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Boyle N, Li Y, Sun X, Xu P, Lai CH, Betts S, Guo D, Simha R, Zeng C, Du J, Lu H. MeCP2 Deficiency Alters the Response Selectivity of Prefrontal Cortical Neurons to Different Social Stimuli. eNeuro 2024; 11:ENEURO.0003-24.2024. [PMID: 39266326 PMCID: PMC11424234 DOI: 10.1523/eneuro.0003-24.2024] [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: 01/02/2024] [Revised: 08/21/2024] [Accepted: 09/09/2024] [Indexed: 09/14/2024] Open
Abstract
Rett syndrome (RTT), a severe neurodevelopmental disorder caused by mutations in the MeCP2 gene, is characterized by cognitive and social deficits. Previous studies have noted hypoactivity in the medial prefrontal cortex (mPFC) pyramidal neurons of MeCP2-deficient mice (RTT mice) in response to both social and nonsocial stimuli. To further understand the neural mechanisms behind the social deficits of RTT mice, we monitored excitatory pyramidal neurons in the prelimbic region of the mPFC during social interactions in mice. These neurons' activity was closely linked to social preference, especially in wild-type mice. However, RTT mice showed reduced social interest and corresponding hypoactivity in these neurons, indicating that impaired mPFC activity contributes to their social deficits. We identified six mPFC neural ensembles selectively tuned to various stimuli, with RTT mice recruiting fewer neurons to ensembles responsive to social interactions and consistently showing lower stimulus-ON ensemble transient rates. Despite these lower rates, RTT mice exhibited an increase in the percentage of social-ON neurons in later sessions, suggesting a compensatory mechanism for the decreased firing rate. This highlights the limited plasticity in the mPFC caused by MeCP2 deficiency and offers insights into the neural dynamics of social encoding. The presence of multifunctional neurons and those specifically responsive to social or object stimuli in the mPFC emphasizes its crucial role in complex behaviors and cognitive functions, with selective neuron engagement suggesting efficiency in neural activation that optimizes responses to environmental stimuli.
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Affiliation(s)
- Natalie Boyle
- Department of Pharmacology and Physiology, School of Medicine and Health Sciences, The George Washington University, Washington, DC 20037
| | - Yipeng Li
- Department of Pharmacology and Physiology, School of Medicine and Health Sciences, The George Washington University, Washington, DC 20037
| | - Xiaoqian Sun
- Department of Computer Science, School of Engineering and Applied Science, The George Washington University, Washington, DC 20037
| | - Pan Xu
- Department of Pharmacology and Physiology, School of Medicine and Health Sciences, The George Washington University, Washington, DC 20037
| | - Chien-Hsien Lai
- Department of Pharmacology and Physiology, School of Medicine and Health Sciences, The George Washington University, Washington, DC 20037
| | - Sarah Betts
- Department of Pharmacology and Physiology, School of Medicine and Health Sciences, The George Washington University, Washington, DC 20037
| | - Dian Guo
- Department of Pharmacology and Physiology, School of Medicine and Health Sciences, The George Washington University, Washington, DC 20037
| | - Rahul Simha
- Department of Computer Science, School of Engineering and Applied Science, The George Washington University, Washington, DC 20037
| | - Chen Zeng
- Department of Physics, Columbia College of Art and Sciences, The George Washington University, Washington, DC 20037
| | - Jianyang Du
- Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, Tennessee 38163
- Neuroscience Institute, University of Tennessee Health Science Center, Memphis, Tennessee 38163
| | - Hui Lu
- Department of Pharmacology and Physiology, School of Medicine and Health Sciences, The George Washington University, Washington, DC 20037
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Medeiros D, Polepalli L, Li W, Pozzo-Miller L. Altered activity of mPFC pyramidal neurons and parvalbumin-expressing interneurons during social interactions in a Mecp2 mouse model for Rett syndrome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.06.606882. [PMID: 39149275 PMCID: PMC11326302 DOI: 10.1101/2024.08.06.606882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
Social memory impairments in Mecp2 knockout (KO) mice result from altered neuronal activity in the monosynaptic projection from the ventral hippocampus (vHIP) to the medial prefrontal cortex (mPFC). The hippocampal network is hyperactive in this model for Rett syndrome, and such atypically heightened neuronal activity propagates to the mPFC through this monosynaptic projection, resulting in altered mPFC network activity and social memory deficits. However, the underlying mechanism of cellular dysfunction within this projection between vHIP pyramidal neurons (PYR) and mPFC PYRs and parvalbumin interneurons (PV-IN) resulting in social memory impairments in Mecp2 KO mice has yet to be elucidated. We confirmed social memory (but not sociability) deficits in Mecp2 KO mice using a new 4-chamber social memory arena, designed to minimize the impact of the tethering to optical fibers required for simultaneous in vivo fiber photometry of Ca2+-sensor signals during social interactions. mPFC PYRs of wildtype (WT) mice showed increases in Ca2+ signal amplitude during explorations of a novel toy mouse and interactions with both familiar and novel mice, while PYRs of Mecp2 KO mice showed smaller Ca2+ signals during interactions only with live mice. On the other hand, mPFC PV-INs of Mecp2 KO mice showed larger Ca2+ signals during interactions with a familiar cage-mate compared to those signals in PYRs, a difference absent in the WT mice. These observations suggest atypically heightened inhibition and impaired excitation in the mPFC network of Mecp2 KO mice during social interactions, potentially driving their deficit in social memory.
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Affiliation(s)
- Destynie Medeiros
- Department of Neurobiology, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Likhitha Polepalli
- Department of Neurobiology, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Wei Li
- Department of Neurobiology, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Lucas Pozzo-Miller
- Department of Neurobiology, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
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Strohm AO, Majewska AK. Physical exercise regulates microglia in health and disease. Front Neurosci 2024; 18:1420322. [PMID: 38911597 PMCID: PMC11192042 DOI: 10.3389/fnins.2024.1420322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Accepted: 05/20/2024] [Indexed: 06/25/2024] Open
Abstract
There is a well-established link between physical activity and brain health. As such, the effectiveness of physical exercise as a therapeutic strategy has been explored in a variety of neurological contexts. To determine the extent to which physical exercise could be most beneficial under different circumstances, studies are needed to uncover the underlying mechanisms behind the benefits of physical activity. Interest has grown in understanding how physical activity can regulate microglia, the resident immune cells of the central nervous system. Microglia are key mediators of neuroinflammatory processes and play a role in maintaining brain homeostasis in healthy and pathological settings. Here, we explore the evidence suggesting that physical activity has the potential to regulate microglia activity in various animal models. We emphasize key areas where future research could contribute to uncovering the therapeutic benefits of engaging in physical exercise.
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Affiliation(s)
- Alexandra O. Strohm
- Department of Environmental Medicine, University of Rochester Medical Center, Rochester, NY, United States
| | - Ania K. Majewska
- Department of Neuroscience, University of Rochester Medical Center, Rochester, NY, United States
- Del Monte Institute for Neuroscience, University of Rochester Medical Center, Rochester, NY, United States
- Center for Visual Science, University of Rochester Medical Center, Rochester, NY, United States
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Kuo JY, Denman AJ, Beacher NJ, Glanzberg JT, Zhang Y, Li Y, Lin DT. Using deep learning to study emotional behavior in rodent models. Front Behav Neurosci 2022; 16:1044492. [PMID: 36483523 PMCID: PMC9722968 DOI: 10.3389/fnbeh.2022.1044492] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 11/02/2022] [Indexed: 11/25/2023] Open
Abstract
Quantifying emotional aspects of animal behavior (e.g., anxiety, social interactions, reward, and stress responses) is a major focus of neuroscience research. Because manual scoring of emotion-related behaviors is time-consuming and subjective, classical methods rely on easily quantified measures such as lever pressing or time spent in different zones of an apparatus (e.g., open vs. closed arms of an elevated plus maze). Recent advancements have made it easier to extract pose information from videos, and multiple approaches for extracting nuanced information about behavioral states from pose estimation data have been proposed. These include supervised, unsupervised, and self-supervised approaches, employing a variety of different model types. Representations of behavioral states derived from these methods can be correlated with recordings of neural activity to increase the scope of connections that can be drawn between the brain and behavior. In this mini review, we will discuss how deep learning techniques can be used in behavioral experiments and how different model architectures and training paradigms influence the type of representation that can be obtained.
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Affiliation(s)
- Jessica Y. Kuo
- Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, United States
| | - Alexander J. Denman
- Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, United States
| | - Nicholas J. Beacher
- Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, United States
| | - Joseph T. Glanzberg
- Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, United States
| | - Yan Zhang
- Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, United States
| | - Yun Li
- Department of Zoology and Physiology, University of Wyoming, Laramie, WY, United States
| | - Da-Ting Lin
- Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, United States
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Yue Y, Ash RT, Boyle N, Kinter A, Li Y, Zeng C, Lu H. MeCP2 deficiency impairs motor cortical circuit flexibility associated with motor learning. Mol Brain 2022; 15:76. [PMID: 36064580 PMCID: PMC9446698 DOI: 10.1186/s13041-022-00965-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 08/29/2022] [Indexed: 11/19/2022] Open
Abstract
Loss of function mutations in the X-linked gene encoding methyl-CpG binding protein 2 (MECP2) cause Rett syndrome (RTT), a postnatal neurological disorder. The loss of motor function is an important clinical feature of RTT that manifests early during the course of the disease. RTT mouse models with mutations in the murine orthologous Mecp2 gene replicate many human phenotypes, including progressive motor impairments. However, relatively little is known about the changes in circuit function during the progression of motor deficit in this model. As the motor cortex is the key node in the motor system for the control of voluntary movement, we measured firing activity in populations of motor cortical neurons during locomotion on a motorized wheel-treadmill. Different populations of neurons intermingled in the motor cortex signal different aspects of the locomotor state of the animal. The proportion of running selective neurons whose activity positively correlates with locomotion speed gradually decreases with weekly training in wild-type mice, but not in Mecp2-null mice. The fraction of rest-selective neurons whose activity negatively correlates with locomotion speed does not change with training in wild-type mice, but is higher and increases with the progression of locomotion deficit in mutant mice. The synchronization of population activity that occurs in WT mice with training did not occur in Mecp2-null mice, a phenotype most clear during locomotion and observable across all functional cell types. Our results could represent circuit-level biomarkers for motor regression in Rett syndrome.
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Affiliation(s)
- Yuanlei Yue
- grid.253615.60000 0004 1936 9510Department of Pharmacology and Physiology, School of Medicine and Health Sciences, The George Washington University, Washington, DC 20037 USA
| | - Ryan T. Ash
- grid.168010.e0000000419368956Department of Psychiatry, Stanford University, Palo Alto, CA 94305 USA
| | - Natalie Boyle
- grid.253615.60000 0004 1936 9510Department of Pharmacology and Physiology, School of Medicine and Health Sciences, The George Washington University, Washington, DC 20037 USA
| | - Anna Kinter
- grid.253615.60000 0004 1936 9510Department of Pharmacology and Physiology, School of Medicine and Health Sciences, The George Washington University, Washington, DC 20037 USA
| | - Yipeng Li
- grid.253615.60000 0004 1936 9510Department of Pharmacology and Physiology, School of Medicine and Health Sciences, The George Washington University, Washington, DC 20037 USA
| | - Chen Zeng
- grid.253615.60000 0004 1936 9510Department of Physics, Columbian College of Arts and Sciences, The George Washington, University, Washington, DC 20037 USA
| | - Hui Lu
- Department of Pharmacology and Physiology, School of Medicine and Health Sciences, The George Washington University, Washington, DC, 20037, USA.
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Xu P, Yue Y, Su J, Sun X, Du H, Liu Z, Simha R, Zhou J, Zeng C, Lu H. Pattern decorrelation in the mouse medial prefrontal cortex enables social preference and requires MeCP2. Nat Commun 2022; 13:3899. [PMID: 35794118 PMCID: PMC9259602 DOI: 10.1038/s41467-022-31578-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Accepted: 06/21/2022] [Indexed: 11/08/2022] Open
Abstract
Sociability is crucial for survival, whereas social avoidance is a feature of disorders such as Rett syndrome, which is caused by loss-of-function mutations in MECP2. To understand how a preference for social interactions is encoded, we used in vivo calcium imaging to compare medial prefrontal cortex (mPFC) activity in female wild-type and Mecp2-heterozygous mice during three-chamber tests. We found that mPFC pyramidal neurons in Mecp2-deficient mice are hypo-responsive to both social and nonsocial stimuli. Hypothesizing that this limited dynamic range restricts the circuit's ability to disambiguate coactivity patterns for different stimuli, we suppressed the mPFC in wild-type mice and found that this eliminated both pattern decorrelation and social preference. Conversely, stimulating the mPFC in MeCP2-deficient mice restored social preference, but only if it was sufficient to restore pattern decorrelation. A loss of social preference could thus indicate impaired pattern decorrelation rather than true social avoidance.
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Affiliation(s)
- Pan Xu
- The GW Institute for Neuroscience, The George Washington University, Washington, DC, 20037, USA
- Department of Pharmacology and Physiology, School of Medicine and Health Sciences, The George Washington University, Washington, DC, 20037, USA
- Institute of Basic Science, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021, China
- Medical Science and Technology Innovation Center, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong, 250000, China
| | - Yuanlei Yue
- The GW Institute for Neuroscience, The George Washington University, Washington, DC, 20037, USA
- Department of Pharmacology and Physiology, School of Medicine and Health Sciences, The George Washington University, Washington, DC, 20037, USA
| | - Juntao Su
- The GW Institute for Neuroscience, The George Washington University, Washington, DC, 20037, USA
| | - Xiaoqian Sun
- Department of Computer Science, School of Engineering and Applied Science, The George Washington University, Washington, DC, 20037, USA
| | - Hongfei Du
- Department of Statistics, Columbian College of Art and Sciences, The George Washington University, Washington, DC, 20037, USA
| | - Zhichao Liu
- Department of Physics, Columbian College of Art and Sciences, The George Washington University, Washington, DC, 20037, USA
- School of Biological Information, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China
| | - Rahul Simha
- Department of Computer Science, School of Engineering and Applied Science, The George Washington University, Washington, DC, 20037, USA
| | - Jianhui Zhou
- Department of Statistics, School of Arts and Sciences, University of Virginia, Charlottesville, VA, 22904, USA
| | - Chen Zeng
- Department of Statistics, Columbian College of Art and Sciences, The George Washington University, Washington, DC, 20037, USA
| | - Hui Lu
- The GW Institute for Neuroscience, The George Washington University, Washington, DC, 20037, USA.
- Department of Pharmacology and Physiology, School of Medicine and Health Sciences, The George Washington University, Washington, DC, 20037, USA.
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