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Phalip A, Netser S, Wagner S. Understanding the neurobiology of social behavior through exploring brain-wide dynamics of neural activity. Neurosci Biobehav Rev 2024; 165:105856. [PMID: 39159735 DOI: 10.1016/j.neubiorev.2024.105856] [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: 05/10/2024] [Revised: 08/11/2024] [Accepted: 08/14/2024] [Indexed: 08/21/2024]
Abstract
Social behavior is highly complex and adaptable. It can be divided into multiple temporal stages: detection, approach, and consummatory behavior. Each stage can be further divided into several cognitive and behavioral processes, such as perceiving social cues, evaluating the social and non-social contexts, and recognizing the internal/emotional state of others. Recent studies have identified numerous brain-wide circuits implicated in social behavior and suggested the existence of partially overlapping functional brain networks underlying various types of social and non-social behavior. However, understanding the brain-wide dynamics underlying social behavior remains challenging, and several brain-scale dynamics (macro-, meso-, and micro-scale levels) need to be integrated. Here, we suggest leveraging new tools and concepts to explore social brain networks and integrate those different levels. These include studying the expression of immediate-early genes throughout the entire brain to impartially define the structure of the neuronal networks involved in a given social behavior. Then, network dynamics could be investigated using electrode arrays or multi-channel fiber photometry. Finally, tools like high-density silicon probes and miniscopes can probe neural activity in specific areas and across neuronal populations at the single-cell level.
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Affiliation(s)
- Adèle Phalip
- Sagol Department of Neurobiology, Faculty of Natural Sciences, University of Haifa, Haifa, Israel.
| | - Shai Netser
- Sagol Department of Neurobiology, Faculty of Natural Sciences, University of Haifa, Haifa, Israel
| | - Shlomo Wagner
- Sagol Department of Neurobiology, Faculty of Natural Sciences, University of Haifa, Haifa, Israel
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2
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Láng T, Dimén D, Oláh S, Puska G, Dobolyi A. Medial preoptic circuits governing instinctive social behaviors. iScience 2024; 27:110296. [PMID: 39055958 PMCID: PMC11269931 DOI: 10.1016/j.isci.2024.110296] [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] [Indexed: 07/28/2024] Open
Abstract
The medial preoptic area (MPOA) has long been implicated in maternal and male sexual behavior. Modern neuroscience methods have begun to reveal the cellular networks responsible, while also implicating the MPOA in other social behaviors, affiliative social touch, and aggression. The social interactions rely on input from conspecifics whose most important modalities in rodents are olfaction and somatosensation. These inputs bypass the cerebral cortex to reach the MPOA to influence the social function. Hormonal inputs also directly act on MPOA neurons. In turn, the MPOA controls social responses via various projections for reward and motor output. The MPOA thus emerges as one of the major brain centers for instinctive social behavior. While key elements of MPOA circuits have been identified, a synthesis of these new data is now provided for further studies to reveal the mechanisms by which the area controls social interactions.
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Affiliation(s)
- Tamás Láng
- Laboratory of Neuromorphology, Department of Anatomy, Histology and Embryology, Semmelweis University, Budapest, Hungary
| | - Diána Dimén
- Laboratory of Neuromorphology, Department of Anatomy, Histology and Embryology, Semmelweis University, Budapest, Hungary
- Addiction and Neuroplasticity Laboratory, Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Szilvia Oláh
- Laboratory of Molecular and Systems Neurobiology, Department of Physiology and Neurobiology, Eötvös Loránd University, Budapest, Hungary
| | - Gina Puska
- Laboratory of Molecular and Systems Neurobiology, Department of Physiology and Neurobiology, Eötvös Loránd University, Budapest, Hungary
- Department of Zoology, University of Veterinary Medicine Budapest, Budapest, Hungary
| | - Arpád Dobolyi
- Laboratory of Neuromorphology, Department of Anatomy, Histology and Embryology, Semmelweis University, Budapest, Hungary
- Laboratory of Molecular and Systems Neurobiology, Department of Physiology and Neurobiology, Eötvös Loránd University, Budapest, Hungary
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3
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Chen Y, Chien J, Dai B, Lin D, Chen ZS. Identifying behavioral links to neural dynamics of multifiber photometry recordings in a mouse social behavior network. J Neural Eng 2024; 21:10.1088/1741-2552/ad5702. [PMID: 38861996 PMCID: PMC11246699 DOI: 10.1088/1741-2552/ad5702] [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: 01/09/2024] [Accepted: 06/11/2024] [Indexed: 06/13/2024]
Abstract
Objective.Distributed hypothalamic-midbrain neural circuits help orchestrate complex behavioral responses during social interactions. Given rapid advances in optical imaging, it is a fundamental question how population-averaged neural activity measured by multi-fiber photometry (MFP) for calcium fluorescence signals correlates with social behaviors is a fundamental question. This paper aims to investigate the correspondence between MFP data and social behaviors.Approach:We propose a state-space analysis framework to characterize mouse MFP data based on dynamic latent variable models, which include a continuous-state linear dynamical system and a discrete-state hidden semi-Markov model. We validate these models on extensive MFP recordings during aggressive and mating behaviors in male-male and male-female interactions, respectively.Main results:Our results show that these models are capable of capturing both temporal behavioral structure and associated neural states, and produce interpretable latent states. Our approach is also validated in computer simulations in the presence of known ground truth.Significance:Overall, these analysis approaches provide a state-space framework to examine neural dynamics underlying social behaviors and reveals mechanistic insights into the relevant networks.
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Affiliation(s)
- Yibo Chen
- Department of Psychiatry, Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
- Program in Artificial Intelligence, University of Science and Technology of China, Hefei, Anhui, China
- Equal contributions (Y.C. and J.C.)
| | - Jonathan Chien
- Department of Psychiatry, Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
- Equal contributions (Y.C. and J.C.)
| | - Bing Dai
- Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, USA
| | - Dayu Lin
- Department of Psychiatry, Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
- Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, USA
- Center for Neural Science, New York University, New York, NY, USA
| | - Zhe Sage Chen
- Department of Psychiatry, Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
- Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, USA
- Department of Biomedical Engineering, NYU Tandon School of Engineering, Brooklyn, NY, USA
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4
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Velazquez-Hernandez G, Miller NW, Curtis VR, Rivera-Pacheco CM, Lowe SM, Moy SS, Zannas AS, Pégard NC, Burgos-Robles A, Rodriguez-Romaguera J. Social threat alters the behavioral structure of social motivation and reshapes functional brain connectivity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.17.599379. [PMID: 38948883 PMCID: PMC11212885 DOI: 10.1101/2024.06.17.599379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Traumatic social experiences redefine socially motivated behaviors to enhance safety and survival. Although many brain regions have been implicated in signaling a social threat, the mechanisms by which global neural networks regulate such motivated behaviors remain unclear. To address this issue, we first combined traditional and modern behavioral tracking techniques in mice to assess both approach and avoidance, as well as sub-second behavioral changes, during a social threat learning task. We were able to identify previously undescribed body and tail movements during social threat learning and recognition that demonstrate unique alterations into the behavioral structure of social motivation. We then utilized inter-regional correlation analysis of brain activity after a mouse recognizes a social threat to explore functional communication amongst brain regions implicated in social motivation. Broad brain activity changes were observed within the nucleus accumbens, the paraventricular thalamus, the ventromedial hypothalamus, and the nucleus of reuniens. Inter-regional correlation analysis revealed a reshaping of the functional connectivity across the brain when mice recognize a social threat. Altogether, these findings suggest that reshaping of functional brain connectivity may be necessary to alter the behavioral structure of social motivation when a social threat is encountered.
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5
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Aspesi D, Cornil CA. Role of neuroestrogens in the regulation of social behaviors - From social recognition to mating. Neurosci Biobehav Rev 2024; 161:105679. [PMID: 38642866 DOI: 10.1016/j.neubiorev.2024.105679] [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: 12/07/2023] [Revised: 03/12/2024] [Accepted: 04/15/2024] [Indexed: 04/22/2024]
Abstract
In this mini-review, we summarize the brain distribution of aromatase, the enzyme catalyzing the synthesis of estrogens from androgens, and the mechanisms responsible for regulating estrogen production within the brain. Understanding this local synthesis of estrogens by neurons is pivotal as it profoundly influences various facets of social behavior. Neuroestrogen action spans from the initial processing of socially pertinent sensory cues to integrating this information with an individual's internal state, ultimately resulting in the manifestation of either pro-affiliative or - aggressive behaviors. We focus here in particular on aggressive and sexual behavior as the result of correct individual recognition of intruders and potential mates. The data summarized in this review clearly point out the crucial role of locally synthesized estrogens in facilitating rapid adaptation to the social environment in rodents and birds of both sexes. These observations not only shed light on the evolutionary significance but also indicate the potential implications of these findings in the realm of human health, suggesting a compelling avenue for further investigation.
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Affiliation(s)
- Dario Aspesi
- Center for Behavioral Neuroscience, Georgia State University, Atlanta, GA 30303, USA
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6
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Inoue S. Hormonal and circuit mechanisms controlling female sexual behavior. Front Neural Circuits 2024; 18:1409349. [PMID: 38752168 PMCID: PMC11094328 DOI: 10.3389/fncir.2024.1409349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Accepted: 04/15/2024] [Indexed: 05/18/2024] Open
Abstract
Sexual behavior is crucial for reproduction in many animals. In many vertebrates, females exhibit sexual behavior only during a brief period surrounding ovulation. Over the decades, studies have identified the roles of ovarian sex hormones, which peak in levels around the time of ovulation, and the critical brain regions involved in the regulation of female sexual behavior. Modern technical innovations have enabled a deeper understanding of the neural circuit mechanisms controlling this behavior. In this review, I summarize our current knowledge and discuss the neural circuit mechanisms by which female sexual behavior occurs in association with the ovulatory phase of their cycle.
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Affiliation(s)
- Sayaka Inoue
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, St. Louis, MO, United States
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7
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He ZX, Yue MH, Liu KJ, Wang Y, Qiao JY, Lv XY, Xi K, Zhang YX, Fan JN, Yu HL, He XX, Zhu XJ. Substance P in the medial amygdala regulates aggressive behaviors in male mice. Neuropsychopharmacology 2024:10.1038/s41386-024-01863-w. [PMID: 38649427 DOI: 10.1038/s41386-024-01863-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 04/06/2024] [Accepted: 04/08/2024] [Indexed: 04/25/2024]
Abstract
Behavioral and clinical studies have revealed a critical role of substance P (SP) in aggression; however, the neural circuit mechanisms underlying SP and aggression remain elusive. Here, we show that tachykinin-expressing neurons in the medial amygdala (MeATac1 neurons) are activated during aggressive behaviors in male mice. We identified MeATac1 neurons as a key mediator of aggression and found that MeATac1→ventrolateral part of the ventromedial hypothalamic nucleus (VMHvl) projections are critical to the regulation of aggression. Moreover, SP/neurokinin-1 receptor (NK-1R) signaling in the VMHvl modulates aggressive behaviors in male mice. SP/NK-1R signaling regulates aggression by influencing glutamate transmission in neurons in the VMHvl. In summary, these findings place SP as a key node in aggression circuits.
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Affiliation(s)
- Zi-Xuan He
- Key Laboratory of Molecular Epigenetics Ministry of Education, Institute of Genetics and Cytology, Northeast Normal University, Changchun, 130021, China
| | - Mei-Hui Yue
- Key Laboratory of Molecular Epigenetics Ministry of Education, Institute of Genetics and Cytology, Northeast Normal University, Changchun, 130021, China
| | - Kai-Jie Liu
- Key Laboratory of Molecular Epigenetics Ministry of Education, Institute of Genetics and Cytology, Northeast Normal University, Changchun, 130021, China
| | - Yao Wang
- Key Laboratory of Molecular Epigenetics Ministry of Education, Institute of Genetics and Cytology, Northeast Normal University, Changchun, 130021, China
| | - Jiu-Ye Qiao
- Key Laboratory of Molecular Epigenetics Ministry of Education, Institute of Genetics and Cytology, Northeast Normal University, Changchun, 130021, China
| | - Xin-Yue Lv
- Key Laboratory of Molecular Epigenetics Ministry of Education, Institute of Genetics and Cytology, Northeast Normal University, Changchun, 130021, China
| | - Ke Xi
- Key Laboratory of Molecular Epigenetics Ministry of Education, Institute of Genetics and Cytology, Northeast Normal University, Changchun, 130021, China
| | - Ya-Xin Zhang
- Key Laboratory of Molecular Epigenetics Ministry of Education, Institute of Genetics and Cytology, Northeast Normal University, Changchun, 130021, China
| | - Jia-Ni Fan
- Key Laboratory of Molecular Epigenetics Ministry of Education, Institute of Genetics and Cytology, Northeast Normal University, Changchun, 130021, China
| | - Hua-Li Yu
- Key Laboratory of Molecular Epigenetics Ministry of Education, Institute of Genetics and Cytology, Northeast Normal University, Changchun, 130021, China
| | - Xiao-Xiao He
- Key Laboratory of Molecular Epigenetics Ministry of Education, Institute of Genetics and Cytology, Northeast Normal University, Changchun, 130021, China
| | - Xiao-Juan Zhu
- Key Laboratory of Molecular Epigenetics Ministry of Education, Institute of Genetics and Cytology, Northeast Normal University, Changchun, 130021, China.
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8
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Dai B, Guo Z, Lin D. Brain-wide multi-fiber recording of neuronal activity in freely moving mice. STAR Protoc 2024; 5:102882. [PMID: 38340320 PMCID: PMC10873755 DOI: 10.1016/j.xpro.2024.102882] [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: 10/12/2023] [Revised: 12/16/2023] [Accepted: 01/26/2024] [Indexed: 02/12/2024] Open
Abstract
While brain regions function in coordination to mediate diverse behaviors, techniques allowing simultaneous monitoring of many deep brain regions remain limited. Here, we present a multi-fiber recording protocol that enables simultaneous recording of fluorescence signals from multiple brain regions in freely behaving mice. We describe steps for assembling a multi-fiber array and patch cord, implantation, and recording. We then detail procedures for data extraction and visualization. This protocol enables a comprehensive view of the neural activity at the network level. For complete details on the use and execution of this protocol, please refer to Guo et al.1.
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Affiliation(s)
- Bing Dai
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA.
| | - Zhichao Guo
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA; School of Life Sciences, Peking University, Beijing 100871, China
| | - Dayu Lin
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA; Department of Psychiatry, New York University Langone Health, New York, NY, USA.
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9
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Walder-Christensen K, Abdelaal K, Klein H, Thomas GE, Gallagher NM, Talbot A, Adamson E, Rawls A, Hughes D, Mague SD, Dzirasa K, Carlson DE. Electome network factors: Capturing emotional brain networks related to health and disease. CELL REPORTS METHODS 2024; 4:100691. [PMID: 38215761 PMCID: PMC10832286 DOI: 10.1016/j.crmeth.2023.100691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 10/17/2023] [Accepted: 12/21/2023] [Indexed: 01/14/2024]
Abstract
Therapeutic development for mental disorders has been slow despite the high worldwide prevalence of illness. Unfortunately, cellular and circuit insights into disease etiology have largely failed to generalize across individuals that carry the same diagnosis, reflecting an unmet need to identify convergent mechanisms that would facilitate optimal treatment. Here, we discuss how mesoscale networks can encode affect and other cognitive processes. These networks can be discovered through electrical functional connectome (electome) analysis, a method built upon explainable machine learning models for analyzing and interpreting mesoscale brain-wide signals in a behavioral context. We also outline best practices for identifying these generalizable, interpretable, and biologically relevant networks. Looking forward, translational electome analysis can span species and various moods, cognitive processes, or other brain states, supporting translational medicine. Thus, we argue that electome analysis provides potential translational biomarkers for developing next-generation therapeutics that exhibit high efficacy across heterogeneous disorders.
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Affiliation(s)
- Kathryn Walder-Christensen
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, USA; Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA
| | - Karim Abdelaal
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA; Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA
| | - Hunter Klein
- Department of Electrical and Computer Engineering, Duke University, Durham, NC 27710, USA
| | - Gwenaëlle E Thomas
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA; Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA
| | - Neil M Gallagher
- Department of Psychiatry, Weill Cornell Medical Center, New York City, NY 10065, USA
| | - Austin Talbot
- Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA
| | - Elise Adamson
- Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA; Department of Biomedical Engineering, Duke University, Durham, NC 27710, USA
| | - Ashleigh Rawls
- Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC 27710, USA; Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA
| | - Dalton Hughes
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA; Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA
| | - Stephen D Mague
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, USA; Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA
| | - Kafui Dzirasa
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, USA; Department of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA; Department of Neurosurgery, Duke University Medical Center, Durham, NC 27710, USA; Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA; Department of Biomedical Engineering, Duke University, Durham, NC 27710, USA.
| | - David E Carlson
- Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC 27710, USA; Department of Civil and Environmental Engineering, Duke University, Durham, NC 27710, USA.
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10
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Chen Y, Chien J, Dai B, Lin D, Chen ZS. Identifying behavioral links to neural dynamics of multifiber photometry recordings in a mouse social behavior network. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.25.573308. [PMID: 38234793 PMCID: PMC10793434 DOI: 10.1101/2023.12.25.573308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Distributed hypothalamic-midbrain neural circuits orchestrate complex behavioral responses during social interactions. How population-averaged neural activity measured by multi-fiber photometry (MFP) for calcium fluorescence signals correlates with social behaviors is a fundamental question. We propose a state-space analysis framework to characterize mouse MFP data based on dynamic latent variable models, which include continuous-state linear dynamical system (LDS) and discrete-state hidden semi-Markov model (HSMM). We validate these models on extensive MFP recordings during aggressive and mating behaviors in male-male and male-female interactions, respectively. Our results show that these models are capable of capturing both temporal behavioral structure and associated neural states. Overall, these analysis approaches provide an unbiased strategy to examine neural dynamics underlying social behaviors and reveals mechanistic insights into the relevant networks.
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Affiliation(s)
- Yibo Chen
- Department of Psychiatry, Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
- Program in Artificial Intelligence, University of Science and Technology of China, Hefei, Anhui, China
| | - Jonathan Chien
- Department of Psychiatry, Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
| | - Bing Dai
- Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, USA
| | - Dayu Lin
- Department of Psychiatry, Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
- Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, USA
- Center for Neural Science, New York University, New York, NY, USA
| | - Zhe Sage Chen
- Department of Psychiatry, Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
- Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, USA
- Department of Biomedical Engineering, NYU Tandon School of Engineering, Brooklyn, NY, USA
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11
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Mohapatra AN, Peles D, Netser S, Wagner S. Synchronized LFP rhythmicity in the social brain reflects the context of social encounters. Commun Biol 2024; 7:2. [PMID: 38168971 PMCID: PMC10761981 DOI: 10.1038/s42003-023-05728-8] [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: 08/10/2023] [Accepted: 12/19/2023] [Indexed: 01/05/2024] Open
Abstract
Mammalian social behavior is highly context-sensitive. Yet, little is known about the mechanisms that modulate social behavior according to its context. Recent studies have revealed a network of mostly limbic brain regions which regulates social behavior. We hypothesize that coherent theta and gamma rhythms reflect the organization of this network into functional sub-networks in a context-dependent manner. To test this concept, we simultaneously record local field potential (LFP) from multiple social brain regions in adult male mice performing three social discrimination tasks. While LFP rhythmicity across all tasks is dominated by a global internal state, the pattern of theta coherence between the various regions reflect the behavioral task more than other variables. Moreover, Granger causality analysis implicate the ventral dentate gyrus as a main player in coordinating the context-specific rhythmic activity. Thus, our results suggest that the pattern of coordinated rhythmic activity within the network reflects the subject's social context.
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Affiliation(s)
- Alok Nath Mohapatra
- Sagol Department of Neurobiology, Faculty of Natural Sciences, University of Haifa, POB. 3338, Haifa, 3103301, Israel.
| | - David Peles
- Sagol Department of Neurobiology, Faculty of Natural Sciences, University of Haifa, POB. 3338, Haifa, 3103301, Israel
| | - Shai Netser
- Sagol Department of Neurobiology, Faculty of Natural Sciences, University of Haifa, POB. 3338, Haifa, 3103301, Israel
| | - Shlomo Wagner
- Sagol Department of Neurobiology, Faculty of Natural Sciences, University of Haifa, POB. 3338, Haifa, 3103301, Israel
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12
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Lischinsky JE, Yin L, Shi C, Prakash N, Burke J, Shekaran G, Grba M, Corbin JG, Lin D. Transcriptionally defined amygdala subpopulations play distinct roles in innate social behaviors. Nat Neurosci 2023; 26:2131-2146. [PMID: 37946049 PMCID: PMC10689240 DOI: 10.1038/s41593-023-01475-5] [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: 07/16/2022] [Accepted: 09/29/2023] [Indexed: 11/12/2023]
Abstract
Social behaviors are innate and supported by dedicated neural circuits, but the molecular identities of these circuits and how they are established developmentally and shaped by experience remain unclear. Here we show that medial amygdala (MeA) cells originating from two embryonically parcellated developmental lineages have distinct response patterns and functions in social behavior in male mice. MeA cells expressing the transcription factor Foxp2 (MeAFoxp2) are specialized for processing male conspecific cues and are essential for adult inter-male aggression. By contrast, MeA cells derived from the Dbx1 lineage (MeADbx1) respond broadly to social cues, respond strongly during ejaculation and are not essential for male aggression. Furthermore, MeAFoxp2 and MeADbx1 cells show differential anatomical and functional connectivity. Altogether, our results suggest a developmentally hardwired aggression circuit at the MeA level and a lineage-based circuit organization by which a cell's embryonic transcription factor profile determines its social information representation and behavioral relevance during adulthood.
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Affiliation(s)
- Julieta E Lischinsky
- Neuroscience Institute, New York University School of Medicine, New York, NY, USA.
| | - Luping Yin
- Neuroscience Institute, New York University School of Medicine, New York, NY, USA
| | - Chenxi Shi
- Neuroscience Institute, New York University School of Medicine, New York, NY, USA
- Hunter College, New York, NY, USA
| | - Nandkishore Prakash
- Center for Neuroscience Research, Children's National Hospital, Washington, DC, USA
| | - Jared Burke
- Neuroscience Institute, New York University School of Medicine, New York, NY, USA
- Center for Neural Science, New York University, New York, NY, USA
| | - Govind Shekaran
- Neuroscience Institute, New York University School of Medicine, New York, NY, USA
- Center for Neural Science, New York University, New York, NY, USA
| | - Maria Grba
- Neuroscience Institute, New York University School of Medicine, New York, NY, USA
- Center for Neural Science, New York University, New York, NY, USA
| | - Joshua G Corbin
- Center for Neuroscience Research, Children's National Hospital, Washington, DC, USA
| | - Dayu Lin
- Neuroscience Institute, New York University School of Medicine, New York, NY, USA.
- Center for Neural Science, New York University, New York, NY, USA.
- Department of Psychiatry, New York University School of Medicine, New York, NY, USA.
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13
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Mei L, Osakada T, Lin D. Hypothalamic control of innate social behaviors. Science 2023; 382:399-404. [PMID: 37883550 PMCID: PMC11105421 DOI: 10.1126/science.adh8489] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 09/25/2023] [Indexed: 10/28/2023]
Abstract
Sexual, parental, and aggressive behaviors are central to the reproductive success of individuals and species survival and thus are supported by hardwired neural circuits. The reproductive behavior control column (RBCC), which comprises the medial preoptic nucleus (MPN), the ventrolateral part of the ventromedial hypothalamus (VMHvl), and the ventral premammillary nucleus (PMv), is essential for all social behaviors. The RBCC integrates diverse hormonal and metabolic cues and adjusts an animal's physical activity, hence the chance of social encounters. The RBCC further engages the mesolimbic dopamine system to maintain social interest and reinforces cues and actions that are time-locked with social behaviors. We propose that the RBCC and brainstem form a dual-control system for generating moment-to-moment social actions. This Review summarizes recent progress regarding the identities of RBCC cells and their pathways that drive different aspects of social behaviors.
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Affiliation(s)
- Long Mei
- Neuroscience Institute, New York University Langone Medical Center, New York, NY 10016, USA
| | - Takuya Osakada
- Neuroscience Institute, New York University Langone Medical Center, New York, NY 10016, USA
| | - Dayu Lin
- Neuroscience Institute, New York University Langone Medical Center, New York, NY 10016, USA
- Department of Psychiatry, New York University Langone Medical Center, New York, NY 10016, USA
- Department of Neuroscience and Physiology, New York University Langone Medical Center, New York, NY 10016, USA
- Center for Neural Science, New York University, New York, NY 10016, USA
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