu
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Siyu Zhang
- Songjiang Research Institute, Shanghai Songjiang District Central Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, 200025, China.
- Center for Brain Science of Shanghai Children's Medical Center, Department of Anatomy and Physiology, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China.
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36
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Kubo R, Yoshida T, Yamaoka K, Hashimoto K. The indirect corticopontine pathway relays perioral sensory signals to the cerebellum via the mesodiencephalic junction. iScience 2023; 26:107301. [PMID: 37539042 PMCID: PMC10393762 DOI: 10.1016/j.isci.2023.107301] [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: 02/16/2023] [Revised: 05/26/2023] [Accepted: 07/03/2023] [Indexed: 08/05/2023] Open
Abstract
In the cerebro-cerebellar loop, outputs from the cerebral cortex are thought to be transmitted via monosynaptic corticopontine gray (PG) pathways and subsequently relayed to the cerebellum. However, it is unclear whether this pathway is used constitutively for cerebro-cerebellar transduction. We examined perioral sensory pathways by unit recording from Purkinje cells in ketamine/xylazine-anesthetized mice. Infraorbital nerve stimulations enhanced simple spikes (SSs) with short and long latencies (first and second peaks), followed by SS inhibition. The second peak and SS inhibition were suppressed by muscimol (a GABAA agonist) injections into not only the PG but also the mesodiencephalic junction (MDJ). The pathway from the secondary somatosensory area (SII) to the MDJ, but not the cortico-PG pathway, transmitted the second peak signals. SS inhibition was processed in the SII and primary motor area. Thus, the indirect cortico-PG pathway, via the MDJ, is recruited for perioral sensory transduction.
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Affiliation(s)
- Reika Kubo
- Department of Neurophysiology, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima 734-8551, Japan
| | - Takayuki Yoshida
- Department of Neurophysiology, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima 734-8551, Japan
| | - Kenji Yamaoka
- Department of Neurophysiology, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima 734-8551, Japan
| | - Kouichi Hashimoto
- Department of Neurophysiology, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima 734-8551, Japan
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37
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Majumder S, Hirokawa K, Yang Z, Paletzki R, Gerfen CR, Fontolan L, Romani S, Jain A, Yasuda R, Inagaki HK. Cell-type-specific plasticity shapes neocortical dynamics for motor learning. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.09.552699. [PMID: 37609277 PMCID: PMC10441538 DOI: 10.1101/2023.08.09.552699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
Neocortical spiking dynamics control aspects of behavior, yet how these dynamics emerge during motor learning remains elusive. Activity-dependent synaptic plasticity is likely a key mechanism, as it reconfigures network architectures that govern neural dynamics. Here, we examined how the mouse premotor cortex acquires its well-characterized neural dynamics that control movement timing, specifically lick timing. To probe the role of synaptic plasticity, we have genetically manipulated proteins essential for major forms of synaptic plasticity, Ca2+/calmodulin-dependent protein kinase II (CaMKII) and Cofilin, in a region and cell-type-specific manner. Transient inactivation of CaMKII in the premotor cortex blocked learning of new lick timing without affecting the execution of learned action or ongoing spiking activity. Furthermore, among the major glutamatergic neurons in the premotor cortex, CaMKII and Cofilin activity in pyramidal tract (PT) neurons, but not intratelencephalic (IT) neurons, is necessary for learning. High-density electrophysiology in the premotor cortex uncovered that neural dynamics anticipating licks are progressively shaped during learning, which explains the change in lick timing. Such reconfiguration in behaviorally relevant dynamics is impeded by CaMKII manipulation in PT neurons. Altogether, the activity of plasticity-related proteins in PT neurons plays a central role in sculpting neocortical dynamics to learn new behavior.
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Affiliation(s)
- Shouvik Majumder
- Max Planck Florida Institute for Neuroscience, Jupiter, FL 33458, USA
| | - Koichi Hirokawa
- Max Planck Florida Institute for Neuroscience, Jupiter, FL 33458, USA
| | - Zidan Yang
- Max Planck Florida Institute for Neuroscience, Jupiter, FL 33458, USA
| | - Ronald Paletzki
- National Institute of Mental Health, Bethesda, MD 20814, USA
| | | | - Lorenzo Fontolan
- Turing Centre for Living Systems, Aix- Marseille University, INSERM, INMED U1249, Marseille, France
- Janelia Research Campus, HHMI, Ashburn VA 20147, USA
| | - Sandro Romani
- Janelia Research Campus, HHMI, Ashburn VA 20147, USA
| | - Anant Jain
- Max Planck Florida Institute for Neuroscience, Jupiter, FL 33458, USA
| | - Ryohei Yasuda
- Max Planck Florida Institute for Neuroscience, Jupiter, FL 33458, USA
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38
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Gongwer MW, Klune CB, Couto J, Jin B, Enos AS, Chen R, Friedmann D, DeNardo LA. Brain-Wide Projections and Differential Encoding of Prefrontal Neuronal Classes Underlying Learned and Innate Threat Avoidance. J Neurosci 2023; 43:5810-5830. [PMID: 37491314 PMCID: PMC10423051 DOI: 10.1523/jneurosci.0697-23.2023] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 07/12/2023] [Accepted: 07/18/2023] [Indexed: 07/27/2023] Open
Abstract
To understand how the brain produces behavior, we must elucidate the relationships between neuronal connectivity and function. The medial prefrontal cortex (mPFC) is critical for complex functions including decision-making and mood. mPFC projection neurons collateralize extensively, but the relationships between mPFC neuronal activity and brain-wide connectivity are poorly understood. We performed whole-brain connectivity mapping and fiber photometry to better understand the mPFC circuits that control threat avoidance in male and female mice. Using tissue clearing and light sheet fluorescence microscopy (LSFM), we mapped the brain-wide axon collaterals of populations of mPFC neurons that project to nucleus accumbens (NAc), ventral tegmental area (VTA), or contralateral mPFC (cmPFC). We present DeepTraCE (deep learning-based tracing with combined enhancement), for quantifying bulk-labeled axonal projections in images of cleared tissue, and DeepCOUNT (deep-learning based counting of objects via 3D U-net pixel tagging), for quantifying cell bodies. Anatomical maps produced with DeepTraCE aligned with known axonal projection patterns and revealed class-specific topographic projections within regions. Using TRAP2 mice and DeepCOUNT, we analyzed whole-brain functional connectivity underlying threat avoidance. PL was the most highly connected node with functional connections to subsets of PL-cPL, PL-NAc, and PL-VTA target sites. Using fiber photometry, we found that during threat avoidance, cmPFC and NAc-projectors encoded conditioned stimuli, but only when action was required to avoid threats. mPFC-VTA neurons encoded learned but not innate avoidance behaviors. Together our results present new and optimized approaches for quantitative whole-brain analysis and indicate that anatomically defined classes of mPFC neurons have specialized roles in threat avoidance.SIGNIFICANCE STATEMENT Understanding how the brain produces complex behaviors requires detailed knowledge of the relationships between neuronal connectivity and function. The medial prefrontal cortex (mPFC) plays a key role in learning, mood, and decision-making, including evaluating and responding to threats. mPFC dysfunction is strongly linked to fear, anxiety and mood disorders. Although mPFC circuits are clear therapeutic targets, gaps in our understanding of how they produce cognitive and emotional behaviors prevent us from designing effective interventions. To address this, we developed a high-throughput analysis pipeline for quantifying bulk-labeled fluorescent axons [DeepTraCE (deep learning-based tracing with combined enhancement)] or cell bodies [DeepCOUNT (deep-learning based counting of objects via 3D U-net pixel tagging)] in intact cleared brains. Using DeepTraCE, DeepCOUNT, and fiber photometry, we performed detailed anatomic and functional mapping of mPFC neuronal classes, identifying specialized roles in threat avoidance.
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Affiliation(s)
- Michael W Gongwer
- Department of Physiology
- Neuroscience Interdepartmental Program
- Medical Scientist Training Program
| | | | | | - Benita Jin
- Department of Physiology
- Molecular, Cellular and Integrative Physiology Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095
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Rocha GS, Freire MAM, Britto AM, Paiva KM, Oliveira RF, Fonseca IAT, Araújo DP, Oliveira LC, Guzen FP, Morais PLAG, Cavalcanti JRLP. Basal ganglia for beginners: the basic concepts you need to know and their role in movement control. Front Syst Neurosci 2023; 17:1242929. [PMID: 37600831 PMCID: PMC10435282 DOI: 10.3389/fnsys.2023.1242929] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 07/21/2023] [Indexed: 08/22/2023] Open
Abstract
The basal ganglia are a subcortical collection of interacting clusters of cell bodies, and are involved in reward, emotional, and motor circuits. Within all the brain processing necessary to carry out voluntary movement, the basal nuclei are fundamental, as they modulate the activity of the motor regions of the cortex. Despite being much studied, the motor circuit of the basal ganglia is still difficult to understand for many people at all, especially undergraduate and graduate students. This review article seeks to bring the functioning of this circuit with a simple and objective approach, exploring the functional anatomy, neurochemistry, neuronal pathways, related diseases, and interactions with other brain regions to coordinate voluntary movement.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - José R. L. P. Cavalcanti
- Laboratory of Experimental Neurology, Department of Biomedical Sciences, State University of Rio Grande do Norte, Mossoró, Brazil
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40
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Xu T, Jin Z, Yang M, Chen Z, Xiong H. Whole brain inputs to major descending pathways of the anterior lateral motor cortex. J Neurophysiol 2023; 130:278-290. [PMID: 37377198 DOI: 10.1152/jn.00112.2023] [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: 03/16/2023] [Revised: 06/09/2023] [Accepted: 06/21/2023] [Indexed: 06/29/2023] Open
Abstract
The anterior lateral motor cortex (ALM) is critical to subsequent correct movements and plays a vital role in predicting specific future movements. Different descending pathways of the ALM are preferentially involved in different roles in movements. However, the circuit function mechanisms of these different pathways may be concealed in the anatomy circuit. Clarifying the anatomy inputs of these pathways should provide some helpful information for elucidating these function mechanisms. Here, we used a retrograde trans-synaptic rabies virus to systematically generate, analyze, and compare whole brain maps of inputs to the thalamus (TH)-, medulla oblongata (Med)-, superior colliculus (SC)-, and pontine nucleus (Pons)-projecting ALM neurons in C57BL/6J mice. Fifty-nine separate regions from nine major brain areas projecting to the descending pathways of the ALM were identified. Brain-wide quantitative analyses revealed identical whole brain input patterns between these descending pathways. Most inputs to the pathways originated from the ipsilateral side of the brain, with most innervations provided by the cortex and TH. The contralateral side of the brain also sent sparse projections, but these were rare, emanating only from the cortex and cerebellum. Nevertheless, the inputs received by TH-, Med-, SC-, and Pons-projecting ALM neurons had different weights, potentially laying an anatomical foundation for understanding the diverse functions of well-defined descending pathways of the ALM. Our findings provide anatomical information to help elucidate the precise connections and diverse functions of the ALM.NEW & NOTEWORTHY Distinct descending pathways of anterior lateral motor cortex (ALM) share common inputs. These inputs are with varied weights. Most inputs were from the ipsilateral side of brain. Preferential inputs were provided by cortex and thalamus (TH).
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Affiliation(s)
- Tonghui Xu
- Department of Laboratory Animal Science, Fudan University, Shanghai, People's Republic of China
| | - Zitao Jin
- Institute of Life Science, Nanchang University, Nanchang, People's Republic of China
| | - Mei Yang
- Department of Laboratory Animal Science, Fudan University, Shanghai, People's Republic of China
| | - Zhilong Chen
- Key Laboratory of Biomaterials of Guangdong Higher Education Institutes, Department of Biomedical Engineering, Jinan University, Guangzhou, People's Republic of China
- Piedmont Medical Technology Co., Ltd., Zhuhai, People's Republic of China
| | - Huan Xiong
- Department of Neurosurgery, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
- Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu, People's Republic of China
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41
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Schlegel P, Yin Y, Bates AS, Dorkenwald S, Eichler K, Brooks P, Han DS, Gkantia M, Dos Santos M, Munnelly EJ, Badalamente G, Capdevila LS, Sane VA, Pleijzier MW, Tamimi IFM, Dunne CR, Salgarella I, Javier A, Fang S, Perlman E, Kazimiers T, Jagannathan SR, Matsliah A, Sterling AR, Yu SC, McKellar CE, Costa M, Seung HS, Murthy M, Hartenstein V, Bock DD, Jefferis GSXE. Whole-brain annotation and multi-connectome cell typing quantifies circuit stereotypy in Drosophila. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.27.546055. [PMID: 37425808 PMCID: PMC10327018 DOI: 10.1101/2023.06.27.546055] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
The fruit fly Drosophila melanogaster combines surprisingly sophisticated behaviour with a highly tractable nervous system. A large part of the fly's success as a model organism in modern neuroscience stems from the concentration of collaboratively generated molecular genetic and digital resources. As presented in our FlyWire companion paper 1 , this now includes the first full brain connectome of an adult animal. Here we report the systematic and hierarchical annotation of this ~130,000-neuron connectome including neuronal classes, cell types and developmental units (hemilineages). This enables any researcher to navigate this huge dataset and find systems and neurons of interest, linked to the literature through the Virtual Fly Brain database 2 . Crucially, this resource includes 4,552 cell types. 3,094 are rigorous consensus validations of cell types previously proposed in the hemibrain connectome 3 . In addition, we propose 1,458 new cell types, arising mostly from the fact that the FlyWire connectome spans the whole brain, whereas the hemibrain derives from a subvolume. Comparison of FlyWire and the hemibrain showed that cell type counts and strong connections were largely stable, but connection weights were surprisingly variable within and across animals. Further analysis defined simple heuristics for connectome interpretation: connections stronger than 10 unitary synapses or providing >1% of the input to a target cell are highly conserved. Some cell types showed increased variability across connectomes: the most common cell type in the mushroom body, required for learning and memory, is almost twice as numerous in FlyWire as the hemibrain. We find evidence for functional homeostasis through adjustments of the absolute amount of excitatory input while maintaining the excitation-inhibition ratio. Finally, and surprisingly, about one third of the cell types proposed in the hemibrain connectome could not yet be reliably identified in the FlyWire connectome. We therefore suggest that cell types should be defined to be robust to inter-individual variation, namely as groups of cells that are quantitatively more similar to cells in a different brain than to any other cell in the same brain. Joint analysis of the FlyWire and hemibrain connectomes demonstrates the viability and utility of this new definition. Our work defines a consensus cell type atlas for the fly brain and provides both an intellectual framework and open source toolchain for brain-scale comparative connectomics.
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42
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Dura-Bernal S, Neymotin SA, Suter BA, Dacre J, Moreira JVS, Urdapilleta E, Schiemann J, Duguid I, Shepherd GMG, Lytton WW. Multiscale model of primary motor cortex circuits predicts in vivo cell-type-specific, behavioral state-dependent dynamics. Cell Rep 2023; 42:112574. [PMID: 37300831 PMCID: PMC10592234 DOI: 10.1016/j.celrep.2023.112574] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 02/27/2023] [Accepted: 05/12/2023] [Indexed: 06/12/2023] Open
Abstract
Understanding cortical function requires studying multiple scales: molecular, cellular, circuit, and behavioral. We develop a multiscale, biophysically detailed model of mouse primary motor cortex (M1) with over 10,000 neurons and 30 million synapses. Neuron types, densities, spatial distributions, morphologies, biophysics, connectivity, and dendritic synapse locations are constrained by experimental data. The model includes long-range inputs from seven thalamic and cortical regions and noradrenergic inputs. Connectivity depends on cell class and cortical depth at sublaminar resolution. The model accurately predicts in vivo layer- and cell-type-specific responses (firing rates and LFP) associated with behavioral states (quiet wakefulness and movement) and experimental manipulations (noradrenaline receptor blockade and thalamus inactivation). We generate mechanistic hypotheses underlying the observed activity and analyzed low-dimensional population latent dynamics. This quantitative theoretical framework can be used to integrate and interpret M1 experimental data and sheds light on the cell-type-specific multiscale dynamics associated with several experimental conditions and behaviors.
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Affiliation(s)
- Salvador Dura-Bernal
- Department of Physiology and Pharmacology, State University of New York (SUNY) Downstate Health Sciences University, Brooklyn, NY, USA; Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
| | - Samuel A Neymotin
- Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA; Department of Psychiatry, Grossman School of Medicine, New York University (NYU), New York, NY, USA
| | - Benjamin A Suter
- Department of Physiology, Northwestern University, Evanston, IL, USA
| | - Joshua Dacre
- Centre for Discovery Brain Sciences, Edinburgh Medical School: Biomedical Sciences, University of Edinburgh, Edinburgh, UK
| | - Joao V S Moreira
- Department of Physiology and Pharmacology, State University of New York (SUNY) Downstate Health Sciences University, Brooklyn, NY, USA
| | - Eugenio Urdapilleta
- Department of Physiology and Pharmacology, State University of New York (SUNY) Downstate Health Sciences University, Brooklyn, NY, USA
| | - Julia Schiemann
- Centre for Discovery Brain Sciences, Edinburgh Medical School: Biomedical Sciences, University of Edinburgh, Edinburgh, UK; Center for Integrative Physiology and Molecular Medicine, Saarland University, Saarbrücken, Germany
| | - Ian Duguid
- Centre for Discovery Brain Sciences, Edinburgh Medical School: Biomedical Sciences, University of Edinburgh, Edinburgh, UK
| | | | - William W Lytton
- Department of Physiology and Pharmacology, State University of New York (SUNY) Downstate Health Sciences University, Brooklyn, NY, USA; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA; Department of Neurology, Kings County Hospital Center, Brooklyn, NY, USA
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43
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Wang ZA, Chen S, Liu Y, Liu D, Svoboda K, Li N, Druckmann S. Not everything, not everywhere, not all at once: a study of brain-wide encoding of movement. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.08.544257. [PMID: 37333216 PMCID: PMC10274914 DOI: 10.1101/2023.06.08.544257] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Activity related to movement is found throughout sensory and motor regions of the brain. However, it remains unclear how movement-related activity is distributed across the brain and whether systematic differences exist between brain areas. Here, we analyzed movement related activity in brain-wide recordings containing more than 50,000 neurons in mice performing a decision-making task. Using multiple techniques, from markers to deep neural networks, we find that movement-related signals were pervasive across the brain, but systematically differed across areas. Movement-related activity was stronger in areas closer to the motor or sensory periphery. Delineating activity in terms of sensory- and motor-related components revealed finer scale structures of their encodings within brain areas. We further identified activity modulation that correlates with decision-making and uninstructed movement. Our work charts out a largescale map of movement encoding and provides a roadmap for dissecting different forms of movement and decision-making related encoding across multi-regional neural circuits.
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44
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Itoh Y, Sahni V, Shnider SJ, McKee H, Macklis JD. Inter-axonal molecular crosstalk via Lumican proteoglycan sculpts murine cervical corticospinal innervation by distinct subpopulations. Cell Rep 2023; 42:112182. [PMID: 36934325 PMCID: PMC10167627 DOI: 10.1016/j.celrep.2023.112182] [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: 08/16/2021] [Revised: 11/07/2022] [Accepted: 02/14/2023] [Indexed: 03/19/2023] Open
Abstract
How CNS circuits sculpt their axonal arbors into spatially and functionally organized domains is not well understood. Segmental specificity of corticospinal connectivity is an exemplar for such regional specificity of many axon projections. Corticospinal neurons (CSN) innervate spinal and brainstem targets with segmental precision, controlling voluntary movement. Multiple molecularly distinct CSN subpopulations innervate the cervical cord for evolutionarily enhanced precision of forelimb movement. Evolutionarily newer CSNBC-lat exclusively innervate bulbar-cervical targets, while CSNmedial are heterogeneous; distinct subpopulations extend axons to either bulbar-cervical or thoraco-lumbar segments. We identify that Lumican controls balance of cervical innervation between CSNBC-lat and CSNmedial axons during development, which is maintained into maturity. Lumican, an extracellular proteoglycan expressed by CSNBC-lat, non-cell-autonomously suppresses cervical collateralization by multiple CSNmedial subpopulations. This inter-axonal molecular crosstalk between CSN subpopulations controls murine corticospinal circuitry refinement and forelimb dexterity. Such crosstalk is generalizable beyond the corticospinal system for evolutionary incorporation of new neuron populations into preexisting circuitry.
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Affiliation(s)
- Yasuhiro Itoh
- Department of Stem Cell and Regenerative Biology and Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Vibhu Sahni
- Department of Stem Cell and Regenerative Biology and Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Sara J Shnider
- Department of Stem Cell and Regenerative Biology and Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Holly McKee
- Department of Stem Cell and Regenerative Biology and Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Jeffrey D Macklis
- Department of Stem Cell and Regenerative Biology and Center for Brain Science, Harvard University, Cambridge, MA 02138, USA.
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45
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Musall S, Sun XR, Mohan H, An X, Gluf S, Li SJ, Drewes R, Cravo E, Lenzi I, Yin C, Kampa BM, Churchland AK. Pyramidal cell types drive functionally distinct cortical activity patterns during decision-making. Nat Neurosci 2023; 26:495-505. [PMID: 36690900 PMCID: PMC9991922 DOI: 10.1038/s41593-022-01245-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 12/06/2022] [Indexed: 01/25/2023]
Abstract
Understanding how cortical circuits generate complex behavior requires investigating the cell types that comprise them. Functional differences across pyramidal neuron (PyN) types have been observed within cortical areas, but it is not known whether these local differences extend throughout the cortex, nor whether additional differences emerge when larger-scale dynamics are considered. We used genetic and retrograde labeling to target pyramidal tract, intratelencephalic and corticostriatal projection neurons and measured their cortex-wide activity. Each PyN type drove unique neural dynamics, both at the local and cortex-wide scales. Cortical activity and optogenetic inactivation during an auditory decision task revealed distinct functional roles. All PyNs in parietal cortex were recruited during perception of the auditory stimulus, but, surprisingly, pyramidal tract neurons had the largest causal role. In frontal cortex, all PyNs were required for accurate choices but showed distinct choice tuning. Our results reveal that rich, cell-type-specific cortical dynamics shape perceptual decisions.
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Affiliation(s)
- Simon Musall
- Institute of Biological Information Processing (IBI-3), Forschungszentrum Jülich, Jülich, Germany.
- Department of Systems Neurophysiology, Institute for Zoology, RWTH Aachen University, Aachen, Germany.
| | - Xiaonan R Sun
- Cold Spring Harbor Laboratory, Neuroscience, Cold Spring Harbor, New York, NY, USA
- Department of Neurosurgery, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Hemanth Mohan
- Cold Spring Harbor Laboratory, Neuroscience, Cold Spring Harbor, New York, NY, USA
- Department of Neurobiology, Duke University Medical Center, Durham, NC, USA
| | - Xu An
- Cold Spring Harbor Laboratory, Neuroscience, Cold Spring Harbor, New York, NY, USA
- Department of Neurobiology, Duke University Medical Center, Durham, NC, USA
| | - Steven Gluf
- Cold Spring Harbor Laboratory, Neuroscience, Cold Spring Harbor, New York, NY, USA
| | - Shu-Jing Li
- Cold Spring Harbor Laboratory, Neuroscience, Cold Spring Harbor, New York, NY, USA
| | - Rhonda Drewes
- Cold Spring Harbor Laboratory, Neuroscience, Cold Spring Harbor, New York, NY, USA
| | - Emma Cravo
- Department of Systems Neurophysiology, Institute for Zoology, RWTH Aachen University, Aachen, Germany
| | - Irene Lenzi
- Institute of Biological Information Processing (IBI-3), Forschungszentrum Jülich, Jülich, Germany
- Department of Systems Neurophysiology, Institute for Zoology, RWTH Aachen University, Aachen, Germany
| | - Chaoqun Yin
- Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Björn M Kampa
- Department of Systems Neurophysiology, Institute for Zoology, RWTH Aachen University, Aachen, Germany
- JARA Brain, Institute for Neuroscience and Medicine (INM-10), Forschungszentrum Jülich, Jülich, Germany
| | - Anne K Churchland
- Cold Spring Harbor Laboratory, Neuroscience, Cold Spring Harbor, New York, NY, USA.
- Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
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46
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Wang Q, Wang Y, Kuo HC, Xie P, Kuang X, Hirokawa KE, Naeemi M, Yao S, Mallory M, Ouellette B, Lesnar P, Li Y, Ye M, Chen C, Xiong W, Ahmadinia L, El-Hifnawi L, Cetin A, Sorensen SA, Harris JA, Zeng H, Koch C. Regional and cell-type-specific afferent and efferent projections of the mouse claustrum. Cell Rep 2023; 42:112118. [PMID: 36774552 PMCID: PMC10415534 DOI: 10.1016/j.celrep.2023.112118] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 12/17/2022] [Accepted: 01/30/2023] [Indexed: 02/13/2023] Open
Abstract
The claustrum (CLA) is a conspicuous subcortical structure interconnected with cortical and subcortical regions. Its regional anatomy and cell-type-specific connections in the mouse remain not fully determined. Using multimodal reference datasets, we confirmed the delineation of the mouse CLA as a single group of neurons embedded in the agranular insular cortex. We quantitatively investigated brain-wide inputs and outputs of CLA using bulk anterograde and retrograde viral tracing data and single neuron tracing data. We found that the prefrontal module has more cell types projecting to the CLA than other cortical modules, with layer 5 IT neurons predominating. We found nine morphological types of CLA principal neurons that topographically innervate functionally linked cortical targets, preferentially the midline cortical areas, secondary motor area, and entorhinal area. Together, this study provides a detailed wiring diagram of the cell-type-specific connections of the mouse CLA, laying a foundation for studying its functions at the cellular level.
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Affiliation(s)
- Quanxin Wang
- Allen Institute for Brain Science, Seattle, WA 98109, USA.
| | - Yun Wang
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Hsien-Chi Kuo
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Peng Xie
- Institute for Brain and Intelligence, Southeast University, Nanjing, Jiangsu, China
| | - Xiuli Kuang
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, Zhejiang 325000, China
| | | | - Maitham Naeemi
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Shenqin Yao
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Matt Mallory
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Ben Ouellette
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Phil Lesnar
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Yaoyao Li
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, Zhejiang 325000, China
| | - Min Ye
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, Zhejiang 325000, China
| | - Chao Chen
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, Zhejiang 325000, China
| | - Wei Xiong
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, Zhejiang 325000, China
| | | | | | - Ali Cetin
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Julie A Harris
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Christof Koch
- Allen Institute for Brain Science, Seattle, WA 98109, USA.
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Brandalise F, Kalmbach BE, Cook EP, Brager DH. Impaired dendritic spike generation in the Fragile X prefrontal cortex is due to loss of dendritic sodium channels. J Physiol 2023; 601:831-845. [PMID: 36625320 PMCID: PMC9970745 DOI: 10.1113/jp283311] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 01/04/2023] [Indexed: 01/11/2023] Open
Abstract
Patients with Fragile X syndrome, the leading monogenetic cause of autism, suffer from impairments related to the prefrontal cortex, including working memory and attention. Synaptic inputs to the distal dendrites of layer 5 pyramidal neurons in the prefrontal cortex have a weak influence on the somatic membrane potential. To overcome this filtering, distal inputs are transformed into local dendritic Na+ spikes, which propagate to the soma and trigger action potential output. Layer 5 extratelencephalic (ET) prefrontal cortex (PFC) neurons project to the brainstem and various thalamic nuclei and are therefore well positioned to integrate task-relevant sensory signals and guide motor actions. We used current clamp and outside-out patch clamp recording to investigate dendritic spike generation in ET neurons from male wild-type and Fmr1 knockout (FX) mice. The threshold for dendritic spikes was more depolarized in FX neurons compared to wild-type. Analysis of voltage responses to simulated in vivo 'noisy' current injections showed that a larger dendritic input stimulus was required to elicit dendritic spikes in FX ET dendrites compared to wild-type. Patch clamp recordings revealed that the dendritic Na+ conductance was significantly smaller in FX ET dendrites. Taken together, our results suggest that the generation of Na+ -dependent dendritic spikes is impaired in ET neurons of the PFC in FX mice. Considering our prior findings that somatic D-type K+ and dendritic hyperpolarization-activated cyclic nucleotide-gated-channel function is reduced in ET neurons, we suggest that dendritic integration by PFC circuits is fundamentally altered in Fragile X syndrome. KEY POINTS: Dendritic spike threshold is depolarized in layer 5 prefrontal cortex neurons in Fmr1 knockout (FX) mice. Simultaneous somatic and dendritic recording with white noise current injections revealed that larger dendritic stimuli were required to elicit dendritic spikes in FX extratelencephalic (ET) neurons. Outside-out patch clamp recording revealed that dendritic sodium conductance density was lower in FX ET neurons.
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Affiliation(s)
- Federico Brandalise
- Center for Learning and Memory, University of Texas at Austin, Austin, TX 78712 USA
- Department of Neuroscience University of Texas at Austin, Austin, TX 78712 USA
- Current address: Department of Biosciences, University of Milan, Milano Italy
| | - Brian E. Kalmbach
- Center for Learning and Memory, University of Texas at Austin, Austin, TX 78712 USA
- Department of Neuroscience University of Texas at Austin, Austin, TX 78712 USA
- Current address: Allen Institute for Brain Science, Seattle, WA and Department of Physiology and Biophysics, University of Washington
| | - Erik P. Cook
- Department of Physiology, McGill University, Montreal QC, Canada
| | - Darrin H. Brager
- Center for Learning and Memory, University of Texas at Austin, Austin, TX 78712 USA
- Department of Neuroscience University of Texas at Austin, Austin, TX 78712 USA
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48
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Banerjee A, Chen F, Druckmann S, Long MA. Neural dynamics in the rodent motor cortex enables flexible control of vocal timing. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.23.525252. [PMID: 36747850 PMCID: PMC9900850 DOI: 10.1101/2023.01.23.525252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Neocortical activity is thought to mediate voluntary control over vocal production, but the underlying neural mechanisms remain unclear. In a highly vocal rodent, the Alston's singing mouse, we investigate neural dynamics in the orofacial motor cortex (OMC), a structure critical for vocal behavior. We first describe neural activity that is modulated by component notes (approx. 100 ms), likely representing sensory feedback. At longer timescales, however, OMC neurons exhibit diverse and often persistent premotor firing patterns that stretch or compress with song duration (approx. 10 s). Using computational modeling, we demonstrate that such temporal scaling, acting via downstream motor production circuits, can enable vocal flexibility. These results provide a framework for studying hierarchical control circuits, a common design principle across many natural and artificial systems.
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Affiliation(s)
- Arkarup Banerjee
- NYU Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
- Department of Otolaryngology, New York University Langone Health, New York, NY 10016, USA
- Center for Neural Science, New York University, New York, NY 10003, USA
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Feng Chen
- Department of Applied Physics, Stanford University, Stanford, CA 94305, USA
| | - Shaul Druckmann
- Department of Neuroscience, Stanford University, Stanford, CA 94304, USA
| | - Michael A Long
- NYU Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
- Department of Otolaryngology, New York University Langone Health, New York, NY 10016, USA
- Center for Neural Science, New York University, New York, NY 10003, USA
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
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49
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Yang W, Kanodia H, Arber S. Structural and functional map for forelimb movement phases between cortex and medulla. Cell 2023; 186:162-177.e18. [PMID: 36608651 PMCID: PMC9842395 DOI: 10.1016/j.cell.2022.12.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 10/10/2022] [Accepted: 12/05/2022] [Indexed: 01/07/2023]
Abstract
The cortex influences movement by widespread top-down projections to many nervous system regions. Skilled forelimb movements require brainstem circuitry in the medulla; however, the logic of cortical interactions with these neurons remains unexplored. Here, we reveal a fine-grained anatomical and functional map between anterior cortex (AC) and medulla in mice. Distinct cortical regions generate three-dimensional synaptic columns tiling the lateral medulla, topographically matching the dorso-ventral positions of postsynaptic neurons tuned to distinct forelimb action phases. Although medial AC (MAC) terminates ventrally and connects to forelimb-reaching-tuned neurons and its silencing impairs reaching, lateral AC (LAC) influences dorsally positioned neurons tuned to food handling, and its silencing impairs handling. Cortico-medullary neurons also extend collaterals to other subcortical structures through a segregated channel interaction logic. Our findings reveal a precise alignment between cortical location, its function, and specific forelimb-action-tuned medulla neurons, thereby clarifying interaction principles between these two key structures and beyond.
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Affiliation(s)
- Wuzhou Yang
- Biozentrum, Department of Cell Biology, University of Basel, 4056 Basel, Switzerland,Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland
| | - Harsh Kanodia
- Biozentrum, Department of Cell Biology, University of Basel, 4056 Basel, Switzerland,Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland
| | - Silvia Arber
- Biozentrum, Department of Cell Biology, University of Basel, 4056 Basel, Switzerland,Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland,Corresponding author
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50
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Bolding KA, Franks KM. Electrophysiological Recordings from Identified Cell Types in the Olfactory Cortex of Awake Mice. Methods Mol Biol 2023; 2710:209-221. [PMID: 37688735 DOI: 10.1007/978-1-0716-3425-7_16] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/11/2023]
Abstract
Neural circuits consist of a myriad of distinct cell types, each with specific intrinsic properties and patterns of synaptic connectivity, which transform neural input and convey this information to downstream targets. Understanding how different features of an odor stimulus are encoded and relayed to their appropriate targets will require selective identification and manipulation of these different elements of the circuit. Here, we describe methods to obtain dense, extracellular electrophysiological recordings of odor-evoked activity in olfactory (piriform) cortex of awake, head-fixed mice, and optogenetic tools and procedures to identify genetically defined cell types within this circuit.
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Affiliation(s)
- Kevin A Bolding
- Department of Neurobiology, Duke University, Durham, NC, USA
- Monell Chemical Senses Center, Philadelphia, PA, USA
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
| | - Kevin M Franks
- Department of Neurobiology, Duke University, Durham, NC, USA.
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