1
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Mountoufaris G, Nair A, Yang B, Kim DW, Vinograd A, Kim S, Linderman SW, Anderson DJ. A line attractor encoding a persistent internal state requires neuropeptide signaling. Cell 2024:S0092-8674(24)00906-1. [PMID: 39191257 DOI: 10.1016/j.cell.2024.08.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 06/23/2024] [Accepted: 08/07/2024] [Indexed: 08/29/2024]
Abstract
Internal states drive survival behaviors, but their neural implementation is poorly understood. Recently, we identified a line attractor in the ventromedial hypothalamus (VMH) that represents a state of aggressiveness. Line attractors can be implemented by recurrent connectivity or neuromodulatory signaling, but evidence for the latter is scant. Here, we demonstrate that neuropeptidergic signaling is necessary for line attractor dynamics in this system by using cell-type-specific CRISPR-Cas9-based gene editing combined with single-cell calcium imaging. Co-disruption of receptors for oxytocin and vasopressin in adult VMH Esr1+ neurons that control aggression diminished attack, reduced persistent neural activity, and eliminated line attractor dynamics while only slightly reducing overall neural activity and sex- or behavior-specific tuning. These data identify a requisite role for neuropeptidergic signaling in implementing a behaviorally relevant line attractor in mammals. Our approach should facilitate mechanistic studies in neuroscience that bridge different levels of biological function and abstraction.
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Affiliation(s)
- George Mountoufaris
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA; Tianqiao and Chrissy Chen Institute for Neuroscience, California Institute of Technology, Pasadena, CA, USA
| | - Aditya Nair
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA; Program in Computation and Neural Systems, California Institute of Technology, Pasadena, CA, USA; Tianqiao and Chrissy Chen Institute for Neuroscience, California Institute of Technology, Pasadena, CA, USA
| | - Bin Yang
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA; Tianqiao and Chrissy Chen Institute for Neuroscience, California Institute of Technology, Pasadena, CA, USA
| | - Dong-Wook Kim
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA; Tianqiao and Chrissy Chen Institute for Neuroscience, California Institute of Technology, Pasadena, CA, USA
| | - Amit Vinograd
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA; Tianqiao and Chrissy Chen Institute for Neuroscience, California Institute of Technology, Pasadena, CA, USA
| | - Samuel Kim
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA; Tianqiao and Chrissy Chen Institute for Neuroscience, California Institute of Technology, Pasadena, CA, USA
| | - Scott W Linderman
- Department of Statistics, Stanford University, Stanford, CA 94305, USA; Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA 94305, USA
| | - David J Anderson
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA; Tianqiao and Chrissy Chen Institute for Neuroscience, California Institute of Technology, Pasadena, CA, USA; Howard Hughes Medical Institute, Pasadena, CA 91001, USA.
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2
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Michel L, Molina P, Mameli M. The behavioral relevance of a modular organization in the lateral habenula. Neuron 2024; 112:2669-2685. [PMID: 38772374 DOI: 10.1016/j.neuron.2024.04.026] [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: 02/23/2024] [Revised: 04/19/2024] [Accepted: 04/23/2024] [Indexed: 05/23/2024]
Abstract
Behavioral strategies for survival rely on the updates the brain continuously makes based on the surrounding environment. External stimuli-neutral, positive, and negative-relay core information to the brain, where a complex anatomical network rapidly organizes actions, including approach or escape, and regulates emotions. Human neuroimaging and physiology in nonhuman primates, rodents, and teleosts suggest a pivotal role of the lateral habenula in translating external information into survival behaviors. Here, we review the literature describing how discrete habenular modules-reflecting the molecular signatures, anatomical connectivity, and functional components-are recruited by environmental stimuli and cooperate to prompt specific behavioral outcomes. We argue that integration of these findings in the context of valence processing for reinforcing or discouraging behaviors is necessary, offering a compelling model to guide future work.
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Affiliation(s)
- Leo Michel
- The Department of Fundamental Neuroscience, The University of Lausanne, 1005 Lausanne, Switzerland
| | - Patricia Molina
- The Department of Fundamental Neuroscience, The University of Lausanne, 1005 Lausanne, Switzerland
| | - Manuel Mameli
- The Department of Fundamental Neuroscience, The University of Lausanne, 1005 Lausanne, Switzerland; Inserm, UMR-S 839, 75005 Paris, France.
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3
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Zhang Z, Zhang W, Fang Y, Wang N, Liu G, Zou N, Song Z, Liu H, Wang L, Xiao Q, Zhao J, Wang Y, Lei T, Zhang C, Liu X, Zhang B, Luo F, Xia J, He C, Hu Z, Ren S, Zhao H. A potentiation of REM sleep-active neurons in the lateral habenula may be responsible for the sleep disturbance in depression. Curr Biol 2024; 34:3287-3300.e6. [PMID: 38944036 DOI: 10.1016/j.cub.2024.05.075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 03/25/2024] [Accepted: 05/31/2024] [Indexed: 07/01/2024]
Abstract
Psychiatric disorders with dysfunction of the lateral habenula (LHb) show sleep disturbance, especially a disinhibition of rapid eye movement (REM) sleep in major depression. However, the role of LHb in physiological sleep control and how LHb contributes to sleep disturbance in major depression remain elusive. Here, we found that functional manipulations of LHb glutamatergic neurons bidirectionally modulated both non-REM (NREM) sleep and REM sleep. Activity recording revealed heterogeneous activity patterns of LHb neurons across sleep/wakefulness cycles, but LHb neurons were preferentially active during REM sleep. Using an activity-dependent tagging method, we selectively labeled a population of REM sleep-active LHb neurons and demonstrated that these neurons specifically promoted REM sleep. Neural circuit studies showed that LHb neurons regulated REM sleep via projections to the ventral tegmental area but not to the rostromedial tegmental nucleus. Furthermore, we found that the increased REM sleep in a depression mouse model was associated with a potentiation of REM sleep-active LHb neurons, including an increased proportion, elevated spike firing, and altered activity mode. Importantly, inhibition of REM sleep-active LHb neurons not only attenuated the increased REM sleep but also alleviated depressive-like behaviors in a depression mouse model. Thus, our results demonstrated that REM sleep-active LHb neurons selectively promoted REM sleep, and a potentiation of these neurons contributed to depression-associated sleep disturbance.
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Affiliation(s)
- Zehui Zhang
- Department of Physiology, College of Basic Medical Sciences, Jilin University, Changchun 130021, China
| | - Wei Zhang
- Department of Physiology, College of Basic Medical Sciences, Army Medical University, Chongqing 400038, China
| | - Yuanyuan Fang
- Department of Physiology, College of Basic Medical Sciences, Army Medical University, Chongqing 400038, China; Department of Anaesthesiology, Zhongnan Hospital, Wuhan University, Wuhan, Hubei 430071, China
| | - Na Wang
- Department of Physiology, College of Basic Medical Sciences, Army Medical University, Chongqing 400038, China
| | - Guoying Liu
- Chongqing Institute for Brain and Intelligence, Guangyang Bay Laboratory, Chongqing 400064, China
| | - Nan Zou
- Chongqing Institute for Brain and Intelligence, Guangyang Bay Laboratory, Chongqing 400064, China
| | - Zhenbo Song
- Department of Physiology, College of Basic Medical Sciences, Army Medical University, Chongqing 400038, China
| | - Hanshu Liu
- Department of Physiology, College of Basic Medical Sciences, Army Medical University, Chongqing 400038, China; Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, China
| | - Longshuo Wang
- Department of Physiology, College of Basic Medical Sciences, Jilin University, Changchun 130021, China
| | - Qin Xiao
- Department of Physiology, College of Basic Medical Sciences, Army Medical University, Chongqing 400038, China
| | - Juanjuan Zhao
- Department of Physiology, College of Basic Medical Sciences, Army Medical University, Chongqing 400038, China
| | - Yaling Wang
- Department of Physiology, College of Basic Medical Sciences, Army Medical University, Chongqing 400038, China
| | - Ting Lei
- Department of Physiology, College of Basic Medical Sciences, Jilin University, Changchun 130021, China
| | - Cai Zhang
- Department of Physiology, College of Basic Medical Sciences, Army Medical University, Chongqing 400038, China
| | - Xiaofeng Liu
- Department of Physiology, College of Basic Medical Sciences, Jilin University, Changchun 130021, China
| | - Beilin Zhang
- Department of Physiology, College of Basic Medical Sciences, Jilin University, Changchun 130021, China
| | - Fenlan Luo
- Department of Physiology, College of Basic Medical Sciences, Army Medical University, Chongqing 400038, China
| | - Jianxia Xia
- Department of Physiology, College of Basic Medical Sciences, Army Medical University, Chongqing 400038, China
| | - Chao He
- Department of Physiology, College of Basic Medical Sciences, Army Medical University, Chongqing 400038, China
| | - Zhian Hu
- Department of Physiology, College of Basic Medical Sciences, Army Medical University, Chongqing 400038, China; Chongqing Institute for Brain and Intelligence, Guangyang Bay Laboratory, Chongqing 400064, China.
| | - Shuancheng Ren
- Department of Physiology, College of Basic Medical Sciences, Army Medical University, Chongqing 400038, China.
| | - Hua Zhao
- Department of Physiology, College of Basic Medical Sciences, Jilin University, Changchun 130021, China.
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4
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Liu Y, Wang Y, Zhao ZD, Xie G, Zhang C, Chen R, Zhang Y. A subset of dopamine receptor-expressing neurons in the nucleus accumbens controls feeding and energy homeostasis. Nat Metab 2024; 6:1616-1631. [PMID: 39147933 DOI: 10.1038/s42255-024-01100-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Accepted: 07/09/2024] [Indexed: 08/17/2024]
Abstract
Orchestrating complex behaviors, such as approaching and consuming food, is critical for survival. In addition to hypothalamus neuronal circuits, the nucleus accumbens (NAc) also controls appetite and satiety. However, specific neuronal subtypes of the NAc that are involved and how the humoral and neuronal signals coordinate to regulate feeding remain incompletely understood. Here we decipher the spatial diversity of neuron subtypes of the NAc shell (NAcSh) and define a dopamine receptor D1-expressing and Serpinb2-expressing subtype controlling food consumption in male mice. Chemogenetics and optogenetics-mediated regulation of Serpinb2+ neurons bidirectionally regulate food seeking and consumption specifically. Circuitry stimulation reveals that the NAcShSerpinb2→LHLepR projection controls refeeding and can overcome leptin-mediated feeding suppression. Furthermore, NAcSh Serpinb2+ neuron ablation reduces food intake and upregulates energy expenditure, resulting in reduced bodyweight gain. Our study reveals a neural circuit consisting of a molecularly distinct neuronal subtype that bidirectionally regulates energy homeostasis, providing a potential therapeutic target for eating disorders.
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Affiliation(s)
- Yiqiong Liu
- Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA, USA
- Program in Cellular and Molecular Medicine, Boston Children's Hospital, Boston, MA, USA
- Division of Hematology/Oncology, Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA
| | - Ying Wang
- Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA, USA
- Program in Cellular and Molecular Medicine, Boston Children's Hospital, Boston, MA, USA
- Division of Hematology/Oncology, Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA
| | - Zheng-Dong Zhao
- Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA, USA
- Program in Cellular and Molecular Medicine, Boston Children's Hospital, Boston, MA, USA
- Division of Hematology/Oncology, Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA
| | - Guoguang Xie
- Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA, USA
- Program in Cellular and Molecular Medicine, Boston Children's Hospital, Boston, MA, USA
- Division of Hematology/Oncology, Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA
| | - Chao Zhang
- Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA, USA
- Program in Cellular and Molecular Medicine, Boston Children's Hospital, Boston, MA, USA
- Division of Hematology/Oncology, Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA
| | - Renchao Chen
- Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA, USA
- Program in Cellular and Molecular Medicine, Boston Children's Hospital, Boston, MA, USA
- Division of Hematology/Oncology, Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA
| | - Yi Zhang
- Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA, USA.
- Program in Cellular and Molecular Medicine, Boston Children's Hospital, Boston, MA, USA.
- Division of Hematology/Oncology, Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA.
- Department of Genetics, Harvard Medical School, Boston, MA, USA.
- Harvard Stem Cell Institute, Boston, MA, USA.
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5
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Vincent JP, Economo MN. Assessing Cross-Contamination in Spike-Sorted Electrophysiology Data. eNeuro 2024; 11:ENEURO.0554-23.2024. [PMID: 39095090 DOI: 10.1523/eneuro.0554-23.2024] [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: 12/30/2023] [Revised: 07/06/2024] [Accepted: 07/20/2024] [Indexed: 08/04/2024] Open
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 long-standing method of assessing the false discovery rate (FDR) of spike sorting-the rate at which spikes are assigned to the wrong cluster-has been the rate of interspike 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, remains limited. Here, we describe an analytical solution that can be used to predict FDR from the ISI violation rate (ISIv). 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 ISIv and FDR is highly nonlinear, with additional dependencies on firing frequency, the correlation in activity between neurons, and contaminant neuron count. Predicted median FDRs in public datasets recorded in mice were found to range from 3.1 to 50.0%. We found 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, Massachusetts 02215
- Center for Neurophotonics, Boston University, Boston, Massachusetts 02215
| | - Michael N Economo
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215
- Center for Neurophotonics, Boston University, Boston, Massachusetts 02215
- Center for Systems Neuroscience, Boston University, Boston, Massachusetts 02215
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6
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Wang Z, Yu J, Zhai M, Wang Z, Sheng K, Zhu Y, Wang T, Liu M, Wang L, Yan M, Zhang J, Xu Y, Wang X, Ma L, Hu W, Cheng H. System-level time computation and representation in the suprachiasmatic nucleus revealed by large-scale calcium imaging and machine learning. Cell Res 2024; 34:493-503. [PMID: 38605178 PMCID: PMC11217450 DOI: 10.1038/s41422-024-00956-x] [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: 10/31/2023] [Accepted: 03/28/2024] [Indexed: 04/13/2024] Open
Abstract
The suprachiasmatic nucleus (SCN) is the mammalian central circadian pacemaker with heterogeneous neurons acting in concert while each neuron harbors a self-sustained molecular clockwork. Nevertheless, how system-level SCN signals encode time of the day remains enigmatic. Here we show that population-level Ca2+ signals predict hourly time, via a group decision-making mechanism coupled with a spatially modular time feature representation in the SCN. Specifically, we developed a high-speed dual-view two-photon microscope for volumetric Ca2+ imaging of up to 9000 GABAergic neurons in adult SCN slices, and leveraged machine learning methods to capture emergent properties from multiscale Ca2+ signals as a whole. We achieved hourly time prediction by polling random cohorts of SCN neurons, reaching 99.0% accuracy at a cohort size of 900. Further, we revealed that functional neuron subtypes identified by contrastive learning tend to aggregate separately in the SCN space, giving rise to bilaterally symmetrical ripple-like modular patterns. Individual modules represent distinctive time features, such that a module-specifically learned time predictor can also accurately decode hourly time from random polling of the same module. These findings open a new paradigm in deciphering the design principle of the biological clock at the system level.
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Affiliation(s)
- Zichen Wang
- National Biomedical Imaging Center, State Key Laboratory of Membrane Biology, Institute of Molecular Medicine, Peking-Tsinghua Center for Life Sciences, College of Future Technology, Peking University, Beijing, China
- Research Unit of Mitochondria in Brain Diseases, Chinese Academy of Medical Sciences, PKU-Nanjing Institute of Translational Medicine, Nanjing, Jiangsu, China
| | - Jing Yu
- National Biomedical Imaging Center, State Key Laboratory of Membrane Biology, Institute of Molecular Medicine, Peking-Tsinghua Center for Life Sciences, College of Future Technology, Peking University, Beijing, China
- Research Unit of Mitochondria in Brain Diseases, Chinese Academy of Medical Sciences, PKU-Nanjing Institute of Translational Medicine, Nanjing, Jiangsu, China
| | - Muyue Zhai
- National Biomedical Imaging Center, State Key Laboratory of Membrane Biology, Institute of Molecular Medicine, Peking-Tsinghua Center for Life Sciences, College of Future Technology, Peking University, Beijing, China
| | - Zehua Wang
- Wangxuan Institute of Computer Technology, Peking University, Beijing, China
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Kaiwen Sheng
- Beijing Academy of Artificial Intelligence, Beijing, China
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Yu Zhu
- Beijing Academy of Artificial Intelligence, Beijing, China
| | - Tianyu Wang
- National Biomedical Imaging Center, State Key Laboratory of Membrane Biology, Institute of Molecular Medicine, Peking-Tsinghua Center for Life Sciences, College of Future Technology, Peking University, Beijing, China
| | - Mianzhi Liu
- National Biomedical Imaging Center, State Key Laboratory of Membrane Biology, Institute of Molecular Medicine, Peking-Tsinghua Center for Life Sciences, College of Future Technology, Peking University, Beijing, China
| | - Lu Wang
- National Biomedical Imaging Center, State Key Laboratory of Membrane Biology, Institute of Molecular Medicine, Peking-Tsinghua Center for Life Sciences, College of Future Technology, Peking University, Beijing, China
| | - Miao Yan
- National Biomedical Imaging Center, State Key Laboratory of Membrane Biology, Institute of Molecular Medicine, Peking-Tsinghua Center for Life Sciences, College of Future Technology, Peking University, Beijing, China
| | - Jue Zhang
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- College of Engineering, Peking University, Beijing, China
| | - Ying Xu
- Jiangsu Key Laboratory of Neuropsychiatric Diseases and Cambridge-Su Genomic Resource Center, Medical School of Soochow University, Suzhou, Jiangsu, China
| | - Xianhua Wang
- National Biomedical Imaging Center, State Key Laboratory of Membrane Biology, Institute of Molecular Medicine, Peking-Tsinghua Center for Life Sciences, College of Future Technology, Peking University, Beijing, China
- Research Unit of Mitochondria in Brain Diseases, Chinese Academy of Medical Sciences, PKU-Nanjing Institute of Translational Medicine, Nanjing, Jiangsu, China
| | - Lei Ma
- National Biomedical Imaging Center, State Key Laboratory of Membrane Biology, Institute of Molecular Medicine, Peking-Tsinghua Center for Life Sciences, College of Future Technology, Peking University, Beijing, China.
- Beijing Academy of Artificial Intelligence, Beijing, China.
| | - Wei Hu
- Wangxuan Institute of Computer Technology, Peking University, Beijing, China.
| | - Heping Cheng
- National Biomedical Imaging Center, State Key Laboratory of Membrane Biology, Institute of Molecular Medicine, Peking-Tsinghua Center for Life Sciences, College of Future Technology, Peking University, Beijing, China.
- Research Unit of Mitochondria in Brain Diseases, Chinese Academy of Medical Sciences, PKU-Nanjing Institute of Translational Medicine, Nanjing, Jiangsu, China.
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7
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Piet A, Ponvert N, Ollerenshaw D, Garrett M, Groblewski PA, Olsen S, Koch C, Arkhipov A. Behavioral strategy shapes activation of the Vip-Sst disinhibitory circuit in visual cortex. Neuron 2024; 112:1876-1890.e4. [PMID: 38447579 PMCID: PMC11156560 DOI: 10.1016/j.neuron.2024.02.008] [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: 05/31/2023] [Revised: 11/17/2023] [Accepted: 02/08/2024] [Indexed: 03/08/2024]
Abstract
In complex environments, animals can adopt diverse strategies to find rewards. How distinct strategies differentially engage brain circuits is not well understood. Here, we investigate this question, focusing on the cortical Vip-Sst disinhibitory circuit between vasoactive intestinal peptide-postive (Vip) interneurons and somatostatin-positive (Sst) interneurons. We characterize the behavioral strategies used by mice during a visual change detection task. Using a dynamic logistic regression model, we find that individual mice use mixtures of a visual comparison strategy and a statistical timing strategy. Separately, mice also have periods of task engagement and disengagement. Two-photon calcium imaging shows large strategy-dependent differences in neural activity in excitatory, Sst inhibitory, and Vip inhibitory cells in response to both image changes and image omissions. In contrast, task engagement has limited effects on neural population activity. We find that the diversity of neural correlates of strategy can be understood parsimoniously as the increased activation of the Vip-Sst disinhibitory circuit during the visual comparison strategy, which facilitates task-appropriate responses.
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Affiliation(s)
- Alex Piet
- Allen Institute, Mindscope Program, Seattle, WA, USA.
| | - Nick Ponvert
- Allen Institute, Mindscope Program, Seattle, WA, USA
| | | | | | | | - Shawn Olsen
- Allen Institute, Mindscope Program, Seattle, WA, USA
| | - Christof Koch
- Allen Institute, Mindscope Program, Seattle, WA, USA
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8
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Vinograd A, Nair A, Linderman SW, Anderson DJ. Intrinsic Dynamics and Neural Implementation of a Hypothalamic Line Attractor Encoding an Internal Behavioral State. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.21.595051. [PMID: 38826298 PMCID: PMC11142118 DOI: 10.1101/2024.05.21.595051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Line attractors are emergent population dynamics hypothesized to encode continuous variables such as head direction and internal states. In mammals, direct evidence of neural implementation of a line attractor has been hindered by the challenge of targeting perturbations to specific neurons within contributing ensembles. Estrogen receptor type 1 (Esr1)-expressing neurons in the ventrolateral subdivision of the ventromedial hypothalamus (VMHvl) show line attractor dynamics in male mice during fighting. We hypothesized that these dynamics may encode continuous variation in the intensity of an internal aggressive state. Here, we report that these neurons also show line attractor dynamics in head-fixed mice observing aggression. We exploit this finding to identify and perturb line attractor-contributing neurons using 2-photon calcium imaging and holographic optogenetic perturbations. On-manifold perturbations demonstrate that integration and persistent activity are intrinsic properties of these neurons which drive the system along the line attractor, while transient off-manifold perturbations reveal rapid relaxation back into the attractor. Furthermore, stimulation and imaging reveal selective functional connectivity among attractor-contributing neurons. Intriguingly, individual differences among mice in line attractor stability were correlated with the degree of functional connectivity among contributing neurons. Mechanistic modelling indicates that dense subnetwork connectivity and slow neurotransmission are required to explain our empirical findings. Our work bridges circuit and manifold paradigms, shedding light on the intrinsic and operational dynamics of a behaviorally relevant mammalian line attractor.
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Affiliation(s)
- Amit Vinograd
- Division of Biology and Biological Engineering, California Institute of Technology; Pasadena, USA
- Tianqiao and Chrissy Chen Institute for Neuroscience Caltech; Pasadena, USA
- Howard Hughes Medical Institute; Chevy Chase, USA
| | - Aditya Nair
- Division of Biology and Biological Engineering, California Institute of Technology; Pasadena, USA
- Tianqiao and Chrissy Chen Institute for Neuroscience Caltech; Pasadena, USA
- Howard Hughes Medical Institute; Chevy Chase, USA
| | - Scott W. Linderman
- Department of Statistics, Stanford University, Stanford, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, USA
| | - David J. Anderson
- Division of Biology and Biological Engineering, California Institute of Technology; Pasadena, USA
- Tianqiao and Chrissy Chen Institute for Neuroscience Caltech; Pasadena, USA
- Howard Hughes Medical Institute; Chevy Chase, USA
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9
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Groos D, Helmchen F. The lateral habenula: A hub for value-guided behavior. Cell Rep 2024; 43:113968. [PMID: 38522071 DOI: 10.1016/j.celrep.2024.113968] [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: 10/30/2023] [Revised: 01/20/2024] [Accepted: 02/29/2024] [Indexed: 03/26/2024] Open
Abstract
The habenula is an evolutionarily highly conserved diencephalic brain region divided into two major parts, medial and lateral. Over the past two decades, studies of the lateral habenula (LHb), in particular, have identified key functions in value-guided behavior in health and disease. In this review, we focus on recent insights into LHb connectivity and its functional relevance for different types of aversive and appetitive value-guided behavior. First, we give an overview of the anatomical organization of the LHb and its main cellular composition. Next, we elaborate on how distinct LHb neuronal subpopulations encode aversive and appetitive stimuli and on their involvement in more complex decision-making processes. Finally, we scrutinize the afferent and efferent connections of the LHb and discuss their functional implications for LHb-dependent behavior. A deepened understanding of distinct LHb circuit components will substantially contribute to our knowledge of value-guided behavior.
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Affiliation(s)
- Dominik Groos
- Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich, Zurich, Switzerland.
| | - Fritjof Helmchen
- Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich, Zurich, Switzerland; University Research Priority Program (URPP), Adaptive Brain Circuits in Development and Learning, University of Zurich, Zurich, Switzerland
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10
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Huang T, Guo X, Huang X, Yi C, Cui Y, Dong Y. Input-output specific orchestration of aversive valence in lateral habenula during stress dynamics. J Zhejiang Univ Sci B 2024:1-11. [PMID: 38616136 DOI: 10.1631/jzus.b2300933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Accepted: 01/14/2024] [Indexed: 04/16/2024]
Abstract
Stress has been considered as a major risk factor for depressive disorders, triggering depression onset via inducing persistent dysfunctions in specialized brain regions and neural circuits. Among various regions across the brain, the lateral habenula (LHb) serves as a critical hub for processing aversive information during the dynamic process of stress accumulation, thus having been implicated in the pathogenesis of depression. LHb neurons integrate aversive valence conveyed by distinct upstream inputs, many of which selectively innervate the medial part (LHbM) or lateral part (LHbL) of LHb. LHb subregions also separately assign aversive valence via dissociable projections to the downstream targets in the midbrain which provides feedback loops. Despite these strides, the spatiotemporal dynamics of LHb-centric neural circuits remain elusive during the progression of depression-like state under stress. In this review, we attempt to describe a framework in which LHb orchestrates aversive valence via the input-output specific neuronal architecture. Notably, a physiological form of Hebbian plasticity in LHb under multiple stressors has been unveiled to incubate neuronal hyperactivity in an input-specific manner, which causally encodes chronic stress experience and drives depression onset. Collectively, the recent progress and future efforts in elucidating LHb circuits shed light on early interventions and circuit-specific antidepressant therapies.
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Affiliation(s)
- Taida Huang
- Department of Neurology and International Institutes of Medicine, the Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu 322000, China
- Department of Neurology of Sir Run Run Shaw Hospital and School of Brain Science and Brain Medicine, Zhejiang University School of Medicine, Hangzhou 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Science and Brain-Machine Integration, Zhejiang University, Hangzhou 310058, China
- Research Centre, the Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen 518107, China
| | - Xiaonan Guo
- Department of Neurology of Sir Run Run Shaw Hospital and School of Brain Science and Brain Medicine, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Xiaomin Huang
- Research Centre, the Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen 518107, China
| | - Chenju Yi
- Research Centre, the Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen 518107, China.
- Guangdong Provincial Key Laboratory of Brain Function and Disease, Guangzhou 510080, China.
- Shenzhen Key Laboratory of Chinese Medicine Active Substance Screening and Translational Research, Shenzhen 518107, China.
| | - Yihui Cui
- Department of Neurology of Sir Run Run Shaw Hospital and School of Brain Science and Brain Medicine, Zhejiang University School of Medicine, Hangzhou 310058, China. ,
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Science and Brain-Machine Integration, Zhejiang University, Hangzhou 310058, China. ,
| | - Yiyan Dong
- Department of Neurology and International Institutes of Medicine, the Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu 322000, China. ,
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11
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Liu Y, Zhao ZD, Xie G, Chen R, Zhang Y. A molecularly defined NAcSh D1 subtype controls feeding and energy homeostasis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.02.27.530275. [PMID: 36909586 PMCID: PMC10002697 DOI: 10.1101/2023.02.27.530275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/04/2023]
Abstract
Orchestrating complex behavioral states, such as approach and consumption of food, is critical for survival. In addition to hypothalamus neuronal circuits, the nucleus accumbens (NAc) also plays an important role in controlling appetite and satiety in responses to changing external stimuli. However, the specific neuronal subtypes of NAc involved as well as how the humoral and neuronal signals coordinate to regulate feeding remain incompletely understood. Here, we deciphered the spatial diversity of neuron subtypes of the NAc shell (NAcSh) and defined a dopamine receptor D1(Drd1)- and Serpinb2-expressing subtype located in NAcSh encoding food consumption. Chemogenetics- and optogenetics-mediated regulation of Serpinb2 + neurons bidirectionally regulates food seeking and consumption specifically. Circuitry stimulation revealed the NAcSh Serpinb2 →LH LepR projection controls refeeding and can overcome leptin-mediated feeding suppression. Furthermore, NAcSh Serpinb2 + neuron ablation reduces food intake and upregulates energy expenditure resulting in body weight loss. Together, our study reveals a neural circuit consisted of molecularly distinct neuronal subtype that bidirectionally regulates energy homeostasis, which can serve as a potential therapeutic target for eating disorders.
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Affiliation(s)
- Yiqiong Liu
- Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, Massachusetts 02115, USA
- Program in Cellular and Molecular Medicine, Boston Children’s Hospital, Boston, Massachusetts 02115, USA
- Division of Hematology/Oncology, Department of Pediatrics, Boston Children’s Hospital, Boston, Massachusetts 02115, USA
| | - Zheng-dong Zhao
- Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, Massachusetts 02115, USA
- Program in Cellular and Molecular Medicine, Boston Children’s Hospital, Boston, Massachusetts 02115, USA
- Division of Hematology/Oncology, Department of Pediatrics, Boston Children’s Hospital, Boston, Massachusetts 02115, USA
| | - Guoguang Xie
- Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, Massachusetts 02115, USA
- Program in Cellular and Molecular Medicine, Boston Children’s Hospital, Boston, Massachusetts 02115, USA
- Division of Hematology/Oncology, Department of Pediatrics, Boston Children’s Hospital, Boston, Massachusetts 02115, USA
| | - Renchao Chen
- Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, Massachusetts 02115, USA
- Program in Cellular and Molecular Medicine, Boston Children’s Hospital, Boston, Massachusetts 02115, USA
- Division of Hematology/Oncology, Department of Pediatrics, Boston Children’s Hospital, Boston, Massachusetts 02115, USA
| | - Yi Zhang
- Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, Massachusetts 02115, USA
- Program in Cellular and Molecular Medicine, Boston Children’s Hospital, Boston, Massachusetts 02115, USA
- Division of Hematology/Oncology, Department of Pediatrics, Boston Children’s Hospital, Boston, Massachusetts 02115, USA
- Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
- Harvard Stem Cell Institute, WAB-149G, 200 Longwood Avenue, Boston, Massachusetts 02115, USA
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12
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Koppensteiner P, Bhandari P, Önal C, Borges-Merjane C, Le Monnier E, Roy U, Nakamura Y, Sadakata T, Sanbo M, Hirabayashi M, Rhee J, Brose N, Jonas P, Shigemoto R. GABA B receptors induce phasic release from medial habenula terminals through activity-dependent recruitment of release-ready vesicles. Proc Natl Acad Sci U S A 2024; 121:e2301449121. [PMID: 38346189 PMCID: PMC10895368 DOI: 10.1073/pnas.2301449121] [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: 01/26/2023] [Accepted: 01/03/2024] [Indexed: 02/15/2024] Open
Abstract
GABAB receptor (GBR) activation inhibits neurotransmitter release in axon terminals in the brain, except in medial habenula (MHb) terminals, which show robust potentiation. However, mechanisms underlying this enigmatic potentiation remain elusive. Here, we report that GBR activation on MHb terminals induces an activity-dependent transition from a facilitating, tonic to a depressing, phasic neurotransmitter release mode. This transition is accompanied by a 4.1-fold increase in readily releasable vesicle pool (RRP) size and a 3.5-fold increase of docked synaptic vesicles (SVs) at the presynaptic active zone (AZ). Strikingly, the depressing phasic release exhibits looser coupling distance than the tonic release. Furthermore, the tonic and phasic release are selectively affected by deletion of synaptoporin (SPO) and Ca2+-dependent activator protein for secretion 2 (CAPS2), respectively. SPO modulates augmentation, the short-term plasticity associated with tonic release, and CAPS2 retains the increased RRP for initial responses in phasic response trains. The cytosolic protein CAPS2 showed a SV-associated distribution similar to the vesicular transmembrane protein SPO, and they were colocalized in the same terminals. We developed the "Flash and Freeze-fracture" method, and revealed the release of SPO-associated vesicles in both tonic and phasic modes and activity-dependent recruitment of CAPS2 to the AZ during phasic release, which lasted several minutes. Overall, these results indicate that GBR activation translocates CAPS2 to the AZ along with the fusion of CAPS2-associated SVs, contributing to persistency of the RRP increase. Thus, we identified structural and molecular mechanisms underlying tonic and phasic neurotransmitter release and their transition by GBR activation in MHb terminals.
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Affiliation(s)
| | - Pradeep Bhandari
- Institute of Science and Technology Austria, Klosterneuburg3400, Austria
| | - Cihan Önal
- Institute of Science and Technology Austria, Klosterneuburg3400, Austria
| | | | - Elodie Le Monnier
- Institute of Science and Technology Austria, Klosterneuburg3400, Austria
| | - Utsa Roy
- Institute of Science and Technology Austria, Klosterneuburg3400, Austria
| | - Yukihiro Nakamura
- Department of Pharmacology, Jikei University School of Medicine, Nishishinbashi, Minato-ku, Tokyo105-8461, Japan
| | - Tetsushi Sadakata
- Advanced Scientific Research Leaders Development Unit, Gunma University Graduate School of Medicine, Maebashi, Gunma371-8511, Japan
| | - Makoto Sanbo
- Section of Mammalian Transgenesis, National Institute for Physiological Sciences, Okazaki444-8585, Japan
| | - Masumi Hirabayashi
- Section of Mammalian Transgenesis, National Institute for Physiological Sciences, Okazaki444-8585, Japan
| | - JeongSeop Rhee
- Department of Molecular Neurobiology, Max Planck Institute for Multidisciplinary Sciences, Göttingen37077, Germany
| | - Nils Brose
- Department of Molecular Neurobiology, Max Planck Institute for Multidisciplinary Sciences, Göttingen37077, Germany
| | - Peter Jonas
- Institute of Science and Technology Austria, Klosterneuburg3400, Austria
| | - Ryuichi Shigemoto
- Institute of Science and Technology Austria, Klosterneuburg3400, Austria
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13
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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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14
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Congiu M, Mondoloni S, Zouridis IS, Schmors L, Lecca S, Lalive AL, Ginggen K, Deng F, Berens P, Paolicelli RC, Li Y, Burgalossi A, Mameli M. Plasticity of neuronal dynamics in the lateral habenula for cue-punishment associative learning. Mol Psychiatry 2023; 28:5118-5127. [PMID: 37414924 PMCID: PMC11041652 DOI: 10.1038/s41380-023-02155-3] [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: 01/12/2023] [Revised: 05/30/2023] [Accepted: 06/19/2023] [Indexed: 07/08/2023]
Abstract
The brain's ability to associate threats with external stimuli is vital to execute essential behaviours including avoidance. Disruption of this process contributes instead to the emergence of pathological traits which are common in addiction and depression. However, the mechanisms and neural dynamics at the single-cell resolution underlying the encoding of associative learning remain elusive. Here, employing a Pavlovian discrimination task in mice we investigate how neuronal populations in the lateral habenula (LHb), a subcortical nucleus whose excitation underlies negative affect, encode the association between conditioned stimuli and a punishment (unconditioned stimulus). Large population single-unit recordings in the LHb reveal both excitatory and inhibitory responses to aversive stimuli. Additionally, local optical inhibition prevents the formation of cue discrimination during associative learning, demonstrating a critical role of LHb activity in this process. Accordingly, longitudinal in vivo two-photon imaging tracking LHb calcium neuronal dynamics during conditioning reveals an upward or downward shift of individual neurons' CS-evoked responses. While recordings in acute slices indicate strengthening of synaptic excitation after conditioning, support vector machine algorithms suggest that postsynaptic dynamics to punishment-predictive cues represent behavioral cue discrimination. To examine the presynaptic signaling in LHb participating in learning we monitored neurotransmitter dynamics with genetically-encoded indicators in behaving mice. While glutamate, GABA, and serotonin release in LHb remain stable across associative learning, we observe enhanced acetylcholine signaling developing throughout conditioning. In summary, converging presynaptic and postsynaptic mechanisms in the LHb underlie the transformation of neutral cues in valued signals supporting cue discrimination during learning.
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Affiliation(s)
- Mauro Congiu
- The Department of Fundamental Neuroscience, The University of Lausanne, 1005, Lausanne, Switzerland
| | - Sarah Mondoloni
- The Department of Fundamental Neuroscience, The University of Lausanne, 1005, Lausanne, Switzerland
| | - Ioannis S Zouridis
- Institute of Neurobiology and Werner Reichardt Centre for Integrative Neuroscience (CIN), University of Tübingen, 72076, Tübingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School (IMPRS), University of Tübingen, Tübingen, Germany
| | - Lisa Schmors
- Institute for Ophthalmic Research, University of Tübingen, Tübingen, Germany
- Hertie Institute for AI in Brain Health, University of Tübingen, Tübingen, Germany
| | - Salvatore Lecca
- The Department of Fundamental Neuroscience, The University of Lausanne, 1005, Lausanne, Switzerland
| | - Arnaud L Lalive
- The Department of Fundamental Neuroscience, The University of Lausanne, 1005, Lausanne, Switzerland
| | - Kyllian Ginggen
- The Department of Biomedical Sciences, The University of Lausanne, 1005, Lausanne, Switzerland
| | - Fei Deng
- School of Life Sciences, Peking University, Beijing, 100871, China
| | - Philipp Berens
- Institute for Ophthalmic Research, University of Tübingen, Tübingen, Germany
- Tübingen AI Center, University of Tübingen, Tübingen, Germany
| | - Rosa Chiara Paolicelli
- The Department of Biomedical Sciences, The University of Lausanne, 1005, Lausanne, Switzerland
| | - Yulong Li
- School of Life Sciences, Peking University, Beijing, 100871, China
| | - Andrea Burgalossi
- Institute of Neurobiology and Werner Reichardt Centre for Integrative Neuroscience (CIN), University of Tübingen, 72076, Tübingen, Germany
| | - Manuel Mameli
- The Department of Fundamental Neuroscience, The University of Lausanne, 1005, Lausanne, Switzerland.
- Inserm, UMR-S 839, 75005, Paris, France.
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15
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Mountoufaris G, Nair A, Yang B, Kim DW, Anderson DJ. Neuropeptide Signaling is Required to Implement a Line Attractor Encoding a Persistent Internal Behavioral State. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.01.565073. [PMID: 37961374 PMCID: PMC10635056 DOI: 10.1101/2023.11.01.565073] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Internal states drive survival behaviors, but their neural implementation is not well understood. Recently we identified a line attractor in the ventromedial hypothalamus (VMH) that represents an internal state of aggressiveness. Line attractors can be implemented by recurrent connectivity and/or neuromodulatory signaling, but evidence for the latter is scant. Here we show that neuropeptidergic signaling is necessary for line attractor dynamics in this system, using a novel approach that integrates cell type-specific, anatomically restricted CRISPR/Cas9-based gene editing with microendoscopic calcium imaging. Co-disruption of receptors for oxytocin and vasopressin in adult VMH Esr1 + neurons that control aggression suppressed attack, reduced persistent neural activity and eliminated line attractor dynamics, while only modestly impacting neural activity and sex- or behavior-tuning. These data identify a requisite role for neuropeptidergic signaling in implementing a behaviorally relevant line attractor. Our approach should facilitate mechanistic studies in neuroscience that bridge different levels of biological function and abstraction.
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16
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Tajima S, Kim YS, Fukuda M, Jo Y, Wang PY, Paggi JM, Inoue M, Byrne EFX, Kishi KE, Nakamura S, Ramakrishnan C, Takaramoto S, Nagata T, Konno M, Sugiura M, Katayama K, Matsui TE, Yamashita K, Kim S, Ikeda H, Kim J, Kandori H, Dror RO, Inoue K, Deisseroth K, Kato HE. Structural basis for ion selectivity in potassium-selective channelrhodopsins. Cell 2023; 186:4325-4344.e26. [PMID: 37652010 PMCID: PMC7615185 DOI: 10.1016/j.cell.2023.08.009] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 05/11/2023] [Accepted: 08/07/2023] [Indexed: 09/02/2023]
Abstract
KCR channelrhodopsins (K+-selective light-gated ion channels) have received attention as potential inhibitory optogenetic tools but more broadly pose a fundamental mystery regarding how their K+ selectivity is achieved. Here, we present 2.5-2.7 Å cryo-electron microscopy structures of HcKCR1 and HcKCR2 and of a structure-guided mutant with enhanced K+ selectivity. Structural, electrophysiological, computational, spectroscopic, and biochemical analyses reveal a distinctive mechanism for K+ selectivity; rather than forming the symmetrical filter of canonical K+ channels achieving both selectivity and dehydration, instead, three extracellular-vestibule residues within each monomer form a flexible asymmetric selectivity gate, while a distinct dehydration pathway extends intracellularly. Structural comparisons reveal a retinal-binding pocket that induces retinal rotation (accounting for HcKCR1/HcKCR2 spectral differences), and design of corresponding KCR variants with increased K+ selectivity (KALI-1/KALI-2) provides key advantages for optogenetic inhibition in vitro and in vivo. Thus, discovery of a mechanism for ion-channel K+ selectivity also provides a framework for next-generation optogenetics.
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Affiliation(s)
- Seiya Tajima
- Komaba Institute for Science, The University of Tokyo, Meguro, Tokyo, Japan
| | - Yoon Seok Kim
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Masahiro Fukuda
- Komaba Institute for Science, The University of Tokyo, Meguro, Tokyo, Japan
| | - YoungJu Jo
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Peter Y Wang
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Joseph M Paggi
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Masatoshi Inoue
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Eamon F X Byrne
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Koichiro E Kishi
- Komaba Institute for Science, The University of Tokyo, Meguro, Tokyo, Japan
| | - Seiwa Nakamura
- Komaba Institute for Science, The University of Tokyo, Meguro, Tokyo, Japan
| | | | - Shunki Takaramoto
- The Institute for Solid State Physics, The University of Tokyo, Kashiwa, Japan
| | - Takashi Nagata
- The Institute for Solid State Physics, The University of Tokyo, Kashiwa, Japan
| | - Masae Konno
- The Institute for Solid State Physics, The University of Tokyo, Kashiwa, Japan; PRESTO, Japan Science and Technology Agency, Kawaguchi, Saitama, Japan
| | - Masahiro Sugiura
- Department of Life Science and Applied Chemistry, Nagoya Institute of Technology, Showa-ku, Japan
| | - Kota Katayama
- Department of Life Science and Applied Chemistry, Nagoya Institute of Technology, Showa-ku, Japan
| | - Toshiki E Matsui
- Komaba Institute for Science, The University of Tokyo, Meguro, Tokyo, Japan
| | - Keitaro Yamashita
- MRC Laboratory of Molecular Biology, Cambridge Biomedical Campus, Cambridge, UK
| | - Suhyang Kim
- Komaba Institute for Science, The University of Tokyo, Meguro, Tokyo, Japan
| | - Hisako Ikeda
- Komaba Institute for Science, The University of Tokyo, Meguro, Tokyo, Japan
| | - Jaeah Kim
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Hideki Kandori
- Department of Life Science and Applied Chemistry, Nagoya Institute of Technology, Showa-ku, Japan; OptoBioTechnology Research Center, Nagoya Institute of Technology, Showa-ku, Japan
| | - Ron O Dror
- Department of Computer Science, Stanford University, Stanford, CA, USA; Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA
| | - Keiichi Inoue
- The Institute for Solid State Physics, The University of Tokyo, Kashiwa, Japan
| | - Karl Deisseroth
- Department of Bioengineering, Stanford University, Stanford, CA, USA; CNC Program, Stanford University, Stanford, CA, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA; Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
| | - Hideaki E Kato
- Komaba Institute for Science, The University of Tokyo, Meguro, Tokyo, Japan; Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Bunkyo, Tokyo, Japan; FOREST, Japan Science and Technology Agency, Kawaguchi, Saitama, Japan.
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17
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Liu M, Nair A, Linderman SW, Anderson DJ. Periodic hypothalamic attractor-like dynamics during the estrus cycle. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.22.541741. [PMID: 37292695 PMCID: PMC10245896 DOI: 10.1101/2023.05.22.541741] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Cyclic changes in hormonal state are well-known to regulate mating behavior during the female reproductive cycle, but whether and how these changes affect the dynamics of neural activity in the female brain is largely unknown. The ventromedial hypothalamus, ventro-lateral subdivision (VMHvl) contains a subpopulation of VMHvl Esr1+,Npy2r- neurons that controls female sexual receptivity. Longitudinal single cell calcium imaging of these neurons across the estrus cycle revealed that overlapping but distinct subpopulations were active during proestrus (mating-accepting) vs. non-proestrus (rejecting) phases. Dynamical systems analysis of imaging data from proestrus females uncovered a dimension with slow ramping activity, which generated approximate line attractor-like dynamics in neural state space. During mating, the neural population vector progressed along this attractor as male mounting and intromission proceeded. Attractor-like dynamics disappeared in non-proestrus states and reappeared following re-entry into proestrus. They were also absent in ovariectomized females but were restored by hormone priming. These observations reveal that hypothalamic line attractor-like dynamics are associated with female sexual receptivity and can be reversibly regulated by sex hormones, demonstrating that attractor dynamics can be flexibly modulated by physiological state. They also suggest a potential mechanism for the neural encoding of female sexual arousal.
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18
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Ho A, Orton R, Tayler R, Asamaphan P, Herder V, Davis C, Tong L, Smollett K, Manali M, Allan J, Rawlik K, McDonald SE, Vink E, Pollock L, Gannon L, Evans C, McMenamin J, Roy K, Marsh K, Divala T, Holden MTG, Lockhart M, Yirrell D, Currie S, O'Leary M, Henderson D, Shepherd SJ, Jackson C, Gunson R, MacLean A, McInnes N, Bradley-Stewart A, Battle R, Hollenbach JA, Henderson P, Odam M, Chikowore P, Oosthuyzen W, Chand M, Hamilton MS, Estrada-Rivadeneyra D, Levin M, Avramidis N, Pairo-Castineira E, Vitart V, Wilkie C, Palmarini M, Ray S, Robertson DL, da Silva Filipe A, Willett BJ, Breuer J, Semple MG, Turner D, Baillie JK, Thomson EC. Adeno-associated virus 2 infection in children with non-A-E hepatitis. Nature 2023; 617:555-563. [PMID: 36996873 DOI: 10.1038/s41586-023-05948-2] [Citation(s) in RCA: 55] [Impact Index Per Article: 55.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 03/10/2023] [Indexed: 04/01/2023]
Abstract
An outbreak of acute hepatitis of unknown aetiology in children was reported in Scotland1 in April 2022 and has now been identified in 35 countries2. Several recent studies have suggested an association with human adenovirus with this outbreak, a virus not commonly associated with hepatitis. Here we report a detailed case-control investigation and find an association between adeno-associated virus 2 (AAV2) infection and host genetics in disease susceptibility. Using next-generation sequencing, PCR with reverse transcription, serology and in situ hybridization, we detected recent infection with AAV2 in plasma and liver samples in 26 out of 32 (81%) cases of hepatitis compared with 5 out of 74 (7%) of samples from unaffected individuals. Furthermore, AAV2 was detected within ballooned hepatocytes alongside a prominent T cell infiltrate in liver biopsy samples. In keeping with a CD4+ T-cell-mediated immune pathology, the human leukocyte antigen (HLA) class II HLA-DRB1*04:01 allele was identified in 25 out of 27 cases (93%) compared with a background frequency of 10 out of 64 (16%; P = 5.49 × 10-12). In summary, we report an outbreak of acute paediatric hepatitis associated with AAV2 infection (most likely acquired as a co-infection with human adenovirus that is usually required as a 'helper virus' to support AAV2 replication) and disease susceptibility related to HLA class II status.
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Affiliation(s)
- Antonia Ho
- Medical Research Council-University of Glasgow Centre for Virus Research, Glasgow, UK
| | - Richard Orton
- Medical Research Council-University of Glasgow Centre for Virus Research, Glasgow, UK
| | - Rachel Tayler
- Department of Paediatrics, Royal Hospital for Children, Glasgow, UK
| | - Patawee Asamaphan
- Medical Research Council-University of Glasgow Centre for Virus Research, Glasgow, UK
| | - Vanessa Herder
- Medical Research Council-University of Glasgow Centre for Virus Research, Glasgow, UK
| | - Chris Davis
- Medical Research Council-University of Glasgow Centre for Virus Research, Glasgow, UK
| | - Lily Tong
- Medical Research Council-University of Glasgow Centre for Virus Research, Glasgow, UK
| | - Katherine Smollett
- Medical Research Council-University of Glasgow Centre for Virus Research, Glasgow, UK
| | - Maria Manali
- Medical Research Council-University of Glasgow Centre for Virus Research, Glasgow, UK
| | - Jay Allan
- Medical Research Council-University of Glasgow Centre for Virus Research, Glasgow, UK
| | - Konrad Rawlik
- Pandemic Science Hub, Centre for Inflammation Research and Roslin Institute, University of Edinburgh, Edinburgh, UK
| | - Sarah E McDonald
- Medical Research Council-University of Glasgow Centre for Virus Research, Glasgow, UK
| | - Elen Vink
- Medical Research Council-University of Glasgow Centre for Virus Research, Glasgow, UK
| | - Louisa Pollock
- Medical Research Council-University of Glasgow Centre for Virus Research, Glasgow, UK
- Department of Paediatrics, Royal Hospital for Children, Glasgow, UK
| | | | - Clair Evans
- Department of Pathology, Queen Elizabeth University Hospital, Glasgow, UK
| | | | | | | | | | | | | | | | | | | | | | | | - Celia Jackson
- West of Scotland Specialist Virology Centre, Glasgow, UK
| | - Rory Gunson
- West of Scotland Specialist Virology Centre, Glasgow, UK
| | | | - Neil McInnes
- West of Scotland Specialist Virology Centre, Glasgow, UK
| | | | - Richard Battle
- Histocompatibility and Immunogenetics (H&I) Laboratory, Scottish National Blood Transfusion Service, Edinburgh Royal Infirmary, Edinburgh, UK
| | - Jill A Hollenbach
- Department of Neurology and Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Paul Henderson
- Child Life and Health, University of Edinburgh, Edinburgh, UK
| | - Miranda Odam
- Pandemic Science Hub, Centre for Inflammation Research and Roslin Institute, University of Edinburgh, Edinburgh, UK
| | - Primrose Chikowore
- Pandemic Science Hub, Centre for Inflammation Research and Roslin Institute, University of Edinburgh, Edinburgh, UK
| | - Wilna Oosthuyzen
- Pandemic Science Hub, Centre for Inflammation Research and Roslin Institute, University of Edinburgh, Edinburgh, UK
| | | | - Melissa Shea Hamilton
- Section of Paediatric Infectious Disease, Department of Infectious Disease, Imperial College London, London, UK
| | - Diego Estrada-Rivadeneyra
- Section of Paediatric Infectious Disease, Department of Infectious Disease, Imperial College London, London, UK
| | - Michael Levin
- Section of Paediatric Infectious Disease, Department of Infectious Disease, Imperial College London, London, UK
| | - Nikos Avramidis
- Pandemic Science Hub, Centre for Inflammation Research and Roslin Institute, University of Edinburgh, Edinburgh, UK
| | - Erola Pairo-Castineira
- Pandemic Science Hub, Centre for Inflammation Research and Roslin Institute, University of Edinburgh, Edinburgh, UK
| | - Veronique Vitart
- Pandemic Science Hub, Centre for Inflammation Research and Roslin Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, Institute for Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Craig Wilkie
- School of Mathematics and Statistics, University of Glasgow, Glasgow, UK
| | - Massimo Palmarini
- Medical Research Council-University of Glasgow Centre for Virus Research, Glasgow, UK
| | - Surajit Ray
- School of Mathematics and Statistics, University of Glasgow, Glasgow, UK
| | - David L Robertson
- Medical Research Council-University of Glasgow Centre for Virus Research, Glasgow, UK
| | - Ana da Silva Filipe
- Medical Research Council-University of Glasgow Centre for Virus Research, Glasgow, UK
| | - Brian J Willett
- Medical Research Council-University of Glasgow Centre for Virus Research, Glasgow, UK
| | | | | | - David Turner
- Histocompatibility and Immunogenetics (H&I) Laboratory, Scottish National Blood Transfusion Service, Edinburgh Royal Infirmary, Edinburgh, UK
| | - J Kenneth Baillie
- Pandemic Science Hub, Centre for Inflammation Research and Roslin Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, Institute for Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Emma C Thomson
- Medical Research Council-University of Glasgow Centre for Virus Research, Glasgow, UK.
- Department of Clinical Research, London School of Hygiene and Tropical Medicine, London, UK.
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19
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Ables JL, Park K, Ibañez-Tallon I. Understanding the habenula: A major node in circuits regulating emotion and motivation. Pharmacol Res 2023; 190:106734. [PMID: 36933754 PMCID: PMC11081310 DOI: 10.1016/j.phrs.2023.106734] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 03/04/2023] [Accepted: 03/14/2023] [Indexed: 03/18/2023]
Abstract
Over the last decade, the understanding of the habenula has rapidly advanced from being an understudied brain area with the Latin name 'habena" meaning "little rein", to being considered a "major rein" in the control of key monoaminergic brain centers. This ancient brain structure is a strategic node in the information flow from fronto-limbic brain areas to brainstem nuclei. As such, it plays a crucial role in regulating emotional, motivational, and cognitive behaviors and has been implicated in several neuropsychiatric disorders, including depression and addiction. This review will summarize recent findings on the medial (MHb) and lateral (LHb) habenula, their topographical projections, cell types, and functions. Additionally, we will discuss contemporary efforts that have uncovered novel molecular pathways and synaptic mechanisms with a focus on MHb-Interpeduncular nucleus (IPN) synapses. Finally, we will explore the potential interplay between the habenula's cholinergic and non-cholinergic components in coordinating related emotional and motivational behaviors, raising the possibility that these two pathways work together to provide balanced roles in reward prediction and aversion, rather than functioning independently.
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Affiliation(s)
- Jessica L Ables
- Psychiatry Department, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kwanghoon Park
- The Laboratory of Molecular Biology, The Rockefeller University, New York, NY, USA
| | - Inés Ibañez-Tallon
- The Laboratory of Molecular Biology, The Rockefeller University, New York, NY, USA.
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20
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Hsueh B, Chen R, Jo Y, Tang D, Raffiee M, Kim YS, Inoue M, Randles S, Ramakrishnan C, Patel S, Kim DK, Liu TX, Kim SH, Tan L, Mortazavi L, Cordero A, Shi J, Zhao M, Ho TT, Crow A, Yoo ACW, Raja C, Evans K, Bernstein D, Zeineh M, Goubran M, Deisseroth K. Cardiogenic control of affective behavioural state. Nature 2023; 615:292-299. [PMID: 36859543 PMCID: PMC9995271 DOI: 10.1038/s41586-023-05748-8] [Citation(s) in RCA: 81] [Impact Index Per Article: 81.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 01/20/2023] [Indexed: 03/03/2023]
Abstract
Emotional states influence bodily physiology, as exemplified in the top-down process by which anxiety causes faster beating of the heart1-3. However, whether an increased heart rate might itself induce anxiety or fear responses is unclear3-8. Physiological theories of emotion, proposed over a century ago, have considered that in general, there could be an important and even dominant flow of information from the body to the brain9. Here, to formally test this idea, we developed a noninvasive optogenetic pacemaker for precise, cell-type-specific control of cardiac rhythms of up to 900 beats per minute in freely moving mice, enabled by a wearable micro-LED harness and the systemic viral delivery of a potent pump-like channelrhodopsin. We found that optically evoked tachycardia potently enhanced anxiety-like behaviour, but crucially only in risky contexts, indicating that both central (brain) and peripheral (body) processes may be involved in the development of emotional states. To identify potential mechanisms, we used whole-brain activity screening and electrophysiology to find brain regions that were activated by imposed cardiac rhythms. We identified the posterior insular cortex as a potential mediator of bottom-up cardiac interoceptive processing, and found that optogenetic inhibition of this brain region attenuated the anxiety-like behaviour that was induced by optical cardiac pacing. Together, these findings reveal that cells of both the body and the brain must be considered together to understand the origins of emotional or affective states. More broadly, our results define a generalizable approach for noninvasive, temporally precise functional investigations of joint organism-wide interactions among targeted cells during behaviour.
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Affiliation(s)
- Brian Hsueh
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Ritchie Chen
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - YoungJu Jo
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Daniel Tang
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Misha Raffiee
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Yoon Seok Kim
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Masatoshi Inoue
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Sawyer Randles
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | | | - Sneha Patel
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Doo Kyung Kim
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Tony X Liu
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Soo Hyun Kim
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Longzhi Tan
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Leili Mortazavi
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Arjay Cordero
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Jenny Shi
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Mingming Zhao
- Department of Pediatrics, Stanford University, Stanford, CA, USA
| | - Theodore T Ho
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Ailey Crow
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Ai-Chi Wang Yoo
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Cephra Raja
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Kathryn Evans
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Daniel Bernstein
- Department of Pediatrics, Stanford University, Stanford, CA, USA
| | - Michael Zeineh
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Maged Goubran
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Karl Deisseroth
- Department of Bioengineering, Stanford University, Stanford, CA, USA.
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA.
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21
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Nair A, Karigo T, Yang B, Ganguli S, Schnitzer MJ, Linderman SW, Anderson DJ, Kennedy A. An approximate line attractor in the hypothalamus encodes an aggressive state. Cell 2023; 186:178-193.e15. [PMID: 36608653 PMCID: PMC9990527 DOI: 10.1016/j.cell.2022.11.027] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 10/05/2022] [Accepted: 11/22/2022] [Indexed: 01/07/2023]
Abstract
The hypothalamus regulates innate social behaviors, including mating and aggression. These behaviors can be evoked by optogenetic stimulation of specific neuronal subpopulations within MPOA and VMHvl, respectively. Here, we perform dynamical systems modeling of population neuronal activity in these nuclei during social behaviors. In VMHvl, unsupervised analysis identified a dominant dimension of neural activity with a large time constant (>50 s), generating an approximate line attractor in neural state space. Progression of the neural trajectory along this attractor was correlated with an escalation of agonistic behavior, suggesting that it may encode a scalable state of aggressiveness. Consistent with this, individual differences in the magnitude of the integration dimension time constant were strongly correlated with differences in aggressiveness. In contrast, approximate line attractors were not observed in MPOA during mating; instead, neurons with fast dynamics were tuned to specific actions. Thus, different hypothalamic nuclei employ distinct neural population codes to represent similar social behaviors.
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Affiliation(s)
- Aditya Nair
- Division of Biology and Biological Engineering, Caltech, Pasadena, CA 91125, USA; Howard Hughes Medical Institute; Tianqiao and Chrissy Chen Institute for Neuroscience, Caltech, Pasadena, CA 91125, USA
| | - Tomomi Karigo
- Division of Biology and Biological Engineering, Caltech, Pasadena, CA 91125, USA; Howard Hughes Medical Institute; Tianqiao and Chrissy Chen Institute for Neuroscience, Caltech, Pasadena, CA 91125, USA
| | - Bin Yang
- Division of Biology and Biological Engineering, Caltech, Pasadena, CA 91125, USA; Howard Hughes Medical Institute; Tianqiao and Chrissy Chen Institute for Neuroscience, Caltech, Pasadena, CA 91125, USA
| | - Surya Ganguli
- Department of Applied Physics, Stanford University, Stanford, CA, USA
| | - Mark J Schnitzer
- Howard Hughes Medical Institute; Department of Applied Physics, Stanford University, Stanford, CA, USA; Department of Biology, Stanford University, Stanford, CA, USA
| | - Scott W Linderman
- Department of Statistics, Stanford University, Stanford, CA 94305, USA; Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA 94305, USA
| | - David J Anderson
- Division of Biology and Biological Engineering, Caltech, Pasadena, CA 91125, USA; Howard Hughes Medical Institute; Tianqiao and Chrissy Chen Institute for Neuroscience, Caltech, Pasadena, CA 91125, USA.
| | - Ann Kennedy
- Division of Biology and Biological Engineering, Caltech, Pasadena, CA 91125, USA; Howard Hughes Medical Institute; Tianqiao and Chrissy Chen Institute for Neuroscience, Caltech, Pasadena, CA 91125, USA; Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago IL 60611, USA.
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